A Tufts School of Medicine researcher is developing a test to predict lung cancer risk more accurately and reduce the number of scans to detect the condition.
Category: biotech/medical – Page 542
Cancer cells are characterized by their aggressiveness: they grow rapidly and spread to other parts of the body. To enable this, numerous mechanisms come into play, and one of them involves a protein called MYC, which activates certain genes on the cancer cell’s DNA strand, causing the cancer cell to grow and divide.
The MYC protein is also present in healthy individuals, where it plays a crucial role in regulating many cell functions.
“When cancer occurs, it is due to an accumulation of mutations in our DNA, often resulting in the overactivation of the MYC protein. Therefore, this protein plays a crucial role in most cancer forms,” says Rasmus Siersbæk, head of research at the Department of Biochemistry and Molecular Biology, University of Southern Denmark.
With a mobile app powered by artificial intelligence (AI), Caitlin Hicks, MD, MS, reviews selfies of patients’ feet in real time to track their wounds as part of a clinical trial. The app saves time for Hicks, a vascular surgeon at Johns Hopkins Medicine, but also reduces clinic trips for her patients with diabetes in inner-city Baltimore, many of whom are elderly and less mobile or have other socioeconomic barriers to care. Hicks knows that for these patients, wound vigilance is the linchpin to preventing infection, hospitalization, or, worse, amputation or even death.
Despite their crushing toll, diabetic foot infections remain stubbornly hard to treat, but multidisciplinary care teams, new drugs and devices on the horizon, and practical solutions to socioeconomic factors could budge the needle.
Startup seeks new biomarkers as it develops cellular reprogramming drugs designed to reverse brain aging and combat dementia.
Researchers from the UoC’s Center for Biochemistry at the Faculty of Medicine and the UoC CECAD Cluster of Excellence in Aging Research have discovered that an excessive immune response can be prevented by the intramembrane protease RHBDL4.
In a study now published in Nature Communications under the title “RHBDL4-triggered downregulation of COPII adaptor protein TMED7 suppresses TLR4-mediated inflammatory signaling,” the previously unknown regulatory mechanism is described.
The researchers discovered that the cleavage of a cargo receptor by a so-called intramembrane protease reduces the localization of a central immune receptor on the cell surface and thereby the risk of an overreaction of the immune system.
Guanylate binding proteins (GBP) were discovered by YSM’s John MacMicking, PhD, and colleagues over a decade ago as major organizers of cellular immune response.
In a recent study, MacMicking’s team used advanced cryo-and electron microscope technology to visualize in high resolution the way GBPs…
Yale scientists have discovered a family of immune proteins, which they describe as a “massive molecular machine,” that could affect the way our bodies fight infection.
Our immune system mobilizes numerous proteins to detect viruses and bacteria — and to bring them under control. But until recently, limits to research technology have thwarted scientists’ understanding of how to prevent different pathogens from occupying and replicating within specific parts of our cells in the first place.
Harnessing the latest cryo‐electron microscopy techniques to look inside human cells, researchers at the Yale Systems Biology Institute have identified a family of large immune proteins that assemble into a massive signaling platform directly on the surface of microbial pathogens.
Bats are an important group of mammals to understand the ecology, diversity, and transmission of associated microbes – including viruses, bacteria, and fungi.
Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes.
Studies of bat-associated microbes (i.e. microorganisms detected in or isolated from bats) date back to rabies virus investigations in the early 1900s [1]. In the past two decades, following the emergence of Severe Acute Respiratory Syndrome (SARS) coronavirus (CoV) in 2003 and SARS-CoV-2 in 2019, there has been a dramatic increase in research on bat-associated microbes, including viruses, bacteria, haemosporidians and fungi [2–5]. These microbes may or may not cause disease in bats, and thus we broadly use the term ‘microbes’ rather than ‘pathogens’ throughout this paper to acknowledge that detecting microorganisms in bats is distinct from the process of determining pathogenicity [6].
Emerging nanotechnology and molecular innovations present promising strategies in combating inflammation and diabetes, aiming to transform treatment methods and improve patient outcomes significantly.
The intersection of nanotechnology and biomedicine has sparked significant advances in the treatment and understanding of both inflammatory and metabolic diseases. These advances have brought about innovative solutions to longstanding medical challenges, such as rheumatoid arthritis (RA) and type 2 diabetes mellitus (T2DM), diseases that collectively affect millions worldwide.
Summary: A recent study showcases a significant leap in the study of brain oscillations, particularly ripples, which are crucial for memory organization and are affected in disorders like epilepsy and Alzheimer’s. Researchers have developed a toolbox of AI models trained on rodent EEG data to automate and enhance the detection of these oscillations, proving their efficacy on data from non-human primates.
This breakthrough, stemming from a collaborative hackathon, offers over a hundred optimized machine learning models, including support vector machines and convolutional neural networks, freely available to the scientific community. This development opens new avenues in neurotechnology applications, especially in diagnosing and understanding neurological disorders.
Original Article from The New England Journal of Medicine — Cognition and Memory after Covid-19 in a Large Community Sample.