Anemarrhenae Rhizoma is bitter, sweet, and cold in nature, and has the effects of clearing heat, dispelling fire, nourishing Yin, and moisturizing dryness. It is associated with the lung, stomach, and kidney meridians, and is mainly distributed in the northwestern and northern regions of China. Modern research has shown that Anemarrhenae Rhizoma contains various chemical active constituents, including steroidal saponins, flavonoids, polysaccharides, lignans, volatile oils, and alkaloids. These constituents exhibit pharmacological effects such as anti-tumor, hypoglycemic, anti-inflammatory, and neuroprotective activities. However, there have been few comprehensive summaries of Anemarrhenae Rhizoma in recent years, which has limited its in-depth research and development. The complexity of traditional Chinese medicine constituents, along with their quality and efficacy, is easily influenced by processing, preparation, and the growing environment and resource distribution. This paper summarizes the resources, chemical constituents, and pharmacological effects of Anemarrhenae Rhizoma, and predicts its quality markers(Q-markers) from several aspects, including the specificity of chemical composition, properties related to preparation and active ingredients, measurability of chemical components, compounding environment, construction of the ″active ingredient-target″ network pathway, and differences in active ingredient content from different origins and parts. These predicted Q-markers may provide a basis for improving the quality evaluation system of Anemarrhenae Rhizoma.
Anemarrhena/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Rhizome/chemistry* ; Humans ; Animals ; Quality Control

OBJECTIVE: To explore prevalence, incidence and possible factors of immediate herniated discs after posterior cervical expansive open-door laminoplasty (EODL). METHODS: Totally 29 patients with cervical spinal stenosis and intervertebral disc herniation who underwent EODL from October 2020 to December 2021 were collected, including 24 males and 5 females, aged from 43 to 81 years old with an average of (61.3±9.0) years old;the courses of disease ranged from 1 to 120 months with an average of (36.4±37.0) months. Three or more intervertebral discs on C₃-C₇ were observed. The clinical efficacy was evaluated according to Japanese Orthopaedic Association (JOA) score before operation, 3 days and 1, 3, 6 and 12 months after operation, respectively. The changes of herniated disc before and after operation were measured by multipoint area method and two-dimensional distance method, and incidence and percentage of herniated disc regression were further calculated. Cervical imaging parameters such as Cobb angle (C₃-C₇), intervertebral angle, T₁ slope (T₁S), spinal canal sagittal diameter, K-line angle, dural sac sagittal diameter were measured and compared before and after operation. Pearson correlation was used to analyze correlation between cervical sagittal imaging parameters and disc herniation changes before and after operation. RESULTS: All patients obtained grade A wound healing, and 14 of them were followed up for 3(1.00, 5.25) months. There were no immediate or long-term postoperative complications. Totally 101 herniated intervertebral discs were measured, of which 79 regression numbers were obtained by area measurement. The number of intervertebral disc regressions by distance measurement was 77. There was no statistically significant difference in Cobb angle, intervertebral angle, T₁S and K-line angle of C₃-C₇ (P>0.05), however, there were statistically significant differences in sagittal diameter of spinal canal, sagittal diameter of dural sac, and JOA score before and after operation(P<0.05). The regression ratio of disc herniation ranged from 5% to 50%, and regression ratio of disc herniation was greater than 25% in 45.57%(36/79). Disc herniation in C_4,5 was positively correlated with sagittal plane diameter in C₅(r=0.423, P=0.028). There was a negative correlation between changes of C_3,4 and C_3,4 intervertebral angle (r=-0.450, P=0.041). The improvement rate of cervical JOA score immediately after operation was (59.54±15.07) %, and postoperative follow-up improved to (76.57±14.66) %. CONCLUSION Herniated disc regression immediately after EODL is a common occurrence, and EODL should be selected as far as possible under the premise of satisfying surgical indications. The regression of disc herniation is positively correlated with spinal canal sagittal diameter, and spinal canal should be enlarged as far as possible in the appropriate scope during EODL, so as to create more opportunities and conditions for disc regression and achieve better clinical results.
Humans ; Female ; Male ; Intervertebral Disc Displacement/diagnostic imaging* ; Spinal Stenosis/diagnostic imaging* ; Laminoplasty/methods* ; Middle Aged ; Aged ; Cervical Vertebrae/diagnostic imaging* ; Adult ; Aged, 80 and over ; Intervertebral Disc/surgery*

