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Archive for the ‘Diabetes’ Category

Substance in Tears Could Be Used for Diabetes Monitoring – Medscape

Tuesday, October 20th, 2020

Dr Masakazu Aihara

Measuring glycated albumin (glycoalbumin, GA) in tears could be a future way for those with diabetes to monitor their blood sugar levels noninvasively.

In a 100-patient trial, levels of GA in tears were found to be strongly correlated (r = .722;P< .001) with those in the blood.

"GA levels in blood are widely measured in clinical practice in Japan," said study investigator Masakazu Aihara, MD, PhD, in an interview.

"It's a biomarker that reflects the 2-week average blood glucose level like fructosamine," explained the researcher from the department of diabetes and metabolic diseases in the Graduate School of Medicine at the University of Tokyo.

This could make it a better biomarker for detecting earlier changes in blood glucose than glycated hemoglobin (HbA1c), which reflects changes in blood glucose over the preceding 2-3 months.

Prior studies had shown that glucose levels can be measured in tear samples and that tear glucose levels correlated with blood glucose levels, Aihara and fellow researchers observed in a poster presentation at the virtual annual meeting of the European Association for the Study of Diabetes.

"While looking for noninvasive diabetes-related markers, we found that tears contained albumin. Based on this fact, we thought that GA could be measured in tears," Aihara explained.

Usingtears to test for biomarkersis not a new idea tears not only protect the eye, they contain a variety of large proteins, and their composition can change with disease. Indeed, researchers have been looking at their usefulness in helping find biomarkers forParkinson's diseaseanddiabetic peripheral neuropathy.

Duringtheir study, Aihara and associates collected tear and blood samples at the same time. Tear samples were assessed using liquid chromatography (LC) and mass spectrometry (MS). An enzymic method was used to measure GA levels in blood. Several diagnosis assay kits for GA are sold in Japan, Aihara said, and at leastone of thesehas U.S. Food and Drug Administration approval.

Multiple regression analysis revealed that the correlation between GA levels in tears and in blood was maintained even after adjustment for age, gender, nephropathy stage, and obesity (P< .001). The results obtained from the tests were thought unlikely to be affected by any changes in the concentration or dilution of tear samples.

"Since GA levels in blood are clinically used in all types of diabetes, GA levels in tears is also expected to be useful in all types of diabetes," Aihara said, noting that the effects of receiving treatment on GA levels in tears is something that he would like to look at.

The team would also like to optimize how tear samples are collected and reduce the volume of tears that are required for analysis. At the moment tears are collected via a dropper and about 100 mcL of tear fluid is required for measurement.

"At present, it is difficult to measure for dry eye patients because sufficient tears cannot be collected, but if the required amount of tears decreases in the future, it may be indicated for dry eye patients," Aihara noted.

Discussing further research plans, he added: "We would like to examine the conditions of LC-MS/MS so that the correlation coefficient with GA in blood can be improved.

"Since LC-MS/MS is a large equipment in the laboratory, I would like to develop a device that can measure at the clinic or at home in the future."

The study was funded by a grant from the Japan Agency for Medical Research and Development. Aihara had no conflicts of interest.

SOURCE:Aihara M et al. EASD 2020,poster presentation 624.

This article originally appeared on MDedge.com, part of the Medscape Professional Network.

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SGLT2 Inhibitors Shown to Reduce Risk of Heart Attacks and Strokes in People with Type 2 Diabetes – EndocrineWeb

Tuesday, October 20th, 2020

With Amy Hess-Fischl RD

It's no secret that people with type 2 diabetes are at an increased risk for major health complications. But one class of medicine might be able to change that, researchers say. According to a recent studypublished in the British Medical Journal (BMJ), a type of medication called SGLT2 inhibitors reduced the risk of heart failure and stroke among patients with type 2 diabetes, suggesting they have cardio-protective benefits.

Otherwise known as sodium glucose co-transporter 2 inhibitors,SGLT2 inhibitorsare a class of medication, delivered in pill form, that can help lower blood glucose levels in diabetic patients.

SGLT2 inhibitors are a relatively new class of medication that can have really impressive results, says Amy Hess-Fischl RD, a certified diabetes educator at the University of Chicago. While most diabetes medications either increase insulin or insulin sensitivity, SGLT2 inhibitors cause the kidneys to excrete glucose into the urine, preventing it from being reabsorbed back into the bloodstream.

By decreasing blood sugar levels, SGLT2 inhibitors can help improve your A1C levels as well, and potentially even aid in medically advised weight loss. According torecent research from Johns Hopkins University, SGLT2 inhibitors typically improve A1C levels anywhere from 0.5% to 1% when taken daily over the course of six months.

Because SGLT2s help decrease sugar in the blood, this also helps reduce some of the complications and long-term damage that can come from having high blood sugar.

Glucose is very attracted to hemoglobin, which is in our red blood cells, says Fischl. The more sugar we have in our blood, the more it can attach to the hemoglobin, and the harder our red blood cells get. Those hard red blood cells, pounding up against our blood vessels for years on end, can cause a lot of damage.

One recent study published in the 2019 issue of theNew England Medical Journal(NEJM) found that the risk of renal failure was 30 percent lower in patients with type 2 diabetes who took the SGLT2 inhibitor Canagliflozin, compared with patients in the control group who took a placebo.

The latest research, published in the September 2020 issue of theBritish Medical Journal(BMJ), reinforces what earlier studies have shown: SGLT2s can protect against heart attack, heart failure, and stroke among patients with type 2 diabetes.

The study authors used five years of healthcare data from type 2 diabetes patients across Canada and the United Kingdom. They surveilled over 200,000 patients who took SGLT2 inhibitors and compared them to the same number of patients who took another class of medication known as DPP-4 inhibitors. (DPP-4s help reduce blood sugar levels in diabetic patients by increasing insulin.) The researchers then recorded any major cardiac events such as heart attack, stroke, and heart failure for an average of 11 months.

The results showed that SGLT2 inhibitors were associated with a lower risk of cardiac events in type 2 diabetics when compared to DPP-4 inhibitors. For example, the rate of heart failure was 3.1 events per 1,000 people among patients who took SGLT2s and 7.7 events per 1,000 people among patients who took DPP-4s. Heart attacks, strokes, and overall mortality rates were also lower in patients who took SGLT2s. These results were consistent across age, sex, past insulin use, and history of cardiovascular disease, the study found.

While the new study produced notable results, it also has some limitations. Observational studies are just that observational, according to Hess-Fischl. They're nice because they give researchers a place to start, but we really need comparative data next.

Additionally, while it may be true that SGLT2s have some cardioprotective benefit, people with type 2 diabetes should be aware that the medication is not without risk.

What we've been finding is that SGLT2s tend to increase the risk of a condition called Euglycemic Diabetic Ketoacidosis, which is a life-threatening condition caused by a buildup of ketones in the bloodstream," Hess-Fischl says. SGLT2s can also cause urinary tract infections particularly in females due to increased sugar being excreted in urine. They are also contraindicated for patients in kidney failure.

All in all, Fischl says, while SGLT2s can be a godsend for some patients with type 2 diabetes, they're far from a miracle drug. More research, such as double-blind placebo studies, is still needed to determine whether or not they can truly guard against cardiac events.

Last updated on 10/20/2020

All About Type 2 Diabetes

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Kids with Type 1 Diabetes Increasingly Have Other Autoimmune Diseases – Celiac Disease and Gluten-Free Diet Support – Celiac.com

Tuesday, October 20th, 2020

Celiac.com 10/20/2020 - Doctors diagnosing children for type 1 diabetes are increasingly finding other autoimmune conditions that can complicate the outlook for these patients. A team of researchers recently set out to study rates of comorbid autoimmune diseases, including celiac disease, and type 1 diabetes mellitus (T1D) in children.

Rates of type 1 diabetes mellitus (T1D) in children are on the rise, but it's unclear what relationship, if any, this might have with other coexistent autoimmune conditions, since diabetes onset is not well understood.

The team studied 264 boys and 229 girls between 0 and 18 years old with newly diagnosed with T1D in one of the Polish centers from 20102018. They determined diagnoses for related autoimmune illnesses from initial data recorded when patients first received diagnosis for T1D.

The team found that the standardized incidence rate of T1D in children rose 170% over the 9-year study period, while the incidence rate ratio rose 4% per year.

As rates of T1D have risen rapidly in all children of all ages in recent years, so, too have rates of the autoimmune diseases that frequently accompany these conditions. Having an additional autoimmunity disorder is a serious burden for patients with new-onset T1D.

Stay tuned for more information on the challenges faced by children with more than one auto-immune disease.

Read more in Front Endocrinol (Lausanne). 2020; 11: 476.

Reference:Gowiska-Olszewska B, Szabowski M, Panas P, et al. Increasing co-occurance of additional autoimmune disorders at diabetes type 1 onset among children and adolescents diagnosed in years 2010-2018single-center study. Front Endocrinol. Published online August 6, 2020. doi:10.3389/fendo.2020.00476

The research team included Barbara Gowiska-Olszewska,Maciej Szabowski,Patrycja Panas,Karolina oadek,Milena Jamiokowska-Sztabkowska,Anna Justyna Milewska,Anna Kadubiska,Agnieszka Polkowska,Wodzimierz uczyski,and Artur Bossowski. They are variously affiliated with the Department of Pediatrics, Endocrinology, Diabetology With Cardiology Division, Medical University of Bialystok, Biaystok, Poland; the Department of Pediatrics, Rheumatology, Immunology and Metabolic Bone Diseases, Medical University of Bialystok, Biaystok, Poland; the Department of Statistics and Medical Informatics, Medical University of Bialystok, Biaystok, Poland; and the Department of Medical Simulations, Medical University of Bialystok, Biaystok, Poland.

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Need help managing diabetes? A local nutrition and wellness educator is offering guidance – WHBF – OurQuadCities.com

Tuesday, October 20th, 2020

Know someone with diabetes? Have it yourself? If so, youre not alone.

One in 11 American has diabetes, and one in three has prediabetes.

Managing this disease will help prevent damage to your heart, eyes and nerves over time, says Kristin Bogdonas, a nutrition and wellness educator for University of Illinois Extension.

Bogdonas is offering two Tools to Manage Diabetes workshops in the month of November that will introduce participants to some tools that can help manage carbohydrate intake and plan meals effectively.

One program is online, and the other is in person.

The Tools to Manage Diabetes online program will be 4 to 5 p.m. Tuesday, Nov. 10, via Zoom.

This program is free and offered in conjunction with the Rock Island Public Library.

Once registered, participants will pick up their class materials from the main library, located at 401 19th St., Rock Island.

Class size is limited to 20.

The Tools to Manage Diabetes in-person program will be 1 to 2 p.m. Wednesday, Nov. 11, at the Rock Island County Extension, located at 321 2nd Ave. West, Milan.

There is a $5 cost to attend, and class size is limited to eight persons.

Masks will be required, and social distancing will be practiced.

Space is limited and available on a first-come, first-served basis.

Register through the University of Illinois Extension events page by Monday, Nov. 9.

Participants will receive a diabetes portion plate, carbohydrate counting pocket guide and presentation handouts.

These class materials are funded in part by a City of Rock Island Gaming Grant.

More information about University of Illinois Extension is here.

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National Survey Reveals People Living with Diabetes Feel They Are Doing Everything They Can to Manage Their Condition, Yet Believe More Can Be Done -…

Tuesday, October 20th, 2020

Respondents recognize the importance of tracking their insulin data over time but admit to being too busy and/or forgetting to log their insulin use about eight times within the past month.

Respondents believe technology can help them more effectively manage their condition.

CHICAGO, Oct. 19, 2020 /PRNewswire/ -- The Association of Diabetes Care & Education Specialists (ADCES) today announced the results of a national survey that uncovered people living with diabetes are challenged by tracking information related to their condition over time. The survey found that while 65 percent of respondents report they are doing everything they possibly can to manage their diabetes, just as many (67 percent) feel guilty about not doing a better job. The national survey was supported by Sanofi US.

More than 30 million people have diabetes in the U.S., and for those who take insulin and have been trained on the self-adjustment of doses glucose (blood sugar) readings offer the opportunity to address out-of-range glucose levels. The survey showed that people living with diabetes, who track their insulin use, recognize the importance of looking back at their data over time, but nearly two-thirds agree it would be more helpful if there were better tools for doing it. When citing the most common challenges they have had in tracking their insulin use over a month's time, 62 percent of respondents reported being too busy to log and/or forgetting to log their insulin use.

"The management of diabetes is complex and so deeply personal that people living with diabetes often need to make drastic changes to their lifestyle, relearning their body's needs at the most basic level," said Lorena Drago, MS, RDN, CDN, CDCES and multi-cultural nutrition education expert. "Since the changes people make can impact every area of their lives, I understand why respondents may feel that they are doing all that they can to manage their diabetes, while at the same time still believing they are still not doing enough. The complex nature of managing diabetes presents an opportunity for healthcare professionals to personalize diabetes management. One way to personalize diabetes management is to collect useful diabetes information automatically in one place."

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Challenges with Tracking Data Over Time & Benefit of Added TechnologyWhile there are several methods available to manage diabetes information, including tracking glucose levels and insulin use, there is still room for improvement. For example:

Among people who track their blood glucose levels with a blood glucose monitor or continuous glucose monitor, 47 percent feel their current method of tracking glucose levels is simple and easy to do, while also wishing it was even more simple and easy to do.

Similarly, among people who currently track their insulin use, 45 percent agree that looking back at their insulin use and how it impacts their glucose levels is easy to do, but they still desire it to be easier.

When considering what could make tracking their diabetes information easier, the survey revealed people living with diabetes wish all their data was put together automatically so they could see everything they need in one place (82 percent). In particular, the vast majority of respondents (more than 80 percent) believe a device which connects to an insulin pen, automatically tracks/records insulin use and wirelessly sends the information to an app on a smartphone or tablet, would be helpful in more effectively managing their diabetes.

"Given the personal nature of diabetes, and the constant management needed, these data truly underscore the challenges people face in tracking and managing diabetes information. These data also show the potential benefits of integrating technology into the care routines of people living with diabetes," said Kellie Antinori-Lent, MSN, RN, ACNS-BC, BC-ADM, CDCES, FADCES and president of ADCES. "My goal as a diabetes care and education specialist is to help overcome the challenges of managing diabetes and it is my belief that tools which automate this process may not only improve the individual's understanding of their condition, but can inform care providers in efficient patient management."

Measuring glucose accurately and logging insulin data is the first step in the wellbeing and care of a person living with diabetes. The potential benefits of a device that automatically brings diabetes data together for people living with diabetes range from having better conversations with their provider and health care team to improving the accuracy of managing or tracking insulin use. Specifically, respondents of the survey living with diabetes would find such a device helpful in:

Giving them a more personalized understanding of their diabetes (79 percent)

Making managing or tracking insulin use less time consuming (78 percent)

Making them feel more empowered when it comes to managing diabetes (75 percent)

"These findings highlight the ongoing need to provide support to people living with diabetes," said Rogelio Braceras, MD, North America Medical Head of General Medicines, Sanofi. "We are proud to be collaborating with ADCES to better understand this population's unmet needs and bring them to the forefront to inform and ultimately help advance personalized care for people living with diabetes."

The national survey was conducted by a market research firm in June and July of 2020 and included more than 700 American adults living with Type 1 or Type 2 diabetes who take insulin. All respondents were taking insulin that was administered with a vial/syringe or pen regularly for at least six months. Respondents were not excluded if they delivered their insulin via an insulin pump or if they also used inhaled insulin.

About the Association of Diabetes Care & Education Specialists: ADCES is an interdisciplinary professional membership organization dedicated to improving prediabetes, diabetes and cardiometabolic care through innovative education, management and support. With more than 12,000 professional members including nurses, dietitians, pharmacists and others, ADCES has a vast network of practitioners working to optimize care and reduce complications. ADCES supports an integrated care model that lowers the cost of care, improves experiences and helps its members lead so better outcomes follow. Learn more at DiabetesEducator.org, or visit us on Facebook or LinkedIn (Association of Diabetes Care & Education Specialists), Twitter (@ADCESdiabetes) and Instagram (@ADCESdiabetes).

About Sanofi:Sanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions.

With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.

Sanofi, Empowering Life

Contact:Matt Eaton, 312-601-4866, meaton@adces.org

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SOURCE Association of Diabetes Care & Education Specialists

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Coos Family Health to offer specialized support to those living with Diabetes – Berlindailysun

Tuesday, October 20th, 2020

BERLIN Coos County Family Health Services has begun offering specialized support services to people living with diabetes.

Heather Beaudry, RN, will lead this new program as part of her work as a certified diabetes care and support specialist. The program is newly accredited by the Association of Diabetes Care & Education Specialists, and is available to all Coos County Family Health Servicespatients.

Our mission is to help people living with diabetes gain control of their illness, and live full and active lives, said Beaudry. Diabetes is a chronic illness that poses many challenges. We can help people with the skills and knowledge they need to improve their health.

The program will be offered at the organizations Pleasant Street Clinic on Monday through Thursday, from 8 a.m.-5 p.m. The service is covered by most insurances, and can be provided on a discounted basis for those in need. Diabetes education is a covered Medicare benefit when delivered through an accredited program.

Diabetes is one of the most common and significant illnesses affecting older adults in our community, said Patty Couture, Coos County Family Health Serviceschief operating officer.

Diabetes education services utilize a collaborative process through which people with diabetes work with a Certified Diabetes Care and Education Specialist to receive individualized care to help them reach their health goals.

