Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

BACKGROUND:Various proteins,signaling pathways,and inflammatory mediators are involved in the pathophysiological process of osteoarthritis.The development of small molecule drugs targeting these proteins,signaling pathways,and inflammatory mediators can effectively delay the progression of osteoarthritis and ameliorate its clinical manifestations. OBJECTIVE:To review the research progress of small molecule drugs in the treatment of osteoarthritis based on the pathogenesis of osteoarthritis. METHODS:PubMed,CNKI,and WanFang databases were searched with English search terms"osteoarthritis,arthritis,osteoarthrosis,degenerative,arthritides,deformans,small molecule drugs,small molecule inhibitors,small molecule agents"and Chinese search terms"osteoarthritis,small molecule drugs,small molecule inhibitors."A total of 68 articles were included for review according to the inclusion and exclusion criteria. RESULTS AND CONCLUSION:(1)Currently,studies concerning the pathogenesis of osteoarthritis remain unclear.The occurrence and development of osteoarthritis are strongly associated with proteins,cytokines,and signal transduction pathways,so its therapeutic mechanism is relatively complex.Currently,targeting proteins,cytokines,and signal transduction pathways related to osteoarthritis with small molecule drugs has become a major research focus.(2)Small molecule drugs frequently possess visible intracellular or extracellular targets and efficacy,containing enhancing cartilage repair,resisting joint degradation,attenuating inflammation,and relieving pain.Other anti-osteoarthritis small molecule drugs have shown promise in promoting stem cell chondrogenic differentiation and cartilage matrix reconstruction.(3)At present,small molecule drugs targeting the pathophysiological process of osteoarthritis to delay the progression of osteoarthritis are still in the experimental stage,but most of these small molecule drugs have shown the expected results in the experimental process,and there are no relevant studies to illustrate the efficacy of small molecule drugs in the treatment of osteoarthritis.(4)Small molecule drugs for the treatment of osteoarthritis have reached the expected experimental results in the basic experimental stage.Numerous studies have exhibited that small molecule drugs can target the suppression of specific proteins,cytokines,and signal transduction pathways that cause osteoarthritis,so as to treat osteoarthritis.Nevertheless,its safety and effectiveness still need to be identified by further basic and clinical studies.This process needs to be investigated and studied by more scholars.(5)At present,many scholars in and outside China have made contributions to the treatment of osteoarthritis.Compared with traditional treatment methods,small molecule drugs reveal better efficacy and safety in the basic experimental stage,and it is expected to become an emerging method for the treatment of osteoarthritis in the future to rid patients of pain.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

Naringin is a flavonoid compound with a wide range of biological and pharmacologi-cal activities,which can be used in treating tumor,diabetes,neurodegenerative diseases,cardiovascu-lar diseases,metabolic syndrome,etc.Among them,the application of naringin in cardiovascular diseases has attracted the attention of many re-searchers.This article mainly reviews the role of naringin in cardiovascular disease(regulating blood lipids,anti atherosclerosis,lowering blood pres-sure,inhibiting myocardial hypertrophy,anti myo-cardial infarction,protecting myocardial ischemia/reperfusion injury,reducing myocardial ischemia/reperfusion injury and improving pulmonary arteri-al hypertension),the protective effect on cardiotox-icity,and the signal pathways in cardiovascular dis-ease(PI3K-Akt-mTOR,p-eNOS/p-Akt/p-ERK,miR-126/GSK-3 β/β-Catenin),clinical trials,etc.This pa-per is expected to review the current research sta-tus of naringin in cells and animal models so as to reveal its clinical application prospects and provide reference for further research in related fields.

