Body

A new comparison of two breast-screening technologies has found that, for most women, digital breast tomosynthesis (DBT, also called 3D mammography) is superior to digital mammography for cancer detection and for reducing recall visits due to unclear or false findings.

The study's distinction, though, is in identifying women for whom DBT's advantage is less. Previous evidence had suggested that DBT would generally benefit all women.

"DBT is improving screening outcomes for the vast majority of women getting screening mammography. Unfortunately, it does not seem to benefit the 10% of women who have extremely dense breasts and who already experience the poorest of mammography outcomes today," said Kathryn Lowry, an assistant professor of radiology at the University of Washington School of Medicine.

Lowry and Yates Coley, an assistant investigator in biostatistics at Kaiser Permanente Washington Health Research Institute, were co-lead authors on the paper. It was published today by JAMA Network Open.

Digital mammography is a long-established X-ray diagnostic for breast cancer. DBT, known as three-dimensional mammography, was approved by the FDA in 2011, but clinicians did not have a corresponding medical billing code for it until 2015. Despite its recent emergence, several studies have associated DBT with better cancer detection and fewer recall visits than digital mammography, but few have been able to examine differences between subgroups of women.

In this research, the investigators analyzed more than 1.5 million breast exams from women ages 40-79, measuring cancers detected and patient recalls by age groups, breast densities, and by baseline exam versus subsequent exams.

The researchers found that DBT is most beneficial for women undergoing their first screening mammogram, associating that group with the largest improvements in recall reduction and cancer detection. In subsequent exams, most women experience one or both of these benefits with DBT. But for women whose breasts were categorized as "extremely dense," DBT did not make a difference in how many cancers were found or how many recalls these women had.

"This is a concern because this group of women is known to be at higher risk for cancer and higher risk for having cancers missed by mammography," Lowry said.

Beyond that subgroup, DBT's superior performance to digital mammography was broadly experienced, she added. Importantly, most women with dense breasts are in the heterogeneously dense category, and these women had the largest boost in cancer detection with DBT.

The findings accrue to research being pursued by members of the Breast Cancer Surveillance Consortium, a U.S. network of breast imaging registries. Coley conducted the analysis of data from the participating registries, which was pooled at Kaiser Permanente Washington.

"This study incorporated so much data and from sites that are geographically, racially, and ethnically diverse, and this allowed us to explore questions that other researchers have not," Coley said.

"Our findings can help providers and patients better decide how to make decisions about screening mammography. If a provider only has access to one or two DBT machines, it will help them determine which patients should get priority with those. If a patient has to pay more out of pocket or drive several hours to reach a provider who offers DBT, this can help them know whether they're likely to experience benefit," she added.

Today, FDA data suggests that about two-thirds of U.S. mammography facilities offer DBT. Insurance coverage, however, has lagged and is inconsistent across states.

Many women do not know the density of their breasts, Lowry said. There are four categories of density, each describing a different mix of glandular tissue, fibrous connective tissue, ducts, and fat. About half of all women have dense breasts, with a higher proportion of glandular and connective tissue; about 10% of all women have "extremely dense" breasts.

Nearly 40 states now mandate that women having mammograms receive some form of notification about the impact of breast density on breast cancer risk and detection of cancer.

Language of these laws varies by state, and not all women are informed of their specific density category, Lowry said. For instance, a woman may be told she has "dense breasts" but not specifically told she is among the 10% of women whose breasts are extremely dense.

When DBT was introduced, "we hoped that it would benefit these women," Lowry said, "but unfortunately this adds to the evidence that we still need to think about how to improve screening for this group."

A prior fracture is a well-documented risk factor for future fracture, with the risk highest in the two years following the sentinel fracture and subsequently declining with time. This early phase of particularly high risk is termed 'imminent risk'.

Currently, the widely used Fracture Risk Assessment Tool (FRAX®) algorithm [1] accounts for prior fracture, but not for the recency of the prior fracture in its calculation of individualised 10-year probability of hip and major osteoporotic fracture.

Now, an important new study by Kanis et al provides probability ratios that can be used to adjust conventional FRAX estimates of fracture probability by accounting for the site of a recent fracture [2].

The study used data from the Reykjavik Study fracture register that documented prospectively all fractures at all skeletal sites in a large sample of the population of Iceland. The authors determined fracture probabilities after a sentinel fracture (humeral, clinical vertebral, forearm and hip fracture) from the hazards of death and fracture. Fracture probabilities were computed for sentinel fractures occurring within the previous two years and for prior osteoporotic fractures irrespective of recency.

Professor John A. Kanis, first author and director of the Centre for Metabolic Bone Diseases at Sheffield University, stated:

"The probability ratios derived from this study will facilitate the more accurate categorization of risk in individuals who have sustained a recent fracture. It is important that we are able to identify individuals who are at very high risk so that appropriate treatment to prevent recurrent fractures can be initiated as early as possible."

Study findings include:

- Probability ratios to adjust 10-year FRAX probabilities of a major osteoporotic fracture for recent sentinel fractures were age dependent, decreasing with age in both men and women;

- Probability ratios varied according to the site of sentinel fracture, with higher ratios for hip and vertebral fracture than for humerus or forearm fracture;

- Probability ratios to adjust 10-year FRAX probabilities of a hip fracture for recent sentinel fractures were also age dependent, decreasing with age in both men and women, with the exception of forearm fractures.

