The research builds on a recent body of work that suggests that #mitochondria are social organelles that can talk to one another even when they are in different tissues.
Biologists discovered that mitochondria in different tissues talk to each other to repair injured cells. When their signal fails, the biological clock starts winding down.
Nabla Copilot sits as a web app or Chrome extension on a doctor’s computer and listens to their consultation with patients.
Nabla Copilot generates clinical notes almost instantly, saving doctors the trouble of documenting the information manually.
A new study published in Nature Cell Biology by Mark Alkema, PhD, professor of neurobiology, establishes an important molecular link between specific B12-producing bacteria in the gut of the roundworm C. elegans and the production of acetylcholine, a neurotransmitter important to memory and cognitive function.
There is growing recognition among scientists that diet and gut microbiota may play an important role in brain health. Changes in the composition of the microbiome have been linked to neurological disorders such as anxiety, depression, migraines and neurodegeneration. Yet, teasing out the cause and effect of individual bacteria or nutrients on brain function has been challenging.
“There are more bacteria in your intestine than you have cells in your body,” said Woo Kyu Kang, PhD, a postdoctoral fellow in the Alkema lab and first author of the current study. “The complexity of the brain, the hundreds of bacterial species that comprise the gut microbiome and the diversity of metabolites make it almost impossible to discern how bacteria impact brain function.”
“Epigenetic changes determine whether genes are turned on or off, and can potentially reverse disease, broadening the therapeutic landscape to find potential cures previously thought impossible.”
Company co-founded by Alex Aravanis and Feng Zhang targets epigenetic code to reprogram cells to a healthy state.
Diverse gut microbiomes protect against pathogens by blocking nutrient access, according to a new Science study. The findings highlight why microbiome diversity is important to human health.
Chronic liver diseases such as hepatitis, liver cirrhosis, and hepatocellular carcinoma are a major cause of morbidity and mortality worldwide. Fibrosis—the thickening and scarring of connective tissue—plays a major role in these liver diseases but detection of fibrosis is limited to biopsy, which suffers from limitations including the risk of complications, sampling only a tiny fraction of the liver, and an inability to serially monitor disease progression due to its invasive nature.
To provide better diagnosis and treatment of chronic liver diseases, researchers are working to use non-invasive magnetic resonance imaging (MRI) to detect and quantify liver fibrosis throughout the entire organ, which would enable earlier detection and the ability to monitor disease progression as well as the effects of treatment over time.
Adapting MRI for detecting chronic conditions such as fibrosis involves the development of tissue-specific MRI contrast agents that target diseased tissue such as the collagen that accumulates in fibrotic liver. To develop such agents, researchers have been challenged to design and synthesize compounds that must find and bind the tissue target, provide a strong signal under MRI, and rapidly clear from the system to minimize any toxicity.
Summary: Scientists are using epigenetic clocks to reveal our biological age, a true marker of health.
A new study delves into the immune system’s role in understanding and improving the accuracy of these clocks. Their innovative approach sheds light on the relationship between immune cell composition and biological age, with a focus on the balance between naïve and memory immune cells.
This research has significant implications for aging insights, health interventions, and targeted cancer treatments.
YSM researchers are using deeplearning AI models to improve detection of patients at risk for multiple hospitalizations due to asthma and COPD.
Asthma and chronic obstructive pulmonary disease (COPD) are two of the most common lung diseases worldwide, and exacerbation of these conditions can negatively impact health and increase health care costs. A new study shows that deep learning, a type of artificial intelligence (AI) that uses large amounts of data to process information, can improve detection of patients with these diseases who are at increased risk for multiple hospitalizations.
The study was published Dec. 13, 2023, in the journal Respiratory Research.
Continue reading “Using AI to Identify High Risk Patients With Asthma and COPD” »
The integration of mechanical memory in the form of springs has for hundreds of years proven to be a key enabling technology for mechanical devices (such as clocks), achieving advanced functionality through complex autonomous movements. Currently, the integration of springs in silicon-based microtechnology has opened the world of planar mass-producible mechatronic devices from which we all benefit, via air-bag sensors for example.
For a new generation of minimally and even non-invasive biomedical applications however, mobile devices that can safely interact mechanically with cells must be achieved at much smaller scales (10 microns) and with much softer forces (pico Newton scale, i.e., lifting weights less than one millionth of a mg) and in customized three-dimensional shapes.
Researchers at the Chemnitz University of Technology, the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences and the Leibniz IFW Dresden, in a recent publication in Nature Nanotechnology, have demonstrated that controllable springs can be integrated at arbitrary chosen locations within soft three-dimensional structures using confocal photolithographic manufacturing (with nanoscale precision) of a novel magnetically active material in the form of a photoresist impregnated with customizable densities of magnetic nanoparticles.
Scientists have grown a tiny brain-like organoid out of human stem cells, hooked it up to a computer, and demonstrated its potential as a kind of organic machine learning chip, showing it can quickly pick up speech recognition and math predictions.
Clusters of brain cells grown in the lab have shown potential as a new type of hybrid bio-computer.
