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New AI tool predicts whether aggressive small cell lung cancer will respond to treatment

Results of a new study conclude that a pathology tool powered by artificial intelligence can predict whether a patient with extensive-stage small cell lung cancer will respond to platinum-based chemotherapy—before treatment has begun, and without additional biopsies. That means patients can avoid treatments that are unlikely to help them, have a chance to enroll earlier in clinical trials of newer drugs, and may get a clearer picture of their prognosis.

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Scalable sensors lower the cost of studying genetic disorders

Researchers have demonstrated a new class of low-cost, scalable sensors that can be used to monitor electrical activity in human cerebral organoids. Because electrical signals are key to understanding brain function, this advancement facilitates research into both neurodevelopment and genetic disorders such as Angelman syndrome.

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