Tech

Researchers at North Carolina State University have made what is believed to be the smallest state-of-the-art RFID chip, which should drive down the cost of RFID tags. In addition, the chip's design makes it possible to embed RFID tags into high value chips, such as computer chips, boosting supply chain security for high-end technologies.

"As far as we can tell, it's the world's smallest Gen2-compatible RFID chip," says Paul Franzon, corresponding author of a paper on the work and Cirrus Logic Distinguished Professor of Electrical and Computer Engineering at NC State.

Gen2 RFID chips are state of the art and are already in widespread use. One of the things that sets these new RFID chips apart is their size. They measure 125 micrometers (μm) by 245μm. Manufacturers were able to make smaller RFID chips using earlier technologies, but Franzon and his collaborators have not been able to identify smaller RFID chips that are compatible with the current Gen2 technology.

"The size of an RFID tag is largely determined by the size of its antenna - not the RFID chip," Franzon says. "But the chip is the expensive part."

The smaller the chip, the more chips you can get from a single silicon wafer. And the more chips you can get from the silicon wafer, the less expensive they are.

"In practical terms, this means that we can manufacture RFID tags for less than one cent each if we're manufacturing them in volume," Franzon says.

That makes it more feasible for manufacturers, distributors or retailers to use RFID tags to track lower-cost items. For example, the tags could be used to track all of the products in a grocery store without requiring employees to scan items individually.

"Another advantage is that the design of the circuits we used here is compatible with a wide range of semiconductor technologies, such as those used in conventional computer chips," says Kirti Bhanushali, who worked on the project as a Ph.D. student at NC State and is first author of the paper. "This makes it possible to incorporate RFID tags into computer chips, allowing users to track individual chips throughout their life cycle. This could help to reduce counterfeiting, and allow you to verify that a component is what it says it is."

"We've demonstrated what is possible, and we know that these chips can be made using existing manufacturing technologies," Franzon says. "We're now interested in working with industry partners to explore commercializing the chip in two ways: creating low-cost RFID at scale for use in sectors such as grocery stores; and embedding RFID tags into computer chips in order to secure high-value supply chains."

Loss of smell, or anosmia, is one of the earliest and most commonly reported symptoms of COVID-19. But the mechanisms involved had yet to be clarified. Scientists from the Institut Pasteur, the CNRS, Inserm, Université de Paris and the Paris Public Hospital Network (AP-HP) determined the mechanisms involved in the loss of smell in patients infected with SARS-CoV-2 at different stages of the disease. They discovered that SARS-CoV-2 infects sensory neurons and causes persistent epithelial and olfactory nervous system inflammation. Furthermore, in some patients with persistent clinical signs, anosmia is associated with prolonged epithelial and olfactory nervous system inflammation and lasting presence of the virus in the olfactory epithelium. These findings were published in the journal Science Translational Medicine on May 3, 2021.

Although COVID-19 caused by the SARS-CoV-2 virus is principally a respiratory disease, many patients present with non-respiratory symptoms. These include a sudden loss of smell in individuals infected with SARS-CoV-2, which has been reported throughout the world since the beginning of the pandemic. Until recently, there has been uncertainty as to whether the virus plays a direct role in anosmia. According to one hypothesis generally accepted until now, it was assumed that a transient edema of the olfactory clefts inhibited airflow transporting odor molecules to the olfactory neurons (the familiar sensation of a blocked nose experienced during a common cold).

In a recent study, scientists from the Institut Pasteur, the CNRS, Inserm, Université de Paris, and the Paris Public Hospital Network (AP-HP) shed light on the mechanisms involved in COVID-19-related anosmia. The study was conducted with COVID-19 patients and supplemented with tests on an animal model. This study unexpectedly demonstrates that nasopharyngeal swabs may test negative by standard RT-qPCR even if the virus is still present at the back of the nasal cavities, in the olfactory epithelium. In light of this discovery, SARS-CoV-2 diagnosis by nasal brushing may be envisaged in addition to nasopharyngeal swabbing for the PCR test in patients experiencing loss of smell.

This work also sheds light on the mechanism of COVID-19-related smell loss by revealing a series of chronological steps:

1) Cilia carried by sensory neurons are lost post-viral infection. These cilia enable the sensory neurons to receive odor molecules;

2) Virus present in sensory neurons;

3) Disruption of the olfactory epithelium (sensory organ) integrity linked to apoptosis (i.e. cell death). The epithelium is organized into regular lamellae, which are destructured by coronavirus infection;

4) Virus dissemination to the olfactory bulb, which is the first cerebral relay station in the olfactory system;

5) Inflammation and viral RNA present in several regions of the brain.

This study demonstrates that loss of smell is also caused by deterioration of the sensory organ at the back of the nasal cavities. "We observed that SARS-CoV-2 infects not only the sensory neurons, but also the olfactory nerve and the olfactory nerve centers in the brain," comments Pierre-Marie Lledo, CNRS scientist, head of the Perception and Memory Unit (Institut Pasteur/CNRS), and co-author of the study.

"Another key finding from this study emerged from an observation of animal models, which revealed that once the virus enters the olfactory bulb, it spreads to other nerve structures, where it induces a major inflammatory response," explains Hervé Bourhy, head of the Lyssavirus Epidemiology and Neuropathology Unit at the Institut Pasteur and co-author of the study. Infection of the olfactory neurons may therefore provide a gateway to the brain and explain why some patients develop various psychological clinical signs (anxiety disorders, depression) or those of a neurological nature (cognitive decline, susceptibility to developing a neurodegenerative disease), for which further studies are necessary.

Marc Lecuit, head of the Biology of Infection Unit (Institut Pasteur, Inserm, Université de Paris, AP-HP) and co-author of the study concludes: "According to our results, loss of smell in COVID-19 may persists for several months in some patients and this persistence of clinical signs may be attributed to the persistence of the virus and inflammation in the olfactory mucosa." These observations should be used to adapt the diagnosis and management of long-term COVID-19 signs.

