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.

Senecavirus A (SVA) is a major viral pathogen causing disease in pigs, and effective monitoring of SVA infection is critical for disease control. In this study, we aimed to develop a reliable ELISA method for rapidly detecting neutralizing antibodies against SVA. We used HEK293F cells to express an SVA-specific porcine Fab antibody and verified the biological activity of the Fab antibody by indirect ELISA, immunofluorescence assay, virus neutralization test, and Western blotting. The Fab antibody was biotinylated and used as a competitive antibody to establish a competitive ELISA (C-ELISA) for detecting neutralizing antibodies against SVA. We then evaluated the C-ELISA in terms of sensitivity, specificity, repeatability, and result agreement rate with the VNT. The results showed that we successfully prepared an SVA-specific porcine Fab antibody, which showed high affinity for SVA. We named this antibody 1M33Fab and designated it as Bio-1M33Fab after biotin labeling. The assay conditions were optimized as follows: the coating concentration of SVA particles being 1 μg/mL, the working concentration of Bio-1M33Fab being 0.5 μg/mL, the optimal serum dilution of 1:10, and the optimal dilution of enzyme-labeled avidin being 1:30 000. At a percent inhibition (PI) of 47%, the assay demonstrated the highest sensitivity (96.88%) and specificity (100%), with no cross-reactivity observed with the positive sera of major porcine viral diseases. The intra-assay coefficient of variation ranged from 1.12% to 7.34%, while the inter-assay coefficient of variation ranged from 1.10% to 8.97%, indicating good repeatability. In the detection of 224 clinical pig serum samples, C-ELISA and VNT showed a result agreement rate of 93.75%. In conclusion, we successfully develop a C-ELISA method for detecting neutralizing antibodies against SVA by using a porcine-derived Fab antibody, which lays a foundation for the development of detection kits.
Animals ; Swine ; Antibodies, Neutralizing/immunology* ; Enzyme-Linked Immunosorbent Assay/methods* ; Immunoglobulin Fab Fragments/immunology* ; Antibodies, Viral/immunology* ; Picornaviridae/immunology* ; Humans ; HEK293 Cells ; Swine Diseases/diagnosis* ; Picornaviridae Infections/diagnosis*

Objective:To identify and trace the origin of the Francisella tularensis subsp. novicida strain SJCS-979 isolated from the blood of a patient, so as to provide a reference for the traceability investigation of such infection events. Methods:Hot spring water samples that the patient had recently bathed in were collected to culture the causative agent, combined with the pathogenic characteristics and the patient′s activity before the bloodstream infection. The water samples were concentrated, acid-treated, and then the isolation of the causative agent was performed, following the method for Legionella detection in circulating cooling water. Suspected strains detected from the hot spring water were subjected to classical phenotypic identification, API ZYM and API NH strips tests, drug sensitivity testing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification, and the obtained data were compared with those of strain SJCS-979 isolated from the patient′s blood. A phylogenetic tree was constructed based on genomic analysis to determine the taxonomic status of strain SJCS-979 and related strains. Epidemiological data of Francisella tularensis subsp. novicida were collected and analyzed by integrating the global genetic and genomic data on GenBank database. Core single nucleotide polymorphism(SNP) comparisons were obtained using Snippy 3.2 software, and then an evolutionary tree was built to determine its population structure based on BAPS analysis. Results:Strain CC-2, isolated from the hot spring water, shared the same biochemical and drug sensitivity phenotype, and had a nearly consistent mass spectrometric profile with strain SJCS-979 isolated from the blood of a patient. Genomic phylogenetic tree analysis based on 120 core protein sequences showed that strains SJCS-979 and CC-2 fell on the same branch with known Francisella tularensis subsp. novicida strains. Bayesian genotyping showed that the global Francisella tularensis subsp. novicida strains with genomic data could be divided into six different sequence clusters. Strains SJCS-979 and CC-2 were located in the same taxonomic group with only 4 SNP differences, indicating that they might be the same clone. Conclusions:This study reports a case of bacteremia caused by Francisella tularensis subsp. novicida, and natural hot spring water may be the environmental source of this infection event.

