Genetic changes linked to two different syndromic forms of autism enhance reinforcement learning in adolescent male but not female mice.

Unlabelled: Autism Spectrum Disorder (ASD) is characterized by restricted and repetitive behaviors and social differences, both of which may manifest, in part, from underlying differences in corticostriatal circuits and reinforcement learning. Here, we investigated reinforcement learning in mice with mutations in either or , both high-confidence ASD risk genes associated with major syndromic forms of ASD. Using an odor-based two-alternative forced choice (2AFC) task, we tested adolescent mice of both sexes and found male and heterozygote (Het) mice showed enhanced learning performance compared to their wild type (WT) siblings.

A Bayesian Joint Model of Multiple Nonlinear Longitudinal and Competing Risks Outcomes for Dynamic Prediction in Multiple Myeloma: Joint Estimation and Corrected Two-Stage Approaches.

Predicting cancer-associated clinical events is challenging in oncology. In Multiple Myeloma (MM), a cancer of plasma cells, disease progression is determined by changes in biomarkers, such as serum concentration of the paraprotein secreted by plasma cells (M-protein). Therefore, the time-dependent behavior of M-protein and the transition across lines of therapy (LoT), which may be a consequence of disease progression, should be accounted for in statistical models to predict relevant clinical outcomes.

Clinical, Analytical, and Echocardiographic Associations of Impaired Cardiorespiratory Fitness After Anthracycline Chemotherapy in Breast Cancer: EPIC Fitness Study.

Purpose: This study explores the effects of anthracycline chemotherapy (AC) on breast cancer patients, focusing on changes in body composition, advanced echocardiographic parameters at rest and during exercise, and biomarkers; and subsequently assesses whether these parameters are associated with impaired cardiorespiratory fitness (CRF).

Methods: In this prospective study, we evaluated women with early-stage breast cancer undergoing AC at three visits: before AC, 1 month after, and 6 months post-AC.

Results: The study included 32 women with breast cancer, with functional disability increasing from 9.

Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features using a machine learning approach. Fifty-four participants (27 stroke patients and 27 healthy age and sex-matched controls) were recruited.

Chitosan/γ-PGA nanoparticles and IFN-γ immunotherapy: A dual approach for triple-negative breast cancer treatment.

Interferon-γ (IFN-γ) is a key mediator in antitumor immunity and immunotherapy responses, yet its clinical applications remain restricted to chronic granulomatous disease and malignant osteopetrosis. IFN-γ effectiveness as a standalone treatment has shown limited success in clinical trials and its potential for synergistic effects when combined with immunotherapies is under clinical exploration. A particularly compelling combination is that of IFN-γ with Toll-like receptor (TLR) agonists that holds significant promise for cancer treatment.