OBJECTIVES: To identify immunosuppressive neutrophil subsets in patients with prostate cancer (PCa) and construct a risk prediction model for prognosis and immunotherapy response of the patients based on these neutrophil subsets. METHODS: Single-cell and transcriptome data from PCa patients were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Neutrophil subsets in PCa were identified through unsupervised clustering, and their biological functions and effects on immune regulation were analyzed by functional enrichment, cell interaction, and pseudo-time series analyses. Lasso-Cox regression was utilized to construct a prognostic risk model based on the immunosuppressive neutrophil subsets, and survival analysis and ROC curve analysis were used to compare the prognosis of PCa patients with high and low risks stratified using this model. The relationship of the prognostic risk model with PCa immune infiltration and immune response was evaluated using CIBERSORT and TIDE scores. RESULTS: PCa tissues showed a significantly greater proportion of infiltrating neutrophils than the adjacent normal tissues (P<0.05). PCa-associated neutrophils could be clustered into two independent cell subsets: Neu_1 and Neu_2. Neu_2 cells exhibited highly enriched immunoregulatory functions and were highly differentiated and mature, with upregulated immunosuppressive cytokines such as TGFB1, ITGB2, and LGALS3. Based on the genetic characteristics of Neu_2 cell subsets, the prognostic risk model was constructed. The patients in the high-risk group identified by the model had a shorter biochemical recurrence time (P<0.05) and a higher proportion of Tregs and M2-TAMs cell infiltration (P<0.05) with a higher risk of immune rejection and poorer immune response scores. CONCLUSIONS PCa-associated neutrophils are highly heterogeneous. The prognostic risk model constructed based on the immunosuppressive neutrophil Neu_2 subset can effectively predict both the survival outcomes and immune response of PCa patients.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Prognosis ; Neutrophils/immunology* ; Immunotherapy

Objective To explore the effect of ionizing radiation on the fertility of male mice and its offspring and the intergenerational and transgenerational genetic effect mechanism of ionizing radiation through sperm DNA methylation sequencing.Methods Eight-week-old(8 w)C57BL/6 male mice were irradiated with 60Co radiation source at a dose of 3 Gy(3 Gy-F0 group,n=60)and non-irradiated mice of the same age were used as controls(0 Gy-F0 group,n=60).Afetr 5-,6-,7-,8-,9-,10-,11-,and 12-week radiation,the mice began to breed with healthy females,and the first generation(F1 generation)male mice then breed with healthy female mice to obtain the offspring(F2 generation)male mice.The structure of testis was detected by hematoxylin-eosin staining;serum follicle-stimulating hormone(FSH),testosterone(T)and luteinizing hormone(LH)levels were determined by enzyme-linked immunosorbent assay.Automatic sperm analysis system was used to detect sperm concentration and activity.The DNA of F0 generation sperm was extracted and analyzed by genome-wide DNA methylation sequencing.MassARRAY methylation sites were detected in sperm DNA of F1 generation mice and verified by quantitative polymerase chain reaction(qPCR).Results Compared with the 0 Gy-F0 group,male mice in the 3 Gy-F0 group gradually regained their reproductive ability 7 weeks after ionizing radiation.There was no significant difference in the number of surviving offspring between the 3 Gy-F0 group and 0 Gy-F0 group 10-11 weeks after radiation(P＞0.05).There were no significant differences in body weight,testicular morphology,or sperm concentration of F1 generation mice between the 3 Gy-F1 group and the 0 Gy-F1 group(all P＞0.05).However,compared with the 0 Gy-F1 group,the contents of LH,FSH and T in the 3 Gy-F1 group were all decreased(all P＜0.05),the testicle volume,total sperm motility rate,forward motility rate and the fertility were considerably decreased(all P＜0.05).DNA methylation sequencing showed that more differentially methylated genes were enriched in the pathway regulating microtubule formation.MassARRAY methylation sites analysis showed that the methylation level of Mid1 was significantly increased(P＜0.05 or P＜0.01).Mid1 was verified down-regulated in Fl and F0 sperm by qPCR(P＜0.05 or P＜0.01).However,there were no significant differences in volume of testes,testicular index,sperm concentration,sperm motility,hormone levels or Mid1 expression level between 0 Gy-F2 and 3 Gy-F2 mice in F2 generation male mice(all P＞0.05).Conclusion Sperm damage in mice caused by ionizing radiation at a dose of 3 Gy can recover by itself.However,it may decrease sperm activity by regulating Mid1 methylation level of sperm in F1 mice,thus affect the fertility of F1 mice,but has no effect on the fertility of male F2 mice.

