Currently, the treatment of schizophrenia remains primarily pharmacological, with approximately 30% of patients diagnosed with treatment-resistant schizophrenia (TRS). Clozapine continues to be the first choice treatment for this subgroup of patients. As the preferred treatment, clozapine offers clear advantages in efficacy; however, its complex and troublesome adverse effects pose significant challenges for psychiatrists. Common side effects include granulocytopenia, intestinal obstruction, myocarditis, cardiomyopathy, constipation, and seizures. The first two complications are easier to manage due to the availability of laboratory monitoring, and improved management strategies are now in place in clinical practice. In recent years, clozapine-induced myocarditis (CIM) has gained considerable attention because of its potentially severe outcomes. However, the mechanism behind its lethality remains unclear, and there is no widely accepted consensus or treatment guideline, which complicates the implementation of targeted prevention in clinical practice. This review aims to summarize the clinical manifestations of CIM, explore the underlying mechanisms, and discuss recent advances in monitoring, diagnosis, and treatment, with the goal of offering constructive recommendations for future clinical management.

Objective To explore the effects of on-line mindfulness-based stress reduction (MBSR) on the anxiety and depression status, and quality of life in the caregivers of patients with severe mental disorders. Methods Ninety-three caregivers for patients with severe schizophrenia or bipolar disorder, who were hospitalized in Yunnan Provincial Mental Hospital in March 2021, were enrolled and randomly divided into control group (n=47) and MBSR intervention group (n=46). Both groups received the basic health education and rehabilitation skill training, while the intervention group received additional on-line MBSR for 8 weeks. The anxiety and depression status, and the quality of life of the caregivers were evaluated by Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS) and the 36-item Short Form Health Survey (SF-36) before and 8 weeks after intervention, respectively. Results Thirteen caregivers dropped of the study, and 80 subjects (40 in each group) were included in the final analysis. At the baseline, there were no significant differences in SAS, SDS and SF-36 scores between two groups (P>0.05). Compared with baseline, the SAS and SDS scores in the intervention group significantly decreased after 8 weeks of intervention (both P<0.01), which were significantly lower than those in the control group (both P<0.01); while there were no significant changes in the control group. The total score and the scores of each dimension of SF-36 in the intervention group were significantly increased after 8-week intervention, except the physiological function dimension (all P<0.05), which were significantly higher than that those in the control group (all P<0.01, physiological function dimension P>0.05); while there were no significant changes in the control group before and after intervention (all P>0.05). Conclusion On-line MBSR can reduce the anxiety and depression levels, improve the quality of life in the caregivers of patients with severe mental disorders, which has the value of further promotion.

Previous studies have largely overlooked cellular differential alterations across differentially affected brain regions in both disease mechanisms and therapeutic development of Alzheimer’s disease (AD). This study aimed to compare the differential cellular and transcriptional changes in the prefrontal cortex (PFC) and entorhinal cortex (EC) of AD patients through an integrated single-cell transcriptomic analysis. We integrated three single-cell RNA sequencing (scRNA-seq) datasets comprising PFC and EC samples from AD patients and age-matched healthy controls. A total of 124,658 nuclei and 31 cell clusters were obtained and classified into eight major cell types, with EC exhibiting much more pronounced transcriptional alterations than PFC. Through network analysis, we pinpointed hub regulatory genes that form interconnected networks driving AD pathogenesis, findings validated by RT-qPCR showing more pronounced expression changes in EC versus PFC of AD mice. Moreover, dysregulation of the LINC01099-associated regulatory networks in the PFC and EC, showing correlation with AD progression, may present new therapeutic targets for AD. Together, these results suggest that effective AD biomarkers and therapeutic strategies may require simultaneous, precise targeting of specific cell populations across multiple brain regions.

The metabolism of the four major substances—glucose, lipids, amino acids, and nucleotides—constitutes the most prominent metabolic phenotype of schizophrenia. The pathological axis shared by these substances involves energy pathway imbalances, redox stress, immune-inflammatory activation, and abnormalities in neurotransmitter synthesis/degradation. Existing research confirms that key metabolites within these pathways hold potential as biomarkers for diagnosis or progression monitoring. In recent years, electroconvulsive therapy (ECT) has been shown to improve psychotic symptoms while exerting broad regulatory effects on neurogenesis, immune homeostasis, and the hypothalamic–pituitary–target gland axis, though its precise mechanisms remain unclear. Recent studies indicate that ECT treatment can also regulate changes in brain and peripheral metabolism. We propose an integrated “metabolism-immunity-neuroendocrine” hypothesis to systematically elucidate how metabolic reprogramming during ECT treatment cascades sequentially to the immune, neural, and endocrine systems, thereby revealing the molecular basis of its antipsychotic effects. Furthermore, we conduct a comparative analysis of the effects of antipsychotic drugs on the same metabolic network and explore the universality and specificity of metabolic regulation in other physical therapies (such as rTMS, tDCS) and psychiatric disorders like depression and bipolar disorder. This research aims to provide novel biomarkers and intervention targets for the precision diagnosis and treatment of schizophrenia.