OBJECTIVE To investigate the therapeutic effect and mechanism of Qiwei dongqingye powder （QDP） on bronchial asthma in mice. METHODS The mice were divided into blank group （normal saline）， model group （normal saline）， dexamethasone group （2 mg/kg）， and QDP low-， medium-， and high-dose groups （200， 400， 800 mg/kg）， with 14 mice in each group. Except for the blank group， mice in all other groups were given ovalbumin via intraperitoneal injection followed by aerosol inhalation to induce a bronchial asthma model. During the modeling process， mice in each group were administered corresponding drug solutions or normal saline intragastrically/intraperitoneally. After the last medication， the number of cells in the bronchoalveolar lavage fluid （BALF） of the mice was observed and counted； the pathological changes of the bronchus and lung tissue were observed； the levels of malondialdehyde （MDA）， nitric oxide （NO）， total superoxide dismutase （T-SOD）， and glutathione peroxidase （GSH-Px） in the lung tissue of the mice were determined， and the level of interleukin-17 （IL-17） in the BALF and serum was determined. Transcriptomics was employed to predict and validate the mechanism of action of QDP against bronchial asthma. RESULTS Compared with the model group， the total cell count， neutrophil count， lymphocyte count， and macrophage counts in the BALF of the QDP high-dose group were all significantly reduced （ P ＜0.05）； the levels of MDA and NO in the lung tissue， and the levels of IL-17 in the BALF and serum were all decreased significantly （ P ＜0.05）； the levels of T-SOD and GSH-Px were significantly increased （ P ＜0.05）； the arrangement of lung tissue cells tended to normalize， with reduced infiltration of inflammatory cells and decreased exfoliation of bronchial simple columnar epithelial cells. The transcriptomic results revealed that the differentially expressed genes were B-cell receptor signaling pathway， nuclear factor κB （NF-κB） signaling pathway， ferroptosis signaling pathway， and others. Further validation revealed that， compared with the model group， the expression levels of NF-κB p65 and chemokine ligand 20， as well as the phosphorylation level of NF-κB inhibitor protein α， were significantly decreased in the lung tissues of the mice in all QDP groups （ P ＜0.05）. Conversely， the protein expression of nuclear factor erythroid 2-related factor 2 （Nrf2） and heme oxygenase 1 （HO-1） were significantly increased （ P ＜0.05）. CONCLUSIONS QDP can effectively alleviate bronchial asthma by inhibiting the NF-κB signaling pathway， activating the Nrf2/HO-1 signaling pathway， regulating oxidative stress， and reducing inflammatory responses.

Background Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen for both human bloodstream infections and mastitis in cows. However, little attention has been paid to the cross-host transmission of MRSA from cows to high-risk groups in China. Objective To determine the MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang, identify the antibiotic resistance profiles and molecular characteristics of the isolates, and provide scientific evidence for the formulation of targeted infection control strategies. Method A cross-sectional survey combined with laboratory pathogen analysis was conducted. From June to August 2024, large-scale dairy farms in Xinjiang region were selected as study sites. Nasal swabs (n=96) and skin swabs (n=39) were collected from workers, and bovine nasal swab samples (n=109) were collected simultaneously. All samples were subjected to MRSA isolation, cultivation, and identification, followed by antibiotic susceptibility testing to characterize resistance phenotypes. Staphylococcus aureus protein A (Spa) typing was performed to determine strain genotypes and elucidate MRSA colonization rates and molecular epidemiological patterns. Results A total of 35 MRSA strains was successfully isolated from 244 samples. The MRSA colonization rates among dairy farm workers and dairy cows were 20.83% (20/96) and 12.84% (14/109), respectively, with an overall isolation rate of 14.34% (35/244). Among the workers, the nasal colonization rate was 16.67% (16/96), and the skin colonization rate was 12.82% (5/39). One worker exhibited MRSA colonization at multiple body sites. All MRSA strains were resistant to cefoxitin (100%, 35/35). The resistance rates to erythromycin and clindamycin were 42.86% (15/35) and 34.29% (12/35), respectively. Thirteen strains showed a multidrug-resistant phenotype, whereas all strains were susceptible to vancomycin. The MRSA isolates exhibited high genetic diversity, with 13 Spa types identified, among which t441 was the most prevalent (8 strains). Both t441 and t034 types were detected in samples from both the dairy cows and their handlers. These two Spa types also carried and stably inherited specific resistance combinations, including erythromycin–clindamycin–cefoxitin and ciprofloxacin–erythromycin–clindamycin–gentamicin–cefoxitin–tetracycline, and a statistically significant association was also observed between the two resistance profiles and the bacterial types (P < 0.001). In addition, one novel Spa type strain was identified. Conclusion MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang are relatively high, with evidence of multi-site colonization. The isolates exhibit high levels of multidrug resistance and genetic diversity, indicating a potential risk of cross-host transmission.

