Bioscience News - GEG Tech top picks

In a recent review published in the journal Nature Medicine, scientists discussed the results of a two-year weekly effort to track and communicate significant developments in medical AI. In particular, AI has been a game-changer in the crucial task of protein folding, which involves predicting the 3D structure of a protein from its chemical sequence. Improvements in protein structure prediction can reveal mechanistic information about a variety of events, including drug-protein interactions and mutation effects. With AI, non-invasive cancer screening, prognosis, and tumor origin identification are now possible. Moreover, deep learning has improved CRISPR-based gene editing by helping predict guide RNA activity and identifying anti-CRISPR protein families. According to one study, BioBERT, a model trained on a large corpus of medical literature, outperformed previous peers on natural language tasks such as answering biological questions.  

SpaceX and Tesla CEO Elon Musk is backing a brain-computer interface venture called Neuralink, according to The Wall Street Journal. The company, which is still in the earliest stages of existence and has no public presence whatsoever, is centered on creating devices that can be implanted in the human brain, with the eventual purpose of helping human beings merge with software and keep pace with advancements in artificial intelligence. These enhancements could improve memory or allow for more direct interfacing with computing devices.

In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here the authors report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching.

The US-based researchers say the new system, which is based on image recognition, could be developed for smartphones, increasing access to screening and providing a low-cost way to check whether skin lesions are cause for concern.