Objective:To investigate the predictive value of the triglyceride-high-density lipoprotein cholesterol-glucose-body mass index (TyHGB) and triglyceride-glucose-body mass index (TyG-BMI) in early pregnancy for gestational diabetes mellitus (GDM) and pregnancy outcomes.Methods:A retrospective analysis was conducted, a total of 600 pregnant women who underwent prenatal examinations at North China Medical and Health Group Xingtai General Hospital from August 2020 to August 2023 were collected. Participants were divided into GDM group (76 cases) and non-GDM group (524 cases) based on GDM occurrence, and further categorized into adverse pregnancy group (101 cases) and favorable pregnancy group (499 cases) based on outcomes. Multivariate Logistic regression was used to identify risk factors for GDM and adverse pregnancy. The predictive performance of TyHGB and TyG-BMI was evaluated using receiver operating characteristic (ROC) curves.Results:After adjusting for confounders, TyHGB and TyG-BMI were independent risk factors for GDM ( OR = 1.569, 95% CI 1.259 -1.955; OR = 1.109, 95% CI 1.029 - 1.038) and adverse pregnancy ( OR = 1.438, 95% CI 1.193 - 1.734; OR = 1.021, 95% CI 1.014 - 1.029). The area under the curve (AUC) for TyHGB and TyG-BMI alone in predicting GDM was 0.677 and 0.731, respectively. Combined prediction of GDM yielded an AUC of 0.793, with sensitivity of 72.37% and specificity of 65.81%. For adverse pregnancy, the AUC of TyHGB and TyG-BMI alone were 0.666 and 0.692, respectively, while their combination achieved AUC of 0.746, with specificity of 69.34% and sensitivity of 65.35%. Conclusions:TyHGB and TyG-BMI in early pregnancy are risk factors for GDM and adverse pregnancy outcomes. Their combination can enhance predictive efficacy for both conditions.

Objective:To identify and trace the origin of the Francisella tularensis subsp. novicida strain SJCS-979 isolated from the blood of a patient, so as to provide a reference for the traceability investigation of such infection events. Methods:Hot spring water samples that the patient had recently bathed in were collected to culture the causative agent, combined with the pathogenic characteristics and the patient′s activity before the bloodstream infection. The water samples were concentrated, acid-treated, and then the isolation of the causative agent was performed, following the method for Legionella detection in circulating cooling water. Suspected strains detected from the hot spring water were subjected to classical phenotypic identification, API ZYM and API NH strips tests, drug sensitivity testing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification, and the obtained data were compared with those of strain SJCS-979 isolated from the patient′s blood. A phylogenetic tree was constructed based on genomic analysis to determine the taxonomic status of strain SJCS-979 and related strains. Epidemiological data of Francisella tularensis subsp. novicida were collected and analyzed by integrating the global genetic and genomic data on GenBank database. Core single nucleotide polymorphism(SNP) comparisons were obtained using Snippy 3.2 software, and then an evolutionary tree was built to determine its population structure based on BAPS analysis. Results:Strain CC-2, isolated from the hot spring water, shared the same biochemical and drug sensitivity phenotype, and had a nearly consistent mass spectrometric profile with strain SJCS-979 isolated from the blood of a patient. Genomic phylogenetic tree analysis based on 120 core protein sequences showed that strains SJCS-979 and CC-2 fell on the same branch with known Francisella tularensis subsp. novicida strains. Bayesian genotyping showed that the global Francisella tularensis subsp. novicida strains with genomic data could be divided into six different sequence clusters. Strains SJCS-979 and CC-2 were located in the same taxonomic group with only 4 SNP differences, indicating that they might be the same clone. Conclusions:This study reports a case of bacteremia caused by Francisella tularensis subsp. novicida, and natural hot spring water may be the environmental source of this infection event.

Objective:To investigate the predictive value of the triglyceride-high-density lipoprotein cholesterol-glucose-body mass index (TyHGB) and triglyceride-glucose-body mass index (TyG-BMI) in early pregnancy for gestational diabetes mellitus (GDM) and pregnancy outcomes.Methods:A retrospective analysis was conducted, a total of 600 pregnant women who underwent prenatal examinations at North China Medical and Health Group Xingtai General Hospital from August 2020 to August 2023 were collected. Participants were divided into GDM group (76 cases) and non-GDM group (524 cases) based on GDM occurrence, and further categorized into adverse pregnancy group (101 cases) and favorable pregnancy group (499 cases) based on outcomes. Multivariate Logistic regression was used to identify risk factors for GDM and adverse pregnancy. The predictive performance of TyHGB and TyG-BMI was evaluated using receiver operating characteristic (ROC) curves.Results:After adjusting for confounders, TyHGB and TyG-BMI were independent risk factors for GDM ( OR = 1.569, 95% CI 1.259 -1.955; OR = 1.109, 95% CI 1.029 - 1.038) and adverse pregnancy ( OR = 1.438, 95% CI 1.193 - 1.734; OR = 1.021, 95% CI 1.014 - 1.029). The area under the curve (AUC) for TyHGB and TyG-BMI alone in predicting GDM was 0.677 and 0.731, respectively. Combined prediction of GDM yielded an AUC of 0.793, with sensitivity of 72.37% and specificity of 65.81%. For adverse pregnancy, the AUC of TyHGB and TyG-BMI alone were 0.666 and 0.692, respectively, while their combination achieved AUC of 0.746, with specificity of 69.34% and sensitivity of 65.35%. Conclusions:TyHGB and TyG-BMI in early pregnancy are risk factors for GDM and adverse pregnancy outcomes. Their combination can enhance predictive efficacy for both conditions.

