Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

Objective To evaluate the noise hazard level of a coal mining enterprise, and identify high-risk operation types and people, and to provide a basis for preventing and controlling the health damage caused by noise. Methods A large coal mining enterprise in Shaanxi Province was selected as the research object. The noise monitoring data of the coal mine over the years was used to calculate the noise exposure matrix of each post in the enterprise, and the classification of occupational hazards at workplaces (GBZ/T 229.4-2012) was used to assess the occupational health risk levels. Results Among the 22 noise-exposed positions in the enterprise, the 8-hour working day equivalent sound level in positions of shearer driver, horseshoe driver, crusher driver, shuttle driver, relaxation screen driver, and grading screen driver were all higher than the occupational exposure limit of noise. In 2021, the noise exposure levels of shearer drivers, crusher drivers, and coal-selecting workers were all higher than 90 dB (A), and the occupational hazard level was moderate hazard level. In addition, the noise exposure levels of most other jobs also exceeded the occupational exposure limit. Conclusion The noise hazards in the coal mine industry are mainly concentrated in the posts of the coal mining system, tunneling system, and screening workshop. Among them, the shearer driver, the crusher driver, and the coal preparation workers have higher noise exposure levels. It is recommended to take corresponding noise reduction measures and strengthen the protection level to reduce the noise exposure risk of workers.

Objective To explore the development and validation of a prediction model for severe communi-ty-acquired pneumonia in adults based on peripheral blood inflammatory indicators.Methods Venous blood samples of 204 community-acquired pneumonia in adults patients admitted to 7 hospitals in Chongqing area from April 2021 to August 2022 were collected to detect C-reactive protein(CRP),peripheral white blood cell count(WBC),neutrophil to lymphocyte ratio(NLR),cytokines,lymphocyte subgroups and neutrophil CD64 index.All of patients were divided into a training group and a validation group according to the time of admis-sion.Univariate and multivariate Logistic regression were used to analyze the data of the training group,the characteristic factors of severe progression for pneumonia were selected to construct the nomogram model,and the data of the validation group was used to verify the model.The receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to evaluate the prediction ability of the model for severe community-acquired pneumonia in adults.Results Logistic regression analysis showed that age,CRP,WBC,interleukin(IL)-4/interferon gamma ratio and IL-6/IL-10 ratio were independent risk factors for severe community-acquired pneumonia in adults.The area under the ROC curve of the nomogram model in the training group and the validation group was 0.893 and 0.880,respectively.The calibration curve and DCA results shown that the model had a good prediction effect for severe community-acquired pneumonia in adults.Conclusion The inflammatory indicators included in this model are simple and easy to obtain clinically.This model with good differentiation and accuracy,it can be used as a practical tool to predict severe community-ac-quired pneumonia in adults,and has certain clinical application value.

OBJECTIVE To explore the neuroprotective effect of sodium aescinate on rats with Parkinson’s disease by regulating the silent information regulator 1 （SIRT1）/nuclear factor-κB （NF-κB） signaling pathway. METHODS The Parkinson’s disease rat model was constructed by using 6-hydroxydopamine injection method. Forty-eight rats successfully modeled were randomly divided into model group， sodium aescinate low-dose group （1.8 mg/kg）， sodium aescinate high-dose group （3.6 mg/kg）， sodium aescinate+EX527 （sodium aescinate 3.6 mg/kg+SIRT1 inhibitor EX527 5 mg/kg） group， with 12 rats in each group. Another 12 healthy rats were selected as the sham operation group. Each group was injected with the corresponding drug solution intraperitoneally， once a day， for 21 consecutive days. Twenty-four hours after the end of the last administration， the motor and cognitive functions of rats were detected， and the morphology of neurons in the substantia nigra and CA1 region of hippocampal tissue were observed. The content of dopamine （DA） in the nigrostriatal and the expression levels of tyrosine hydroxylase （TH） and α-synuclein （α-Syn） in the substantia nigra were detected. The serum levels of pro-inflammatory factor [interleukin-6 （IL-6）， IL-18]， anti-inflammatory factor （IL-10）， and the expression levels of SIRT1， phosphorylated NF-κB p65 （p-NF-κB p65） and NF- κB p65 protein in nigrostriatal were detected. RESULTS Compared with sham operation group， the neurons in the substantia nigra and CA1 region of hippocampal tissue were seriously damaged in model group； the number of rotations， escape latency， the expression levels of α-Syn in substantia nigra， the levels of serum pro-inflammatory factors， the relative expression ratio of p-NF- κB p65 and NF-κB p65 protein in nigrostriatal were increased or prolonged significantly （P＜0.05）； the target quadrant residence time， the content of DA in nigrostriatal， the expression level of TH in substantia nigra， the serum level of anti-inflammatory factor， and the expression level of SIRT1 protein in substantia nigra striatum were significantly decreased or shortened （P＜0.05）. Compared with model group， the damage degrees of neuron in sodium aescinate groups were alleviated， and the quantitative indicators were significantly improved， which were more significant in the high-dose group （P＜0.05）； EX527 could reverse the improvement effect of high-dose sodium aescinate （P＜0.05）. CONCLUSIONS Sodium aescinate can inhibit the activation of NF-κB signal by up-regulating the protein expression of SIRT1， thereby reducing the neuroinflammation of rats with Parkinson’s disease， improving the motor and cognitive dysfunctions， and finally playing a neuroprotective role.