Professor Cyrus Cooper, President of the International Osteoporosis Foundation and Professor of Musculoskeletal Science and Director of the MRC Lifecourse Epidemiology Unit, Universities of Southampton and Oxford, UK, added:

"There is a strong rationale for very early intervention immediately after a first fracture to avoid recurrent fractures, which place such a heavy burden on individuals and society as a whole. The possibility to adjust FRAX estimates for recency of fracture is therefore a significant development at many levels. For the physician it provides a new way to categorize a patient's risk, and to identify patients who may benefit from treatment with anabolic first regimens. Additionally, the probability adjustments will impact on FRAX-based guidance and be useful in health economic models that incorporate imminent risk."

It is anticipated that the results of this study will soon be applied to conventional FRAX estimates with appropriate programmes on a web-based platform.

Artificial intelligence (AI) could help to diagnose Alzheimer's faster and improve patient prognosis, a new study from the University of Sheffield has revealed.

The new research from the University of Sheffield's Neuroscience Institute examines how the routine use of AI in healthcare could help to relieve the time and economic impact that common neurodegenerative diseases, such as Alzheimer's and Parkinson's, put on the NHS.

The main risk factor for many neurological disorders is age, and with populations worldwide living longer than ever before, the number of people with a neurodegenerative disease is expected to hit unprecedented levels. The number of people living with Alzheimer's alone is predicted to treble to 115 million by 2050, posing a real challenge for the health system.

The new study, published in the journal Nature Reviews Neurology, highlights how AI technologies, such as machine learning algorithms, can detect neurodegenerative disorders - which cause part of the brain to die - before progressive symptoms worsen. This can improve patients' chances of benefitting from successful disease-modifying treatment.

Lead author of the study, Dr Laura Ferraiuolo from the University of Sheffield, said: "Most neurodegenerative diseases still do not have a cure and in many cases are diagnosed late due to their molecular complexity.

"Widespread implementation of AI technologies can help, for example, predict which patients showing mild cognitive impairment will go on to develop Alzheimer's disease, or how severely their motor skills will decline over time.

"AI-powered technologies can also be used to help patients communicate their symptoms remotely and in the privacy of their own homes, which will be an enormous benefit to patients with mobility issues."

Machine learning algorithms can be trained to recognise changes caused by diseases in medical images, patient movement information, speech recordings or footage showing patient behaviour, making the AI a valuable diagnostic aid.

For example, it can be used by trained professionals in radiology departments to analyse images more quickly and highlight critical results for an immediate follow-up.

Algorithms can also listen to patients' speech and analyse their vocabulary and other semantic features to assess their cognitive function. Machine learning can also use information contained within electronic health records or genetic profiles to suggest the best treatments for individual patients.

The study is the result of a long-term close collaboration between the biotech company BenevolentAI and a team of researchers at the University of Sheffield's Neuroscience Institute, Monika Myszczynska, Dr Richard Mead and Dr Guillaume Hautbergue.

First author of the paper, Monika Myszczynska from the University of Sheffield, said: "Using AI in clinical settings can lead to savings in the NHS by reducing the necessity of patients affected by debilitating diseases, like MND, to travel to clinic - which is very relevant during the current pandemic - and the time patients and physicians spend in clinic.

"It is too early to talk about outcomes in terms of treatments but, in this study, we examined how machine learning methods can be used to identify the best course of treatment for patients based on their disease progression or how it could be used to identify new therapeutic targets and drugs.

"Further research will now focus on the improvement of current diagnostic technologies, as well as a generation of new algorithms to make the use of AI in prognosis prediction and drug discovery a reality. AI feeds on data, therefore generation of international consortia and collaborations are the key to these future endeavours."

The research forms part of the work of the University of Sheffield's Neuroscience Institute, which aims to bring academics and scientists together from across varied specialties to translate scientific discoveries from the lab into pioneering treatments that will benefit patients living with neurodegenerative disorders.

Washington, DC - Antibiotic consumption per capita increased nearly 40 percent worldwide between 2000 and 2015, primarily driven by increases in low- and middle-income countries (LMICs) where lack of access to antibiotics exists alongside overuse. In an effort to balance appropriate access to antibiotics and stewardship across countries, the World Health Organization (WHO) introduced the Access, Watch, Reserve (AWaRe) framework in 2017, which classifies antibiotics based on their resistance potential. Monitoring global antibiotic use is an essential strategy in reducing the threat of antimicrobial resistance, and evidence is lacking on global antibiotic consumption based on AWaRe classification over time.

To measure these patterns, researchers calculated the proportion of antibiotic consumption in each AWaRe category as well as the ratio of Access to Watch antibiotics across 76 countries between 2000 and 2015 using quarterly national sample survey data from IQVIA. Results were expressed in defined daily doses per 1,000 inhabitants per day (DIDs).

"Antibiotic stewardship is one of the key pillars of improved use of antibiotics, which both ensures appropriate therapy and reduces the emergence and spread of antibiotic resistance. The AWaRe classification tool allows national and global inference about the overall quality of antibiotic use in a country. Evaluating the long-term changes in consumption, provides one mechanism for evaluating and establishing global consumption goals," said CDDEP Senior Fellow, Eili Klein.

