Objective This study aims to investigate the expression, phenotypic changes, and mechanisms of action of guanylate-binding protein 2 (GBP2) in the process of silica-induced pulmonary fibrosis. Methods The expression and localization of GBP2 in silicotic lung tissue were detected by immunohistochemical staining and immunofluorescence. An in vitro cell model was constructed, and methods such as Western blot and real-time quantitative reverse transcription polymerasechain reaction were utilized to investigate the function of GBP2 in different cell lines following silica stimulation. The mechanism of action of GBP2 in various cell lines was elucidated using Western blot analysis. Results GBP2 was highly expressed in the lung tissue of patients with silicosis. Immunohistochemical staining and immunofluorescence have revealed that GBP2 was localized in macrophages and epithelial cells. In vitro cell experiments demonstrated that silicon dioxide stimulated THP-1 cells to activate the c-Jun pathway through GBP2, promoting the secretion of inflammatory factors and facilitating the occurrence of M2 macrophage polarization. In epithelial cells, GBP2 promoted the occurrence of epithelial to mesenchymal transition (EMT) by upregulating Krueppel-like factor 8 (KLF8). Conclusion GBP2 not only activates c-Jun in macrophages to promote the production of inflammatory factors and the occurrence of M2 macrophage polarization, but also activates the transcription factor KLF8 in epithelial cells to induce EMT, collectively promoting the progression of silicosis.
Humans ; Silicosis/genetics* ; Macrophages/cytology* ; Epithelial Cells/pathology* ; GTP-Binding Proteins/physiology* ; Epithelial-Mesenchymal Transition ; Disease Progression ; Cell Line ; Male

Objective:To explore the predictive value of preoperative peripheral hematological parameters combined with clinicopathological features for cervical lymph node metastasis（CLNM） in patients with laryngeal squamous cell carcinoma（LSCC）, and to construct and validate a nomogram model for CLNM. Methods:A retrospective analysis was conducted on the clinical data of 264 LSCC patients who underwent surgical treatment and were pathologically confirmed, collected from the Second Affiliated Hospital of Shandong First Medical University and Taian 88 Hospital. Specifically, 161 patients from one hospital were allocated to the training cohort, while 103 patients from another hospital constituted the validation cohort. Based on postoperative pathological results, patients were categorized into CLNM-positive and CLNM-negative groups. The general clinical data, clinicopathological features, and hematological parameters of the two groups were analyzed and compared. A preoperative predictive model for CLNM was developed using logistic regression analysis, followed by validation and sensitivity analysis to evaluate the robustness of the model's predictive performance. Results:The results showed that there were significant differences in tumor location, tumor size, tumor differentiation, neutrophil percentage, lymphocyte count, lymphocyte percentage, c-reactive protein（CRP）, fibrinogen, neutrophil-to-lymphocyte ratio（NLR）, platelet-to-lymphocyte ratio（PLR）, systemic immune-inflammation index（SII）, systemic inflammation response index（SIRI）, and prognostic inflammatory index（PIV） between the CLNM-positive and CLNM-negative groups（P<0.05）. Lasso regression identified tumor location, clinical T stage, tumor size, tumor differentiation degree, red blood cell distribution width（RDW） -coefficient of variation（RDW-CV）, CRP, FIB, D-dimer, NLR, and lymphocyte-to-monocyte ratio（LMR） were the most predictive parameters. Multivariate logistic regression revealed that tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients（P<0.05）. A nomogram was constructed based on these five factors. The model demonstrated excellent discrimination, with a C-index of 0.837（95%CI 0.766-0.908） in the training cohort and 0.809（95%CI 0.698-0.920） in the validation cohort. Calibration curves and DCA curves in both cohorts confirmed the clinical utility of the model. Sensitivity analysis further supported the robustness of the results, showing good discrimination and calibration across different age and BMI subgroups. Conclusion:Tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients. The nomogram based on these variables exhibits strong discrimination, calibration, and clinical applicability, and may serve as a valuable tool for preoperative risk assessment and individualized treatment planning.
Humans ; Nomograms ; Laryngeal Neoplasms/blood* ; Retrospective Studies ; Lymphatic Metastasis ; Carcinoma, Squamous Cell/blood* ; Lymph Nodes/pathology* ; Male ; Female ; Middle Aged ; Neck ; C-Reactive Protein ; Aged ; Logistic Models ; Neutrophils ; Prognosis

