Objective To analyze the factors affecting the prognosis of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy and construct an individualized prognostic nomogram prediction model. Methods A retrospective analysis was conducted on the clinical data of 385 patients with driver gene-negative, locally advanced or metastatic NSCLC who received first-line immune checkpoint inhibitors. Univariate and multivariate Cox regression analyses were used to identify prognostic risk factors, and a prognostic nomogram model was established. The predictive performance of the model was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC), and calibration curves. The cutoff value of the nomogram was calculated to stratify patients by risk. Survival curves were calculated by Kaplan-Meier analysis. Results Age (HR=1.775, 95%CI: 1.265-2.490), degree of differentiation (HR=0.365, 95%CI: 0.257-0.519), low PD-L1 expression (HR=0.661, 95%CI: 0.455-0.960), high PD-L1 expression (HR=0.423, 95%CI: 0.297-0.603), SCC-Ag (HR=1.549, 95%CI: 1.109-2.163), and CONUT score (HR=2.527, 95%CI: 1.797-3.554) were independent risk factors affecting overall survival (OS) of patients with NSCLC undergoing immunotherapy. The nomogram prediction model constructed on the basis of these factors had a C-index of 0.767. Time-dependent ROC curves for survival showed that the AUCs for 1-, 2-, and 3-year OS were 0.830, 0.853, and 0.886, respectively. Calibration curves indicated that the nomogram-predicted survival rates were in good agreement with the actual outcomes. The cutoff value for the study’s nomogram prediction model was 136.60 points, and survival curves showed statistically significant differences between different risk groups (P<0.05). Conclusion The nomogram model established in this study can effectively predict the prognosis of patients with driver gene-negative locally advanced or metastatic NSCLC treated with first-line immunosuppressive therapy. It provides a new tool for assessing prognosis and aids clinicians in formulating individualized treatment plans.

Objective To construct a diagnostic and prognostic model for malignant pleural effusion (MPE) in patients with non-M1b stage (AJCC 7th edition) non-small cell lung cancer (NSCLC) by machine learning. Methods Retrospective analysis was conducted on patients diagnosed with NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2015, excluding those in the M1b stage. Two sets of data were collected: data 1 (patients with non-M1b stage NSCLC, n=47 392) was used to construct the MPE diagnostic model; and data 2 (patients with M1a stage NSCLC and MPE, n=2 422) was used to construct a prognostic model. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen feature variables, with a training set and validation set ratio of 7:3. Models were built using eight machine learning algorithms, with evaluation metrics including accuracy, precision, recall, F1 score, area under the ROC curve (AUC), decision curve, calibration curve, and precision recall curve (PR), with ROC-AUC as the main evaluation metric. Results The incidence of MPE in patients with non-M1b stage NSCLC was 5.12%, and the 1-year survival rate of patients with MPE was 32.5%. LASSO regression identified nine diagnostic-related variables and 12 prognostic-related variables. The AUC values of the models constructed by eight machine learning algorithms all exceeded 0.70. The random forest model performed the best in the diagnostic model (training set AUC=0.908, validation set AUC=0.897), and the XGBoost model showed the best performance in the prognostic model (training set AUC=0.905, validation set AUC=0.875). Other evaluation indicators showed good results and balanced distribution. SHAP feature importance analysis showed that tumor size, lymph node metastasis, and histological type were important influencing factors for the occurrence of MPE, and chemotherapy intervention was the most remarkably prognostic factor. Conclusion The random forest diagnostic model constructed in this study can effectively predict the risk of MPE in patients with non-M1b stage NSCLC, and the XGBoost prognostic model can predict the prognosis of M1a-stage NSCLC patients with concurrent MPE.

Objective: To investigate the prevalence and influencing factors of menopausal syndrome among postmenopausal women in Pan'an County, Zhejiang Province, so as to provide the basis for guiding the health management of postmenopausal women. Methods: From May 2023 to April 2024, the postmenopausal women aged 40 to 69 years in Pan'an County were selected using the random cluster sampling method. Demographic information, lifestyle and prevalence of gynecological diseases were collected through questionnaire surveys. The prevalence of menopausal syndrome was assessed by modified Kupperman Score Scale. Factors affecting menopausal syndrome were analyzed by a multivariable logistic regression model. Results: A total of 816 postmenopausal women were surveyed, with an mean age of (57.63±2.92) years and a mean natural menopause age of (49.85±2.13) years. There were 574 cases with menopausal syndrome, with a prevalence of 70.34%. Flashes and sweating, insomnia and irritability were common symptoms, accounting for 62.87%, 47.43% and 41.18%, respectively. Multivariable logistic regression analysis showed that monthly personal income of ≤5 000 yuan (<3 000 yuan, OR=3.124, 95%CI: 1.829-5.335; 3 000-5 000 yuan, OR=2.399, 95%CI: 1.370-4.201) and having gynecological diseases (OR=1.970, 95%CI: 1.292-3.004) were associated with a higher risk of menopausal syndrome, while average (OR=0.141, 95%CI: 0.072-0.276) or sufficient sleep quality (OR=0.095, 95%CI: 0.049-0.185) were associated with a lower risk of menopausal syndrome. Conclusion The prevalence of menopausal syndrome among postmenopausal women in Pan'an County is relatively high, and is mainly influenced by personal economic status, sleep quality and the presence of gynecological diseases.

