Emerging evidence suggests a possible link between anorexia nervosa (AN) and alterations in the gut microbiota. This study aimed to characterize the gut microbiota profile in a cohort of Chinese female patients with AN.

A comparative analysis of the gut microbiota was conducted between 30 female patients with AN and 30 sex- and age-matched healthy controls (HCs). Fecal samples were collected for 16S rRNA gene sequencing analysis. All participants were assessed using the Eating Disorder Inventory (EDI) and the Childhood Trauma Questionnaire (CTQ). Bioinformatics analysis was performed using QIIME2, and statistical analyses were carried out with SPSS 26.0 and R software. Correlations between microbiota differences and body mass index (BMI), EDI, and CTQ were further investigated.

The analysis revealed differences in beta diversity and the abundances of specific microbial taxa between the two groups; however, no significant differences were observed in alpha diversity nor in the associations between gut microbiota and BMI, disease severity, or childhood trauma.

This study identified limited differences in the gut microbiota composition between patients with AN and HCs. Critically, no robust associations between gut microbiota and clinical features were found after rigorous multiple comparison correction. While nominal (uncorrected) correlations were observed between the specific microbiota and psychological traits, these results are exploratory and should be considered hypothesis-generating. They highlight a potential avenue for future research but require validation in larger, longitudinal cohorts to determine their reproducibility and biological significance.

This study aimed to investigate the preoperative psychological status of adult patients with equinocavovarus foot deformity and to examine the association between preoperative anxiety/depressive symptoms and the clinical outcomes of corrective surgery in this population.

A retrospective analysis was conducted on 103 adult patients who underwent corrective surgery for equinocavovarus foot at Xi'an Honghui Hospital between March 2014 and July 2023. Baseline data were collected. Patient psychological status, ankle-hindfoot function, pain, and quality of life were assessed preoperatively and at the final follow-up using the Hospital Anxiety and Depression Scale (HADS), the American Orthopedic Foot & Ankle Society (AOFAS) ankle-hindfoot score, the Visual Analog Scale (VAS), and the 36-Item Short Form Health Survey (SF-36). Based on preoperative HADS scores, patients were categorized into an anxiety/depression group (Group A) and a non-anxiety/depression group (Group B). The two groups were compared with respect to baseline characteristics (gender, age, disease duration, BMI, follow-up duration), clinical outcomes, and the degree of improvement in all assessment metrics.

A total of 83 patients completed the follow-up, among whom 38 (45.78%) exhibited preoperative anxiety/depression symptoms. No significant differences were found in baseline characteristics between the two groups (all P > 0.05). At the final follow-up, both groups showed significant improvement in VAS, AOFAS, SF-36 (PCS/MCS), and HADS (A/D) scores compared to their preoperative baselines (all P < 0.001). Intergroup comparisons revealed that Group A had significantly lower AOFAS and SF-36 (PCS/MCS) scores, and significantly higher VAS and HADS (A/D) scores than Group B, both preoperatively and at the final follow-up (all P < 0.001). Regarding the degree of improvement, Group A demonstrated a smaller magnitude of improvement in VAS (P < 0.01), AOFAS (P < 0.01), and SF-36 PCS (P < 0.001) compared to Group B. Conversely, Group A showed a greater improvement in SF-36 MCS and HADS (A/D) scores (all P < 0.001).

While surgery improved all outcomes, patients with preoperative anxiety/depression exhibited persistently worse clinical scores. Their improvement profile was distinct: smaller gains in pain and physical function but greater mental health improvement. Addressing preoperative psychological status may optimize comprehensive outcomes.

Chimeric antigen receptor T (CAR-T) cell therapy has achieved transformative success in hematological malignancies; however, its translation to solid tumors remains severely limited by tumor heterogeneity, immunosuppressive microenvironments, and safety concerns such as on-target/off-tumor toxicity. A major contributor to these challenges is the lack of preclinical models capable of faithfully recapitulating human tumor architecture and tumor-immune interactions. Conventional two-dimensional cell cultures and animal models frequently fail to predict CAR-T efficacy, resistance, and toxicity observed in patients. Organoid technology, particularly patient-derived organoids (PDOs) and immune-integrated organoid systems, has emerged as a next-generation platform that bridges this translational gap. By preserving patient-specific genetic, phenotypic, and spatial heterogeneity, organoids provide a physiologically relevant and scalable system for interrogating CAR-T cell behavior in human-like tumor contexts. Recent advances in tumor-immune co-culture, vascularized organoids, and microfluidic organoid-on-a-chip platforms have further expanded their utility for dynamic assessment of CAR-T infiltration, cytotoxicity, cytokine release, and adaptive resistance mechanisms. In this review, we comprehensively examine how organoid-based models are reshaping the CAR-T development pipeline, spanning target discovery and validation, functional efficacy assessment, safety profiling, and optimization of combination therapies. We further discuss emerging applications of organoids as patient-specific "avatars" for personalized CAR-T selection and response prediction. Finally, we highlight current technical limitations and future bioengineering directions required to enable clinical translation. Collectively, organoid platforms represent a transformative tool for accelerating precision development of next-generation CAR-T cell therapies and advancing human-relevant immuno-oncology research.