Programs like the one we have established can help people with diabetes improve their health and to live long and productive lives, said Beaudry.

For more information about the program, or to schedule a time to meet with Heather Beaudry, contact any of the Family Health Clinics or call (603) 752-2040.

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Growth Of Diabetes Treatment Market In Global Industry: Overview, Size And Share 2020-2027 – The Think Curiouser

Tuesday, October 20th, 2020

IndustryGrowthInsights (IGI), a prominent market research firm in its own industry, has published a detailed report on Global Diabetes Treatment Market. This market research report provides comprehensive and in-depth analysis on the market which can possibly help an enterprise to identify lucrative opportunities and assist them with fabricating creative business strategies. The market report provides information about the current market scenario regarding the global supply and demand, key market trends and opportunities in the market, and challenges and threats faced by the industry players.

The Diabetes Treatment market report talks about the competitive scenario among the industry players and imparts aspiring and emerging industry players with the future market insights in a detailed manner. This market report includes crucial data and figures which are structured out in a concise yet understandable manner. The research report covers the updates on the government regulations and policies which illustrates key opportunities and challenges of the market. IndustryGrowthInsights (IGI) has been monitoring the market since few years and collaborated with eminent players of the industry to give better insights on the market. It has conducted vigorous research and implied robust methodology to provide accurate predictions about the market.

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Impacts of Advancements and COVID-19 on the market.

Amidst the COVID-19, few segments of the market have witnessed a disruption due to the gap in supply and demand which has impacted the growth of the Diabetes Treatment market. Along with this, the latest advancements have changed the market dynamics of the market. This research report covers the wide-range analysis of the COVID-19 impact to the industry and gives out insights on the change in the market scenario due to the advancements.

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Market Segmentation

Some of the major companies that are covered in the report.

Novo NordiskBayerTeva Pharmaceuticals Pvt Ltd.MerckCompany Inc.Medtronic Inc.JohnsonJohnsonHome Diagnostics Inc.Amylin Pharmaceuticals Inc.Abbott Laboratories

Note: Additional companies

Based on the type, the market is segmented into

InsulinOral Hypoglycaemic DrugsNon-Insulin Injectable Drugs

Based on the application, the market is segregated into

HospitalPersonal UseClinic

Based on the geographical location, the market is segregated into

Asia Pacific: China, Japan, India, and Rest of Asia PacificEurope: Germany, the UK, France, and Rest of EuropeNorth America: The US, Mexico, and CanadaLatin America: Brazil and Rest of Latin AmericaMiddle East & Africa: GCC Countries and Rest of Middle East & Africa

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This report includes latest product news, advancements, and updates from the prominent player of the industry that has leveraged their position in the market. It also provides business strategies implemented by the key players and yardstick to arrive on informed business decisions. Moreover, it gives insights on the consumer behavior patterns that can help the enterprise to curate the business strategies accordingly.

IndustryGrowthInsights (IGI) bestows the clients with the specialized customized options related to the regional analysis, company analysis, and product analysis, among others.

Complete Table Content of the Market

Executive Summary

Assumptions and Acronyms Used

Research Methodology

Diabetes Treatment Market Overview

Diabetes Treatment Supply Chain Analysis

Diabetes Treatment Pricing Analysis

Global Diabetes Treatment Market Analysis and Forecast by Type

Global Diabetes Treatment Market Analysis and Forecast by Application

Global Diabetes Treatment Market Analysis and Forecast by Sales Channel

Global Diabetes Treatment Market Analysis and Forecast by Region

North America Diabetes Treatment Market Analysis and Forecast

Latin America Diabetes Treatment Market Analysis and Forecast

Europe Diabetes Treatment Market Analysis and Forecast

Asia Pacific Diabetes Treatment Market Analysis and Forecast

Middle East & Africa Diabetes Treatment Market Analysis and Forecast

Competition Landscape

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Diabetes may not increase your risk of catching the coronavirus – The Herald-News

Tuesday, October 20th, 2020

As a public service, Shaw Media will provide open access to information related to the COVID-19 (Coronavirus) emergency. Sign up for the newsletter here

Dr. Tiffany E. Groen likened learning about the coronavirus as running across a bridge while trying to build it.

Its amazing how differently the virus affects people, Groen said. It might give one person respiratory issues. Another person might have no respiratory issues but have blood clots.

But one thing appears clear. Having diabetes is a risk factor for severe COVID-19.

People with diabetes arent necessarily more at catching the virus, according to the American Diabetes Association.

But they do have increased risk for severe complications, especially if they have other conditions, too, such as heart disease, the ADA said.

There is not enough evidence that having diabetes will increase the risk of contracting the virus, Dr. Babak Pazooki, an endocrinologist with AMITA Health Saint Joseph Medical Center in Joliet, said. But there is enough evidence to support the notion that if you have diabetes, your outcome may be worse.

In fact, diabetics are at risk of complications when they contract any virus, the ADA said.

Diabetics are also at greater risk of acquiring and having worse outcomes certain infections, such as urinary tract and respiratory infections, Pazooki said

Groen said diabetes, especially diabetes that isnt well-controlled, can cause inflammation. This may lead to complications in times of illness.

When a diabetic gets sick with any illness, the tendency is for the blood sugar to be elevated, Groen said. The immune system doesnt work as well, and it cant fight it [the illness] very well.

Jan Smith of Joliet saw that firsthand with her husband James V. Smith, who was diagnosed with type 2 diabetes about five years ago. He kept it under good control until he caught the coronavirus, she said.

Jan feels her husbands lack of appetite during his illness might have affected his blood sugar control. She said James was treated in an emergency department on Aug. 31, but his condition continued to worsen.

He went into the hospital on Sept. 8, Jan said. and he died on Sept. 23.

Pazooki said diabetes becomes difficult to manage once the patient becomes severely ill.

In July, the Centers for Disease Control and Prevention published a study of 10,000 people who died from the virus, which further showed the connection between diabetes and COVID-19.

The study found that 49.6% of those aged 65 and up had diabetes as did 35% of those younger than age 65. When compared to people who were white more Hispanic and non-white people were older than 65, the CDC study also said.

But generally speaking, diabetes is more common in people of color and the complications and outcomes are worse, for whatever the reasons might be, Pazooki said.

The CDC study also said more studies are needed to clarify some of the associations, such as those among age, race/ethnicity, SARS-CoV-2 infection, disease severity, underlying medical conditions (especially diabetes) poverty and access to health care and the ability to comply with mitigation recommendations while maintaining essential work responsibilities.

Groen said the longstanding health and social inequities in the U.S. increases the risk in some minority groups, who often have additional chronic conditions, too, such as obesity and high blood pressure.

On top of that, not all types of diabetes are the same and its unclear if the risks are the same.

Certainly high blood sugar plays a role in all forms of diabetes, she said.

A study published April 15 in the Journal of Medical Virology suggests that blood sugars that remain high over time might contribute to the severity of COVID-19 in some people with diabetes.

Pregnant women are also more prone to blood clots, Groen said. In some cases, the SARS-CoV-2 virus also causes blood clots, she added.

What might make Type 2 diabetes particularly troublesome in terms of covid is that it often involves multiple other factors: metabolic syndrome, obesity and even genetics, Pazooki said.

So it is possible that those are other conditions that leads to the type 2 diabetes being more of a bigger risk factor for having adverse outcomes, Pazooki said.

But even treating the coronavirus in a diabetic patient is tricky, Groen said.

If they need steroids, that can elevate the blood sugar, she said.

A study published July 17 in The Lancet said these blood sugar elevations can become quite high, along with an increase insulin resistance, when steroids are administered to a diabetic patient.

Pazooki said diabetics who dont normally take insulin might have their oral diabetes medication temporarily stopped and then switched to insulin if they are being treated for COVID-19 in the hospital.

Oral medication might be harmful if the patient has abnormal kidney function, needs to fast for tests, or has an irregular meal schedule, Pazooki said.

But often this change in treating the diabetes is temporary.

The majority of patients go back home on the medications they came to the hospital with, Pazooki said.

So whats a diabetic to do?

Pazooki suggests diabetics work with their health care providers to keep their condition controlled. Eat a healthy diet, get regular exercise, he said.

Then, hypothetically, outcomes from COVID-19 might be better, he said.

We dont have strong evidence in terms of COVID-19, Pazooki said. But we do have strong evidence in terms of all other types of infectionand COVID-19 is just another infection.

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Combating Diabetes-Induced Blindness – Texas A&M Today – Texas A&M University Today

Tuesday, October 20th, 2020

Six Texas A&M engineering and medical students came together to develop tools to more effectively diagnose diabetic retinopathy.

Texas A&M Engineering

About 10% of the U.S. population has diabetes, and about a third of that number, around 11 million people, will suffer from diabetic retinopathy diabetes-induced irreversible vision loss, at some point in their lifetime. People in both rural and underserved communities may suffer more because they dont have access to specialists, and its likely the disease is underdiagnosed.

Ai-Ris (pronounced A-Iris), a team comprised of six engineering and medical students from Texas A&M University, are working to address these diagnosis barriers. Specifically, they are designing a tool to better reach individuals in rural or underserved communities.

Were developing this system that leverages machine learning and also uses low-cost hardware in a user-friendly form, something like a headset that can be used in a non-clinical setting and doesnt require the presence of an optometrist or ophthalmologist, said T.J. Falohun, team member and biomedical engineering doctoral student.

Uthej Vattipalli, civil engineering graduate student, has personally witnessed the impact of diabetic retinopathy. His grandfather began to lose his eyesight after retirement, but could not afford to get a diagnosis. Vattipalli said the teams work could transform the health care market.

We are going to need an army to go into what we want to do if we want that impact, Vattipalli said. Not everybody has all the skill in the world. Theres definitely been complementary skill sets required to get tasks accomplished. One of the good things of being on an interdisciplinary team is the variety of skill sets that help you keep moving forward.

The project started as a Sling Health initiative.Sling Health National Networkis a student-run biotechnology incubator that provides resources, training and mentorship to teams of students in engineering, medicine and business tackling clinical problems by developing innovative solutions.

The project began to gain members and motivation and spread outside of Sling Health into its entrepreneurship effort. The team continued its work with the help of the Engineering Incubator at Texas A&M, where the students worked with Rodney Boehm, director of Engineering Entrepreneurship, to expand their access to resources.

Now a limited liability company, Ai-Ris placed second in the 2020 Sling Health Demo Day and participated in the Innovation Corps Site Fellows program at Texas A&M. The team also recently won a VentureWell E-team Grant. Through VentureWell, the team will receive funding, connections and training to further their entrepreneurial efforts.

Amir Tofighi Zavareh 19, an electrical engineering doctoral graduate, said beyond making an impact, he joined the team because he is intrigued by the technical challenges involved. He said collecting the retinal images at a low cost is a challenge that is not being addressed in the market.

Right now in the clinics, they use this benchtop device that costs tens of thousands of dollars. Its a very tricky thing to do, Tofighi Zavareh said. We want to do that with low-cost devices, so thats going to make it challenging to do that at the same quality levels but at lower costs so it can be available to rural areas.

Harsha Mohan, a former student and current graduate student studying robotics at Johns Hopkins University, said working on a multidisciplinary team has taught members soft skills such as communicating effectively and elevating each members strengths.

We have people from all over the world; we have people from different backgrounds, and to work toward health care equity at this point of my life, Im not sure theres anything better than this, Mohan said.

Saurabh Biswas, principal investigator of VentureWell Grant and faculty advisor of Sling Health, said Ai-Ris is a great example of a highly motivated team with complementary skill sets, which Biswas said is critical to solve problems in health care.

I truly hope otherAggie innovators will follow their example and take advantage of great programs like VentureWell Grants, Sling Health andNSF I-site and I-Corpto bring their ideas from concept to prototype with extensive customerdiscovery to validate product-market fit, said Biswas, who also serves as executive director of TEES Commercialization and Entrepreneurship and as a professor of practicein the Department of Biomedical Engineering.

While the team continues to delve into the world of entrepreneurship and health care integration, the students are already seeing how their work can play a part in treating many ocular diseases in the future. Marcus Deayala, a biotechnology graduate student, said he is excited to play a part in breaking down barriers to AI diagnostics, which he says will shape the landscape of health care in the future.

I think we all understand that in the richest country (in the world), this many people going blind by a completely avoidable disease is ridiculous, Deayala said. If the level of health care is going to increase, the cost has to come down. We have to become more efficient and devices like these have to be instituted in one way or another.

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Diabetes Diet: This Stuffed Ragi Roti Could Be The Healthiest Way To Manage Blood Sugar Levels – NDTV Food

Saturday, October 10th, 2020

Ragi (nachni) is often suggested to diabetics since it helps in maintaining blood sugar levels.

Highlights

Diabetes is perhaps one of the biggest challenges faced by many people around the world. A lifestyle disease, diabetes is distinguished by elevated blood sugar levels. It is an irreversible condition where one can only manage the symptoms and your diet plays a major role in managing it. As per many health experts and nutritionists, small meals at regular intervals full of fibre and antioxidants (and devoid of sugar) is ideal for someone suffering from diabetes.

(Also Read:17 Easy Diabetes-Friendly Snack Ideas To Manage Blood Sugar Levels)

Choosing what to eat and what to avoid can be quite a task. But our desi meals can easily be moulded into healthy, diabetic-friendly ones by tweaking certain ingredients and veggies here and there. Roti (or bread) is an essential part of an Indian meal and you'll be surprised to know that one can make a wholesome meal out of just roti! While most of us use whole wheat flour to make rotis, one can simple add or replace it with ragi flour or finger millet. Ragi (nachni) is often suggested to diabetics since it helps in maintaining blood sugar levels. In addition to that, ragi is rich in dietary fibre which keeps the cravings at bay and maintains the digestive pace, subsequently, keeping blood sugar in control.

There could be many ways to include ragi in your diet, and this stuffed ragi roti seems to be one of the perfect ways for a light yet wholesome meal for those managing diabetes. Not only is it absolutely healthy and fulfilling but is also delicious and flavourful. The vegetables stuffed in ragi roti are fibre-rich and brimming with antioxidants. Bitter-gourd, especially, contains active substances that lend anti-diabetic properties like charantin, which is known for its blood glucose-lowering effect and an insulin-like compound known as polypeptide-p. Here's how you can make stuffed ragi roti.

(Also Read:Diabetes And Covid-19: Expert Tips And Full-Day Diet Plan For Diabetics)

Ragi flour is said to be a better alternative to regular whole wheat flour.

Ingredients-

- Dough:

- Ragi flour- 1/2 cup

- Whole Wheat Flour- 1/2 cup

- Water- as needed

- Salt- As per taste

For Stuffing-

- Bitter gourd (chopped)- 1 tbsp

- Fenugreek leaves (chopped)- 2 tbsp

- Spinach (chopped)- 2 tbsp

- Cauliflower (grated)- 2 tbsp

- Green chillies (finely chopped)- 1 tsp

- Ginger (chopped)- 1/2 tsp

- Salt- As per taste

- Oil- 1 tsp

Method:

Prepare the dough:

1. Combine all the ingredients for the dough together. Add water and knead soft dough.

2. Divide the dough into the number of rotis you want to make and keep aside.

Prepare the stuffing:

1. Mix all the vegetables together with ginger, chillies and salt to prepare a smooth stuffing.

2. Now roll one portion of the divided dough into a circle.

3. Put some amount of stuffing in the middle of circle, fold the dough from all sides and seal it. You can use a pinch of oil to seal well.

4. Roll it again over some flour and cook it over a hot non-stick pan with ghee or oil .

5. Repeat the process with rest of the divided dough. Serve hot.

Promoted

Be careful to prepare the vegetable stuffing right before making the rotis since the veggies would start to get watery.

Try these diabetic-friendly, nutritious stuffed rotis for lunch next and share your experience with us in the comments section below.

About Aanchal MathurAanchal doesn't share food. A cake in her vicinity is sure to disappear in a record time of 10 seconds. Besides loading up on sugar, she loves bingeing on FRIENDS with a plate of momos. Most likely to find her soulmate on a food app.

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Emerging Data on Type 1 Diabetes and COVID-19 Reassuring – Medscape

Saturday, October 10th, 2020

Editor's note: Find the latest COVID-19 news and guidance in Medscape's Coronavirus Resource Center.

Most people with type 1 diabetes do not appear to be at increased risk for hospitalization or death from COVID-19 compared to the general population, new research suggests.

Two retrospective studies of type 1 diabetes and COVID-19 were published in the October issue of Diabetes Care.

One, by Roman Vangoitsenhoven, MD, PhD, of University Hospitals Leuven, Belgium, and colleagues, found no evidence of increased hospitalization for COVID-19 among people with type 1 diabetes during the first 3 months of the pandemic in Belgium.

The other, from Maria Vamvini, MD, of the Joslin Diabetes Center, Boston, Massachusetts, and colleagues, showed that age and glycemic control didn't differ significantly between adults with type 1 diabetes hospitalized for COVID-19 and those hospitalized for other reasons.

Previous data from the UK Biobank and the Type 1 Diabetes (T1D) Exchange support these findings.

Altogether, these results suggest that although the risk for death from COVID-19 is higher overall among people with type 1 diabetes, that increased risk is mostly limited to a subset of particularly vulnerable patients, said Catarina Limbert, MD, PhD, during a press briefing at the virtual annual meeting of the European Association for the Study of Diabetes (EASD).

"Those with type 1 diabetes dying from COVID-19 were a specific population," stressed Limbert, of the University Center of Central Lisbon and Hospital Dona Estefania, Lisbon, Portugal.