OBJECTIVE To systematically evaluate the therapeutic effect of acupuncture on geriatric insomnia.METHODS Randomized controlled trials(RCTs)on acupuncture in the treatment of senile insomnia were searched in CNKI,VIP,Wanfang,China Biomedical Database,PubMed,Web of science,Embase and Cochrane Library databases from inception dates to June 24,2024.Litera-ture was screened and data were extracted based on the inclusion and exclusion criteria.The literature quality was evaluated according to the risk of bias table recommended by the Cochrane Collaboration Handbook 5.1.0,and the outcome indicators were graded using the GRADE system for the quality of evidence.RevMan5.4 software was used to evaluate the quality of the included literature,and Sta-ta18.0 software was used to conduct Meta-analysis on the included literature.RESULTS A total of 18 studies involving 1399 pa-tients were included.Meta-analysis showed that:compared with the simple western medicine treatment,acupuncture in the treatment of senile insomnia patients could improve the clinical effective rate[RR=1.18,95%CI(1.13,1.24),P<0.001],reduce the total PSQI score[MD=-1.10,95%CI(-1.25,-0.96),P<0.001],daytime dysfunction[MD=-1.38,95%CI(-1.59,-1.16),P<0.001],sleep latency[MD=-0.66,95%CI(-0.86,-0.47),P<0.001],sleep duration[MD=-0.45,95%CI(-0.64,-0.25),P<0.001],sleep efficiency[MD=-0.69,95%CI(-0.89,-0.49),P<0.001],sleep disorder[MD=-1.24,95%CI(-1.47,-1.01),P<0.001],sleep quality[MD=-0.84,95%CI(-1.05,-0.64),P<0.001].GRADE classification showed that the clinical efficacy was advanced evidence;the adverse reactions were intermediate evidence;the total score of PSQI,daytime dysfunction,sleep latency,sleep efficien-cy,sleep quality and sleep disorder were low evidence;sleep time was extremely low evidence.CONCLUSION Acupuncture inter-vention in senile insomnia patients is superior to the control group in clinical efficiency and various PSQI scores.Acupuncture interven-tion is worthy of further promotion and use in clinical practice as the complementary and alternative therapy for the conventional western medication treatment of senile insomnia.However,the evidence levels of some outcome indicators are relatively low,and more high-quality RCTs with large sample sizes are still needed to increase the strength of evidence.

Objective To investigate the influencing factors of medication adherence among renal transplant recipients taking immunosuppressive drugs. Methods In this study, 377 kidney transplant recipients who received follow-up care in the kidney transplant follow-up center of the Affiliated Hospital of Guizhou Medical University from October 2021 to July 2022 was selected by convenience sampling method. General data questionnaire and Basel Assessment Scale of immunosuppressive drug compliance were used for questionnaire analysis. Results A total of 377 renal transplant recipients were included in this study, including 236 males and 141 females. The overall adherence score was (4.90±1.55), indicating poor adherence. Multivariate Logistic regression analysis revealed that medication adherence among renal transplant recipients taking immunosuppressive drugs was correlated with marital status and postoperative time of renal transplantation. Conclusion Medication adherence among renal transplant recipients taking immunosuppressive drugs needs to be improved, with marital status and postoperative time of renal transplantation being the primary influencing factors.

