Skip to main content

diabetes

Science, Serendipity, and Art

Posted on by Lawrence Tabak, D.D.S., Ph.D.

green and blue, fractal-like patterns
Credit: Bryan Bogin and Matthew Steinsaltz, Zachary Levine Lab, Yale University School of Medicine, New Haven, CT

Fractals are complex geometric patterns repeated at progressively smaller scales. You’ll find them throughout nature. That includes in the 3D structures and shapes of tissues throughout our bodies, from the bones in our skulls down to the blood vessels in our feet. But the fractal pattern above isn’t from a precisely patterned human tissue. It comes from some unexpected biochemistry that formed the stunning pattern on its own.

In fact, the exact source for this fractal pattern reminiscent of peacock feathers isn’t known. It turned up out of the blue (and green) in a sample that had been sitting around on the shelf for some time. The original image appeared in black and white, but the colors added post-collection help to highlight the fractal pattern of a sample including an essential hormone produced in the pancreas. The hormone is called islet amyloid polypeptide (IAPP).

Also known as amylin, IAPP plays many important roles in our bodies, including the feeling of fullness after a meal. But the amino acid chains that make up IAPP also are prone to forming abnormal clumps of misfolded polypeptides (a long name for proteins) known as amyloids. Much like the amyloid plaques in the brains of people with Alzheimer’s disease, misfolded IAPP amyloids in people with type 2 diabetes also can damage insulin-producing beta cells in the pancreas and make controlling their blood sugar levels even more difficult.

This unusual image comes from graduate students Bryan Bogin and Matthew Steinsaltz. They study the biophysics and biochemistry of protein folding and misfolding in the lab of Zachary Levine, Yale School of Medicine, New Haven, CT. The Levine lab recently moved to the Altos Labs San Diego Institute. However, Bogin and Steinsaltz continue to conduct their studies at Yale.

The two conduct in-solution experiments and molecular simulations to elucidate the precise conditions and triggers that can lead otherwise normal polypeptide chains to fold up incorrectly and wreak havoc as they do in diabetes and other diseases. When Steinsaltz was learning how to use transmission electron microscopy (TEM), a technique in which an electron beam captures images including detailed molecular-level structures, Bogin handed over an assortment of IAPP samples in different solution conditions from some of his past experiments for a look.

In those microscopy images, they expected to see long, linear fibrils consisting of IAPP polypeptides. While that’s indeed what they saw in most of the samples, this one was the exception. It was such a remarkable image that they submitted it in the Biophysical Society’s 2022 Art of Science Image Contest, where it took the top prize.

Bogin and Steinsaltz say they still can’t explain the source or meaning behind these unusual fractal patterns. But they do continue to conduct experiments to understand how various polypeptides implicated in health and disease misfold to form destructive aggregates. This striking image may not hold the answers they seek, but it is an inspiring reminder that the path to making groundbreaking biomedical discoveries will have many beautiful surprises along the way.

Links:

Type 2 Diabetes (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Zachary Levine Lab (Yale School of Medicine, New Haven, CT)

Art of Science Image Contest (Biophysical Society, Rockville, MD)

NIH Support: National Institute on Aging


Artificial Pancreas Improves Blood Glucose Control in Young Kids with Type 1 Diabetes

Posted on by Lawrence Tabak, D.D.S., Ph.D.

Smiling young girl with a photo of an insulin pump
Credit: Shutterstock/sirtravelalot; Tandem Diabetes Care, San Diego, CA

Last week brought some great news for parents of small children with type 1 diabetes (T1D). It involved what’s called an “artificial pancreas,” a new type of device to monitor continuously a person’s blood glucose levels and release the hormone insulin at the right time and at the right dosage, much like the pancreas does in kids who don’t have T1D.

Researchers published last week in the New England Journal of Medicine [1] the results of the largest clinical trial yet of an artificial pancreas technology in small children, ages 2 to 6. The data showed that their Control-IQ technology was safe and effective over several weeks at controlling blood glucose levels in these children. In fact, the new device performed better than the current standard of care.

Two previous clinical trials of the Control-IQ technology had shown the same in older kids and adults, age 6 and up [2,3], and the latest clinical trial, one of the first in young kids, should provide the needed data for the U. S. Food and Drug Administration (FDA) to consider whether to extend the age range approved to use this artificial pancreas. The FDA earlier approved two other artificial pancreas devices—the MiniMed 770G and the Insulet Omnipod 5 systems—for use in children age 2 and older [4,5].

