Lifeboat Foundation

Many Black Americans who are thought to have a high risk of developing kidney disease possess a protective genetic variant that nullifies the extra risk, a new study from Columbia researchers has found. The work is published in the journal Nature Communications.

The study found that high-risk people who carry this variant have a risk of developing kidney disease much closer to that of the general population.

The findings will have an immediate impact on clinical practice, says study leader Simone Sanna-Cherchi, MD, associate professor of medicine at Columbia’s Vagelos College of Physicians and Surgeons.

Researchers at UT Southwestern Medical Center have developed a novel artificial intelligence (AI) model that analyzes the spatial arrangement of cells in tissue samples. This innovative approach, detailed in Nature Communications, has accurately predicted outcomes for cancer patients, marking a significant advancement in utilizing AI for cancer prognosis and personalized treatment strategies.

“Cell spatial organization is like a complex jigsaw puzzle where each cell serves as a unique piece, fitting together meticulously to form a cohesive tissue or organ structure. This research showcases the remarkable ability of AI to grasp these intricate spatial relationships among cells within tissues, extracting subtle information previously beyond human comprehension while predicting patient outcomes,” said study leader Guanghua Xiao, Ph.D., Professor in the Peter O’Donnell Jr. School of Public Health, Biomedical Engineering, and the Lyda Hill Department of Bioinformatics at UT Southwestern. Dr. Xiao is a member of the Harold C. Simmons Comprehensive Cancer Center at UTSW.

Tissue samples are routinely collected from patients and placed on slides for interpretation by pathologists, who analyze them to make diagnoses. However, Dr. Xiao explained, this process is time-consuming, and interpretations can vary among pathologists. In addition, the human brain can miss subtle features present in pathology images that might provide important clues to a patient’s condition.

LJI scientists harness bioinformatics to predict how T cells may adapt to fighting the highly mutated Pirola variant.

In August, researchers detected a new SARS-CoV-2 “variant of concern” in patients in Israel and Denmark. Since then, this variant, dubbed BA.2.86 or “Pirola,” has made its way around the globe. The Pirola variant has raised alarms because it is highly mutated. In fact, Pirola is as mutated as the Omicron variant was, compared with the early SARS-CoV-2 variant included in the original vaccinations.

As Pirola spreads, researchers at La Jolla Institute for Immunology (LJI) are investigating whether COVID-19 vaccines (or previous SARS-CoV-2 exposure) can still protect people from severe disease.

Conference is exploring burgeoning connections between the two fields.

Traditionally, mathematicians jot down their formulas using paper and pencil, seeking out what they call pure and elegant solutions. In the 1970s, they hesitantly began turning to computers to assist with some of their problems. Decades later, computers are often used to crack the hardest math puzzles. Now, in a similar vein, some mathematicians are turning to machine learning tools to aid in their numerical pursuits.

Embracing Machine Learning in Mathematics.

PET scans of people with mild cognitive impairment detected lower levels of serotonin, the brain chemical associated with positive mood, compared to those without it.

Comparing PET scans of more than 90 adults with and without mild cognitive impairment (MCI), Johns Hopkins Medicine researchers say relatively lower levels of the so-called “happiness” chemical, serotonin, in parts of the brain of those with MCI may play a role in memory problems including Alzheimer’s disease.

The findings, recently published in the Journal of Alzheimer’s Disease, lend support to growing evidence that measurable changes in the brain happen in people with mild memory problems long before an Alzheimer’s diagnosis, and may offer novel targets for treatments to slow or stop disease progression.

New research on electrochemical reactions highlights the critical role of electrolyte ions, aiding in the advancement of sustainable energy technologies.

Electrochemical reactions are central to the green transition. These reactions use the electric current and potential difference to carry out chemical reactions, which enables binding and realizing electric energy from chemical bonds. This chemistry is the basis for several applications, such as hydrogen technology, batteries, and various aspects of circular economy.

Developments and improvement in these technologies require detailed insight into the electrochemical reactions and different factors impacting them. Recent studies have shown that besides the electrode material also the used solvent, its acidity, and the used electrolyte ions crucially impact the efficiency of electrochemical reactions. Therefore, recent focus has shifted to studying how the electrochemical interfaces, i.e. the reaction environment at the electrode and the electrolyte interface shown in Figure 1, impact the outcome of electrochemical reactions.

When electricity flows through a battery, the materials inside it gradually wear down. The physical forces of stress and strain also play a role in this process, but their exact effects on the battery’s performance and lifespan are not completely known.

A team led by researchers at the Department of Energy’s Oak Ridge National Laboratory developed a framework for designing solid-state batteries, or SSBs, with mechanics in mind. Their paper, published in Science, reviewed how these factors change SSBs during their cycling.

The ability to accurately detect heat and pain is critical to human survival. However, the molecular mechanisms behind how our bodies identify these dangers have long been a mystery to scientists.

Now, University at Buffalo researchers have unraveled the complex biological phenomena that drive these critical functions. Their research, recently published in the Proceedings of the National Academy of Sciences, has uncovered a previously unknown and completely unexpected “suicidal” reaction in ion channel receptors that explains the complicated mechanisms that underlie sensitivity to temperature and pain.

The research could be applied to the development of more effective pain relievers.

Researchers at the Francis Crick Institute, UCL, and MSD have identified a potential treatment target for a genetic type of epilepsy.

Developmental and epileptic encephalopathies are rare types of epilepsy that start in early childhood. One of the most common types of genetic epilepsy, CDKL5 deficiency disorder (CDD), causes seizures and impaired development. Children are currently treated with generic antiepileptic drugs, as there aren’t yet any disease-targeting medications for this disorder.

CDD involves losing the function of a gene producing the CDKL5 enzyme, which phosphorylates proteins, meaning it adds an extra phosphate molecule to alter their function. Until now, researchers have not been sure how genetic mutations in CDKL5 cause CDD.