ObjectiveTo investigate the effect of transcutaneous electrical acupoint stimulation (TEAS) on pulmonary function, exercise endurance and clinical symptoms in patients with chronic obstructive pulmonary disease (COPD). MethodsRandomized controlled trials on the effect of TEAS on COPD were systematically searched in CNKI, Wanfang Data, VIP Database, SinoMed, PubMed, Embase and Cochrane Library from inception to March, 2025. Two researchers independently screened the literature and extracted data. The methodological quality of the included researches was assessed using the Cochrane Handbook for Systematic Reviews of Interventions version 5.1.0 risk-of-bias tool and the PEDro scale. Statistical analysis was performed using RevMan 5.4. ResultsA total of eleven studies involving 542 patients were included. Scores of PEDro scale ranged from five to nine. TEAS significantly improved forced expiratory volume in one second (FEV₁) (MD = 0.19, 95%CI 0.08 to 0.29, P < 0.001), FEV₁/forced vital capacity (MD = 5.15, 95%CI 4.21 to 6.09, P < 0.001), FEV₁% predicted (MD = 8.46, 95%CI 5.71 to 11.22, P < 0.001), peak expiratory flow (MD = 0.18, 95%CI 0.05 to 0.31, P = 0.006), and COPD Assessment Test (CAT) score (MD = -3.60, 95%CI -4.81 to -2.40, P < 0.001). Distance of 6-minute walk test increased significantly (MD = 25.97, 95%CI 7.88 to 44.05, P = 0.005), however, after sensitivity analysis, the magnitude of improvement was limited and did not reach the minimal clinically important difference threshold. Subgroup analysis showed that multi-acupoint intervention was more effective than single-acupoint intervention (MD = 0.29 vs. 0.12), and one to two weeks of intervention was the most effective (MD = 0.37). TEAS combined with conventional medication or exercise training showed synergistic benefits. ConclusionTEAS helps improve pulmonary function and clinical symptoms in patients with COPD. TEAS combined with conventional interventions may produce synergistically enhanced effects.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To analyze functional changes in macrophages in mouse models of vulvovaginal candidiasis (VVC) by modulating indoleamine 2,3-dioxygenase 1 (IDO1) .Methods:Forty specific-pathogen-free female ICR mice were randomly divided into 4 groups using a complete randomization method: a blank group, a VVC model group, a VVC model + 1-methyltryptophan (1-MT) group (referred to as the 1-MT group), a VVC model + interferon-γ (IFN-γ) group (referred to as the IFN-γ group), with 10 mice in each group. Except for the blank group, all the mice were injected subcutaneously with estradiol benzoate oil solution in the abdomen every other day for 6 days prior to modeling to induce pseudoestrus; after successful induction of pseudoestrus, the mice were inoculated vaginally with Candida albicans suspensions at a concentration of 2 × 10 9 CFU/ml once a day for 5 days to establish VVC mouse models, and subcutaneous injections of estradiol benzoate oil solution were continued simultaneously to maintain the pseudoestrus state; 1 day before inoculation with fungal suspensions, mice in the 1-MT group and IFN-γ group were pretreated with 1-MT and IFN-γ respectively, followed by once-daily same intervention for 6 consecutive days; mice in the blank group and VVC model group were intraperitoneally injected with physiological saline solution once a day for 6 consecutive days. On the 5th day of modeling, vaginal conditions in mice were observed and vaginal symptoms were scored; the vaginal lavage fluid was collected for smear microscopy and fungal colony counting; then, the mice were sacrificed, the vaginal tissues were collected and subjected to hematoxylin-eosin (HE) staining and periodic acid-Schiff (PAS) staining, and the expression of IDO1 and the macrophage surface marker F4/80 was determined in the vaginal tissues by an immunofluorescence method; real-time fluorescence-based quantitative PCR (qPCR) was performed to determine mRNA expression levels of IDO1, inducible nitric oxide synthase (iNOS), and arginase 1 (Arg-1) in the vaginal tissues, and Western blot analysis to determine the IDO1 protein expression in the vaginal tissues. One-way analysis of