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 discuss the influencing factors of angina pectoris in the patients with diabetes mellitus(DM),to construct a Bayesian network model to explore the network relationships among the influencing factors,and to predict the risk of angina pectoris in the patients with DM.Methods:Based on the UK Biobank(UKB)database,the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM.The taboo search algorithm was used for structure learning,and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model.Results:A total of 22 712 DM patients were included.The influencing factors of angina pectoris in the patients with DM included 14 variables:gender,age,body mass index(BMI),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HbA1c),hypertension,maternal smoking around delivery,smoking status,alcohol consumption,regular exercise,insomnia,sleep duration,and childhood relative body size(P<0.05).A Bayesian network model was constructed with 15 nodes and 22 directed edges.Among them,age,HbA1c,hypertension,regular exercise,BMI,and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM,while gender,smoking status,alcohol consumption,TC,TG,insomnia,childhood relative body size,and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM.Conclusion:Age,HbA1c,hypertension,regular exercise,BMI,and sleep duration are direct influencing factors of angina pectoris in the patients with DM.Controlling HbA1c,blood pressure,and BMI levels,engaging in regular exercise,and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Objective:To explore the therapeutic effect of compound Kuijie Ankang Decoction on ulcerative colitis (UC) model mice by non targeted metabonomics; To explore its mechanism.Compound Kuijie Ankang.Methods:The mice were randomly divided into blank control group, model group, Kuijie Ankang Decoction group and sulfasalazine group, with 12 mice in each group. Except the blank control group, the other groups were given 1.5% DSS solution for free drinking to prepare UC model. After successful modeling, Kuijie Ankang Decoction group was intragastrically administered with compound Kuijie Ankang Decoction of 9.68 g/kg, sulfasalazine group was intragastrically administered with sulfasalazine capsule suspension of 320 mg/kg, model group and blank control group were intragastrically administered with equal volume of purified water, once a day, for 7 consecutive days. The body mass and disease activity index (DAI) score of mice were measured. ELISA was used to measure the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-10 (IL-10) in the colon tissue of mice; the protein expressions of Claudin-1 and Zo-1 in colon tissue were detected by immunofluorescence method. HE staining was used to observe the pathological changes in the colon, and UHPLC-OE-MS technology was used to analyze the endogenous metabolite structure of mouse colon tissue, differential metabolites and related metabolic pathways were screened.Results:Compared with the model group, the colon length in Kuijie Ankang Decoction group and sulfasalazine group increased ( P<0.01), the DAI score decreased ( P<0.01), the levels of TNF-α, IL-1β and IL-6 in colon tissue decreased ( P<0.01), the level of IL-10 increased ( P<0.01), and the average optical density of Claudin-1 and Zo-1 protein increased ( P<0.01 or P<0.05). Metabolomics analysis identified 26 potential differential metabolites, including nicotinamide adenine dinucleotide, guanine, gamma aminobutyric acid, and thiamine, affecting 26 key metabolic pathways, including lysine biosynthesis, thiamine metabolism, cysteine and methionine metabolism. Conclusion:Kuaijie Ankang Decoction may improve metabolites such as Gamma aminobutyric acid and thiamine through metabolic pathways such as lysine biosynthesis to alleviate inflammatory reactions, thereby exerting therapeutic effects on ulcerative colitis in mice.

