Publisher Health

Every day, your pancreas produces about one cup of digestive juices, a mixture of molecules that can break down the food you eat. But if these powerful molecules become activated before they make their way to the gut, they can damage the pancreas itself — digesting the very cells that created them, leading to the painful inflammation known as pancreatitis, and predisposing a person to pancreatic cancer.
Now, Salk scientists report in the journal Gastroenterology on April 21, 2022 that a protein known as estrogen-related receptor gamma (ERR ɣ) is critical for preventing pancreatic auto-digestion in mice. Moreover, they discovered that people with pancreatitis have lower levels of ERR ɣ in cells affected by this inflammation.
These findings suggest that new therapies aimed at regulating ERR ɣ activity could help prevent or treat pancreatitis and pancreatic cancer.
“Our finding provides new insight into both the basic biology of how pancreas cells function, and what might drive pancreatitis and pancreatic cancer,” says Professor Ronald Evans, director of Salk’s Gene Expression Laboratory, March of Dimes Chair in Molecular and Developmental Biology, and co-senior author of the study.
The pancreas is home to two main cell types with distinct functions: beta cells that release insulin to control blood sugar levels and acinar cells that produce digestive juices. Evans and his colleagues previously discovered that ERR ɣ helps pancreatic beta cells release insulin and might be useful as a treatment for diabetes. In follow-up studies, the team also discovered that mice lacking ERR ɣ developed severe pancreatitis.
To understand the role of ERR ɣ in pancreatic acinar cells, the researchers compared mice, as well as isolated cells, with and without the protein. They discovered ERR ɣ is required for the functioning of the acinar cells’ mitochondria — organelles that generate energy.

Existing methods for detecting and diagnosing COVID-19 are either expensive and complex or inaccurate. Now, scientists from the Gwangju Institute of Science and Technology have developed a novel biosensing platform to detect and quantify viral particles using a simple optical microscope and antibody proteins. Their versatile approach, based on slowing down light, could pave the way to new diagnostic tools and next-generation detection platforms that are fast, accurate, and low-cost.
Despite all the bad news the COVID-19 pandemic brought upon the world, it has helped us gain a better perspective of our readiness to fend off highly contagious diseases. Rapid diagnostic test kits and PCR testing quickly became essential tools when the pandemic hit, helping with timely diagnoses. However, these tools have inherent limitations. PCR tests are complex and require expensive equipment while rapid diagnostic test kits have lower accuracy.
Against this backdrop, a research group led by Professor Young Min Song of the Gwangju Institute of Science and Technology in Korea has recently developed a new technique to easily visualize viruses using an optical microscope. A recent study explains in detail the operating principle of their detection platform, called the “Gires-Tournois immunoassay platform” (GTIP). This paper was made available online on March 22, 2022, and was published in the journal Advanced Materials on March 26, 2022.
The key element of GTIP is the Gires-Tournois “resonance structure,” a film made from three stacked layers of specific materials that produce a peculiar optical phenomenon called “slow light.” Because of how incident light rebounds inside the resonant layers before being reflected, the color of the platform seen through an optical microscope appears very uniform. However, nanometer-sized virus particles affect the resonance frequency of GTIP in their immediate vicinity by slowing down the light that gets reflected around them. The “slow light” manifests as a vivid color change in the reflected light so that, when viewed through the microscope, the virus particle clusters look like “islands” of a different color compared to the background.
To ensure that their system only detects coronavirus particles, the researchers coated the top layer of GTIP with antibody proteins specific to SARS-CoV-2. Interestingly, not only did the system enable the detection of viral particles, but, by using colorimetric analysis techniques, the researchers could even effectively quantify the number of virus particles present in different areas of a sample depending on the color of the light reflected locally.
The overall simplicity of the design is one of the main selling points of GTIP. As Prof. Song explains, “Compared to existing COVID-19 diagnostic methods, our approach enables rapid detection and quantification of SARS-CoV-2 without needing extra sample treatments, such as amplification and labeling.” Given that optical microscopes are available in most laboratories, the method developed by the group could become a valuable and ubiquitous diagnostic and virus research tool.