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary dis-ease(COPD),so as to promote COPD patients to participate in home rehabilitation exercise.Methods Using the convenient sampling method,80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects.Ac-cording to the random number table method,they were divided into a control group and an experimental group,with 40 cases in each group.The control group adopted the traditional exercise training method,and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise in-tervention,with 5 times a week,and the intervention was implemented for 12 weeks.The pulmonary function index,modified Medical Research Council scale score,physical fitness level,Chronic Obstructive Pulmonary Disease As-sessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention.Results 77 patients completed the study,with 39 in the experimental group and 38 in the control group.The forced vital capacity,forced expiratory volume in one second,forced expiratory volume in one second to forced vital capacity ratio,physical fitness level and exercise compliance of the experimental group were higher than those of the control group,while the modified British Medical Research Council scale score and Chron-ic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group.The differences were statistically significant(P＜0.05).Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD,improve the exercise compliance and physical fitness in-dicators of elderly patients and improve the quality of life of the patients.

Objective:To investigate the current status and influencing factors of barriers to going out among elderly patients with chronic obstructive pulmonary disease (COPD), and to provide a reference for implementing targeted preventive measures.Methods:Elderly COPD patients from the People's Hospital of Xinjiang Uygur Autonomous Region were selected between January and May 2024 by convenience sampling. A cross-sectional survey was conducted using a general information questionnaire, Scale on Barriers to Going Out for the Elderly, Perceived Isolation Scale and COPD Assessment Test (CAT).Results:A total of 270 questionnaires were distributed, with 250 valid responses, the effective response rate was 92.6%. Among the 250 elderly COPD patients, there were 124 males and 126 females, with age distributions: 116 patients aged 60-69 years, 94 aged 70-79 years, and 40 aged ≥80 years. The total score for Scale on Barriers to Going Out for the Elderly was (20.01 ± 4.09). The score on barriers to going out in elderly COPD patients were positively correlated with the Perceived Isolation Scale and CAT scores ( r = 0.456 and 0.625, both P <0.05). Multiple linear regression analysis revealed that age, oxygen therapy, exercise habits,Perceived Isolation Scale, and CAT score classification were the main influencing factors for barriers to going out ( t values were -2.85 to 8.93, all P<0.05), explaining 63.0% of the total variance. Conclusions:The level of barriers to going out in elderly COPD patients is moderate-to-high level. Healthcare professionals should emphasize the assessment of barriers to going out, closely monitor high-risk groups, and develop and implement interventions to prevent such barriers.

Objective: To investigate the mechanism by which icariin ( ICA) inhibits the invasion and metastasis of human triple-negative breast cancer ( TNBC) cells via downregulation of the transforming growth factor-β/ Smad ( TGF-β/ Smad) signaling pathway． Methods: TNBC cells ( MDA-MB-231 and MDA-MB-468) were cultured in vitro and divided into four groups: an experimental group treated with 15 μmol / L ICA; a model group treated with 10 μmol / L TGF-β receptor inhibitor LY2109761; a combination group ( LY2109761 + ICA) treated with both 15 μmol / L ICA and 10 μmol / L LY2109761; and a control group．Cell proliferation，migration，and invasion were as- sessed using CCK-8，colony formation，5-ethynyl-2 '-deoxyuridine ( EdU) ，wound healing，and Transwell assays． The expression levels of epithelial-mesenchymal transition ( EMT) -related proteins，as well as TGF-β1，Smad2， and phosphorylated Smad2 ( P-Smad2) were detected by immunofluorescence and Western blot． Results: CCK-8 results showed that cell proliferation decreased gradually with increasing concentrations of ICA ( P＜0. 05) ．Colony formation and EdU assays indicated significantly inhibited proliferation in the ICA-treated group compared to the control ( P＜0. 05) ．Wound healing and Transwell assays demonstrated reduced migration and invasion capabilities in the experimental group relative to the control ( P＜0. 05) ．Compared to the model group，the LY2109761 + ICA group exhibited further suppression of invasion ( P＜0. 05) ．Immunofluorescence revealed decreased Vimentin ex- pression in the experimental group ( P＜0. 05) ，with an even more pronounced reduction in the LY2109761 + ICA group ( P＜0. 01) ．Western blot analysis showed that the protein levels of N-cadherin，matrix metalloproteinase-9( MMP9) ，Vimentin，TGF-β1，Smad2，and P-Smad2 were downregulated in the experimental group compared to the control ( P＜0. 05) ．These proteins were further suppressed in the LY2109761 + ICA group compared to the model group ( P＜0. 05) ． Conclusion ICA inhibits TNBC cells proliferation，invasion，metastasis，and EMT by downregulating the TGF-β/ Smad signaling pathway．

