Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

OBJECTIVES: To study clinical manifestations and gene mutation features of neonates with centronuclear myopathy. METHODS: A retrospective analysis was conducted on the medical data of 5 neonates with centronuclear myopathy diagnosed in the Neonatal Intensive Care Unit of Children's Hospital, Zhejiang University School of Medicine from January 2020 to August 2024. The data included gender, gestational age, birth weight, Apgar score, clinical manifestations, creatine kinase level, electromyography, genetic testing results and the outcomes of the infants. RESULTS: All 5 male neonates had a history of postpartum asphyxia and resuscitation. They all presented with hypotonia, myasthenia, and respiratory failure; two neonates also had swallowing dysfunction. Of the five neonates, three had normal creatine kinase levels, while two had slightly elevated levels. Electromyography was performed for three neonates, among whom two had myogenic damage. MTM1 gene mutations were identified by genetic testing in all five neonates, including two nonsense mutations and three missense mutations, among which one variant had not been previously reported. Four mutations were inherited from the mother, and the other one was a de novo mutation. The five neonates showed no clinical improvement following treatment, failed weaning from mechanical ventilation, and ultimately died after withdrawal of life-sustaining therapy. CONCLUSIONS Centronuclear myopathy caused by MTM1 gene mutation often has a severe phenotype and a poor prognosis, and it should be considered for neonates with hypotonia and myasthenia after birth. Genetic testing should be performed as soon as possible.
Humans ; Myopathies, Structural, Congenital/genetics* ; Male ; Infant, Newborn ; Retrospective Studies ; Mutation ; Female ; Protein Tyrosine Phosphatases, Non-Receptor/genetics*

Objective To study the antioxidant activity and organ protection of different components of Panax notoginseng polysaccharide(PNPS)in D-galactose-induced oxidative damage aging model mice.Methods KM mice were randomly divided into normal group,model group,vitamin C(VC)group(given 200 mg·kg-1 VC),crude polysaccharide from Panax notoginseng(CPPN)group,neutral polysaccharide from Panax notoginseng(NPPN)group and acidic polysaccharide from Panax notoginseng(APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ)group(given 400 mg·kg-1 CPPN,NPPN,APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ,respectively).Except for the normal group,oxidative injury aging mouse models were established by intraperitoneal injection of 1 g·kg-1 D-galactose.The mice were sacrificed after continuous administration for 42 days,and serum and liver homogenate were prepared.Malondialdehyde(MDA)was determined by thiobarbituric acid method;superoxide dismutase(SOD)was determined by tetrazole salt method;glutathione peroxidase(GSH-Px)was determined by double antibody sandwich method.Results Serum SOD in the normal group,model group,VC group,CPPN group,NPPN group and APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ groups were(15.07±0.69),(12.79±1.51),(15.56±1.01),(13.69±0.96),(14.27±0.64),(14.31±0.99),(14.18±0.79)and(15.85±0.89)U·mL-1;serum GSH-Px were(105.35±4.97),(90.36±4.31),(111.51±7.00),(113.03±8.06),(118.77±5.19),(123.60±8.08),(131.65±3.60)and(149.22±13.32)ng·L-1;serum MDA were(1.72±0.26),(4.16±0.92),(2.26±0.59),(2.82±0.47),(2.46±0.50),(1.98±0.41),(2.39±0.39)and(2.07±0.24)nmol·mL-1;the liver SOD were(234.22±3.84),(205.04±7.28),(234.63±6.37),(214.99±17.66),(234.13±3.63),(234.63±3.44),(233.87±5.63)and(235.42±2.33)U·mgprot-1;liver GSH-Px were(274.27±23.72),(207.00±15.22),(257.68±16.39),(249.79±18.78),(252.62±10.92),(256.25±21.83),(261.20±17.52)and(263.16±17.98)ng·L-1;liver MDA were(35.70±3.52),(49.65±6.32),(36.15±2.48),(39.17±4.29),(37.40±6.19),(35.34±4.06)and(35.90±5.36),(33.31±7.64)nmol·mgprot-1.Compared with the normal group,SOD,GSH-Px in serum and liver of mice in the model group were significantly reduced,and the content of MDA was significantly increased(all P＜0.01).After treatment with different components of Panax notoginseng polysaccharide,the oxidative indicators in mice were significantly improved,among which APPN-Ⅲ have the best antioxidant activity,which could significantly increase the activities of SOD,GSH-Px in serum and liver,and reduce the content of MDA(all P＜0.01).Conclusion Different components of Panax notoginseng polysaccharide have antioxidant activity and organ protection in vivo,among which APPN-Ⅲ has the best antioxidant activity and has a good organ protection effect.