Objective:To analyze clinical indicators and imaging data of hospitalized pneumonia patients and develop prediction models for length of hospital stay based on CT radiomics features and clinical indicators.Methods:Patients admitted to the First Clinical School of Hainan Medical University for pneumonia treatment between November 2020 and May 2024 were enrolled. Clinical data and CT imaging were collected, and radiomics features were extracted. Patients were divided into three groups based on the length of stay (<8 d, 8-28 d,>28 d, and poor prognosis). Three prediction models were constructed using logistic regression (LR): clinical features model, imaging features model and a combined clinical and imaging features model. The predictive performance of three models was evaluated using the area under the receiver operating characteristic (ROC) curve and DeLong test, followed by feature analysis. The Kappa test was used to compare the consistency of the overall classification.Results:A total of 343 subjects were included, with an average age of 61.46±20.98 years. The area under the curve (AUC) values of the combined model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.73, 0.65 and 0.78 in the training set, and 0.71, 0.65 and 0.76 in the validation set, respectively. The AUC values of the clinical feature model in different hospitalization duration classifications were 0.63, 0.64 and 0.73 in the training set, and 0.60, 0.52 and 0.63 in the validation set, respectively. The AUC values of the imaging feature model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.67, 0.66 and 0.73 in the training set, and 0.68, 0.54 and 0.66 in the validation set, respectively. The DeLong test results showed that the combined model outperformed other models in hospitalization duration classification (validation set AUC, all P<0.05, Bonferroni correction). Kappa test results showed that the combined model achieved the highest consistency between predicted classifications and actual hospitalization classifications ( K=0.615). Shape features, texture features and clinical features all contributed proportionally to the combined model. Conclusion:The combined model integrating radiomics features with clinical indicators can significantly enhance the predictive efficacy for the length of hospitalization in pneumonia patients.

Objective:To investigate the correlation between non-Hodgkin lymphoma (NHL) and chronic hepatitis B virus (HBV) infection by using the method of two-sample bidirectional Mendelian randomization (MR) analysis.Methods:Genetic variation data for NHL came from the Finnish database (FinnGen) Consortium 2021 public genome-wide association study (GWAS) dataset including 1 088 patients with NHL and 299 952 control subjects. The GWAS dataset for chronic HBV infection was derived from GWAS analysis published in 2021, including 145 NHL patients and 351 740 control subjects. NHL was used as an exposure factor, single nucleotide polymorphism (SNP) significantly associated with NHL was used as an instrumental variable (IV), chronic HBV infection was used as an outcome variable. The two-sample MR analysis was performed by using inverse-variance weighted (IVW) method. Chronic HBV infection was taken as an exposure factor, SNP significantly associated with chronic HBV infection was taken as IV, and NHL was taken as outcome variable, and then reverse two-sample MR analysis was performed. The IVW method used the inverse variance of each IV as the weight to fit, and the ratio method was used to measure SNP one by one and make weighted regression analysis, so as to obtain the overall estimate. MR-Egger regression and the weighted median (WME) method were also used to supplement the IVW method. In sensitivity analysis, leave-one-out sensitivity analysis was used to evaluate the impact of a single SNP. Cochran Q test was used to analyze the heterogeneity of the selected IV. MR-Egger regression was used to measure the average horizontal pleiotropy of IV, and the P-value of directivity was calculated. The MR-pleiotropy residual sum and outlier (MR-PRESSO) Global Test was used to exclude possible horizontal pleiotropic outliers and reduce bias. Results:In the leave-one-out sensitivity analysis, SNP with significant effects on causal associations was excluded. In forward MR analysis, IVs were 10 SNPs associated with NHL; the IVW method indicated that there was no causal association between NHL and chronic HBV infection ( OR = 0.979, 95% CI: 0.925-1.036, P = 0.465). MR-Egger regression ( OR = 0.992, 95% CI: 0.926-1.062, P = 0.825) and WME method ( OR = 0.992, 95% CI: 0.934-1.055, P = 0.805) were used as supplementary methods to obtain the consistent results. In sensitivity analysis, Cochran Q test showed no heterogeneity among IVs (IVW method: P = 0.271, MR-Egger regression: P = 0.239). Horizontal pleiotropy was not found in the MR-Egger regression (intercept was -0.01, P = 0.778) and the MR-PRESSO Global Test ( P > 0.05), suggesting robust results. In the reverse MR analysis, IVs were 8 SNPs associated with NHL; the IVW method ( OR = 1.117, 95% CI: 0.942-1.324, P = 0.202) also found no significant causal relationship between chronic HBV infection and NHL; MR-Egger regression ( OR = 0.777, 95% CI: 0.450-1.343, P = 0.401) and WME method ( OR = 1.120, 95% CI: 0.887-1.415, P = 0.351) also showed similar risk estimates. Sensitivity analysis also suggested the consistency and reliability of the results. Cochran Q test showed no heterogeneity among IVs (IVW method: P = 0.775, MR-Egger regression: P = 0.903). Horizontal pleiotropy was not found by MR-Egger regression (intercept was 0.102, P = 0.548) and MR-PRESSO Global Test ( P > 0.05). Conclusions:MR analysis suggests no causal relationship between NHL and chronic HBV infection.