ObjectiveTo explore the effect of modified Ditan Decoction （涤痰汤） on chronic intermittent hypoxia cognitive function and the potential function mechanism. MethodsTwenty-four Sprague-Dawley （SD） rats were randomly divided into a normal group， a model group， and a modified Ditan Decoction group， with eight rats in each group. Rats in the modified Ditan Decoction group were administered the decoction by gavage at 14.8 ml/（kg·d）， while the normal group and the model group received the same dose of normal saline. Thirty minutes after daily gavage， the rats in all three groups were placed in an intermittent hypoxia chamber. The oxygen concentration for the model group and the modified Ditan Decoction group was adjusted daily for 8 hours using a computer program to establish the model， while the normal group was exposed to the same airflow rate of ambient air. The intervention was continued for 12 weeks to establish a chronic intermittent hypoxia rat model. The Y-maze test was used to evaluate spatial working memory in the rats. Resting-state functional magnetic resonance imaging （rs-fMRI） was performed to detect whole-brain regional homogeneity （ReHo） and seed-based functional connectivity （FC）. Brain regions showing significant differences in rs-fMRI were selected for further analysis. Immunofluorescence was used to detect β-amyloid （Aβ） deposition and the number of ionized calcium-binding adapter molecule 1 （IBA1）-positive microglial cells. Immunohistochemistry was employed to assess the expression of synaptophysin （SYP）， the excitatory synapse marker vesicular glutamate transporter 1 （Vglut1）， and the inhibitory synapse marker vesicular γ-aminobutyric acid transporter （VGAT）. ResultsCompared with the normal group， the model group showed a reduced spontaneous alternation rate in the Y-maze test. The smoothed Z-score standardized regional homogeneity （SzReHo） value in the left entorhinal cortex significantly increased， and the FC value from this seed point to the left basal forebrain significantly reduced. Additionally， the model group exhibited significantly higher Aβ fluorescence intensity and Iba1 positivity in the left entorhinal cortex， decreased expression of SYP， Vglut1， and VGAT， along with an increased Vglut1/VGAT ratio （P＜0.05 or P＜0.01）. Compared to the model group， the modified Ditan Decoction group demonstrated an increased spontaneous alternation rate， a significantly reduced SzReHo value in the left entorhinal cortex， and a significantly increased FC value from this region to the left basal forebrain. Furthermore， this group showed significantly lower Aβ fluorescence intensity and Iba1 positivity in the left entorhinal cortex， increased levels of SYP， Vglut1， and VGAT， and a decreased Vglut1/VGAT ratio （P＜0.05 or P＜0.01）. ConclusionModified Ditan Decoction can reconstruct the projection from the left basal forebrain to the entorhinal cortex in chronic intermittent hypoxia， thereby reducing Aβ aggregation and excessive microglial activation in the left entorhinal cortex. This process improves the excitation/inhibition imbalance caused by synaptic remodeling， ultimately enhancing cognitive function in rats of chronic intermittent hypoxia.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

ObjectiveThis study aims to observe the clinical effect of Danggui Liuhuang Tang （DGLHT） on patients with type 2 diabetes mellitus （T2DM） complicated by atherosclerotic cardiovascular disease （ASCVD） at high risk， focus on evaluating the influence of DGLHT on cardiovascular risk indicators such as flow-mediated dilation （FMD）， atherogenic index of plasma （AIP）， and triglyceride-glucose index （TyG）， and explore the regulatory effect of DGLHT on the myeloid differentiation factor 88/nuclear factor-kappa B （MyD88/NF-κB） signaling pathway. MethodsThe clinical study was a single-center， double-blind， and randomized controlled trial. A total of 68 patients with T2DM-ASCVD at high risk for cardiovascular events with Yin deficiency and fire excess syndrome were enrolled and randomly assigned to a treatment group and a control group. The treatment group was given atorvastatin calcium tablets and DGLHT， while the control group was given atorvastatin calcium tablets and placebos. The treatment course was 12 weeks， with a final study completion of 30 patients in the treatment group and 29 in the control group. Changes in cardiovascular risk indicators such as FMD， AIP， TyG， and small dense low-density lipoprotein cholesterol （sdLDL-C） index were compared. Human umbilical vein endothelial cells （HUVECs） were used to establish a vascular endothelial injury and inflammation model. The protective effect of DGLHT on endothelial injury was verified by reverse transcription polymerase chain reaction （Real-time PCR） and Western