ObjectiveTo explore the factors influencing home-based rehabilitation exercise and the needs for digital interventions among patients with spinal muscular atrophy (SMA), based on the behavior change wheel (BCW), and to provide evidence for the development of digital home-based rehabilitation interventions. MethodsA two-phase qualitative study was conducted from December, 2024 to March, 2025. Using convenience sampling, 14 participants were recruited, including patients with SMA, primary caregivers, rehabilitation professionals, clinicians, a patient organization representative and a health policy expert. In phase 1, semi-structured individual interviews were conducted with seven participants, including patients, caregivers and a patient organization representative, to identify factors influencing home-based rehabilitation exercise and unmet needs. In phase 2, a focus group involving 12 stakeholders was conducted, including five participants who had participated in phase 1, to explore requirements for the functions, knowledge content and interface design of a digital intervention, five of them had participated in phase 1. Overall, the two phases involved 14 individual participants, accounting for 19 participant-instances. Thematic analysis was performed using both deductive and inductive approaches, guided by the capability-opportunity-motivation-behavior (COM-B) model. ResultsSix themes were identified. phase 1 showed that patients with SMA experienced inadequate continuity of rehabilitation services and limited access to professional rehabilitation resources, with interruptions in institution-based rehabilitation coexisting with declining adherence to home-based exercise. Home-based rehabilitation exercise was jointly influenced by capability-, opportunity- and motivation-related factors, including limited capabilities of patients and caregivers, constraints in time and supportive conditions and insufficient goals, feedback, and incentives. Individualized rehabilitation plans and professional guidance were the major unmet needs. phase 2 showed that the core functions of a digital intervention should include individualized exercise plans, professional guidance and feedback, reminders and incentives, safety monitoring, remote assessment, and privacy and permission management. Core knowledge content should include stratified exercise guidance, caregiving skills, recognition of abnormal conditions, and information on when and how to seek help. The interface should be simple, impose a low user burden and accommodate different types of users. ConclusionHome-based rehabilitation exercise among patients with SMA is jointly influenced by multiple capability-, opportunity- and motivation-related factors. Digital interventions should prioritize individualized rehabilitation plans, professional guidance and sustained behavioral support. These findings may inform the development of a digital home-based rehabilitation intervention prototype for patients with SMA; its feasibility, safety, clinical effectiveness and economic value require further evaluation.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Objective To investigate the effect of senkyunolide I(SEN I)on neuronal apoptosis in sepsis-associated encephalopathy(SAE)rats via modulation of the mixed-lineage kinase 3(MLK3)/c-Jun N-terminal kinase 3(JNK3)signaling pathway.Methods Screening for a SAE model by monitoring neurobehavioral and electroencephalographic alterations in rats with sepsis induced by cecal ligation and puncture(CLP).Divided into normal control group,sham operation group,sepsis without encephalopathy group,SAE model group,SAE+MLK3/JNK3 signaling pathway inhibitor(URMC-099)group,SAE+low-dose SEN I group(36 mg/kg),and SAE+high-dose SEN I group(144 mg/kg),with 10 animals in each group.After 30 minutes of successful modeling,intraperitoneal injection was administered according to the group,and the administration was completed within 24 hours.HE staining was used to observe the pathological conditions of hippocampal tissue under a light microscope,transmission electron microscopy was used to observe changes in the morphology of neuronal nuclei,cytoplasm,and mitochondrial ultrastructure,TUNEL staining was used to detect hippocampal neuronal apoptosis,and Western blotting was used to detect the expression levels of p-JNK3,JNK3,p-MLK3,MLK3,and Fas ligand(Fas-L)proteins.Results Compared with the normal control group and sham surgery group,the sepsis without encephalopathy group showed no significant changes in neuronal structural morphology and neuronal apoptosis,and there were no significant differences in the expression of p-JNK3,JNK3,p-MLK3,MLK3,and Fas-L proteins(P＞0.05).However,the SAE model group had aggravated neuronal structural morphology damage,increased neuronal apoptosis rate,and increased expression level of p-JNK3,JNK3,p-MLK3,MLK3,and Fas-L proteins(P＜0.01);Compared with the SAE model group,the inhibitor URMC-099 and SEN I treatment groups showed significant improvement in neuronal structural and morphological damage,decreased neuronal apoptosis rates,and reduced p-JNK3,JNK3,p-MLK3,MLK3,and Fas-L protein expression(P＜0.01),with the high-dose SEN I group showing more significant improvement.Conclusion SEN I effectively reduces neuronal apoptosis in SAE and exerts neuroprotective effects on SAE by inhibiting the activation of the MLK3/JNK3 signaling pathway.

