The signatures and crosstalk of gut mycobiome, microbiome, and metabolites in drug-induced liver injury
Peer-Reviewed Publication
Updates every hour. Last Updated: 26-May-2026 01:15 ET (26-May-2026 05:15 GMT/UTC)
In a paper published in Mycology, a research group presented results of microbial sequencing of traditional Chinese medicine (TCM)-associated drug-induced liver injury (DILI). This study aimed to distinguish TCM-associated DILI from healthy controls (HCs) and to classify moderate-to-severe DILI.
Acetylcholine, dopamine, noradrenaline, and γ-aminobutyric acid have long been considered exclusive messengers of the nervous system. But a growing number of evidence challenges this traditional view, revealing that immune cells also speak this neural language. A comprehensive review published by the team of Professor Liwei Lu and Dr. Fan Xiao at the University of Hong Kong systematically summarizes the emerging field of immune cell-derived neurotransmitters, illuminating their roles in immunity and disease.
Using GLOBOCAN 2022 and GBD 2021 data, researchers conducted a comprehensive analysis of hematological malignancies’ global burden, focusing on China and the US. They found NHL is most common globally/in the US, and leukemia in China; males and the elderly are high-risk groups, with smoking, high BMI, and benzene/formaldehyde exposure as key factors, and projected a 69.6% global rise in new cases by 2050, emphasizing the urgent need for tailored interventions.
In a bid to better understand, and potentially treat, a host of conditions that affect early cognition, neurodevelopment and the brain later in life, investigators at Johns Hopkins Medicine and colleagues throughout the world have been mapping the molecular construction of the human brain. These models, which are supported in part by federal and international research grants, are helping researchers study genetic links and pathways involved in a variety of conditions, ranging from autism spectrum disorder, which affects about 1 in 31, or 3%, of children in the U.S., to Alzheimer’s disease, which is estimated to affect more than 7 million U.S. adults, including 1 in 9, or 11%, age 65 and older.
To support this blueprint, Carlo Colantuoni, Ph.D., an adjunct professor of neurology at Johns Hopkins Medicine and the Institute for Genome Sciences at the University of Maryland School of Medicine, and other researchers have, in their most recent study, which publishes March 25 in Nature Neuroscience, brought together data from nearly 200 published studies and more than 30 million cells to advance insight about how the neocortex, the outermost layers of the brain, develops and forms over time. This region of the brain is responsible for a variety of functions, including how we think, sense, process and store information, and make decisions.
Researchers have determined how a key protein activates brown fat by expanding blood vessels and nerves in the heat-generating tissue. The findings, published in Nature Communications, point to a potential strategy for treating obesity that deviates from the current approach of suppressing appetite.
Researchers from the Keck School of Medicine of USC are receiving up to $6.8 million for a two-year research project to develop new computational models and support tools that could accelerate access to cell and gene therapies for children with rare diseases. The team will develop a new framework that combines detailed data about the biological features of each therapy and how patients respond to them. By using artificial intelligence (AI) to study these connections, the project aims to better understand how specific features of a therapy relate to patient outcomes. The research is funded by the Advanced Research Projects Agency for Health (ARPA-H) UNIfying Cell Therapy Outcome prediction and Regulatory Navigation (UNICORN) project, led by ARPA-H Program Manager Daria Fedyukina, Ph.D. UNICORN combines advanced cell analysis technology developed by the team with machine learning tools to identify biological patterns and therapy product features linked to treatment response. This approach aims to enable the development of a regulatory decision-support tool that guides interpretation of product-related evidence when limited data makes conventional measures difficult to establish, enabling patients and families to access new treatments sooner.