The study found that global per capita antibiotic consumption increased 90.9 percent in Watch antibiotics and 26.2 percent in Access antibiotics between 2000 and 2015. The substantial increase in the proportion of Watch antibiotic consumption was driven primarily by low- and middle-income countries, which saw an increase of 165 percent (2.0 to 5.3 DIDs), compared to just 27.9 percent in high-income countries (HICs) (6.1 to 7.8 DIDs). The ratio of Access to Watch antibiotics varied considerably across countries, decreasing by 46.7 percent in LMICs (from 3.0 to 1.6) and 16.7 percent in HICs (from 1.8 to 1.5) over the study period. Of concern, the proportion of countries that met the WHO national-level target of at least 60 percent of a country's total antibiotic consumption comprising Access antibiotics, decreased from 76 percent in 2000 to 55 percent in 2015.

"The rapid increase in the use of Watch antibiotics, particularly in LMICs, poses a significant challenge for global health. While greater understanding of the reasons for this rise is needed at the country level, taken as a whole they paint a bleak future for antibiotic effectiveness," according to co-author and CDDEP Director, Ramanan Laxminarayan.

Overall, results indicate that the growth of Watch antibiotic consumption was nearly four times greater than that of Access antibiotic consumption over 15 years, which reflects challenges in improving appropriate antibiotic use and access to antibiotics, particularly in LMICs. Current estimates suggest that without policy changes, reaching the WHO national-level target by 2023 will be difficult to achieve for many countries. The study titled, "Assessment of WHO antibiotic consumption and access targets in 76 countries, 2000-15: an analysis of pharmaceutical sales data," was published on July 24, 2020 in The Lancet Infectious Diseases and is available online.

WHAT:
Two doses of an experimental vaccine to prevent coronavirus disease 2019 (COVID-19) induced robust immune responses and rapidly controlled the coronavirus in the upper and lower airways of rhesus macaques exposed to SARS-CoV-2, report scientists from the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health. SARS-CoV-2 is the virus that causes COVID-19.

The candidate vaccine, mRNA-1273, was co-developed by scientists at the NIAID Vaccine Research Center and at Moderna, Inc., Cambridge, Massachusetts. The animal study results published online today in the New England Journal of Medicine complement recently reported interim results from an NIAID-sponsored Phase 1 clinical trial of mRNA-1273. The candidate mRNA-1273 vaccine is manufactured by Moderna.

In this study, three groups of eight rhesus macaques received two injections of 10 or 100 micrograms (μg) of mRNA-1273 or a placebo. Injections were spaced 28 days apart. Vaccinated macaques produced high levels of neutralizing antibodies directed at the surface spike protein used by SARS-CoV-2 to attach to and enter cells. Notably, say the investigators, animals receiving the 10-μg or 100-μg dose vaccine candidate produced neutralizing antibodies in the blood at levels well above those found in people who recovered from COVID-19.

The experimental vaccine also induced Th1 T-cell responses but not Th2 responses. Induction of Th2 responses has been associated with a phenomenon called vaccine-associated enhancement of respiratory disease (VAERD). Vaccine-induced Th1 responses have not been associated with VAERD for other respiratory diseases. In addition, the experimental vaccine induced T follicular helper T-cell responses that may have contributed to the robust antibody response.

Four weeks after the second injection, all the macaques were exposed to SARS-CoV-2 via both the nose and the lungs. Remarkably, after two days, no replicating virus was detectable in the lungs of seven out of eight of the macaques in both vaccinated groups, while all eight placebo-injected animals continued to have replicating virus in the lung. Moreover, none of the eight macaques vaccinated with 100 μg of mRNA-1273 had detectable virus in their noses two days after virus exposure. This is the first time an experimental COVID-19 vaccine tested in nonhuman primates has been shown to produce such rapid viral control in the upper airway, the investigators note. A COVID-19 vaccine that reduces viral replication in the lungs would limit disease in the individual, while reducing shedding in the upper airway would potentially lessen transmission of SARS-CoV-2 and consequently reduce the spread of disease, they add.

A study published in the journal Nature Communications has pinpointed a number of areas of the human genome that may help explain the neonatal origins of chronic immune and inflammatory diseases of later life, including type 1 diabetes, rheumatoid arthritis and coeliac disease.

The research, led by scientists at the Cambridge Baker Systems Genomics Initiative, identified several genes that appear to drive disease risk at birth, and which could be targeted for therapeutic intervention to stop these diseases in their tracks, well before symptoms occur.

Dr Michael Inouye, Munz Chair of Cardiovascular Prediction and Prevention at the Baker Institute and Principal Researcher at Cambridge University, said chronic immune and inflammatory diseases of adulthood often originated in early childhood, with an individual's genetic make-up causing changes to the function of different genes involved in disease.

For this study, the team collected cord blood samples from more than 100 Australian newborns as part of the Childhood Asthma Study, and investigated the role of genetic variation in DNA in changing how genes are expressed in the two main arms of the immune system.

The neonatal immune cells were exposed to certain stimuli, to see how the cells responded and to identify genetic variants that changed these responses.

"We looked for overlap between these genetic signals and those that are known to be associated with diseases where we know the immune system plays a role," Dr Inouye said.

