The role that Epstein-Barr virus (EBV) plays in the development of multiple sclerosis (MS) may be caused by a higher level of cross-reactivity, where the body’s immune system binds to the wrong target, than previously thought.
In a new study published in PLOS Pathogens, researchers looked at blood samples from people with MS, as well as healthy people infected with EBV and people recovering from glandular fever caused by recent EBV infection.
The study investigated how the immune system deals with EBV infection as part of worldwide efforts to understand how this common virus can lead to the development of multiple sclerosis, following 20 years of mounting evidence showing a link between the two.
Mitochondria supply energy to the brain, and the new study shows that…
Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain?
Researchers are on a quest to outsmart and overcome the sophisticated security system of the brain. Julia Robinson reports on some of the approaches being studied.
This single-center longitudinal cohort study has followed known carriers of PRNP pathogenic variants at risk for prion disease, individuals with a close relative who died of genetic prion disease but who have not undergone predictive genetic testing, and controls. All participants were asymptomatic at first visit and returned roughly annually. We determined PRNP genotypes, measured NfL and GFAP in plasma, and RT-QuIC, total PrP, NfL, T-tau, and beta-synuclein in CSF.
Cirrus Therapeutics, the University of Bristol, and London’s Global University Institute of Ophthalmology have discovered a new treatment for age-related macular degeneration (AMD), the leading cause of vision loss among older adults.
Featured on the cover of the journal Science Translational Medicine, this research reveals that boosting a specific protein, IRAK-M, in retinal cells could offer a new and highly effective therapy for AMD.
AMD can severely impact a person’s vision. Patients suffering from AMD often start with blurred vision or seeing a black dot in their central vision, which can ultimately expand to the point where there is no useful central vision. Currently, AMD affects approximately 200 million people worldwide, a number projected to rise to 288 million by 2040 with graying populations. The exact cause of AMD is complex and thought to involve a combination of aging, environmental, and lifestyle factors.
The probe also achieved stable neural recordings in rat brains for up to two years, showing excellent biocompatibility and long-term recording stability, state news agency Xinhua reported.
Cheng Heping, with the Chinese Academy of Sciences and director of the National Centre for Biomedical Imaging Science at Peking University, told Xinhua that the achievement provided a powerful tool for high-throughput simultaneous monitoring of activity in multiple brain regions, and for exploring the relationships between neural activity and behaviour.
This study uncoversthe pivotal role of the enzyme METTL4 in promoting tumor metastasis through the mediation of nuclear N6-methyldeoxyadenosine (6mA) in mammalian cells. By utilizing cellular models, the study demonstrates how hypoxia induces METTL4 to mediate 6mA modifications. This process, in turn, activates genes essential for tumor metastasis, including the involvement of specific long noncoding RNA and a novel HIF-1α co-activator, ZMIZ1. These findings not only shed light on the epigenetic mechanisms driving tumor progression but also establish METTL4 as a prognostic marker for cancer and a potential target for therapeutic intervention. The promise of this discovery lies in its potential to inspire new strategies for combating hypoxia-induced tumor progression, opening avenues for further research and development in cancer treatment.
DNA N6-methyldeoxyadenosine (6mA) has been recognized in various organisms for its role in gene regulation. However, its function in mammalian cells, particularly in the context of cancer, has remained elusive. Previous studies have shown that 6mA modifications can influence gene expression and are present in several species, indicating a potential regulatory role in tumorigenesis. This research addresses a critical gap in understanding the nuclear role of 6mA and its enzymatic mediator METTL4, in mammalian tumor cells, particularly under hypoxia (a common condition in tumor microenvironments that promotes metastasis). The study posits that METTL4-mediated 6mA deposition is a key epigenetic modification that activates metastasis-inducing genes. This finding offers a new perspective on the mechanisms of tumor progression and identifying novel targets for therapeutic intervention.
According to recent World Health Organization statistics, cancer remains a leading cause of death globally, with metastatic cancers posing significant treatment challenges. This study’s revelations underscore the urgent need for novel therapeutic strategies to address the complex mechanisms of cancer metastasis. By linking the research findings to SDG 3, which aims to ensure healthy lives and promote well-being for all, the study highlights the potential for significant advancements in cancer treatment. Ultimately, the study paves the way for improved health outcomes and underscores the importance of continued investment in research and development to combat the global cancer burden.
But deep learning has a massive drawback: The algorithms can’t justify their answers. Often called the “black box” problem, this opacity stymies their use in high-risk situations, such as in medicine. Patients want an explanation when diagnosed with a life-changing disease. For now, deep learning-based algorithms—even if they have high diagnostic accuracy—can’t provide that information.
To open the black box, a team from the University of Texas Southwestern Medical Center tapped the human mind for inspiration. In a study in Nature Computational Science, they combined principles from the study of brain networks with a more traditional AI approach that relies on explainable building blocks.
The resulting AI acts a bit like a child. It condenses different types of information into “hubs.” Each hub is then transcribed into coding guidelines for humans to read—CliffsNotes for programmers that explain the algorithm’s conclusions about patterns it found in the data in plain English. It can also generate fully executable programming code to try out.
