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Focal Therapy for Prostate Cancer

This retrospective study used the National Cancer Database (NCDB) to identify patients 50 years or older with nonmetastatic prostate cancer diagnosed between 2010 and 2023 and seen at US centers with Commission on Cancer accreditation.9 Treatment categories were derived from NCDB first-course treatment variables. The study was approved by the University of Pittsburgh institutional review board (STUDY26020146) and followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.10

Inappropriate focal therapy use was defined as focal therapy in low-, high-, or very–high-risk disease.2 Intermediate-risk focal therapy was reported separately because the NCDB does not capture trial enrollment, registry participation, or lesion characteristics needed to classify appropriateness.

Temporal trends were assessed using Cochran-Armitage tests. Multivariable logistic regression evaluated patient-and facility-level characteristics associated with focal therapy vs radical prostatectomy. Adjusted predicted probabilities and average marginal effects were estimated using facility-clustered robust standard errors. The eMethods in Supplement 1 provide additional methodologic detail.

Navigating Challenges and Opportunities in MultiOmics Integration for Personalized Healthcare

The field of multi-omics has witnessed unprecedented growth, converging multiple scientific disciplines and technological advances. This surge is evidenced by a more than doubling in multi-omics scientific publications within just two years (2022–2023) since its first referenced mention in 2002, as indexed by the National Library of Medicine. This emerging field has demonstrated its capability to provide comprehensive insights into complex biological systems, representing a transformative force in health diagnostics and therapeutic strategies. However, several challenges are evident when merging varied omics data sets and methodologies, interpreting vast data dimensions, streamlining longitudinal sampling and analysis, and addressing the ethical implications of managing sensitive health information. This review evaluates these challenges while spotlighting pivotal milestones: the development of targeted sampling methods, the use of artificial intelligence in formulating health indices, the integration of sophisticated n-of-1 statistical models such as digital twins, and the incorporation of blockchain technology for heightened data security. For multi-omics to truly revolutionize healthcare, it demands rigorous validation, tangible real-world applications, and smooth integration into existing healthcare infrastructures. It is imperative to address ethical dilemmas, paving the way for the realization of a future steered by omics-informed personalized medicine.

Multidisciplinary research priorities for artificial intelligence in mental health: a call to action

The use of artificial intelligence (AI) is anticipated to transform mental health care. However, the rapid research growth in this field has outpaced coordinated frameworks, leaving research efforts fragmented, standards inconsistent, and safeguards for safety and ethics largely absent. This Position Paper outlines a coordinated roadmap to guide the responsible evaluation and implementation of AI in mental health, structured across four overarching priority domains that define near-term actions and longer-term strategic goals.

Banks can freeze accounts starting this week in ‘good faith’ law

A LAW to protect vulnerable citizens in one US state has gone into effect this week.

Colorado banks and credit unions can begin freezing suspicious transactions under a new law designed to protect older and vulnerable residents from financial scams.

The Adults’ Security and Safeguards from Exploitations in Transactions Act, or ASSET Act, came into effect on August 12.

Curiosity Mars rover discovers field of honeycomb textures

As NASA’s Curiosity rover recently began climbing a Martian valley nicknamed “Valle Grande,” it sent back images that were a familiar sight to mission scientists: honeycomb-like textures called polygonal fractures, each about 1.5–3 inches (4–8 centimeters) across. The mission has spotted small patches of these geometric shapes several times before, but nothing at the scale discovered in Valle Grande.

In a 360-degree panorama that the rover captured on June 19 and 20, the 4,930th and 4,931st Martian days, or sols, of the mission, the polygonal shapes spread in all directions for as far as the rover can see. They even wrap around the sides of a nearby butte nicknamed “Miraflores,” which stands 20 feet (6 meters) tall and is topped with a thick cap of sand.

“We’ve seen a lot of fascinating landscapes through Curiosity’s eyes, but this sea of polygons took our breath away,” said the mission’s project scientist, Ashwin Vasavada of NASA’s Jet Propulsion Laboratory in Southern California. “We measured their shapes and chemistry carefully and are hopeful there are clues in the data as to how these features formed.”

Artificial hibernation reveals synaptic engram architecture associated with memory retention

If individual synapses were the sole key to holding onto memories, this sudden structural “demolition” should have erased everything the mice learned. Remarkably, it didn’t. Once the mice woke up and recovered, their memories were completely intact.

The Power Clusters: The synapses connecting “memory-encoding” neurons (the specific cells storing the memory) weren’t randomly scattered. Instead, they were organized into tightly bound, spatially clustered groups. When hibernation wiped out standard synapses, the brain prioritized protecting these specialized clusters.

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