ObjectiveTo explore the effect of Yishen Tongluo prescription on sperm DNA fragmentation index （DFI） and sperm mitochondrial membrane potential （MMP） in patients with asymptomatic idiopathic asthenospermia infertility. MethodsA total of 128 patients with asymptomatic idiopathic asthenospermia were randomly assigned to an experimental group （64 cases） and a control group （64 cases）. The experimental group received Yishen Tongluo prescription， while the control group was treated with Wuzi Yanzongwan combined with L-carnitine oral solution. One treatment course lasted 12 weeks. Spouse pregnancy rate， sperm progressive motility （PR）， total sperm motility （PR+NP）， sperm function （sperm tail hypotonic swelling rate， sperm acrosin activity）， sperm DFI， and sperm MMP were compared between the two groups before and after treatment. Adverse reactions were observed and recorded during the study， and clinical efficacy and safety were systematically evaluated. ResultsA total of 121 patients completed the study， including 61 in the experimental group and 60 in the control group. The spouse pregnancy rate in the experimental group was 14.75% （9/61）， higher than that in the control group at 6.67% （4/60）， though the difference was not statistically significant. Clinical efficacy in the experimental group was superior to that in the control group （P<0.05）. Compared with the results before treatment， sperm PR， PR + NP， sperm tail hypotonic swelling rate， sperm acrosin activity， sperm DFI， and sperm MMP were significantly improved in both groups after treatment （P<0.05）， with greater improvements in the experimental group （P<0.05）. However， there was no significant change in sperm concentration in either group after treatment. During the study， no abnormal safety indicators or significant adverse reactions occurred in either group. ConclusionThe kidney-tonifying and collateral-dredging method shows good clinical efficacy in the treatment of asymptomatic idiopathic asthenospermia infertility. Yishen Tongluo prescription can improve sperm motility， increase spouse pregnancy rate， enhance sperm function， and demonstrates good safety. Its mechanism may be related to reducing sperm DFI and increasing sperm MMP.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective To construct a diagnostic and prognostic model for malignant pleural effusion (MPE) in patients with non-M1b stage (AJCC 7th edition) non-small cell lung cancer (NSCLC) by machine learning. Methods Retrospective analysis was conducted on patients diagnosed with NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2015, excluding those in the M1b stage. Two sets of data were collected: data 1 (patients with non-M1b stage NSCLC, n=47 392) was used to construct the MPE diagnostic model; and data 2 (patients with M1a stage NSCLC and MPE, n=2 422) was used to construct a prognostic model. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen feature variables, with a training set and validation set ratio of 7:3. Models were built using eight machine learning algorithms, with evaluation metrics including accuracy, precision, recall, F1 score, area under the ROC curve (AUC), decision curve, calibration curve, and precision recall curve (PR), with ROC-AUC as the main evaluation metric. Results The incidence of MPE in patients with non-M1b stage NSCLC was 5.12%, and the 1-year survival rate of patients with MPE was 32.5%. LASSO regression identified nine diagnostic-related variables and 12 prognostic-related variables. The AUC values of the models constructed by eight machine learning algorithms all exceeded 0.70. The random forest model performed the best in the diagnostic model (training set AUC=0.908, validation set AUC=0.897), and the XGBoost model showed the best performance in the prognostic model (training set AUC=0.905, validation set AUC=0.875). Other evaluation indicators showed good results and balanced distribution. SHAP feature importance analysis showed that tumor size, lymph node metastasis, and histological type were important influencing factors for the occurrence of MPE, and chemotherapy intervention was the most remarkably prognostic factor. Conclusion The random forest diagnostic model constructed in this study can effectively predict the risk of MPE in patients with non-M1b stage NSCLC, and the XGBoost prognostic model can predict the prognosis of M1a-stage NSCLC patients with concurrent MPE.

