Background As one of the most severe occupational diseases in China, pneumoconiosis is significantly burdened by its complications, which adversely affects patients' quality of life. Objective To identify the influencing factors of complications in pneumoconiosis and to construct an early prediction model for pneumoconiosis complications, providing theoretical guidance for clinical diagnosis, treatment, and rehabilitation. Methods A case-control study was conducted using data from the Chongqing 5G Pneumoconiosis Rehabilitation Management Information Platform. A total of 1872 pneumoconiosis patients with complications, who received rehabilitation at various rehabilitation stations in Chongqing from January 2021 to December 2024, were enrolled as the case group. Concurrently, 2348 patients without complications from the same platform and period were included as the control group. Univariate analysis, LASSO regression, and logistic regression were employed to identify influencing factors for complications. An extreme gradient boosting (XGBoost) model was trained using ten-fold cross-validation to predict pneumoconiosis complications. The SHapley Additive exPlanations (SHAP) method was applied for model visualization. Results The analysis of influencing factors revealed that increased age, silicosis type, advanced stage of pneumoconiosis, dependence in activities of daily living, abnormal muscle strength, increased dyspnea index, presence of cough, viscous sputum, impaired cardiac function, severe abnormality in the 6-minute walk test (6MWT), and increased Borg score were risk factors for complications (P<0.05). The XGBoost model demonstrated an area under the curve (AUC) of receiver operating characteristic of 0.718, and a Brier score of 0.211 for the calibration curve. Decision curve analysis demonstrated a superior net benefit within the threshold probability range of 0.2 to 1.0 compared to "all-patient intervention" and "no-patient intervention" strategies, indicating good predictive performance and significant clinical utility. SHAP visualization identified the top six important features as Borg score, age, 6MWT, muscle strength, pneumoconiosis stage, and cough symptoms. Conclusion Multiple factors influence the occurrence of complications in pneumoconiosis patients. Clinical attention should be focused on elderly patients with decreased cardiopulmonary reserve, pronounced respiratory symptoms, and diminished muscle strength. The XGBoost model demonstrates satisfactory discrimination, calibration, and clinical applicability in predicting pneumoconiosis complications and may serve as a useful reference for clinical decision-making.

Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

Objective To investigate the epidemiological characteristics and changing trend of typhus in Shaanxi Province from 2005 to 2023 to provide a scientific basis for its prevention and control. Methods Excel 2007, SPSS 25.0, Joinpoint 4.9.1.0, and Geoda 1.6 were used for data collection and statistical analysis. Super Map was used for data visualization to describe the changing characteristics of the disease. Results A total of 394 typhus cases were reported in Shaanxi Province from 2005 to 2023. The average annual incidence of typhus was 0.054/100 000, showing a dynamic fluctuation trend(AAPC=-3.3, t=-0.3, P>0.05). The cases were mainly concentrated in Baoji, Hanzhong and Xi′an, accounting for 78.68%. The incidence peak was from May to October, accounting for 64.21% of annual incidence. The epidemic season was from May to October and December. The incidence of the disease was concentrated in the 40-69 age group, accounting for 58.88%, and the sex was 1.07:1. The main occupation was farmers, accounting for 72.08%. The median time from onset to diagnosis was 7 days. Global spatial autocorrelation analysis showed that there were significant spatial autocorrelations in 11 years from 2005 to 2023(P<0.05). Local spatial autocorrelation analysis detected a total of 43“high-high”clustering areas, mainly concentrated in Baoji City. Conclusions The overall incidence of typhus in Shaanxi Province showed a dynamic fluctuation trend, with notable seasonal and regional aggregation. The incidence of typhus was higher in middle-aged and elderly people in rural areas. Surveillance should be strengthened in typhus endemic areas in summer and autumn, and health education should be conducted for key population to form good health habits and reduce the incidence of typhus.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

