Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

As one of the chronic diseases with high incidence in contemporary society, cervical spondylosis has increasing patient groups who gradually present a low age, and it seriously affects social and public health. Although modern medicine has made great progress in the pathological research and clinical treatment of cervical spondylosis, patients still face gastrointestinal side effects of nonsteroidal anti-inflammatory drugs(NSAIDs), neck pain, limited mobility, upper limb numbness, and other symptoms after conservative or surgical treatment. In the theory of traditional Chinese medicine(TCM), cervical spondylosis belongs to the categories of "Bi syndrome" "stiff neck" "stiff Bi", etc. With the change of the times, the change of lifestyle, and the application of western medicine treatment, the etiology and pathogenesis of TCM in cervical spondylosis also show new characteristics. In terms of etiology and pathogenesis, it involves the invasion of wind, cold, and dampness, long-term strain, liver and kidney deficiency, Qi and blood stasis, which are associated with factors such as cervical degeneration, muscle tension and spasm, intervertebral disc herniation, and nerve root compression in modern medicine. In terms of the evolution of pathogenesis, in the early stage, wind, cold, and dampness, were more common in Xuanfu, resulting in unfavorable muscles and bones, poor flow of Qi and blood, and cervical spondylosis and radiculopathy. Medium-term phlegm stasis and internal knots, sluggish muscles and veins, and long-term weathering and fire are more likely to occur in the vertebral artery and sympathetic radiculopathy. In the later stage, the positive Qi is depleted; the true Yin is damaged, and the viscera Qi and blood are deficient, which is most common in cervical myelopathy. The strategy of treating cervical spondylosis with TCM classic formulas applies Gegen Decoction, Wutou Decoction, Qianghuo Shengshi Decoction, Mahuang Jiazhu Decoction to patients with wind, cold, and dampness. Patients with phlegm dampness and blood stasis are treated with Huoxue Xiaoling Dan, Jinlingzi Powder, Siwu Decoction, Banxia Baizhu Tianma Decoction, Shuanghe Decoction, etc. For those patients with liver, spleen, and kidney deficiency, Huangqi Guizhi Wuwu Decoction, Tianma Gouteng Decoction, Guishao Dihuang Pills, Shenling Baizhu Powder, and Lizhong Decoction are used to invigorate the spleen, nourish Qi and blood, and tonify liver and kidney. In clinical practice, the authors advocate a safe and effective treatment plan of classic formulas based on deficiency and excess, the integration of formulas and syndromes, and the combination of modern research results, so as to relieve symptoms, reduce recurrence, and reduce medical burden.
Humans ; Spondylosis/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Cervical Vertebrae/pathology*

OBJECTIVE: To explore the therapeutic effect of polygonum cuspidatum glycoside on steroid-induced osteonecrosis of the femoral head(SONFH) in rats and its potential mechanism of protecting bone tissue by regulating the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway(JAK2/STAT3). METHODS: Fifty male SD rats were randomly divided into control group, model group, low-dose polygonum cuspidatum glycoside group (polygonum cuspidatum glycoside-L), high-dose polygonum cuspidatum glycoside group (polygonum cuspidatum glycoside-H), and polygonum cuspidatum glycoside-H+Colivelin (JAK2/STAT3 pathway activator) group. SONFH model was induced by lipopolysaccharide and dexamethasone. The treatment groups were given polygonum cuspidatum glycoside orally(polygonum cuspidatum glycoside-L 10 mg·kg^-1, polygonum cuspidatum glycoside-H 20 mg·kg^-1, and the polygonum cuspidatum glycoside-H+Colivelin group was injected with Colivelin (1 mg·kg^-1) intraperitoneally once a day, while the control and model groups were given an equal volume of saline for 6 weeks. The observed indicators included serum calcium(Ca), serum phosphorus (P), alkaline phosphatase, and transforming growth factor β1(TGF-β1) levels, micro-CT scanning, hematoxylin-eosin staining, and Western blot detection of JAK2/STAT3 signaling pathway and osteogenic differentiation marker genes, including Runt-related transcription factor 2 (Runx2), bone morphogenetic protein 2 (BMP2), and osteopontin (OPN) protein expression. RESULTS: Compared with the model group, the trabecular bone area percentage in the polygonum cuspidatum glycoside-L and polygonum cuspidatum glycoside-H groups was significantly increased, and the empty lacunar rate was significantly decreased (P<0.05). Micro-CT analysis showed that the bone volume fraction, trabecular number, and thickness increased, and the trabecular separation decreased in the polygonum cuspidatum glycoside-treated groups(P<0.05). Serum biochemical tests found that the serum Ca and P concentrations in the polygonum cuspidatum glycoside-L and polygonum cuspidatum glycoside-H groups were restored, the alkaline phosphatase levels decreased, and the transforming growth factor β1 levels increased (P<0.05). Western blot analysis showed that polygonum cuspidatum glycoside significantly inhibited the activation of the JAK2/STAT3 signaling pathway in the model group and promoted the expression of osteogenic differentiation marker genes such as Runx2, BMP2, and OPN (P<0.05). Compared with the polygonum cuspidatum glycoside-H group, the improvements in the polygonum cuspidatum glycoside-H+Colivelin group were somewhat weakened, indicating the importance of the JAK2/STAT3 signaling pathway in the action of polygonum cuspidatum glycoside. CONCLUSION polygonum cuspidatum glycoside promotes osteogenic differentiation, improves bone microstructure, and has significant therapeutic effects on rat SONFH by regulating the JAK2/STAT3 signaling pathway.
Animals ; Male ; Janus Kinase 2/physiology* ; Rats, Sprague-Dawley ; Rats ; Signal Transduction/drug effects* ; Glucosides/pharmacology* ; STAT3 Transcription Factor/genetics* ; Femur Head Necrosis/chemically induced* ; Stilbenes/pharmacology*