In summary, this study has led to the following 4 key findings:

* The virus can be detected by nasal brushing in instances where it is not detected by swabs;

* SARS-CoV-2 may persist in the olfactory epithelium for several months;

* SARS-CoV-2 infects sensory neurons and prompts immune cell recruitment in the sensory organ;

* SARS-CoV-2 may cause persistent inflammation of the olfactory epithelium and the olfactory nervous system.

Peri-implantitis, a condition where tissue and bone around dental implants becomes infected, besets roughly one-quarter of dental implant patients, and currently there's no reliable way to assess how patients will respond to treatment of this condition.

To that end, a team led by the University of Michigan School of Dentistry developed a machine learning algorithm, a form of artificial intelligence, to assess an individual patient's risk of regenerative outcomes after surgical treatments of peri-implantitis.

The algorithm is called FARDEEP, which stands for Fast and Robust Deconvolution of Expression Profiles. In the study, researchers used FARDEEP to analyze tissue samples from a group of patients with peri-implantitis who were receiving reconstructive therapy. They quantified the abundance of harmful bacteria and certain infection fighting immune cells in each sample.

Patients who were at low risk for periodontal disease showed more immune cells that were highly adept at controlling bacterial infections, said Yu Leo Lei, senior author and assistant professor of dentistry.

The team was surprised that the types of cells associated with better outcomes for implant patients challenge conventional thinking, said Lei, who also has an appointment at the Rogel Cancer Center.

"Much emphasis has been placed on the immune cell types that are more adept at wound healing and tissue repair," he said. "However, here we show that immune cell types that are central to microbial control are strongly correlated with superior clinical outcomes.

"Surgical management can reduce bacterial burdens across all patients, however, only the patients with more immune cell subtypes for bacterial control can suppress the recolonization of pathogenic bacteria and show better regenerative outcomes."

Dental implant-supported crowns offer esthetic, functional and natural-feeling tooth replacements, and the market is estimated to reach $6.8 billion by 2024. Dental implants have transformed reconstructive options, but the emerging endemic of peri-implantitis has severely compromised the long-term success of implant dentistry, the researchers said.

Peri-implantitis can lead to progressive bone loss, bleeding, pus and eventual loss of the dental implants and associated crowns or dentures that they support. Replacement of a new dental implant at the previously damaged site is often challenging because of poor bone quality and delayed healing. Preventive implant maintenance and long-term management of peri-implantitis becomes part of the routine practice after implant reconstruction.

"Regenerative therapy for peri-implantitis is expensive and treatment outcomes are unpredictable," said first author Jeff Wang, U-M clinical assistant professor and principal investigator for the regenerative treatment of peri-implantitis clinical trial. "It would be very helpful if we could use the information to determine the best course of treatment, or maybe we'd decide that the more sensible option would be to replace an old implant with a new one, despite the challenge to rebuild the bone."

In the future, it may be possible to predict the risk of peri-implantitis before a dental implant is placed, he said. More human clinical trials are required before FARDEEP is ready to be used widely by clinicians.

"However, this proof-of-concept study offers a personalized approach to identify the types of patients that better respond to regenerative therapies," said co-author William Giannobile, a professor of oral medicine, infection and immunity, and dean of the Harvard School of Dental Medicine. Previously, Giannobile was at the U-M School of Dentistry.

An international research team led by the University of Cologne has succeeded for the first time in connecting several atomically precise nanoribbons made of graphene, a modification of carbon, to form complex structures. The scientists have synthesized and spectroscopically characterized nanoribbon heterojunctions. They then were able to integrate the heterojunctions into an electronic component. In this way, they have created a novel sensor that is highly sensitive to atoms and molecules. The results of their research have been published under the title 'Tunneling current modulation in atomically precise graphene nanoribbon heterojunctions' in Nature Communications. The work was carried out in close cooperation between the Institute for Experimental Physics with the Department of Chemistry at the University of Cologne, as well as with research groups from Montreal, Novosibirsk, Hiroshima, and Berkeley. It was funded by the German Research Foundation (DFG) and the European Research Council (ERC).

The heterojunctions of graphene nanoribbons are just one nanometre - one millionth of a millimetre - wide. Graphene consists of only a single layer of carbon atoms and is considered the thinnest material in the world. In 2010, researchers in Manchester succeeded in making single-atom layers of graphene for the first time, for which they won the Nobel Prize. 'The graphene nanoribbon heterojunctions used to make the sensor are each seven and fourteen carbon atoms wide and about 50 nanometres long. What makes them special is that their edges are free of defects. This is why they are called "atomically precise" nanoribbons,' explained Dr Boris Senkovskiy from the Institute for Experimental Physics. The researchers connected several of these nanoribbon heterojunctions at their short ends, thus creating more complex heterostructures that act as tunnelling barriers.

The heterostructures were investigated using angle-resolved photoemission, optical spectroscopy, and scanning tunnelling microscopy. In the next step, the generated heterostructures were integrated into an electronic device. The electric current flowing through the nanoribbon heterostructure is governed by the quantum mechanical tunnelling effect. This means that under certain conditions, electrons can overcome existing energy barriers in atoms by 'tunnelling', so that a current then flows even though the barrier is greater than the available energy of the electron.

The researchers built a novel sensor for the adsorption of atoms and molecules from the nanoribbon heterostructure. The tunnel current through the heterostructure is particularly sensitive to adsorbates that accumulate on surfaces. That is, the current strength changes when atoms or molecules, such as those of gases, accumulate on the surface of the sensor. 'The prototype sensor we built has excellent properties. Among other things, it is particularly sensitive and can be used to measure even the smallest amounts of adsorbates,' said Professor Dr Alexander Grüneis, head of a research group at the Institute of Experimental Physics.

