Radically different
WASHINGTON — President Trump moved on Saturday to “reverse the crisis of serious mental illness in America” by boosting access to psychedelic drugs in clinical settings. In an executive order, he directed the federal government to rush access to treatments and reevaluate their status as controlled substances.
The order directs the Food and Drug Administration to expedite some psychedelics as breakthrough drugs, as well as allowing them to be used through right-to-try legislation, which allow terminally ill patients to try experimental drugs outside of usual regulatory pathways.
Background: Alzheimer disease (AD) affects cognition, treatment adherence, family connections, and health care resource allocation. Most patients with AD have low adherence to medication therapy due to the limitations associated with cognitive impairment. Therefore, increasing the involvement of patients and their family members in medication management is important to improve treatment outcomes and reduce the burden of care. Objective: This study explores the potential application of artificial intelligence (AI) in medication management for Chinese patients with early- to mid-stage AD focusing on enhancing medication adherence. The study first predicts and evaluates key factors through an online Delphi study, which provides a basis for their subsequent incorporation into the AI model as input variables to enable prediction of medication-taking behaviors. Since AI research in medication management for this population is still undeveloped, this paper further explores the multiple potentials of AI from a theoretical view, including drug dosage optimization, multidrug interaction detection, and family education support. It will provide a preliminary direction and theoretical basis for the development of an intelligent medication management system in the future. Methods: The exploratory online Delphi study with no modification predicted the key factors influencing medication adherence. Based on the results, the study confirmed the potential of AI to improve adherence. Participation by 12 experts in 3 rounds systematically assessed the core elements influencing patients’ adherence to their medication. Results: Family care, social support, environmental factors, emotional support, and patient behaviors were identified as the primary factors influencing medication adherence among Chinese patients with AD. These factors were validated and ranked through iterative Delphi rounds, with family care and social support receiving the highest importance scores. The Wilcoxon signed-rank test indicated no significant difference between rounds (=.06), supporting the stability of the consensus. These findings establish a foundational set of variables for AI systems that predict and enhance medication adherence. Conclusions: This study highlights the critical factors affecting medication adherence by Chinese patients with AD. It was designed as an exploratory online Delphi study to identify and prioritize key influencing factors, rather than to validate a specific AI-based system, and the findings provide a theoretical foundation for future AI-informed interventions. The results also indicate theoretical potential roles for AI in supporting medication management, such as optimizing drug dosage, detecting multidrug interactions, and enhancing family education.
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Background: Pediatric chronic pain affects up to one-third of youth and is associated with significant disruptions in social, emotional, and behavioral functioning. Although behavioral treatments are effective, access remains limited due to geographic, financial, and systemic barriers. Digital behavioral health interventions offer a promising solution, but many lack user-centered design, iterative refinement, and implementation-informed development strategies that support usability and scalability. Objective: This study aimed to develop and iteratively refine iGET Living, a digital graded exposure intervention for youth with chronic pain, using a combined user-centered and implementation-informed framework, and to evaluate its preliminary acceptability, feasibility, and user-perceived success. Methods: Guided by the Consolidated Framework for Implementation Research (CFIR) and the mHealth (mobile health) Agile Development and Lifecycle model, intervention development proceeded through 3 phases. Phase 0 translated an evidence-based in-person graded exposure treatment (GET Living) into an initial digital prototype. Phase 1 involved iterative user-centered refinement across 3 cycles of qualitative development sessions with youth with chronic pain (n=15), incorporating think-aloud usability testing, Likert-rated feedback, and rapid qualitative analysis mapped to CFIR constructs to guide real-time modifications to content, design, and functionality. Phase 2 piloted the refined intervention with a new sample of youth (n=38, n=30 completers) recruited from a tertiary pediatric pain clinic to evaluate feasibility, acceptability, treatment credibility and expectancy, and user-perceived functional improvements. Quantitative outcomes were summarized descriptively, and qualitative exit interview data were analyzed using rapid qualitative analysis. Results: Across development cycles, youth feedback informed substantive refinements to the intervention, including reducing text density, incorporating animated educational videos, enhancing interactive features, and improving navigation and layout. These changes resulted in progressive improvements in clarity, satisfaction, and acceptability across prototypes. In the Phase 2 pilot study, participants reported moderate-to-high treatment credibility (mean of 19.71 out of 30) and expectancy (mean of 17.96 out of 30), as well as high satisfaction (mean of 46.12 out of 60). Acceptability ratings across domains of the Theoretical Framework of Acceptability were favorable. Qualitative exit interviews highlighted the interventions’ perceived role in helping youth re-engage in valued activities. Conclusions: Using a combined CFIR and agile development approach, iGET Living emerged as a feasible, acceptable, engaging digital graded exposure intervention for youth with chronic pain. These findings highlight the value of integrating implementation frameworks and participatory design early in digital intervention development and support further evaluation in a preliminary efficacy trial. Trial Registration: ClinicalTrials.gov NCT05079984; https://clinicaltrials.gov/study/NCT05079984 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2022-065997
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Thousands of genes are expressed differently in the brains of men and women, researchers have discovered.
