Summary: A new theory suggests glial cells, specifically astrocytes, play a key role in cognitive processing.
Source: University Health Network.
A team of scientists from the Krembil Brain Institute, part of the University Health Network in Toronto, and Duke University in Durham, North Carolina, has developed the first computer model predicting the role of cortical glial cells in cognition.
Genomic medicine is undergoing rapid change after the Japanese public health insurance system began to cover genetic testing in 2019. Cancer patients who meet certain criteria are able to take these tests for a relatively affordable price, and their genetic information is collected in a massive database and analyzed with the help of around 170 hospitals across the country. But challenges remain, with suitable drugs available for only 10% of patients who undergo testing.
Plastic is everywhere and is even in us. This poses an environmental and health risk. What are researchers doing to combat this?
We ingest it. It is in our oceans, water, and soil. Researchers are trying to clean up our mess. Here are two projects to note.
A new technology that incorporates flexible fiber sensors into shoes has been developed by the National Nanotechnology Research Center (UNAM) at Bilkent University and is able to identify a number of health issues, including Parkinson’s disease and gait disorders.
Project manager Mustafa Ordu, who specialized in the production and characterization of fiber cables that can generate electricity for wearable devices, explained that the technology developed at UNAM is loaded with smart sensors that can monitor body movements and determine issues and diseases, with the potential to diagnose many health problems.
Further explaining the cutting-edge technology, he said that it can be woven into body wear or incorporated into footwear since by knitting these cables together like a type of threaded fabric, they can be incorporated into clothing as fibers. “This is what makes our team stand out among the existing laboratories in the world; we make smart sensors with flexible fiber and two-dimensional materials,” said Ordu.
At 200 times stronger than steel, graphene has been hailed as a super material of the future since its discovery in 2004. The ultrathin carbon material is an incredibly strong electrical and thermal conductor, making it a perfect ingredient to enhance semiconductor chips found in many electrical devices.
But while graphene-based research has been fast-tracked, the nanomaterial has hit roadblocks: in particular, manufacturers have not been able to create large, industrially relevant amounts of the material. New research from the laboratory of Nai-Chang Yeh, the Thomas W. Hogan Professor of Physics, is reinvigorating the graphene craze.
In two new studies, the researchers demonstrate that graphene can greatly improve electrical circuits required for wearable and flexible electronics such as smart health patches, bendable smartphones, helmets, large folding display screens, and more.
The WHO said that case numbers last week were on the rise in several countries in the Americas and it stressed that a slowdown worldwide in new cases could be the “most dangerous” time in the outbreak.
WHO chief Tedros Adhanom Ghebreyesus said more than 70,000 cases have now been reported to the U.N. health agency this year, with 26 deaths.
“Globally, cases are continuing to decline, but 21 countries in the past week reported an increase in cases, mostly in the Americas, which accounted for almost 90 percent of all cases reported last week,” he told a press conference in Geneva.
Real-world data (and real-world evidence) can also play roles outside of public health emergencies like Covid and monkeypox. They can help determine the long-term effectiveness of many treatments, especially those subject to the expedited approval process, such as those used for rare diseases, and can help determine the value of drugs in general. In many cases, clinical trials are not enough to understand how well drugs really work. Janet Woodcock, the director of the FDA’s Center for Drug Evaluation and Research, has said that the clinical trial system is “broken” and that more use of real-world evidence could be an effective addition to the approval process.
The FDA has been taking steps toward using more real-world data outside of public health emergencies like Covid and monkeypox. In 2018, the agency issued guidance for use of such evidence in approving drugs. By 2021, when the FDA issued enhanced guidance on the topic, real-world evidence had been used in approving 90 medical devices and the new use of a drug, Prograf. But this is not happening enough in practice.
Failing to use real-world data means missing out not just on better understanding of the effectiveness of individual drugs but also on a chance to improve the entire pharmaceutical sector, including addressing issues like rising costs. The availability of more data on real-world outcomes from using drugs, especially gene therapies and other innovative and often very expensive treatments, would pave the way for pricing to take patient outcomes into account through approaches like value-based contracting, when health insurers base drug prices on how well drugs work in the people who take them, rather than just in premarket clinical trials.
An interdisciplinary team of researchers has developed a blueprint for creating algorithms that more effectively incorporate ethical guidelines into artificial intelligence (AI) decision-making programs. The project was focused specifically on technologies in which humans interact with AI programs, such as virtual assistants or “carebots” used in healthcare settings.
“Technologies like carebots are supposed to help ensure the safety and comfort of hospital patients, older adults and other people who require health monitoring or physical assistance,” says Veljko Dubljević, corresponding author of a paper on the work and an associate professor in the Science, Technology & Society program at North Carolina State University. “In practical terms, this means these technologies will be placed in situations where they need to make ethical judgments.”
“For example, let’s say that a carebot is in a setting where two people require medical assistance. One patient is unconscious but requires urgent care, while the second patient is in less urgent need but demands that the carebot treat him first. How does the carebot decide which patient is assisted first? Should the carebot even treat a patient who is unconscious and therefore unable to consent to receiving the treatment?”
In an effort to streamline the process of diagnosing patients with multiple sclerosis and Parkinson’s disease, researchers used digital cameras to capture changes in gait—a symptom of these diseases—and developed a machine-learning algorithm that can differentiate those with MS and PD from people without those neurological conditions.
Their findings are reported in the IEEE Journal of Biomedical and Health Informatics.
The goal of the research was to make the process of diagnosing these diseases more accessible, said Manuel Hernandez, a University of Illinois Urbana-Champaign professor of kinesiology and community health who led the work with graduate student Rachneet Kaur and industrial and enterprise systems engineering and mathematics professor Richard Sowers.