By Karina Ninni | Agência FAPESP – A study of 92 adolescents conducted in Brazil suggests girls are more likely than boys to develop metabolic alterations associated with obesity, such as high blood pressure and excessive blood levels of cholesterol and triglycerides (dyslipidemia).

The study was conducted with FAPESP’s support by scientists affiliated with the University of São Paulo’s Biomedical Sciences Institute (ICB-USP) and the Medical School of Santa Casa de Misericórdia de São Paulo (FCM-SCMSP). The findings are reported in an article in the journal Frontiers in Nutrition.

According to the authors, the obese girls displayed a pattern of lipid profile alterations not seen in girls without obesity and a higher propensity to develop cardiovascular disease in adulthood. “We found that girls have a much greater tendency to undergo the alterations typical of obesity, such as elevated blood pressure and dyslipidemia. In our study, they had augmented levels of triglycerides and LDL, so-called ‘bad cholesterol’, while HDL, ‘good cholesterol’, was lower than in eutrophic [normal weight] girls,” said Estefania Simoes, first author of the article.

The lipid profile of the obese boys included in the study displayed no significant differences from that of normal-weight boys, according to the researchers.

Childhood obesity is a growing concern among health authorities and scientists in the field. The World Health Organization (WHO) estimates that some 340 million children aged 5-19 worldwide were overweight or obese in 2016. It is well known that childhood obesity is associated with a higher likelihood of metabolic disorders and cardiovascular disease in adulthood.

A substantial amount of research shows this, but the differences between boys and girls in terms of the effects of obesity have not been studied in depth. “We compared obese and non-obese girls and boys aged 11-18, simultaneously addressing anthropometrics, lipid and lipoprotein profile, and hormone and neuropeptide levels, with a special emphasis on sex-dependent responses. To our knowledge, this is the first study to take this multifactor approach,” Simoes said.

The study was funded by FAPESP via two projects: “Cerebral anatomy, inflammatory mediators and appetite regulatory hormones in obese pediatric patients: A neurobiological study of obesity” and “Systemic inflammation in cachectic cancer patients: Mechanisms and therapeutic strategies, a translational medicine approach”.

Collaborations

The study was conducted in collaboration with Ricardo Riyoiti Uchida, a neurologist and psychiatrist who acted as principal investigator and recruited the 92 participants at the Child Obesity Outpatient Clinic of the Santa Casa de Misericórdia Hospital in São Paulo. Uchida uses neuroimaging to try to find out whether there are alterations in the brain regions associated with satiety and appetite in obese subjects. “An article on this topic is about to be published, focusing on characterization of the central nervous system in obese patients. Uchida has been studying adolescent obesity for many years,” Simoes said.

The SCMSP team took the subjects’ blood pressure and collected blood samples to measure fasting serum concentration of total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), very-low-density lipoprotein cholesterol (VLDL), and triglycerides (TG).

The researchers also looked for binge eating patterns and addiction to high-sugar and high-fat foods using special-purpose questionnaires. They also measured neuropeptides linked to neuro-humoral alterations and detected significant alterations in obese subjects. Neuropeptides are released in response to peripheral signals such as hormones to regulate appetite and energy balance. “In addition, leptin and insulin interact with neuropeptides NPY, MCH and α-MSH, not only regulating appetite but also activating the sympathetic nervous system, which may contribute to the high blood pressure associated with obesity,” Simoes said.

The new data on differences between girls’ and boys’ hormone, cytokine and neuropeptide profiles points to the need for personalized treatment. “However much we may want to design a single therapeutic strategy based on drugs or food supplements, our findings show that girls and boys shouldn’t be treated alike even if they have the same weight and age, because their organisms respond to treatment differently,” Simoes said.

Fruitful research

According to Joanna Correia-Lima, second author of the article, two other papers were written using the data collected from the same group of volunteers. The first, published in the International Journal of Obesity, focuses on characterizing the inflammatory process since systemic chronic inflammation is significant in obese subjects.

“At the laboratory headed by Professor Marília Seelaender, a co-author with us of both articles, we’ve long been studying a disorder that’s the opposite of obesity: cachexia [extreme weight loss and muscle wasting, frequently in cancer and AIDS patients]. Systemic inflammation plays a key role in both,” Correia-Lima said. “We first focused on inflammation and then on the role of hormones and how they relate to the predisposition to develop cardiovascular disease.”

Most scientific publications on childhood obesity, she added, focus on a single specific alteration, such as inflammation or a hormone, for example, or on a specific consequence of obesity such as high blood pressure. “Our research set out to connect the dots. We have a large cohort and a large amount of data, so we can characterize the links in this group, showing how all alterations in the obese organism are associated. The most important aspect of our work is showing these links,” Correia-Lima said.

According to Simoes, it was the researchers’ statistical analysis of the data that pointed to these links. “Elevated levels of hormones such as insulin and leptin [the satiety hormone] may be the cause of high blood pressure, for example,” she said. “This kind of information should be taken into consideration when treating obesity. Physicians often prescribe anti-inflammatory drugs, which can indeed mitigate one aspect of the disease, but the treatment will be more complete if you know about other contributing factors.”

Obesity is a multifactor disease, and treatment cannot be one-size-fits-all. Diet and exercise are important, but medication may also be needed, as well as surgical intervention and psychotherapy. “Questionnaire-based assessments point to eating disorders at the psychological level among these girls and boys,” Simoes said. “However much we show that there are alterations in neuropeptides and hormones, as well as high blood pressure, inflammation and so on, ultimately the child doesn’t just have an organic problem but a psychological one. Hence the importance of childhood obesity studies, to assist early diagnosis and attempt timely treatment before adult complications set in.”

Asian students and faculty have long been a cornerstone of science in the U.S., drawn by the promise of collaboration and cutting-edge research. However, the Asian community is facing increased racist attacks and scrutiny from the government. A cover story in Chemical & Engineering News, the weekly newsmagazine of the American Chemical Society, explores how Asian scientists are reassessing their futures in the U.S.