The findings could help explain differences in neurodevelopmental, psychiatric, and neurodegenerative disorders between the sexes.
While men are more likely to experience schizophrenia, attention deficit hyperactivity disorder, and Parkinson’s disease, women are more prone to mood disorders and Alzheimer’s disease.
The U.S. study, in Science, is the first systemic single-cell survey of sex differences in gene expression across multiple regions of the human brain.
“Together, these findings provide a comprehensive map of molecular sex differences in the human brain and offer initial insight into their underlying mechanisms and potential functional consequences,” Alex DeCasien, PhD, from the National Institute of Mental Health in Bethesda, Maryland, told Inside Precision Medicine.
DeCasien and co-workers conducted a high-resolution analysis of gene expression in tissue samples from the brains of 15 men and 15 women using single-nucleus RNA sequencing.
They then used data from earlier large neuroimaging studies to select six cortical regions to sample, four of which showed sex-related differences in grey matter volume and two in which no such differences were found.
The team found subtle but widespread differences in gene activity between men and women. Biological sex explained very little of the variance in gene expression across the brain, at less than 1%, but differences were widespread—with more than 3000 genes showing different expression according to sex in at least one cortical region.
The greatest sex-related differences in gene expression were on the sex chromosomes. However, most of the genes showing sex-related variations in expression were autosomal—carried on one of the 22 numbered non-sex chromosomes.
The predominant driver for sex-biased expression of genes on these autosomal chromosomes were sex steroid hormones such as estrogen and testosterone.
Surprisingly, more than half the X chromosome genes in women were expressed in both alleles for at least one cell type. This indicated that many had escaped X chromosome inactivation—a female phenomenon in which one of the two X chromosomes is switched off early in development to stop women producing double the number of X-linked gene products to men.
“That finding has implications for understanding sex-biased disease susceptibility because several genes implicated in neurodevelopmental disorders reside on the X chromosome,” commented Jessica Tollkuhn, PhD, from Cold Spring Harbor Laboratory, and S Marc Breedlove, from Michigan State University, in an accompanying Perspective article.
They noted that autosomal genes showing sex-biased expression were substantially enriched for extracellular matrix components, hormone signaling pathways, and metabolic processes. “Genes with greater expression in women were enriched for mitochondrial and synaptic functions, whereas male-biased genes were associated with metabolic and structural pathways,” the editorialists added.
“By pinpointing these sexually differentiated processes, the data provide a treasure trove for the discovery of biomarkers of and/or therapeutic targets for differential disease risk in men and women.”
DeCasien and team added: “These findings raise the possibility that sex differences in gene expression modulate the magnitude of genetic effects at risk loci, contributing to differences in disease vulnerability and to reduced portability of polygenic risk prediction across sexes.”
The post Brain Gene Variations Help Explain Neurological and Psychiatric Sex Differences appeared first on Inside Precision Medicine.
Across Europe, a movement is coming together for mental health. From local communities to European institutions, people are joining forces to place mental health at the centre of the conversation. […]
The post European Mental Health Week 2026 – Full Programme appeared first on Mental Health Europe.