"We then used statistical analysis to search for possible links between the cell response in newborns and immune diseases in adulthood."

Chronic immune diseases - including type 1 diabetes, coeliac disease and multiple sclerosis - are caused by an overactive immune system and affect about 5 per cent of Australians. Allergies are immune-mediated too and affect one in five Australians, with hay fever, asthma, eczema, anaphylaxis and food allergies the most common. Inflammation and autoimmunity are also known to be driving factors in cardiovascular diseases, for example when an overactive immune system mistakenly attacks the heart.

Dr Qinqin Huang, lead author of the study and now a researcher at the Wellcome Sanger Institute in Cambridge, said the findings were unique in their scale, with thousands of genetic variants driving gene expression across different immune and inflammatory conditions, some of which had wide-ranging effects.

"Our study showed the potential roles of gene expression in disease development, which has helped us to better understand the link between DNA variation and disease risk," Dr Huang said.

"To date, similar studies have only been conducted in adult immune cells. Given the huge difference between neonatal and adult immunity, it is not surprising to see many signals that were unique to newborns."

The study is part of the Cambridge Baker Systems Genomics Initiative's wider work in developing polygenic risk scores to predict an individual's likelihood of developing particular chronic diseases. To date, the team have already developed potential methods to test for future risk of stroke and coronary artery disease.

"Disease is partly due to changes, both large and small, in our genome - the DNA that we're born with and which is a major driving force in all our cells. That means, genomics can be used to estimate disease risk from a very early age," Dr Inouye said.

"Common diseases, such as type 2 diabetes and cardiovascular disease, tend to be polygenic - influenced by a large number of genetic variants scattered throughout the genome, which combine with environmental and lifestyle factors. By using new genomic technology and supercomputing capabilities, we can sift through this DNA data and piece together the puzzles that underlie each disease.

"With so many diseases sharing a root in the immune system and inflammation we can leverage this information to better understand where each disease has a molecular weak spot and to what extent these are shared among different diseases.

"We've shown this can be dissected using genetics and polygenic risk, hopefully leading to targeted preventative interventions for those who need them most, with the aim of keeping people living healthier for longer."

Durham, NC - A new study released today in STEM CELLS Translational Medicine shows promise of a major breakthrough in healing chronic foot ulcers resulting from diabetes. The study, by researchers at the University of California, Davis, is the first to demonstrate how a bioengineered scaffold made up of human mesenchymal stem cells (MSCs) combined with timolol -- a drug commonly used to treat glaucoma -- improved healing and decreased inflammation in the wounds of diabetic mice by as much as 75 percent over the control groups.

Chronic foot ulcers are some of the most dangerous and common complications of diabetes, affecting up to a quarter of the 25 million people living with diabetes in the United States alone, according to the American Diabetes Association. The association also predicts that 30 percent of these cases will eventually lead to amputation. Even more alarming is the projected five-year mortality rate of those who undergo an amputation -- 48 percent, a statistic on par with colon cancer.

"U.S. healthcare expenditures for diabetes foot ulcers (DFUs) is over $43 billion a year. Yet, these expenditures for good standard of care -- which includes such things as following a strict diet, off-loading pressure from the foot to allow wounds to heal, antibiotics or surgery -- result in healing in only 30 percent of patients," said Roslyn Rivkah Isseroff, M.D., professor of dermatology at UC Davis, chief of the Dermatology Service VA Northern California Healthcare System and head of the Wound Healing clinic. "Treating these patients and trying to get them to heal is what propelled me to work on this problem." She led the study along with Jan Nolta, Ph.D., who directs the Stem Cell Program at UC Davis School of Medicine and its Institute for Regenerative Cures.

"This rather dismal cure rate has prompted vigorous research for therapeutic alternatives," Dr. Nolta said. "Several cellular therapies for treating DFU have already been approved by the Food and Drug Administration (FDA), but the healing rates show only modest improvement when compared to the DFU standard of care. None of these products, however, are composed primarily of MSCs. MSC-based therapies may offer advantages over the currently available cellular therapies by regulating the abnormal immune and inflammatory response typical of DFU."

Previous studies by the UC Davis team showed that 85 percent of MSCs applied to scaffolds localize to the seeding side and are retained and viable in culture for 15 days. Their work also demonstrated that hypoxia pre-treatment - that is, depriving the MSCs of oxygen - increased their survival and improved cell retention at the wound site. "Hypoxic preconditioning decreases glucose consumption by the cells, resulting in longer survival in a nutrient-deficient environment," Dr. Nolta explained.

The idea behind adding timolol to this latest study grew out of another study by the UC Davis researchers in which they showed how wound tissue generates a stress hormone called catecholamine and that catecholamine impairs healing. (Catecholamine plays an important role in the body's response to stress by elevating blood pressure and blood glucose levels.) Timolol is known to reverse catecholamine's negative effects and, thus, improve healing.

To conduct their latest study, the research team seeded MSCs, collected from the bone marrow of healthy human donors, on circular matrix scaffolds. Several MSC concentrations were tested in an effort to determine optimal MSC dosing. Next, the scaffolds were incubated in timolol at 1 percent oxygen (hypoxia) in the MSC culture medium.

