Objective: To analyze serum anti-Müllerian hormone (AMH) level and its influencing factors among female undergoing premarital and preconception examinations, so as to provide the evidence for optimizing reproductive health management measures. Methods: Female who received free premarital and preconception examinations and voluntarily underwent serum AMH testing at Women and Children's Health Center of Gongshu District, Hangzhou City from January 2022 to April 2025 were selected as study subjects. Demographic information and reproductive history were collected through questionnaire survey. Venous blood was collected to detect thyroid-stimulating hormone (TSH), alanine aminotransferase, hemoglobin (Hb), and AMH levels. The original AMH values did not follow a normal distribution, but followed a normal distribution after natural logarithm transformation, recorded as ln (AMH). Pearson correlation analysis was used to analyze the correlation between variables, and multiple linear regression model was used to analyze the influencing factors for ln (AMH) levels among female undergoing premarital and preconception examinations. Results: A total of 1 073 females undergoing premarital and preconception examinations were surveyed, with a mean age of (29.43±3.30) years. There were 959 females without pregnancy (89.38%) and 1 042 females without full-term live birth history (97.11%). The median AMH level was 3.85 (interquartile range, 3.63) ng/mL, and the mean ln (AMH) level was 1.27±0.75. The ln (AMH) levels were higher in females without pregnancy and without full-term live birth history (both P<0.05). The ln (AMH) level was negatively correlated with age (r=-0.260) and TSH (r=-0.093), and positively correlated with Hb (r=-0.260, -0.093, and 0.073, all P<0.05). Multiple linear regression analysis showed that age (β′=-0.253) and TSH (β′=-0.103) were statistically associated with ln (AMH) levels among female undergoing premarital and preconception examinations (both P<0.05). The associations of other variables with ln (AMH) levels were not statistically significant (all P>0.05). Conclusions Age and TSH level are influencing factors for AMH levels among female undergoing premarital and preconception examinations. AMH levels among female undergoing premarital and preconception examinations decrease with increasing age and increasing TSH level.

Objective: To investigate whether TYRO protein tyrosine kinase-binding protein (TYROBP) affects the progression of diabetic kidney disease (DKD) through the extracellular signal-regulated kinase ( ERK) pathway. Methods: Key genes in DKD were identified through bioinformatics analysis . Immunohistochemical staining and quantitative real-time PCR (qPCR) were used to validate the expression levels of TYROBP in a DKD mouse model and high glucose-stimulated NRK-52E cells . NRK-52E cell models with stable TYROBP overexpression/knockdown and their corresponding empty vector (ev) /scrambled sequence (ss) controls were established via lentiviral trans- fection . Cells were treated with 5 . 5 mmol/L or 30. 0 mmol/L glucose for 72 hours to mimic normal glucose (NG) and high glucose ( HG) conditions , respectively. High glucose medium containing 3 . 5 μmol/L FR180204 was used for ERK inhibitor intervention . The experiment included seven groups : ev + NG , ev + HG , oe-TYROBP + HG , ss + NG , ss + HG , sh-TYROBP + HG , and sh-TYROBP + HG + ERK inhibitor. Western blot was used to de- tect the expression levels of phosphorylated ERK/total ERK (p-ERK/ERK) , apoptosis-related proteins B-cell lym- phoma-2 (Bcl-2) and Bcl-2-associated X protein ( Bax) , and epithelial-mesenchymal transition ( EMT)-related proteins E-cadherin and α-smooth muscle actin ( α-SMA) . Tetramethylrhodamine ethyl ester (TMRE) staining and Annexin V-fluorescein isothiocyanate/propidium iodide (Annexin V-FITC/PI) flow cytometry were performed to as- sess mitochondrial membrane potential and apoptosis levels . Results: Bioinformatics analysis identified TYROBP as a key gene in DKD . In vivo and in vitro validation showed increased TYROBP mRNA levels in DKD models . The results from the HG model indicated that , compared to the ev + NG/ss + NG group , the ev + HG/ss + HG group demonstrated increased p-ERK/ERK expression , reduced mitochondrial membrane potential , elevated apoptosis , and enhanced EMT. In TYROBP-perturbed NRK-52E cells , compared to the ev + HG group , the oe-TYROBP + HG group showed decreased p-ERK/ERK expression (P < 0. 01) , increased mitochondrial membrane potential (P < 0. 05) , reduced apoptosis (P < 0. 001) , and attenuated EMT; whereas compared to the ss + HG group , the sh- TYROBP + HG group exhibited increased p-ERK/ERK expression ( P < 0. 001) , decreased mitochondrial mem- brane potential (P < 0. 01) , elevated apoptosis (P < 0. 001) , and enhanced EMT. Furthermore , compared to the sh-TYROBP + HG group , the sh-TYROBP + HG + ERK inhibitor group displayed reduced p-ERK/ERK expression (P < 0. 01) , increased mitochondrial membrane potential ( P < 0. 001) , decreased apoptosis ( P < 0. 001) , and suppressed EMT. Compared with the scrambled sequence control + high glucose group , the TYROBP knockdown + high glucose group showed elevated p-ERK/ERK expression ( P < 0. 001) , reduced mitochondrial membrane potential (P < 0. 01) , increased apoptosis level (P < 0. 001) , and enhanced EMT. Compared with the TYROBP knockdown + high glucose group , the TYROBP knockdown + high glucose + ERK inhibitor group demonstrated decreased p-ERK/ERK expression (P < 0. 01) , restored mitochondrial membrane potential (P < 0. 001) , reduced apoptosis level (P < 0. 001) , and suppressed EMT. Conclusion TYROBP may regulate the ERK signaling path- way to modulate apoptosis- and EMT-related proteins , thereby influencing mitochondrial membrane potential , apop- tosis , and EMT in renal tubular epithelial cells and contributing to DKD progression .

