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Rice University engineers have developed the smallest implantable brain stimulator demonstrated in a human patient. Thanks to pioneering magnetoelectric power transfer technology, the pea-sized device developed in the Rice lab of Jacob Robinson in collaboration with Motif Neurotech and clinicians Dr. Sameer Sheth and Dr. Sunil Sheth can be powered wirelessly via an external transmitter and used to stimulate the brain through the dura ⎯ the protective membrane attached to the bottom of the skull.

The device, known as the Digitally programmable Over-brain Therapeutic (DOT), could revolutionize treatment for drug-resistant depression and other psychiatric or neurological disorders by providing a therapeutic alternative that offers greater patient autonomy and accessibility than current neurostimulation-based therapies and is less invasive than other brain-computer interfaces (BCIs).

Using AI and ALMA data, scientists create a groundbreaking 3D video of flares around our galaxy’s central black hole, offering new insights into its dynamic environment.

Scientists believe the environment immediately surrounding a black hole is tumultuous, featuring hot magnetized gas that spirals in a disk at tremendous speeds and temperatures. Astronomical observations show that within such a disk, mysterious flares occur up to several times a day, temporarily brightening and then fading away. Now a team led by Caltech scientists has used telescope data and an artificial intelligence (AI) computer-vision technique to recover the first three-dimensional video showing what such flares could look like around Sagittarius A* (Sgr A*, pronounced sadge-ay-star), the supermassive black hole at the heart of our own Milky Way galaxy.

The 3D flare structure features two bright, compact features located about 75 million kilometers (or half the distance between Earth and the Sun) from the center of the black hole. It is based on data collected by the Atacama Large Millimeter Array (ALMA) in Chile over a period of 100 minutes directly after an eruption seen in X-ray data on April 11, 2017.

Advances in gene sequencing technology and computing power have significantly increased the availability of bioinformatic data and processing capabilities. This convergence provides an ideal opportunity for artificial intelligence (AI) to develop methods to control cellular behavior.

In a new study, Northwestern University researchers have reaped fruit from this nexus by developing an AI-powered transfer learning approach that repurposes publicly available data to predict combinations of gene perturbations that can transform cell type or restore diseased cells to health.

The study was recently published in the Proceedings of the National Academy of Sciences.

Generative A.I. technologies can write poetry and computer programs or create images of teddy bears and videos of cartoon characters that look like something from a Hollywood movie.

Now, new A.I. technology is generating blueprints for microscopic biological mechanisms that can edit your DNA, pointing to a future when scientists can battle illness and diseases with even greater precision and speed than they can today.