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Life’s Edge by Carl Zimmer review – what does it mean to be alive?
At a medical research laboratory in California, Alysson Muotri, PhD has used chemistry to change skin cells into neurons, which have multiplied to form “organoids” – globes of interconnected brain cells. The organoids can expand to hundreds of thousands of cells, live for years, and even produce detectable patterns of brain waves, like those of premature babies. “The most incredible thing is that they build themselves,” says Muotri. He even wonders whether they could one day become conscious.
Girdin One’s Loins
A research team, led by senior author Pradipta Ghosh, MD, professor in the departments of Medicine and Cellular and Molecular Medicine at UC San Diego School of Medicine, found that GIV — a member of the G protein family that serve as molecular switches inside cells, transmitting and fine-tuning signals — regulates the activity of enzymes that turn on and turn off the processes of capacitation and AR in mammalian reproduction.

“The findings demonstrate how GIV orchestrates distinct signaling programs in sperm that separated by space and time, effectively supporting capacitation while inhibiting premature AR,” said Ghosh. “As a result, GIV plays an essential role in male fertility.”
Unchanging Rules of Gene Expression Could Improve Drug Approval Odds
Network theory holds that everything is connected, including people (e.g., Facebook), but few will have many connections, and most will have few. The same rule applies if the “nodes” happen to be human cells, genomes, proteomes, or transcriptomes, says Pradipta Ghosh, MD, professor in the departments of medicine and cellular and molecular medicine at the University of California San Diego (UCSD) School of Medicine as well as cofounder of the Institute for Network Medicine (iNetMed) endeavoring to chart the most powerful connections.
AI Helps Predict Winners and Losers in Clinical Trials
Somewhere between assessing safety in healthy volunteers and testing effectiveness in hundreds to thousands of patients, most drugs in clinical trials fail. Pradipta Ghosh, MD, and her colleagues at the University of California, San Diego (UCSD) School of Medicine have developed a blueprint that they hope will end this disheartening phenomenon.

Ghosh and her team used artificial intelligence (AI) to discern patterns in gene expression datasets that apply to all patients with inflammatory bowel disease (IBD) and to identify clinically actionable drug targets. After testing drug candidates in mouse models, typically the final step before clinical trials, the researchers conducted a “Phase 0” clinical trial. Using patient-derived organoid models, they determined whether any observed therapeutic effect resulted from the candidate drug or confounding variables.
Artificial Intelligence Could Be New Blueprint for Precision Drug Discovery
Writing in the July 12, 2021 online issue of Nature Communications , researchers at University of California San Diego School of Medicine describe a new approach that uses machine learning to hunt for disease targets and then predicts whether a drug is likely to receive FDA approval.

The study's findings could measurably change how researchers sift through big data to find meaningful information with significant benefit to patients, the pharmaceutical industry and the nation’s health care systems.

“Academic labs and pharmaceutical and biotech companies have access to unlimited amounts of ‘big data’ and better tools than ever to analyze such data. However, despite these incredible advances in technology, the success rates in drug discovery are lower today than in the 1970s,” said Pradipta Ghosh, MD, senior author of the study and professor in the departments of Medicine and Cellular and Molecular Medicine at UC San Diego School of Medicine.
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