Toggle light / dark theme

Artificial intelligence in various forms has been used in medicine for decades — but not like this. Experts predict that the adoption of large language models will reshape medicine. Some compare the potential impact with the decoding of the human genome, even the rise of the internet. The impact is expected to show up in doctor-patient interactions, physicians’ paperwork load, hospital and physician practice administration, medical research, and medical education.

Most of these effects are likely to be positive, increasing efficiency, reducing mistakes, easing the nationwide crunch in primary care, bringing data to bear more fully on decision-making, reducing administrative burdens, and creating space for longer, deeper person-to-person interactions.

Sleep is known to contribute to the healthy functioning of the brain and the consolidation of memories. Past psychology research specifically highlighted its role in retaining episodic memories, which are memories of specific events or experiences.

Researchers at Rotman Research Institute at Baycrest Academy for Research and Education, University of Toronto and other institutes recently carried out a study to better understand the extent to which transforms how we remember real-world experiences over time and what processes could underpin this transformation. Their findings, published in Nature Human Behaviour, suggest that sleep actively and selectively improves the accuracy with which we remember one-time real-world experiences.

“My lab studies real-life memory such as the memory of events that occur as part of daily experiences,” Brian Levine, senior author of the paper, told Medical Xpress. “We are interested in how these memories are transformed over time and why some elements are remembered while others are forgotten. This is hard to do with naturalistic events in peoples’ lives where we have no control over what happened. So we set up the Baycrest Tour as a controlled but naturalistic event that we could use to memory.”

Researchers will soon be able to study biological changes at scales and speeds not previously possible to significantly expand knowledge in areas such as disease progression and drug delivery.

Physicists at The University of Queensland have used “tweezers made from light” to measure activity within microscopic systems over timeframes as short as milliseconds. Professor Halina Rubinsztein-Dunlop from UQ’s School of Mathematics and Physics said the method could help biologists understand what was happening within single living cells.

“For example, they will be able to look at how a cell is dividing, how it responds to outside stimuli, or even how affect cell properties,” Professor Rubinsztein-Dunlop said.

A new imaging technique is helping ultra-powerful MRI scanners detect tiny differences in the brains of patients with treatment-resistant epilepsy. In a groundbreaking study, doctors at Addenbrooke’s Hospital in Cambridge used this approach to identify hidden brain lesions, allowing them to offer patients surgery that could cure their condition.

7T MRI scanners, named for their use of a 7 Tesla magnetic field, which is more than twice as strong as the 3T scanners commonly used, have previously struggled with signal blackspots in key areas of the brain. However, researchers from Cambridge and Paris have developed a technique that overcomes this issue, as detailed in a study published today (March 21) in Epilepsia.

The challenge of treating focal epilepsy.

Rabah et al. discover an astrocyte-to-neuron hydrogen peroxide signalling cascade, which is crucial for long-term memory formation in Drosophila. This signalling is found to be inhibited by amyloid-β peptide, suggesting a link to Alzheimer’s disease.

Mechanism of neuroinflammation protection by astrocytes.

How astrocytes controls neuroinflammation is not clearly understood.

The researchers demonstrate that the upregulation of basic leucine zipper ATF-like transcription factor (BATF)2 downstream of IFNg regulates the inflammatory potential of astrocytes during neuroinflammation.

In vivo evidence suggests that BATF2 limits CNS autoimmunity and the expression of IFNg-driven inflammatory mediators.

Mechanistically, BATF2 binds and prevents the overexpression of IFN regulatory factor (IRF)1 and IRF1 targets such as caspase-1. Batf2−/− mice exhibit exacerbated clinical disease severity in a murine model of central nervous system autoimmunity and express increased astrocyte-specific IRF1 and caspase-1, suggesting an amplified IFN response in vivo.

They also demonstrate that BATF2 expressed primarily in astrocytes within multiple sclerosis lesions and that this expression is colocalized with IRF1.

These data suggest that BATF2 contributes to protective mechanisms in astrocytes during chronic neuroinflammation. https://sciencemission.com/BATF2-and-neuroinflammation

Here Harkos et al. review the role of continuous models and discrete models in predicting and understanding therapy delivery and efficacy in solid tumours. They propose ways to integrate mechanistic and AI-based models to further improve patient outcomes.