NCCN Guidelines® Insights: Management of Immunotherapy-Related Toxicities, Version 2.2024.

The NCCN Guidelines for the Management of Immunotherapy-Related Toxicities are intended to provide oncology practitioners with guidance on how to manage the wide-ranging and potentially fatal toxicities that may occur with cancer immunotherapy. The guidelines address immune-related adverse events related to immune checkpoint inhibitors, CAR T-cell therapies, and lymphocyte engagers (which include T-cell-engaging bispecific antibodies). These NCCN Guidelines Insights highlight recent guideline updates pertaining to the management of emerging toxicities related to cancer immunotherapy.

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine.

Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship.

Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds.

A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challenge, we have created "encoding manifolds" that reveal the overall responses of brain areas to diverse stimuli with the resolution of individual neurons and their response dynamics. Here we use encoding manifold to compare the population-level encoding of primary visual cortex (VISp) with five higher visual areas (VISam, VISal, VISpm, VISlm, and VISrl).