Objective:To observe the clinical efficacy and safety of Tongren Niuhuang Qingxin Pills combined with telmisartan tablets in the treatment of hypertensive vertigo syndrome of phlegm-heat disturbance.Methods:Randomized controlled trial was conducted. Totally 80 patients with hypertension vertigo and phlegm-heat disturbance syndrome were selected from March 2021 to August 2022 at Beijing Tongrentang Hospital of Traditional Chinese Medicine as the observation objects. They were randomly divided into two groups using a random number table method, with 40 cases in each group. The control group received oral telmisartan tablets, while the experimental group received Tongren Niuhuang Qingxin Pills in addition to the control group. Both groups were treated for 28 days and followed up for 1 month. The patients' room blood pressure before and after treatment was measured, and TCM syndrome scores were evaluated. The dizziness assessment rating scale (DARS) was used to evaluate the severity of dizziness, adverse reactions during treatment were recorded, drug safety was observed, and clinical efficacy was evaluated.Results:The total effective rate of the experimental group was 85.0% (34/40), and that of the control group was 7.5% (3/40), with statistical significance between the two groups ( χ2=48.32, P<0.001). Compared with before treatment, the experimental group had SBP [(136.63 ± 6.01) mmHg vs. (159.30 ± 9.01) mmHg, t=-21.00] and DBP [(84.48 ± 4.36) mmHg vs. (95.30 ± 3.75) mmHg, t=-13.80] after treatment; after treatment, SBP [(137.34 ± 6.39) mmHg vs. (158.00 ± 10.06) mmHg, t=-5.28] and DBP [(86.08 ± 4.43) mmHg vs. (95.18 ± 6.61) mmHg, t=-8.09] decreased in the control group ( P<0.01), but there was no statistical significance between the two groups after treatment ( P>0.05). After treatment, the TCM syndrome scores in the experimental group (8.68 ± 3.39 vs. 15.12 ± 3.03, Z=-6.61) were lower than those in the control group ( P<0.001), and DARS score [(8.53 ± 3.93) vs. (12.20 ± 3.95), Z=-3.63] was lower than that in the control group ( P<0.001). After treatment, the therapeutic effect index of TCM syndromes in the experimental group improved compared to before treatment in the same group. The therapeutic effect index of each symptom, from high to low, was as follows: rotation of oneself or visual objects>numbness of limbs>dry stool>dizziness and dizziness>liking cold drinks>bitter and dry mouth>red urine>red tongue, yellow coating, and greasy tongue>vomiting sticky and turbid phlegm>tinnitus>smooth pulse. There were no significant adverse reactions during the treatment of the two groups. Conclusion:Tongren Niuhuang Qingxin Pills combined with telmisartan can reduce the blood pressure of patients with hypertensive vertigo syndrome of phlegm-heat disturbance, improve the vertigo symptoms and TCM syndromes of patients, and the efficacy evaluation is superior to that of telmisartan alone.

Objective: Many studies have shown that respiratory syncytial virus persistent infection may be the main cause of chronic respiratory pathology. However, the mechanism is unclear. Cystic fibrosis transmembrane conduction regulator (CFTR) is an apical membrane chloride channel, which is very important for the regulation of epithelial fluid, chloride ion, and bicarbonate transport. CFTR dysfunction will lead to changes in bronchial secretions and impair mucus clearance, which is related to airway inflammation. In our previous study, we observed the down-regulation of CFTR in airway epithelial cells in respiratory syncytial virus (RSV) infected mouse model. In this study, we further investigated the expression and function of CFTR by constructing an airway epithelial cell model of RSV persistent infection. Methods: 16HBE14o- cells were infected with RSV at 0.01 multiplicity of infection (MOI). The expression of CFTR was detected by real-time RT-PCR, immunofluorescence, and Western blotting. The intracellular chloride concentration was measured by N-(ethoxycarbonylmethyl)-6-methoxyquinolium bromide (MQAE) and the chloride current was measured by whole-cell patch clamp recording. Results:16HBE14o-cells infected with RSV were survived to successive passages of the third generation (G3), while the expression and function of CFTR was progressively decreased upon RSV infection from the first generation (G1) to G3. Exposure of 16HBE14o-cells to RSV led to the gradual increase of TGF-β1 as well as phosphorylation of Smad2 following progressive RSV infection. Disruption of TGF-β1 signaling by SB431542 prevented Smad2 phosphorylation and rescued the expression of CFTR. Conclusion:RSV infection can lead to defective CFTR function in airway epithelial cells, which may be mediated via activation of TGF-β1 signaling pathway.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.