Objective: To understand the impact of childhood trauma on psychological distress among upper grade elemetary school students, and to explore the mediating role of leisure activities in the relationship, so as to provide a basis for developing mental health intervention strategies. Methods: From August to November 2024, a combination of convenience sampling and stratified cluster random sampling was employed to recruit 1 373 fourth to sixth grade students from four primary schools in Harbin. The Childhood Trauma Questionnaire(CTQ), a self designed leisure activity scale (including active and passive leisure activities), and the Kessler Psychological Distress Scale (K10) were used to assess childhood trauma experiences, leisure activities, and levels of psychological distress. Spearman correlation analysis and linear regression analysis were conducted to explore the relationships among childhood trauma, leisure types, leisure time, and psychological distress. Based on the mediation analysis framework proposed by Hayes (Model 4), the mediating role of leisure types in the relationship between childhood trauma and psychological distress was examined. Results: Totally 19.1% of the upper elemetary school students exhibited psychological distress, while 30.2% had experienced childhood trauma. During school days, 64.6% of the students were reported of having leisure time concentrated between 1 and 5 hours per day, whereas 67.4% reported leisure time exceeding 5 hours per day on weekends. After controlling for potential demographic confounders such as gender, grade, ethnicity, household registration, being an only child, parents educational level, co residence, and whether parents are first time married,linear regression analysis showed that childhood trauma experience had positive predictive effect on psychological distress in upper primary school students( β =0.20, P <0.01). Leisure time showed no statistically significant association with psychological distress, both on school days ( β =-0.58 to -0.56) and weekends ( β =0.26- 0.98 )(all P >0.05). Active leisure activities were negatively associated with psychological distress ( β =-0.20), while passive leisure activities were positively associated with psychological distress ( β =0.29)(both P <0.01). Leisure type partially mediated the relationship between childhood trauma and psychological distress, accounting for 11.7% of the indirect effect. Conclusion Childhood trauma experiences positively predict psychological distress in upper elementary school students, and affect psychological distress through active leisure and passive leisure.

OBJECTIVE To investigate the current career development status and existing bottlenecks among graduates of clinical pharmacist training bases， and to provide evidence for optimizing the training system， enhancing trainees’ job competency， and promoting the sound development of the clinical pharmacy discipline. METHODS Graduates from a clinical pharmacist training base in a tertiary class A hospital were selected as survey subjects. A six-dimensional questionnaire was designed using “Wenjuanxing” platform， distributed and collected via a mobile APP and E-mail. The survey analyzed participants’ basic characteristics， the impact of training on their professional roles， as well as their satisfaction regarding professional sentiment， competence， career status， professional recognition， the current state of the clinical pharmacist workforce， and the teaching model of the training base. The reliability of the questionnaire responses was assessed using Cronbach’s α coefficient. RESULTS A total of 164 questionnaires were distributed， and 147 valid responses were recovered， yielding a valid response rate of 89.63%. The Cronbach’s α coefficient for the questionnaire content was 0.943. The surveyed trainees were primarily employed at general hospitals （81.63%） and tertiary class A hospitals （72.11%）， with women constituting the majority （79.59%）. Their ages were concentrated between 26 and 35 years old （63.27%）， and most of them were supervising pharmacists（59.86%）. After training， 96.60% of graduates returned to their original institutions， and the proportion working in clinical pharmacist positions increased from 52.38% to 84.35%. Trainees’ overall satisfaction rate with the training model was 84.35%. However， their satisfaction with innovation and research capacity in clinical pharmacy was only 42 .18%， the satisfaction with salary and benefits was 35.37%， and the satisfaction with both occupational recognition and rationality of staffing was less than 50%. CONCLUSIONS Clinical pharmacist training bases can effectively promote trainees’ career transition， enhance job competency， and stabilize the talent pool among trainees. Nonetheless， the profession still faces bottlenecks such as relatively weak research capacity， low compensation， insufficient professional recognition， and unreasonable staffing. These issues require a multi-pronged， collaborative approach involving the optimization of training systems， the enhancement of career support， and the improvement of industry policies.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