Objective To investigate the mechanism of Kuijie Ankang Decoction in regulating immune,autophagy and intestinal flora in the treatment of ulcerative colitis(UC).Methods UC mouse model was established by free drinking with sodium dextran sulfate.The mice were randomly divided into blank control group,model group,Kuijie Ankang Decoction group,salazine sulfopyridine(SASP)group and 3-methyladenine(3-MA)group,with 12 mice in each group.Each drug group was given corresponding drugs for gavage,the blank control group and model group were given the same volume of distilled water for gavage for 7 days.The general condition of mice was observed and the disease activity index(DAI)was scored,the morphology of colon tissue was observed by HE staining,the contents of TNF-α,IL-1β,IL-6,IL-8 and IL-10 in colon tissue were detected by ELISA,the mRNA and protein expressions of LC3,Beclin-1 and p62 in colon tissue were detected by RT-qPCR and Western blot,respectively.16S rDNA sequencing was used to analyze the structure of intestinal flora.Results Compared with the blank control group,the mice in the model group showed a decrease in body mass,an increase in DAI score,a decrease in colon length,serious mucosal injury and inflammatory cell infiltration,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue significantly increased(P<0.05,P<0.01),the content of IL-10 decreased(P<0.01),the mRNA expressions of LC3 and Beclin-1 in colon tissue decreased(P<0.05,P<0.01),the mRNA and protein expression of p62 increased(P<0.01),while the expressions of LC3Ⅱ/LC3Ⅰ and Beclin-1 proteins decreased(P<0.05,P<0.01).Compared with the model group,the body mass of mice in Kuijie Ankang Decoction group and SASP group increased(P<0.05),DAI score decreased(P<0.05),the colon length increased(P<0.05),the pathological damage of colon mucosa was alleviated,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue decreased(P<0.05,P<0.01),the content of IL-10 increased(P<0.01),the expressions of LC3 and Beclin-1 mRNA in colon tissue increased(P<0.05,P<0.01),the expression of p62 mRNA and protein decreased(P<0.05,P<0.01),the expressions of LC3Ⅱ/LC3Ⅰand Beclin-1 protein increased(P<0.05,P<0.01).16S rDNA sequencing results showed that the diversity and evenness of the intestinal flora in the model group mice decreased,with a decrease in the relative abundance of Firmicutes,Actinobacteria and Patescibacteria(P<0.05),and an increase in the relative abundance of Bacteroidota,Verrucomicrobiota and Proteobacteria(P<0.05);the relative abundance of Bacilli and Coriobacteriia decreased(P<0.05),the relative abundance of Bacteroidia,Clostridia and Verrucomicrobiae increased(P<0.05);the relative abundance of Ligilactobacillus and Dubosiella decreased(P<0.05),the relative abundance of unclassified Muribaculaceae,Lachnospiraceae NK4A136_group,Akkermansia and unclassified Lachnospiraceae increased(P<0.05).Compared with the model group,the diversity and evenness of intestinal flora increased in Kuijie Ankang Decoction group and SASP group,with an increase in the relative abundance of Firmicutes(P<0.05),a decrease in the relative abundance of Bacteroidota and Verrucomicrobiota(P<0.05),the relative abundance of Bacteroidia and Bacilli increased(P<0.05),the relative abundance of Verrucomicrobiae decreased(P<0.05);the relative abundance of unclassified Muribaculaceae and Ligilactobacillus increased(P<0.05),while the relative abundance of Lachnospiraceae NK4A136_group and Akkermansia decreased(P<0.05).Conclusion Kuijie Ankang Decoction can significantly improve the intestinal mucosal injury of UC mice,and the mechanism may be related to the regulation of colon autophagy level and intestinal flora disorder.

Objective To investigate the mechanism of Kuijie Ankang Decoction in regulating immune,autophagy and intestinal flora in the treatment of ulcerative colitis(UC).Methods UC mouse model was established by free drinking with sodium dextran sulfate.The mice were randomly divided into blank control group,model group,Kuijie Ankang Decoction group,salazine sulfopyridine(SASP)group and 3-methyladenine(3-MA)group,with 12 mice in each group.Each drug group was given corresponding drugs for gavage,the blank control group and model group were given the same volume of distilled water for gavage for 7 days.The general condition of mice was observed and the disease activity index(DAI)was scored,the morphology of colon tissue was observed by HE staining,the contents of TNF-α,IL-1β,IL-6,IL-8 and IL-10 in colon tissue were detected by ELISA,the mRNA and protein expressions of LC3,Beclin-1 and p62 in colon tissue were detected by RT-qPCR and Western blot,respectively.16S rDNA sequencing was used to analyze the structure of intestinal flora.Results Compared with the blank control group,the mice in the model group showed a decrease in body mass,an increase in DAI score,a decrease in colon length,serious mucosal injury and inflammatory cell infiltration,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue significantly increased(P<0.05,P<0.01),the content