Objective To identify the biomarkers for early rheumatoid arthritis(RA)diagnosis and explore the possible immune regulatory mechanisms.Methods The differentially expressed genesin RA were screened and functionally annotated using the limma,RRA,batch correction,and clusterProfiler.The protein-protein interaction network was retrieved from the STRING database,and Cytoscape 3.8.0 and GeneMANIA were used to select the key genes and predicting their interaction mechanisms.ROC curves was used to validate the accuracy of diagnostic models based on the key genes.The disease-specific immune cells were selected via machine learning,and their correlation with the key genes were analyzed using Corrplot package.Biological functions of the key genes were explored using GSEA method.The expression of STAT1 was investigated in the synovial tissue of rats with collagen-induced arthritis(CIA).Results We identified 9 core key genes in RA(CD3G,CD8A,SYK,LCK,IL2RG,STAT1,CCR5,ITGB2,and ITGAL),which regulate synovial inflammation primarily through cytokines-related pathways.ROC curve analysis showed a high predictive accuracy of the 9 core genes,among which STAT1 had the highest AUC(0.909).Correlation analysis revealed strong correlations of CD3G,ITGAL,LCK,CD8A,and STAT1 with disease-specific immune cells,and STAT1 showed the strongest correlation with M1-type macrophages(R=0.68,P=2.9e-08).The synovial tissues of the ankle joints of CIA rats showed high expressions of STAT1 and p-STAT1 with significant differential expression of STAT1 between the nucleus and the cytoplasm of the synovial fibroblasts.The protein expressions of p-STAT1 and STAT1 in the cell nuclei were significantly reduced after treatment.Conclusion CD3G,CD8A,SYK,LCK,IL2RG,STAT1,CCR5,ITGB2,and ITGAL may serve as biomarkers for early diagnosis of RA.Gene-immune cell pathways such as CD3G/CD8A/LCK-γδ T cells,ITGAL-Tfh cells,and STAT1-M1-type macrophages may be closely related with the development of RA.

Objective To identify the biomarkers for early rheumatoid arthritis(RA)diagnosis and explore the possible immune regulatory mechanisms.Methods The differentially expressed genesin RA were screened and functionally annotated using the limma,RRA,batch correction,and clusterProfiler.The protein-protein interaction network was retrieved from the STRING database,and Cytoscape 3.8.0 and GeneMANIA were used to select the key genes and predicting their interaction mechanisms.ROC curves was used to validate the accuracy of diagnostic models based on the key genes.The disease-specific immune cells were selected via machine learning,and their correlation with the key genes were analyzed using Corrplot package.Biological functions of the key genes were explored using GSEA method.The expression of STAT1 was investigated in the synovial tissue of rats with collagen-induced arthritis(CIA).Results We identified 9 core key genes in RA(CD3G,CD8A,SYK,LCK,IL2RG,STAT1,CCR5,ITGB2,and ITGAL),which regulate synovial inflammation primarily through cytokines-related pathways.ROC curve analysis showed a high predictive accuracy of the 9 core genes,among which STAT1 had the highest AUC(0.909).Correlation analysis revealed strong correlations of CD3G,ITGAL,LCK,CD8A,and STAT1 with disease-specific immune cells,and STAT1 showed the strongest correlation with M1-type macrophages(R=0.68,P=2.9e-08).The synovial tissues of the ankle joints of CIA rats showed high expressions of STAT1 and p-STAT1 with significant differential expression of STAT1 between the nucleus and the cytoplasm of the synovial fibroblasts.The protein expressions of p-STAT1 and STAT1 in the cell nuclei were significantly reduced after treatment.Conclusion CD3G,CD8A,SYK,LCK,IL2RG,STAT1,CCR5,ITGB2,and ITGAL may serve as biomarkers for early diagnosis of RA.Gene-immune cell pathways such as CD3G/CD8A/LCK-γδ T cells,ITGAL-Tfh cells,and STAT1-M1-type macrophages may be closely related with the development of RA.