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

Objective:This study aimed to investigate the correlation between the ingested dose of amlodipine and the severity of shock in affected patients by analyzing clinical data from documented cases.Methods:This study respectively included adult patients treated for amlodipine poisoning-induced shock at the emergency department of Peking University Third Hospital between January 2018 and December 2022. Additionally, cases reported in the literature from January 1997 to December 2022 were also included. Patients were categorized into two groups: non-refractory shock and refractory shock. Statistical analysis was conducted on the data between the two groups.Results:This study included a total of 80 patients, with 37 experiencing non-refractory shock patients and 43 presenting with refractory shock patients. Significant differences were observed between the two groups in terms of sex distribution ( P=0.037) and the ingested amlodipine dose ( P=0.001). Through binary logistic regression analysis, the amlodipine dose was identified as an independent predictor of shock severity ( OR=1.43, 95% CI: 1.12-1.84, P=0.005). A subgroup analysis was performed on patients who were poisoned by ingesting amlodipine alone, further confirming the significant dose difference ( P=0.003) between the non-refractory shock and refractory shock categories. The area under the receiver operating characteristic curve (AUC) for predicting refractory shock in patients with amlodipine poisoning was 0.723 (95% CI: 0.613-0.833). The optimal cutoff dose for predicting refractory shock was 347.5 mg, with a sensitivity of 0.651 and a specificity of 0.784. Sensitivity analyses, excluding cases of mixed poisoning, yielded a higher AUC of 0.795 (95% CI: 0.634-0.956), with a slightly adjusted cutoff dose of 350 mg, a sensitivity of 0.867, and a specificity of 0.737. The dose-response relationship table between medication dosage and incidence of refractory shock shows that as the dosage increases, the proportion of refractory shock also increases. Conclusions:In adult patients with amlodipine poisoning, the severity of shock was correlated with the ingested dose of the drug. When the ingested amlodipine dose exceeds 347.5 mg, it is crucial to be cautious of the development of refractory shock.

This paper explored the specific mechanism of ginsenoside Rg_1 in regulating mitochondrial fusion through the neurogenic gene Notch homologous protein 1(Notch1) pathway to alleviate hypoxia/reoxygenation(H/R) injury in HL-1 cells. The relative viability of HL-1 cells after six hours of hypoxia and two hours of reoxygenation was detected by cell counting kit-8(CCK-8). The lactate dehydrogenase(LDH) activity in the cell supernatant was detected by the lactate substrate method. The content of adenosine triphosphate(ATP) was detected by the luciferin method. Fluorescence probes were used to detect intracellular reactive oxygen species(Cyto-ROS) levels and mitochondrial membrane potential(ΔΨ_m). Mito-Tracker and Actin were co-imaged to detect the number of mitochondria in cells. Fluorescence quantitative polymerase chain reaction and Western blot were used to detect the mRNA and protein expression levels of Notch1, mitochondrial fusion protein 2(Mfn2), and mitochondrial fusion protein 1(Mfn1). The results showed that compared with that of the control group, the cell activity of the model group decreased, and the LDH released into the cell culture supernatant increased. The level of Cyto-ROS increased, and the content of ATP decreased. Compared with that of the model group, the cell activity of the ginsenoside Rg_1 group increased, and the LDH released into the cell culture supernatant decreased. The level of Cyto-ROS decreased, and the ATP content increased. Ginsenoside Rg_1 elevated ΔΨ_m and increased mitochondrial quantity in HL-1 cells with H/R injury and had good protection for mitochondria. After H/R injury, the mRNA and protein expression levels of Notch1 and Mfn1 decreased, while the mRNA and protein expression levels of Mfn2 increased. Ginsenoside Rg_1 increased the mRNA and protein levels of Notch1 and Mfn1, and decreased the mRNA and protein levels of Mfn2. Silencing Notch1 inhibited the action of ginsenoside Rg_1, decreased the mRNA and protein levels of Notch1 and Mfn1, and increased the mRNA and protein levels of Mfn2. In summary, ginsenoside Rg_1 regulated mitochondrial fusion through the Notch1 pathway to alleviate H/R injury in HL-1 cells.
Ginsenosides/pharmacology* ; Receptor, Notch1/genetics* ; Signal Transduction/drug effects* ; Mice ; Animals ; Mitochondrial Dynamics/drug effects* ; Mitochondria/metabolism* ; Cell Line ; Reactive Oxygen Species/metabolism* ; Oxygen/metabolism* ; Cell Hypoxia/drug effects* ; Cell Survival/drug effects* ; Membrane Potential, Mitochondrial/drug effects* ; Humans

