Publisher Health

Since antiretroviral therapy (ART) for HIV was introduced in 1996, AIDS-related morbidity and mortality has declined significantly. People living with HIV are now expected to live nearly as long as people without HIV. Despite these advances, those living with HIV often report poor well-being and health-related quality of life.
To guide stakeholders in improving health system responses to achieve the best possible long-term health outcomes for people living with HIV, a global multidisciplinary group of HIV experts led by CUNY SPH Senior Scholar Jeffrey Lazarus and including Distinguished Professor Denis Nash and Associate Professor Diana Romero developed a consensus statement identifying the key issues health systems must address in order to move beyond the longtime emphasis on viral suppression to instead deliver integrated, person-centered healthcare for people living with HIV throughout their lives.
Following a rigorous, multi-stage Delphi process, the research team established a diverse panel of experts with expertise in the long-term health needs of people living with HIV. The panel reviewed the literature on multimorbidity and stigma and discrimination in order to identify priority issues to incorporate in the Delphi process to develop a consensus statement.
“An important strength of this consensus statement is that it was generated through this rigorous process, incorporating quantitative and qualitative data from experts from over 20 countries,” says Dr. Romero.
The panel found that multimorbidity, health-related quality of life, and stigma and discrimination continue to be major issues for people living with HIV, including those who have achieved viral suppression and in particular those from marginalized populations.
“These factors can lead to depression, social isolation and barriers in accessing health and support services,” says Dr. Lazarus, who is also associate professor at the Barcelona Institute for Global Health. “Many of these issues are not currently addressed in HIV monitoring, strategies or guideline.”
‘There is ample evidence that addressing things like mental health, stigma reduction, quality of life, and in many settings, housing and food security, will also improve HIV outcomes like adherence to antiretroviral medications and viral suppression,” Dr. Nash says. “The field of HIV implementation science can play a key role in assessing the impact of strategies integrated into HIV service delivery to mitigate these issues.”
The World Health Organization (WHO) and UNAIDS should create new HIV monitoring processes and guidelines, and Member States should commit to report on the indicators and implement policies to enhance health system performance and ensure the long-term well-being of the millions of people around the world living with HIV, the authors note.
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Materials provided by CUNY Graduate School of Public Health and Health Policy. Note: Content may be edited for style and length.

During the height of the pandemic, some hospitals were overwhelmed with patients seeking treatment for COVID-19. This situation could happen again during future outbreaks, especially with SARS-CoV-2 variants of concern on the rise. Now, researchers reporting in ACS’ Analytical Chemistry have developed a blood test to predict which people infected with COVID-19 are most likely to experience serious symptoms, which could help health care workers prioritize patients for hospitalization and intensive care.
Although many people who contract COVID-19 have either no symptoms or mild ones, some require intensive care for pneumonia with acute respiratory distress syndrome. Risk factors for severe disease include older age, heart disease, cancer and diabetes, but these characteristics alone are not sufficient to predict which patients will become the sickest. Measuring levels of certain proteins or metabolites in the blood could help, but these tests are often slow, complicated or expensive. For more effective triage of COVID-19 patients at hospitals, Michelle Hill, Sanjeeva Srivastava and colleagues aimed to develop an easy-to-use method that could quickly and cost-effectively predict COVID-19 severity.
To measure changes in blood biochemistry that occur with severe COVID-19, the researchers chose a technique called attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), which has been tested previously as a COVID-19 diagnostic tool. Two regions of FTIR spectra from 128 patient plasma samples showed small but observable differences between those with severe and non-severe COVID-19. Using these data together with clinical information about patients, the researchers developed a statistical model to predict COVID-19 severity. They found that the best predictor was whether the patient had diabetes, followed by the two regions in the FTIR spectra. Adding the FTIR data to the model improved the sensitivity for detecting severe disease in a different set of 30 patients from 41.2% to 94.1%, but reduced the specificity from 84.6% to 69.2%, compared with the clinical factors alone. This means that the new test was more likely to identify severe cases, but it also had a higher rate of false positives, than the clinical data alone. Although the strategy needs to be tested in larger numbers of patients, it shows promise as a rapid, simple and economic triaging test for hospitals, the researchers say.
The authors acknowledge funding from the Science and Engineering Research Board of the Government of India, the Industrial Research and Consultancy Centre of the Indian Institute of Technology Bombay, the Council of Scientific and Industrial Research, India, the Australian Government Research Training Program and the QIMR Berghofer Medical Research Institute, as well as instrument support from Agilent Technologies.
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Materials provided by American Chemical Society. Note: Content may be edited for style and length.