In the wake of the COVID-19 pandemic, racist attacks against the Asian community in the U.S. have increased notably, with nearly 4,000 incidents reported between March 2020 and February 2021. Some attribute this to former President Donald Trump's rhetoric about the pandemic originating in China, writes Senior Editor Andrea Widener. Beyond the pandemic, the Trump administration implemented policies that hinder collaborations with researchers in China, including the China Initiative launched by the U.S. Department of Justice in 2018. Initiatives like this have placed Asian researchers under increased scrutiny and suspicion, and many are still in place despite the new presidential administration. Even before Trump and the coronavirus, Asian scientists have said they struggled with feeling welcome in the U.S. due to stereotypes and perceived cultural differences.

These challenging circumstances have led Asian scientists to change how they collaborate with other researchers, recruit students to their labs and choose a career path. Some scientists of Chinese origin in the U.S. have been targeted by investigations from the China Initiative, and they say it's "like walking on eggshells" when disclosing collaborators and funding sources to the government. Visa restrictions and a hostile political climate are also making it harder to recruit international students and for the students to remain in the U.S. after graduation. Some scientists are choosing to return to their countries of origin or seek new opportunities in other parts of the world. While the Biden administration hopes to revise immigration policies and retain U.S.-trained international scientists, the Asian community is fighting for more awareness and tolerance despite an uncertain future.

TAMPA, Fla. -- Melanocytic nevi, or moles, are nonmalignant growths that arise from pigment producing cells of the skin. They are mostly found in sun-exposed areas; however, they also can be found in sun-protected areas, such as the palms, soles of feet and nail beds, where they are known as acral nevi. While the mutation profile of nevi in sun-exposed areas is well understood, less is known about the genes that are commonly mutated in acral nevi. And while a subset of melanoma of sun-exposed skin arises in nevi, the link between nevi and melanoma in acral skin is poorly understood. In a new study published in JAMA Dermatology, Moffitt Cancer Center researchers report on the mutation profile of acral nevi and describe differences between acral nevi and acral melanoma.

Melanoma is one of the most common types of cancer, with an estimated 100,000 new cases diagnosed in 2020 in the United States. Acral melanoma is a subtype on nonsun-exposed areas of the skin and is not linked to ultraviolet radiation exposure. Despite both conditions being derived from pigment-producing melanocytes, melanoma and acral melanoma differ in several ways. Patients with acral melanoma tend to have a poorer response to treatment and a higher mortality rate than patients with typical melanoma. Additionally, the two types of melanoma differ in their mutation profile.

Approximately 30% of malignant melanoma are derived from nonmalignant melanocytic nevi. One of the most common genetic alterations in melanocytic nevi, as well as melanoma, are mutations in the BRAF gene.

To determine if there is a genetic link between acral nevi and acral melanoma, Moffitt researchers performed a genetic analysis on 50 acral nevi from 49 patients - 19 males and 30 females. They discovered that unlike acral melanoma, activating mutations in the BRAF gene were very common in the nevi, with 86% of patients having a mutation in the BRAF gene. Additionally, 10% of the patients had activating mutations in the NRAS gene, which were mutually exclusive from BRAF mutations.

These observations demonstrate that acral nevi and acral melanoma have different mutation patterns. "Acral nevi demonstrated a mutational spectrum very similar to that of nevi on sun-exposed skin, suggesting that acral nevi are unlikely to be the precursor lesion for the majority of acral melanomas," said Keiran Smalley, Ph.D., study author and director of Moffitt's Donald A. Adam Melanoma and Skin Cancer Center of Excellence. "We hope our findings will lead to a better understanding of how acral melanoma develops."

"This is the largest series of acral nevi that have been sequenced to date, and the results were surprising to me," said Jane Messina, M.D., senior study author and senior member in the Department of Cutaneous Oncology. "Additionally, most of our patients were white/European in origin, while previous studies were mostly performed in Asian populations where there is a much higher frequency of acral nevi. The frequent presence of a mutation with a strong link to sun exposure suggests that even acral skin may be subject to the ravages of the sun."

URBANA, Ill. - Gut health is having a moment, with sales of fermented foods such as kefir, kombucha, and kimchi steadily on the rise. The benefits of "good bacteria" in fermented foods and supplements go well beyond the gut, moderating immune responses, heart health, weight, and even mood. But do products hold up to the claims on their labels?

A new study from the University of Illinois and The Ohio State University examined bacterial content of five brands of kefir, a fermented dairy beverage often likened to drinkable yogurt. The research showed the majority of products overstated bacterial density and contained species not included on the label.

"Our study shows better quality control of kefir products is required to demonstrate and understand their potential health benefits. It is important for consumers to know the accurate contents of the fermented foods they consume," says Kelly Swanson, the Kraft Heinz Company Endowed Professor in Human Nutrition in the Department of Animal Sciences and the Division of Nutritional Sciences at Illinois.

Label-reading consumers might be familiar with typical units listed on fermented products: colony-forming units per gram (cfu/g). Generally, the more bacteria per gram, the more likely they are to provide health benefits.

Most companies guarantee minimum counts of at least a billion bacteria per gram, with many claiming up to 10 or 100 billion. Because food-fermenting microorganisms have a long history of use, are non-pathogenic, and do not produce harmful substances, they are considered "Generally Recognized As Safe" (GRAS) by the U.S. Food and Drug Administration and require no further approvals for use. That means companies are free to make claims about bacteria count with little regulation or oversight.

Swanson and his colleagues purchased two bottles each of five major kefir brands and brought them back to the lab. There, they cultured and counted bacterial cells and sequenced DNA to identify bacterial species.

Only one product delivered 10 billion bacteria per gram, the quantity promised on its label. All the others fell short of their claims, delivering between 10 million (in a product promising 100 billion) and one billion (in a product promising 10 billion).

