Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To investigate the effect of sodium-glucose cotransporter 2 inhibitor (empagliflozin, EMPA) on myocardial remodeling in a mouse uremic cardiomyopathy (UCM) model induced by 5/6 nephrectomy, through the phosphatidylinositol 3 kinase (PI3K)/protein kinase B (PKB/AKT)/p65 signaling pathway. Methods The animals were divided into three groups: Sham group (n=6), UCM group (n=8), and UCM＋EMPA group (n=8). A UCM model was established in C57BL/6N mice using the 5/6 nephrectomy. Starting from 5 weeks post-surgery, EMPA or a placebo was administered. After 16 weeks, blood pressure, serum creatinine, blood urea nitrogen, 24-hour urine glucose and urine sodium were measured. Cardiac structure and function were assessed by echocardiography. Hematoxylin-eosin (HE) staining and Masson trichrome staining were used to observe pathological changes in the heart and kidneys. Wheat germ agglutinin (WGA) staining was used to evaluate myocardial hypertrophy. The real-time quantitative PCR (RT-qPCR) was used to detect the expression levels of myocardial hypertrophy- and fibrosis-related mRNAs. Western blotting was used to detect the expression levels of PI3K, AKT and p65 in myocardial tissues. Results After 16 weeks, UCM group exhibited significantly higher blood pressure, serum creatinine, blood urea nitrogen than sham group (P＜0.01); UCM＋EMPA group exhibited lower blood pressure, serum creatinine, blood urea nitrogen, and higher 24 h urine sodium and glucose than UCM group (P＜0.05). Echocardiographic results showed ventricular remodeling in the UCM group, evidenced by left ventricular wall thickening, left ventricular enlargement, increased left ventricular mass, and decreased systolic function (P＜0.05); ventricular remodeling was alleviated (P＜0.05), though there was no significant improvement in systolic function in UCM＋EMPA group. HE and Masson stainings revealed myocardial degeneration, necrosis, and interstitial fibrosis in UCM group (P＜0.01); the myocardial pathology improved with reduced collagen deposition in UCM＋EMPA group (P＜0.01). WGA staining confirmed myocardial hypertrophy in UCM group (P＜0.01), while myocardial hypertrophy was alleviated in UCM＋EMPA group (P＜0.01). RT-qPCR results showed myocardial hypertrophy- and fibrosis-related genes (NPPA, NPPB, MYH7, COL1A1, COL3A1, TGF-β1) were upregulated in UCM group (P＜0.05), but downregulated in UCM＋EMPA group. Western blotting showed PI3K, p-AKT/AKT ratio, and p-p65/p65 ratio were increased in UCM group, but decreased in UCM＋EMPA group (P＜0.05). Conclusion EMPA can improve myocardial hypertrophy and fibrosis in the UCM mouse model, and it may play the role through inhibiting the PI3K/AKT/p65 signaling pathway.

ObjectiveTo investigate the pathogenic spectrum and epidemiological characteristics of diarrheal disease in Fengxian District of Shanghai, and to provide scientific basis for the prevention and control of diarrheal diseases. MethodsBasic information of the initial adult cases visited diarrheal disease surveillance sentinel hospital in Fengxian District, Shanghai, was collected from August 2013 to 2023, and fecal samples were collected at 1∶5 sampling intervals to isolate and identify 5 kinds of diarrheagenic Escherichia coli (DEC), Salmonella (SAL), Vibrio parahaemolyticus, Campylobacter, Vibrio cholerae, Shigella and Yersinia enterocolitica (YE). Simultaneously, nucleic acid detection was performed for 3 kinds of rotavirus, 2 kinds of norovirus, intestinal adenovirus, astrovirus and sapovirus. ResultsA total of 1 861 cases of newly diagnosed diarrheal disease were reported, with the peak in July to August. Additionally, 704 surveillance samples were detected, with a total positive detection rate of 50.57%. The detection rates of bacterial, viral and mixed infection were 25.14%, 21.02% and 4.40%, respectively. Among the pathogens detected, DEC accounted for the highest (17.61%, 124/704), followed by norovirus (16.48%, 116/704), rotavirus (6.39%, 45/704), SAL (5.97%, 42/704) and Campylobacter (3.84%, 27/704). DEC detected were mainly enteroaggregative Escherichia coli and enterotoxigenic Escherichia coli, with no detection of Vibrio cholerae, Shigella and YE. The highest total pathogen detection rate was observed from June to September, and the detection peaks of norovirus were from March to June and from October to December, whereas that of DEC was from June to October. The detection rate of rotavirus peaked from January to February, but which was not detected between 2020‒2023. The SAL positive rate peak was in September, whereas that of Campylobacter was from July to September. ConclusionThe main pathogens detected in Fengxian District from 2013‒2019 are DEC, norovirus, rotavirus, SAL and Campylobacter. Different pathogens have different detection peaks, with bacteria predominating in summer and viruses in winter and spring. Prevention and control measures should be carried out according to the epidemiological characteristics of different seasons.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