of IL-10 decreased(P<0.01),the mRNA expressions of LC3 and Beclin-1 in colon tissue decreased(P<0.05,P<0.01),the mRNA and protein expression of p62 increased(P<0.01),while the expressions of LC3Ⅱ/LC3Ⅰ and Beclin-1 proteins decreased(P<0.05,P<0.01).Compared with the model group,the body mass of mice in Kuijie Ankang Decoction group and SASP group increased(P<0.05),DAI score decreased(P<0.05),the colon length increased(P<0.05),the pathological damage of colon mucosa was alleviated,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue decreased(P<0.05,P<0.01),the content of IL-10 increased(P<0.01),the expressions of LC3 and Beclin-1 mRNA in colon tissue increased(P<0.05,P<0.01),the expression of p62 mRNA and protein decreased(P<0.05,P<0.01),the expressions of LC3Ⅱ/LC3Ⅰand Beclin-1 protein increased(P<0.05,P<0.01).16S rDNA sequencing results showed that the diversity and evenness of the intestinal flora in the model group mice decreased,with a decrease in the relative abundance of Firmicutes,Actinobacteria and Patescibacteria(P<0.05),and an increase in the relative abundance of Bacteroidota,Verrucomicrobiota and Proteobacteria(P<0.05);the relative abundance of Bacilli and Coriobacteriia decreased(P<0.05),the relative abundance of Bacteroidia,Clostridia and Verrucomicrobiae increased(P<0.05);the relative abundance of Ligilactobacillus and Dubosiella decreased(P<0.05),the relative abundance of unclassified Muribaculaceae,Lachnospiraceae NK4A136_group,Akkermansia and unclassified Lachnospiraceae increased(P<0.05).Compared with the model group,the diversity and evenness of intestinal flora increased in Kuijie Ankang Decoction group and SASP group,with an increase in the relative abundance of Firmicutes(P<0.05),a decrease in the relative abundance of Bacteroidota and Verrucomicrobiota(P<0.05),the relative abundance of Bacteroidia and Bacilli increased(P<0.05),the relative abundance of Verrucomicrobiae decreased(P<0.05);the relative abundance of unclassified Muribaculaceae and Ligilactobacillus increased(P<0.05),while the relative abundance of Lachnospiraceae NK4A136_group and Akkermansia decreased(P<0.05).Conclusion Kuijie Ankang Decoction can significantly improve the intestinal mucosal injury of UC mice,and the mechanism may be related to the regulation of colon autophagy level and intestinal flora disorder.

Objective:To explore the feasibility and effect of applying spherical fitting technology in CT three-dimensional reconstruction in preoperative planning of the resection range of Cam-type femoral acetabular impingement (FAI).Methods:46 Cam-type FAI patients who underwent arthroscopic femoroplasty in the Department of Sports Medicine in the Third Affiliated Hospital of Southern Medical University from July 2020 to June 2022 were enrolled in the spherical fitting group, including 26 females and 20 males, with an average age of 38.4±15.2 years (range of 24-53 years). The preoperative planning was performed using spherical fitting technology in CT three-dimensional reconstruction. Another 42 Cam-type FAI patients who underwent arthroscopic femoroplasty from July 2018 to June 2020 were enrolled in the observation group, including 25 females and 17 males, with an average age of 43.6±18.4 years (range 24-61 years). The preoperative planning was performed using CT three-dimensional reconstruction observation method. This study evaluated the impact of femoroplasty planned by spherical fitting technique on patients' prognosis though comparing the differences of postoperative α angle, femoral head-neck offset ratio, modified Harris hip score (mHHS), and visual analog score (VAS) at 3, 6, 9, and 12 months between two groups.Results:The average follow-up time was 11.8±0.6 months in spherical fitting group and 11.3±0.8 months in observation group. There was no significant difference regarding α angle, femoral head-neck offset ratio, mHHS, and VAS between two groups preoperatively ( P>0.05). The mHHS in two groups increased gradually, while VAS decreased sequentially at 3, 6, 9, and 12 months postoperatively. The postoperative mHHS and VAS were significantly better than those before surgery ( P<0.05). The mHHS was 83.2±14.8 vs. 70.5±11.2 in spherical fitting group and observation group at the followup of 9 months with significant difference ( t=4.471, P=0.007). It was 85.7±13.3 vs. 73.2±12.5 at the followup of 12 months with significant difference ( t=4.596, P=0.008). No significant difference was found in α angle, femoral head-neck offset ratio or mHHS at 3 and 6 months postoperatively ( P>0.05), and no significant difference was found in VAS at 3, 6, 9, and 12 months postoperatively between two groups. Conclusion:The spherical fitting technology in CT three-dimensional reconstruction could assist surgeons with planning of the resection range of Cam deformity preoperatively, and achieve a smooth progress of arthroscopic femoroplasty intraoperatively; after short term follow-up, we found that patients who underwent femoroplasty using this technology achieved satisfactory outcomes.