This study explores whether the current external quality assessment (EQA) level and acceptable bias for basic semen analysis in China are clinically useful. We collected data of semen EQA from Andrology laboratories in the Hunan Province (China) in 2022 and searched for data in the published literature from January 2000 to December 2023 in China. On the basis of these data, we analyzed the coefficients of variation and acceptable biases of different quality control materials for basic semen analysis through robust statistics. We compared these findings with quality specifications based on biological variation from optimal, desirable, and minimum levels of bias to seek a unified and more suitable semen EQA bias evaluation standard for China's national conditions. Different sources of semen quality control material exhibited considerable variation in acceptable biases among laboratories, ranging from 8.2% to 56.9%. A total of 50.0% of the laboratories met the minimum quality specifications for progressive motility (PR), whereas 100.0% and 75.0% of laboratories met only the minimum quality specifications for sperm concentration and total motility (nonprogressive [NP] + PR), respectively. The Z value for sperm concentration and PR+NP was equivalent to the desirable performance specification, whereas the Z value for PR was equivalent only to the minimum performance specification. This study highlights the feasibility of operating external quality assessment schemes for basic semen analysis using quality specifications based on biological variation. These specifications should be unified among external quality control (EQC) centers based on biological variation.
Semen Analysis/standards* ; Humans ; China ; Male ; Quality Control ; Sperm Motility ; Sperm Count/standards*

Purpose To investigate the role of ultrasound-guided fine needle aspiration cytology(US-FNAC)in the diagnosis of breast cancer.Methods Fine needle aspiration cytology(FNAC)samples of 203 patients with breast cancer were selected and prepared by liquid-based cytology.The results of histopathology after neoadjuvant therapy were used as the gold standard to compare with the diagnostic results of FNAC samples,and then evaluated the diagnos-tic coincidence rate of FNAC samples.Results Of 203 axillary lymph node FNAC samples,111 cases were diagnosed as positive,38 cases were diagnosed as suspicious for positivity,and 54 cases were diagnosed as negative.The diag-nostic accuracy of FNAC was 85.2％,the sensitivity of FNAC was 98.0％,and the specificity of FNAC was 90.0％.Conclusion FNAC has high sensitivity and accuracy in the diagnosis of axillary lymph node metastasis.Sentinel lymph node biopsy is recommended for patients with negative FNAC but clinically and radiographically suspected lymph node metastasis.

Objective To translate Evidence-Informed Decision-Making Competence Measure for Chinese nurses and test its validity and reliability.Methods A research group was set up to use the Brislin translation model to translate the original scale into Chinese,and the back translation,cross-cultural adaptation,pre-experiment and cognitive interview were conducted to finally form the Chinese version of the Evidence-Informed Decision-Making Competence Measure for nurses.A total of 1 247 nurses from 7 tertiary A hospitals in Beijing,Hubei,Hunan and Xinjiang were selected by convenience sampling method in April 2024 to test its reliability and validity.Results 1 026 effective question-naires were collected,with an effective recovery rate of 82.28％.The Chinese version of the Evidence-Informed Decision-Making Competence Measure included 25 items,including knowledge/skill,attitude and behavior.A total of 3 common factors were extracted from exploratory factor analysis,and the cumulative variance contribution rate was 91.725％.The content validity index at the item level was 0.83-1.00;the content validity index at the scale level was 0.988;the calibration association validity was 0.496.The Cronbach's α coefficient of the whole scale was 0.992;the half-point reliability was 0.930;the retest reliability was 0.927.Conclusion The Chinese version of Evidence-Informed Decision-Making Competence Measure for nurses has good reliability and validity,and it can be used to evaluate the evidence-informed decision-making competence of Chinese nurses,provide references for promoting evidence-based nursing practice and evidence-informed decision-making.