"Just like probiotics, the health benefits of kefirs and other fermented foods will largely be dependent on the type and density of microorganisms present," Swanson says. "With trillions of bacteria already inhabiting the gut, billions are usually necessary for health promotion. These product shortcomings in regard to bacterial counts will most certainly reduce their likelihood of providing benefits."

When the research team identified bacteria in their samples against the ones listed on the label, there were distinct discrepancies. Some species were missing altogether, while others were present but unlisted. All five products contained, but didn't list, Streptococcus salivarius. And four out of five contained Lactobacillus paracasei.

Both species are common starter strains for the production of yogurts and other fermented foods. Because they are relatively safe and may contribute to the health benefits of fermented foods, Swanson says it's not clear why they aren't listed on the labels.

Although the study only tested five products, Swanson suggests the results are emblematic of a larger issue in the fermented foods market.

"Even though fermented foods and beverages have been important components of the human food supply for thousands of years, few well-designed studies on their composition and health benefits have been conducted outside of yogurt. Our results underscore just how important it is to study these products," he says. "And given the absence of regulatory scrutiny, consumers should be wary and demand better-quality commercial fermented foods."

East Hanover, NJ. May 12, 2021. A team of specialists in regenerative rehabilitation conducted a successful pilot study investigating micro-fragmented adipose tissue (MFAT) injection for rotator cuff disease in wheelchair users with spinal cord injury. They demonstrated that MFAT injection has lasting pain-relief effects. The article, "A pilot study to evaluate micro-fragmented adipose tissue injection under ultrasound guidance for the treatment of refractory rotator cuff disease in wheelchair users with spinal cord injury," (doi: 10.1080/10790268.2021.1903140) was published ahead of print on April 8, 2021, by the Journal of Spinal Cord Medicine.

The authors are Trevor Dyson-Hudson, MD, and Nathan Hogaboom, PhD, at Kessler Foundation; and Gerard Malanga, MD, a founder of the New Jersey Regenerative Institute and visiting scientist at Kessler Foundation, and Chris Cherian, MD, of Rutgers New Jersey Medical School. The study was conducted at the Derfner-Lieberman Laboratory for Regenerative Rehabilitation Research in the Center for Spinal Cord Injury Research at Kessler Foundation.

Shoulder pain is a common occurrence among wheelchair users with spinal cord injury because they rely solely on their upper limbs to perform everyday tasks. Often, pain is caused by soft-tissue injuries such as damage to rotator cuff tendons. Many non-surgical therapies for shoulder pain exist, including pain medication, physical therapy, and equipment modifications, but these have shown limited efficacy. Persistent shoulder pain can significantly lessen quality of life, and if conservative therapies fail, shoulder surgery is frequently the only option, which comes with its own set of risks and potential setbacks.

In this single-group pilot study, researchers explored the efficacy of a minimally invasive biological intervention involving an ultrasound-guided injection of MFAT, which harbors a potential source of bioactive and regenerative components for orthopedic conditions and may provide cushioning that can improve function and alleviate pain caused by rotator cuff injuries.

Ten wheelchair users with chronic spinal cord injury who had moderate-to-severe shoulder pain for more than six months caused by refractory rotator cuff disease participated in the study. All received an injection of MFAT and were evaluated at six and 12 months after treatment. Evaluation metrics included the 11-point Numerical Rating Scale, the Wheelchair User's Shoulder Pain Index, Brief Pain Inventory pain interference items (BPI-17), Patient Global Impression of Change, ultrasound and physical examinations, and adverse events.

The results were encouraging, according to Drs. Hogaboom and Dyson-Hudson, co-directors of the Derfner-Lieberman Laboratory. Nearly 80 percent saw a meaningful decrease in pain symptoms, and all but one reported some improvement in pain and function. Moreover, scores declined steadily over the first three months for all metrics, and over the entire year for the BPI-17 metric, suggesting that this intervention has long-lasting effects. There were no significant adverse events.

"These results show that the minimally invasive injection of micro-fragmented adipose tissue is a safe and efficacious option for wheelchair users with shoulder pain caused by rotator cuff disease," said Dr. Malanga. "Based on the success of our study, a randomized controlled study with a larger number of subjects has been initiated in this patient population through funding from the New Jersey Commission for Spinal Cord Research," he added. " We feel there is great potential for this therapy to help people with shoulder pain manage their symptoms and improve their quality of life. We credit our success to the Derfner Foundation for providing the initial funding to pursue this promising intervention, and acknowledge the ongoing efforts of the Alliance for Regenerative Rehabilitation Research & Training to advance the fields of rehabilitation sciences and regenerative medicine."

New guidelines for coral reef restoration aiming to reduce the risk of flooding in tropical coastal communities have been set out in a new study that simulated the behavior of ocean waves travelling over and beyond a range of coral reef structures. Published in Frontiers in Marine Science, these guidelines hope to optimize restoration efforts not only for the benefit of the ecosystem, but also to protect the coast and people living on it.

"Our research reveals that shallow, energetic areas such as the upper fore reef and middle reef flat, typically characterized by physically-robust coral species, should be targeted for restoration to reduce coastal flooding," says Floortje Roelvink, lead author on the paper and researcher at Deltares, a Dutch research institute. "This will benefit both coral ecosystems and human coastal populations that rely on them for tourism, fisheries, and recreation."

Important structures

Coral reefs help to sustain the economy of 500 million people in tropical coastal communities and can offer protection from wave-driven flooding and coastal erosion, especially in the face of climate change. Reef restoration, which involves coral planting and reef management to improve the health, abundance, and biodiversity of the ecosystem, has been suggested as a way of reducing flood risk.

"Our research can help guide the design of coral reef restorations to best increase the resiliency of coastal communities from flooding," said Curt Storlazzi, U.S. Geological Survey research geologist and project lead. "Such information can increase the efficiency of coral restoration efforts, assisting a range of stakeholders in not only coral reef conservation and management, but also coastal hazard risk reduction."

