Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Purpose To explore the clinicopathologic features and differential diagnosis of nephrogenic adenomas(NAs)in urinary tract.Methods 27 cases of NA were collected.The clinicopathological features and differential di-agnosis were analyzed,and the relevant literatures were reviewed.Results A total of 27 cases of NA in urinary tract were included in this study,including 20 males and 7 females,ranging in age from 24 to 84 years.Among them,clini-cal manifestations included urinary tract irritation in 8 cases,hematuria in 7 cases,and no obvious symptoms or other comorbidities in 12 cases.Comorbidities:17 cases combined with urothelial tumors,4 cases with cystitis,2 cases with tuberculosis,2 cases with urethral diverticulum,and 2 cases with ureteral calculi or stenosis.Gross inspection:19 ca-ses occurred in the bladder,5 in the ureter,and 3 in the urethra.The average size of the lesions was about 4.3 mm.Local edema or protrusion of the mucosa with roughness were found in 18 cases,papillary or polypoid masses in 5 ca-ses,or follicular-like neoplasma in 4 cases.Histologic features:these lesions were mainly composed of papillary,tubu-lar and cystic structure,and eosinophilic colloid secretions were seen in the lumen.The lining epithelium was cuboidal or low columnar,some of which were 'hobnail' or signet ring-like cells,and stroma showed edema and chronic inflam-mation.Immunohistochemistry:epithelial cells expressed PAX8 and CK7,partially expressed P504S and GAT A3,but not p63 and PSA.p53 was wild type,and Ki67 proliferation index was low(1％-8％).Molecular testing:no ab-normalities were found in 14 urine FISH tests before surgery,and no fusion mutation was detected in 2 samples selected for second-generation sequencing.Treatment and follow-up:follow-up data were obtained for all cases,of which 24 un-derwent transurethral resection of bladder lesions,and the rest underwent nephroureterectomy or cystoprostatectomy.The mean follow-up was 26.6(1-59)months,and the lesion recurred in 2 cases.Conclusion NAs are relatively rare,and their final diagnosis depends on pathological examination.When the biopsy sample is small or the histomor-phology is atypical,it's often necessary to differentiate it from urothelial tumor,prostate adenocarcinoma and clear cell adenocarcinoma.Understanding the clinicopathologic and immunohistochemical features of NA is helpful to improve the diagnostic rate and avoid missed-diagnosis or misdiagnosis.

Objective To explore the predictive value of ultra-sound(US)combined with multi-sequence MRI in a clinical-deep learning radiomics nomogram(DLRN)for the short-term efficacy of neoadjuvant chemotherapy(NAC)in patients with triple-negative breast cancer(TNBC).Methods A total of 122 TNBC patients from five hospitals were retrospectively analyzed,and divided into training group(72 cases)and validation group(50 cases).The clinical and pathological data,NAC regimens,and imaging data were collected.The lesions and its surrounding 10-unit voxels from US and MRI images were retained as the region of interest(ROI).Pyradiomics software and a ResNet152 convolutional neural network(CNN)framework were used to extract radiomics and deep learning features to construct a clinical-DLRN with outcome dimension fusion.The receiver operating characteristic(ROC)curve and calibration curve were plotted,and five-fold cross-validation decision curve were used to verify the model's clinical effec-tiveness.Results The clinical-DLRN constructed by US combined with multi-sequence MRI showed that area under the curve(AUC)was 0.967[95％confidence interval(CI)0.782-0.967]and accuracy(ACC)was 0.900,respectively.The five-fold cross-validation decision curve showed good generalization,with the highest clinical net benefit between risk thresholds of 0.72 and 0.96.Conclusion The clinical-DLRN integrating US and multi-sequence MRI has the best efficacy in predicting the short-term efficacy of NAC in TNBC patients,which offering potential guidance for personalized TNBC treatment.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective:To investigate the different clinical characteristics and prognosis of patients with diabetic nephropathy (DN) accompanied by IgA deposition diagnosed by renal biopsy.Methods:The study was a retrospective cohort study. Clinical and pathological data of patients diagnosed with DN through renal biopsy in Beijing Anzhen Hospital affiliated to Capital Medical University from January 1, 2010 to March 31, 2023 were retrospectively collected. The clinical and pathological characteristics and prognosis of DN patients with IgA deposition and DN control group patients without IgA deposition were compared. Immunofluorescence staining was used to detect the intensity of galactose-deficient IgA1 (Gd-IgA1) staining in renal tissue of DN patients with DN IgA deposition, and grouping was performed according to whether the staining intensity was≥2+. Enzyme linked immunosorbent assay was used to detect the serum level of Gd-IgA1 in patients. A 50% decrease in estimated glomerular filtration rate (eGFR) from baseline or progression to end-stage renal disease within 5 years was defined as a renal endpoint event, and Kaplan-Meier survival analysis and Log-rank test were used to compare the difference in cumulative incidence of renal endpoint events between two groups of patients.Results:A total of 101 DN patients were enrolled in this study, including 68 males (67.3%) and 33 females (32.7%), with age of (52.2±10.3) years and a median follow-up time of 13.5(4.8, 26.3) months. There were 44 patients with IgA deposition (43.6%) and 57 patients without IgA deposition (56.4%). Compared with DN control group, Kaplan-Meier analysis showed that DN patients with IgA deposition had a higher cumulative incidence of renal endpoint within 5 years ( χ2=6.473, P=0.011). The proportion of positive glomerular Gd-IgA1 (KM55) staining in the DN patients with IgA deposition was 54.5% (24/44), and immunofluorescence examination showed consistent distribution of Gd-IgA1 and IgA in the glomerular mesangial and capillary regions. The serum level of Gd-IgA1 in the glomerular Gd-IgA1 positive patients was significantly higher than that in those negative patients [(6 296.4± 1 535.4) μg/L vs. (4 057.4±1 082.0) μg/L, t=-3.037, P=0.010]. In DN patients with IgA deposition, the age of the subgroup with endpoint events was younger [(42.8±6.9) years vs. (53.3±9.4) years, t=-3.440, P=0.002], the duration of proteinuria was shorter [6.0(1.0, 22.0) months vs. 12.0(10.0, 36.0) months, Z=-2.150, P=0.032], and the proportion of patients with glomerular Gd-IgA1 staining intensity ≥2+ was higher [Fisher'exact test, 30.8%(4/13) vs. 0(0/20), P=0.017]. Kaplan-Meier survival analysis showed that patients with glomerular Gd-IgA1 staining intensity≥2+ had a significantly higher cumulative incidence of renal endpoint events ( χ2=4.846, P=0.028). Conclusion:DN patients with glomerular IgA deposition and Gd-IgA1 positivity may be associated with worse prognosis.