The Control-IQ clinical trial results are a culmination of more than a decade-long effort by the NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and many others to create technologies, such as an artificial pancreas, to improve blood glucose control. The reason is managing blood glucose levels remains critical for the long-term health of people with T1D.

What exactly is an artificial pancreas? It consists of three fully integrated components: a glucose monitor, an insulin pump, and a computer algorithm that allows the other two components to communicate. This automation frees people with T1D from checking their blood glucose levels multiple times a day and from many insulin dosing decisions, though they still interact with the system at mealtimes.

Abdomen of a young child. A glucose sensor, attached to the skin sends a signal to an insulin pump which is hanging from the child's pants. A tube runs to a another adhesive on the abdomen to deliver insulin.

In this clinical trial, led by Marc D. Breton, University of Virginia School of Medicine, Charlottesville, researchers tested their Control-IQ technology (manufactured by Tandem Diabetes Care, San Diego, CA), also known as a hybrid closed-loop control system. Thanks to an algorithm developed at the University of Virginia Center for Diabetes Technology, insulin doses are administered automatically every few minutes based on readings from a continuous glucose monitor.

But treating younger children with T1D presents its own set of age-specific challenges. Younger kids generally require smaller doses of insulin more frequently. They also tend to have a more unpredictable schedule with lots of small snacks and random bursts of physical activity.

On top of all that, these young children have a tougher time than kids a few years older when it comes to understanding their own needs and letting the adults around them know when they need help. For all these reasons, young children with T1D tend to spend a greater proportion of time than older kids or adults do with blood glucose levels that are higher, or lower, than they should be. The hope was that the artificial pancreas might help to simplify things.

To find out, the trial enrolled 102 volunteers between ages 2 and 6. Sixty-eight were randomly assigned to receive the artificial pancreas, while the other 34 continued receiving insulin via either an insulin pump or multiple daily injections. The primary focus was on how long kids in each group spent in the target blood glucose range of 70 to 180 milligrams per deciliter, as measured using a continuous glucose monitor.

During the trial’s 13 weeks, participants in the artificial pancreas group spent approximately three more hours per day with their blood glucose in a healthy range compared to the standard care group. The greatest difference in blood glucose control was seen at night while the children should have been sleeping, from 10 p.m. to 6 a.m. During this important period, children with the artificial pancreas spent 18 percent more time in normal blood glucose range than the standard care group. That’s key because nighttime control is especially challenging to maintain in children with T1D.

Overall, the findings show benefits to young children similar to those seen previously in older kids. Those benefits also were observed in kids regardless of age, racial or ethnic group, parental education, or family income.

In the artificial pancreas group, there were two cases of severe hypoglycemia (low blood glucose) compared to one case in the other group. One child in the artificial pancreas group also developed diabetic ketoacidosis, a serious complication in which the body doesn’t have enough insulin. These incidents, while unfortunate, happened infrequently and at similar rates in the two groups.

Interestingly, the trial took place during the COVID-19 pandemic. As a result, much of the training on use of the artificial pancreas system took place virtually. Breton notes that the success of the artificial pancreas under these circumstances is an important finding, especially considering that many kids with T1D live in areas that are farther from endocrinologists or other specialists.

Even with these clinical trials now completed and a few devices on the market, there’s still more work to be done. The NIDDK has plans to host a meeting in the coming months to discuss next steps, including outstanding research questions and other priorities. It’s all very good news for people with T1D, including young kids and their families.

References:

[1] Trial of hybrid closed-loop control in young children with type 1 diabetes. Wadwa RP, Reed ZW, Buckingham BA, DeBoer MD, Ekhlaspour L, Forlenza GP, Schoelwer M, Lum J, Kollman C, Beck RW, Breton MD; PEDAP Trial Study Group. N Engl J Med. 2023 Mar 16;388(11):991-1001.