Objective:To construct an evaluation system for clinical thinking ability of general practitioners in the treatment of multimorbidity.Methods:This was a cross-sectional study. The draft of evaluation indexes for clinical thinking ability of general practitioners in treatment of multimorbidity was preliminary developed through literature review, collation, analysis and discussion. Nineteen clinical and teaching experts of general practice were selected for consultation via anonymous convenient sampling. From January to June 2022, 2 rounds of expert consultation were conducted using the Delphi method. During the first round of consultation, according to the survey feedback, we modified and improved the evaluation system of general practitioners′ clinical thinking ability for multi-disease co-treatment. During the second round, experts were asked to assess the importance of each index, and to calculate the weight of each index accordingly. Questionnaires were sent to experts via letters. The content of the questionnaires encompasses the basic information of experts, evaluation for various indexes and relevant opinions. The mean value of importance assignment ≥3.5, coefficient of variation ≤0.25 and the full score frequency ≥30% were taken as the criteria. Indexes unsatisfying the criteria were removed, so that the final index system could be constructed.Results:The average age of 19 experts was 50.2 years old, 9 of them were male. A total of 2 rounds of expert consultation were conducted, 19 questionnaires were issued in each round, and 19 effective questionnaires were received afterwards. In the first round of consultation, 10 experts put forward revised opinions, and some indexes were adjusted according to the definition criteria and the discussion of the research group. In the second round of consultation, 3 experts put forward suggestions for modification. According to the definition criteria, no need to delete the indexes. After discussion by the research group, some indexes were adjusted, and finally an evaluation system of clinical thinking ability for multi-disease co-treatment of general practitioners was established, including 4 first-level indexes and 30 second-level indexes. The weights of the 4 first-level indexes in descending order were "overall thinking ability" (38.01%), "diagnostic thinking ability" (33.96%), "evidence-based thinking ability" (14.75%), and "critical thinking ability" (13.28%). Among the 30 secondary indexes, the top 5 were "ability to identify and handle priority emergency incidents" (5.04%), "risk assessment and critical illness identification ability" (4.63%), "emergency referral ability" (4.61%), "communication and expression ability" (4.57%), and "standardized diagnosis and treatment ability" (4.23%).Conclusion:This study successfully constructed an evaluation system for clinical thinking ability of general practitioners in the treatment of multimorbidity.

The management of antibiotic-resistant, bacterial biofilm infections in skin wounds poses an increasingly challenging clinical scenario. Pseudomonas aeruginosa infection is difficult to eradicate because of biofilm formation and antibiotic resistance. In this study, we identified a new benzothiazole derivative compound, SN12 (IC₅₀ = 43.3 nmol/L), demonstrating remarkable biofilm inhibition at nanomolar concentrations in vitro. In further activity assays and mechanistic studies, we formulated an unconventional strategy for combating P. aeruginosa-derived infections by targeting the two-component (Gac/Rsm) system. Furthermore, SN12 slowed the development of ciprofloxacin and tobramycin resistance. By using murine skin wound infection models, we observed that SN12 significantly augmented the antibacterial effects of three widely used antibiotics-tobramycin (100-fold), vancomycin (200-fold), and ciprofloxacin (1000-fold)-compared with single-dose antibiotic treatments for P. aeruginosa infection in vivo. The findings of this study suggest the potential of SN12 as a promising antibacterial synergist, highlighting the effectiveness of targeting the two-component system in treating challenging bacterial biofilm infections in humans.