The molecular mechanism of verbascoside(OC1) in promoting acetylcholine(ACh) release in the pathogenesis of Alzheimer's disease(AD) was studied. Adrenal pheochromocytoma cells(PC12) of rats induced by β-amyloid protein(1-42)(Aβ_(1-42)) were used as AD models in vitro and were divided into control group, model group(Aβ_(1-42) 10 μmol·L~(-1)), OC1 treatment group(2 and 10 μg·mL~(-1)). The effect of OC1 on phosphorylated proteins in AD models was analyzed by whole protein phosphorylation quantitative omics, and the selectivity of OC1 for calcium channel subtypes was virtually screened in combination with computer-aided drug design. The fluorescence probe Fluo-3/AM was used to detect Ca~(2+) concentration in cells. Western blot analysis was performed to detect the effects of OC1 on the expression of phosphorylated calmodulin-dependent protein kinase Ⅱ(p-CaMKⅡ, Thr286) and synaptic vesicle-related proteins, and UPLC/Q Exactive MS was used to detect the effects of OC1 on ACh release in AD models. The effects of OC1 on acetylcholine esterase(AChE) activity in AD models were detected. The results showed that the differentially modified proteins in the model group and the OC1 treatment group were related to calcium channel activation at three levels: GO classification, KEGG pathway, and protein domain. The results of molecular docking revealed the dominant role of L-type calcium channels. Fluo-3/AM fluorescence intensity decreased under the presence of Ca~(2+) chelating agent ethylene glycol tetraacetic acid(EGTA), L-type calcium channel blocker verapamil, and N-type calcium channel blocker conotoxin, and the effect of verapamil was stronger than that of conotoxin. This confirmed that OC1 promoted extracellular Ca~(2+) influx mainly through its interaction with L-type calcium channel protein. In addition, proteomic analysis and Western blot results showed that the expression of p-CaMKⅡ and downstream vesicle-related proteins was up-regulated after OC1 treatment, indicating that OC1 acted on vesicle-related proteins by activating CaMKⅡ and participated in synaptic remodeling and transmitter release, thus affecting learning and memory. OC1 also decreased the activity of AChE and prolonged the action time of ACh in synaptic gaps.
Animals ; Rats ; Glucosides/administration & dosage* ; Acetylcholine/metabolism* ; Alzheimer Disease/genetics* ; PC12 Cells ; Phenols/chemistry* ; Neurotransmitter Agents/metabolism* ; Drugs, Chinese Herbal ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/genetics* ; Humans ; Phosphorylation/drug effects* ; Calcium/metabolism* ; Polyphenols

Signal detection is a critical task in drug safety regulation. However, it inevitably generates irrelevant or false signals, posing challenges for resource allocation by marketing authorization holders. To reasonably assess these signals, different countries have established various principles for prioritizing the evaluation of risk signals. This study systematically compares these principles and finds that the U.S. Food and Drug Administration(FDA) focuses on practical issues, such as identifying drug confusion or drug interactions. However, China's Good Pharmacovigilance Practices and the European Medicines Agency(EMA) emphasize a comprehensive evaluation framework. The Council for International Organizations of Medical Sciences(CIOMS) emphasizes the consistency of multiple data sources, highlighting the reliability of signal evaluation. China practices a multidisciplinary approach combining traditional Chinese and western medicine, and the risk signals related to traditional Chinese medicine(TCM) have unique characteristics, including complex components, cumulative toxicity, specific theoretical foundations, and drug interactions. The different priorities in risk signal evaluation principles across countries suggest that China should strengthen clinical trial research, emphasize corroboration with evidence of multiple sources, and pay particular attention to the risks of drug interactions in the TCM regulatory science. Establishing the risk signal prioritization principles that align with the characteristics of TCM enables more precise and efficient scientific regulation of TCM.
Humans ; Medicine, Chinese Traditional/standards* ; China ; Drugs, Chinese Herbal/adverse effects* ; United States ; United States Food and Drug Administration