"Although we know that coral reefs can efficiently attenuate ocean wave energy and reduce coastal flooding, knowledge of specifically where to locate and design coral reef restorations on specific types of reefs is lacking," explains Ap van Dongeren, coastal morphology specialist at Deltares and project co-lead. "We were keen to fill this knowledge gap because the costs and practical constraints of reef recovery efforts necessitate an approach to design and restoration that produces the most benefit for all."

Reef by design

To first understand the range of naturally occurring reef shapes, such as fringing reefs, straight sloping reefs, convex reefs and reefs with an offshore shelf, the researchers analyzed a database of over 30,000 coral reef profiles across the U.S., including those in the Mariana, Hawaii, and Virgin Islands. Using these reef profiles, they numerically "designed" reef restorations to be both feasible from an operational and ecological perspective and to have an expected beneficial impact on coastal flooding.

The researchers established that reef restorations should not be placed too deep because of operational constraints and limit on the wave reduction efficiency. Restorations should also not be too shallow, to prevent the drying of reef restorations and reef degradation due to thermal intolerance.

Different types of coral restorations were also investigated - "green", entailing solely outplanting corals, or "gray-green hybrid" restorations, entailing emplacement of structures (such as ReefBalls) and then outplanting corals on top of them. The team then used a numerical model to simulate waves travelling over both the restored and unrestored coral reef profiles to see how far those waves ran up the coast, providing an indication of the effect of the different reef restorations on coastal flooding.

"We hope this study will motivate others to continue and expand on this research, among others by conducting field and laboratory experiments to validate our findings," concludes Roelvink.

A scientist from HSE University has developed an image recognition algorithm that works 40% faster than analogues. It can speed up real-time processing of video-based image recognition systems. The results of the study have been published in the journal Information Sciences.

Convolutional neural networks (CNNs), which include a sequence of convolutional layers, are widely used in computer vision. Each layer in a network has an input and an output. The digital description of the image goes to the input of the first layer and is converted into a different set of numbers at the output. The result goes to the input of the next layer and so on until the class label of the object in the image is predicted in the last layer. For example, this class can be a person, a cat, or a chair. For this, a CNN is trained on a set of images with a known class label. The greater the number and variability of the images of each class in the dataset are, the more accurate the trained network will be.

If there are only a few examples in the training set, the additional training (fine-tuning) of the neural network is used. CNN is trained to recognize images from a similar dataset that solves the original problem. For example, when a neural network learns to recognize faces or their attributes (emotions, gender, age), it is preliminary trained to identify celebrities from their photos. The resulting neural network is then fine-tuned on the available small dataset to identify the faces of family or relatives in home video surveillance systems. The more depth (number) of layers there are in a CNN, the more accurately it predicts the type of object in the image. However, if the number of layers is increased, more time is required to recognize objects.

The study's author, Professor Andrey Savchenko of the HSE Campus in Nizhny Novgorod, was able to speed up the work of a pre-trained convolutional neural network with arbitrary architecture, consisting of 90-780 layers in his experiments. The result was an increase in recognition speed of up to 40%, while controlling the loss in accuracy to no more than 0.5-1%. The scientist relied on statistical methods such as sequential analysis and multiple comparisons (multiple hypothesis testing).

"The decision in the image recognition problem is made by a classifier -- a special mathematical algorithm that receives an array of numbers (features/embeddings of an image) as inputs, and outputs a prediction about which class the image belongs to. The classifier can be applied by feeding it the outputs of any layer of the neural network. To recognize "simple" images, the classifier only needs to analyse the data (outputs) from the first layers of the neural network.

There is no need to waste further time if we are already confident in the reliability of the decision made. For "complex" pictures, the first layers are clearly not enough -- you need to move on to the next. Therefore, classifiers were added to the neural network into several intermediate layers. Depending on the complexity of the input image, the proposed algorithm decided whether to continue recognition or complete it. Since it is important to control errors in such a procedure, I applied the theory of multiple comparisons: I introduced many hypotheses, at which intermediate layer to stop, and sequentially tested these hypotheses," explained Professor Savchenko.

If the first classifier already produced a decision that was considered reliable by the multiple hypothesis testing procedure, the algorithm stopped. If the decision was declared unreliable, the calculations in the neural network continued to the intermediate layer, and the reliability check was repeated.

As the scientist notes, the most accurate decisions are obtained for the outputs of the last layers of the neural network. Early network outputs are classified much faster, which means it is necessary to simultaneously train all classifiers in order to accelerate recognition while controlling loss in accuracy. For example, so that the error due to an earlier stop is no more than 1%.

"High accuracy is always important for image recognition. For example, if a decision in face recognition systems is made incorrectly, then either someone outside can gain access to confidential information or conversely the user will be repeatedly denied access, because the neural network cannot identify him correctly. Speed ??can sometimes be sacrificed, but it matters, for example, in video surveillance systems, where it is highly desirable to make decisions in real time, that is, no more than 20-30 milliseconds per frame. To recognize an object in a video frame here and now, it is very important to act quickly, without losing accuracy," said Professor Savchenko.

The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.

While the AI model was used on a retrospective cohort of patient data collected during the pandemic's first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.

The researchers say the approach, where each patient's data were analysed day-by-day instead of only on admission, could be used to improve guidelines in clinical practice going forward. It could be applied to potential future waves of the pandemic and other diseases treated in similar clinical settings.

This is the first study that examines daily COVID-19 patient data, using AI to understand the clinical response to the rapidly changing needs of patients in ICUs. Led by a team from Imperial College London and Royal Brompton and Harefield hospitals for the COVID-ICU Consortium, the research is published today in the journal Intensive Care Medicine.

First author and clinical science lead Dr Brijesh Patel, from Imperial's Department of Surgery & Cancer and senior intensivist at Royal Brompton Hospital, said: "Most studies look at the health of a patient on admission to ICU, and whether they were discharged or sadly died. In ICU there is a huge amount of information which we use at the bedside to manage patients on a day-by-day basis, and our study focuses on how the patients' state changed daily.