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

BackgroundNon-suicidal self-injury （NSSI） in adolescents is a serious global public health issue. Self-stigma is identified as a key factor hindering adolescents from seeking professional psychological help， while only a few studies have dealt with the self-stigma in adolescents with mood disorder exhibiting NSSI behavior. ObjectiveTo investigate the influencing factors of self-stigma among adolescents with mood disorder who exhibit NSSI behavior， and to examine the chained mediation role of self-esteem and social avoidance/distress in the relationship between NSSI behavior and self-stigma， with the aim of providing references for the detection and intervention of self-stigma in such patients. MethodsA total of 220 consecutive adolescent patients with mood disorder who met "the International Classification of Diseases， Tenth Edition"（ICD-10） diagnostic criteria for depressive disorder or depressive episode of bipolar disorder and attended the Fourth People's Hospital of Wuhu from November 2022 to November 2023 were recruited. The Adolescent Non-suicidal Self-injury Assessment Questionnaire （ANSAQ）， Internalized Stigma of Mental Illness （ISMI） Scale， Self-Esteem Scale （SES）， and Social Avoidance/Distress Scale （SADS） were employed to assess the participants. Correlation among variables was evaluated using Pearson's correlation coefficient. Multivariate linear regression analysis was utilized to identify the factors influencing self-stigma among adolescent patients with mood disorder exhibiting NSSI. The proposed mediating hypotheses were tested using Model 6 in the SPSS Process macro （version 3.0）. ResultsValid responses were received from 204/220 （92.73%） participants， including 153 cases with NSSI and 51 cases without NSSI. The NSSI （vs. no NSSI） group reported significantly higher scores on ISMI and SADS （t=-5.187， -4.564， P<0.01）， and lower scores on SES （t=4.478， P<0.01）. In the NSSI group， the total score of ISMI demonstrated a positive correlation with the total score of SADS and the behavioral questionnaire score in ANSAQ （r=0.644， 0.316， P<0.01）， and a negative correlation with the total score of SES （r=-0.724， P<0.01）. Multivariate linear regression analysis revealed that NSSI severity （β=0.132， P<0.05） and social avoidance/distress （β=0.309， P<0.01） were found to be positive predictors of the self-stigma， whereas self-esteem （β=-0.493， P<0.01） was a significant negative predictor of the self-stigma. Additionally， self-esteem and social avoidance/distress partially mediated the relationship between NSSI and self-stigma， with a mediating effect of 0.237 （95% CI： 0.103~0.374）， which constituted 55.89% of the total effect. The mediating effect included two paths： NSSI behavior→self-esteem→self-stigma （effect size was 0.163， 95% CI： 0.069~0.273） and NSSI behavior→self-esteem→social avoidance/distress→self-stigma （effect size was 0.063， 95% CI： 0.020~0.119）. ConclusionThe severity of NSSI can affect self-stigma in adolescents with mood disorders either directly through mediating self-esteem or indirectly through the chained mediation path of self-esteem and social avoidance/distress.［Funded by Scientific Research Projects of Wuhu Fourth People's Hospital in 2000（number，kjxm202203）］

The Hedgehog (Hh) signaling pathway is a critical transduction system regulating cell proliferation, differentiation, and tissue homeostasis during embryonic development. Its aberrant activation is closely associated with the pathogenesis of malignancies such as basal cell carcinoma and medulloblastoma. Although Smoothened (SMO)-targeting inhibitors have received clinical approval, their therapeutic efficacy is limited by acquired resistance mutation and compensatory pathway activation. Glioma-associated oncogene homolog 1 (GLI1), the terminal effector transcription factor of the Hh pathway, has emerged as a promising therapeutic target due to its tumor-specific overexpression and lower propensity for resistance induction. However, GLI1 is classified as an "undruggable" target due to the absence of well-defined ligand-binding pockets, low inhibitory activity, and poor drug-like properties. Currently, no GLI1 inhibitor has entered clinical trials. This review systematically analyzes multidimensional modulation strategies (e.g., allosteric modulation, protein-protein interaction disruption, targeted protein degradation) for targeting transcription factors, based on the structural and functional features of GLI1-DNA interaction combined with recent advances in structural biology and chemical biology, offering new paradigms to overcome therapeutic barriers against undruggable targets.