Objective:To analyze the clinical characteristics of dengue fever patients, summarize the course and characteristics of the disease, and analyze the risk factors that affect the condition.Methods:Retrospective collection of general information, clinical symptoms, medical history, laboratory tests, prognosis and other clinical data of dengue fever patients that admitted to Jinghong First People's Hospital and severe dengue fever patients at People's Hospital of Xishuangbanna Dai Autonomous Prefecture from June to December 2023 was conducted using a case report form (CRF). According to the diagnostic criteria of the World Health Organization (WHO), patients were divided into dengue fever group, dengue fever with warning signs group, and severe dengue fever group. The differences in clinical data between different groups of patients were analyzed and compared. Binary multiple factor Logistic regression analysis was used to explore the risk factors affecting the severity of dengue fever in patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of prediction models constructed for various risk factors for severe dengue fever. Subgroup analysis was performed on the prognosis of severe dengue fever patients, and the differences in clinical data between two groups of patients with different prognoses were compared. Binary multivariate Logistic regression analysis was used to explore the risk factors affecting the prognosis of severe dengue fever patients. ROC curve was drawn to analyze the predictive value of prediction models constructed for various risk factors on the prognosis of severe dengue fever patients.Results:A total of 2 264 patients were included, including 499 cases in the dengue fever group, 1 379 cases in the dengue fever with warning signs group, and 386 in the severe dengue fever group (43 deaths and 343 survivors). The most common symptom of dengue fever patients was fever (94.70%), followed by muscle soreness (70.54%), headache (63.12%), fatigue (58.92%), and chills (46.02%). Compared with the dengue fever group and the dengue fever with warning signs group, the ratio of thalassemia and the levels of cardiac troponin (cTnI, cTnT), MB isoenzyme of creatine kinase (CK-MB), and myoglobin were significantly increased in patients with severe dengue fever group, albumin (Alb) was significantly decreased in patients with severe dengue fever group. The levels of cTnT and myoglobin in patients with dengue fever with warning signs group were significantly higher than those in the dengue fever group, and the level of Alb in patients with dengue fever with warning signs group was significantly lower than that in the dengue fever group, the differences were statistically significant (all P < 0.05). Binary multivariate Logistic regression analysis showed that thalassemia [odds ratio ( OR) = 6.214, 95% confidence interval (95% CI) was 2.337-16.524, P < 0.001], Alb ≤ 36 g/L ( OR = 6.297, 95% CI was 4.270-9.286, P < 0.001), and cTnT levels ( OR = 1.008, 95% CI was 1.002-1.015, P = 0.016) were risk factors for severe dengue fever. ROC curve analysis showed that the area under the ROC curve (AUC) for predicting severe dengue fever based on the prediction models constructed for the above risk factors was 0.856, with the best predictive value of 0.067, sensitivity of 67.1%, and specificity of 99.4%. In the subgroup analysis of patients with severe dengue fever, compared with the survival group, the levels of hematocrit (HCT), cTnT, and CK-MB in the death group patients were significantly increased, while the level of Alb was significantly decreased, and the differences were statistically significant. Binary multivariate Logistic regression analysis showed that Alb ( OR = 0.839, 95% CI was 0.755-0.932, P = 0.001), HCT ( OR = 1.086, 95% CI was 1.010-1.168, P = 0.025), elevated troponin level ( OR = 10.119, 95% CI was 2.596-39.440, P < 0.001), and CK-MB ( OR = 1.081, 95% CI was 1.032-1.133, P < 0.001) were risk factors for mortality in patients with severe dengue fever. ROC curve analysis showed that the AUC for predicting death in severe dengue fever patients based on the prediction models constructed for the above risk factors was 0.881, with the best predictive value of 0.113, sensitivity of 75.0%, and specificity of 88.9%. Conclusion:Thalassemia, Alb≤36 g/L, and cTnT level are risk factors for severe dengue fever, while HCT level, Alb level, CK-MB level, and elevated troponin level are risk factors for death in patients with severe dengue fever.

Objective:To analyze the biological characteristics, phylogeny and the taxonomic status of strain 7712 (=CGMCC 1.17031=NBRC 113783=KCTC 15766) isolated from a clinical blood sample.Methods:Strain 7712 was identified by the cultural properties, cellular and colonial morphology, physiological and biochemical reactions, matrix-assisted laser desorption ionization time-of-flight mass spectrometry system, and genome correlation index analysis. The genomic phylogenetic tree was construct to analyze the taxonomic position. The virulence factors and resistance genes of strain 7712 and related strains were then compared by the online virulence factor database and online comprehensive antibiotic research database respectively.Results:Strain 7712 was urease negative, gram-negative nonfermenters, which was identified as Ochrobactrum anthropi by VITEK GN card. The 16S rRNA gene analysis showed that the strain was closely related to the members of genera Ochrobactrum and Brucella. The phylogenetic tree showed that strain 7712 was clustered together with Ochrobactrum teleogrylli LCB8 T and Ochrobactrum haematophilum CCUG 38531 T, along with genus Brucella and other Ochrobactrum species. The genome relatedness indexes analysis showed that the average nucleotide identity between strain 7712 and Ochrobactrum teleogrylli LCB8 T was 98.16%, which was higher than the threshold for prokaryotic species. Genetic prediction showed that strain 7712 carried several virulence-related genes and resistance-related genes, of which the existence of OCH gene might be responsible to the resistance to cephalosporin. Conclusions:A case of human infection caused by Ochrobactrum teleogrylli is identified, which would help promote the understanding of biodiversity of genus Ochrobactrum.