A protein involved in making cells move offers a clue to how certain types of cancer metastasize and develop into secondary tumours, according to new research from the University of Warwick.
Scientists from Warwick Medical School have demonstrated for the first time that levels of this protein can increase and decrease the movement of a cell, including cancer cells — suggesting that they could play a role in the spread of tumours.
The study is published today (21 July) in the Journal of Cell Biology and was funded by the Medical Research Council, part of UK Research and Innovation.
The researchers are investigating a tiny cell component called an Intracellular nanovesicle (INV) which acts like a courier within a cell by transporting cargo to where it is needed. When a cell moves, the INV moves a particle called an integrin from the cell’s surface to ‘unstick it’ from the surface it is attached to. It then recycles and replaces the integrin to stick it to a new surface.
INVs have a protein called Tumour Protein D54, increased levels of which have been associated with certain types of breast cancer and often a poor prognosis for the patient. These patients tend to have more metastases, where tumour cells spread to other parts of the body.
To investigate TPD54’s role in cell movement, the Warwick team observed cells migrating on a surface coated with fibronectin, a type of extra-cellular matrix, using a live cell microscope. They then reduced or increased the expression of the protein TPD54 to mimic the expression in a cancer cell, observing how the cell migrates more or less depending upon the levels of TPD54.

Babies who were breastfed, even for a few days, had lower blood pressure as toddlers and these differences in blood pressure may translate into improved heart and vascular health as adults, according to new research published today in the Journal of the American Heart Association, an open access journal of the American Heart Association.
Research has found that cardiovascular disease risk factors, including high blood pressure, can start in childhood. Studies have also confirmed breastfeeding is associated with lower cardiovascular disease risk in adulthood. However, the amount and length of time breastfeeding that is needed to achieve cardiovascular benefit has not been clear.
“This is the first study to evaluate the association of breastfeeding in the first days of life and blood pressure in early childhood,” said lead study author Kozeta Miliku, M.D., Ph.D., clinical science officer of the CHILD Cohort Study and post-doctoral fellow in medicine at McMaster University in Hamilton, Ontario, Canada. “Infants who received even a relatively small amount of their mother’s early breast milk, also known as colostrum, had lower blood pressure at 3 years of age, regardless of of how long they were breastfed or when they received other complementary foods.”
Colostrum is known to be especially rich in growth factors, immunologic components and stem cells that are extremely beneficial to newborns and only found in human breastmilk.
Researchers used data from the ongoing Canadian CHILD Cohort Study — a study of over 3,000 children who were born between 2009-2012 and have been followed ever since to understand how early life experiences shape health and development. They analyzed infant feeding information collected from hospital records and caregiver questionnaires for nearly 2,400 children.
Among those children, 98% were breastfed to some extent, including 4% who received “early limited breastfeeding” defined as a few breastfeedings during the hospital stay. Only 2% of children in the study were not breastfed at all.

Researchers led by the Garvan Institute of Medical Research have discovered a link between cognitive decline and a faster rate of bone loss, and found that cognitive decline over five years increased future fracture risk in women. The association between cognitive decline and bone loss was weaker in men.
The study of individuals aged 65 and older was carried out over 16 years and has revealed a potential new approach to help identify older people who may be at risk of fracture.
“Bone loss and cognitive decline are major public health issues, but both are ‘silent diseases’ that can go undetected and untreated for long periods, often until the conditions are severely progressed,” says Professor Jacqueline Center, Head of the Clinical Studies and Epidemiology lab at Garvan, endocrinologist at St Vincent’s Hospital and senior author of the findings published in the Journal of Bone and Mineral Research.
“Our study has revealed a link between the two in women, which suggests that cognition should be monitored together with bone health, as a decline in one could mean a decline in the other. These findings may help refine best practice guidelines of how cognition and bone health are monitored in older age, to ensure appropriate treatment can be more effectively administered.”
New insights on major public health issues
Around the world, 200 million people are affected by osteoporosis and more than 35 million by dementia — numbers which are expected to double over the next two decades due to a global increase in life expectancy.

