Steroid receptor coactivator-1 (SRC-1), also known as nuclear receptor coactivator-1 (NCOA1), represents the first identified member of the p160 nuclear receptor coactivator family and plays a pivotal role in integrating steroid hormone signals, regulating gene transcription, and maintaining neural homeostasis in the central nervous system (CNS). SRC-1 exhibits region-specific, cell-type-specific, and sexually dimorphic expression patterns in the brain, with prominent distribution in key regions including the hippocampus, cerebral cortex, hypothalamus, and amygdala. Functional studies demonstrate that SRC-1 participates in diverse neural functions such as learning and memory, energy metabolism, emotional regulation, and reproductive behavior through modulation of synaptic plasticity-related genes, neurotrophic factors, and metabolic pathways. Aberrant SRC-1 expression is closely associated with neurodegenerative diseases, autism spectrum disorders, and glioblastoma. This review systematically summarizes the molecular structure, expression characteristics, physiological functions of SRC-1, and its roles in neurological disorders, while discussing its potential applications as a diagnostic biomarker and therapeutic target.
Exploring the neuroprotective potential of ligustrazine: a preclinical meta-analysis and machine learning perspective on cerebral ischemia-reperfusion injury
ObjectiveThis study aimed to assess the efficacy of ligustrazine in treating cerebral ischemia-reperfusion (I/R) injury and construct a preclinical evidence framework by meta-analysis and machine learning.MethodsA systematic search was conducted for preclinical studies published in PubMed, Embase, Web of Science, and the Cochrane Library up to June 25, 2024. The inclusion criteria encompassed preclinical animal studies pertinent to the topic. Data extraction was performed independently by two individuals, Stata 17.0 software was used for quantitative analysis, R (version 4.3.3) and Python (version 3.11.4) were used for machine learning with neurological function score as the dependent variable.ResultsA total of 23 articles were included, involving 381 animals in the meta-analysis and 321 animals in the machine learning component. Ligustrazine significantly improved neurofunctional scores (NFS) [Longa criteria, SMD = −1.59, 95%CI (−2.16, −1.01), P < 0.001; mNSS criteria, SMD = −1.67, 95%CI (−2.36, −0.97), P < 0.001], cerebral infarct volume (%) [SMD = −2.56, 95%CI (−3.03, −2.09), P < 0.001], and BBB [SMD = −3.06, 95%CI (−4.53, −1.59), P < 0.001]. Furthermore, machine learning analyses, with NFS as the dependent variable, identified the time of first dose, duration, and dose as key determinants of neurofunctional improvement with ligustrazine. Notably, model interpretation suggested that greater improvements were more likely to occur when the initial administration of ligustrazine occurred within 24 h prior to (or 2.21 h post) the ischemic event, at a dosage of 23.53–34.69 mg/kg/day (or 45.71 to 75.65 mg/kg/day), and with an administration duration exceeding 71.43 h.ConclusionThe combination of meta-analysis and machine learning in this study not only confirms that ligustrazine is effective in reducing cerebral I/R injury, but also provides a framework for elucidating the preclinical intervention variables, thus offering novel insights for optimizing preclinical strategies of ligustrazine in cerebral I/R injury.
LFP-LOC: an LFP power–based method for validating the anatomical placement of high-density neural probes in rodents
High-density CMOS-based neural probes provide unprecedented spatiotemporal resolution for in-vivo electrophysiology, yet accurate validation of implant position remains challenging. Here we present LFP-LOC, a simple and interpretable method for intraoperative validation and refinement of probe anatomical location based on the spatial distribution of local field potential (LFP) power. Using spontaneous activity recordings performed in rodents, we compute power spectral densities in canonical LFP bands and apply dimensionality reduction and clustering to identify electrodes with shared spectral signatures. Across multiple implant sites, probe technologies, electrode layouts, and experimental conditions, the resulting clusters consistently align with anatomical boundaries. Applied to high-density probes with up to 1,024 electrodes/channels and sub-30 μm pitch, power features converge within approximately 20 s of recordings, allowing online intraoperative assessment. By leveraging the robust relationship between LFP power and brain structure, LFP-LOC enables rapid validation and adjustment of probe placement during surgery, complements histological validation, and may facilitate mesoscale electrophysiological studies.