Objective To investigate the induction factors of hypotension during cesarean section for perilous placenta previa under combined spinal-epidural anesthesia (CSEA) and to construct a nomogram prediction model. Methods A total of 130 parturients who underwent cesarean section for perilous placenta previa under CSEA from January 2020 to December 2023 in Yulin Maternity and Child Healthcare Hospital were selected as study subjects. A self-designed general information questionnaire was used to investigate the basic information and the occurrence of hypotension of the subjects. According to the occurrence of intraoperative hypotension, the patients were divided into hypotension group (47 cases) and non-hypotension group (83 cases). Univariate analysis was performed on the general information of the two groups, and multivariate Logistic regression analysis was used to explore the induction factors of intraoperative hypotension. Results Univariate analysis showed that there were statistically significant differences in body mass index, anesthesia level, presence of multiple pregnancy, preoperative systolic blood pressure, operative time, and the occurrence of Bezold-Jarisch reflex between the two groups (P < 0.05). Multivariate Logistic regression analysis revealed that body mass index≥ 24 kg/m², anesthesia level was in the eighth thoracic vertebra(T8) or above, multiple pregnancy, preoperative systolic blood pressure < 90 mmHg, operative time >1.5 h, and the occurrence of Bezold-Jarisch reflex were independent risk factors for hypotension during cesarean section for perilous placenta previa under CSEA (P < 0.05). A regression equation for the induction factors of hypotension during cesarean section for perilous placenta previa under CSEA was constructed: Logit(P)=-23.211+1.079×(body mass index ≥ 24 kg/m²)+1.101×anesthesia level (≥T8)+3.193×multiple pregnancy+2.214×preoperative systolic blood pressure (< 90 mmHg)+4.606×operative time (>1.5 h)+2.011×occurrence of Bezold-Jarisch reflex. The nomogram showed high discrimination and accuracy for patients with preoperative systolic blood pressure < 90 mmHg. After 1, 000 times of Bootstrap resampling for the nomogram model, a calibration curve was obtained, and the consistency index was calculated as 0.850, indicating good calibration of the nomogram model. The receiver operating characteristic (ROC) curve was plotted, with an area under the curve of 0.896 and 95% confidence interval of 0.802 to 0.956, suggesting good predictive performance. Conclusion Body mass index ≥24 kg/m², anesthesia level ≥ T8, multiple pregnancy, preoperative systolic blood pressure < 90 mmHg, operative time >1.5 h, and the occurrence of Bezold-Jarisch reflex are induction factors for hypotension during cesarean section for perilous placenta previa under CSEA.

ObjectiveTo explore the interaction between bruceoside B and gut microbiota and the inhibitory activity of its metabolites on human lung cancer A549 cells， and to explore the value of bruceoside B in the treatment of non-small cell lung cancer（NSCLC）. MethodBruceoside B was co-incubated with the human gut microbiota under anoxic conditions in vitro， and ultra high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was used to analyze the metabolic transformation products. Cell counting kit-8（CCK-8） assay was performed to determine the effects of bruceoside B and its metabolites on the proliferation of human lung cancer A549 cells and the half inhibitory concentration（IC₅₀） was calculated. Five healthy male rats were gavaged with bruceoside B（2 mg·kg^-1） for 7 days after adaptive feeding. The feces of rats were collected before and after administration. 16S rRNA sequencing was used to assess gut microbiota. ResultBruceoside B was mainly metabolized to brusatol by human gut microbiota， the IC₅₀ of bruceoside B and the conversion product to A549 cells were 1 755.50， 19.57 μmol·L^-1， respectively， and the conversion product had a better activity at inhibiting A549 cells proliferation than bruceoside B. Additionally， The results of intestinal flora analysis showed no significant differences in α diversity and β diversity of gut microbiota after administration. In terms of species abundance， at the phylum level， bruceoside B decreased the relative abundance of Actinobacteriota and Proteobacteria， increased the relative abundance of Firmicutes， Patescibacteria and Cyanobacteria. At the genus level， bruceoside B decreased the relative abundance of Staphylococcus， Aerococcus and Psychrobacter， increased the relative abundance of Romboutsia， Lactobacillus， Clostridium sensu stricto 1， Norank-f-norank-o-Clostridia-UCG-014， Turicibacter， Allobaculum and Candidatus Saccharimonas. The results of functional prediction showed that the gut microbiota functional compositions were relatively stable. ConclusionBruceoside B can be deglycosylated by intestinal flora and converted into brusatol， with a significant increase in antitumor activity. The administration of bruceoside B will not cause significant changes in the structure and function of the intestinal flora， resulting in intestinal microecological balance disorders， and the administration appears to be beneficial to the intestinal flora of NSCLC patients.

Chronic chloropropene poisoning is a disease mainly caused by peripheral nerve damage due to close contact with chloropropene in industrial production, its clinical manifestations include varying degrees of sensory, motor, or tendon reflex disorders in the distal limbs, and neuromyography can show neurogenic damage. This article analyzed and summarized the clinical characteristics, diagnosis and treatment methods of three patients with occupational chronic chloropropene poisoning, in order to enhance the clinical understanding of occupational chronic chloropropene poisoning and provide reference for clinical diagnosis and treatment.

Chronic chloropropene poisoning is a disease mainly caused by peripheral nerve damage due to close contact with chloropropene in industrial production, its clinical manifestations include varying degrees of sensory, motor, or tendon reflex disorders in the distal limbs, and neuromyography can show neurogenic damage. This article analyzed and summarized the clinical characteristics, diagnosis and treatment methods of three patients with occupational chronic chloropropene poisoning, in order to enhance the clinical understanding of occupational chronic chloropropene poisoning and provide reference for clinical diagnosis and treatment.