[2] A randomized trial of closed-loop control in children with type 1 diabetes. Breton MD, Kanapka LG, Beck RW, Ekhlaspour L, Forlenza GP, Cengiz E, Schoelwer M, Ruedy KJ, Jost E, Carria L, Emory E, Hsu LJ, Oliveri M, Kollman CC, Dokken BB, Weinzimer SA, DeBoer MD, Buckingham BA, Cherñavvsky D, Wadwa RP; iDCL Trial Research Group. N Engl J Med. 2020 Aug 27;383(9):836-845.

[3] Six-month randomized, multicenter trial of closed-loop control in type 1 diabetes. Brown SA, Kovatchev BP, Raghinaru D, Lum JW, Buckingham BA, Kudva YC, Laffel LM, Levy CJ, Pinsker JE, Wadwa RP, Dassau E, Doyle FJ 3rd, Anderson SM, Church MM, Dadlani V, Ekhlaspour L, Forlenza GP, Isganaitis E, Lam DW, Kollman C, Beck RW; N Engl J Med. 2019 Oct 31;381(18):1707-1717.

[4] MiniMed 770G System-P160017/S076. U. S. Food and Drug Administration, December 23, 2020.

[5] FDA authorizes Omnipod 5 for ages 2+ in children with type 1 diabetes. Juvenile Diabetes Research Foundation news release, August 22, 2022

Links:

Type I Diabetes (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Artificial Pancreas (NIDDK)

Marc Breton (University of Virginia, Charlottesville)

NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases


Unlocking Potential in The Next Generation of Scientists

Posted on by Griffin P. Rodgers, M.D., M.A.C.P., National Institute of Diabetes and Digestive and Kidney Diseases

Photo of smiling people stand with ocean behind them, over map of Guam
Caption: The Pacific STEP-UP team visits Guam for opening of NIDDK lab (l-r): George Hui, University of Hawaii at Manoa; NIDDK’s Griffin P. Rodgers and Lawrence Agodoa; Aneesa Golshan, University of Hawaii at Manoa; Robert Rivers, NIDDK. Credit: Kristina C. Sayama, University of Guam

While talent is everywhere, opportunity is not. That belief, and meeting people where they are, have been the impetus for the efforts of NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to nurture diverse research talent in the Pacific Islands. Most recently that effort manifested in opening a new biomedical research laboratory at Southern High School, located in Santa Rita village on the island of Guam.

One of seven research labs in the Pacific Islands established under NIDDK’s Short-Term Research Experience Program to Unlock Potential (STEP-UP), the facility provides research training to high school and college students from historically underserved populations, which is the mission of STEP-UP. The goal is to foster a diverse, talented scientific workforce.

Created by NIDDK more than 20 years ago, STEP-UP aims to make opportunities accessible to aspiring scientists nationwide, regardless of their background or zip code. In 2009, we expanded the program to the Pacific Islands. By working with academic and nonprofit coordinating centers throughout the United States and its Pacific territories, the program enables students to gain hands-on research experience, one-on-one mentorship, and access to modern laboratory techniques without travelling far from home.

For Mata’uitafa Solomona-Faiai, a Ph.D. student at Yale University School of Public Health, New Haven, CT, the exposure to science through STEP-UP turned into a passion for research. Solomona-Faiai participated in STEP-UP as a high schooler in American Samoa, and again as a college undergraduate. After getting her master’s degree at George Washington University in Washington, D.C., she returned to American Samoa to conduct epidemiology research—and became a co-mentor to high school STEP-UP students. 

Her experiences in STEP-UP made her realize she wanted to pursue a life of public health research and gave her the skills to help pave that path. I was delighted to learn that Solomona-Faiai recently received an NIDDK Diversity Supplement to help support her research, which will focus on improving diabetes outcomes among adolescents from the Pacific Islands. She also hopes one day to run her own research group as an independent principal investigator, and I’m confident in her tenacity to make that happen! 

Solomona-Faiai is among more than 2,300 students who have participated in STEP-UP since 2000. Her story embodies the scientific potential we can access if we contribute the right resources and tools. Early evaluation results of STEP-UP from 2002 to 2018 showed that many of the program’s participants have pursued careers as researchers, physicians, and physician-scientists [1]. In addition, of the more than 300 high school STEP-UP participants in the Pacific Islands, most have gone on to attend four-year universities, many majoring in STEM disciplines [2]. I’m heartened to know our efforts are paying off.