The scaffolds were then applied to the wounds of a group of diabetic mice. Two small, circular wounds were created opposite each other along the animal's spine and individually splinted to keep the skin from contracting as it healed. An MSC-treated scaffold was then inserted cell-side down into the wound. The control group of mice were all treated with a matrix scaffold only (no MSCs or timolol). The idea was to see how effective the animals' own cells were in rebuilding the damaged tissue in comparison to the wounds treated with MSC-matrix and timolol.

Additionally, several of the MSC-matrix treated wounds received a daily application of timolol (different doses were tested) to gauge how the drug affected the healing process.

Seven days later the results were analyzed. The researchers discovered that all the matrix scaffolds using the combination of MSCs with hypoxia and timolol preconditioning showed significantly improved wound epithelialization (that is, tissue repair) -- by more than 70 percent -- relative to the matrix-alone group. The additional timolol applications applied to the matrix/MSC combination also increased re-epithelialization, by nearly 75 percent as compared to the non-timolol treated controls.

"Overall, the combination of MSCs and timolol successfully improved wound healing and reduced inflammatory response in the mice," Dr. Nolta said. "This suggests that this unique approach could potentially provide superior healing responses in humans with diabetic wounds."

"For this work, scientists have combined adult stem cells with a repurposed drug that improves healing to create a novel bioengineered scaffold that could someday lead to a new treatment for chronic diabetic ulcers," said Anthony Atala, M.D., Editor-in-Chief of STEM CELLS Translational Medicine and director of the Wake Forest Institute for Regenerative Medicine. "The outcomes from this study are promising and offer therapy not just for diabetic ulcers, but also for other types of wounds."

Even short, single antibiotic courses given to young animals can predispose them to inflammatory bowel disease (IBD) when they are older, according to Rutgers researchers.

The study, published in Genome Medicine, provides further evidence supporting the idea that the use of antibiotics in children under 1 year old disrupts the intestinal microbiota - the trillions of beneficial microorganisms that live in and on our bodies - that play a crucial role in the healthy maturation of the immune system and the prevention of diseases, such as inflammatory bowel disease and type 1 diabetes.

"This study provides experimental evidence strengthening the idea that the associations of antibiotic exposures to the later development of disease in human children are more than correlations, but that they are actually playing roles in the disease causation," said study co-author Martin Blaser, director of the Rutgers Center for Advanced Biotechnology and Medicine.

To determine if the increased disease risk was due to the disruption of the microbiome from antibiotics, the researchers studied the effects of exposure to dextran sulfate sodium, a chemical known to injure the colon, both in mice that received antibiotics, and in mice that had perturbed microbial contents transplanted into their intestines versus a control group.

They found that the mice that received either the antibiotics themselves or received the antibiotic-perturbed microbiome had significantly worse colitis, showing that exposure to antibiotics changed the microbiome, altered the immune response in the colon and worsened the experimental colitis.

"The use of a well-validated model of colitis enabled us to study the effects of prior antibiotic exposures on the development of an important disease process," said lead author Ceren Ozkul, a visiting scholar from the Department of Pharmaceutical Microbiology at Hacettepe University in Turkey.

The study continues Blaser's work on the hypothesis that disrupting the early life microbiome, especially by antibiotics and C-section, is one of the factors driving modern epidemics.

Vaccination is the most effective public health measure to prevent infectious diseases. Vaccines can greatly reduce the risk of infection by working with the body's natural defenses to safely develop immunity to disease. However, the immune system fights infection in many different ways, and in order to be effective, a vaccine must trigger the right type of immune response to recognize and destroy a specific virus, bacteria or parasite.

The majority of vaccines, such as those for polio and measles, stimulate a type of immune response called antibody-mediated immunity. But for some chronic infectious diseases such as tuberculosis and malaria, a different type of immune response, called cell-mediated immunity, is needed. Unfortunately, efforts to create a vaccine that prompts a cell-mediated immune response have had limited success.

Now, researchers at the University of Calgary's Snyder Institute for Chronic Diseases have unlocked new insights that may help in developing this type of vaccine.

"What we already know is vaccination often involves polarizing the immune system towards the type of immune response believed to provide protection to a given infection and away from responses believed to be non-protective," says Dr. Nathan Peters, PhD, study lead, associate professor at the University of Calgary's Cumming School of Medicine (CSM) and Faculty of Veterinary Medicine (UCVM).

"Because of this approach, we've been very focused on generating the cell-mediated response that is required to directly fight these chronic infections. What we have realized through our research is that types of immunity that we didn't think were important, or were thought to be non-protective, are actually critical to regulate the protective cell-mediated response to ensure the immune system mounts a balanced defense."

The findings, published in Cell Host and Microbe, show that rather than enhancing protection, a highly polarized cell-mediated response that was believed to be protective was, in fact, detrimental.

"By studying the regulation of the body's own immune response to infection, our team has found that excessive polarization can actually backfire," says Dr. Matheus Carneiro, PhD, postdoctoral scholar and co-author on the study. "Understanding this drove us to investigate the importance of other aspects of the immune response during these infections. We found these other responses played a big role in regulating excessive inflammation, which, in the absence of regulation, actually facilitated infection."

Peters says this fundamental observation could also help inform vaccine design for infectious diseases such as COVID-19, malaria, tuberculosis and the parasitic disease leishmaniasis.