Objective To investigate the effects of mirabegron combined with electroacupuncture on urodynamic parameters in rats with overactive bladder(OAB)by regulating the insulin receptor substrate(IRS)/phosphatidylinositol 3-kinase(PI3 K)/protein kinase B(AKT)/endothelial nitric oxide synthase(eNOS)signaling pathway.Methods Sixty female SD rats were selected as the study subjects and randomly divided into control group,model group,mirabegron group,electroacupunc-ture group,and mirabegron+electroacupuncture group using a random number table method,with 12 rats in each group.Except for the control group,the other groups were used to establish OAB rat models by the bladder outlet obstruction method.The mirabegron group received intragastric administra-tion of 8 mg/kg mirabegron suspension.The electroacupuncture group received electroacupuncture stimu-lation for 5 min each time.The mirabegron+electroacupuncture group received intragastric administration of mirabegron suspension while undergoing electroacupuncture stimulation.The control group,the model group,and the electroacupuncture group received an equal volume of normal saline intragastrically once a day for 7 consecutive days.Urodynamic parameters(basal micturition pressure,peak mictu-rition pressure,micturition interval,and residual urine volume)were measured in each group.After measuring bladder blood flow using a laser speckle imaging instrument,the wet weight of the rat bladder tissue was weighed,and the bladder index was calculated.Enzyme-linked immunosorbent assay(ELISA)was used to detect the contents of urinary nerve growth factor(NGF),and interleu-kin-1[3(IL-1β),malondialdehyde(MDA),and superoxide dismutase(SOD)in bladder tissue.Western blot was used to detect the expression levels of phosphorylated(p)-IRS1,p-PI3K,p-AKT and p-eNOS in bladder tissue.Results Compared with the model group,the basal micturition pressure,peak micturition pressure,and bladder index were all decreased,the residual urine vol-ume was reduced,the micturition interval was prolonged,the bladder blood flow was increased,the SOD content in bladder tissue was increased,the NGF content in urine and the IL-1 β and MDA contents in bladder tissue were decreased,and the expression levels of p-IRS1,p-PI3K,p-AKT and p-eNOS were increased in the mirabegron group,the electroacupuncture group,and the mirabegron+electroacupuncture group,with statistically significant differences(P＜0.05 or P＜0.01).The results of the above indicators in the mirabegron+electroacupuncture group were all better than those in the mirabegron group and the electroacupuncture group,with statistically significant differ-ences(P＜0.05 or P＜0.01).Conclusion Mirabegron combined with electroacupuncture can improve urodynamic parameters in OAB rats than used alone,and its mechanism may be related to the activation of the IRS/PI3K/AKT/eNOS signaling pathway.

Objective To analyze the qualitative efficacy of MRI multi-sequence scanning combined with fPSA/tPSA in benign and malignant prostate lesions.Methods A retrospective analysis was conducted on the clinical data of 118 patients with suspected prostate cancer who visited Hebei Provincial First Veterans Hospital from January 2021 to November 2023.All the patients underwent DWI and DCE-MRI examinations.They were divided into the benign group(n=39)and the malignant group(n=39)based on the pathological results of partial prostatectomy or ultrasound-guided prostate biopsy.The DWI parameters,DCE-MRI parameters,PI-RADS scores,and fPSA/tPSA of the two groups were compared to analyze the factors influencing benign and malignant prostate lesions.ROC curves were drawn to analyze the diagnostic value of each index for benign and malignant prostate lesions.Results Among 118 suspected prostate cancer patients,118 lesions were detected through biopsy at our hospital or initial diagnosis at Hebei Provincial First Veterans Hospital followed by surgical and biopsy pathological examinations at external medical institutions.Of these lesions,79(66.95%)were malignant and 39(33.05%)were benign;the Rmax and SImax of the malignant group were higher than those of the benign group,and the Tmax and ADC values were lower than those of the benign group(P<0.05);the PI-RADS scores were higher than the benign group,and fPSA/tPSA was lower than the benign group(P<0.05);Multivariate logistic regression analysis revealed that Rmax[OR:1.374(95%CI:1.211～1.560)],SImax[OR:6.849(95%CI:2.573～18.230)],and PI-RADS score[OR:4.689(95%CI:2.646～8.309)]were the risk factors for malignant prostate lesions(P<0.05),while Tmax[OR:0.906(95%CI:0.873～0.941)],ADC value[OR:0.930(95%CI:0.905～0.955)],and fPSA/tPSA[OR:0.859(95%CI:0.812～0.908)]were protective factors(P<0.05);the ROC curve revealed that the AUC(95%CI)of Rmax,SImax,Tmax,ADC value,fPSA/tPSA,and PI-RADS score for the diagnosis of benign and malignant prostate lesions were 0.827(0.747～0.906),0.752(0.660～0.844),0.851(0.773～0.930),0.845(0.765～0.925),0.813(0.722～0.905),0.844(0.768～0.920),and 0.940(0.883～0.997).Conclusion DCE-MRI and DWI combined with PI-RADS score and fPSA/tPSA can improve the qualitative diagnostic accuracy of malignant prostate lesions,and provide reference for clinical identification of benign and malignant lesions.