variance was used to analyze the differences in indices among groups, and Tukey test was used for multiple comparisons. Results:Smear microscopic examination of the vaginal lavage fluid on the 5th day of modeling showed elongated hyphae with a few spores in the VVC model group, a large number of elongated hyphae aggregating in clusters with surrounding spores in the 1-MT group, and a few thin and short hyphae with a large number of spores in the IFN-γ group. Compared with the VVC model group (360.0 ± 15.9), the fungal colony counts in the vaginal lavage fluid significantly increased in the 1-MT group (523.7 ± 67.7, P = 0.002), but significantly decreased in the IFN-γ group (258.3 ± 27.57, P = 0.026). HE staining and PAS staining showed small abscess formation in the epidermis and predominant infiltration of neutrophils throughout the epidermal and dermal layers with a large number of spores and a few hyphae in the VVC model group; thickened epidermis and diffuse inflammatory infiltration predominated by neutrophils in the dermis were seen in the 1-MT group, with a large number of hyphae and spores aggregating into clusters, which were predominated by hyphae; in the IFN-γ group, spores aggregated in the epidermis without obvious hyphae, and a small amount of inflammatory cells predominated by neutrophils infiltrated the dermis. Immunofluorescence assay revealed that the relative fluorescence intensities of IDO1 and F4/80 were highest in the IFN-γ group and the 1-MT group, respectively. Western blot analysis revealed that the IDO1 protein expression in the VVC model group was significantly higher than that in the blank group ( P < 0.001) and the 1-MT group ( P < 0.05), but significantly lower than that in the IFN-γ group ( P < 0.05). qPCR showed that iNOS mRNA expression significantly increased in the VVC model group compared with the blank group ( P < 0.01), and increased in the IFN-γ group compared with the blank group, VVC model group and 1-MT group (all P < 0.001); Arg-1 mRNA expression significantly increased in the VVC model group compared with the blank group ( P < 0.001) and IFN-γ group ( P < 0.01), and increased in the 1-MT group compared with the blank group, VVC model group, and IFN-γ group (all P < 0.001) . Conclusion:In the VVC mouse models, upregulation of IDO1 may cause macrophage polarization toward the M1 phenotype, and inhibition of IDO1 may cause increased macrophage recruitment and exacerbate the inflammatory response.

Objective To compare the diagnostic efficiencies of different scanning schemes of dualphase 99Tcm-methoxyisobutylisonitrile (MIBI) planar imaging with or without SPECT/CT in the preoperative localization of parathyroid lesions.Methods Forty-two patients (20 males,22 females;average age (53.1 ± 14.8) years) with primary or secondary hyperparathyroidism who underwent parathyroidectomy from June 2011 to June 2016 were analyzed retrospectively.All patients underwent dual-phase 99Tcm-MIBI planar scan and dual-phase SPECT/CT scan.The images were collected according to the following 4 procedures:dualphase planar imaging (S1),dual-phase planar imaging+early-phase SPECT/CT (S2),dual-phase planar imaging+delayed-phase SPECT/CT (S3),dual-phase planar imaging+dual-phase SPECT/CT (S4).Pathological results were considered as the gold standard.A total of 168 parathyroid glands in 42 patients were evaluated by the 4 imaging procedures respectively.The diagnostic efficiencies were calculated and compared by x2 test.Results Seventy-eight abnormal parathyroid lesions were found.The diagnostic sensitivities of S1,S2,S3,S4 were 66.7％ (52/78),89.7％(70/78),69.2％(54/78),89.7％(70/78),and the accuracies were 78.6％ (132/168),94.0％ (158/168),85.1％ (143/168),94.0％ (158/168),respectively.The diagnostic accuracies of S2 and S4 were significantly higher than those of S1 and S3 (x2 values:17.027 and 7.176,both P＜0.01).Condusions The dual-phase planar imaging together with early-phase and dualphase SPECT/CT imaging have high diagnostic efficiencies in the preoperative localization of parathyroid lesions.Considering reducing radiation dose and examine time,the dual-phase planar imaging together with early-phase SPECT/CT is a better choice.