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

Background Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants widely distributed in the environment. Epidemiological studies have shown that PFAS exposure is closely associated with liver dysfunction and an increased risk of liver cancer. Some animal and cell experiments have also revealed its hepatotoxicity and potential carcinogenicity; however, the related carcinogenic mechanism has not yet been fully elucidated. Objective To explore the potential molecular mechanism of PFAS-induced liver cancer, identify the key causal genes, and specifically evaluate the causal association and expression changes of KMT2C in this process, as well as the binding stability between KMT2C and PFAS, and to provid a theoretical basis for mechanistic studies and molecular target discovery in PFAS-related liver cancer. Methods Toxicity prediction was performed on six representative PFAS. Potential target genes of PFAS were identified by integrating results from SwissTargetPrediction, STITCH, and TargetNet databases. Liver cancer-related genes were retrieved from GeneCards, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). The intersection of PFAS targets and liver cancer-related genes was used to obtain core genes. A compound-gene-disease regulatory network was constructed, and a protein–protein interaction network was established using STRING database. A core gene network was visualized based on node degree values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore biological functions and enriched signaling pathways. Subsequently, two-sample Mendelian randomization was employed to assess potential causal relationships between candidate genes and hepatocellular carcinoma, enabling the identification of key genes. Molecular docking analysis using AutoDock was conducted to evaluate the binding stability between KMT2C and PFAS, and TCGA data were used to validate the differential expression of KMT2C between hepatocellular carcinoma and adjacent normal tissues. Results PFAS exhibited multisystem toxicity and posed significant risks of liver injury and carcinogenesis. A total of 266 PFAS target genes and 2923 liver cancer-related genes were identified, with 61 intersecting genes obtained. The enrichment analysis revealed that these intersecting genes were primarily involved in epigenetic regulation, nuclear receptor signaling pathways, and apoptosis-related pathways including TGF-β FoxO and Notch, suggesting their roles in diverse tumor-related biological processes. The two-sample Mendelian randomization results showed a significant negative causal association between KMT2C and hepatocellular carcinoma (OR=0.68, P <0.05). The molecular docking results demonstrated that all tested PFAS exhibited favorable binding to the KMT2C protein, with binding energies below –5.0 kcal·mol⁻¹. KMT2C was significantly upregulated in hepatocellular carcinoma tissues (unpaired P=0.025; paired P=8.38 × 10⁻⁴). Conclusion The KMT2C protein is found to stably bind with all six PFAS, exhibiting strong structural affinity. A causal relationship is identified between KMT2C and the development of hepatocellular carcinoma. TCGA data indicate that KMT2C is significantly upregulated in hepatocellular carcinoma tissues, and it may serve as a key regulatory target in PFAS-related liver cancer.

Objective To explore the risk factors for 28-day mortality of sepsis-associated acute kidney injury(SA-AKI)patients and to develop a nomogram risk prediction model.Methods A retrospective cohort study was conducted,involving 184 patients with SA-AKI admitted to the intensive care unit(ICU)of the 940th Hospital of Joint Logistic Support Force of PLA between January 2017 and December 2022.Patients were categorized into survival(n=135)and non-survival(n=49)groups based on 28-day mortality.Clinical data were collected,and statistically significant risk factors were preliminarily screened.Multivariate stepwise logistic regression analysis was performed to identify independent risk factors for 28-day mortality of SA-AKI patients.A nomogram predictive model was constructed using these factors,and internally validated with the Bootstrap method.The receiver operating characteristic curve(ROC curve)was drawn,and the area under the ROC curve(AUC)was calculated to verify the predictive value and accuracy of the model.Results The 28-day mortality rate among 184 SA-AKI patients was 26.6％(49/184).Multivariate stepwise logistic regression analysis identified multiple organ dysfunction syndrome(MODS)(OR=16.393,95％CI 4.317-62.254,P＜0.001),high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(OR=1.097,95％CI 1.036-1.161,P=0.002),low oxygenation index(OR=0.992,95％CI 0.986-0.998,P=0.015),low neutrophil count(OR=0.912,95％CI 0.860-0.968,P=0.002)and low fibrinogen concentration(OR=0.733,95％CI 0.549-0.978,P=0.034)as independent risk factors.The prediction model equation was P=1/1+e-logit(P),logit(P)=-1.626+2.797×MODS+0.092×AP ACHE Ⅱ+(-0.311)×fibrinogen+(-0.092)×neutrophil count+(-0.008)×oxygenation index.Internal validation with 1000 Bootstrap resamples showed high consistency between predicted and actual values.ROC analysis showed an AUC of 0.911(95％CI 0.868-0.955,P＜0.05)for the model,with 93.9％sensitivity and 78.5％specificity at a cut-off of 0.194.The Hosmer-Lemeshow test confirmed good calibration(P=0.62),and decision-making curve analysis demonstrated clinical utility within the high-risk threshold range(0.1-0.9).Conclusions MODS,high APACHE Ⅱ score,low oxygenation index,low neutrophil count,and low fibrinogen concentration are independent risk factors for 28-day mortality in SA-AKI patients.The developed nomogram risk prediction model may provide important guidance for predicting 28-day mortality in SA-AKI patients.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.

Objective Human papillomavirus(HPV)is a detriment virus to human health,because it can cause malignant tumors.HPV vaccine has been developed and plays an important role in preventing a range of diseases caused by HPV.HPV vaccine as a primary prevention measure,has demonstrated excellent protective efficacy and safety in preventing HPV-related infection and cervical cancer.This article summarizes the application of preventive HPV vaccine and its safety,and provides reference for the widespread vaccination of HPV vaccine in China.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.