ObjectiveBased on ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， network pharmacology and molecular docking techniques， to explore the pharmacodynamic material basis and mechanism of Renshen Wuweizi Tang in treating spleen-lung Qi deficiency syndrome. MethodsThe chemical components in the decoction of Renshen Wuweizi Tang were systematically characterized and identified by UPLC-Q-TOF-MS/MS， and network pharmacology was used to screen potential active ingredients， collect component targets and gene sets related to spleen-lung Qi deficiency syndrome， and obtain protein interaction relationships through STRING. Cytoscape 3.9.1 was used to construct a "formula-syndrome" association network and calculate topological feature values. Gene ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were performed on core genes to explore potential pharmacodynamic links， the average shortest path between the formula-drug target network and the pharmacodynamic link gene network was calculated to discover dominant pharmacodynamic links， and MCODE plugin was used to identify core gene clusters from the dominant pharmacodynamic links， which were validated using Gene Expression Omnibus（GEO）， and molecular docking was performed between key components and core targets. ResultsOne hundred and thirty-seven components were identified in the negative ion mode， and eighty components were identified in the positive ion mode. After deduplication， a total of 185 components were identified， mainly composed of triterpenoid saponins（49） and flavonoids（54）. Based on the "formula-syndrome" correlation network analysis， energy metabolism was determined to be the dominant pharmacodynamic link of Renshen Wuweizi Tang in the treatment of spleen-lung Qi deficiency syndrome. The results of molecular docking showed that 7 components（adenosine， atractylenolide Ⅱ， atractylenolide Ⅲ， ginsenoside Rg₁， glycyrrhizin B₂， glycyrrhizin E₂ and campesterol） from 4 medicinal materials（Ginseng Radix et Rhizoma， Atractylodis Macrocephalae Rhizoma， Glycyrrhizae Radix et Rhizoma and Poria） in this formula might regulate energy metabolism by acting on 6 targets， namely cyclic adenosine monophosphate-response element binding protein 1（CREB1）， glyceraldehyde-3-phosphate dehydrogenase（GAPDH）， interleukin（IL）-6， nuclear transcription factor（NF）-κB1， peroxisome proliferator-activated receptor α（PPARα）， and tumor necrosis factor（TNF）， thus improving the symptoms of diseases related to spleen-lung Qi deficiency syndrome. ConclusionThis study established a UPLC-Q-TOF-MS/MS for rapid characterization and identification of chemical components in the decoction of Renshen Wuweizi Tang， expanding the understanding of the material composition of this formula， and found that 7 components might act on the key advantageous pharmacodynamic link "energy metabolism" through 6 targets to improve the related symptoms of spleen-lung Qi deficiency syndrome. This can provide a reference for the subsequent exploration of the material benchmark and mechanism of the famous classical formula.

ObjectiveTo study the clinical features of viral encephalitis with isolated dizziness，and to analyze the diagnostic efficacy of vestibular function examination and cerebrospinal fluid cytology in these patients. MethodsTotally 37 cases of viral encephalitis with isolated dizziness and 10 healthy volunteers were included. Clinical data ［dizziness handicap inventory （DHI） score，head imaging，electroencephalogram，vestibular function test，cerebrospinal fluid routine，biochemistry，cell morphology，etiology second-generation sequencing，misdiagnosis］ were collected. The area under the ROC curve（AUC）of diagnostic value of each type of test was analyzed. The changes of each examination before and after treatment were compared. ResultsWe found 89.19%（33/37）of the patients were misdiagnosed. Vestibular function smooth follow-up test indicated vestibular central lesion （AUC value：0.82）in 64.86%（24/37）of the patients. The number of CSF transformed lymphocytes increased in 86.49%（32/37）of the patients（AUC value：0.93），the CSF large lymphocytes increased in 97.30% （36/37）of the patients （AUC value：0.99），and the mononucleosis was activated in 94.59%（35/37）of the patients（AUC value：0.97）. Furthermore，18.92%（7/37）of the patients had increased EEG slow wave（AUC value：0.60），while 13.51%（5/37） of the patients showed cortical swelling on head MR （AUC：0.60）. After antiviral treatment，dizziness grade decreased（Z=-4.899，P<0.001），smooth tracking abnormalities decreased（Z=-4.583，P<0.001），the proportion of CSF transformed lymphocytes decreased（t=4.281，P<0.001），and the proportion of large lymphocytes decreased（t=6.905，P<0.001）. ConclusionThe misdiagnosis rate of viral encephalitis with isolated dizziness is high. Incorporating into diagnosis the increased large lymphocytes， transformed lymphocytes，activated monocytes in CSF cytology with smooth follow-up test may improve diagnostic efficiency .