"These observations provide new insight into the regulation of immunity against infectious diseases and could provide a more holistic framework to design vaccines against those infections that don't have one." he says.

Researchers at the University of Chicago Medicine Comprehensive Cancer Center, working with colleagues in Europe, created a deep learning algorithm that can infer molecular alterations directly from routine histology images across multiple common tumor types.

The study, published July 27 in Nature Cancer, highlights the potential of artificial intelligence to help clinicians make personalized treatment plans for patients based on the information gained from how tissues appear under the microscope.

"We found that using artificial intelligence, we can quickly and accurately screen cancer patient biopsies for certain genetic alterations that may inform their treatment options and likelihood to respond to specific therapies," said co-corresponding author Alexander Pearson, MD, PhD, assistant professor of medicine at UChicago Medicine.

"We are able to detect these genetic alterations almost instantly from a single slide, instead of requiring additional testing post-biopsy," said Pearson. "If this model was validated and deployed at scale, it could dramatically improve the speed of molecular diagnosis across many cancers."

Pearson and colleagues noted that although comprehensive molecular and genetic tests are difficult to implement at scale, tissue sections stained and mounted on a slide are commonplace and easy to study. And because molecular alterations in cancer can cause observable changes in tumor cells and their microenvironment, the researchers hypothesized that these structural changes would be visible on images of tissue slices captured under the microscope. In other words, genotype, the genetic make-up of the tumor cells, including gene mutations in key oncogenic pathways, influences the visible traits of those cells, known as their phenotype.

To test this, they set out to systematically investigate the presence of genotype-phenotype links for a wide range of clinically relevant molecular features across all major solid tumor types. Specifically, they asked which molecular features leave a strong enough footprint in histomorphology that they can be determined from histology images alone with deep learning.

To this end, the research team developed, optimized and externally validated a one-stop-shop workflow to train and evaluate deep learning networks to detect any sequence variants in these target genes. Leveraging The Cancer Genome Atlas, they applied this approach to hundreds of molecular alterations in tissue slides of more than 5,000 patients across 14 major tumor types.

They found that in 13 out of 14 tested tumor types, the mutation of one or more such genes could be inferred from histology images alone. In particular, in major cancer types such as lung, colorectal, breast and gastric cancers, alterations of several genes of particular clinical interest were detectable.

Examples include mutations in TP53, which could be significantly detected in all four of these cancer types, as well as mutations of BRAF in colorectal cancer. Among all tested tumor types, gastric cancer and colorectal cancer had the highest absolute number of detectable mutations.

In addition, they found that higher-level gene expression clusters or signatures can be inferred from histological images. These findings that molecular signatures of tumors reflect biologically distinct groups and are correlated with clinical outcome could open up new options for personalized cancer treatment.

Another research group has independently validated these results with a similar AI algorithm applied to images from common cancer types. Their study was published in the same issue of Nature Cancer.

PITTSBURGH, July 27, 2020 - A study published today in The Lancet Digital Health by UPMC and University of Pittsburgh researchers demonstrates the highest accuracy to date in recognizing and characterizing prostate cancer using an artificial intelligence (AI) program.

"Humans are good at recognizing anomalies, but they have their own biases or past experience," said senior author Rajiv Dhir, M.D., M.B.A., chief pathologist and vice chair of pathology at UPMC Shadyside and professor of biomedical informatics at Pitt. "Machines are detached from the whole story. There's definitely an element of standardizing care."

To train the AI to recognize prostate cancer, Dhir and his colleagues provided images from more than a million parts of stained tissue slides taken from patient biopsies. Each image was labeled by expert pathologists to teach the AI how to discriminate between healthy and abnormal tissue. The algorithm was then tested on a separate set of 1,600 slides taken from 100 consecutive patients seen at UPMC for suspected prostate cancer.

During testing, the AI demonstrated 98% sensitivity and 97% specificity at detecting prostate cancer -- significantly higher than previously reported for algorithms working from tissue slides.

Also, this is the first algorithm to extend beyond cancer detection, reporting high performance for tumor grading, sizing and invasion of the surrounding nerves. These all are clinically important features required as part of the pathology report.

AI also flagged six slides that were not noted by the expert pathologists.

But Dhir explained that this doesn't necessarily mean that the machine is superior to humans. For example, in the course of evaluating these cases, the pathologist could have simply seen enough evidence of malignancy elsewhere in that patient's samples to recommend treatment. For less experienced pathologists, though, the algorithm could act as a failsafe to catch cases that might otherwise be missed.

"Algorithms like this are especially useful in lesions that are atypical," Dhir said. "A nonspecialized person may not be able to make the correct assessment. That's a major advantage of this kind of system."

While these results are promising, Dhir cautions that new algorithms will have to be trained to detect different types of cancer. The pathology markers aren't universal across all tissue types. But he didn't see why that couldn't be done to adapt this technology to work with breast cancer, for example.

It's no secret that the current health care system doesn't best serve every American's needs, and one of the most evident examples of this is the rising unaffordability of insulin for patients with diabetes.

In fact, insulin can be so expensive that some patients with diabetes ration it - and those who do are more likely to have poor glucose control, potentially leading to life-threatening complications such as diabetic ketoacidosis.