ObjectiveMethylthioadenosine phosphorylase (MTAP) is found to be frequently deleted in malignant cancers, but the role of MTAP underlying metastasis and stemness of liver cancer remains far from clear. 5-fluorouracil (5-Fu) is clinically used in treating advanced liver cancer, however, chemoresistance is one of the major barriers impeding its efficacy. Liver cancer stem cells are considered to be the reservoir for tumor progression and chemoresistance. This study aims to explore the role of MTAP in regulating stemness and chemoresistance of 5-Fu in liver cancer. It is designed to elucidate the molecular mechanisms underlying MTAP-manipulated stemness. How MTAP influences metastasis and chemoresistance against 5-Fu in liver cancer is also elaborated. MethodsThe correlation of MTAP expression with stemness marker CD133 was evaluated by flow cytometry. Colony formation assays were conducted to analyze the tumorigenic ability. Western blot assays were applied to delineate the molecular mechanisms underlying MTAP-regulated stemness. Trans-well assays were conducted to analyze the metastatic potential of liver cancer cells.In vivo experiments were performed using subcutaneous xenograft and lung metastasis model on nude mice. Tumor size and weight were analyzed upon 5-Fu treatment. Metastatic nodules on lungs were evaluated. Immunohistochemical and TUNNEL assays were performed on slides obtained from tumor tissues. ResultsMTAP overexpression inhibited expression of CD133 and colony formation, which is further ablated by MTAP inhibitor. MTAP deprivation augmented stemness and colony formation, which is reversed by protein arginine methyltransferase 5 (PRMT5) overexpression but not its catalytically inactive counterparts. Critically, SRY-box transcription factor 2 (SOX2) was found to be a downstream regulator of MTAP/PRMT5, leading to stemness of liver cancer cells. MTAP overexpression suppressed SOX2 expression, while MTAP inhibition augmented expression of SOX2. Critically, MTAP overexpression inhibited migration and invasion of liver cancer cells. In vivo experiments in animal model found that MTAP deprivation promotes tumor growth and metastatic nodules of liver cancer. Additionally, MTAP overexpression inhibits tumor growth. Moreover, MTAP deprivation contributes to chemoresistance shown by increased tumor size and weight treated by 5-Fu. In contrast, MTAP overexpression led to further decline in tumor size and weight elicited by 5-Fu treatment. Accordingly, SOX2 was inhibited in tumor tissues after MTAP overexpression. Marker of proliferation Ki67 (Ki67) expression was dampened while apoptosis was found in MTAP-overexpressed tumor tissues. ConclusionIn this study, plethora of experimental studies collectively demonstrated that MTAP deprivation enhances stemness of liver cancer by regulating SOX2, exerting anti-cancer and chemoresistant role against 5-Fu in liver cancer. It is also worth noting that MTAP inhibition promoted metastasis of liver cancer. MTAP overexpression augmented tumor shrinking elicited by 5-Fu and SOX2 was involved in this process. These results concluded that MTAP/PRMT5/SOX2 signaling axis was involved in regulating stemness and chemoresistance of liver cancer. These findings help to exploit novel therapies by targeting stemness in MTAP-depleted liver cancer. It shed novel light on unveiling MTAP-regulated stemness in antagonizing 5-Fu treatment in liver cancer. It also adds mounting evidence to the theoretical basis for accomplishing personalized chemotherapy of liver cancer patients by targeting MTAP or its downstream PRMT5/SOX2.

