Lifeboat Foundation

Washington, Scientists have found a novel immunotherapy that could bolster the effectiveness of cancer treatment, according to a study. Rather than rally T cells against cancer, scientists have used different human immune cells called natural killer (NK) cells as a novel means to fight cancer, according to a study.

The team of scientists at Albert Einstein College of Medicine described findings that could boost the impact of immune-checkpoint therapy, the study said. Findings have been published in The Journal of Clinical Investigation (JCI).

Immune checkpoint inhibitors such as Keytruda and Opdivo work by unleashing the immune system’s T cells to attack tumour cells. Their introduction a decade ago marked a major advance in cancer therapy, but only 10 per cent to 30 per cent of treated patients experience long-term improvement, the study said.

Triple threat. Tripledemic. A viral perfect storm. These frightening phrases have dominated recent headlines as some health officials, clinicians, and scientists forecast that SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) could surge at the same time in Northern Hemisphere locales that have relaxed masking, social distancing, and other COVID-19 precautions.

But a growing body of epidemiological and laboratory evidence offers some reassurance: SARS-CoV-2 and other respiratory viruses often “interfere” with each other. Although waves of each virus may stress emergency rooms and intensive care units, the small clique of researchers who study these viral collisions say there is little chance the trio will peak together and collectively crash hospital systems the way COVID-19 did at the pandemic’s start.

“Flu and other respiratory viruses and SARS-CoV-2 just don’t get along very well together,” says virologist Richard Webby, an influenza researcher at St. Jude Children’s Research Hospital. “It’s unlikely that they will circulate widely at the same time.”

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The study was conducted at the University of Limerick’s (UL) Bernal Institute in Ireland by a team of researchers from across the globe who created a new type of organic material that can learn from its prior behavior.

Jimi Olaghere feels like he’s been reborn after a pioneering new treatment for sickle cell disease.

A researcher at the University of Houston College of Pharmacy is reporting an effective protocol for reprogramming human heart cells into specialized cells that conduct electricity throughout the heart to enable rhythmic heartbeat and repair diseased hearts. Bradley McConnell, professor of pharmacology, is the first to demonstrate the process and is reporting it in iScience.

It could be a massive breakthrough.

Currently, there are no treatments for cardiac cell death, the underlying basis of cardiovascular disease (CVD), which remains the leading cause of death globally. By 2035, CVD prevalence is expected to increase to 45.1% (more than 130 million people) in the U.S. while the financial cost is projected to increase by more than $131 million over the next two decades, reaching an astounding $1.1 trillion.

An international team of astrophysicists has made a puzzling discovery while analyzing certain star clusters. The University of Bonn played a major role in the study. The finding challenges Newton’s laws of gravity, the researchers write in their publication. Instead, the observations are consistent with the predictions of an alternative theory of gravity. However, this is controversial among experts. The results have now been published in the Monthly Notices of the Royal Astronomical Society.

In their work, the researchers investigated the so-called open star clusters. These are formed when thousands of stars are born within a short time in a huge gas cloud. As they “ignite,” the galactic newcomers blow away the remnants of the gas cloud. In the process, the cluster expands considerably. This creates a loose formation of several dozen to several thousand stars. The weak gravitational forces acting between them hold the cluster together.

“In most cases, open star clusters survive only a few hundred million years before they dissolve,” explains Prof. Dr. Pavel Kroupa of the Helmholtz Institute of Radiation and Nuclear Physics at the University of Bonn. In the process, they regularly lose stars, which accumulate in two so-called “tidal tails.” One of these tails is pulled behind the cluster as it travels through space. The other, in contrast, takes the lead like a spearhead.

Research in the field continues to focus on seizure prevention, prediction and treatment. Dr. Van Gompel predicts that the use of artificial intelligence and machine learning will help neurologists and neurosurgeons continue to move toward better treatment options and outcomes.

“I think we will continue to move more and more toward removing less and less brain,” says Dr. Van Gompel. “And in fact, I do believe in decades, we’ll understand stimulation enough that maybe we’ll never cut out brain again. Maybe we’ll be able to treat that misbehaving brain with electricity or something else. Maybe sometimes it’s drug delivery, directly into the area, that will rehabilitate that area to make it functional cortex again. That’s at least our hope.”

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Continuous-time neural networks are one subset of machine learning systems capable of taking on representation learning for spatiotemporal decision-making tasks. Continuous differential equations are frequently used to depict these models (DEs). Numerical DE solvers, however, limit their expressive potential when used on computers. The scaling and understanding of many natural physical processes, like the dynamics of neural systems, have been severely hampered by this restriction.

Inspired by the brains of microscopic creatures, MIT researchers have developed “liquid” neural networks, a fluid, robust ML model that can learn and adapt to changing situations. These methods can be used in safety-critical tasks such as driving and flying.

However, as the number of neurons and synapses in the model grows, the underlying mathematics becomes more difficult to solve, and the processing cost of the model rises.