A new study from Oregon State University found that infants born within 3 kilometers of oil and natural gas drilling facilities in Texas had slightly lower birthweights than those born before drilling began in their vicinity.
The study, published today in the journal Environmental Health Perspectives, found that the type of drilling or resource being extracted did not change the result.
“Most studies to date focus exclusively on unconventional natural gas drilling, or fracking. That particular process is a small subset of the oil and natural gas industry. We find it doesn’t matter — where people are extracting oil and gas resources, we’re still seeing an impact on infant health,” said study author Mary Willis, a postdoctoral researcher in OSU’s College of Public Health and Human Sciences. “A lot of policy is exclusively focusing on fracking, but our study shows that’s a really limited view of how this industry may impact local populations.”
Developing fetuses are highly sensitive to environmental pollution and contaminants, so to measure potential impact, this study examined birthweight and location data for 2,598,025 mother-infant pairs in Texas between 1996 and 2009 in which the mother was pregnant while living within 10 kilometers of a current or future oil or gas drilling site.
Prior research estimates that 4.5 million Texans live within 1.6 kilometers (one mile) of at least one oil or gas drilling site. However, little work to date has focused on the population health impacts of living near an oil or gas drilling site in Texas, the state that produces the most oil and gas in the U.S.
The potential exposures related to drilling are numerous: air pollution from drilling activities, flaring and increased traffic going to and from the drilling site; water contamination from hydraulic fracturing chemicals; noise pollution from industrial activity and increased traffic; and light pollution from new drilling facilities.

You can’t make a banana split without bananas. And you can’t generate stable regulatory T cells without Vitamin C or enzymes called TET proteins, it appears.
Regulatory T cells (Tregs) help control inflammation and autoimmunity in the body. Tregs are so important, in fact, that scientists are working to generate stable induced Tregs (iTregs) in vitro for use as treatments for autoimmune diseases as well as rejection to transplanted organs. Unfortunately, it has proven difficult to find the right molecular ingredients to induce stable iTregs.
Now scientists at La Jolla Institute for Immunology and Emory University School of Medicine report that Vitamin C and TET proteins can work together to give Tregs their life-saving power.
“Vitamin C can be used to stabilize iTregs generated in vitro,” says LJI Instructor Xiaojing Yue, Ph.D., who served as co-first author for the EMBO Reports study. “We hope that these kinds of induced Tregs can be used in the future for treatment of autoimmune diseases and organ transplantation.”
The recent study, led by LJI Professor Anjana Rao, Ph.D., and Emory Instructor Benjamin G Barwick, Ph.D., builds on the previous discovery that Vitamin C can enhance the enzymatic activity of TET proteins and prompt the generation of stable iTregs under lab conditions.
This finding was encouraging, but the scientists did not want to work toward new autoimmune therapies without first analyzing the gene expression patterns and other key epigenetic features of the induced Tregs.

The parasites that cause severe malaria are well-known for the sinister ways they infect humans, but new research may lead to drugs that could block one of their most reliable weapons: interference with the immune response.
In the study, scientists defined the atomic-level architecture of the connection between a protein on the surface of a parasite-infected red blood cell when it binds to a receptor on the surface of an immune cell.
When that protein-receptor connection is made under normal circumstances, the infected red blood cell, hijacked by the disease-causing parasite, de-activates the immune cell — meaning the body won’t fight the infection. A drug designed to fit into that space could block the interaction, allowing the immune system to get to work clearing away the pathogen.
In a previous study, a team including the Ohio State University and National Institutes of Health scientists who led this research did similar work with another immune cell receptor that the protein, called RIFIN, binds to in its bid to suppress the immune response.
Through a genome-wide analysis of the parasite that causes malaria, the scientists found RIFIN exerts the same type of immune-suppressing function in various species of Plasmodium infecting humans, gorillas and chimpanzees. This suggests it is a mechanism that has not changed over the course of evolution — meaning this function is critical to the parasite’s success and therefore an attractive target for intervention.
The researchers envision either a vaccine or a chemical compound, or both, could be developed to disable this function, reducing the risk of severe malaria cases that require hospitalization and rapid treatment.