In a new study published in JAMA Pediatrics, University of Michigan researchers found that capping the amount patients pay out-of-pocket for insulin could substantially improve affordability for many families of children and young adults with type 1 diabetes.

The amount of benefit varied by the generosity of the cap and whether families were enrolled in high-deductible health plans.

"Cost-sharing caps don't help the uninsured and don't address the underlying problem of high insulin prices", says lead author Kao-Ping Chua, M.D., Ph.D., a researcher and pediatrician at C.S. Mott Children's Hospital and the University of Michigan Medical School's Susan B. Meister Child Health Evaluation and Research Center.

"However, our study shows that caps could be a useful stop-gap measure to improve insulin affordability until more comprehensive reforms are implemented."

The study

The study team analyzed more than 12,000 privately insured children and young adults under the age of 21 with type 1 diabetes.

The data showed that patients paid an average of $494 out-of-pocket for insulin in 2018, and that 1 in 8 patients had out-of-pocket spending exceed $1,000.

"To put those numbers in perspective, the Federal Reserve Board reported that 40% of Americans didn't have enough savings to pay for a $400 emergency in 2018," Chua says.

Chua's team estimated the effects of two hypothetical national caps on cost-sharing for insulin: one that limited cost-sharing to $25 for a 30-day supply, and one that limited cost-sharing to $100.

The data showed that approximately 60% of patients would have lower out-of-pocket spending under a $25 cap, with average savings of almost $480 per year. Approximately 18% of patients would have lower out-of-pocket spending under a $100 cap, with average savings of almost $560 per year.

Among those covered by high-deductible health plans, three-quarters would benefit from a $25 cap, while one-third would benefit from a $100 cap. Among those covered by other plans, half would benefit from a $25 cap, while one-eighth would benefit from a $100 cap.

This indicates caps would benefit patients covered by high-deductible health plans to a greater degree because their out-of-pocket costs for insulin are higher at baseline.

What's the issue?

Insulin prices have tripled over the last decade, but not because it's become more expensive to make. According to Chua, the increases are due to lack of competition in the insulin market, coupled with the lack of regulation of drug prices in the U.S.

For many privately insured patients who face deductibles for prescription drugs, insulin price increases result in higher out-of-pocket costs. Patients have to pay full-price for insulin until the deductible is met, and then pay a portion of the price after that, such as 20%.

In 2019, several insurance companies, like Cigna, Express Scripts and Medica started implementing cost-sharing caps, which are typically $25 for a 30-day supply. In 2020, the federal government announced that some Medicare Part D plans will also cap insulin cost-sharing to $35 per 30-day supply.

States across the country, such as Colorado, New Mexico, and California, have similarly passed laws limiting cost-sharing for insulin in private insurance plans. Chua emphasizes that these caps don't help the uninsured better afford insulin.

This is of particular concern now, as millions of Americans have lost their jobs and job-based insurance due to the COVID-19 pandemic.

"Unfortunately, patients who lose health insurance and cannot afford insulin are becoming additional victims of the COVID-19 pandemic," he said.

SINGAPORE, 27 July 2020 - The Epstein-Barr virus (EBV), one of the most common human viruses, is associated with about 8-10 per cent of stomach -- or gastric -- cancers, the third leading cause of cancer death globally. Researchers from Chiba University in Japan, Duke-NUS Medical School, Singapore, and the Agency for Science, Technology and Research (A*STAR)'s Genome Institute of Singapore (GIS) have revealed a novel paradigm in EBV-associated gastric cancer, whereby the EBV viral genome directly alters the host epigenetic landscape to promote the activation of proto-oncogenes (genes involved in normal cell growth that can mutate into cancer-causing genes) and tumorigenesis.

The human genome is the complete set of human genetic information, and the epigenome describes modifications to the genome that determine whether genes are turned on or off when and where they are needed. Unlike genetic information, the epigenome is dynamic and responsive to external stimuli; certain external stimuli can cause abnormal DNA modifications which, in turn, can disrupt normal gene expression and contribute to cancer development.

The research group, led by senior and co-corresponding authors, Dr Atsushi Kaneda, Professor at the Graduate School of Medicine, Chiba University, and Dr Patrick Tan, Professor at the Programme in Cancer and Stem Cell Biology, Duke-NUS Medical School, and Executive Director of GIS, conducted a comprehensive analysis of three-dimensional genomic structures in human cells. These ranged from gastric cancer cell lines, patient samples, normal gastric epithelial cells, and EBV-associated gastric cancer. Combined with virus infection analyses, the researchers found abnormally activated genomic regions specific to EBV-positive stomach cancer. Experimental EBV infection of cultured stomach cells reproduced the phenomena of EBV binding to these inactive and closed genomic regions and their abnormal activation.

?Cells put active marks on genomic regions necessary for their behaviours and utilise them, and inactive marks on unnecessary genomic regions that are tightly closed and not to be utilised," explained Prof Kaneda. "We made the striking observation that strong inactive marks were lost in specific genomic regions when we infected stomach cells with EBV."

The researchers further found that genetic enhancers (short pieces of DNA that help encourage genes to make proteins) 'silenced' in the closed regions were activated by the virus to upregulate nearby cancer-related genes, leading to the proliferation of cancerous cells. This 'enhancer infestation' model, as the researchers termed it, reveals a novel mechanism of tumorigenesis that does not require genetic alterations, and instead works by reprograming the epigenetic landscape of human cells to convert latent enhancers from a silenced to an active state.