Bringing scientific opportunity to the Pacific Islands has entailed more than just placing students into research labs. We found we had to help create infrastructure—building labs in often under-resourced areas where nearly no biomedical infrastructure previously existed.

Since 2008, NIDDK has helped establish research labs at high schools and community colleges in the American Samoa, Commonwealth of the Northern Mariana Islands, Republic of the Marshall Islands, Federated States of Micronesia, Republic of Palau, and now Guam. The labs are also available to faculty to conduct their own science and to train as mentors. Having the support of their teachers is particularly important for students in these areas, many of whom have never heard of biomedical research before. For them, the labs often provide their first real exposure to science.  

As proud as I am of the strides we’ve made, I know we have much more work to do. That’s why I’m grateful to the unwavering commitment of my colleagues, including Lawrence Agodoa who has pioneered STEP-UP and other programs in NIDDK’s Office of Minority Health Research Coordination; Robert Rivers, who coordinates NIDDK’s training programs; and George Hui at University of Hawaii at Manoa, who has directed the Pacific STEP-UP for 15 years.

They, like so many of NIDDK’s staff, partners, and grantees, will continue to work relentlessly to achieve our institute’s vision of developing a talented biomedical research workforce that fully represents the diverse fabric of the United States and its territories.

This month, we welcome a new class of STEP-UP participants, and I hope that, like Solomona-Faiai, they’ll experience the excitement of scientific discovery that will help shape their career goals and propel them to attain those goals. And I’m reminded of the tremendous responsibility we have to nurture and support the next generation of scientists. After all, the future of our nation’s health is in their hands.

References:

[1] NIDDK’s short-term research experience for underrepresented persons (STEP-UP) program. Rivers, R., Brinkley, K., Agodoa, L. JHDRP. 2019 Summer; 12: 1-2.

[2] Promoting local talents to fight local health issues: STEP-UP in the Pacific. Golshan, A., Hui, G. JHDRP. 2019 Summer; 12: 31-32.

Links:

Short-Term Research Experience Program to Unlock Potential (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Office of Minority Health Research Coordination (NIDDK)

Note: Acting NIH Director Lawrence Tabak has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 12th in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.


Artificial Intelligence Getting Smarter! Innovations from the Vision Field

Posted on by Michael F. Chiang, M.D., National Eye Institute

AI. Photograph of retina

One of many health risks premature infants face is retinopathy of prematurity (ROP), a leading cause of childhood blindness worldwide. ROP causes abnormal blood vessel growth in the light-sensing eye tissue called the retina. Left untreated, ROP can lead to lead to scarring, retinal detachment, and blindness. It’s the disease that caused singer and songwriter Stevie Wonder to lose his vision.

Now, effective treatments are available—if the disease is diagnosed early and accurately. Advancements in neonatal care have led to the survival of extremely premature infants, who are at highest risk for severe ROP. Despite major advancements in diagnosis and treatment, tragically, about 600 infants in the U.S. still go blind each year from ROP. This disease is difficult to diagnose and manage, even for the most experienced ophthalmologists. And the challenges are much worse in remote corners of the world that have limited access to ophthalmic and neonatal care.

Caption: Image of a neonatal retina prior to AI processing. Left: Image of a premature infant retina showing signs of severe ROP with large, twisted blood vessels; Right: Normal neonatal retina by comparison. Credit: Casey Eye Institute, Oregon Health and Science University, Portland, and National Eye Institute, NIH

Artificial intelligence (AI) is helping bridge these gaps. Prior to my tenure as National Eye Institute (NEI) director, I helped develop a system called i-ROP Deep Learning (i-ROP DL), which automates the identification of ROP. In essence, we trained a computer to identify subtle abnormalities in retinal blood vessels from thousands of images of premature infant retinas. Strikingly, the i-ROP DL artificial intelligence system outperformed even international ROP experts [1]. This has enormous potential to improve the quality and delivery of eye care to premature infants worldwide.

Of course, the promise of medical artificial intelligence extends far beyond ROP. In 2018, the FDA approved the first autonomous AI-based diagnostic tool in any field of medicine [2]. Called IDx-DR, the system streamlines screening for diabetic retinopathy (DR), and its results require no interpretation by a doctor. DR occurs when blood vessels in the retina grow irregularly, bleed, and potentially cause blindness. About 34 million people in the U.S. have diabetes, and each is at risk for DR.