To address clinical bottlenecks of traditional antipsychotic drugs, including delayed onset of action, significant peripheral side effects, and poor patient compliance, nanodelivery systems offer a feasible approach through their unique physicochemical properties to improve drug solubility, optimize in vivo transport, and enhance blood-brain barrier (BBB) penetration efficiency. This review focuses on the application potential and translational value of nanodelivery systems in psychiatric disorders. We systematically summarize recent advances in the construction strategies of mainstream nanocarriers, including lipid‑based, polymer‑based, inorganic nanomaterials, Metal-Organic Frameworks (MOFs), and Extracellular Vesicles (EVs), as well as commonly used nanoparticle preparation and characterization techniques. We briefly discuss key challenges facing nanoformulations, such as long‑term safety, large‑scale production, and batch‑to‑batch consistency, and highlight future directions driven by artificial intelligence and precision medicine. This review aims to provide insights for the rational design of nanodelivery systems for psychiatric disorders and to advance the development of precision psychiatry.

Chronic constipation and depression are highly prevalent worldwide. These two conditions frequently co-occur in clinical practice. Accumulating evidence indicates that gut microbiota dysbiosis mediates this comorbidity through the microbiota-gut-brain axis (MGBA).

This narrative review systematically summarizes current research on MGBA bidirectional communication mechanisms, gut microbiota alterations in comorbid patients, and microbiota-targeted intervention strategies.

The MGBA facilitates bidirectional communication through four major pathways: neural pathways via the vagus nerve, immune pathways via cytokines, endocrine pathways via the HPA axis, and metabolic pathways via short-chain fatty acids and neurotransmitter precursors. Gut dysbiosis is associated with comorbidity and may contribute to its pathogenesis through multiple mechanisms. First, neurotransmitter metabolism becomes dysregulated, particularly in the serotonin and GABA systems. Second, chronic low-grade inflammation develops with elevated pro-inflammatory cytokines. Third, intestinal barrier dysfunction occurs, leading to increased permeability and bacterial translocation. Fourth, HPA axis hyperactivity emerges. Fifth, production of microbial metabolites is altered, including short-chain fatty acids and tryptophan metabolites. Comorbid patients exhibit characteristic microbiota signatures. These include reduced abundance of butyrate-producing bacteria such as Faecalibacterium, Roseburia, and Coprococcus. Microbial diversity decreases significantly. Pro-inflammatory taxa become enriched. Several evidence-based interventions show promise. These include psychobiotics, fecal microbiota transplantation, and dietary modifications such as Mediterranean diet and high-fiber intake. Exercise and integrative approaches including traditional Chinese medicine also demonstrate beneficial effects.

The gut microbiota represents a critical hub connecting gastrointestinal and mental health. Microbiota-targeted therapies offer promising strategies for managing chronic constipation-depression comorbidity. Future research should establish causal relationships and develop reliable microbial biomarkers. Precision medicine approaches based on individual microbiome profiles are needed to optimize therapeutic outcomes.

Ethnic inequalities exist in the prevalence of mental disorders and their associated treatment outcomes. Cultural variation may influence psychological symptom expression; understanding this might inform care and ultimately reduce care disparities.

Data were analysed from 147,037 individuals referred to psychological treatment services in London, England. Moderated network analysis was used to examine the expression and co-occurrence of symptoms of depression, anxiety, and social functioning. Age and gender were included as covariates, and ethnicity (11 categories) was entered as the moderating variable. Symptom-level differences and differences in symptom-to-symptom relationships were estimated across all ethnic group comparisons.