"They had hemoglobin A1c levels above 10% and were over age 50 with a long diabetes duration. They were the more fragile, who couldn't survive the severity and aggressiveness of the virus. Good glucose control is a good sign and protective," she added.

Daniel Drucker, MD, of Mount Sinai Hospital, Toronto, Canada who spoke at the EASD press briefing regarding potential mechanisms involved in COVID-19 morbidity in diabetes reiterated the importance of glycemic control.

He showed a slide with the following advice for patients with both types of diabetes during the pandemic in addition to the general and now-familiar physical distancing, personal hygiene, hand washing, and wearing of masks:

Prepare a list of all medications, written and on the phone.

Consider supplies of medications, test strips, and continuous glucose monitoring equipment.

Don't neglect exercise, diet, and blood glucoseand blood pressure control.

Use telemedicine and devices to communicate with healthcare professionals.

Maintain appropriate levels of hydration, exercise, and glucose and ketone monitoring.

Optimize glycemic control whenever possible.

In hospitalized patients with type 2 diabetes, medications may need adjustment. Insulin is often the preferred glucose-lowering prescription.

In the Belgian study, medical records were analyzed for a total of 2336 patients with type 1 diabetes who received care at two specialist diabetes centers. The hospital admission rate was compared with national population data.

Overall, 0.21% (n = 5) of the patients with type 1 diabetes were admitted to the hospital with COVID-19, similar to the 0.17% (n = 15,239) of the general population, as of April 30, 2020 (P = .76).

During the same period, 127 individuals with type 1 diabetes were hospitalized for reasons other than COVID-19, including poor glycemic control (22%), diabetic ketoacidosis (8%), planned surgery (21%), diabetic foot problems (5%), and delivery (5%).

"It is noteworthy that the number of hospitalizations for reasons other than COVID-19 exceeded by far the number of COVID-19related hospitalizations," Vangoitsenhoven and colleagues write.

"Interpretation of adverse outcomes of people with type 1 diabetes during the COVID-19 epidemic should therefore be performed cautiously, as overinterpretation of the impact of COVID-19 itself on adverse outcomes in people with type 1 diabetes is likely," they conclude.

The Boston study, which was smaller, involved retrospective chart reviews of seven patients with type 1 diabetes hospitalized with COVID-19 and another 28 patients hospitalized for other reasons, all during the period from March to May 2020. The groups didn't differ in outpatient insulin doses corrected for weight or in glycemic control in the months preceding admission.

Diabetic ketoacidosis (DKA) occurred in one patient with COVID-19 and in two of the non-COVID patients. Both groups had significant preexisting diabetes-related complications, including nephropathy in more than half of each group and receipt of an organ transplant with immunosuppression in 14% of each group.

The composite outcome intensive care unit (ICU) admission, intubation, or death occurred in two COVID-19 patients (both cases involved ICU admission without intubation, and both patients recovered) and in four non-COVID patients, of whom two died.

The two groups showed "remarkable" similarity in age and glycemic control, although the COVID-19 patients were more likely to be Black (four vs two), consistent with other retrospective studies.

None of the patients had new-onset type 1 diabetes, which contrasts with the 15% seen in the T1D Exchange study.

Just 1 of the 7 patients with COVID-19 (14%) had DKA, compared with 30% of the confirmed and probable COVID-19 patients in the T1D Exchange study.

The significant difference in age about 52 years in the current study vs 21 years in the T1D Exchange study might explain those differences, Vamvini and colleagues say.

Limbert has received grants and personal fees from Abbott, Ipsen, and Sanofi. Vangoitsenhoven has disclosed no relevant financial relaitonships. Vamvini was supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Drucker receives research support, consulting fees, and/or lecture fees from Novo Nordisk, Merck, Pfizer, and Intarcia.

Diabetes Care. 2020 Oct;43:e118-e119. Vangoitsenhoven et al, Full text; 2020 Oct;43:e120-e122. Vamvini et al, Full text

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A 3D atlas of the dynamic and regional variation of pancreatic innervation in diabetes – Science Advances

Saturday, October 10th, 2020

INTRODUCTION

Insulin-producing cells do not exist in isolation, and their environment has substantial effects on their architecture and function. In addition to the adjacent , delta, ghrelin, pancreatic polypeptide, and other endocrine cells, the exocrine pancreas, vasculature, and innervation all modify cell organization and insulin release (1). Islets are innervated by autonomic parasympathetic and sympathetic fibers, as well as by sensory fibers (2, 3). Evidence from many studies over the past century has identified a critical role for neural signals in modulating insulin and glucagon release to regulate blood glucose (4). For example, anticipatory signals increase insulin release upon food consumption but before any changes in blood glucose, and neural signals suppress insulin and stimulate glucagon release to counteract hypoglycemia (4). Since central nervous system (CNS) and nerve stimulation studies demonstrate that neural signals can override the effects of circulating glucose (5, 6), neural modulation is an attractive target for therapies to improve metabolic control.

Our current understanding of islets and their innervation largely relies on traditional histological techniques using immunolabeled structures in thin sections. These studies have provided a wealth of knowledge about islet structure at high resolution. However, pancreata are highly heterogeneous (7), with distinct regional embryological origins. Sections also lack landmarks to precisely and consistently identify the location of internal structures (8). Until now, laborious serial sectioning and reconstruction have been needed to deliver information about islet anatomy throughout the pancreas. In addition, thin filamentous structures, such as nerves, are difficult to quantify and trace over large volumes using this approach. Recent studies have applied confocal imaging of small pieces and thick sections of cleared pancreatic tissue to examine endocrine innervation (914). These have revealed dense nerve processes within both mouse and human islets. However, given the heterogeneity in the pancreas, there is a clear need for high-resolution, organ-wide imaging to accurately quantify and map regional variation and to assess the three-dimensional (3D) relationship between islets and their environment in health and disease.

Here, we used a tissue-clearing technique, iDISCO+ (15), to determine the 3D distribution of insulin-producing cells, glucagon-producing cells, and neurofilament 200 kDa (NF200)positive innervation across the whole pancreas in healthy animals and in mouse models of diabetes. NF200 is a pan-neuronal marker expressed in sympathetic, sensory, and vagal neurons but, unlike other neural markers, is not expressed in pancreatic endocrine cells (1618). NF200 is expressed in small and large myelinated and small unmyelinated fibers (19), so examining NF200+ fibers provides a comprehensive overview of pancreatic innervation. In addition, NF200 protein levels are altered by nerve damage and repair (2022), so NF200 intensity may reflect remodeling of pancreatic nerves. Using whole-organ 3D imaging and analysis, we readily quantified cell volume and provide detailed information about islet distribution and heterogeneity in mouse and human pancreatic tissue from healthy and diabetic donors. We quantified the dense endocrine innervation and its regional variation and demonstrated significant differences between innervated and noninnervated islets. Islet nerve density is significantly increased in diabetic nonobese diabetic (NOD) mice, with streptozotocin (STZ) treatment, and greater in pancreatic tissue from diabetic human donors. We systematically quantified intrapancreatic ganglia and nerve contacts with and cells to demonstrate that these are largely preserved in diabetes. These findings constitute a 3D atlas of pancreatic innervation for pancreas and diabetes investigators examining pancreatic innervation, the regional heterogeneity in the healthy pancreas, and responses to metabolic disease. Our studies suggest that diabetes is associated with significant remodeling of neural inputs into islets and that neural contacts with endocrine cells are preserved in diabetes.

We applied tissue clearing and whole-organ 3D imaging to examine cell mass, expressed as cell volume, and islet number, as well as spatial distribution in whole pancreata from C57BL/6 mice (Fig. 1, A to C, and movies S1 and S2).

(A) Pancreatic dissection. Photo credit: A.A., Icahn School of Medicine at Mount Sinai. (B) Duodenal (left) and splenic (right) pancreas, maximum projection (1.3). Scale bars, 500 m. (C) Pancreata, maximum projection at 4 (left) and 12 (right). Scale bars, 500 and 200 m. (D) cell volume. (E) Insulin+ islets per cubic millimeter. (F) Insulin intensity (normalized to whole pancreas). (G) Insulin+ islet volume distribution (left axis) and median volume (right axis). Islets per group: 27,092/12,260/14,832. (H) 3D projection of insulin, NF200+ exocrine innervation, and NF200+ surfaces within insulin+ islets (yellow). (I) Exocrine nerve volume. (J) Endocrine nerve volume per insulin+ islet. (K) Endocrine nerve volume/islet volume. (L) Left: 3D model of pancreatic innervation (NF200, white) and insulin (green). Right: Distance transformation analysis with islet surfaces pseudocolored based on distance from the nearest nerve surface. Scale bar, 500 m. Boxed area magnified in the right panel. Scale bar, 200 m. Data are shown as means SEM or median 95% confidence interval as indicated. Analyses by unpaired t test, *P < 0.05 and **P < 0.01. T, total; D, duodenal; S, splenic. N = 7 (D to G) and N = 5 (I to K).

The total cell volume made up 1.31 0.17% of the total pancreatic volume (Fig. 1D), with a greater cell volume in the splenic region. In line with previous reports (23, 24), there were 3874 264.2 islets per pancreas, with 1822 230.4 in the duodenal and 2052 129 in the splenic regions. Islet density (islet number per cubic millimeter) did not differ significantly across the pancreas (Fig. 1E). Insulin intensity showed significant regional variation with intensity in the duodenal pancreas being 25% greater than that in the splenic region (Fig. 1F).

We next examined islet distribution throughout the pancreas to determine whether there were regional differences in cell volume per islet (Fig. 1G). Islets with cell volumes between 1000 and 50,000 m3 were the most abundant (39.29%), followed by islets in the 50,000 to 499,999 m3 range (36.58%). Very large islets (>500,000 m3) comprised 20% of the islet population, and insulin+ structures with volumes below 1000 m3, consisting of five or fewer cells, were the least abundant (3.13%).

There are reported differences in the origins of nerves innervating the duodenal and splenic pancreas (25). Therefore, we hypothesized that there may be regional variations in pancreatic innervation. Thus, we next analyzed the 3D distribution of the pan-neuronal marker NF200 in the healthy mouse pancreas to determine regional variations and relationship to islets (Fig. 1H and movies S3 to S5).

The exocrine nerve volume was 40% greater in the duodenal pancreas compared with the splenic region (Fig. 1I). Pancreatic islets were highly innervated compared to exocrine tissue, with an endocrine nerve density over sixfold greater than the exocrine nerve density. In addition, there was significant regional variation in islet innervation. Nerve volume per islet in the duodenal region was almost double that in the splenic region (Fig. 1J). This difference was more pronounced when the endocrine nerve volume was corrected for cell volume (Fig. 1K). These findings are consistent with marked regional variation in the density of islet innervation.

The proximity of nerves and endocrine cells may have important biological consequences. Autonomic neurotransmission occurs over 1 to 2 m (26), but endocrine and immune cells may influence nerve growth, repair, and function over longer ranges (27, 28). As a result, we examined the proportion of islets in contact with NF200+ fibers and the distance of each islet from the closest NF200+ fiber (Fig. 1L and movie S6). Only 6.1% of islets contained or were in contact with NF200+ fibers, with no significant difference between duodenal and splenic regions (Fig. 2A). The proportion of innervated (NF200+) islets increased with islet volume (fig. S1C). Most islets were within 250 m of an NF200+ fiber, and islets in the duodenal pancreas were significantly closer to nerves than those in the splenic pancreas (fig. S1A).

(A) Distribution of insulin+ islets (<1.6 and >1.6 m from the nearest nerve). Islets per group: 25,310/10,030/15,280. (B) Mean insulin+ islet volume NF200+ innervation; islets per group: 11,869/929/4690/325/7179/604. (C) Total insulin+ islet volume NF200+ innervation. (D) NF200 intensity sum normalized for insulin+ islet volume; islets per group: 5174/4530/2264/687/2196/1788/701/330/2978/2742/1563/357. (E) Intrapancreatic ganglia (NF200, magenta) and cells (insulin, green). Arrows mark ganglia. Scale bar, 50 m. (F) NF200+ intrapancreatic ganglia per cubic millimeter. (G) Intrapancreatic ganglia volume. Ganglia per group: 123/43/80. (H) Distance between intrapancreatic ganglia and insulin+ islets. Ganglia per group: 123/43/80. (I) cells contacting nerves per islet. Islets per group: 69/40/29. Data are shown as means SEM or median 95% confidence interval as indicated. Analyses by Kruskal-Wallis test with Dunns test (B to D) or unpaired t test (F to I), ***P < 0.001. T, total; D, duodenal; S, splenic. N = 5 (A to D), N = 3 (F to H), and N = 4 (I).

To test the hypothesis that innervated islets differ from those without innervation, we then analyzed islet volume based on whether islets were innervated by NF200+ fibers, hypothesizing that neural signals may play a role in determining islet size. NF200-innervated islets were 10-fold larger than islets without NF200 innervation (Fig. 2B and fig. S1B), and as a result, innervated islets made up 43% of the total cell volume in the pancreas (Fig. 2C). Both innervated and noninnervated islets in the splenic region were larger than those in the duodenal pancreas (Fig. 2B).

Next, we analyzed the intensity of NF200+ immunostaining within each islet. NF200 protein levels are associated with structural stability of nerves and increased conduction velocity, so NF200+ immunostaining intensity may have functional correlates (29, 30). While the largest islets were more likely to be innervated, the intensity of NF200+ immunostaining was twofold greater in the smallest islets compared to the largest islets and greater in subpopulations of duodenal islets (Fig. 2D).

These data demonstrate that innervated islets are a small fraction of the total islet number but are significantly larger than islets without NF200 innervation and form a substantial portion of the total cell volume. These findings suggest the potential involvement of NF200+ nerves in islet development and cell growth.

Intrapancreatic ganglia integrate inputs from the sympathetic and parasympathetic nervous systems and provide significant islet innervation (31). Regional differences in ganglia size in the pancreas have been reported (32). Intrapancreatic ganglia are sparse (21.5 2.5 ganglia/mm3; Fig. 2, E and F), with an average volume of 83,467 10,646 m3 (Fig. 2G) and located close to islets (47.3 5.7 m; Fig. 2H). There were no significant regional differences in ganglia density, size, or location.

To assess whether islet innervation could directly influence endocrine cell function through neural signals, we quantified the number of cells contacting NF200+ nerves. Only 9.4 2.2% of cells contacted NF200+ nerves (Fig. 2I) with no regional difference. As expected, a larger number of cells contacted nerves in large islets compared to small islets (fig. S1D), but the proportion of cells contacting NF200+ nerves did not differ with islet size (fig. S1E). In aggregate, these data provide a comprehensive 3D atlas of the anatomy and NF200+ innervation of the entire mouse endocrine and exocrine pancreas that can be used as a benchmark to assess the effects of specific pancreatic innervation during development and in disease.

The 3D relationships between islets and innervation across the whole endocrine pancreas are largely unknown in diabetes. Hence, we determined how pancreatic anatomy and cell innervation were affected in a mouse model of type 1 diabetes (T1D). NOD mice provide a model of diabetes with autoimmune cell destruction and spontaneous T1D development. We examined the 3D structure of NF200+ innervation and islets in nondiabetic NOD mice (average nonfasting blood glucose, 115 4 mg/dl) and diabetic NOD mice (average nonfasting blood glucose, 495 62 mg/dl; Fig. 3A and movies S7 and S8).

(A) Pancreata from nondiabetic and diabetic NOD mice [maximum projection at 1.3 (top), 4 (middle), and 12 (bottom); scale bars, 2000, 500, and 200 m]. (B) cell volume. (C) Insulin+ islets per cubic millimeter of pancreatic tissue. (D) Insulin intensity (normalized against total pancreas, nondiabetic). (E) Insulin+ islet volume distribution (left axis) and median volume (right axis). Islets per group: 11,404/6285/5119/4057/2203/1854. (F) Exocrine nerve volume. (G) Endocrine nerve volume per insulin+ islet. (H) Endocrine nerve volume by islet volume. (I) Distribution of insulin+ islets located <1.6 and >1.6 m from the nearest nerve. (J) Mean insulin+ islet volume NF200+ innervation. Islets per group: 8815/857/4296/436. (K) Total insulin+ islet volume NF200+ innervation. (L) NF200 intensity sum normalized for insulin+ islet volume. Islets per group: 4941/3341/1209/383/2862/1586/189/73. (M) Intrapancreatic ganglia per cubic millimeter. (N) Intrapancreatic ganglia volume. Ganglia per group: 112/82. (O) Distance between intrapancreatic ganglia and insulin+ islets. Ganglia per group: 111/54. (P) cells contacting nerves per islet. Islets per group: 28/14. Data are shown as means SEM or median 95% confidence interval where indicated. Analyses by one-way ANOVA with Tukeys test (B to D and F to G), Kruskal-Wallis with Dunns test (H and J to L), or unpaired t test between diabetic and nondiabetic groups (H). *P < 0.05, **P < 0.01, and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 7 nondiabetic and N = 7 diabetic (B to E, P); N = 8 nondiabetic and N = 7 diabetic (F to L); N = 6 nondiabetic and N = 6 diabetic (M to O).

Across the whole pancreas, islet density and cell volume in female nondiabetic NOD mice were similar to that seen in male C57BL/6 mice (Figs. 1, D and E, and 3, A to C). In female diabetic NOD mice, the cell volume was significantly lower across the whole pancreas, reduced to 10% of the volume in nondiabetic NOD mice in both splenic and duodenal regions (Fig. 3B). The islet number was also significantly reduced in diabetic NOD mice, particularly in the splenic, but not duodenal pancreas (Fig. 3C). However, the intensity of insulin immunostaining was preserved in the remaining islets that were detected in diabetic NOD mice (Fig. 3D). There was a significant inverse correlation between blood glucose levels and both islet number and cell volume (fig. S2A).

