Bio-engineering researchers of the endocrine pancreas for type 1 diabetes

Published Date: 02 Mar 2023

In people with type 1 diabetes, the immune system attacks and destroys insulin. The cells that control blood sugar and are part of the cells of the pancreas are called islets. Looking for...

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Northwestern Medicine investigators have developed a new imaging approach to more accurately assess blood flow in the spinal cord, a method that could be used to better inform treatment for neurological diseases and injuries, ...

A rare glimpse into the brain activity of a patient with obesity and loss of control eating on tirzepatide, marketed as Mounjaro and Zepbound, revealed that the medication suppresses signaling in the brain's "reward center" ...

Researchers at The Johns Hopkins Medicine say they have developed a new electronic medical records-based tool that should help doctors predict which patients are most at risk of losing a transplanted kidney graft.

Harnessing the muscle of one of the world's fastest supercomputers, researchers have built one of the largest and most detailed biophysically realistic brain simulations of an animal ever.

A new artificial intelligence tool that can create virtual representations of patients and predict individual health trajectories has been hailed a potential gamechanger for the clinical trial sector.

A health care chatbot can be a patient's first point of contact for some sensitive conversations from mental health to billing, a new CU Anschutz study has found.

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At some doctors' offices, AI is listening in the exam room

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Speeding the detection of three serious regional fungal infections

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Kidney organoids uncover Hippo signaling pathway as a therapeutic target for nephronophthisis

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FDA approves Caplyta for major depressive disorder in adults

The U.S. Food and Drug Administration has approved Caplyta (lumateperone) as an adjunctive therapy with antidepressants for the treatment of major depressive disorder in adults.

Family history key to predicting antidepressant response

A new study from Queen Mary University of London shows that a family's experience with certain medicines could help doctors predict how future generations will respond to the same drugs.

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