"This helped focus our attention on which specific parameters matter the most, and how the importance of each parameter changes over time. This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works."

The prone position is used in ICUs to help improve blood oxygenation in people with severe acute respiratory distress syndrome, and has been used extensively during the pandemic. However, proning did not help all COVID-19 patients and, when used in patients who will not benefit, can delay the start of other sequential treatments like using extracorporeal membrane oxygenation (ECMO), a life-support machine that takes over for the heart and lungs to oxygenate blood and pump it round the body. Better analysis of proning implementation and prediction of failed proning could lead to more personalised applications.

Dr Patel said: "ECMO is currently the last resort for many patients, after all other less invasive interventions such as prone position have failed, but it has associated risks. Over 20% of all patients on a mechanical ventilator were referred to and received management advice from one of the five national ECMO centres. Patients appropriately placed early onto ECMO show better outcomes. However, only 4% of referred patients received ECMO, which is due to a number of reasons, but one of which could have been delays in assessment of responsiveness to interventions like prone position.

"Advanced analytics to enable tracking of disease allows patient care to be streamlined so that the window of opportunity for any intervention is not missed. The data from this national evaluation enabled us not only to examine how our management decisions affected disease course but importantly where we could improve."

The new findings show that the AI model identified factors that determined which patients were likely to get worse and not respond to interventions like proning. The researchers found that during the first wave of the pandemic, patients with blood clots or inflammation in the lungs, lower oxygen levels, lower blood pressure, and lower lactate levels were less likely to benefit from being proned. Overall, proning improved oxygenation in only 44% of patients.

Senior author and data science lead Professor Aldo Faisal, Director of Imperial's Centre in AI for Healthcare at the Departments of Computing and Bioengineering said: "In the ever-changing landscape of the pandemic, clinicians are constantly learning and adapting to patient needs, which themselves change every day. Critically, we have set up a standing digital service evaluation of UK ICUs, getting day-by-day treatment data from ICUs across the nations. Our machine learning tool could help track patient progress in real time and help inform ICU guidelines by filling the gaps of patient care - reflecting back to clinicians to identify best practice quickly and benefit from sharing.

"More than one year on, we're still learning how the course of COVID-19 affects the body, and how this can change day-by-day. Data science and the daily data feeds from ICUs across the country help us learn much faster how best to treat individual patients based on their daily symptoms and needs."

The researchers analysed data from 633 mechanically ventilated COVID-19 patients across 20 UK ICUs during the first wave of the COVID-19 outbreak (1 March - 31 August 2020). They examined the importance of factors associated with disease progression, like blood clots and inflammation in the lungs, as well as treatments given and whether the patient ultimately died or was discharged.

They used this data, which was collected daily by legions of medical students, nurses, doctors, audit, research and data staff, to design and train the AI tool which then made predictions on factors that determine outcomes.

Dr Patel added: "Our findings could help inform ICU guidelines and clinicians going forward, and AI could play a pivotal role in how we learn about and adapt to COVID-19 disease progression on a daily basis. Our mantra within the NHS is to innovate and improve patient care and this form of national evaluation helps us to understand our own biases as clinicians. We hope our findings will help and encourage more research to be undertaken that focuses on the daily needs of patients."

The researchers continue to collect patient data and are currently analysing findings from the second wave of the pandemic. They note that in the first wave there were limited drug treatments available, so more COVID-19 patients may have been triaged directly to ICU for breathing support. However, in the second wave, proven treatments such as steroids and tociluzimab, pioneered by other Imperial researchers, were more widely available, so those who progressed to ICU had a different disease profile, as they were patients who were inherently resistant to these initial drug treatments.

Professor Faisal said: "Findings from the first and second wave will differ because approaches to treating patients in ICU evolved with the pandemic. However, our AI tool kit is already set up across UK ICUs to monitor daily patient data and adapt to the changing situation."

Alexandria, Va., USA -- Carbon dioxide (CO2) is a byproduct of human metabolism and exists in high levels in exhaled air, and is therefore often used as a proxy for indoor air quality. The study "Ventilation Assessment by Carbon Dioxide Levels in Dental Treatment Rooms," published in the Journal of Dental Research (JDR), evaluated CO2 levels in dental operatories and determined the accuracy of using CO2 levels to assess ventilation rate in dental clinics.

Researchers at the University of Rochester, Eastman Institute for Oral Health, N.Y., USA, conducted CO2 concentration and ventilation rate assessments in 10 closed dental treatment rooms with varying air change rates by ventilation. Mechanical ventilation rate in air change per hour was measured with an air velocity sensor and air flow balancing hood.

The results showed that CO2 level in dental treatment rooms could be measured with a simple consumer-grade CO2 sensor, and that ventilation rate could be determined by either natural or experimental buildup of CO2 levels in dental settings. Assessing CO2 levels allows dental care professionals to conveniently and accurately calculate the ventilation rates in their offices and help them to devise effective strategies for ventilation improvement. They also demonstrated that ventilation rates in air change per hour could be accurately assessed by observing CO2 levels after a simple mixing of household baking soda and vinegar.

"Accurate measurements of ventilation rate in dental settings are important for risk assessment and for risk mitigation, especially during the COVID-19 pandemic," said JDR Editor-in-Chief Nicholas Jakubovics, Newcastle University, England. "This study demonstrates the precision of a practical tool that will enable dental care professionals to conveniently and accurately monitor CO2 levels and assess the ventilation rates in order to devise a pragmatic and effective strategy for ventilation improvement in their work environment."

Roads can be barriers to wildlife of all sorts, and scientists have studied road impacts on animals ranging from Florida panthers and grizzly bears to box turtles, mice, rattlesnakes and salamanders.