As with ROP, early diagnosis and intervention is crucial to preventing vision loss to DR. The American Diabetes Association recommends people with diabetes see an eye care provider annually to have their retinas examined for signs of DR. Yet fewer than 50 percent of Americans with diabetes receive these annual eye exams.

The IDx-DR system was conceived by Michael Abramoff, an ophthalmologist and AI expert at the University of Iowa, Iowa City. With NEI funding, Abramoff used deep learning to design a system for use in a primary-care medical setting. A technician with minimal ophthalmology training can use the IDx-DR system to scan a patient’s retinas and get results indicating whether a patient should be sent to an eye specialist for follow-up evaluation or to return for another scan in 12 months.

Caption: The IDx-DR is the first FDA-approved system for diagnostic screening of diabetic retinopathy. It’s designed to be used in a primary care setting. Results determine whether a patient needs immediate follow-up. Credit: Digital Diagnostics, Coralville, IA.

Many other methodological innovations in AI have occurred in ophthalmology. That’s because imaging is so crucial to disease diagnosis and clinical outcome data are so readily available. As a result, AI-based diagnostic systems are in development for many other eye diseases, including cataract, age-related macular degeneration (AMD), and glaucoma.

Rapid advances in AI are occurring in other medical fields, such as radiology, cardiology, and dermatology. But disease diagnosis is just one of many applications for AI. Neurobiologists are using AI to answer questions about retinal and brain circuitry, disease modeling, microsurgical devices, and drug discovery.

If it sounds too good to be true, it may be. There’s a lot of work that remains to be done. Significant challenges to AI utilization in science and medicine persist. For example, researchers from the University of Washington, Seattle, last year tested seven AI-based screening algorithms that were designed to detect DR. They found under real-world conditions that only one outperformed human screeners [3]. A key problem is these AI algorithms need to be trained with more diverse images and data, including a wider range of races, ethnicities, and populations—as well as different types of cameras.

How do we address these gaps in knowledge? We’ll need larger datasets, a collaborative culture of sharing data and software libraries, broader validation studies, and algorithms to address health inequities and to avoid bias. The NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) project and NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program project will be major steps toward addressing those gaps.

So, yes—AI is getting smarter. But harnessing its full power will rely on scientists and clinicians getting smarter, too.

References:

[1] Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks. Brown JM, Campbell JP, Beers A, Chang K, Ostmo S, Chan RVP, Dy J, Erdogmus D, Ioannidis S, Kalpathy-Cramer J, Chiang MF; Imaging and Informatics in Retinopathy of Prematurity (i-ROP) Research Consortium. JAMA Ophthalmol. 2018 Jul 1;136(7):803-810.

[2] FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems. Food and Drug Administration. April 11, 2018.

[3] Multicenter, head-to-head, real-world validation study of seven automated artificial intelligence diabetic retinopathy screening systems. Lee AY, Yanagihara RT, Lee CS, Blazes M, Jung HC, Chee YE, Gencarella MD, Gee H, Maa AY, Cockerham GC, Lynch M, Boyko EJ. Diabetes Care. 2021 May;44(5):1168-1175.

Links:

Retinopathy of Prematurity (National Eye Institute/NIH)

Diabetic Eye Disease (NEI)

NEI Research News

Michael Abramoff (University of Iowa, Iowa City)

Bridge to Artificial Intelligence (Common Fund/NIH)

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program (NIH)

[Note: Acting NIH Director Lawrence Tabak has asked the heads of NIH’s institutes and centers to contribute occasional guest posts to the blog as a way to highlight some of the cool science that they support and conduct. This is the second in the series of NIH institute and center guest posts that will run until a new permanent NIH director is in place.]


How COVID-19 Can Lead to Diabetes

Posted on by Dr. Francis Collins

Human abdominal anatomy with highlighted pancreas. Cluster of Infected Beta Cells with cornaviruses are in foreground.

Along with the pneumonia, blood clots, and other serious health concerns caused by SARS-CoV-2, the COVID-19 virus, some studies have also identified another troubling connection. Some people can develop diabetes after an acute COVID-19 infection.

What’s going on? Two new NIH-supported studies, now available as pre-proofs in the journal Cell Metabolism [1,2], help to answer this important question, confirming that SARS-CoV-2 can target and impair the body’s insulin-producing cells.