Exercise as a multiscale recalibration of stress-related homeostatic balance
Chronic stress disrupts homeostasis in the brain and body, leading to anxiety, depression, and cardiovascular and metabolic dysfunction. Although exercise can counter these effects, the mechanisms are scattered across fields and not yet integrated. This review proposes a multi-scale framework. Exercise is not only stress-relieving; it is also a controllable challenge that can recalibrate the system when repeated bouts are matched by sufficient recovery and bioenergetic support. We propose that repeated exercise engages a stress response–adaptation–recovery cycle, in which peripheral signals from skeletal muscles, liver, adipose tissue and gut convey body metabolic state to the brain and are consolidated into durable plasticity only when mitochondrial capacity, substrate availability, and redox balance permit recovery. These signals pass through the blood-brain barrier and engage plasticity switches, including neurotrophic signals, epigenetic modification and metabolic coupling, thus stabilizing the neural circuits of threat appraisal, reward processing and contextual memory. By integrating these dimensions, we clarify how exercise can transform short-term physical stress into lasting resilience and provide direction for future research.
Task-aligned outcome learning in psychiatry: reducing endpoint dilution
Psychiatric research relies on well-defined outcomes for standardization, comparability, and replication, yet investigators often fix broad endpoints before knowing which symptom domains carry task-relevant signal. Even when psychometrically sound and clinically useful, composite measures can dilute predictive information and attenuate treatment effects when predictability or responsiveness concentrates in only a subset of symptoms—thus making studies appear negative despite meaningful change. This Perspective proposes a task-aligned, two-stage machine-learning framework for learning the appropriate outcome. In the first stage, constrained discovery derives a clinically interpretable outcome from a prespecified item pool. In the second, confirmatory evaluation tests the prespecified hypothesis either on a fixed learned outcome, when the aim is to assess a previously derived endpoint in a closely matched study, or on a relearned outcome generated by the same prespecified procedure, when the aim is to test whether that procedure can recover a task-aligned endpoint across different studies. The framework complements psychometrics and open-science practices, shifting focus from broad unsupervised composites to empirically supported targets, with safeguards to keep results interpretable and rigorous.
Editorial: Perinatal substance use and maternal mental health
The correlation between phubbing and depression anxiety stress of first-year medical students: the mediating role of sedentary behavior
BackgroundFreshmen often experience challenges when adjusting from high school to college, which may elevate levels of depression, anxiety, and stress. This phenomenon is particularly pronounced in medical schools, where the overall academic atmosphere is widely regarded as exceptionally demanding and stressful.ObjectivesTo examine the indirect effect of sedentary behavior on the relationship between phubbing and depression anxiety stress of first-year medical students.MethodsThis study conducted a cross-sectional survey with 795 first-year medical students from Soochow University in China from October 2024 to November 2024 by using electronic questionnaire. The instruments were Depression Anxiety Stress Scale-21 (DASS-21), Generic Scale of Phubbing (GSP), and Adolescent Sedentary Activity Questionnaire (ASAQ).ResultsThe findings indicate that first-year medical students’ phubbing and sedentary behavior positively affects their depression anxiety stress (r = 0.120 ~ 0.815, both p < 0.01), and phubbing positively impacts medical students’ sedentary behavior (r = 0.128, p < 0.01). Additionally, sedentary behavior acts as a significant mediator between phubbing and depression, anxiety, and stress. The indirect effect contributes to 1.9%~2.5% of the total effect.ConclusionThese findings indicate that reducing depression anxiety stress in first-year medical students can be achieved not only through direct improvements in phubbing but also through the indirect effects of reducing sedentary behavior.