But much less is known about the impact of roads on pollinating insects such as bees and to what extent these structures disrupt insect pollination, which is essential to reproduction in many plant species.

In a paper published online May 10 in the Journal of Applied Ecology, University of Michigan researchers describe how they used fluorescent pigment as an analog for pollen. They applied the luminous pigment to the flowers of roadside plants to study how roads affected the movement of pollen between plants at 47 sites in Ann Arbor, Michigan.

The researchers found that plants across a road from pigment-added plants received significantly less pigment than plants on the same side of the road. The study also suggests relatively simple ways to reduce this road-barrier effect.

"Our study shows that roads and paths pose a significant barrier to bee movement and therefore substantially reduce pollen transfer," said study author Gordon Fitch, a doctoral candidate in the U-M Department of Ecology and Evolutionary Biology. His co-lead author is Chatura Vaidya, also an EEB doctoral candidate.

The study focused on two species of insect-pollinated flowering plants native to the region, wild bergamot (Monarda fistulosa) and threadleaf coreopsis (Coreopsis verticillata).

At each site, three potted plants were placed along the roadside on a warm, sunny morning. Luminous pigment was applied to the reproductive structures in the flowers of one plant (the "pigment-added" plant).

Then a second plant (the "across" plant) was placed across the road from the pigment-added plant, and the distance between the two plants was measured. Finally, a third plant (the "along" plant) was placed on the same side of the road as the pigment-added plant, at the same distance from the pigment-added plant as the "across" plants.

At most sites, both species of flowering plants were deployed in this fashion.

The researchers left the plants outside for the day, collected them in the evening, and brought them to a dark location. An ultraviolet flashlight was used to determine how patterns of pigment transfer varied, depending on whether the plants were located on the same side of the road or on opposite sides of the road.

To do this, the researchers counted the number of flowers on each plant that held pigment. Because wind and nonpollinating insects can sometimes transfer pigment, only flowers with pigment on their reproductive parts, not the petals, were counted.

Fitch and Vaidya found that being across the road reduced pigment transfer by 50% for the threadleaf coreopsis plants and by 34% for wild bergamot plants, compared to plants on the same side of the road.

"Ours is the first well-replicated study to examine how roads impact bee movement," Fitch said. "Moreover, we used an innovative technique relying on pigment as a pollen analog--rather than direct observation of insect behavior--which allowed us to collect data efficiently. As such, we are also the first to show that roads disrupt the movement of pollen between plants."

During the study, Fitch and Vaidya observed 65 insect visits to threadleaf coreopsis plants and 356 to wild bergamot plants. Ninety-seven percent of the visits were from bees.

Bees are indispensable pollinators, supporting both agricultural productivity and the diversity of flowering plants worldwide. In recent decades, both native bees and managed honeybee colonies have seen population declines blamed on multiple interacting factors including habitat loss, parasites and disease, and pesticide use.

Fitch and Vaidya found that reduced pigment transfer was driven by the size of the road, as well as the size of the bees: As the number of road lanes increased, or as the size of the bee decreased, the effect was greater.

Pigment transfer across roads with three or more lanes of traffic was rare for either plant species, they found, suggesting that medium-sized and large roads may impede the movement of bees sufficiently to impact foraging and pollination.

The researchers recommend the evaluation and implementation of strategies to make roads less of a barrier to pollinators--without spending huge sums of money to do so.

Wildlife crossing structures that have been used in North America and Europe to facilitate movement of animals through landscapes fragmented by roads include wildlife overpasses, bridges, culverts and pipes.

In a similar fashion, existing pedestrian overpasses could potentially be modified to help bees and other flying pollinators, simply by adding flower-containing planter boxes to the landscaping, Fitch said. He cautioned that such an approach is largely hypothetical and is untested.

Such measures could potentially dovetail with efforts in some cities to promote alternative modes of transportation and to reduce traffic accidents by using so-called road diets. This increasingly popular design strategy reduces the amount of a roadway dedicated to vehicular traffic through, for example, the addition of bicycle lanes or wider sidewalks.

In downtown Ann Arbor, recently installed examples of road diets include the protected, two-way bike lanes on William and Ashley streets.

"Since road width and traffic volume were major predictors of pigment transfer in our study, this suggests that road diets could also help reduce the effects of roads on flying insects, particularly if they included pollinator-friendly plantings," Fitch said.

(Boston)--Knee osteoarthritis (OA) is a global health problem. Almost half the adults over the age of 75 have some form of knee OA--one of the leading causes of disability worldwide. Because there is no cure for knee OA, current treatment relies on accurately identifying and staging the disease.

Using an Artificial Intelligence-based approach known as deep learning, researchers from Boston University School of Medicine (BUSM) have now identified a new measure to determine the severity of knee osteoarthritis--named "subchondral bone length" (SBL).

There are only a handful of proven imaging markers of knee OA. Currently, medical imaging tools such as Magnetic Resonance Imaging (MRI) or x-rays are used to examine the knee joint. "Our study identified a new imaging measure that has the potential to become a biomarker of knee OA," explained corresponding author explained corresponding author Vijaya B. Kolachalama, PhD, assistant professor of medicine at BUSM.

The researchers used thousands of knee MRI scans and defined SBL, a novel shape measure characterizing the extent of overlying cartilage and bone flattening and examined its relationship with radiographic joint space narrowing (JSN), concurrent pain and disability as well as subsequent partial or total knee replacement. They then estimated the odds ratios for each of these outcomes using relative changes in SBL. They found that SBL values for knees with joint space narrowing were consistently different from knees without JSN. They also found that greater changes of SBL from baseline were associated with greater pain and disability.

According to the researchers, this study has important clinical implications. "Our study identified SBL as a potentially useful measure of the bone morphology within the knee joint and showed that it varies with disease grade. SBL also has the potential to stage knee OA in the future," adds Kolachalama.

The researchers hope to study if SBL can be used for early detection of disease which can significantly impact patient care management.