Objective:To analyze clinical indicators and imaging data of hospitalized pneumonia patients and develop prediction models for length of hospital stay based on CT radiomics features and clinical indicators.Methods:Patients admitted to the First Clinical School of Hainan Medical University for pneumonia treatment between November 2020 and May 2024 were enrolled. Clinical data and CT imaging were collected, and radiomics features were extracted. Patients were divided into three groups based on the length of stay (<8 d, 8-28 d,>28 d, and poor prognosis). Three prediction models were constructed using logistic regression (LR): clinical features model, imaging features model and a combined clinical and imaging features model. The predictive performance of three models was evaluated using the area under the receiver operating characteristic (ROC) curve and DeLong test, followed by feature analysis. The Kappa test was used to compare the consistency of the overall classification.Results:A total of 343 subjects were included, with an average age of 61.46±20.98 years. The area under the curve (AUC) values of the combined model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.73, 0.65 and 0.78 in the training set, and 0.71, 0.65 and 0.76 in the validation set, respectively. The AUC values of the clinical feature model in different hospitalization duration classifications were 0.63, 0.64 and 0.73 in the training set, and 0.60, 0.52 and 0.63 in the validation set, respectively. The AUC values of the imaging feature model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.67, 0.66 and 0.73 in the training set, and 0.68, 0.54 and 0.66 in the validation set, respectively. The DeLong test results showed that the combined model outperformed other models in hospitalization duration classification (validation set AUC, all P<0.05, Bonferroni correction). Kappa test results showed that the combined model achieved the highest consistency between predicted classifications and actual hospitalization classifications ( K=0.615). Shape features, texture features and clinical features all contributed proportionally to the combined model. Conclusion:The combined model integrating radiomics features with clinical indicators can significantly enhance the predictive efficacy for the length of hospitalization in pneumonia patients.

Objective:To investigate the factors related to hypothyroidism induced by programmed death(PD)-1 treatment in elderly patients with cancer.Methods:A total of 193 older patients(≥60 years old)with advanced solid tumors who received PD-1 treatment between January 2018 and January 2021 at the Department of Oncology of Xiangyang Central Hospital were included in this study.The patients were divided into two groups based on whether they were diagnosed with hypothyroidism after PD-1 treatment: the hypothyroidism group(36 cases)and the non-hypothyroidism group(157 cases).The clinical data of both groups, including age, gender, Eastern Cooperative Oncology Group performance status(ECOG PS), PD-1 inhibitors, thyroid function, and thyroid antibody, were compared to analyze the risk factors associated with hypothyroidism.Results:Among the 193 patients, 36(18.7%)were diagnosed with hypothyroidism.The study found no significant differences between the two groups in terms of age, gender, ECOG PS, tumor type, and PD-1 type(all P>0.05).However, significant differences were observed in the baseline levels of thyroid stimulating hormone(TSH)and thyroid antibody subgroups(both P<0.05).The results of multivariate Logistic regression analysis revealed that the presence of baseline anti-thyroid peroxidase antibody(TPOAb)( OR=20.256, 95% CI: 5.709-71.868, P<0.001), the presence of both baseline thyroglobulin antibody(TGAb)and TPOAb( OR=5.853, 95% CI: 1.475-23.227, P=0.012), and an increase in baseline TSH levels( OR=3.065, 95% CI: 1.049-8.959, P=0.041)were identified as risk factors for hypothyroidism induced by PD-1 treatment.On the other hand, there was no significant association between the presence of baseline TGAb and the occurrence of hypothyroidism( OR=1.373, 95% CI: 0.353-5.341, P=0.648). Conclusions:The incidence rate of hypothyroidism induced by PD-1 inhibitors is high among elderly patients with cancer.Additionally, the risk of hypothyroidism is higher in patients with elevated baseline TSH and positive TPOAb.Therefore, it is crucial to remain vigilant for the occurrence of hypothyroidism during PD-1 treatment.Timely diagnosis and treatment of hypothyroidism are necessary to minimize the incidence of adverse events.