Furthermore, GTIP is not limited to detecting viruses or strictly dependent on antibodies; any other binding agent works as well, helping visualize all kinds of particles that interact with light. “Our strategy can even be applied for a dynamic monitoring of target particles sprayed in the air or dispersed on surfaces. We believe that this approach could be the basis for next-generation biosensing platforms, enabling simple yet accurate detection,” concludes Prof. Song.
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Materials provided by GIST (Gwangju Institute of Science and Technology). Note: Content may be edited for style and length.

Anterior cervical discectomy and fusion (ACDF) is a common type of neck surgery that involves removing a damaged disc to relieve pressure on the spinal cord or nerve root and thereby alleviate associated pain, numbness, weakness or tingling. The damaged disc is removed from between two vertebral bones along with simultaneous fusion surgery. The fusion involves placing a bone graft or “cage” and/or implants where the disc was originally located to stabilize and strengthen the area.
The use of cages for ACDF are important postoperatively to the alignment of the cervical spine and to maintain the intervertebral disc height. Few studies, however, have examined the impact of the underlying cancellous or “spongy” bone contact with regards to handling large loads from the cage. Moreover, it is still not clear whether a cage with or without screws will be the best choice for long-term fusion as the micromotion or sliding distance and subsidence or penetration of the cage still take place repeatedly.
Researchers from Florida Atlantic University’s College of Engineering and Computer Science, in collaboration with Frank Vrionis, M.D., senior author of the study and director of the Marcus Neuroscience Institute, part of Baptist Health; and professor of surgery, FAU’s Schmidt College of Medicine, are the first to evaluate the effect of the range of motion, cage migration and subsidence using variable angle screws. Marcus Neuroscience Institute has its hub on Boca Raton Regional Hospital’s campus and satellite locations at Bethesda Hospital in Boynton Beach and Deerfield Beach.
For the study, researchers developed five finite element models from a cervical spine model. The first model was an intact spine model, and the second model was an altered model with cage insertion and a 2-level static plate. The other three models were altered models with the same cage insertion and a 2-level dynamic plate. They compared ACDF cages with and without screws on the biomechanical characteristics of the human spine, implanted cage, and associated hardware by comparing the micro motion and subsidence.
Results of the study, published in The Spine Journal, the journal World Neurosurgery and Asian Spine Journalshowed that the cage-screw and anterior plating combination model has promising potential to reduce the risk of micro motion and subsidence of implanted cages in two or more level ACDFs. This method could increase the stiffness of the construct and reduce the incidence of clinical and fusion failure following ACDF, which in turn, could decrease the need for revision surgeries or supplemental posterior realignment.
“Anterior cervical discectomy and fusion is widely used to treat patients with spinal disorders, where the cage is a critical component to achieve satisfactory fusion results. The risk factors for cage migration are multifactorial and include patient factors, radiological characteristics, surgical techniques and postoperative factors,” said Vrionis. “Our results showed that the plate used in our study provided directional stability and obtained excellent fusion, indicating promising clinical outcomes for patients with degenerative cervical spine disease.”
Vrionis further explains that because of the biomechanical stability of the current construct, there has been no need for a rigid cervical collar, which is typically used by other surgeons.

In a new Scientific Statement released today, the Endocrine Society describes the importance of extracellular vesicles as a new research target for understanding the causes of certain endocrine disorders such as cancer and diabetes and discovering new treatments for these disorders.
During the last decade, endocrine researchers have shown great interest in extracellular vesicles and their hormone-like role in cell-to-cell communication. The statement provides insight into the functions of extracellular vesicles, which are secreted from all cells into biological fluids and carry endocrine signals that allow interactions between cells and distant sites in the body.
“We’re really excited about this new area of research that can help us better understand how people develop common endocrine conditions such as diabetes, obesity and cancer,” said Carlos Salomon Ph.D., D.Med.Sc., M.Sc., B.Sc., Associate Professor of The University of Queensland in Brisbane, Australia. “The statement highlights the likely uses of extracellular vesicles in detecting and monitoring disease progression and their role as next-generation drug delivery vehicles.”
Extracellular vesicles can help researchers better understand how to diagnose endocrine-related conditions including cancer and predict its progression. The role of extracellular vesicles as a cancer biomarker may extend to predicting real-time response to therapy.