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary dis-ease(COPD),so as to promote COPD patients to participate in home rehabilitation exercise.Methods Using the convenient sampling method,80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects.Ac-cording to the random number table method,they were divided into a control group and an experimental group,with 40 cases in each group.The control group adopted the traditional exercise training method,and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise in-tervention,with 5 times a week,and the intervention was implemented for 12 weeks.The pulmonary function index,modified Medical Research Council scale score,physical fitness level,Chronic Obstructive Pulmonary Disease As-sessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention.Results 77 patients completed the study,with 39 in the experimental group and 38 in the control group.The forced vital capacity,forced expiratory volume in one second,forced expiratory volume in one second to forced vital capacity ratio,physical fitness level and exercise compliance of the experimental group were higher than those of the control group,while the modified British Medical Research Council scale score and Chron-ic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group.The differences were statistically significant(P＜0.05).Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD,improve the exercise compliance and physical fitness in-dicators of elderly patients and improve the quality of life of the patients.

Objective:To investigate the current status and influencing factors of barriers to going out among elderly patients with chronic obstructive pulmonary disease (COPD), and to provide a reference for implementing targeted preventive measures.Methods:Elderly COPD patients from the People's Hospital of Xinjiang Uygur Autonomous Region were selected between January and May 2024 by convenience sampling. A cross-sectional survey was conducted using a general information questionnaire, Scale on Barriers to Going Out for the Elderly, Perceived Isolation Scale and COPD Assessment Test (CAT).Results:A total of 270 questionnaires were distributed, with 250 valid responses, the effective response rate was 92.6%. Among the 250 elderly COPD patients, there were 124 males and 126 females, with age distributions: 116 patients aged 60-69 years, 94 aged 70-79 years, and 40 aged ≥80 years. The total score for Scale on Barriers to Going Out for the Elderly was (20.01 ± 4.09). The score on barriers to going out in elderly COPD patients were positively correlated with the Perceived Isolation Scale and CAT scores ( r = 0.456 and 0.625, both P <0.05). Multiple linear regression analysis revealed that age, oxygen therapy, exercise habits,Perceived Isolation Scale, and CAT score classification were the main influencing factors for barriers to going out ( t values were -2.85 to 8.93, all P<0.05), explaining 63.0% of the total variance. Conclusions:The level of barriers to going out in elderly COPD patients is moderate-to-high level. Healthcare professionals should emphasize the assessment of barriers to going out, closely monitor high-risk groups, and develop and implement interventions to prevent such barriers.

Immunotherapy has become the first-line standard treatment option for driver gene-negative advanced non-small cell lung cancer (NSCLC). But not all patients can benefit from immunotherapy, and can even have serious adverse reactions. It is crucial to identify the predictors of clinical response to immunotherapy. Several studies have shown that elevated baseline C-reactive protein (CRP) or persistent elevation of CRP during the treatment process may indicate a poorer prognosis for patients, and high CRP may be correlated with adverse reactions. Attention to the dynamic changes of CRP during immunotherapy for NSCLC may become an important predictor of prognosis.

Objective:To observe any effect of percutaneous tibial nerve stimulation (PTNS) combined with electro-acupuncture on detrusor overactivity after a spinal cord injury.Methods:Forty spinal cord injury survivors with neurogenic detrusor overactivity were randomly assigned to a control group or an observation group, each of 20. Both groups received routine bladder training and electro-acupuncture modulating 3 sacral spinal nerves. The observation group also received 20 minutes of bilateral PTNS five times a week for 8 weeks. The frequency was 10Hz with a pulse width of 200μs. Before and after the treatment, both groups′ urination frequency, incontinence and average daily urine volume were assessed using a urodynamics analyzer, bladder diaries and an incontinence quality of life questionnaire (I-QOL).Results:After treatment, the average involuntary detrusor contraction volume (IDCV), maximum detrusor pressure at filling time (P det·max), bladder compliance (BC), residual volume and the TL value of the electromyogram of the urethral sphincter (LgTLR) had all improved significantly in both groups. The 1st IDCV, BC and LgTLR of the observation group were then significantly better than in the control group, on average, with the average P det·max and residual volume significantly lower than in the control group. The average daily single urine output and I-QOL score of both groups had increased significantly, while the average daily urination frequency and frequency of urinary incontinence had decreased significantly. Both were again significantly better in the observation group. Conclusion:Combining percutaneous electrical stimulation of the tibial nerves with electro-acupuncture can effectively inhibit detrusor overactivity after a spinal cord injury, reducing urinary incontinence.