Traditional Chinese medicine(TCM) is the pillar for the development of motherland medicine, and animal medicine has a long history of application in China, characterized by wide resources, strong activity, definite efficacy, and great benefits. It has significant potential and important status in the consumption market of raw materials of TCM. In the context of global climate change, farming system alterations, and low renewability, the depletion of wild medicinal animal resources has accelerated. Accordingly, the conservation and sustainable utilization of wild resources of animal medicinal materials has become a problem that garners increasing attention and urgently needs to be solved. This paper summarizes the current situation of domestic and foreign medicinal animal breeding and research progress in industrial application in recent years and points out the issues related to standardized breeding, germplasm selection and breeding, and quality evaluation standards for medicinal animals. Furthermore, this paper discusses standardized breeding, quality standards, resource protection and utilization, and the search for alternative resources for rare and endangered medicinal animals. It proposes that researchers should systematically carry out in-depth basic research on animal medicine, improve the breeding scale and level of medicinal animals, employ modern technology to enhance the quality standards of medicinal materials, and strengthen the research and development of alternative resources. This approach aims to effectively address the relationship between protection and utilization and make a significant contribution to the sustainable development of medicinal animal resources and the animal-based Chinese medicinal material industry.
Animals ; Breeding ; China ; Medicine, Chinese Traditional ; Conservation of Natural Resources

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVE: To investigate the characteristics of central nervous system regulation in patients with refractory overactive bladder (rOAB) using resting-state functional magnetic resonance imaging (rs-fMRI), and to analyze the differences in brain function and connection between the patients and healthy population. METHODS: From May 1 to November 30, 2024, we performed rs-fMRI for 47 rOAB patients and another 47 matched healthy controls, documented relevant clinical data from all the participants and obtained their Overactive Bladder Symptom Scores (OABSS) and Overactive Bladder Questionnaire (OAB-Q) scores. Based on rs-fMRI, we compared the results of Independent Component Analysis (ICA), amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo) and degree centrality (DC) between the rOAB patients and healthy controls. RESULTS: The rOAB patients, in comparison with the healthy controls, showed dramatically higher daytime urination frequency (11.64 ± 3.85) vs (5.76 ± 0.91), nighttime urination frequency (3.72 ± 1.64) vs (0.31 ± 0.47), OABSS (8.22 ± 2.21) vs (0.64±0.78), OAB-Q1 score (20.85 ± 5.28) vs (6.78 ± 1.04), and OAB-Q2 score (45.04 ± 12.11) vs (14.51 ± 1.66) (all P<0.01). No statistically significant differences were observed in the results of ICA and ALFF between the right superior frontal and right middle frontal regions in the rOAB patients (P>0.05), but fALFF, ReHo and DC were significantly decreased in the patients compared with those in the healthy controls (P<0.01). CONCLUSION Compared with healthy population, the functions and connection of the frontal superior right and frontal middle right brain regions in rOAB patients are significantly down-regulated, which may serve as new therapeutic targets.
Humans ; Urinary Bladder, Overactive/physiopathology* ; Magnetic Resonance Imaging ; Brain/physiopathology* ; Female ; Male ; Adult ; Surveys and Questionnaires ; Case-Control Studies ; Middle Aged ; Rest ; Brain Mapping