Autonomic nervous system reactions to secondary exposure to disaster-related imagery
AimThis study investigated how disaster-related imagery affects emotional and autonomic nervous system (ANS) responses, using heart rate (HR) and heart rate variability (HRV), in individuals with indirect exposure to the 2011 Great East Japan Earthquake (GEJE).MethodsThirty-six healthy adults who had experienced strong ground shaking during the GEJE, but not the tsunami directly, viewed four types of videos: natural scenery (neutral), earthquake scenes, tsunami footage, and promotional videos repeatedly broadcast after the disaster. Subjective emotional responses (State-Trait Anxiety Inventory, Positive and Negative Affect Schedule), HR, and HRV indices were measured before, during, and after each video.ResultsCompared to the neutral video, disaster-related videos significantly decreased HR and HRV during viewing, indicating an orienting or freeze-type ANS response. Earthquake footage, likely to evoke autobiographic fear, predominantly suppressed parasympathetic indices, while tsunami footage, associated with vicarious fear, predominantly suppressed sympathetic activity. Immediately after viewing, sympathetic activation increased significantly, consistent with a rebound active defense pattern. Notably, promotional videos did not induce subjective distress but still altered HR and HRV indices, suggesting unconscious physiological reactivity.ConclusionDisaster-related imagery evokes distinct ANS responses depending on the emotional content and the viewer’s trauma history. Autobiographic and vicarious fear may differentially affect sympathetic and parasympathetic suppression, respectively. Furthermore, this cross-sectional evaluation demonstrates that even seemingly non-invasive media exposure years after a disaster can trigger autonomic changes. These findings underscore the urgent need for appropriate media broadcasting guidelines to protect public health following both seismic and climatic catastrophes.
Joint latent profiles of death anxiety and treatment adherence in HCC patients
BackgroundHepatocellular carcinoma (HCC), one of the leading contributors to the global cancer burden, often places patients in a dual predicament of pronounced death anxiety and suboptimal treatment adherence. Prior research has largely treated death anxiety and adherence as independent, homogeneous constructs, thereby overlooking potential within-population heterogeneity and their co-occurring patterns. This study adopted a person-centered approach to identify joint latent profiles of death anxiety and treatment adherence among patients with HCC and to examine factors associated with profile membership.MethodsA cross-sectional design was employed. From October to November 2025, 586 patients with HCC were recruited via convenience sampling from five tertiary general hospitals in Shenzhen, Beijing and Lhasa, China. Data were collected using the Death Anxiety Scale (DAS), General Medication Adherence Scale (GMAS), Health Literacy Scale Short-Form (HLS-SF), and Fear of Progression Questionnaire–Short Form (FoP-Q-SF).ResultsLatent profile analysis identified three qualitatively distinct subgroups: low death anxiety–high treatment adherence, moderate death anxiety–moderate treatment adherence, and high death anxiety–low treatment adherence. Across profiles, death anxiety and treatment adherence exhibited a clear inverse co-variation pattern. Multinomial logistic regression indicated that health literacy and fear of disease progression were key psychosocial factors differentiating profile membership. In addition, demographic and disease-related variables showed varying predictive effects on profile assignment.ConclusionsPatients in the high death anxiety–low treatment adherence profile may represent a clinically important high-risk subgroup for targeted screening and supportive care. Clinical practice should emphasize assessment of health literacy and profile-specific psychosocial needs when planning stratified interventions. However, because of the cross-sectional design, the observed associations should not be interpreted causally, and longitudinal studies are needed to examine temporal transitions between profiles and their effects on subsequent treatment outcomes.
Circling back to RNA vaccines
Nature Biotechnology, Published online: 11 May 2026; doi:10.1038/s41587-026-03155-8
While circRNA is often framed as a more stable, longer-lasting alternative to linear mRNA, its real-world advantages remain largely theoretical, and it is unclear whether greater molecular stability will translate into meaningful clinical gains.