Extracellular vesicles are also involved in understanding the cause and treatment of diabetes, obesity and heart disease. Recent studies have shown the potential of extracellular vesicles, particularly ones derived from stem cells, in treating diabetes. Research into the vesicles provides insights into the causes of insulin resistance and glucose intolerance in obesity.
Extracellular vesicles play an important role in the development of heart disease and could be useful for predicting risk. They also serve as biomarkers for high blood pressure and could have a therapeutic and blood pressure-lowering role.
“We hope this statement brings awareness to the significance of extracellular vesicles in endocrinology and encourages more research on their potential as biomarkers and therapeutics,” Salomon said.
Other authors of this statement are: Saumya Das of Massachusetts General Hospital and Harvard Medical School in Boston, Mass.; Uta Erdbrügger of the University of Virginia in Charlottesville, Va.; Raghu Kalluri of the University of Texas MD Anderson Cancer Center in Houston, Texas; Sai Kiang Lim of the Institute of Molecular and Cell Biology in Singapore; Jerrold M. Olefsky of the University of California-San Diego in La Jolla, Calif.; Gregory E. Rice of Inoviq Limited in Australia; Susmita Sahoo of the Icahn School of Medicine at Mount Sinai in New York, N.Y.; W. Andy Tao of Purdue University in West Lafayette, Ind.; Pieter Vader of Utrecht University and UMC Utrecht in Utrecht, the Netherlands; Qun Wang of Shandong University in Jinan, China; and Alissa M. Weaver of Vanderbilt University School of Medicine and Vanderbilt University Medical Center in Nashville, Tenn. 
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Materials provided by The Endocrine Society. Note: Content may be edited for style and length.

Counteracting antimicrobial resistance needs a multipronged approach, including training, labelling food products, working with the media and changing mindsets, according to a new study.
Antimicrobial resistance occurs when bacteria, viruses, fungi and parasites change over time and no longer respond to medicines, making infections harder to treat and increasing the risk of disease spread, severe illness and death. It claimed 1.27 million lives in 2019. It threatens health, social and economic well-being, and spreads as a result of actions taken across human, animal, agricultural and environmental systems, sometimes referred to as the One Health system.
The study, conducted by researchers at the University of Waterloo, in partnership with colleagues and collaborators from Canada, Sweden and Switzerland, set out to identify the factors influencing antimicrobial resistance in the European food system and places to intervene.
The researchers conducted workshops over two days with participants representing perspectives from government, non-government and healthcare organizations, as well as industry and private consultants. Participants identified 91 factors across the One Health spectrum that influence antimicrobial resistance, with 331 connections between them and many feedback loops. They also identified possible places within this system to target their interventions, which were then classified as shallow or deep.
“Shallow leverage points for intervention are places in the system that may be easier to implement with less potential to change the behaviour of the whole system that gives rise to antimicrobial resistance,” said Irene Lambraki, lead author and a researcher in the School of Public Health Sciences at Waterloo. An example would be increasing the number of staff trained in infection prevention and control in healthcare settings.
“Deep leverage points are places that are more challenging to change yet have greater potential to sustainably transform system behaviour,” she said. “These include delivering information in the system to places where it’s currently missing or informing people of the consequences of their actions to motivate behaviour change.
“The deepest lever participants identified was about changing the mindset that underpins how our systems operate, which is very profit-driven. For example, trying to get leaders to place economic value on health rather than generating profits for shareholders and prioritizing the achievement of the Sustainable Development Goals could create ripple effects across the system in ways that transform antimicrobial use — a major driver of antimicrobial resistance — and mitigate antimicrobial resistance.”
Researchers also identified five additional overarching factors that impact the entire system: regulations, leadership, media, collaboration and climate change.
“The study underscores the complexity of antimicrobial resistance problem, points to the need for global collaboration and coordinated multi-level and multipronged interventions targeting different sectors to effectively and sustainably address the antimicrobial resistance crisis,” said principal investigator Shannon Majowicz, also in the School of Public Health Sciences.
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Materials provided by University of Waterloo. Note: Content may be edited for style and length.

To this day, cavities and damage to enamel are repaired by dentists with the help of synthetic white filling materials. There is no natural alternative to this. But a new 3D model with human dental stem cells could change this in the future. The results of the research led by KU Leuven Professor Hugo Vankelecom and Professor Annelies Bronckaers from UHasselt have been published in Cellular and Molecular Life Sciences.