Objective:To investigate the effect of ribonucleotide reductase regulatory subunit M2 (RRM2) on the malignant biological behavior and aerobic glycolysis of gastric cancer cells by regulating cyclin-dependent kinase (CDK) 1.Methods:Human gastric cancer MKN-45 cells were divided into si-NC group (transfected with blank fragment) , CoCl 2+si-NC group (hypoxia control transfected with blank fragment) , CoCl 2+si-RRM2 group (hypoxia with RRM2 silencing) , CoCl 2+si-RRM2+pcDNA3.1 NC group (hypoxia with RRM2 silencing and blank vector) and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group (hypoxia with RRM2 silencing and CDK1 overexpression) . The mRNA relative expression levels of RRM2 and CDK1 were analyzed by real time fluorescent quantitative reverse transcription PCR. Co-immunoprecipitation (CoIP) was used to analyze the interaction between RRM2 and CDK1 protein. MTT assay was used to analyze the proliferation activity of cells. The cell migration distance was detected by cell scratch assay. Cell apoptosis was detected by flow cytometry. Adenosine triphosphate (ATP) and glucose kit were used to detect ATP production and glucose consumption. The protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1 and p-CDK1/CDK1 were detected by Western blotting. Results:Real time fluorescent quantitative reverse transcription PCR results showed that the relative expression levels of CDK1 mRNA in si-NC group, CoCl 2+si-NC group and CoCl 2+si-RRM2 group were 1.01±0.15, 1.30±0.06 and 0.51±0.18, and the relative expression levels of RRM2 mRNA were 1.03±0.32, 1.59±0.28 and 0.44±0.17, respectively, and there were statistically significant differences ( F=25.52, P=0.001; F=14.47, P=0.005) . The mRNA expressions of RRM2 and CDK1 in CoCl 2+si-NC group were higher than those in si-NC group. Compared with the si-NC group and the CoCl 2+si-NC group, the mRNA expressions of RRM2 and CDK1 were lower in the CoCl 2+si-RRM2 group (all P<0.05) . CoIP results showed that there was interaction between RRM2 and CDK1. MTT assay, cell scratch assay and flow cytometry showed that the cell proliferation activity of si-NC group, CoCl 2+si-NC group, CoCl 2+si-RRM2 group, CoCl 2+si-RRM2+pcDNA3.1 NC group and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were 1.04±0.01, 1.18±0.04, 0.84±0.03, 0.81±0.03 and 0.93±0.05, respectively. The cell migration distances were (301.83±2.75) , (369.67±0.76) , (176.50±6.38) , (175.83±3.69) , (254.17±1.61) μm, respectively. The apoptosis rates were 8.05%±0.21%, 5.75%± 0.20%, 28.28%±0.04%, 30.18%±1.51% and 17.79%±0.22%, respectively, all with statistically significant differences ( F=73.82, P<0.001; F=1 600.01, P<0.001; F=787.15, P<0.001) . Compared with the si-NC group and CoCl 2+si-NC group, the proliferation and migration ability of cells in the CoCl 2+si-RRM2 group, CoCl 2+si-RRM2+pcDNA3.1 NC group and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were weaker, and the apoptosis rates were higher (all P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the proliferation and migration ability of cells in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were stronger, and the apoptosis rate was lower (all P<0.05) . The results of ATP and glucose detection showed that there were statistically significant differences in the amount of ATP production and glucose consumption among the above five groups ( F=12.53, P<0.001; F=19.21, P<0.001) . Compared with the si-NC group, the glucose consumption of cells was lower in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group ( P<0.05) . Compared with the CoCl 2+si-NC group, the ATP production and glucose consumption of cells in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were lower (both P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the ATP production and glucose consumption of the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were higher (both P<0.05) . Western blotting showed that there were statistically significant differences in the protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1, and p-CDK1/CDK1 among the above five groups (all P<0.001) . Compared with the si-NC group and the CoCl 2+si-NC group, the protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1 and p-CDK1/CDK1 in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were lower (all P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the protein expressions of ENO1, RRM2, PKM2, GLUT1 and p-CDK1/CDK1 in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were higher (all P<0.05) . Conclusions:Silencing RRM2 can inhibit the malignant biological behavior of gastric cancer cells and the occurrence of aerobic glycolysis by regulating CDK1.

In recent years, studies have found that the abnormal expression of rhythm genes is closely related to the risk of occurrence and the progression of the disease course of colorectal cancer. In addition, chronotherapy based on the circadian rhythm theory has shown certain effects in the clinical treatment of colorectal cancer, but there are still great limitations. Therefore, it is very important to clarify the mechanism of action of rhythm genes in the occurrence and development of colorectal cancer, which may provide a theoretical basis for the clinical application of chronotherapy.

Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93％of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05％).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50％of primary care facilities,42.86％of secondary hospitals,and 31.58％of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.