blot . ResultsAfter 12 weeks of treatment， the AIP in the treatment group significantly decreased compared with that before the treatment （P<0.05）. Compared with the control group， the treatment group showed significant improvements in FMD and TyG （P<0.05）. Additionally， the treatment group demonstrated significant reductions in two-hour postprandial glucose （2 hPG）， glycated albumin （GA）， triglycerides （TG）， apolipoprotein E （Apo E）， and sdLDL-C （P<0.05）. Analysis of traditional Chinese medicine （TCM） syndrome efficacy indicated that in the treatment group， Yin deficiency and fire excess syndromes， including dry throat and mouth （P<0.05）， excessive thirst （P<0.01）， tidal fever and night sweats （P<0.05）， and dry stools （P<0.05）， improved. Compared with the control group， the treatment group showed significant improvements in symptoms of dry throat and mouth （P<0.05） and excessive thirst （P<0.01）. TCM syndrome scores significantly decreased （P<0.01）， and the overall efficacy rate was 56.67%， significantly higher than the 10.34% observed in the control group （P<0.01）. At the cellular level， increasing concentrations of DGLHT led to decreased messenger ribonucleic acid （mRNA） levels of pro-inflammatory cytokines interleukin-6 （IL-6）， tumor necrosis factor-alpha （TNF-α）， and interleukin-1-beta （IL-1β） in lipopolysaccharide （LPS）-stimulated HUVECs （P<0.01）， with significant reductions in the high-concentration group （P<0.01）. DGLHT may inhibit the expressions of MyD88 and phosphorylated （p）-NF-κB p65 proteins in a concentration-dependent manner. ConclusionDGLHT shows significant effects in reducing cardiovascular risks and may exert an anti-inflammatory effect by inhibiting the MyD88/NF-κB signaling pathway. This finding provides a new perspective for the prevention and treatment of cardiovascular diseases in high-risk individuals with T2DM-ASCVD.

Background Animal farming may affect the structure and diversity of gut microbiota of farm workers, but it needs more studies to provide solid evidence. Objective To analyze the diversity characteristics of gut microbiota in dairy farm workers, dairy cows, and the control population (non-animal contact occupational group), and to assess the impact of dairy farming on the gut microbiota of workers. Methods The 16S rRNA full-length amplicon sequencing technology was used to sequence 60 fecal samples from dairy farm workers, 89 from dairy cows, and 50 from the general population. The gut microbiota structure characteristics, including operational taxonomic units (OTUs), alpha diversity, beta diversity, and the composition of species at the phylum, family, and genus levels were analyzed. The differences in gut microbiota among the three groups of samples were compared to explore the impact of occupational exposure on the gut microbiota structure of dairy farm workers. Results A total of 50478 OTUs were identified in the gut microbiota of farm workers, dairy cows, and the general population, with 23613, 42723, and 16592 OTUs, respectively. The number of shared OTUs between the dairy cows and the general population was 12674 (27.17%), between the general population and the farm workers was 10099 (33.54%), and between the dairy cows and the farm workers was 17690 (36.36%). Compared with the general population, the farm workers and dairy cows showed more shared gut microbiota (P<0.01). The abundance of Firmicutes in the gut of the farm workers was higher than that of the general population (P<0.01), while Actinobacteriota and Proteobacteria were the opposite (P<0.01). The alpha diversity of gut microbiota in the farm workers was different from that of the general population. The ACE index of the farm workers was slightly lower than that of the general population and much lower than that of dairy cows (P<0.05), while their Shannon index was higher than that of the general population but lower than that of dairy cows (P<0.01). The linear discriminant analysis effect size (LefSe) showed that the abundances of Lachnospiraceae and Ruminococcaceae in the gut microbiota of the farm workers were significantly higher than those of the general population, while Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae were lower than those of the general population. Conclusion The dairy farm workers shares a certain proportion of common bacterial communities with dairy cows. Dairy farming operations can affect the structure and diversity of the gut microbiota of workers by increasing the abundances of Lachnospiraceae and Ruminococcaceae, while decreasing the abundances of Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae. The study results provide reference data for further exploring the cross-host transmission of pathogens related to occupational exposure in dairy farming.