Our teeth are very important in everyday activities such as eating and speaking, as well as for our self-esteem and psychological well-being. There is relatively little known about human teeth. An important reason is that certain human dental stem cells, unlike those of rodents, are difficult to grow in the lab. That’s why the KU Leuven team of Professor Hugo Vankelecom, in cooperation with UHasselt, developed a 3D research model with stem cells from the dental follicle, a membraneous tissue surrounding unerupted human teeth.
“The advantage of this type of 3D model is that it reliably reproduces the stem cells’ original properties. We can recreate a small piece of our body in the lab, so to speak, and use it as a research model,” says Professor Vankelecom. “By using dental stem cells, we can develop other dental cells with this model, such as ameloblasts that are responsible for enamel formation.”
Biological filling material
Each day, our teeth are exposed to acids and sugars from food that can cause damage to our enamel. Enamel cannot regenerate, which makes an intervention by the dentist necessary. The latter has to fill any possible cavities with synthetic materials. “In our new model, we have managed to turn dental stem cells into ameloblasts that produce enamel components, which can eventually lead to biological enamel. That enamel could be used as a natural filling material to repair dental enamel, explains doctoral student Lara Hemeryck. “The advantage is that in this way, the physiology and function of the dental tissue is repaired naturally, while this is not the case for synthetic materials. Furthermore, there would be less risk of tooth necrosis, which can occur at the contact surface when using synthetic materials.”
Impact in many sectors
Not only dentists would be able to help their patients with this biological filling material. The 3D cell model can have applications in other sectors as well. For example, it could help the food industry to examine the effect of particular food products on dental enamel, or toothpaste manufacturers to optimise protection and care. “In addition, we want to combine this model with other types of dental stem cells to develop still other tooth structures, and eventually an entire biological tooth. Now, we focused on ameloblasts, but our new model clearly opens up various possibilities for further research and countless applications,” concludes Professor Vankelecom
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Materials provided by KU Leuven. Original written by Nena Testelmans. Note: Content may be edited for style and length.

According to new research, about one third of people who had a large vessel (severe) ischemic stroke, treated with mechanical clot removal, resumed work three months after stroke treatment. However, women were about half as likely to return to work after a severe stroke compared to men, according to the study published today in Stroke, the peer-reviewed, flagship journal of the American Stroke Association, a division of the American Heart Association.
A stroke due to a blockage in a large blood vessel is an indicator of a severe stroke and the potential for continuing loss of function, which makes it less likely people will return to work. According to the American Heart Association, while ischemic stroke accounts for 87% of strokes in the United States, large vessel occlusions only account for approximately 24% — 46% of ischemic strokes.
Endovascular therapy (mechanical clot removal) and clot-busting medications are now a standard treatment for select patients with severe stroke. Endovascular therapy involves threading a slim catheter through a vessel in the leg to mechanically remove a clot blocking a brain vessel. In 2018, the American Heart Association stroke treatment guidelines were updated to recommend mechanical clot removal for select stroke patients to improve the odds of functional recovery.
“Returning to work after a severe stroke is a sign of successful rehabilitation. Resuming pre-stroke levels of daily living and activities is highly associated with a better quality of life,” said Marianne Hahn, M.D., lead study author and a clinician scientist in the department of neurology at Johannes Gutenberg University in Mainz, Germany. “In contrast to most return-to-work studies, we included a large cohort of only people treated with mechanical clot removal; they are a subgroup of stroke patients at high risk for severe, persisting deficits.”
Researchers examined data from the German Stroke Registry — Endovascular Treatment Study Group. The analysis included more than 600 men and women (28% women), ages 18- to 64-years-old who had a large vessel ischemic stroke between 2015 and 2019.
All study participants were employed prior to their stroke and were treated with mechanical thrombectomy. More than half of the study participants also received intravenous thrombolysis (clot-busting medication).

Researchers at Lund University and Uppsala University are conducting one of the largest citizen science projects in Sweden to date. Since the start of the pandemic, study participants have used an app to report how they feel daily even if they are well. This symptom data could be used to estimate COVID-19 infection trends across Sweden and predict hospital admissions due to COVID-19 a week in advance. The results have now been published in the scientific journal Nature Communications.