The volume distribution of insulin+ islets in nondiabetic NOD mice was also comparable to C57BL/6 mice (Fig. 3E). However, islet volume distribution was significantly shifted in diabetic NOD mice, with marked loss of larger islets. Insulin+ islets over 50,000 m3 were reduced by more than half, and the median islet volume decreased by more than 50%. The loss of large islets was particularly notable in the duodenal pancreas (Fig. 3E).

Together, these data demonstrate marked decreases in insulin+ islet number and volume and marked alterations in islet volume distribution in diabetic compared to nondiabetic NOD mice, particularly in the duodenal pancreas. Our data also suggest that the remaining islets in diabetic NOD mice maintained their insulin content.

Previous studies have reported alterations in pancreatic innervation in mouse models of diabetes (13, 3336). Therefore, we examined pancreatic innervation in NOD mice to determine effects on nerve density in the different regions of the pancreas (movies S9 and S10).

Nerve density in insulin+ islets was increased more than twofold in diabetic NOD mice (Fig. 3, G and H), particularly in the splenic pancreas. Islet nerve density in the splenic pancreas positively correlated with blood glucose (fig. S2C). The regional differences in endocrine nerve density observed in C57BL/6 mice were absent in nondiabetic NOD mice. There was no difference in exocrine nerve density between nondiabetic and diabetic NOD mice and no correlation with blood glucose (Fig. 3F and fig. S2B).

Previous studies suggest that neural signals contribute to cell survival (37), so increased islet innervation could result from differences in the susceptibility of innervated and noninnervated islets to immune destruction. To test this, we examined the proportion of NF200+ islets (islets containing or in contact with NF200+ fibers) in NOD mice. We did not see any significant change in the proportion of NF200+ islets (14.6 versus 9.8% islets in nondiabetic and diabetic NOD mice, respectively; Fig. 3I). However, the proportion of NF200+ islets was increased in a subset of islets with volumes between 50,000 and 500,000 m3 in diabetic NOD mice (fig. S2F). The median distance between islets and nerves was similar in diabetic and nondiabetic NOD mice for the total pancreas but significantly reduced in the splenic pancreas (fig. S2D).

In keeping with the results in C57BL/6 mice, NF200+ islets were significantly larger than NF200 islets in both diabetic and nondiabetic NOD mice (Fig. 3J), although, as expected, the average volume of both NF200 and NF200+ islets decreased in diabetic NOD mice. Innervated insulin+ islets remained 60% of the total cell volume in both diabetic and nondiabetic NOD mice (Fig. 3K).

In published studies, the intensity of NF200 immunostaining decreases with nerve damage and increases in nerve regeneration (20, 22). To indirectly assess the effects of autoimmune diabetes on nerve integrity in islets, we examined the intensity of NF200 immunostaining in diabetic and nondiabetic NOD mice and found that the intensity of NF200 immunostaining was significantly increased in islets from diabetic NOD mice (Fig. 3L).

We next examined intrapancreatic ganglia to determine whether autoimmune diabetes altered their distribution or size. There was no significant difference in intrapancreatic ganglia density (18.9 5.2 versus 28.2 10.1 ganglia/mm3, nondiabetic versus diabetic NOD mice, respectively; Fig. 3M) or volume (61,779 5961 versus 59,348 6977 m3, nondiabetic versus diabetic NOD mice, respectively; Fig. 3N), but the distance between intrapancreatic ganglia and islets increased fourfold in diabetic NOD mice (40 5.3 versus 171.7 17.6 m, nondiabetic versus diabetic, respectively; Fig. 3O).

Next, we examined the proportion of cells in contact with NF200+ fibers in nondiabetic and diabetic NOD mice. Despite a significant increase in islet nerve density, there was no significant change in the proportion of cells contacting nerves in diabetic NOD mice (Fig. 3P).

Autoimmune cell destruction principally affects cells in NOD mice resulting in islets composed primarily of glucagon+ cells. The changes in cell innervation in mouse models of diabetes are largely unknown. In diabetic NOD mice, glucagon staining is clearly present, but glucagon+ cells from a single islet may form several clusters rather than a clearly defined, single islet (Fig. 4, A and B). As previously reported (38), the ratio of glucagon to insulin volume (Fig. 4C) was significantly increased in diabetic NOD mice (movies S11 and S12). In nondiabetic NOD mice, NF200 nerve density in cell clusters was markedly higher than nerve density in insulin+ islets. Nerve density in diabetic NOD mice was unchanged (Fig. 4D). The proportion of innervated cell clusters was similar to that of innervated insulin+ islets in nondiabetic NOD mice and increased twofold in diabetic NOD mice (Fig. 4E). In keeping with increased NF200 nerve density in cell clusters of nondiabetic NOD mice, the proportion of cells contacting NF200+ fibers was more than fivefold higher than cells contacting NF200+ fibers in nondiabetic NOD mice. However, the proportion of cell nerve contacts did not change in diabetic mice (Fig. 4F).

(A) Maximum projections of light-sheet images of pancreatic samples from nondiabetic and diabetic NOD mice stained for insulin (green), NF200 (magenta), and glucagon (blue) and imaged at 4 magnification. Scale bars, 200 m. (B) cell volume corrected for pancreatic volume in NOD mice. (C) Glucagon+ cell volume as a percentage of insulin+ cell volume in NOD mice. (D) NF200+ nerve volume within glucagon+ cell clusters in NOD mice. (E) Glucagon+ cell cluster volume (left axis) and median nerve distance (right axis) in NOD mice. (F) Percentage of cells contacting nerves per islet. Number of islets: 23/16. Data are shown as mean SEM or as median 95% confidence interval where indicated. Analyses by one-way ANOVA with Tukeys test (D) or Kruskal-Wallis with Dunns test (B, C, and E). *P < 0.05. T, total; D, duodenal; S, splenic. N = 3 nondiabetic and N = 3 diabetic NOD mice.

In summary, insulin+ islet nerve density and NF200 immunostaining are increased in the surviving insulin+ islets of diabetic NOD mice, and cell contacts with NF200+ fibers are preserved. cell nerve density and cell contacts with NF200+ fibers are greater than contacts with cells, and cell nerve density also increases in diabetic NOD mice.

On the basis of our findings in NOD mice, we hypothesized that nerve density may progressively increase in surviving islets during the development of diabetes. To test this hypothesis, we examined the time course of changes in insulin+ islets and pancreatic nerves in mice with STZ-induced diabetes, as well as in age- and sex-matched C57BL/6 mice. Diabetes secondary to multiple low-dose STZ treatment is likely induced by both direct cell toxicity and islet inflammation. Therefore, using a standard 5-day low-dose STZ model, we examined NF200, insulin, and glucagon staining in mice sacrificed 5 and 15 days after completion of STZ treatment (nonfasting blood glucose: 259 18 and 430 17 mg/dl, respectively) and compared these to untreated littermate controls (nonfasting blood glucose: 123 9 mg/dl; Fig. 5A and movies S13 and S14).

(A) Pancreata at days 5 (left) and 15 (right) after STZ treatment, maximum projections at 1.3 (top), 4 (middle), and 12 (bottom). Scale bars: 1000, 500, and 200 m. (B) cell volume. (C) Insulin+ islets per cubic millimeter. (D) Insulin intensity (normalized against total pancreas, control). (E) Insulin+ islet volume distribution (left axis) and median volume (right axis). Islets per group: 10,479/4682/5797/10,091/5162/4929/14,380/7543/6837. (F) Exocrine nerve volume. (G) Endocrine nerve volume per insulin+ islet. (H) Endocrine nerve by islet volume. Data are shown as mean SEM or as median 95% confidence interval where indicated. Analyses by one-way ANOVA with Tukeys test for comparison between control, STZ day 5, and STZ day 15, and unpaired t test for comparison between duodenal and splenic pancreas (B to D and F to H) or Kruskal-Wallis with Dunns test (E); *P < 0.05, **P < 0.01, and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 5 control, N = 6 STZ day 5, and N = 7 STZ day 15 (B to E); N = 6 control, N = 5 STZ day 5, and N = 5 STZ day 15 (F to H).

First, we analyzed islet number and total cell volume to determine the time course and effects of STZ treatment, hypothesizing that STZ may differentially affect these parameters in different pancreatic regions. As expected in this model, total cell volume was reduced to 40% of control, and intensity of insulin immunostaining was decreased by 50% with STZ treatment (Fig. 5, B to D). Islet number and cell volume negatively correlated with blood glucose in STZ-induced diabetes (fig. S3A). STZ treatment did not significantly alter the distribution of cell volumes throughout the pancreas, suggesting that its effects were uniform across islets of all sizes (Fig. 5E). However, there was a significant decrease in the individual islet volume, first in the duodenal pancreas at day 5 and later at day 15 in both the duodenal and splenic regions. These findings demonstrate that STZ treatment progressively reduces total cell volume, intensity of insulin immunostaining, and the volume of individual islets, with significant differences in the time course and extent of these changes between duodenal and splenic pancreas.

We next examined pancreatic innervation in STZ-treated mice to determine the time course and regional distribution of effects on nerve density (movies S15 and S16). Nerve density in the exocrine pancreas was significantly increased 15 days after STZ treatment (Fig. 5F and fig. S3B). STZ treatment significantly increased islet innervation and islet nerve density by twofold on day 5 (Fig. 5, G and H). Islet nerve density was significantly correlated with blood glucose (fig. S3A).

To test the hypothesis that neural signals may play a role in cell preservation, we assessed whether STZ treatment had differential effects on islets based on whether they contained NF200+ nerves or not. STZ treatment led to a progressive increase in the proportion of NF200+ islets across the duodenal and splenic pancreas (Fig. 6A) and all islet sizes (fig. S3F) but did not reach significance (P = 0.14). STZ treatment significantly reduced the distance between insulin+ islets and NF200+ fibers on day 5, primarily in the splenic pancreas (fig. S3D). In both control and STZ-treated mice, innervated islets are significantly larger than noninnervated islets but decline in volume with STZ treatment (Fig. 6B). The total volume of innervated islets, but not of noninnervated islets, significantly decreased with STZ treatment (Fig. 6C) but remained 54% of the remaining total cell volume.

(A) Distribution of insulin+ islets located <1.6 and >1.6 m from the nearest nerve. (B) Mean volume for insulin+ islets NF200+ innervation. Islets per group: 10,199/929/5300/366/9837/1022. (C) Total volume for insulin+ islets NF200+ innervation. (D) Intensity of NF200 immunolabeling normalized for insulin+ islet volume. Islets per group: 3013/2762/1837/605/2842/1791/1057/336/5800/3274/1500/386. (E) Ganglia per cubic millimeter. (F) Volume of intrapancreatic ganglia. Ganglia per group: 114/73/97. (G) Distance between intrapancreatic ganglia and insulin+ islets. Ganglia per group: 114/73/97. (H) Percentage of cells contacting nerves per islet. Islets per group: 69/28/69. Data are shown as means SEM or as median 95% confidence interval where indicated. Analyses by Kruskal-Wallis with Dunns test (B to D) for comparison between control, STZ day 5, and STZ day 15, and unpaired t test for comparison between duodenal and splenic pancreas (E to H). *P < 0.05, **P < 0.01, and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 6 control, N = 5 STZ day 5, and N = 5 STZ day 15 (A to D); N = 6 control, N = 3 STZ day 5, and N = 3 STZ day 15 (E to H).

To determine whether STZ-induced diabetes modified the expression of NF200, we assessed changes in intensity of NF200 immunostaining in relation to insulin+ islet volume and time after treatment (Fig. 6D). The intensity of NF200 immunostaining (corrected for cell volume) was significantly increased in the largest islets (>500,000 m3) 5 days after STZ treatment and by twofold to fourfold in all islets at 15 days after STZ treatment. These findings demonstrate that STZ treatment increases exocrine and endocrine nerve density and NF200 expression, results that are in keeping with increased nerve growth.

We next examined intrapancreatic ganglia in mice treated with STZ to determine whether cell destruction changed their density or size. While STZ treatment did not change intrapancreatic ganglion density or distance from the islet, there was a 30% decrease in ganglion volume 15 days after STZ treatment (Fig. 6, E to G). Similar to our findings in NOD mice, although islet nerve density increased with STZ treatment, the proportion of cells contacting NF200+ fibers did not change significantly (Fig. 6H).

We next assessed cell volume and nerve density in cell clusters in STZ-treated mice. STZ treatment increased the ratio of glucagon+ to insulin+ cell volume, but total glucagon+ cell volume was reduced after 15 days (Fig. 7, A to C, and movie S17). NF200 nerve density in cell clusters was significantly increased in STZ-treated mice (Fig. 7D), but the proportion of innervated cell clusters did not change (Fig. 7E). Similarly, the proportion of cells contacting NF200+ fibers was not significantly altered by STZ treatment (Fig. 7F).

(A) Pancreata at days 5 (left) and 15 (right) after STZ treatment. Insulin, green; NF200, magenta; glucagon, blue. Imaged at 4 magnification. Scale bars, 200 m. (B) Quantification of cell volume corrected for pancreatic volume in STZ-treated mice. (C) Quantification of glucagon+ cell volume as a percentage of insulin+ cell volume in STZ-treated mice. (D) Quantification of NF200+ nerve volume within glucagon+ cell clusters in STZ-treated mice. (E) Glucagon+ cell cluster volume (left axis) and median nerve distance (right axis) in STZ-treated mice. (F) Percentage of cells contacting nerves per islet. Islet number: 98/37/53. Data are shown as means SEM or as median 95% confidence interval where indicated. Analyses by one-way ANOVA with Tukeys test (C to D) or Kruskal-Wallis with Dunns test (B and E). *P < 0.05, **P < 0.01, and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 6 control, N = 4 STZ day 5, and N = 6 STZ day 15.

In summary, 3D representation faithfully represents the progressive reduction in islet number, cell volume, and intensity of insulin immunostaining in response to STZ treatment. Further, STZ treatment increases insulin+ islet nerve density, the proportion of innervated islets, and intensity of NF200 immunostaining. cell nerve density is increased with STZ treatment, but the proportion of and cells that are in contact with NF200+ fibers is not significantly altered in STZ-treated mice.

Islet innervation differs between species (3, 39) and the 3D relationships between islets and pancreatic nerves in healthy versus diabetic patients remain largely unknown. To assess these, islets and NF200+ innervation were examined in small, cleared pancreatic samples from healthy human donors and donors with type 2 diabetes (T2D; Table 1) by light-sheet imaging to assess islet distribution and relationship to innervation (Fig. 8A and movies S18 and S19).

CVA, cardiovascular accident; HbA1c, hemoglobin A1C; N/A, not applicable; PFA, paraformaldehyde; M, male; F, female.

(A) Maximum projections of pancreatic samples from human donors without (C1 to C5) and with type 2 diabetes (DM2; D1 to D3) at 1.3. Scale bars, 1000 m. (B) cell volume. (C) Insulin+ islets per cubic millimeter. (D) Insulin+ islet volume distribution (left axis) and median volume (right axis). (E) Exocrine nerve volume. (F) Endocrine nerve volume per insulin+ islet. (G) Endocrine nerve volume corrected for insulin+ islet volume. (H) Distribution of insulin+ islets located at <1.6 and >1.6 m from nerves. Islets per group: 28,315 control and 6790 DM2. (I) Mean volume of insulin+ islets NF200+ innervation. Islets per group: 25,519/236/7448/345. (J) Total volume of insulin+ islets NF200+ innervation. (K) Intrapancreatic ganglia (NF200, magenta; confocal, 20). Boxed areas magnified in lower panels with cell bodies indicated by arrows. Scale bars, 50 m (top) and 25 m (bottom). (L) Ganglia per cubic millimeter. (M) Volume of intrapancreatic ganglia. Ganglia per group: 31/12. (N) Distance between intrapancreatic ganglia and insulin+ islets. Ganglia per group: 31/12. (O) cells contacting nerves per islet. Islets per group: 73/28. Data are shown as means SEM or as median 95% confidence interval where indicated. Analyses by unpaired t test (B to G and L to M), Mann-Whitney test (H), or Kruskal-Wallis with Dunns test (I to J). *P < 0.05, **P < 0.01, and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 5 control and N = 3 DM2.

As expected, total cell volume (Fig. 8B) and islet number (Fig. 8C) were highly variable (40). The cell volume (as a percentage of the total pancreatic sample volume) was lower in the diabetic donors, varying between 0.47 and 2.2% in the control group and 0.85 and 0.97% in the diabetic group. Islet numbers ranged from 66 to 200 islets/mm3 in the control group to 58 to 287 islets/mm3 in the diabetic group. While islet number per cubic millimeter was greater in humans than in mice, the cell volume (%) was very similar in murine and human tissues. The cell volume distribution in nondiabetic pancreata was not significantly different to that in mice (Fig. 8D). Larger islets were disproportionately reduced, and the mean volume of an individual islet was significantly lower in diabetic compared to healthy individuals.