This study delves into the mechanism of total flavone of Abelmoschus manihot(TFA) in treating ulcerative colitis(UC) and depression via inhibiting M1 polarization of macrophages and reshaping intestinal flora and glycerolphospholipid metabolism. The study established a mouse model of UC and depression induced by chronic restraint stress(CRS) and dextran sulfate sodium(DSS). The fecal microbiota transplantation(FMT) experiment after TFA intervention was conducted. Mice in the FMT donor group were modeled and treated, and fecal samples were taken to prepare the bacterial solution. Mice in the FMT receptor group were treated with antibiotic intervention, and then administered bacterial solution by gavage from mice in the donor group, followed by UC depression modeling. After the experiment, behavioral tests were conducted to evaluate depressive-like behaviors by measuring the levels of 5-hydroxytryptamine(5-HT) and brain-derived neurotrophic factor(BDNF) in the hippocampus of mice. The levels of tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),and interleukin-1β(IL-1β)in the brain and colon tissue of mice were also measured, and the polarization status of macrophages was evaluated by measuring the mRNA levels of CD86 and CD206. 16S ribosomal RNA(16S rRNA) sequencing technology was used to analyze changes in the intestinal flora of mice. Wide target lipidomics was used to detect serum lipid metabolite levels in mice after FMT,and correlation analysis was conducted between lipids and differential intestinal flora significantly regulated by TFA. In vitro experiments, representative glycerophospholipid metabolites and glycerophospholipid inhibitors were used to intervene in Raw264.7 macrophages, and the mRNA levels of TNF-α,IL-6,IL-1β,CD86,and CD206 were detected. The results showed that TFA and FMT after intervention could significantly improve depressive-like behavior and intestinal inflammation in mice with UC and depression, significantly downregulate pro-inflammatory cytokines and CD86 mRNA expression in brain and colon tissue, inhibiting M1 polarization of macrophages, and significantly upregulate CD206 mRNA expression, promoting M2 polarization of macrophages. In addition, the high-dose group had a more significant effect. After TFA intervention, FMT significantly corrected the metabolic disorder of glycerophospholipids in mice with UC and depression, and there was a significant correlation between differential intestinal flora and glycerophospholipids. In vitro experiments showed that glycerophospholipid metabolites, especially lysophosphatidylcholine(LPC),significantly upregulated pro-inflammatory cytokines and CD86 mRNA expression, promote M1 polarization of macrophages, while glycerophospholipid inhibitors had the opposite effect. The results indicate that TFA effectively treats depression and UC by correcting intestinal flora dysbiosis and reshaping glycerophospholipid metabolism, thereby inhibiting M1 polarization of macrophages.
Animals ; Mice ; Gastrointestinal Microbiome/drug effects* ; Abelmoschus/chemistry* ; Macrophages/metabolism* ; Colitis, Ulcerative/immunology* ; Flavones/administration & dosage* ; Male ; Depression/genetics* ; Glycerophospholipids/metabolism* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred C57BL

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

Fuxiong has a long history of cultivation. Since its first record in the Beneficial Formulas from the Taiping Imperial Pharmacy of the Song Dynasty, Fuxiong had always been used by ancient physicians and became a preponderant variety for some reasons during the periods of the Ming Dynasty, Qing Dynasty, and Republic of China. However, as for modern use, only Chuanxiong Rhizoma is valued, and the medicinal value of Fuxiong is gradually being overlooked. This article systematically researches the nomenclature, producing area, origin, and efficacy of Fuxiong, proving that the planting technology of Fuxiong matured in the Song Dynasty at the latest, slightly later than the emergence of Chuanxiong Rhizoma in the Sui and Tang Dynasties. Over the years, the producing area of Fuxiong has not undergone significant changes, and it is mainly cultivated within Jiangxi province. According to the analysis of the origin of Xiongqiong, combined with modern genetic research, it can be basically clarified that the early source of Xiongqiong may not be single. With the popularization of cultivation, Chuanxiong Rhizoma became a Dao-di herb earliest, gradually replacing Xiongqiong and being recognized clinically. After cultivation, the polyploidy of Chuanxiong Rhizoma varieties formed stable inheritance, forming the later Fuxiong. Medical experts have gradually deepened their understanding of the efficacy of Fuxiong. Initially, they believed that it was a substitute for Chuanxiong Rhizoma and had weaker efficacy than Chuanxiong Rhizoma. Medical experts in Jin and Yuan Dynasties such as Zhu Danxi and Dai Sigong believed that Fuxiong was good at relieving stagnation. Books and records of materia medica in the Ming and Qing Dynasties explicitly proposed the great ability of Fuxiong to relieve stagnation. Fuxiong should be distinguished from Chuanxiong Rhizoma when applied, and the application differences should be clearly reflected in medical records. Based on the comprehensive research in this article, it can be concluded that although most of ancient physicians have attached great importance to genuineness of Chuanxiong Rhizoma, Fuxiong, as a dominant variety of traditional application, has a clear historical context and significant efficacy characteristics, worthy of further in-depth study.
Drugs, Chinese Herbal/history* ; China ; Medicine, Chinese Traditional/history* ; History, Ancient ; Humans ; History, Medieval ; Plants, Medicinal/chemistry* ; Rhizome/growth & development*