Objective To explore the impact of early discharge guidance,based on an intelligent education system,on postoperative pain management,functional recovery,and discharge readiness in lung cancer patients.Methods A total of 170 lung cancer patients were selected from Jinhua Municipal Central Hospital from July 2022 to June 2023.According to the time of admission,patients admitted between July to November 2022 were assigned to control group(n=82),while patients admitted between December 2022 to June 2023 were assigned to observation group(n=88).Control group received routine perioperative health education,while observation group received additional intelligent education system.Following outcomes were compared between two groups:Time to first ambulation after surgery,pain numeric rating scale(NRS)scores on postoperative 1 to 3 days and on day of discharge,performance on 2-minute step test on day of discharge,and readiness for hospital discharge scale(RHDS).Results Time to first ambulation post operative in observation group was shorter than that in control group.NRS scores at 72 hours post operative and on day of discharge were lower in observation group compared to control group.Number of steps completed in 2-minute step test in observation group was higher than that in control group.Additionally,RHDS scores in observation group was higher than that in control group,and all differences were statistically significant(P＜0.05).Conclusion The discharge planning advancement driven by the intelligent education system significantly improved early postoperative ambulation,reduced postoperative pain,enhanced physical function,and increased discharge readiness in lung cancer patients,thereby effectively promoting postoperative recovery.

Recent innovations in endoscopic techniques have dramatically transformed the landscape of biliary and pancreatic disease management,particularly through the synergistic integration of peroral choledochoscope-assisted cholangioscopy and endoscopic retrograde cholangiopancreatography(ERCP).This article delves into the clinical utility of peroral choledochoscope within the ERCP framework,highlighting its pivotal role in enhancing diagnostic precision.

The accurate and timely detection of biochemical coagulation indicators is pivotal in pulmonary and critical care medicine. Despite their reliability, traditional laboratories often lag in terms of rapid diagnosis. Point-of-care testing (POCT) has emerged as a promising alternative, which is awaiting rigorous validation. We assessed 226 samples from patients at the First Affiliated Hospital of Guangzhou Medical University using a Beckman Coulter AU5821 and a PUSHKANG POCT Biochemistry Analyzer MS100. Furthermore, 350 samples were evaluated with a Stago coagulation analyzer STAR MAX and a PUSHKANG POCT Coagulation Analyzer MC100. Metrics included thirteen biochemical indexes, such as albumin, and five coagulation indices, such as prothrombin time. Comparisons were drawn against the PUSHKANG POCT analyzer. Bland-Altman plots (MS100: 0.8206‒0.9995; MC100: 0.8318‒0.9911) evinced significant consistency between methodologies. Spearman correlation pinpointed a potent linear association between conventional devices and the PUSHKANG POCT analyzer, further underscored by a robust correlation coefficient (MS100: 0.713‒0.949; MC100: 0.593‒0.950). The PUSHKANG POCT was validated as a dependable tool for serum and whole blood biochemical and coagulation diagnostics. This emphasizes its prospective clinical efficacy, offering clinicians a swift diagnostic tool and heralding a new era of enhanced patient care outcomes.
Humans ; Point-of-Care Testing ; Critical Care ; Blood Coagulation Tests/methods* ; Male ; Blood Coagulation ; Female ; Middle Aged ; Reproducibility of Results ; Prothrombin Time ; Aged ; Adult ; Point-of-Care Systems

Receptor-interacting protein kinase 1 (RIPK1) plays an essential role in regulating the necroptosis and apoptosis in cerebral ischemia-reperfusion (I/R) injury. However, the regulation of RIPK1 kinase activity after cerebral I/R injury remains largely unknown. In this study, we found the downregulation of protein arginine methyltransferase 1 (PRMT1) was induced by cerebral I/R injury, which negatively correlated with the activation of RIPK1. Mechanistically, we proved that PRMT1 directly interacted with RIPK1 and catalyzed its asymmetric dimethylarginine, which then blocked RIPK1 homodimerization and suppressed its kinase activity. Moreover, pharmacological inhibition or genetic ablation of PRMT1 aggravated I/R injury by promoting RIPK1-mediated necroptosis and apoptosis, while PRMT1 overexpression protected against I/R injury by suppressing RIPK1 activation. Our findings revealed the molecular regulation of RIPK1 activation and demonstrated PRMT1 would be a potential therapeutic target for the treatment of ischemic stroke.

Objective To analyze the occupational health literacy (OHL) level and its influencing factors of workers in non-metallic mineral product industry in Yunfu City. Methods A total of 947 frontline workers from 24 non-metallic mineral products enterprises in Yunfu City were selected as the research subjects using the stratified random sampling method. The OHL level of the workers were assessed using the Occupational Health Literacy Questionnaire of National Key Populations. Results The overall OHL level of the research subjects was 58.3% (552/947). The OHL levels across four dimensions, from highest to lowest, were basic knowledge of occupational health protection (94.7%), healthy work practices and behaviors (81.8%), legal knowledge of occupational health (65.5%), and basic skills of occupational health protection (25.9%). The results of binary logistic regression analysis showed that workers with 2.0-<10.0 years and ≥10 years of work experience had higher OHL levels than those with <2.0 years of work experience (all P<0.01). Workers with a high school education or above had higher OHL levels than those with a junior high school education or below (all P<0.01). Workers in large- and medium-sized enterprises had higher OHL levels than those in small and micro-sized enterprises (both P<0.01). Conclusion The OHL levels of workers in Yunfu City's non-metallic mineral products industry can be further improved, particularly the occupational health protection skills and related legal knowledge. Workers with short seniority, low educational level, and in small and micro enterprises should be the key groups for improving OHL levels.

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 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 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.