In human samples from healthy donors, NF200+ innervation was similar between endocrine (0 to 0.89% nerve volume per islet) and exocrine tissue (0.06% to 0.94% nerve volume per exocrine tissue; Fig. 8, E to G). Exocrine nerve volume, endocrine nerve volume per islet, islet nerve density, and proportion of innervated islets were greater in diabetic individuals (Fig. 8H). In nondiabetic individuals, innervated insulin+ islets are significantly larger than those without innervation, in line with the findings in mice, but innervated insulin+ islets are a smaller proportion of the total islet volume than seen in mouse pancreata. In diabetic individuals, innervated islets are significantly smaller than in nondiabetic individuals (Fig. 8, I and J).

We next assessed intrapancreatic ganglia in human pancreatic samples. Human intrapancreatic ganglia were larger than those found in mice (Fig. 8K), but ganglion density and distance from islets were similar to C57BL/6 and nondiabetic NOD mice. There was no significant difference in ganglia size between nondiabetic and diabetic donors (Fig. 8, L to N). Last, we examined contacts between NF200+ nerves and cells. The proportion of cells in contact with NF200+ fibers was half of that in control mice (4.15 versus 9.44%) and was preserved in individuals with diabetes (6.07%; Fig. 8O).

Together, cell volume and distribution in human pancreata were comparable to murine pancreata, and innervated islets were significantly larger than noninnervated islets. In samples from individuals with diabetes, exocrine and endocrine innervation as well as proportion of innervated islets were increased, and nerve contacts with cells persist.

The pancreas is composed of multiple cell types, is richly vascularized, and is densely innervated by sympathetic, parasympathetic, and sensory nerves. We wanted to compare our analyses of pancreatic innervation using the pan-neuronal marker, NF200, with pathway-specific pancreatic innervation. Using a modified iDISCO+ protocol specifically optimized for pancreatic tissue, we examined tyrosine hydroxylase (TH) immunolabeling to mark sympathetic nerve fibers (movie S20) and vesicular acetylcholine transporter (VAChT) immunolabeling to identify parasympathetic nerve fibers (movie S21) across the mouse pancreas. There was more TH+ (Fig. 9, A to D) and VAChT+ (Fig. 9, H to K) innervation than NF200+ innervation in both the exocrine and endocrine pancreas. In keeping with our findings examining NF200+ fibers, TH and VAChT nerve density were threefold to more than sixfold greater in the endocrine than in the exocrine pancreas. The proportion of islets containing or in contact with TH+ fibers was 27.7% (Fig. 9E) compared to 35.0% for VAChT+ fibers (Fig. 9L). In line with our findings with NF200, both TH (Fig. 9F) and VAChT (Fig. 7M) innervated islets were significantly larger than noninnervated islets, and as a result, the majority of insulin+ islet volume is composed of innervated islets (Fig. 9, G and N).

(A) Maximum projections of TH and insulin. Scale bars, 2000 m at 1.3 and 200 m at 4. (B) TH+ exocrine nerve volume. (C) TH+ endocrine nerve volume per insulin+ islet. (D) TH+ endocrine nerve volume by insulin+ islet volume. (E) Distribution of insulin+ islets located at <1.6 and >1.6 m from TH+ nerves. Islets per group: 10,610/4773/5837. (F) Mean insulin+ islet volume for insulin+ islets with and without TH+ innervation. Islets per group: 8542/3314/4699/1320/3843/1994. (G) Total volume for insulin+ islets with and without TH+ innervation. (H) Maximum projections of VAChT and insulin. Scale bars, 2000 m at 1.3 and 200 m at 4. (I) VAChT+ exocrine nerve volume. (J) VAChT+ endocrine nerve volume per insulin+ islet. (K) VAChT+ endocrine nerve volume corrected for insulin+ islet volume. (L) Distribution of insulin+ islets located at <1.6 and >1.6 m from VAChT+ nerves. Islets per group: 12,661/7165/5496. (M) Mean volume for insulin+ islets with and without VAChT+ innervation. Islets per group: 8542/3314/4699/1320/3843/1994. (N) Total volume for insulin+ islets with and without VAChT+ innervation. Data are shown as means SEM or as median 95% confidence interval where indicated. Analyses by unpaired t test (B to E and I to L) or Kruskal-Wallis with Dunns test (F, G, M, and N). **P < 0.01 and ***P < 0.001. T, total; D, duodenal; S, splenic. N = 5.

The optimized iDISCO+ protocol was also effective for labeling fibers expressing TRPV1 (transient receptor potential cation channel, subfamily V, member 1) and synapsin (fig. S4). In addition, we applied a novel alternative approach to visualize islet vasculature by combining insulin immunolabeling with fluorophore-tagged dextran or CD31 antibody, followed by optical clearing using ethyl cinnamate (ECi) to preserve fluorescence while allowing for additional immunostaining tissue (fig. S4) (41). These data demonstrate that modification of optical clearing protocols allows for visualization of multiple markers in pancreatic tissue.

In summary, NF200, TH, and VAChT immunostaining all demonstrate that large islets have enriched islet innervation and that large innervated islets represent at least half of total pancreatic islet volume. However, analysis of pancreatic innervation using TH and VAChT immunostaining suggests that endocrine nerve density is greater than revealed by NF200 immunostaining.

Tissue clearing, 3D imaging, and unbiased image analysis have been widely used in the CNS to provide new insights into anatomical pathways and patterns of regional activation. However, there have been few applications in peripheral organs such as the pancreas. Whole-organ clearing and imaging are especially suited for the mapping of filamentous structures, particularly to delineating innervation across large distances that can be difficult to achieve using traditional serial sections and 2D imaging. Tissue clearing has been used previously in thick pancreatic sections (350 to 1000 m) (9, 10, 12, 4244) and small pieces of pancreatic tissue (11) and then imaged with optometry or high-magnification confocal microscopy for detailed analysis [see (4547) for review]. This has provided important information about islet characteristics and structural relationships over a close range. In particular, previous studies using 3D imaging in pancreatic sections, fetal tissue, and young mice have provided data about islet innervation (9, 10, 13, 14, 42, 48). Our data extend these important published studies. Different pancreatic regions have diverse embryological origins and variations in islet density and function and are supplied by neurons from different extrapancreatic ganglia. Without assessing pancreatic structure across the whole organ, our understanding and quantification of pancreatic anatomy, including possible regional differences, are incomplete and possibly inaccurate.

Tissue clearing and volume imaging of the pancreas provided several new insights. Innervation of the endocrine pancreas is significantly enriched compared to the surrounding exocrine pancreas, with marked regional variation. Islets are closely associated with pancreatic innervation, and innervated islets are significantly larger than noninnervated islets, in both mouse and human. Intrapancreatic ganglia are sparse and close to islets. Almost half of cells and a tenth of cells contact NF200+ fibers, irrespective of islet size or location. Last, islet nerve density and expression of NF200 are increased in the remaining islets of two mouse models of T1D, with temporal and regional differences, and greater in human T2D, in keeping with nerve remodeling.

3D imaging across the whole pancreas provides straightforward measurement of multiple islet characteristics and identifies significant regional differences that would be laborious or impossible to obtain by serial sectioning. We readily measured cell volume across multiple pancreata, and our findings are in agreement with previous studies at 1 to 2% in mouse pancreas (24) and at 1 to 4% in human pancreas (49, 50). Increased islet volume in the splenic pancreas is in keeping with previous observations using 2D histology, in isolated islets and in transgenic mice (51, 52). Intensity of insulin immunostaining was significantly lower in the splenic pancreas. The splenic pancreas contains significantly larger islets, and previous studies report lower insulin immunostaining intensity and fewer insulin granules in large islets, while other studies demonstrate lower c-peptide content in cells from the splenic pancreas (53, 54). Our approach also facilitates rapid analysis of islet volume distribution across the pancreas. The majority of islets were between 1000 and 500,000 m3, equivalent to islet diameters of 12 to 98 m (assuming spherical islets), with around a fifth of islets having volumes larger than 500,000 m3. Whole-organ imaging demonstrated significant differences in islet biology between diabetes models. Islet number and cell volume were reduced in diabetic NOD mice, with the intensity of insulin immunostaining relatively preserved in some islets and a notable shift to small islets. Islet number and volume were also reduced with STZ treatment, but intensity of insulin immunostaining was markedly reduced, and size distribution was minimally altered. Together, these observations validate tissue clearing and 3D imaging as a reliable straightforward method to assess cell volume and other characteristics across the entire pancreas.

Whole-tissue 3D imaging confirmed dense pancreatic innervation and revealed markedly greater nerve density in the endocrine pancreas, over sixfold greater than in the exocrine pancreas of mice. These findings confirm the results of previous studies reporting close association between islets and nerves using 2D histology and 3D examination of pancreatic sections (3, 9, 10). We extended these findings to show that endocrine NF200+ innervation was not uniform throughout the pancreas but enriched in the duodenal portion. These regional differences may reflect the distinct embryological origins of the duodenal and splenic regions. Further studies will determine whether regional differences in pancreatic innervation contribute to reported regional differences in islet composition, size, function, and susceptibility to immune loss.

3D analysis of islets and innervation across the whole pancreas revealed previously unknown features of the close anatomical relationship between islets and nerves. In mice and human samples, innervated islets are a relatively small fraction of all islets by number, but they are, on average, 10-fold larger than noninnervated islets. As a result, innervated islets represent around half of the total cell volume. The large volume of innervated islets is in accordance with a role for neural signals in islet development and maintenance. In both mice and zebrafish, cells aggregate close to pancreatic nerves in development, and islet architecture is disrupted by loss of neural signals (55, 56). There is also close physical association between nerves and islets in human embryos, particularly in the middle and late trimester, when there is rapid development of the endocrine pancreas (55). Less is known about the role of neural signals in cell maintenance, but vagotomy reduces cell replication in rats (57). Vagotomy disrupts the afferent and efferent signals to several intra-abdominal organs, so further studies are needed to determine whether loss of neural signals, specifically to the pancreas, disrupts islet structure and function during development and after birth.

Islets are closely associated with the pancreatic duct and highly vascularized, so it is possible that the proximity between nerves and islets is related to innervation of the duct or vessels. Islet blood vessels are richly innervated, and neural signals have marked effects on islet blood flow (58). However, several studies suggest that vascular signals actually reduce endocrine cell differentiation during development, and in zebrafish, islets remain densely innervated even in the absence of islet vascularization.

Although NF200-innervated islets are large, on average, NF200 immunostaining intensity is greater in smaller innervated islets. NF200 expression has been linked to nerve diameter and conduction velocity, so it is possible that differences in NF200 immunostaining intensity may have functional consequences (29, 30). In human pancreata, small islets have a greater proportion of cells compared to other endocrine cell types and higher insulin content (59). Similarly, small rat islets were functionally superior to larger islets in ex vivo studies and after transplantation (60). In keeping with previous work (3), NF200+ nerves contact a small proportion of cells in each islet, with no proportional differences between pancreatic regions or islet sizes. The proportion of innervated cells is similar to the percentage of cells that are reported to act as hub cells in the islets, and hub cells are reported to be modulated by cholinergic agonists (61). Although a minority of cells contact NF200+ nerves, neural signals could influence activity across multiple cells through electrical coupling. In contrast, and in keeping with previous work (3), NF200+ nerves contact a much greater proportion of cells, which lack gap junctions. Whether variation in NF200 immunostaining intensity or proximity of individual cells to nerves contributes to functional heterogeneity of cells is currently unknown and warrants further studies.

The development of diabetes in NOD mice and in STZ-treated mice is associated with rapid and significant increases in islet nerve density. In NOD mice, increased nerve/islet volume suggests that nerve volume may be preserved, while cell volume is reduced in surviving islets. The proportion of innervated cell clusters increased in diabetic NOD mice. In STZ-treated mice, nerve volume per islet, nerve density per islet, and nerve density in cell clusters are all increased. These findings suggest that increased nerve density is restricted to the remaining insulin+ islets in NOD mice, while both cell and cell nerve density is increased in STZ-treated mice. The increases in insulin+ islet nerve density in diabetic NOD and STZ-treated mice are similar in magnitude to nerve density changes in response to physiologically relevant stimuli. In the CNS, fasting leads to an almost twofold increase in agouti related neuropeptide (AgRP)/neuropeptide Ypositive (NPY+) terminals in the paraventricular nucleus, a major pathway regulating food intake (62). In the peripheral nervous system, skin inflammation increased sensory nerve density twofold and was associated with increased sensitivity to thermal and mechanical stimuli (63). Further studies will be required to test the functional consequences of increased islet nerve density.

The intensity of NF200 immunostaining was significantly increased in the islets of diabetic NOD and STZ-treated mice. NF200 staining intensity increases in response to nerve regeneration (20, 21), so up-regulation of NF200 may reflect ongoing regeneration of islet innervation. These findings, and the time course of the increased nerve density with STZ treatment, are highly suggestive of nerve regeneration; reported rates of nerve regrowth after crush injury are up to 4 mm/day, and restoration of electrical activity in peripheral nerves after chemical injury occurs within days. Our findings may be responses to STZ directly, to hyperglycemia, and to inflammatory processes and/or interactions between endocrine cells and neurons to regulate neural density. Increased nerve density is reported in response to inflammation in several tissues and their adjacent structures, and these changes can either be protective or exacerbate inflammation (64, 65). Increased insulin+ islet nerve density in NOD mice, and the increase in exocrine and endocrine nerve density in STZ-treated mice, may reflect the major sites of immune activity/inflammation. Both hyperglycemia and STZ treatment increase cell production of nerve growth factor (NGF) (66). Its receptor, tyrosine kinase receptor A (TrkA), is expressed on both sympathetic and sensory nerves, and previous 2D imaging studies report that sensory and sympathetic nerve density are increased with STZ treatment (33). In previous studies, NGF overexpression in cells significantly increased sympathetic islet innervation (67). The cross-talk between nerves and islets in healthy versus diabetic tissue remains largely unstudied.

There is considerable variability in the reported changes in cell mass in models of diabetes. In our studies in diabetic NOD mice, cell volume was not significantly higher as a proportion of total pancreatic volume, but the ratio of to cell volumes was significantly increased (Fig. 4, B and C). Similar to our findings, Plesner et al. (68) describe a non-significant increase in cell mass in prediabetic and diabetic NOD mice and a significant increase in the proportion of cells/islet area in diabetic NOD mice. Our longitudinal studies show changes in cell volume with time after STZ treatment, with a significant decrease 2 weeks after the completion of treatment. This is in keeping with previous studies (69), but the cell response to STZ treatment has also been described to increase (70), to remain unchanged (71), or to vary with time after STZ treatment (72).

In our studies, and cell contacts are maintained in diabetic NOD and STZ-treated mice. One limitation of our assessment is that we quantify the number of endocrine cells contacting nerves, but we cannot quantify the number of contacts per endocrine cell. It is possible that the number of contacts with or cells is modified in diabetes. Sympathetic fibers also contact delta cells and vasculature to a lesser extent (3) in mouse islets. Further work is needed to determine whether NF200+ fibers contact delta cells or other islet structures and the effects of diabetes and STZ treatment on these contacts.

Our results examining innervation in NOD mice are consistent with recent 3D imaging of thick pancreatic sections (9, 13) reporting regions with increased innervation in these mice. Prior 2D studies have reported loss of islet sympathetic innervation in NOD mice (35), but these studies used different neural markers and examined NOD mice with longer duration of diabetes. It is possible that the increased islet innervation in NOD mice we observe is lost with increasing duration of diabetes. Alternatively, there may be pathway-specific changes such that sympathetic innervation is reduced, but parasympathetic and/or sensory innervation are increased, leading to an increase in NF200+ innervation found in our studies. Future studies using iDISCO+ will be required to dissect the longitudinal changes and contribution of specific neural pathways in mouse models of T1D, as well as the associations between innervation and immune infiltration.

There are several differences between mouse and human islets as well as similarities between these species. Human cell volume (%) was similar to the proportion of insulin+ islets in C57BL/6 mice. Islet size distribution was also remarkably similar between mouse and human pancreata. Similar to the findings in mice, intrapancreatic ganglia in human tissue are sparse and close to islets, but they are markedly larger, of the order of 200 neurons on average. There have been conflicting results about islet innervation in human versus murine samples. In our studies, the proportion of innervated islets and the finding that innervated islets were larger than noninnervated were similar in both humans and mice. Initial 2D imaging reported reduced islet innervation in human samples, but recent data from optically cleared human samples using markers for sympathetic nerves suggest that human islets, like mouse islets, have a dense neural network (9, 11). In keeping with previous studies examining TH+ fibers in human pancreatic samples (3, 11), innervation density is similar in human exocrine and endocrine pancreas. We found that NF200+ innervation is present in human islets, in keeping with previous studies demonstrating TH+ fibers in islets (3, 11), but at a lower density than mouse islets. A smaller proportion of human cells contact NF200+ fibers compared to mouse islets.

There are also similarities between innervation in STZ-treated mice and in samples from T2D individuals. In pancreata from T2D donors, nerve volume per islet, nerve density, and the proportion of innervated islets are all increased. The human tissue samples we analyzed provide a snapshot of islets and innervation from postfixed tissue as well as from individuals with variable comorbidities, age, and time from death. These factors likely contribute to the sample variability, in line with previous human data (73). In aggregate, our data suggest that islet innervation is present in human islets, albeit at lower levels than mouse islets, and innervation appears to be at least preserved, possibly increased, in human T2D individuals. The increase in exocrine innervation in pancreatic tissue from T2D donors may reflect more generalized pancreatic pathology that is increasingly recognized as a feature of T2D. One limitation of our studies is that we did not examine insulin islets by glucagon staining in the human samples, so it is unknown whether whole islet nerve density or cell contacts are altered in T2D. Further studies examining specific neural pathways and further endocrine cell types in human pancreatic tissue are required to fully assess normo- and pathophysiological species differences.