PURPOSE: The secondary damage of spinal cord injury (SCI) starts from the collapse of the blood spinal cord barrier (BSCB) to chronic and devastating neurological deficits. Thereby, the retention of the integrity and permeability of BSCB is well-recognized as one of the major therapies to promote functional recovery after SCI. Previous studies have demonstrated that activation of hypoxia inducible factor-1α (HIF-1α) provides anti-apoptosis and neuroprotection in SCI. Endogenous HIF-1α, rapidly degraded by prolylhydroxylase, is insufficient for promoting functional recovery. Dimethyloxalylglycine (DMOG), a highly selective inhibitor of prolylhydroxylase, has been reported to have a positive effect on axon regeneration. However, the roles and underlying mechanisms of DMOG in BSCB restoration remain unclear. Herein, we aim to investigate pathological changes of BSCB restoration in rats with SCI treated by DOMG and evaluate the therapeutic effects of DMOG. METHODS: The work was performed from 2022 to 2023. In this study, Allen's impact model and human umbilical vein endothelial cells were employed to explore the mechanism of DMOG. In the phenotypic validation experiment, the rats were randomly divided into 3 groups: sham group, SCI group, and SCI + DMOG group (10 rats for each). Histological analysis via Nissl staining, Basso-Beattie-Bresnahan scale, and footprint analysis was used to evaluate the functional recovery after SCI. Western blotting, TUNEL assay, and immunofluorescence staining were employed to exhibit levels of tight junction and adhesion junction of BSCB, HIF-1α, cell apoptosis, and endoplasmic reticulum (ER) stress. The one-way ANOVA test was used for statistical analysis. The difference was considered statistically significant at p < 0.05. RESULTS: In this study, we observed the expression of HIF-1α reduced in the SCI model. DMOG treatment remarkably augmented HIF-1α level, alleviated endothelial cells apoptosis and disruption of BSCB, and enhanced functional recovery post-SCI. Besides, the administration of DMOG offset the activation of ER stress induced by SCI, but this phenomenon was blocked by tunicamycin (an ER stress activator). Finally, we disclosed that DMOG maintained the integrity and permeability of BSCB by inhibiting ER stress, and inhibition of HIF-1α erased the protection from DMOG. CONCLUSIONS Our findings illustrate that the administration of DMOG alleviates the devastation of BSCB and HIF-1α-induced inhibition of ER stress.
Spinal Cord Injuries/pathology* ; Animals ; Apoptosis/drug effects* ; Amino Acids, Dicarboxylic/therapeutic use* ; Recovery of Function/drug effects* ; Rats ; Rats, Sprague-Dawley ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Male ; Spinal Cord/blood supply*

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*

Investigating the correlation between micronucleus formation and male infertility has the potential to improve clinical diagnosis and deepen our understanding of pathological progression. Our study enrolled 2252 male patients whose semen was analyzed from March 2023 to July 2023. Their clinical data, including semen parameters and age, were also collected. Genetic analysis was used to determine whether the sex chromosome involved in male infertility was abnormal (including the increase, deletion, and translocation of the X and Y chromosomes), and subsequent semen analysis was conducted for clinical grouping purposes. The participants were categorized into five groups: normozoospermia, asthenozoospermia, oligozoospermia, oligoasthenozoospermia, and azoospermia. Patients were randomly selected for further study; 41 patients with normozoospermia were included in the control group and 117 patients with non-normozoospermia were included in the study group according to the proportions of all enrolled patients. Cytokinesis-block micronucleus (CBMN) screening was conducted through peripheral blood. Statistical analysis was used to determine the differences in micronuclei (MNi) among the groups and the relationships between MNi and clinical data. There was a significant increase in MNi in infertile men, including those with azoospermia, compared with normozoospermic patients, but there was no significant difference between the genetic and nongenetic groups in azoospermic men. The presence of MNi was associated with sperm concentration, progressive sperm motility, immotile spermatozoa, malformed spermatozoa, total sperm count, and total sperm motility. This study underscores the potential utility of MNi as a diagnostic tool and highlights the need for further research to elucidate the underlying mechanisms of male infertility.
Humans ; Male ; Infertility, Male/genetics* ; Adult ; Micronucleus Tests ; Semen Analysis ; Oligospermia/genetics* ; Azoospermia/genetics* ; Chromosome Aberrations ; Sperm Count ; Micronuclei, Chromosome-Defective ; Middle Aged

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 explore the efficacy and apoptosis of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the treatment of acute myeloid leukemia (AML) with ASXL1 mutation. METHODS: The clinical data of 80 AML patients with ASXL1 mutation treated in our hospital from January 2019 to December 2021 were retrospectively analyzed. The clinical characteristics of the patients were summarized, and the therapeutic effect and prognostic factors of allo-HSCT for the patients were analyzed. RESULTS: Among the 80 patients, 38 were males and 42 were females, and the median age was 39(14-65) years. There were 17 patients in low-risk group, 25 patients in medium-risk group and 38 patients in high-risk group. ASXL1 mutation co-occurred with many other gene mutations, and the frequent mutated genes were TET2 (71.25%), NRAS (18.75%), DNMT3A (16.25%), NPM1 (15.00%), CEBPA (13.75%). Among medium and high-risk patients, 29 underwent allo-HSCT, while 34 received chemotherapy. The 2-year overall survival (OS) rate and disease-free survival (DFS) rate of the allo-HSCT group were 72.4% and 70.2%, while those of the chemotherapy group were 44.1% and 34.0%, respectively. The statistical analysis showed significant differences between the two groups (both P < 0.01). Multivariate analysis showed that age at transplantation >50- years and occurrence of acute graft-versus-host disease after transplantation were poor prognostic factors for OS and DFS in transplantation patients. CONCLUSION Allo-HSCT can improve the prognosis of AML patients with ASXL1 mutation.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Middle Aged ; Mutation ; Adult ; Repressor Proteins/genetics* ; Adolescent ; Retrospective Studies ; Aged ; Nucleophosmin ; Young Adult ; Transplantation, Homologous ; Prognosis ; Survival Rate

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.