In order to win the battle against COVID-19, studies to develop vaccines, drugs, devices and re-purposed drugs are urgently needed. Randomized clinical trials are used to provide evidence of safety and efficacy as well as to better understand this novel and evolving virus. As of July 15, more than 6,180 COVID-19 clinical trials have been registered through ClinicalTrials.gov, the national registry and database for privately and publicly funded clinical studies conducted around the world. Knowing which ones are likely to succeed is imperative.
Researchers from Florida Atlantic University’s College of Engineering and Computer Science are the first to model COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning. The study, published in PLOS ONE, provides the most extensive set of features for clinical trial reports, including features to model trial administration, study information and design, eligibility, keywords, drugs and other features.
This research shows that computational methods can deliver effective models to understand the difference between completed vs. ceased COVID-19 trials. In addition, these models also can predict COVID-19 trial status with satisfactory accuracy.
Because COVID-19 is a relatively novel disease, very few trials have been formally terminated. Therefore, for the study, researchers considered three types of trials as cessation trials: terminated, withdrawn, and suspended. These trials represent research efforts that have been stopped/halted for particular reasons and represent research efforts and resources that were not successful.
“The main purpose of our research was to predict whether a COVID-19 clinical trial will be completed or terminated, withdrawn or suspended. Clinical trials involve a great deal of resources and time including planning and recruiting human subjects,” said Xingquan “Hill” Zhu, Ph.D., senior author and a professor in the Department of Computer and Electrical Engineering and Computer Science, who conducted the research with first author Magdalyn “Maggie” Elkin, a second-year Ph.D. student in computer science who also works full-time. “If we can predict the likelihood of whether a trial might be terminated or not down the road, it will help stakeholders better plan their resources and procedures. Eventually, such computational approaches may help our society save time and sources to combat the global COVID-19 pandemic.”
For the study, Zhu and Elkin collected 4,441 COVID-19 trials from ClinicalTrials.gov to build a testbed. They designed four types of features (statistics features, keyword features, drug features and embedding features) to characterize clinical trial administration, eligibility, study information, criteria, drug types, study keywords, as well as embedding features commonly used in state-of-the-art machine learning. In total, 693 dimensional features were created to represent each clinical trial. For comparison purposes, researchers used four models: Neural Network; Random Forest; XGBoost; and Logistic Regression.
Feature selection and ranking showed that keyword features derived from the MeSH (medical subject headings) terms of the clinical trial reports, were the most informative for COVID-19 trial prediction, followed by drug features, statistics features and embedding features. Although drug features and study keywords were the most informative features, all four types of features are essential for accurate trial prediction.
By using ensemble learning and sampling, the model used in this study achieved more than 0.87 areas under the curve (AUC) scores and more than 0.81 balanced accuracy for prediction, indicating high efficacy of using computational methods for COVID-19 clinical trial prediction. Results also showed single models with balanced accuracy as high as 70 percent and an F1-score of 50.49 percent, suggesting that modeling clinical trials is best when segregating research areas or diseases.
“Clinical trials that have stopped for various reasons are costly and often represent a tremendous loss of resources. As future outbreaks of COVID-19 are likely even after the current pandemic has declined, it is critical to optimize efficient research efforts,” said Stella Batalama, Ph.D., dean, College of Engineering and Computer Science. “Machine learning and AI driven computational approaches have been developed for COVID-19 health care applications, and deep learning techniques have been applied to medical imaging processing in order to predict outbreak, track virus spread and for COVID-19 diagnosis and treatment. The new approach developed by professor Zhu and Maggie will be helpful to design computational approaches to predict whether or not a COVID-19 clinical trial will be completed so that stakeholders can leverage the predictions to plan resources, reduce costs, and minimize the time of the clinical study.”
The study was funded by the National Science Foundation awarded to Zhu.
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Materials provided by Florida Atlantic University. Original written by Gisele Galoustian. Note: Content may be edited for style and length.

Scientists at St. Jude Children’s Research Hospital have found a link between post-cancer treatment frailty and neurocognitive decline in young adult childhood cancer survivors. A paper on this work was published today in the Journal of Clinical Oncology.
Though frailty is often associated with the elderly, 8% of young adult childhood cancer survivors meet the criteria for frailty. This study confirms that those who undergo childhood cancer treatment can experience frailty, which can create an early onset of neurocognitive decline in young adults. This study will help with further research to prevent such neurocognitive decline.
“We think this is going to put more attention on this accelerated aging phenotype in young adult survivors,” said first author AnnaLynn Williams, Ph.D., St. Jude Epidemiology and Cancer Control. “It’s going to make it a bit easier for us to identify the survivors most at risk for neurocognitive decline.
“We can use this information, and the rest of our frailty research, to design a broad intervention that might simultaneously help us improve frailty in survivors as well as neurocognitive functioning,” Williams said.
More important than previously recognized
Cancer-related neurocognitive impairment is present in up to 35% of childhood cancer survivors. It can influence all aspects of their lives, including their physical functioning and daily activities.