Our studies using NF200 as a neural marker do not differentiate between parasympathetic, sympathetic, and sensory fibers. Using an optimized iDISCO+ protocol, we examined sympathetic and parasympathetic innervation in wild-type mice, and many findings mirror those seen with NF200+ innervation. Similar to our findings using NF200, both sympathetic and parasympathetic endocrine innervation are enriched compared to exocrine innervation, and innervated islets are significantly larger than noninnervated islets. These findings differ from published studies that show similar TH+ innervation density in exocrine and endocrine tissue (74). However, previous reports analyzed innervation in female mice sampling cryosections every 400 m rather than innervation across the whole pancreas. The proportion of innervated-to-noninnervated islets is also greater when assessed using sympathetic and parasympathetic markers. The distribution of TH+ and VAChT+ innervation differs, with several large volume TH+ fibers contributing to higher TH+ volume compared to VAChT+ innervation in the exocrine pancreas. In keeping with previous reports in adult mice (75, 76), we observed occasional TH+ cells. We excluded these, as far as possible, based on their morphology, volume, and overlap with insulin immunostaining, but it is conceivable that our estimate of TH+ innervation may be an overestimate. TH+ and VAChT+ endocrine innervation are higher than for NF200. However, while NF200 has been reported to be expressed in a wide range of myelinated and unmyelinated fibers, our results and previous studies suggest that NF200 does not label all fibers (19), and it is possible that we may have overlooked alterations in NF200 fibers in our studies. Alternative pan-neuronal markers have significant limitations. For example, protein gene product 9.5 (PGP9.5) is expressed in islet endocrine cells and innervation. Pathway-specific markers are also imperfect. TH labels most, but not all, sympathetic nerve fibers since there are also populations that are TH but express NPY (77). VAChT immunostaining is primarily in the terminal neuronal arborization and so visualizing larger cholinergic nerve fibers may be incomplete (78). While there are similarities among innervation patterns with NF200, TH, and VAChT, our studies do not allow us to determine whether the changes in pancreatic innervation with diabetes are generalized or specific to sympathetic, parasympathetic, or sensory pathways. Future work will assess important pathway-specific changes in pancreatic innervation and their contacts with specific endocrine cell types in both mouse and human metabolic disease. One disadvantage of iDISCO+ is that it does not preserve endogenous fluorescence. Therefore, we also developed and validated a novel alternative approach that combines immunostaining and tissue clearing with ECi for use in adult murine tissues (41). This preserves endogenous fluorescent signals while allowing for antibody labeling of additional targets. ECi clearing also provides a less toxic alternative to iDISCO+ (41). A combination of fluorescently tagged dextran to delineate blood vessels, immunostaining for innervation and islets, and ECi tissue clearing will allow us to further assess the organ-wide association between innervation, islets, and vasculature.

In summary, we have used whole-organ tissue clearing and imaging to create a 3D atlas mapping islets and innervation across the pancreas as a tool to quantify cell mass, define islet characteristics, map pancreatic innervation, and assess the anatomical interaction between islets and innervation in healthy and diabetic mice and humans. This approach demonstrates dense islet innervation and identifies distinguishing features of innervated islets and the regional differences. Such regional variations illustrate the importance of whole-organ imaging when assessing pancreatic anatomy. Our studies confirm that innervation is present in human islets and directly contacts cells. We demonstrate that islet innervation is markedly increased in diabetic NOD mice, STZ-treated mice, and likely in diabetic human pancreata. In combination with up-regulation of NF200 immunostaining, this suggests increased rapid reorganization of pancreatic innervation and possible nerve growth within islets. Future studies will identify the neurochemical characteristics, time course, and functional consequences of these changes. Intrapancreatic ganglia and nerve contacts in islets are maintained in diabetes. The tissue clearing and imaging approaches we have used and optimized are broadly applicable to investigating pancreatic structures and innervation in other diseases, such as pancreatitis and pancreatic cancer, and are relevant to imaging vasculature and innervation in other organs. Our data also have important translational implications. Our data suggest that the close association between islets and pancreatic nerves is maintained in human T2D; therefore, the anatomical pathways that would allow for targeted neuromodulation to regulate pancreatic function are preserved. Defining pancreatic neurocircuitry is crucial to understanding neural regulation of pancreatic function, as it elucidates anatomical pathways for direct effects on endocrine cells. Future studies will determine critical interactions between cells and nerves, whether variation in islet innervation density is associated with differences in islet function, and whether metabolic disease leads to functional deficits in islet innervation independent of structure.

Ad libitum fed C57BL/6 mice were maintained under controlled conditions (12-hour light/12-hour dark cycle, 22C). NOD mice (NOD/ShiLtJ, the Jackson Laboratory, Bar Harbor, ME, USA) and STZ-treated mice were used to model T1D. Female NOD mice aged 12 to 16 weeks with two consecutive blood glucose measurements of >300 mg/dl (morning, nonfasting) were termed diabetic. Littermates with blood glucose <200 mg/dl were used as nondiabetic controls. Multiple low-dose STZ-treated mice (males, aged 10 weeks) were generated by treating C57BL/6N mice (Charles River, Wilmington, MA, USA) intraperitoneally with freshly made STZ (40 mg/kg; Sigma-Aldrich, St. Louis, MO) in citrate-saline buffer (pH 4.5) for five consecutive days and euthanizing them at 5 or 15 days following the final STZ injection. NonSTZ-treated littermates were used as controls. All protocols were approved by the Institutional Animal Care and Use Committee.

Mice were anesthetized with isoflurane (3%) and perfused with heparinized saline followed by 4% paraformaldehyde (PFA; Electron Microscopy Sciences, Hatfield, PA, USA). Pancreata were dissected, cleared of adipose tissue, divided into duodenal and splenic regions (Fig. 1A), with the gastric lobe included with the duodenal lobe, and postfixed overnight in 4% PFA at 4C. For antibody evaluation experiments, small pancreatic samples (2 to 3 mm diameter) were assessed. On the following day, the tissue was washed in phosphate-buffered saline (PBS; 3) before proceeding with optical clearing protocols.

Human samples (Table 1) were obtained from Prodo Laboratories Inc. (Aliso Viejo, CA, USA) and postfixed in 4% PFA. Since human samples were processed upon acquisition and not simultaneously as with mouse tissue, we could not compare staining intensity between samples. All samples were harvested from the superior margin of the tail of the pancreas.

Whole-organ staining and clearing were performed using iDISCO+ (15). Dissected pancreata were dehydrated [20, 40, 60, 80, and 100% methanol at room temperature (RT)], delipidated [100% dichloromethane (DCM; Sigma-Aldrich, St. Louis, MO, USA)], and bleached in 5% H2O2 (overnight, 4C). Pancreata were rehydrated (80, 60, 40, and 20% methanol) and permeabilized [5% dimethyl sulfoxide/0.3 M glycine/0.1% Triton X-100/0.05% Tween-20/0.0002% heparin/0.02% NaN3 in PBS (PTxwH)] for 1 day. Pancreata were then placed in blocking buffer [PTxwH + 3% normal donkey serum (Jackson ImmunoResearch, West Grove, PA, USA)] at 37C overnight. Samples were incubated with primary antibodies (table S1) in blocking buffer for 3 or 6 days (small pancreatic pieces and hemipancreata, respectively) at 37C. After five washes with PTxwH at RT (final wash overnight), samples were incubated with secondary antibodies in blocking buffer (1:500) for 3 or 6 days. Samples were washed with PTxwH (five times, RT) and PBS (five times, RT), dehydrated with a methanol gradient, then washed in 100% methanol (three times, 30 min each) and DCM (three times, 30 min each), and then transferred to dibenzyl ether (DBE; Sigma-Aldrich) to clear. Primary antibody specificity was confirmed in pancreatic tissue from reporter mice expressing tdTomato in defined neural populations. There was no immunolabeling without primary antibodies using iDISCO+ or ECi. A modified iDISCO+ protocol used 0.5% Triton X-100 and 0.1% Tween-20 for the permeabilization, blocking, and primary and secondary antibody buffers.

A modified ECi tissue clearing protocol was used for samples from animals injected intravenously with fluorophore-tagged dextran (100 m, 25 mg/ml) or a direct conjugated CD31 antibody (100 m, 50 mg/ml). Tissue was harvested, postfixed, and washed with PBS as described above. Samples were incubated with 3% H2O2 (10 min, RT), washed in PBS with 0.2% Triton X-100 (Ptx2; three times over 3 h, RT), and incubated overnight in PTx2 + heparin (10 mg/ml; PTwH) and 3% normal donkey serum at RT. Samples were incubated with primary antibodies in PTwH with 3% normal donkey serum (2 days, RT) followed by PTwH washes (four times over 4 hours). Samples were incubated with secondary antibodies in PTwH with 3% normal donkey serum (2 days, RT), followed by PTwH washes as above. Optical clearing was achieved by incubating samples in 50% ethanol, 70% ethanol, 100% ethanol (all pH 9, 4 hours, 4C), 100% ethanol (pH 9, overnight, 4C), and finally one wash and one overnight incubation (RT) in ECi (Sigma-Aldrich) before imaging.

Z-stacked optical sections were acquired with an UltraMicroscope II (LaVision BioTec, Bielefeld, Germany; 1.3, 4, or 12 magnification with dynamic focus with a maximum projection filter). Human samples were imaged at 1.3 with dynamic focus and with multiple Z-stacks acquired at 4 with 20% overlap and tiled using the plugin TeraStitcher through the ImSpector Pro software (LaVision BioTec). Spatial resolutions of light-sheet images were 5 m by 5 m by 5 m at 1.3, 1.63 m by 1.63 m by 5 m at 4, and 0.602 m by 0.602 m by 2 m at 12.

Small mouse pancreatic sections were imaged in glass-bottom eight-well chambers (Ibidi, Grfelfing, Germany) filled with immersion media DBE or ECi and imaged using an inverted Zeiss LSM 880 confocal microscope with a 10 [numerical aperture (NA), 0.3] objective and a step size of 5 m. Spatial resolution for confocal images acquired at 10 was 1.67 m by 1.67 m by 5 m.

Imaris versions 9.1 to 9.3.1 (Bitplane AG, Zrich, Switzerland) were used to create digital surfaces covering the islets (1.3 and 4 images) and innervation (4 images) to automatically determine volumes and intensity data. Volume reconstructions were performed using the surface function with local contrast background subtraction. For detection of islets, the threshold factor corresponded to the largest islet diameter in each sample. For detection of nerves, the threshold factor was set to 12.2 m. A smoothing factor of 10 m was used for islets analyzed at 1.3, and a factor of 3.25 m was used for analysis of islets and nerves at 4. For detection of TH+ nerves, TH+ cells (75, 76) were manually removed from the final TH+ nerve surface by excluding volumes below 120 m3 residing within insulin+ islets and overlapping with insulin staining. The Imaris Distance Transform Matlab XTension function was used to calculate the distance of each islet surface from the innervation surface. Distances of islets are reported as the intensity minimum of the distance transformation channel (intensity 0 = islet touching nerve) for each islet surface to the nerve surface as calculated by the distance transformation operation. In confocal images, digital surfaces were created to cover nerves and individual cells, cells, or ganglia. For detection of ganglia, a region of interest was manually created around each individual ganglion to create a digital surface specifically covering cell bodies, but not nerve fibers. The Imaris Distance Transform Matlab XTension was then used as above to determine the distance between ganglia and insulin+ islets or the distance between nerves and individual or cells with a distance of 0 indicating a nerve contact. Limitations to our analyses of endocrine cell contacts include the following: We may not have captured / cells with lower staining intensity; in some cases, we could not completely separate adjacent endocrine cells and therefore counted multiple adjacent cells as a single cell; our method quantifies the number of endocrine cells contacting nerves but does not allow for quantification of number of contacts per endocrine cell.

Data are shown as means SEM. Distribution was assessed by Shapiro-Wilk test. Significance was determined by unpaired two-way t test or one-way analysis of variance (ANOVA) with post hoc Tukeys multiple comparisons test (Gaussian distribution), Mann-Whitney test, or Kruskal-Wallis test followed by Dunns multiple comparisons test (nonparametric distribution). Significance was set at an level of 0.05.

Acknowledgments: Funding: A.A. was supported by a senior postdoctoral fellowship from the Charles H. Revson Foundation (grant no. 18-25) and a postdoctoral scholarship from the Swedish Society for Medical Research (SSMF). This work was supported by the American Diabetes Association Pathway to Stop Diabetes Grant ADA #1-17-ACE-31 and, in part, by grants from the NIH (DK105015, P-30 DK020541, U01MH105941, R01NS097184, OT2OD024912, and UC4DK104211), JDRF (2-SRA-2017-514-S-B), and the Alexander and Alexandrine Sinsheimer Scholar Award. This work was supported in part by a Mindich Child Health and Development Institute Pilot and Feasibility Grant. Microscopy and image analysis were performed at the Microscopy CoRE at the Icahn School of Medicine at Mount Sinai. We wish to thank the Human Islet and Adenoviral Core (HIAC) of the NIDDK-supported Einstein-Sinai Diabetes Research Center (DRC) and the families of the donors. Author contributions: A.A., A.G.-O., A.F.S., and S.A.S. conceived and designed the study and interpreted the data. A.A. performed all light-sheet experiments and analyzed and interpreted the data. A.A., M.J.-G., and R.L. performed confocal experiments and analyzed and interpreted the data. C.R., M.J.-G., and A.A. provided STZ-treated mice. C.R. and A.G.-O. provided NOD mice and human samples. N.T. and Z.W. provided technical and methodological input. A.A. and S.A.S. drafted the manuscript with input from all other authors. All authors approved of the final submitted version of this paper. Competing interests: S.A.S. is a named inventor of the intellectual property, Compositions and Methods to Modulate Cell Activity, and is a co-founder of, consults for, and has equity in the private company Redpin Therapeutics (preclinical stage gene therapy company developing neuromodulation technologies). The authors declare that they have no other competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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A 3D atlas of the dynamic and regional variation of pancreatic innervation in diabetes - Science Advances

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Pets of the week: A young cat with a brother, and a kissy cat with diabetes – Duluth News Tribune

Saturday, October 10th, 2020

Watson and his brother Sherlock Holmes found themselves at Helping PAWS Pet Rescue in Washburn because they weren't getting good care at their previous home. Watson is a super friendly cat who really like people. He even likes to hug them. He has a mellow nature but also likes to play, as he's on the younger side. Watson would love a home with a cat friend, or with his brother.

Rolly is an orange tiger-and-white domestic short hair cat who is about 9 years old. He found himself at Animal Allies after his previous home could no longer care for him. Rolly is sweet, easygoing and loving, looking to receive endless love and attention. He enjoys giving hugs and even kisses from time to time. Because he has diabetes, he has been around at the shelter for awhile and is ready for a permanent home.

To adopt a cat or dog in the Northland, call:

Animal Allies, Duluth, 218-722-5341, animalallies.net.

Chequamegon Humane Association, Ashland, 715-682-9744, chaadopt.org.

Contented Critters Shelter, Makinen, 218-638-2153, contentedcritters.org.

Helping PAWS Pet Rescue, Inc., 715-373-2222, helpingpawswi.org.

Humane Society of Douglas County, Superior, 715-398-6784, hsdcpets.com.

Mesabi Humane Society, Virginia, 218-741-7425, mesabihumanesociety.org.

Northern Lights Animal Rescue, 218-729-1485, adoptapet.com/adoption_rescue/66719-northern-lights-animal-rescuers-inc-twig-minnesota.

Oreos Kitty Sanctuary, 218-591-7200, email oreosadoptions@yahoo.com.

Precious Paws Humane Society of Chisholm, 218-254-3300, preciouspaws2011@hotmail.com or pphsc.com.

Range Regional Rescue in Hibbing, 218-262-1900.

Star of the North Humane Society, Itasca County, 218-245-3732, starnorth.weebly.com/about-us.html.

Warm Fuzzies Animal Rescue Inc., Warmfuzzies2020@gmail.com, 218-576-8534, warmfuzzies.petfinder.com

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Pets of the week: A young cat with a brother, and a kissy cat with diabetes - Duluth News Tribune

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Tandem Diabetes Care to Announce Third Quarter 2020 Financial Results on November 5, 2020 – Business Wire

Saturday, October 10th, 2020

SAN DIEGO--(BUSINESS WIRE)--Tandem Diabetes Care, Inc. (NASDAQ: TNDM), a leading insulin delivery and diabetes technology company, plans to release its third quarter 2020 results after the financial markets close on Thursday, November 5, 2020. The Company will hold a conference call and simultaneous webcast on the same day at 4:30 pm Eastern Time (1:30 pm Pacific Time), to discuss its third quarter 2020 financial and operating results.

Conference Call/Webcast Details:Date: November 5, 2020Time: 4:30 pm Eastern Time (1:30 pm Pacific Time)Toll Free Dial-In Number: (855) 427-4396International Dial-In Number: (484) 756-4261Conference ID: 8072078Webcast Link: https://edge.media-server.com/mmc/p/mp7mdi2q

An archive of the webcast will be available for 30 days following the event on Tandem Diabetes Cares Investor Center website located at http://investor.tandemdiabetes.com in the Events & Presentations section.

About Tandem Diabetes Care, Inc.

