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Violence linked to depression in adolescent girls but not boys

A longitudinal study of adolescents from the Chicago metropolitan area found that in female, but not in male adolescents, higher exposure to violence was associated with more severe depression symptoms. In males, depression was associated with the expansion of the salience network of the brain and with increased connectivity of this network. The paper was published in Translational Psychiatry.

Violence exposure in this study was defined as experiencing, witnessing, or being repeatedly confronted with acts of interpersonal physical violence, such as being shoved, kicked, punched, or attacked with a weapon. It is a major risk factor for mental health problems, increasing the likelihood of all types of psychopathology.

Childhood adversities such as physical abuse and family violence account for a substantial proportion of psychiatric disorders that emerge during adolescence. This period is especially sensitive because key social and emotional brain systems are still developing. Exposure to violence during adolescence is associated with maladaptive emotion regulation strategies, such as rumination and emotional suppression, which contribute to rising rates of depression.

Study Reveals an Unexpected Way to Boost Recovery After a Stroke

For many stroke survivors, recovery may not mean restoring what was lost but strengthening what remains.

Stroke survivors often face substantial and long-lasting problems with their arms. Both arms often decline together: When one arm is more severely affected by the stroke, the other becomes more difficult to use as well.

Compared with a healthy person’s dominant hand, a stroke survivor may take up to three times longer to complete everyday tasks using their less-impaired arm.

This creates a frustrating reality. People with severe impairment in one arm must rely almost entirely on their other arm for daily activities, such as eating, dressing, and household tasks.

B cells join T cells to drive sight-threatening arthritis in children

A team led by UCL researchers with Great Ormond Street Hospital (GOSH) and Moorfields Eye Hospital, found B cells—alongside T cells—play a key role in arthritis-related eye disease (JIA uveitis), a condition that can cause long-term vision loss in children. The study challenges how the disease has been previously understood, and could open the door to new treatments that help protect children’s sight.

Juvenile idiopathic arthritis (JIA) is the most common form of arthritis in children under the age of 16, affecting around one in every 1,000 children in the UK. Approximately 30% of patients with JIA also develop uveitis—an inflammatory condition of the eye that is potentially sight-threatening.

Although some treatments are available today for the condition, up to a third of affected children still experience some degree of permanent vision loss by the time they reach adulthood.

An off-the-shelf immunotherapy for targeting solid tumors: Ready-to-use CAR-NKT cells show promise

A UCLA research team has identified the best design for a promising new type of immunotherapy that could be mass-produced to treat multiple solid tumors. The study focused on engineered invariant natural killer T cells, or NKT cells—powerful immune cells with a unique ability to infiltrate solid tumors—and systematically compared four targeting systems, called chimeric antigen receptors, or CARs, that direct these cells to attack cancer.

The study was published in the journal Blood Immunology & Cellular Therapy.

CAR-T cell therapies have revolutionized treatment for certain blood cancers like leukemia and lymphoma, but these successes haven’t extended to solid tumors, which make up the vast majority of cancers. Solid tumors build dense protective barriers that block therapeutic cells from reaching the cancer and display varied targets that allow cancer cells to escape detection.

Distinct Mutations in the Same Gene Drive Cancer Differently

Scientists mapped every possible mutation in a key genetic hotspot, revealing how distinct mutations drive tumor growth differently, which could influence anticancer therapy success.

Read more.

Mapping diverse mutations within a cancer hotspot revealed that distinct variants drive tumor growth to different extents, which could guide anticancer therapies.

A simple blood test could change how Alzheimer’s is diagnosed

A blood test, combined with an ultrathin material derived from graphite, could significantly advance efforts to detect Alzheimer’s disease at its very earliest stage, even before symptoms appear.

Alzheimer’s disease is the most common form of dementia. For millions of Europeans—and the health services that care for them—it is a ticking time bomb, with still no cure. But EU researchers are developing a simple tool to enable much earlier detection, potentially decades before symptoms appear.

Early detection matters because treatment is most effective when started as soon as possible. This gives people a better chance to slow the progression of the disease and plan for the future. Today, around 7 million people in Europe live with Alzheimer’s, a number expected to double by 2030, according to the European Brain Council.

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware’s noisy updates with neural network training, slashing energy use by nearly six orders of magnitude versus GPUs while boosting accuracy on vision tasks. The study validates EaPU on 180 nm memristor arrays and large-scale simulations.

Analog in-memory computing with memristors promises to overcome digital chips’ energy bottlenecks by performing matrix operations via physical laws. Memristors are devices that combine memory and processing like brain synapses.

Inference on these systems works well, as shown by IBM and Stanford chips. But training deep neural networks hits a snag: “writing” errors when setting memristor weights.

Physics-driven ML to accelerate the design of layered multicomponent electronic devices

Many advanced electronic devices – such as OLEDs, batteries, solar cells, and transistors – rely on complex multilayer architectures composed of multiple materials. Optimizing device performance, stability, and efficiency requires precise control over layer composition and arrangement, yet experimental exploration of new designs is costly and time-intensive. Although physics-based simulations offer insight into individual materials, they are often impractical for full device architectures due to computational expense and methodological limitations.

Schrödinger has developed a machine learning (ML) framework that enables users to predict key performance metrics of multilayered electronic devices from simple, intuitive descriptions of their architecture and operating conditions. This approach integrates automated ML workflows with physics-based simulations in the Schrödinger Materials Science suite, leveraging physics-based simulation outputs to improve model accuracy and predictive power. This advancement provides a scalable solution for rapidly exploring novel device design spaces – enabling targeted evaluations such as modifying layer composition, adding or removing layers, and adjusting layer dimensions or morphology. Users can efficiently predict device performance and uncover interpretable relationships between functionality, layer architecture, and materials chemistry. While this webinar focuses on single-unit and tandem OLEDs, the approach is readily adaptable to a wide range of electronic devices.

Abstract: It’s about TIME (tumor immune microenvironment) for BreastCancer

Here, Carlos L. Arteaga & team analyze patient biopsies, finding CD8+ T cells in the TIME promote resistance to estrogen suppression in HR+ breast cancer via CXCL11 and immune-related pathways:

The images: GeoMx-based immunofluorescence of breast tumor tissue obtained during estrogen deprivation therapy (letrozole) demonstrates increased immune cell infiltration in estrogen deprivation–resistant tumors (right) compared with sensitive tumors (left).

1UT Southwestern Simmons Comprehensive Cancer Center, Department of Internal Medicine, University of Texas Southwestern (UTSW) Medical Center, Dallas, Texas, USA.

2Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy.

3Division of Pediatric Gastroenterology, Hepatology and Nutrition, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA.

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