BACKGROUND:The sports medicine community has widely called for the use of machine learning technology to efficiently process the huge and complicated sports data resources,and construct intelligent sports injury prediction models,enabling accurate early warning of sports injuries.It is of great significance to comprehensively summarize and review such research results so as to grasp the direction of early warning model improvement and to guide the construction of sports injury prediction models in China. OBJECTIVE:To systematically review and analyze relevant research on sports injury prediction models based on machine learning technology,thereby providing references for the development of sports injury prediction models in China. METHODS:Literature search was conducted on CNKI,Web of Science and EBSCO databases,which mainly searched for literature related to machine learning techniques and sports injuries.Finally,61 articles related to sports injury prediction models were included for analysis. RESULTS AND CONCLUSION:(1)In terms of external risk feature indicators,there is a lack of competition scenario indicators,and the inclusion of related feature indicators needs to be further improved to further enrich the dimensions of the dataset for model training.In addition,the inclusion feature weighting methods of the sports injury prediction model are mainly based on filtering methods and the use of embedding and wrapping weighting methods needs to be strengthened in order to enhance the analysis of the interaction effects of multiple risk factors.(2)In terms of model body training,supervised learning algorithms become the mainstream choice.Such algorithms have higher requirements for the completeness of sample labeling information,and the application scenarios are easily limited.Therefore,the application of unsupervised and semi-supervised algorithms can be increased in the later stage.(3)In terms of model performance evaluation and optimization,the current studies mainly adopt two verification methods:HoldOut crossover and k-crossover.The range of AUC values is(0.76±0.12),the range of sensitivity is(75.92±11.03)%,the range of specificity is(0.03±4.54)%,the range of F1 score is(80.60±10.63)%,the range of accuracy is(69.96±13.10)%,and the range of precision is(70±14.71)%.Data augmentation and feature optimization are the most common model optimization operations.The accuracy and precision of the current sports injury prediction model are about 70%,and the early warning effect is good.However,the model optimization operation is relatively single,and data augmentation methods are often used to improve model performance.Further adjustments to the model algorithm and hyperparameters are needed to further improve model performance.(4)In terms of model feature extraction,most of the internal risk profile indicators included are mainly based on anthropometrics,training load,years of training,and injury history,but there is a lack of sports recovery and physical function indicators.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

OBJECTIVE: To determine risk factors for cutout failure in geriatric intertrochanteric fracture patients after cephalomedullary nail fixation. METHODS: A retrospective review of 518 elderly patients who underwent cephalomedullary nail fixation for intertrochanteric fractures between January 2008 and August 2018 was conducted, including 167 males and 351 females, age from 65 to 97 years old. All patients were followed up for at least one year after surgery and divided into a healed group and a cutout group based on whether the hip screw cutout occurred. Among all patients, 10 cases experienced hip screw cutout. The general information, surgical data, and radiological data of the two groups were compared, and risk factors influencing hip screw cutout were analyzed. Propensity score matching was then performed on the cutout group based on gender, age, body mass index(BMI), and American Society of Anesthesiologists(ASA), and 40 patients from the healed group were matched at a ratio of 1∶4. Key risk factors affecting hip screw cutout were further analyzed. Multivariable logistic regression analysis was conducted to evaluate associations between variables and cutout failure. RESULTS: There were no statistically significant differences between the healed group and the cutout group in terms of age, gender, BMI, ASA, and AO classification. However, statistically significant differences were observed between the two groups in terms of reduction quality(P=0.003) and tip-apex distance(TAD), P<0.001. Multivariate analysis identified poor reduction quality OR=23.138, 95%CI(2.163, 247.551), P=0.009 and TAD≥25 mm OR=30.538, 95%CI(2.935, 317.770), P=0.004 as independent risk factors for cutout failure. CONCLUSION The present study identified poor reduction quality and TAD≥25 mm as factors for cutout failure in geriatric intertrochanteric fractures treated with cephalomedullary nails. Further studies are needed to calculate the optimal TAD for cephalomedullary nails.
Humans ; Male ; Female ; Hip Fractures/surgery* ; Aged, 80 and over ; Aged ; Risk Factors ; Retrospective Studies ; Fracture Fixation, Intramedullary/adverse effects* ; Bone Nails ; Bone Screws