Tandem Diabetes Care, Inc. (www.tandemdiabetes.com) is a medical device company dedicated to improving the lives of people with diabetes through relentless innovation and revolutionary customer experience. The Company takes an innovative, user-centric approach to the design, development and commercialization of products for people with diabetes who use insulin. Tandems flagship product, the t:slim X2 insulin pump, is capable of remote software updates using a personal computer and features integrated continuous glucose monitoring, and optional automated insulin delivery technology. Tandem is based in San Diego, California.

Follow Tandem Diabetes Care on Twitter @tandemdiabetes, use #tslimX2 and $TNDM.Follow Tandem Diabetes Care on Facebook at http://www.facebook.com/TandemDiabetes.Follow Tandem Diabetes Care on LinkedIn at http://www.linkedin.com/company/TandemDiabetes.

Tandem Diabetes Care is a registered trademark and t:slim X2 is a trademark of Tandem Diabetes Care, Inc.

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Tandem Diabetes Care to Announce Third Quarter 2020 Financial Results on November 5, 2020 - Business Wire

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Diabetes Night at the Drive-In in Idaho Falls – Idaho Falls Magazine

Saturday, October 10th, 2020

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Lilly and Dexcom team up on new program to help improve diabetes management – PRNewswire

Saturday, October 10th, 2020

INDIANAPOLIS and SAN DIEGO, Oct. 7, 2020 /PRNewswire/ --Eli Lilly and Company (NYSE: LLY) and DexCom, Inc. (NASDAQ: DXCM) announced today a joint program for U.S. healthcare providers (HCPs) about Lilly's new rapid-acting mealtime insulin Lyumjev (insulin lispro-aabc injection, 100 units/mL and 200 units/mL), now available in U.S. pharmacies, and Dexcom G6 CGM Systems. The program is designed to help clinicians use data to inform diabetes management, including giving visibility to the benefits of a new mealtime insulin.

HCPs treating type 1 and type 2 diabetes will be able to assess their patients' glucose levels and time in range with Dexcom G6 or Dexcom G6 Pro, either in blinded or unblinded mode, helping them quickly identify adult patients who struggle to manage their postprandial glucose (PPG) levels (glucose levels following meals) and who may benefit from a treatment like Lyumjev. As PPG is often overlooked as a significant contributor to A1C,1 this partnership also aims to elevate PPG monitoring as an important component of diabetes treatment management.

"When it comes to treating diabetes, our partnership with Dexcom has the potential to be meaningful for HCPs who want to help their patients who may be struggling to manage their blood glucose levels after meals," said Adrienne Brown, vice president, U.S. Diabetes and Connected Care, Lilly. "Through this program, we can inspire confidence as clinicians and their patients evaluate new treatment options by showcasing how using these resources together can inform diabetes care."

Lilly and Dexcom will enhance HCP education by jointly sharing information about Lyumjev and the Dexcom G6 and G6 Pro through a variety of channels.

"We are thrilled to partner once again with a leader in diabetes care like Lilly," said Rick Doubleday, chief commercial officer at Dexcom. "Our goal is that the real-time data provided through Dexcom G6 and Dexcom G6 Pro will allow healthcare providers to help their patients with diabetes make more informed decisions, measure and evaluate their time in range, and have more visibility to the potential benefits of transitioning to a new mealtime insulin such as Lyumjev."

Those interested in learning more about Dexcom CGM or getting started on the Dexcom G6 should visit Dexcom.com. The Dexcom G6 is covered by 98 percent of private insurance in the U.S., by Medicare and by Medicaid in many states across the country. Dexcom also recently launched a patient assistance programavailable to currentU.S.customers who lost their health insurance coverage due to the impacts of COVID-19.

Lyumjev is a novel formulation of insulin lispro, developed to speed the absorption of insulin into the bloodstream and reduce A1C levels in adults with diabetes. In clinical studies, Lyumjev provided superior reduction in blood sugar spikes compared with Humalog (insulin lispro injection) when blood sugar was measured 1 and 2 hours after a meal. Lyumjev was approved by the FDA on June 15, 2020. HCPs can now prescribe Lyumjev, which is available for pharmacies nationwide to order. People who have commercial insurance can visit http://www.Lyumjev.com to access the Lyumjev Savings Card. For people without insurance coverage, Lyumjev is also included in the Lilly Insulin Value Program for $35 by calling the Lilly Diabetes Solution Center at (833) 808-1234. Operators at the Solution Center are available Monday through Friday from 8 a.m. to 8 p.m. (ET). Lilly is in discussions with insurance providers to make the new rapid-acting insulin available to as many people as possible.

People with diabetes and their HCPs who have questions about Lyumjev can visit http://www.Lyumjev.com or call The Lilly Answers Center at 1-800-LillyRx (1-800-545-5979), Monday through Friday from 9 a.m. to 8 p.m. ET.

Terms, conditions, and limitations apply to Lilly savings cards and the Dexcom patient assistance program. See the companies' respective websites for additional details. The Lilly savings card is not available to those patients with government insurance such as Medicaid, Medicare, Medicare Part D, TRICARE/CHAMPUS, Medigap, DoD, or any State Patient or Pharmaceutical Assistance Program. TRICARE is a registered trademark of the Department of Defense (DoD), DHA.

PURPOSE and SAFETY SUMMARY

Important Facts About LYUMJEV (LOOM-jehv) and Humalog (HU-ma-log)

All Lyumjev and Humalog products contain insulin lispro.

Warnings

Do not take Lyumjev or Humalog if you have:

Do not reuse needles or share your insulin injection supplies with other people. This includes your:

You or the other person can get a serious infection. This can happen even if you change the needle.

Do notchange the type of insulin you take or your dose, unless your doctor tells you to. This could cause low or high blood sugar, which could be serious.

Do notuse a syringe to remove Lyumjev or Humalog from your prefilled pen. This can cause you to take too much insulin. Taking too much insulin can lead to severe low blood sugar. This may result in seizures or death.

Lyumjev and Humalog may cause serious side effects. Some of these can lead to death.The possible serious side effects are:

dizziness or lightheadedness

sweating

confusion

headache

blurred vision

slurred speech

shakiness

fast heartbeat

anxiety

irritability

mood change

hunger

If you are at risk of having severely low blood sugar, your doctor may prescribe a glucagon emergency kit. These are used when your blood sugar becomes too low and you are unable to take sugar by mouth. Glucagon helps your body release sugar into your bloodstream.

a rash over your whole body

trouble breathing

a fast heartbeat

sweating

a faint feeling

shortness of breath

extreme drowsiness

dizziness

confusion

swelling of your face, tongue, or throat

Common side effects

The most common side effects of Lyumjev andHumalog are:

low blood sugar

allergic reactions

reactions where you have injected insulin

skin thickening or pits at the injection

site

itching

weight gain

rash

Other most common side effects with Humalog include swelling of your hands or feet.

These are not all of the possible side effects. Tell your doctor if you have any side effects. You can report side effects at 1-800-FDA-1088 or http://www.fda.gov/medwatch.

Before using

Talk with your doctor about low blood sugar and how to manage it. Also tell your doctor:

How to take

Read the Instructions for Use that come with your Lyumjev or Humalog. Be sure to take your Lyumjev or Humalog and check your blood sugar levels exactly as your doctor tells you to. Your doctor may tell you to change your dose because of illness, increased stress, or changes in your weight, diet, or physical activity level. He or she may also tell you to change the amount or time of your dose because of other medicines or different types of insulin you take.

Before injecting your Lyumjev or Humalog

You can inject your insulin dose yourself, or you can have a trained caregiver inject it for you. Make sure you or your caregiver:

When you are ready to inject

Staying safe while taking your Lyumjev or Humalog

To stay safe while taking your insulin, be sure to never inject Lyumjev U-200 in your vein, muscle, or with an insulin pump. Also be sure not to:

Learn more

For more information, call 1-800-545-5979 or go to http://www.Lyumjev.com or http://www.humalog.com

Thissummaryprovidesbasic information about Lyumjev and Humalog. It does not include all information known about these medicines. Read the information that comes with your prescription each time your prescription is filled. This information does not take the place of talking with your doctor. Be sure to talk to your doctor or other health care provider about your insulin lispro product and how to take it. Your doctor is the best person to help you decide if these medicines are right for you.

Please see Lyumjev Full Prescribing Informationincluding Patient Prescribing Information

Please see Humalog Full Prescribing Informationincluding Patient Prescribing Information

LyumjevTM is a trademark and Humalogis a registeredtrademark owned or licensed by Eli Lilly and Company, its subsidiaries, or affiliates.

UR HI CON BS 15JUN2020

About Diabetes

Approximately 34 million Americans2 (just over 1 in 10) and an estimated 463 million adults worldwide3 have diabetes. Type 2 diabetes is the most common type internationally, accounting for an estimated 90 to 95 percent of all diabetes cases in the United States alone1. Diabetes is a chronic disease that occurs when the body does not properly produce or use the hormone insulin.

About Dexcom CGMThe Dexcom G6 provides data-driven insights that are designed to allow people with diabetes to improve their insulin therapy and condition management. Dexcom G6 capabilities include continuous glucose readings, the elimination of routine fingersticks,* proactive and predictive alerts and alarms, remote glucose monitoring and more. The G6 Pro is also the first and only single use, professional CGM available in blinded and unblinded mode that allows healthcare providers to view data about a patient's glucose patterns over a single 10-day period. Through Dexcom CLARITY a diabetes management application offered for both patients and physicians HCPs can access data remotely, regardless of whether their patients are using the personal or professional version of G6.

About DexCom Inc.

DexCom, Inc. empowers people to take control of diabetes through innovative continuous glucose monitoring (CGM) products. Headquartered in San Diego, California, Dexcom has emerged as a leader of diabetes care technology. By listening to the needs of patients, caregivers, and clinicians, Dexcom simplifies and improves diabetes management around the world.

About Lilly Diabetes

Lilly has been a global leader in diabetes care since 1923, when we introduced the world's first commercial insulin. Today we are building upon this heritage by working to meet the diverse needs of people with diabetes and those who care for them. Through research, collaboration and quality manufacturing we strive to make life better for people affected by diabetes and related conditions. We work to deliver breakthrough outcomes through innovative solutionsfrom medicines and technologies to support programs and more. For the latest updates, visit http://www.lillydiabetes.com/or follow us on Twitter: @LillyDiabetesand Facebook: LillyDiabetesUS.

About Eli Lilly and Company

Lilly is a global healthcare leader that unites caring with discovery to create medicines that make life better for people around the world. We were founded more than a century ago by a man committed to creating high-quality medicines that meet real needs, and today we remain true to that mission in all our work. Across the globe, Lilly employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to communities through philanthropy and volunteerism. To learn more about Lilly, please visit us at lilly.comand lilly.com/newsroom. P-LLY

*If your glucose alerts and readings from the G6 do not match symptoms or expectations, use a blood glucose meter to make diabetes treatment decisions.

Separate Follow app required.

2020 Dexcom, Inc. Dexcom, Dexcom G6 and Dexcom Follow are registered trademarks of Dexcom, Inc. in the U.S., and may be registered in other countries. All rights reserved.

This press release contains forward-looking statements(as that term is defined in the Private Securities Litigation Reform Act of 1995)aboutLyumjev (insulin lispro-aabc injection) as a treatment to improve glycemic control in adults with type 1 and type 2 diabetes, and a joint program between Eli Lilly and Company and DexCom, Inc. designed to help U.S. healthcare providers use data to inform diabetes management and reflects Lilly's current beliefs. However, as with any pharmaceutical product or medical device, there are substantial risks and uncertainties in the process of development and commercialization. Among other things, there is no guarantee that Lyumjevwill be commercially successful or receive additional regulatory approvals. For further discussion of these and other risks and uncertainties, see Lilly's most recent Form 10-K and Form 10-Q filings with the United States Securities and Exchange Commission. Except as required by law, Lilly undertakes no duty to update forward-looking statements to reflect events after the date of this release.

PP-UR-US-0211 10/2020Lilly USA, LLC 2020. All rights reserved.

References

1. Hershon, K., Hirsh, B., and Odugbesan, O. Importance of Postprandial Glucose in Relation to A1C and Cardiovascular Disease. Clinical Diabetes. 2019; 37 (3): 250-269. Available at: https://clinical.diabetesjournals.org/content/37/3/250.article-info2. Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2020. Atlanta, GA: Centers for Disease Control and Prevention, U.S. Dept. of Health and Human Services; 2020. 3. International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels, Belgium: International Diabetes Federation, 2019. Available at: http://diabetesatlas.org.

SOURCE Eli Lilly and Company

http://www.lilly.com

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Lilly and Dexcom team up on new program to help improve diabetes management - PRNewswire

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What We’re Reading: Nobel Prize in Chemistry Awarded; Improving Diabetes Management; COVID-19 Vaccine Trial Still on Hold – AJMC.com Managed Markets…

Saturday, October 10th, 2020

Two women are awarded the Nobel Prize in Chemistry for CRISPR; Eli Lilly partners with DexCom, Inc; the US arm of AstraZenecas coronavirus disease 2019 (COVID-19) vaccine trial remains halted.

Jennifer A. Doudna, PhD, University of California, Berkeley, and Emmanuelle Charpentier, PhD, Max Planck Institute for Infection Biology, have been awarded the Nobel Prize in Chemistry for their discovery of CRISPR gene editing technology. CRISPR involves removing problematic DNA through the use of RNA as its guide molecule and replacing it, if necessary, with healthy DNA. Diseases that hope to be cured with CRISPR genetic therapies include hemophilia, type 1 diabetes, and Rett syndrome. A patent dispute is ongoing, however, for CRISPR, between Doudna and Charpentier and Feng Zhang, PhD, Broad Institute, who many believe also deserves credit for his work in this space.

The new program aims to enhance the ability of health care providers to better manage their patients with type 1 or 2 diabetes, according to the press release from Eli Lilly, through the use of the Dexcom G6 or Dexcom G6 Pro continuous glucose monitoring system. A main focus of this joint effort between Eli Lilly and DexCom is management of postprandial glucose levels (that following meals), which the release calls a significant contributor to A1C [glycated hemoglobin], for which Lillys new rapid-acting mealtime insulin, Lyumjev (insulin lispro-aabc) is now available. Most private insurance companies, as well as Medicare and Medicaid in many states, cover the Dexcom G6.

The phase 3 coronavirus disease 2019 (COVID-19) vaccine trial, jointly led by AstraZeneca and Oxford University, which was first halted in early September, remains on hold, but only in the United States, reported STAT. Patients have so far only received their first dose of the potential vaccine (or a saline placebo) through the double-blinded trial; a booster shot was supposed to be administered 4 weeks later, but the trial timeline is still unclear so that has not happened as of yet. AstraZeneca has not commented on how it will handle the participants who cant get their second dose, although data on everyone who has been administered at least the first dose will be included in the full analysis set.

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What We're Reading: Nobel Prize in Chemistry Awarded; Improving Diabetes Management; COVID-19 Vaccine Trial Still on Hold - AJMC.com Managed Markets...

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NIH funds first nationwide network to study rare forms of diabetes – National Institutes of Health

Friday, October 2nd, 2020

News Release

Wednesday, September 30, 2020

A nationwide study funded by the National Institutes of Health will seek to discover the cause of several unusual forms of diabetes. For years, doctors and researchers have been stymied by cases of diabetes that differ from known types. Through research efforts at 20 U.S. research institutions, the study aims to discover new forms of diabetes, understand what makes them different, and identify their causes.

The Rare and Atypical Diabetes Network, or RADIANT, plans to screen about 2,000 people with unknown or atypical forms of diabetes that do not fit the common features of type 1 and type 2 diabetes.

A person with atypical diabetes may be diagnosed and treated for type 1 or type 2 diabetes, but not have a history or signs consistent with their diagnosis. For example, they may be diagnosed and treated for type 2 diabetes but may not have any of the typical risk factors for this diagnosis, such as being overweight, having a family history of diabetes, or being diagnosed as an adult. Alternately, a person with atypical diabetes may respond differently than expected to the standard diabetes treatments.

Its extremely frustrating for people with atypical diabetes when their diabetes seems so different and difficult to manage, said the studys project scientist, Dr. Christine Lee of NIHs National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Through RADIANT, we want to help patients and the broader healthcare community by finding and studying new types of diabetes to shed light on how and why diabetes can vary so greatly.

RADIANT researchers will build a comprehensive resource of genetic, clinical, and descriptive data on previously unidentified forms of diabetes for the scientific and healthcare communities.

The studys researchers will collect detailed health information using questionnaires, physical exams, genetic sequencing, blood samples, and other tests. People found to have unknown forms of diabetes may receive additional testing. Some participant family members may also be invited to take part in the study.

With help from participants and their families, we aim to develop a comprehensive description of the genetic and clinical characteristics of these rare forms of diabetes, said study chair, Dr. Jeffrey Krischer, director of the Health Informatics Institute at the University of South Florida (USF), Tampa. This information could help to establish new diagnostic criteria for diabetes, find new markers for screening, or identify drug targets for new therapies that could ultimately bring precision medicine to diabetes.

USF is the studys coordinating center, and the lead centers include Baylor College of Medicine in Houston and the University of Chicago. The Broad Institute in Cambridge, Massachusetts, and Baylor serve as the genomic sequencing centers for the project. University of Florida, Gainesville, provides the studys laboratory services. Other participating centers are:

The RADIANT study will further clarify diabetes as a disease that has many different forms, and for which diagnosis and management for some of those forms remain a challenge, said NIDDK Director Dr. Griffin P. Rodgers. The discoveries of the study should provide critical understanding of the spectrum of diabetes and improve lives of people with rare forms of diabetes and everyone who cares for them.