There was substantial variation in symptom networks between ethnic groups. White British individuals showed the most differences compared to other ethnic groups, particularly with higher endorsement of anxiety-related symptoms (e.g. nervousness and excessive worry) and greater reported functional impairment in work and social domains. Differences in symptom co-occurrence (the relationships between symptoms) were less frequent than differences in individual symptom levels. Across groups, several symptoms showed consistent relationships, suggesting shared aspects of distress alongside culturally patterned variation in symptom expression.

The influence of ethnicity on both symptom levels and symptom co-occurrence underscores the importance of culturally informed assessment. These findings highlight the need for services to consider culturally relevant symptom presentations to promote more equitable and appropriate mental health care.

College students face significant mental health challenges during their academic journey, yet the heterogeneity in their psychological adaptation patterns remains poorly understood. Traditional variable-centered approaches fail to capture the diverse trajectories that students may follow. Recent studies indicate that 20-30% of Chinese college students experience clinically significant psychological distress, highlighting the need for person-centered analytical approaches.

This longitudinal study employed formal Latent Class Growth Modeling (LCGM) using the Expectation-Maximization algorithm implemented in Python to identify distinct mental health trajectories among 2,562 Chinese college students assessed at enrollment (T1), sophomore year (T2, 18 months), and junior year (T3, 30 months). The Symptom Checklist-90 (SCL-90) Global Severity Index served as the primary outcome. Model selection was based on a composite score integrating BIC, entropy, bootstrap stability, and clinical relevance.

A four-class solution demonstrated optimal fit (composite score = 0.768, entropy = 0.779, bootstrap stability = 0.933). Four trajectories emerged: Low-Optimal (13.2%; M_T1 = 1.04), Low-Stable (29.8%; M_T1 = 1.19), Moderate-Improving (32.9%; M_T1 = 1.47), and High-Risk-Improving (24.1%; M_T1 = 1.98). The four classes were primarily differentiated by baseline severity (η²baseline = 0.550), with more modest between-class differences in rate of change (η²change = 0.036). The high-risk class showed the steepest decline (slope = - 0.0100/month) but 31.8% remained above clinical threshold at T3. The high-risk class exhibited the largest observed within-class variability at enrollment (T1 SD = 0.562), indicating heterogeneous baseline symptom levels among students in this group.

Approximately one quarter of college students follow a high-risk mental health trajectory requiring targeted intervention. The formal LCGM approach with simultaneous parameter estimation provides robust classification with moderate classification quality (entropy = 0.779) and high bootstrap stability (0.933). These findings support implementing tiered early warning systems based on baseline screening.

Aortic dissection (AD) is a life-threatening cardiovascular emergency with declining postoperative quality of life (QoL). The teach-back method has shown effectiveness in chronic disease management, but its application in postoperative AD patients remains unexplored.

This quasi-experimental study with ward-level cluster allocation enrolled 210 AD patients (105 per group) at a tertiary hospital in Nanchang, China, from January 2023 to June 2024. The experimental group received teach-back method-based continuing nursing, while the control group received routine care. Primary outcomes included self-management behavior assessed by the Self-Management Assessment Scale (SMAS) and QoL measured by the Physical Component Summary (PCS) and Mental Component Summary (MCS) of the Short Form-36 Health Survey (SF-36) at baseline, discharge, 1-month, and 6-month follow-up. Secondary outcomes comprised health knowledge scores at baseline and 1-month post-discharge, and adverse clinical outcomes including 30-day unplanned readmission rates, 6-month AD recurrence rates, and total adverse events.

The experimental group demonstrated significantly higher SMAS across all dimensions with a significant time×group interaction (P < 0.001). Disease knowledge questionnaire score at 1-month was significantly higher in the experimental group (21.36 ± 2.89 vs. 15.82 ± 3.54, P < 0.001). Both PCS and MCS scores showed significant improvements over time (both P < 0.001), with the experimental group achieving higher scores than the control group at all follow-up time points (all P < 0.001). A significant time×group interaction effect was observed for MCS (P = 0.0052) but not for PCS (P = 0.599). The experimental group achieved significantly better blood pressure control at 6 months (SBP: 125.6 ± 10.8 vs. 133.4 ± 14.8 mmHg, P < 0.001). The experimental group had lower 30-day readmission rates (6.67% vs. 17.14%, P = 0.016), 6-month AD recurrence rates (4.76% vs. 14.29%, P = 0.014), and total adverse events (4.76% vs. 12.38%, P = 0.048). Follow-up completion rates exceeded 93% at all time points.

Teach-back method-based continuing nursing significantly improved self-management behaviors, QoL, and reduced adverse outcomes in postoperative AD patients, warranting integration into routine discharge protocols.