The analyses included more than 10 million daily reports from participants in COVID Symptom Study Sweden from April 2020 to February 2021. The scope of the study was to develop and evaluate a framework to estimate the regional prevalence of COVID-19 using symptom-based surveillance, and to test if these prevalence estimates could be used to predict subsequent trends in COVID-19 hospital admissions.
“We show for the first time that symptom data can be informative in predicting subsequent regional trends in hospital admissions due to COVID-19, and confirm previous reports that trends in symptoms are related to community infection rates. These symptoms-based methods could be particularly useful in time periods and areas with low COVID-19-testing,” says Tove Fall, Professor of Molecular Epidemiology at the Department of Medical Sciences, Uppsala University, one of the lead authors of the study.
The app used for data collection was originally developed by ZOE, a health science company, with support from physicians and researchers at King’s College London and Guy’s and St Thomas’ Hospitals, for non-commercial purposes. The ZOE COVID Study was first launched in the UK and the US in March 2020. It was adapted and introduced in Sweden, where it is known as COVID Symptom Study Sweden, in April 2020. Any adult in Sweden can participate by downloading the app and providing in-app consent. Participants fill in a general baseline health survey, and can then report how they feel each day, even if they are well. Over 209,000 participants in Sweden have contributed so far, providing daily reports on symptoms, COVID-19 test results and vaccinations.
“This project would not have been possible without the dedication, hard work and collaborative spirit of our team members and colleagues in the UK and US. Above all, we have to thank each and every study participant for their contributions. Performing ‘real-time’ science is challenging, but of utmost importance during a pandemic. We are proud that we have been able to share real-time national and regional COVID-19 prevalence estimates on our dashboard almost every day since May 2020, and that COVID Symptom Study Sweden data was useful to Swedish municipalities and county councils. With over 4.7 million contributors globally, the ZOE COVID Study is one of the largest ongoing public science projects of its kind and has shown us the power of citizen science,” says Maria Gomez, Professor of Physiology at the Department of Clinical Sciences and Lund University Diabetes Centre, one of the lead authors of the study.
Researchers developed and validated a model to understand which symptoms were associated with a positive COVID-19 test, using data from participants who had reported symptoms and results from COVID-19 PCR-tests. That model could then be employed to estimate daily national and regional COVID-19 prevalence in the entire study population, as well as subsequently in the Swedish adult population. Combining app-based prevalence estimates with information on current hospital admissions, researchers were also able to predict future hospital admissions with moderate accuracy. Furthermore, the same model could be successfully applied to an English dataset to predict hospital admissions across the seven English healthcare regions, highlighting the transferability of the model to other countries.
“Real-time and granular pandemic surveillance requires combining multiple sources of data,” says Beatrice Kennedy, research fellow at the Department of Medical Sciences, Uppsala University and first author of the study. “Our findings highlight how app-based symptom-based surveillance may constitute a scalable and dynamic tool to monitor infection trends, and as such it should be considered in future pandemic preparedness plans.”
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Materials provided by Uppsala University. Note: Content may be edited for style and length.

In a study that offers hope for human dieters, rats on a 30-day diet who exercised intensely resisted cues for favored, high-fat food pellets.
The experiment was designed to test resistance to the phenomenon known as “incubation of craving,” meaning the longer a desired substance is denied, the harder it is to ignore signals for it. The findings suggest that exercise modulated how hard the rats were willing to work for cues associated with the pellets, reflecting how much they craved them.
While more research needs to be done, the study may indicate that exercise can shore up restraint when it comes to certain foods, said Travis Brown, a Washington State University physiology and neuroscience researcher.
“A really important part of maintaining a diet is to have some brain power — the ability to say ‘no, I may be craving that, but I’m going to abstain,'” said Brown, corresponding author on the study published in the journal Obesity. “Exercise could not only be beneficial physically for weight loss but also mentally to gain control over cravings for unhealthy foods.”
In the experiment, Brown and colleagues from WSU and University of Wyoming put 28 rats through a training with a lever that when pressed, turned on a light and made a tone before dispensing a high-fat pellet. After the training period, they tested to see how many times the rats would press the lever just to get the light and tone cue.