The study opened recruitment on September 30, 2020 for people with atypical diabetes or a form of diabetes that seems different from known types of diabetes. Visit http://www.atypicaldiabetesnetwork.org for more information on the study and how to join.

Support for the study is provided through NIDDK grants U54DK118638 and U54DK118612.

The NIDDK, a component of the NIH, conducts and supports research on diabetes and other endocrine and metabolic diseases; digestive diseases, nutrition and obesity; and kidney, urologic and hematologic diseases. Spanning the full spectrum of medicine and afflicting people of all ages and ethnic groups, these diseases encompass some of the most common, severe and disabling conditions affecting Americans. For more information about the NIDDK and its programs, see https://www.niddk.nih.gov/.

About the National Institutes of Health (NIH):NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit http://www.nih.gov.

NIHTurning Discovery Into Health

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Why people with diabetes are being hit so hard by Covid-19 – STAT

Friday, October 2nd, 2020

Some of Mary-Elizabeth Pattis patients with diabetes are in a bind. Careful to practice social distancing, they tell her during telehealth visits they dont feel safe exercising outdoors in their congested neighborhoods though they know staying active and maintaining good blood sugar levels may be their best defense against severe Covid-19.

Im always happy when patients say, yes, Im not going out, Im wearing a mask, Im doing as much as I can. But it makes it harder for people to meet their fitness goal, which is such a critical element of overall health and metabolic health, said Patti, an adult endocrinologist at Joslin Diabetes Center in Boston. It underscores the health inequity problem, she added: Their exposures may be increased due to living in a densely populated neighborhood with multigenerational families [and] more essential workers who cannot work from home.

There are no easy answers to the coronavirus pandemic, but for people with diabetes, its dismayingly difficult to untangle the thicket of biological and socioeconomic factors that make them more likely to suffer severe illness and die should they catch the virus that causes Covid-19. That leaves prevention controlling blood sugar through diet, exercise, monitoring, and medication as the leading tactic to protect people, until a successful vaccine proven to work in people with diabetes, too, reaches a population bearing multiple burdens of chronic illness.

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The numbers are alarming. A Lancet Diabetes & Endocrinology study mining 61 million medical records in the U.K. says 30% of Covid-19 deaths occurred in people with diabetes. After accounting for potentially relevant risk factors such as social deprivation, ethnicity, and other chronic medical conditions, the risk of dying from Covid-19 was still almost three times higher for people with type 1 diabetes and almost twice as high for type 2, versus those without diabetes.

Data from the U.S. Centers for Disease Control and Prevention show more than three-quarters of people who died from Covid-19 had at least one preexisting condition. Overall, diabetes was noted as an underlying condition for approximately 4 in 10 patients. Among people younger than 65 who died from the infection, about half had diabetes.

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Juliana Chan, director of the Hong Kong Institute of Diabetes and Obesity, said the pandemic has intertwined with and exposed two other widespread problems: diabetes and disparities triggered by social determinants of health.

What we are seeing is nothing new, but it is really just on a massive and global scale, she said in an interview. I hope that there is something positive out of this, that people understand that we are hit by three epidemics.

While urging prevention as the first and best course, doctors and scientists are testing hypotheses to understand the biology behind the collision of a new infectious disease with an old metabolic one. The exact molecular mechanisms make for an emerging story, and there is disagreement about why, as case reports from around the world suggest, some people develop type 1 diabetes after their coronavirus infection clears. But clinicians and scientists told STAT there is no question that unless people with diabetes have their glucose under control, Covid-19 poses much more danger to them than to other people.

In people with type 1 diabetes, the insulin-producing pancreatic islet cells have been destroyed, meaning they cannot process the glucose their bodies need for fuel and the sugar accumulates in the blood. In type 2 diabetes, people cant make enough insulin to convert glucose into energy, or they grow insensitive to the insulin they do make.

Over a lifetime, problems with too much or too little glucose inflict widespread damage in the kidney, heart, and liver, as well as around nerves. Stroke, heart attack, kidney failure, eye disease, and limb amputations can be the legacy of poor glucose control. The linings of blood vessels throughout the body become so fragile they cant ferry needed nutrients as well as they should. Inflammation rises and the immune system does not perform well. Obesity, which is more common in type 2 diabetes but can also occur in type 1, makes all these conditions worse.

Once someone with diabetes or obesity became infected with Covid-19, then their outcomes were generally not as good, said Daniel Drucker, of the Lunenfeld-Tanenbaum Research Institute at Mt. Sinai Hospital in Toronto. They were more likely to be hospitalized, more likely to be intubated, more likely to have higher rates of death.

People with obesity as a rule have lower cardiorespiratory fitness, meaning they cant move as well due to poorer lung function, possibly severe sleep apnea, and blood vessel disease.

All of these things are important for when you become ill. You need to be able to breathe. You need to have optimal circulatory function, Drucker said. When we develop obesity, we have excess energy storage and the presence of that fat is inflammatory. And so once we get coronavirus infection, we are less able to mount an appropriate immune response because our immune system is already being set off in an inappropriate manner by the presence of obesity.

Some studies add support to the idea that its not just obesity, but also the downstream hypertension and other cardiovascular diseases that pose greater risk. Drucker said. Its those comorbidities that seem to be affecting the increased risk or poor outcomes.

It isnt clear at what point those comorbidities take their toll. Does the course of disease become severe because of those comorbidities, or is there a difference in the biology of early infection, which may lead to increased viral burden in patients with both uncontrolled glucose and obesity?

For years doctors, patients, and scientists have known from epidemiologic data that infections of any kind viral, bacterial, or fungal can do more harm to people with diabetes because their bodies do not process glucose as well during illness, their immune response is weaker, and their circulation is impaired.

Covid-19s impact on people with diabetes fits that pattern. Janelle Ayres, a professor at the Salk institute in La Jolla, Calif., points to what diabetes and Covid-19 have in common.

The organ systems that the virus targets are the same organ systems that are compromised in diabetic patients, so having both may have synergistic effects that push patients down a more severe disease trajectory, she said. This makes it incredibly difficult to parse out the cause and effect of whats going on in these patients.

People with diabetes tend to live in a chronic inflammatory state, setting them up for a more severe inflammatory response to Covid-19 that can culminate in a life-threatening cytokine storm. That immune overreaction is thought to harm some people more through organ damage than via the actual viral infection. But diabetes can also weaken how well the immune system fights viruses. People with type 2 diabetes also have more ACE2 receptors in many tissues, including those lining blood vessels, Ayres pointed out, opening many more doors to Covid-19 invasion. ACE2 is one receptor that the coronaviruss spike protein uses to gain entry into cells.

There is only one target to control in hospitalized Covid-19 patients with diabetes, Drucker and others said: glucose.

People who have really poorly controlled diabetes are more susceptible to more severe infection, whether its influenza or tuberculosis, he said. Elevated blood sugar directly impairs our immune function.

Age and poor glucose control are the two major drivers of poor outcomes in Covid-19. Someone under 65, not obese, and whose glucose control is good is unlikely to have as much increased risk.

Its very difficult to reverse obesity or to meaningfully lose a sufficient amount of weight during the pandemic. Its very difficult for me to take away your coronary artery disease same thing with hypertension, Drucker said. But if you have poorly controlled diabetes, I can fix that in days to weeks if I had the resources.

Not every person with diabetes and Covid-19 needs to be hospitalized, but if they do require that level of care, controlling and monitoring glucose levels are key. There arent any results from controlled clinical trials yet, Joslins Patti pointed out, but lowering glucose safely to as normal a range as possible is the goal she and other doctors pursue. That can be challenging in the hospital, where typically glucose levels are measured in drops of blood obtained from patients fingertips.

You dont want to ask nursing staff to go in repeatedly to be doing fingerstick glucoses for someone whos severely ill and having to use more PPE, Patti said. So theres more and more use of whats called continuous glucose monitors, which allow frequent every five minutes remote monitoring of glucose levels from outside the room.

Vaccines promise prevention in a shot (or two), but clinical trials will have to answer questions about how well they work in people with diabetes, given differences in immune function. There is some evidence in the scientific literature that flu vaccination is not quite as effective in older people with diabetes, or in people of any age with poorly controlled diabetes.

Will the vaccines that are being developed [provide] equal immunity and equal protection to people with diabetes and obesity? Drucker asked. When you have the added complication of a preexisting abnormal state of inflammation and immune response in people with diabetes and obesity who are not very healthy, thats an additional unknown.

Tight glucose control is number one, but healthy people with diabetes must also remain vigilant about masks and social distancing. Thats been more effective in Hong Kong than in Western countries, Chan said.

Seventeen years ago, when Hong Kong and China were first hit by the SARS-1 virus, we already knew that people with diabetes were three times more likely to die, she said. Thats a painful memory for us. We have 100% compliance on masks now. We never really had a lockdown.

Even with such caution, and even in countries that offer citizens universal health care, disparities driving the social determinants of health persist, she said. Income will always divide those who are homeless, live in crowded conditions, or work in jobs that place them at risk, even if Covid-19 subsides. That makes prevention essential, especially for those who dont have the luxury of protecting themselves.

Currently a lot of the care is focused on acute care, not on educating patients, protecting them, supporting them so that they never come to the hospital, she said about Covid-19.

We must not forget. We have to learn from this.

This story has beenupdated to correctthe percentage of Covid-19 deaths in people with diabetes.

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Why people with diabetes are being hit so hard by Covid-19 - STAT

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Call to Action for Screening, Early Treatment of Diabetes – Medscape

Friday, October 2nd, 2020

People with type 2 diabetes derive benefit from earlier detection and treatment, suggests a decade-long follow-up of the Anglo-Danish-Dutch Study in General Practice of Intensive Treatment and Complication Prevention in Type 2 Diabetic Patients Identified by Screening(ADDITION-Europe).

"The 10-year follow-up findings support the use of intensive treatment of type 2 diabetes soon after diagnosis and have implications for policy relating to early detection and subsequent management of type 2 diabetes in primary care," said Simon Griffin, MD.

Griffin, the study lead from the University of Cambridge, UK, presented the findings at the virtual European Association for the Study of Diabetes (EASD) Annual Meeting 2020.

Although the difference in the primary outcome between the intensive treatment and routine care groups favored the former, the difference was not statistically significant.

Still, "It looks like early intensive treatment of multiple risk factors soon after diagnosis is safe and seems to lower cardiovascular events and mortality...patients benefit from early detection, and in turn, early treatment," Griffin emphasized.

Asked to comment, Andrew Boulton, MD, told Medscape Medical News that these results highlight the importance of recognizing type 2 diabetes not simply as a metabolic disease but as a cardiometabolic problem.

"The nonsignificance of these outcomes should not detract physicians in both primary and secondary care in their quest to achieve optimal control of not only diabetes, but also cholesterol, triglycerides, blood pressure, and body weight...and to avoid therapeutic inertia, which is frequently reported," said Boulton, of University of Manchester and Manchester Royal Infirmary, UK.

The 10-year results from ADDITION-Europe were also published in Lancet Diabetes & Endocrinology. And in an accompanying editorial, Takayoshi Sasako, MD, a diabetologist from the University of Tokyo, Japan, and colleagues say the effects of an intensive treatment program on cardiovascular outcomes and mortality seen at 5 years were largely sustained for an additional 5 years.

"Despite the lack of statistical significance probably partly due to improvements in clinical practice when the study was done these findings lend support to early multifactorial intervention in type 2 diabetes," they stress.

Sasako and colleagues add that it will be interesting to see whether the postulated benefits from intensive multifactorial treatment in ADDITION-Europe will become more evident in the next decade or whether they will fade, as in the Veterans Affairs Diabetes Trial (VADT).

"It will also be important to follow-up the ADDITION-Europe study cohort for the incidence of diabetes complications and mortality in the next decade and beyond, because such a prospective cohort in which patients are exposed to good control of risk factors in the first decade after diagnosis is rare," they add.

ADDITION-Europe aimed to assess the long-term effects of guidelines, education, and training on outcomes for people with diabetes detected by screening, and to quantify the effect of differences in treatment and risk factors in the first 5 years following detection. The 10-year results looked at any effects, including lasting effects on cardiovascular events, after the intensive intervention was stopped at 5 years.

"Most intervention studies informing the management of people with type 2 diabetes focus on treatment of individual risk factors, but in practice, patients receive lifestyle advice and simultaneous pharmacological treatment of several risk factors," explained Griffin.

"Most studies that have looked at multifactorial treatments tend to have been in patients with long-standing disease, whereas here we looked at whether multifactorial treatment given early after diagnosis would make a difference," he explained.

Primary care practices from Denmark, the Netherlands, and the UK used stepwise screening to identify people with previously undiagnosed type 2 diabetes.

A total of 3057 patients with newly diagnosed type 2 diabetes, according to 1999 WHO criteria, took part in the trial.

Patients were randomized to intensive management (n = 1678) and given lifestyle advice on diet, physical activity, and the importance of medication adherence and smoking cessation. Appropriate treatment was begun if A1cwas 6.5%, blood pressure was 120/80 mm Hg, and/or total cholesterol was > 3.5 mmol/L. There were also educational materials for patients and practice-based educational meetings for physicians.

Routine care (n = 1379) was based on national guidelines, and decisions around medication use were made by the individual treating clinician. The very few exclusion criteria make the study highly generalizable.

After 5 years of the intervention, there were no further efforts to encourage primary care teams to continue intensive treatment.

Patient characteristics between groups were similar. There were slightly more men than women, mean age was 60 years, around 95% were White, mean BMI was 31.6 kg/m2, approximately 6% had a history of myocardial infarction, and 28% were current smokers. Median A1c was 6.5% and 6.6% in the routine and intensive groups, respectively, mean systolic blood pressure was 149.8 and 148.5 mm Hg, and mean cholesterol was 5.6 and 5.5 mmol/L.

At 10-years post-randomization, participants were not recalled, but data on mortality, cardiovascular events, laboratory and clinical measures were collected from national registers and national audits, as well as electronic and manual searches of general practice and hospital medical records.

The primary endpoint was a composite of first cardiovascular event including cardiovascular mortality, nonfatal myocardial infarction, stroke and revascularization, and nontraumatic amputation.

Medscape Medical News reported the 5-year results from ADDITION-EUROPE in 2010. Although those in the intensive multifactorial treatment group were less likely to suffer events than those in the routine care group, the difference between groups was not statistically significant in terms of the primary endpoint.

At the time, Griffin said this likely reflected the fact that routine care of diabetes had been improving in the three countries that the patients were from. The results nevertheless illustrate that "intensive treatment in people with screen-detected diabetes is feasible," he emphasized.

For the 10-year analysis, 14 patients were lost to follow-up and 12 withdrew. Primary endpoint data were available for 99% of 3057 participants, and mean duration of follow-up was 9.6 years.

"By 10 years, the significant differences in treatments and [individual] risk factors [seen at 5 years] had largely attenuated except [those] from blood pressure medication and aspirin, which were still significantly different between groups," said Griffin at the virtual EASD.

Regarding treatment, overall, 85% of patients were prescribed antihypertensive medication, 78% statins, and 76% glucose-lowering medication (most commonly metformin).

Aspirin was used by 30.4% of the routine care group and 42.3% of the intensive treatment group. Antihypertensive agents were used by 82.4% in the routine care group and 86.4% in the intensive treatment group.

The primary endpoint at 10 years had occurred in 15.3% of patients in the routine care group versus 13.8% in the intensive treatment group.

"The small differences in treatment and risk factors seen in the first 5 years after diagnosis were associated with a nonsignificant 13% reduction (hazard ratio, 0.87; P = .14) in risk of cardiovascular disease events [composite primary endpoint] over 10 years," said Griffin when reporting the main finding.

There was also a nonsignificant 10% reduction in risk of all-cause death over 10 years (hazard ratio, 0.90); 219 patients (15.9%) in the routine care group died compared with 246 (14.7%) of those receiving intensive treatment.

"It looks like the 13% and the 10% were related to the small differences in treatment and risk factors after 5 years, suggesting a potential legacy effect," asserted Griffin.

"The UK ProspectiveDiabetesStudy has found that if you lower glucose early in disease it can have a lasting effect, whereas the effect for blood pressure, for example, only happens while on treatment. Effectively, treating people earlier will make a difference," he said.

The results overall suggest that identifying people with type 2 diabetes earlier and starting treatment promptly is beneficial, Griffin emphasized.

Also reported at the virtual EASD meeting was a study from the UK Biobank that found that 1% of individuals in the UK have undiagnosedtype 2 diabetes, and that it can take more than 5 years for people to be diagnosed.

Reporting those findings, Katherine Young, PhD, College of Medicine and Health at the University of Exeter, said the study shows "that population-level screening could identify cases of type 2 diabetes far earlier and potentially reduce complications."

Griffin said: "There is a question of how to find people and whether to do a national screening program. I suggest inviting highest risk people for screening. In the UK, the Health Checks [over 40 years] and risk assessments are sensible as long as they're being done systematically, and acted on."

Griffin has reported receiving fees from Novo Nordisk, Napp, AstraZeneca, and Eli Lilly. Sasako has reported receiving fees from Astellas, AstraZeneca, Daiichi Sankyo, MSD, Mitsubishi Tanabe, Nippon Boehringer Ingelheim, Novartis, Ono, Sanofi, Sumitomo Dainippon, Taisho Toyama, and Takeda; and grants from MSD, Nippon Boehringer Ingelheim, and Novo Nordisk. Boulton has reported no relevant financial relationships.

EASD Annual Meeting. Presented September 23, 2020.

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