Prof Patrick Tan, who is also a member of the Singapore Gastric Cancer Consortium, remarked, ?In all EBV-positive stomach cancer cells and primary stomach cancer patient samples studied, EBV DNA bound to largely the same genomic regions that also showed abnormal activation. These same regions also changed from inactive to active states by experimental EBV infection."

This mechanism of 'enhancer infestation' led to the activation of neighbouring proto-oncogenes in human cells and it is likely to contribute to EBV-associated oncogenesis in multiple cancer cell types. Notably, the researchers also found that, even after eliminating EBV genomes, epigenetic modifications that were induced continued to persist, suggesting a 'hit-and-run' mechanism in which, once an EBV episome alters the chromatin topology of human cells, these altered topologies are stable and persist even after removal of the EBV episome.

Prof Kaneda reiterated, "While 8-10 per cent of stomach cancer is associated with EBV, we believe our enhancer infestation model provides a new mechanism of cancer involving epigenomic alterations and viral infection that may be relevant to a broader range of cancers and associated diseases."

Prof Tan added, "Infections by EBV are estimated to cause over 200,000 cancers per year worldwide, including certain stomach cancers. Our study highlights new potential drug targets in EBV-positive malignancies, revealed by epigenetics and previously invisible using more conventional genetic sequencing studies."

What The Viewpoint Says: Recent advancements across disciplines relevant to early child development can be used to understand the consequences of the COVID-19 pandemic and to develop and scale empirically supported interventions for adversity-exposed children and families.

Authors: Danielle Roubinov, Ph.D., of the University of California, San Francisco, is the corresponding author.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jamapediatrics.2020.2354)

Editor's Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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Media advisory: The full study is linked to this news release.

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Reno, Nev. (July 27, 2020) - In a new study published today in the journal Nature Medicine, researchers behind the Healthy Nevada Project® suggest that community-based genetic screening has the potential to efficiently identify individuals who may be at increased risk for three common inherited genetic conditions known to cause several forms of cancer and increased risk for heart disease or stroke.

In 2018, the Healthy Nevada Project® (the largest, community-based population health study combining genetic, clinical, environmental and social data) started notifying consenting study participants who have certain genetic variants which predispose them to the Centers for Disease Control and Prevention (CDC) Tier 1 genetic conditions. The study focused on identifying carriers of these conditions, which include Hereditary Breast and Ovarian Cancer, Lynch Syndrome, and Familial Hypercholesterolemia, because they are the most common conditions and early detection and treatment could significantly lower morbidity and mortality.

Initial results from almost 27,000 study participants showed that 90% of carriers of the CDC Tier 1 genetic conditions were not previously identified in a clinical setting. The authors conclude that population genetic screening would identify at-risk carriers not identified during routine care.

"Our first goal was to deliver actionable health data back to the participants of the study and understand whether or not broad population screening of CDC Tier 1 genomic conditions was a practical tool to identify at-risk individuals," explained Joseph Grzymski, Ph.D., the principal investigator of the Healthy Nevada Project®, a research professor at the Desert Research Institute (DRI), chief scientific officer for Renown Health and lead author of the study.

"Now, two years into doing that, it is clear that the clinical guidelines for detecting risk in individuals are too narrow and miss too many at risk individuals."

Within the group of 26,906 Healthy Nevada Project® participants that Grzymski's research team studied, 358 (1.33%) were carriers for CDC Tier 1 conditions. However, only 25% of those individuals met clinical guidelines for genetic screening. Additionally, more than 20% of the carriers already had a
diagnosis of disease relevant to their underlying genetic condition.

"We're at a point now where it's possible to do clinical-grade genetic screening at population-scale," added James Lu, M.D. Ph.D., co-founder and chief scientific officer of Helix and senior co-author of the study. "What this study demonstrates is the potential impact of doing so. By making genetic screening available more broadly, we can help the millions of Americans who are unaware that they are living at increased risk for highly actionable, genetic conditions take action."

Most notably, the study found that of the 273 participants who were carriers of the CDC Tier 1 genetic conditions and had clinical record information, only 22 individuals showed any previous suspicion of their underlying genetic conditions.

"For the first time, we are providing information at the individual level so study participants can make lifesaving changes to reduce their risk based on their genetics," said Anthony Slonim, M.D., Dr.PH., FACHE, president and CEO of Renown Health and co-director of the Project® study. "We're conducting research on the community level to develop leading-edge research on health determinants for entire neighborhoods, states and eventually, the country. Returning these results allows us to understand the prevalence of genetically programmed diseases and illnesses that we have here in Nevada and ensure we are providing the best prevention and care plans. For the individual, the return of results can be lifechanging."

According to the CDC, early detection and intervention of the Tier 1 genetic conditions could have a meaningful potential for clinical actionability and a positive impact on public health.

The Healthy Nevada Project®, which launched in 2016, offers free genetic testing to every Nevadan, aged 18 and older, interested in learning more about their health and genetic profile. With more than 50,000 study participants enrolled in four years, the Healthy Nevada Project® has become the fastest-enrolling
genetic study in the world.