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.

In recent years, gastrointestinal stromal tumors (GIST) have increased incidence and mortality, and most GIST is caused by the activation mutation of the c-KIT gene. Therefore, c-KIT has become a promising therapeutic target of GIST. At present, the drugs approved for the treatment of GIST including imatinib, sunitinib, regorafenib and ripretinib, are mostly prone to developing resistance and accompanied by various degrees of adverse reactions. Therefore, there is an urgent need to develop new c-KIT inhibitors to solve the problem of resistance. In this study, we investigated the anti-tumor effect of a novel c-KIT inhibitor PN17-1 on gastrointestinal stromal tumor GIST-882 cells in vitro. We found that PN17-1 significantly inhibited the proliferation, colony formation and migration ability of GIST-882 cells, and significantly downregulated the protein expression levels of p-c-KIT and its downstream signals p-AKT, p-STAT5 and p-ERK in GIST-882 cells. In addition, PN17-1 induced apoptosis in GIST-882 cells, and the apoptosis may be mainly related to the mitochondrial-dependent endogenous pathway. In conclusion, the novel c-KIT inhibitor PN17-1 is a promising anti-GIST drug, and this study provides new ideas for further development of c-KIT inhibitors in the future.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective:To investigate the effect of triglyceride-glucose(TyG) index and alkaline phosphatase(ALP) on brachial-ankle pulse wave conduction velocity(baPWV) in postmenopausal women.Methods:A cross-sectional study was conducted, enrolling 3 483 postmenopausal women who underwent health checkup at Taihu Sanatorium in Jiangsu Province from March 2020 to June 2021. The physical activity, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, high-density lipoprotein-cholesterol(HDL-C), low-density lipoprotein-cholesterol(LDL-C), ALP, and baPWV were collected.Results:Age, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, and LDL-C levels were significantly lower in the normal baPWV group( n=1 971) than those in the elevated baPWV group( n=1 512; P<0.001). Logistic regression identified the TyG index( OR=1.75) and ALP level( OR=1.20) as independent risk factors for elevated baPWV( P<0.001), besides with age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise. Individuals with both high TyG index and elevated ALP had a 2.51-fold higher risk of elevated baPWV(95% CI 2.01-3.14). Adjusted interaction measures(including age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise) showed RERI=2.825(95% CI 1.255-3.905), AP=0.348(95% CI 0.180-0.875), and SI=1.657(95% CI 0.628-3.374). Conclusions:The TyG index and ALP levels are independent risk factors for elevated baPWV in postmenopausal women and exhibit an additive interaction effect on arterial stiffness in this population.

Objective:To investigate the dynamic characteristics of human papillomavirus (HPV) genomic integration during cervical lesion progression and the clinical value of HPV integration detection in stratify HPV-positive women, and to explore its molecular mechanisms in cervical carcinogenesis.Methods:A prospective cohort study was designed to enroll high-risk HPV (HR-HPV) positive women who underwent cervical cancer screening in Drum Tower Hospital Affiliated to Nanjing University Medical School and Nanjing Maternity and Child Health Care Hospital from July 2022 to July 2024. Cervical exfoliated cells samples were collected, and HPV whole genome targeted capture and high-throughput sequencing technology were used. The HPV integration patterns, host gene functional region distribution and pathway enrichment characteristics of 157 samples with different cervical lesions grades were analyzed, including 31 cases of normal cervix, 40 cases of cervical intraepithelial neoplasia (CIN) Ⅰ, 32 cases of CIN Ⅱ, 42 cases of CIN Ⅲ, and 12 cases of cervical cancer.Results:HR-HPV integration was detected in 80.2% (126/157) of the 157 HR-HPV positive samples. The incidence of HR-HPV integration in cervical cancer patients was 12/12, which was higher than that in normal women (77%, 24/31). The incidence of HPV16 integration was significantly higher in high-grade lesions, and the incidence of HPV16 integration was 43% (18/42) in CIN Ⅲ patients and 8/12 in cervical cancer patients ( P<0.001). A total of 14 438 integration events were detected in 126 samples with HPV integration. The integration sites were mainly distributed in the host intergenic region (51.0%, 7 359/14 438) and intronic region (38.1%, 5 494/14 438), and the integration frequency of viral L1 gene was the highest (28.4%, 4 498/16 781). Functional enrichment analysis showed that HPV integration-related host genes were significantly enriched in transport of small molecules,cyclic guanosine monophosphate (cGMP)-protein kinase G (PKG) signaling pathway, and purine ribonucleotide biosynthetic process, which synergistically drove carcinogenesis through multiple mechanisms. Conclusions:HPV integration events are significantly associated with the progression of cervical lesions. HPV integrated detection based on cervical exfoliated cells is expected to optimize the current screening strategy, reduce excessive intervention of HPV positive women and facilitate their accurate triage management.