Lifeboat Foundation

Objective To determine whether training with a brain–computer interface (BCI) to control an image of a phantom hand, which moves based on cortical currents estimated from magnetoencephalographic signals, reduces phantom limb pain.

Methods Twelve patients with chronic phantom limb pain of the upper limb due to amputation or brachial plexus root avulsion participated in a randomized single-blinded crossover trial. Patients were trained to move the virtual hand image controlled by the BCI with a real decoder, which was constructed to classify intact hand movements from motor cortical currents, by moving their phantom hands for 3 days (“real training”). Pain was evaluated using a visual analogue scale (VAS) before and after training, and at follow-up for an additional 16 days. As a control, patients engaged in the training with the same hand image controlled by randomly changing values (“random training”). The 2 trainings were randomly assigned to the patients. This trial is registered at UMIN-CTR (UMIN000013608).

Results VAS at day 4 was significantly reduced from the baseline after real training (mean [SD], 45.3 [24.2]–30.9 [20.6], 1/100 mm; p = 0.009 < 0.025), but not after random training (p = 0.047 0.025). Compared to VAS at day 1, VAS at days 4 and 8 was significantly reduced by 32% and 36%, respectively, after real training and was significantly lower than VAS after random training (p < 0.01).

Researchers from the University of Colorado Anschutz Medical Campus and Pathways Bioscience in the United States have found that activating a transcription factor involved in oxidative stress regulation, antiviral activity, and inflammation may serve as a new treatment approach to coronavirus disease 2019 (COVID-19).

The scientists propose that the antiviral and anti-inflammatory effects of activating nuclear factor erythroid 2-related factor 2 (Nrf2) may reduce symptoms and stop the “cytokine storm syndrome” that can be fatal in cases of COVID-19.

A pre-print version of the study can be accessed on the bioRxiv* server, while the manuscript undergoes peer review.

Policymakers had ample warning that COVID-19 posed a high risk for diabetes patients. In 2003, during the coronavirus outbreak known as SARS, or Severe Acute Respiratory Syndrome, more than 20% of people who died had diabetes.

(Reuters) — Devon Brumfield could hear her father gasping for breath on the phone.

Might our DNA be triggered via AI.

Dogs with a few days of training are capable of identifying people infected with the coronavirus, according to a study by a German veterinary university.

Eight dogs from Germany’s armed forces were trained for only a week and were able to accurately identify the virus with a 94% success rate, according to a pilot project led by the University of Veterinary Medicine Hannover. Researchers challenged the dogs to sniff out Covid-19 in the saliva of more than 1,000 healthy and infected people.

When our neurons—the principle cells of the brain—die, so do we.

Most neurons are created during embryonic development and have no “backup” after birth. Researchers have generally believed that their survival is determined nearly extrinsically, or by outside forces, such as the tissues and cells that neurons supply with nerve cells.

A research team led by Sika Zheng, a biomedical scientist at the University of California, Riverside, has challenged this notion and reports the continuous survival of neurons is also intrinsically programmed during development.

Proteins are essential to the life of cells, carrying out complex tasks and catalyzing chemical reactions. Scientists and engineers have long sought to harness this power by designing artificial proteins that can perform new tasks, like treat disease, capture carbon, or harvest energy, but many of the processes designed to create such proteins are slow and complex, with a high failure rate.

In a breakthrough that could have implications across the healthcare, agriculture, and energy sectors, a team lead by researchers in the Pritzker School of Molecular Engineering (PME) at the University of Chicago has developed an artificial intelligence-led process that uses big data to design new proteins.

By developing machine-learning models that can review protein information culled from genome databases, the researchers found relatively simple design rules for building artificial proteins. When the team constructed these artificial proteins in the lab, they found that they performed chemistries so well that they rivaled those found in nature.

From chemistry to materials science to COVID-19 research, the APS is one of the most productive X-ray light sources in the world. An upgrade will make it a global leader among the next generation of light sources, opening new frontiers in science.

In the almost 25 years since the Advanced Photon Source (APS), a U.S. Department of Energy (DOE) Office of Science User Facility, first opened at DOE’s Argonne National Laboratory, it has played an essential role in some of the most pivotal discoveries and advancements in science.

Continue reading “Advanced Photon Source upgrade will transform the world of scientific research” »

UC Davis scientists spent years editing a sex-determining gene into bovine embryos using Crispr. In April, Cosmo arrived—and his DNA reveals how far the field has to go.