Sarcomatoid carcinoma is an uncommon malignancy, and its occurrence in the penis is even rarer. This paper reports a case of primary sarcomatoid carcinoma of the penis. The patient was admitted to the hospital with a mass on the glans penis with ulceration, and underwent partial penectomy, and the postoperative pathology confirmed the diagnosis of sarcomatoid carcinoma. One month after surgery, lower abdominal ultrasound and MRI showed abnormal enlargement of bilateral inguinal area and pelvic lymph nodes, respectively. PET/CT scan showed multiple lymph node metastases in retroperitoneum, pelvis, and inguinal area. The patient was recommended chemotherapy, which was refused by the patient and his family. At 9-month postoperative follow-up, there was no recurrence of the penile stump and no deterioration of the condition.

Objective:To construct patient-derived xenograft (PDX) models from head and neck squamous cell carcinoma (HNSCC) patients, to explore the effect of immune reconstitution timing on the PDX modeling and immune microenvironment in humanized immune system mice (huHSC-NCG-hIL15), and to provide a reliable animal model for research on the mechanisms of head and neck squamous carcinoma and for studies on immune therapy drug interventions.Methods:This study enrolled 28 HNSCC patients (25 laryngeal carcinomas, 3 hypopharyngeal carcinomas). PDX models were established in Balb/c nude (nu) mice, NSG mice, and humanized immune system-reconstituted huHSC-NCG-hIL15 mice. Fresh HNSCC samples were transplanted into Balb/c nu and NSG mice to generate PDX models, with subsequent analysis of success-associated factors. One successfully established PDX tumor was subsequently implanted into humanized immune system-reconstituted huHSC-NCG-hIL15 mice. Tumor transplantation was performed at distinct immune reconstruction timepoints (2 vs. 7 weeks post-reconstitution), and tumor growth patterns were monitored. Flow cytometry and multiplex immunohistochemical staining were utilized to characterize immunological profiles in peripheral lymphoid organs and tumor microenvironments. Hematoxylin-eosin (HE) staining was employed to assess histomorphological concordance between primary patient tumors and PDX model tissues. Results:HNSCC PDX models were successfully established. NSG mice exhibited a higher and more stable tumor take rate compared to Balb/c nu mice (pilot study: 4/10 vs. 3/10 cases; mean take rate 60%-80% vs. 20%-60 %). The PDX success rate in NSG mice was 46.4% (13/28). In the huHSC-NCG-hIL15 mice model with immune reconstitution at 7 weeks, tumors grew significantly faster, and the PDX modeling process was shorter (617 mm3 at day 70 in 7-week cohort vs.280 mm3 in 2-week cohort). Flow cytometry analysis of the immune microenvironment showed that at 7 weeks of immune reconstitution, the proportions of B cells in the spleen and tumor tissues(2-week vs. 7-week: spleen 16.2% vs. 61.7%, tumor 26.0% vs. 38.8%) and myeloid cells in the spleen (2-week vs. 7-week: spleen 47.2% vs. 88.1 %) were significantly higher, while mice at 2 weeks post-reconstitution showed a higher proportion of T cells (2-week vs. 7-week: spleen 13.2% vs. 9.3%, tumor 4.8% vs. 2.5%). HE results demonstrated that the tumor tissues in PDX models maintained a high degree of morphological similarity to the primary tumors in both NSG and huHSC-NCG-hIL15 mouse models. Conclusion:The HNSCC PDX modeling protocol demonstrates operational feasibility and high reproducibility, establishing this model as a robust platform for mechanistic and immunotherapeutic studies.

Objective To construct a mammography image classification assistant system suitable for Chinese population,and explore the potential of artificial intelligence technology to assist early screening of breast cancer in China.Methods Curated breast imaging subset of digital database for screening mammography(CBIS-DDSM),Mammographic image analysis society database(MIAS)and other international open datasets were used to conduct model training respectively in order to reproduce the mainstream in-depth learning methods in the current literature.The model was also tested on the Chinese breast mammography database(CBMD)provided by Huajiao Technology Co.,Ltd,and the performance was compared.Aiming at the problem that the Chinese population data are not ideal in the performance test of the open dataset training model,an optimization strategy based on the sliding window adjustment mechanism was implemented in combination with the characteristics of Chinese population data.Then a two-stage migration learning method was designed to improve the overall performance of the model,and then development of our system was carried out.Results With the sliding window adjustment mechanism and the CBMD training model after two-stage transfer learning,the accuracy of our developed system was improved from 0.50 of the open datasets to 0.80,precision from 0.54 to 0.82,sensitivity from 0.52 to 0.80,F1 value from 0.52 to 0.80,and AUC value from 0.51 to 0.89 based on the Chinese population dataset as the test set.Conclusion Through the introduction of sliding window adjustment mechanism and two-stage migration learning strategy,the performance of the breast molybdenum target image classification model has been significantly improved in the Chinese population dataset,and our system primarily achieves the purpose of assisting the classification of breast molybdenum target images for the Chinese population.