Type 1 diabetes occurs when beta cells in the pancreas don’t secrete enough insulin to allow the body to metabolize food optimally after a meal. As a result of this insulin insufficiency, blood glucose levels go up, the hallmark of diabetes.

Earlier lab studies had suggested that SARS-CoV-2 can infect human beta cells [3]. They also showed that this dangerous virus can replicate in these insulin-producing beta cells, to make more copies of itself and spread to other cells [4].

The latest work builds on these earlier studies to discover more about the connection between COVID-19 and diabetes. The work involved two independent NIH-funded teams, one led by Peter Jackson, Stanford University School of Medicine, Palo Alto, CA, and the other by Shuibing Chen, Weill Cornell Medicine, New York. I’m actually among the co-authors on the study by the Chen team, as some of the studies were conducted in my lab at NIH’s National Human Genome Research Institute, Bethesda, MD.

Both studies confirmed infection of pancreatic beta cells in autopsy samples from people who died of COVID-19. Additional studies by the Jackson team suggest that the coronavirus may preferentially infect the insulin-producing beta cells.

This also makes biological sense. Beta cells and other cell types in the pancreas express the ACE2 receptor protein, the TMPRSS2 enzyme protein, and neuropilin 1 (NRP1), all of which SARS-CoV-2 depends upon to enter and infect human cells. Indeed, the Chen team saw signs of the coronavirus in both insulin-producing beta cells and several other pancreatic cell types in the studies of autopsied pancreatic tissue.

The new findings also show that the coronavirus infection changes the function of islets—the pancreatic tissue that contains beta cells. Both teams report evidence that infection with SARS-CoV-2 leads to reduced production and release of insulin from pancreatic islet tissue. The Jackson team also found that the infection leads directly to the death of some of those all-important beta cells. Encouragingly, they showed this could avoided by blocking NRP1.

In addition to the loss of beta cells, the infection also appears to change the fate of the surviving cells. Chen’s team performed single-cell analysis to get a careful look at changes in the gene activity within pancreatic cells following SARS-CoV-2 infection. These studies showed that beta cells go through a process of transdifferentiation, in which they appeared to get reprogrammed.

In this process, the cells begin producing less insulin and more glucagon, a hormone that encourages glycogen in the liver to be broken down into glucose. They also began producing higher levels of a digestive enzyme called trypsin 1. Importantly, they also showed that this transdifferentiation process could be reversed by a chemical (called trans-ISRIB) known to reduce an important cellular response to stress.

The consequences of this transdifferentiation of beta cells aren’t yet clear, but would be predicted to worsen insulin deficiency and raise blood glucose levels. More study is needed to understand how SARS-CoV-2 reaches the pancreas and what role the immune system might play in the resulting damage. Above all, this work provides yet another reminder of the importance of protecting yourself, your family members, and your community from COVID-19 by getting vaccinated if you haven’t already—and encouraging your loved ones to do the same.

References:

[1] SARS-CoV-2 infection induces beta cell transdifferentiation. Tang et al. Cell Metab 2021 May 19;S1550-4131(21)00232-1.

[2] SARS-CoV-2 infects human pancreatic beta cells and elicits beta cell impairment. Wu et al. Cell Metab. 2021 May 18;S1550-4131(21)00230-8.

[3] A human pluripotent stem cell-based platform to study SARS-CoV-2 tropism and model virus infection in human cells and organoids. Yang L, Han Y, Nilsson-Payant BE, Evans T, Schwartz RE, Chen S, et al. Cell Stem Cell. 2020 Jul 2;27(1):125-136.e7.

[4] SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas. Müller JA, Groß R, Conzelmann C, Münch J, Heller S, Kleger A, et al. Nat Metab. 2021 Feb;3(2):149-165.

Links:

COVID-19 Research (NIH)

Type 1 Diabetes (National Institute of Diabetes, Digestive and Kidney Disorders/NIH)

Jackson Lab (Stanford Medicine, Palo Alto, CA)

Shuibing Chen Laboratory (Weill Cornell Medicine, New York City)

NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases; National Human Genome Research Institute; National Institute of General Medical Sciences; National Cancer Institute; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development


Next Page