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Insulin-like growth factor 2 (IGF2) is a critical endocrine mediator implicated in male reproductive physiology. To investigate the correlation between IGF2 protein levels and various aspects of male infertility, specifically focusing on sperm quality, inflammation, and DNA damage, a cohort of 320 male participants was recruited from the Women's Hospital, Zhejiang University School of Medicine (Hangzhou, China) between 1 st January 2024 and 1 st March 2024. The relationship between IGF2 protein concentrations and sperm parameters was assessed, and Spearman correlation and linear regression analysis were employed to evaluate the independent associations between IGF2 protein levels and risk factors for infertility. Enzyme-linked immunosorbent assay (ELISA) was used to measure IGF2 protein levels in seminal plasma, alongside markers of inflammation (tumor necrosis factor-alpha [TNF-α] and interleukin-1β [IL-1β]). The relationship between seminal plasma IGF2 protein levels and DNA damage marker phosphorylated histone H2AX (γ-H2AX) was also explored. Our findings reveal that IGF2 protein expression decreased notably in patients with asthenospermia and teratospermia. Correlation analysis revealed nuanced associations between IGF2 protein levels and specific sperm parameters, and low IGF2 protein concentrations correlated with increased inflammation and DNA damage in sperm. The observed correlations between IGF2 protein levels and specific sperm parameters, along with its connection to inflammation and DNA damage, underscore the importance of IGF2 in the broader context of male reproductive health. These findings lay the groundwork for future research and potential therapeutic interventions targeting IGF2-related pathways to enhance male fertility.
Humans ; Male ; Insulin-Like Growth Factor II/metabolism* ; Infertility, Male/genetics* ; DNA Damage ; Adult ; Inflammation/metabolism* ; Spermatozoa/metabolism* ; Semen Analysis ; Semen/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Histones/metabolism* ; Interleukin-1beta/metabolism*

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*

BACKGROUND: Chronic kidney disease (CKD) is associated with common pathophysiological processes, such as inflammation and fibrosis, in both the heart and the kidney. However, the underlying molecular mechanisms that drive these processes are not yet fully understood. Therefore, this study focused on the molecular mechanism of heart and kidney injury in CKD. METHODS: We generated an microRNA (miR)-26a knockout (KO) mouse model to investigate the role of miR-26a in angiotensin (Ang)-II-induced cardiac and renal injury. We performed Ang-II modeling in wild type (WT) mice and miR-26a KO mice, with six mice in each group. In addition, Ang-II-treated AC16 cells and HK2 cells were used as in vitro models of cardiac and renal injury in the context of CKD. Histological staining, immunohistochemistry, quantitative real-time polymerase chain reaction (PCR), and Western blotting were applied to study the regulation of miR-26a on Ang-II-induced cardiac and renal injury. Immunofluorescence reporter assays were used to detect downstream genes of miR-26a, and immunoprecipitation was employed to identify the interacting protein of LIM and senescent cell antigen-like domain 1 (LIMS1). We also used an adeno-associated virus (AAV) to supplement LIMS1 and explored the specific regulatory mechanism of miR-26a on Ang-II-induced cardiac and renal injury. Dunnett's multiple comparison and t -test were used to analyze the data. RESULTS: Compared with the control mice, miR-26a expression was significantly downregulated in both the kidney and the heart after Ang-II infusion. Our study identified LIMS1 as a novel target gene of miR-26a in both heart and kidney tissues. Downregulation of miR-26a activated the LIMS1/integrin-linked kinase (ILK) signaling pathway in the heart and kidney, which represents a common molecular mechanism underlying inflammation and fibrosis in heart and kidney tissues during CKD. Furthermore, knockout of miR-26a worsened inflammation and fibrosis in the heart and kidney by inhibiting the LIMS1/ILK signaling pathway; on the contrary, supplementation with exogenous miR-26a reversed all these changes. CONCLUSIONS Our findings suggest that miR-26a could be a promising therapeutic target for the treatment of cardiorenal injury in CKD. This is attributed to its ability to regulate the LIMS1/ILK signaling pathway, which represents a common molecular mechanism in both heart and kidney tissues.
Animals ; MicroRNAs/metabolism* ; Angiotensin II/toxicity* ; Mice ; Renal Insufficiency, Chronic/chemically induced* ; Mice, Knockout ; Disease Models, Animal ; Male ; Signal Transduction/genetics* ; LIM Domain Proteins/genetics* ; Mice, Inbred C57BL ; Cell Line ; Humans