Objective To explore the predictive value of ultra-sound(US)combined with multi-sequence MRI in a clinical-deep learning radiomics nomogram(DLRN)for the short-term efficacy of neoadjuvant chemotherapy(NAC)in patients with triple-negative breast cancer(TNBC).Methods A total of 122 TNBC patients from five hospitals were retrospectively analyzed,and divided into training group(72 cases)and validation group(50 cases).The clinical and pathological data,NAC regimens,and imaging data were collected.The lesions and its surrounding 10-unit voxels from US and MRI images were retained as the region of interest(ROI).Pyradiomics software and a ResNet152 convolutional neural network(CNN)framework were used to extract radiomics and deep learning features to construct a clinical-DLRN with outcome dimension fusion.The receiver operating characteristic(ROC)curve and calibration curve were plotted,and five-fold cross-validation decision curve were used to verify the model's clinical effec-tiveness.Results The clinical-DLRN constructed by US combined with multi-sequence MRI showed that area under the curve(AUC)was 0.967[95％confidence interval(CI)0.782-0.967]and accuracy(ACC)was 0.900,respectively.The five-fold cross-validation decision curve showed good generalization,with the highest clinical net benefit between risk thresholds of 0.72 and 0.96.Conclusion The clinical-DLRN integrating US and multi-sequence MRI has the best efficacy in predicting the short-term efficacy of NAC in TNBC patients,which offering potential guidance for personalized TNBC treatment.

Purpose To explore the clinicopathologic features and differential diagnosis of nephrogenic adenomas(NAs)in urinary tract.Methods 27 cases of NA were collected.The clinicopathological features and differential di-agnosis were analyzed,and the relevant literatures were reviewed.Results A total of 27 cases of NA in urinary tract were included in this study,including 20 males and 7 females,ranging in age from 24 to 84 years.Among them,clini-cal manifestations included urinary tract irritation in 8 cases,hematuria in 7 cases,and no obvious symptoms or other comorbidities in 12 cases.Comorbidities:17 cases combined with urothelial tumors,4 cases with cystitis,2 cases with tuberculosis,2 cases with urethral diverticulum,and 2 cases with ureteral calculi or stenosis.Gross inspection:19 ca-ses occurred in the bladder,5 in the ureter,and 3 in the urethra.The average size of the lesions was about 4.3 mm.Local edema or protrusion of the mucosa with roughness were found in 18 cases,papillary or polypoid masses in 5 ca-ses,or follicular-like neoplasma in 4 cases.Histologic features:these lesions were mainly composed of papillary,tubu-lar and cystic structure,and eosinophilic colloid secretions were seen in the lumen.The lining epithelium was cuboidal or low columnar,some of which were 'hobnail' or signet ring-like cells,and stroma showed edema and chronic inflam-mation.Immunohistochemistry:epithelial cells expressed PAX8 and CK7,partially expressed P504S and GAT A3,but not p63 and PSA.p53 was wild type,and Ki67 proliferation index was low(1％-8％).Molecular testing:no ab-normalities were found in 14 urine FISH tests before surgery,and no fusion mutation was detected in 2 samples selected for second-generation sequencing.Treatment and follow-up:follow-up data were obtained for all cases,of which 24 un-derwent transurethral resection of bladder lesions,and the rest underwent nephroureterectomy or cystoprostatectomy.The mean follow-up was 26.6(1-59)months,and the lesion recurred in 2 cases.Conclusion NAs are relatively rare,and their final diagnosis depends on pathological examination.When the biopsy sample is small or the histomor-phology is atypical,it's often necessary to differentiate it from urothelial tumor,prostate adenocarcinoma and clear cell adenocarcinoma.Understanding the clinicopathologic and immunohistochemical features of NA is helpful to improve the diagnostic rate and avoid missed-diagnosis or misdiagnosis.