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 explore the mechanism of Danxing Zhishuang Prescription in the treatment of Parkinson's disease (PD) by combining network pharmacology with animal models.Methods:TCMSP, BATMAN database, Genecards, and OMIM databases were retrieved to obtain the active components and action targets of Danxing Zhishuang Prescription. Venny 2.1.0 was used to intersect drug targets and PD related genes, and a protein interaction network of the intersection targets was constructed using the STRING 12.0 platform. Topology analysis was performed using Cytoscape 3.10.0 software to identify the key targets of Danxing Zhishuang Prescription on PD; GO functional and KEGG pathway enrichment analysis was performed on key targets using the WeChat platform, and molecular docking was validated through AutoDockTools 1.5.7. Using a random number table method, mice were divided into a blank control group, a model group, and a Danxing Zhishuang Prescription group, with 20 mice in each group; except for the blank group, all other groups of mice were orally administered fisetin to prepare PD models; Danxing Zhishuang Prescription group was orally administered with concentrated Danxing Zhishuang Prescription at a dosage of 10.5 g/kg, while the blank group and model group were orally administered with 0.2 ml of physiological saline for 21 days; Western blot was used to detect the expressions of Akt1, Bcl-2, Bax, and α-Syn proteins.Results:359 intersection targets, 69 core targets, and 185 active components were obtained the treatment of PD with Danxing Zhishuang Prescription. The main active components included quercetin, kaempferol, phenylalanine, etc., and the key targets were AKT1, TP53, TNF, ESR1, etc. KEGG analysis revealed several key signaling pathways, such as AGE-RAGE, PI3K-Akt, fluid shear stress and atherosclerosis signaling pathways. The validation experiment results showed that compared with the model group, the expression of Bcl-2 protein was up-regulated ( P<0.01), and the expressions of Bax, Akt1, and α-Syn proteins were down-regulated in the Danxing Zhishuang Prescription group ( P<0.01). Conclusions:Danxing Zhishuang Prescription has the advantages of multi target and multi pathway treatment for PD. Its mechanism may be related to down-regulating the expressions of Bax, Akt1, and α-Syn proteins, improving brain blood supply, regulating neurotransmitter balance, inhibiting oxidative stress response, and promoting nerve regeneration.

Spinal cord injury(SCI)is a serious central nervous system traumatic disease that usually leads to severe neurological dysfunction below the site of injury.Studies have shown that SCI is closely related to oxidative stress,inflammatory responses,and mitochondrial dynamic imbalance.Mitochondrial dysfunction,such as accumulation of mitochondrial DNA damage,depletion of ATP,and impairment of oxidative stress regulation,can lead to dysfunction or death of neurons.Mitochondrial fusion plays a key role in maintaining energy balance and promoting neurological recovery after SCI.This review summarizes the changes in mitochondrial dynamics after SCI and the neuroprotective mechanisms mediated by mitochondrial fusion,with aim to provide new ideas on the treatment of SCI.

Prostate-specific membrane antigen(PSMA)positron emission tomography(PET)is currently a precise diagnostic imaging technology for prostate cancer(PCa).Artificial intelligence(AI)technologies,particularly machine learning and deep learning algorithms,when combined with PSMA PET,showed extensive potential applications in various aspects of PCa management.These include the diagnosis and differential diagnosis of primary tumors,staging,recurrence detection,and treatment planning for PCa.At present,a few AI models have received clinical approval.This paper reviews the application progress of AI combined with PSMA PET in the diagnosis and treatment of PCa,explores the current limitations of AI technologies in clinical practice,and aim to provide references to future diagnosis and treatment studies for PCa.

Objective To explore the correlation between the rs7296288 single nucleotide polymorphism(SNP)of the DHH gene and the onset of depression.Methods From March 2018 to December 2019,480 patients with depression in Sichuan Provincial People's Hospital,Jining Mental Hospital,Yunnan Mental Health Center were collected as the case group,and 329 patients without depression were collected as the control group.Peripheral blood samples were collected and DNA was extracted.After multiple amplification and high-throughput sequencing,statistical software was used to analyze the relevant data.Results The rs7296288 polymorphism of the DHH gene,the AA genotype was 32.9％in the control group and 36.7％in the case group,with no statistical difference;the AC genotype was 52.8％in the control group and 47.7％in the case group,with no statistical difference;the CC genotype was 14.3％in the control group and 15.6％in the case group,with no statistical difference.The co-dominant,dominant,and recessive statistical models were not statistically significant.Subgroup analysis of the degree of depressive episodes,suicide attempts,and first-episode patients did not find an association between the rs7296288 SNP locus of the DHH gene and the clinical features of depression,that is,the SNP rs7296288 of the DHH gene had no significant correlation with depression.Conclusion The rs7296288 polymorphism of DHH gene is not correlated with the pathogenesis of depression.