Objective To translate Evidence-Informed Decision-Making Competence Measure for Chinese nurses and test its validity and reliability.Methods A research group was set up to use the Brislin translation model to translate the original scale into Chinese,and the back translation,cross-cultural adaptation,pre-experiment and cognitive interview were conducted to finally form the Chinese version of the Evidence-Informed Decision-Making Competence Measure for nurses.A total of 1 247 nurses from 7 tertiary A hospitals in Beijing,Hubei,Hunan and Xinjiang were selected by convenience sampling method in April 2024 to test its reliability and validity.Results 1 026 effective question-naires were collected,with an effective recovery rate of 82.28％.The Chinese version of the Evidence-Informed Decision-Making Competence Measure included 25 items,including knowledge/skill,attitude and behavior.A total of 3 common factors were extracted from exploratory factor analysis,and the cumulative variance contribution rate was 91.725％.The content validity index at the item level was 0.83-1.00;the content validity index at the scale level was 0.988;the calibration association validity was 0.496.The Cronbach's α coefficient of the whole scale was 0.992;the half-point reliability was 0.930;the retest reliability was 0.927.Conclusion The Chinese version of Evidence-Informed Decision-Making Competence Measure for nurses has good reliability and validity,and it can be used to evaluate the evidence-informed decision-making competence of Chinese nurses,provide references for promoting evidence-based nursing practice and evidence-informed decision-making.

Objective To explore the predictive value of fat attenuation index(FAI)and fibrous plaque index(FPI)for the prognosis of patients with acute coronary syndrome(ACS).Methods A retrospective cohort study was conducted on 334 ACS patients undergoing percutaneous coronary intervention(PCI)in the First Affiliated Hospital of Army Military Medical University and Yongchuan Hospital of Chongqing Medical University from March 2021 to July 2023.All patients received coronary computed tomography angiography(CCTA)to measure FAI and FPI.According to the occurrence of major adverse cardiovascular events(MACE)with 1 year of follow-up,they were divided into MACE group(n=108)and non-MACE group(n=226).The baseline data,CCTA data and results of laboratory tests were collected and compared between the 2 groups.Multivariate logistic regression analysis was used to analyze the relationship of FAI and FPI with the prognosis of ACS patients,and ROC curve was drawn to evaluate its predictive efficiency.Results Among the 334 ACS patients,108(32.34%)experienced MACE.When compared with the non-MACE group,the MACE group exhibited significantly larger proportions of diabetes(72.22%vs 31.86%)and left main coronary artery disease(18.52%vs 7.08%),but lower success rate of operation(79.63%vs 93.81%,P<0.05).Radiologic results showed that the proportion of severe stenosis(20.37%vs 10.62%),FAI(-80.12±6.41 HU vs-72.34±7.09 HU)and FPI(0.58±0.41 vs 0.26±0.12)were obviously increased in the MACE group than the non-MACE group(P<0.05).Laboratory tests indicated that there were statistical differences between the 2 groups in high-density lipoprotein-cholesterol(HDL-C,1.20±0.15 vs 1.09±0.16 mmol/L),miR-126(0.91±0.12 vs 0.96±0.15)and SST2(38.45±5.67 vs 34.30±4.89 ng/mL,P<0.05).Multivariate Logistic regression analysis revealed that FAI(OR=1.200,95%CI:1.136～1.268),FPI(OR=63.157,95%CI:14.126～282.374),moderate stenosis(OR=1.332,95%CI:1.024～1.859),severe stenosis(OR=1.480,95%CI:1.074～2.039),miR-126(OR=0.007,95%CI:0.001～0.077),and sST2(OR=1.192,95%CI:1.113～1.277)were independent predictors of MACE(P<0.05).ROC curve analysis displayed that stenosis degree(AUC=0.622,95%CI:0.561～0.683,P=0.001),FAI(AUC=0.790,95%CI:0.741～0.839,P=0.001)and FPI(AUC=0.700,95%CI:0.638～0.761,P=0.001),miR-126(AUC=0.646,95%CI:0.584～0.707,P=0.001),sST2(AUC=0.700,95%CI:0.638～0.761,P=0.001)had certain predictive values for ACS prognosis.Conclusion Coronary FAI and FPI can be used as independent prognostic indicators of ACS patients,and their numerical changes are closely related to plaque stability and inflammatory state.