The researchers then split the rats into two groups: one underwent a regime of high-intensity treadmill running; the other had no additional exercise outside of their regular activity. Both sets of rats were denied access to the high-fat pellets for 30 days. At the end of that period, the researchers gave the rats access to the levers that once dispensed the pellets again, but this time when the levers were pressed, they only gave the light and tone cue. The animals that did not get exercise pressed the levers significantly more than rats that had exercised, indicating that exercise lessened the craving for the pellets.
In future studies, the research team plans to investigate the effect of different levels of exercise on this type of craving as well as how exactly exercise works in the brain to curb the desire for unhealthy foods.
While this study is novel, Brown said it builds on the work of Jeff Grimm at Western Washington University who led the team that first defined the term “incubation of craving” and has studied other ways to subvert it. Brown also credited Marilyn Carroll-Santi’s research at University of Minnesota showing that exercise can blunt cravings for cocaine.
It is still an unsettled research question as to whether food can be addictive in the same way as drugs. Not all foods appear to have an addictive effect; as Brown pointed out, “no one binge eats broccoli.” However, people do seem to respond to cues, such as fast-food ads, encouraging them to eat foods high in fat or sugar, and those cues may be harder to resist the longer they diet.
The ability to disregard these signals may be yet another way exercise improves health, Brown said.
“Exercise is beneficial from a number of perspectives: it helps with cardiac disease, obesity and diabetes; it might also help with the ability to avoid some of these maladaptive foods,” he said. “We’re always looking for this magic pill in some ways, and exercise is right in front of us with all these benefits.”
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Materials provided by Washington State University. Original written by Sara Zaske. Note: Content may be edited for style and length.

Experts from the University of Nottingham have developed a ground-breaking software, which combines DNA sequencing and machine learning to help them find where, and to what extent, antibiotic resistant bacteria is being transmitted between humans, animals and the environment.
The study, which is published in PLOS Computational Biology, was led by Dr Tania Dottorini from the School of Veterinary Medicine and Science at the University.
Anthropogenic environments (spaces created by humans), such as areas of intensive livestock farming, are seen as ideal breeding grounds for antimicrobial-resistant bacteria and antimicrobial resistant genes, which are capable of infecting humans and carrying resistance to drugs used in human medicine. This can have huge implications for how certain illnesses and infections can be treated effectively.
China has a large intensive livestock farming industry, poultry being the second most important source of meat in the country, and is the largest user of antibiotics for food production in the world.
In this new study, a team of experts looked at a large scale commercial poultry farm in China, and collected 154 samples from animals, carcasses, workers and their households and environments. From the samples, they isolated a specific bacteria called Escherichia coli (E. coli). These bacteria can live quite harmlessly in a person’s gut, but can also be pathogenic, and genome carry resistance genes against certain drugs, which can result in illness including severe stomach cramps, diarrhea and vomiting.
Researchers used a computational approach that integrates machine learning, whole genome sequencing, gene sharing networks and mobile genetic elements, to characterise the different types of pathogens found in the farm. They found that antimicrobial genes (genes conferring resistance to the antibiotics) were present in both pathogenic and non-pathogenic bacteria.
The new approach, using machine learning, enabled the team to uncover an entire network of genes associated with antimicrobial resistance, shared across animals, farm workers and the environment around them. Notably, this network included genes known to cause antibiotic resistance as well as yet unknown genes associated to antibiotic resistance.
Dr Dottorini said: “We cannot say at this stage where the bacteria originated from, we can only say we found it and it has been shared between animals and humans. As we already know there has been sharing, this is worrying, because people can acquire resistances to drugs from two different ways — from direct contact with an animal, or indirectly by eating contaminated meat. This could be a particular problem in poultry farming, as it is the most widely used meat in the world.
“The computational tools that we have developed will enable us to analyse large complex data from different sources, at the same time as identifying where hotspots for certain bacteria may be. They are fast, they are precise and they can be applied on large environments — for instance — multiple farms at the same time.
“There are many antimicrobial resistant genes we already know about, but how do we go beyond these and unravel new targets to design new drugs?
“Our approach, using machine learning, opens up new possibilities for the development of fast, affordable and effective computational methods that can provide new insights into the epidemiology of antimicrobial resistance in livestock farming.”
The research was done in collaboration with Professor Junshi Chen, Professor Fengqin Li and Professor Zixin Peng from China National Center for Food Safety Risk Assessment (CFSA).