ObjectiveTo investigate the ability of clinically isolated， Helicobacter pylori （H. pylori）-specific gene polymerase chain reaction （PCR）-positive gastric， vaginal， and fecal Candida to release H. pylori. MethodsResuscitate 4 strains of H. pylori -specific 16S rDNA and ureA gene PCR-positive Candida strains isolated in laboratory from clinical sources， including 1 strain of gastric Candida， 1 strain of fecal Candida， 2 strains of vaginal Candida and the standard Candida albicans strain ATCC10231 （Ca10231）. The presence of H. pylori-specific ureA in the 5 strains of Candida isolates was confirmed by PCR. The aforementioned strains of Candida and H.pylori were inoculated into urea medium and cultured in a constant temperature incubator at 37 ℃. The color change of the medium was observed daily. A change in the medium's color from yellow to red indicated the presence of urease activity. Then， the five strains of Candida and H. pylori were co-incubated with the magnetic beads coated with H. pylori antibodies respectively. Scanning electron microscopy （SEM） was employed to observe the presence of bacilli adsorbed on the surface of the magnetic beads. PCR was used to detect the presence of H.pylori-specific 16S rDNA and ureA genes on magnetic beads. ResultsThe PCR analysis of the ureA gene in the four Candida isolates was positive， whereas the Ca10231 strain tested negative. Upon culturing the four Candida isolates on urea medium， the medium color changed from yellow to red which was determined to be urease positive， while the medium containing Ca10231 remained unchanged， which was urease negative. SEM revealed that bacilli could be observed on the surface of magnetic beads co-incubated with the 4 strains of Candida of clinical origin and H.pylori isolate. Specifically， PCR testing of the magnetic beads co-incubated with one vaginal Candida， one gastric Candida and H.pylori isolate showed positive results for the 16S rDNA and ureA genes of H. pylori； however， the PCR tests for the two genes were negative for the magnetic beads co-incubated with the other two Candida isolate. ConclusionThis study demonstrates that H. pylori-specific genes Candida can release H. pylori.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

ObjectiveTo explore the clinical efficacy and mechanism of Bupi Qingfei prescription （BPQF） in treating stable bronchiectasis in the patients with syndromes of lung-spleen Qi deficiency and phlegm-heat accumulation in the lungs. MethodsA randomized， double-blind， placebo-controlled trial was conducted. Patients were randomized into BPQF and placebo control （PC） groups. On the basis of conventional Western medicine treatment， the BPQF granules and placebo were respectively administered at 10 g each time， twice a day， for a course of 24 weeks. The TCM symptom scores， Quality of Life Questionnaire for Bronchiectasis （QOL-B） scores， lung function indicators， T lymphocyte subsets， level of inflammatory factors in the sputum， level of neutrophil elastase （NE） in the sputum， and occurrence of adverse reactions were observed before and after treatment in the two groups. ResultsA total of 64 patients completed the study， encompassing 32 in the BPQF group and 32 in the PC group. After treatment， the BPQF group showed decreased TCM symptom scores （P<0.01）， increased QOL-B scores （P<0.01）， and declined levels of tumor necrosis factor （TNF）-α and NE （P<0.05， P<0.01）. The PC group showed decreased TCM symptom （except spleen deficiency） scores （P<0.01）， increased the QOL-B health cognition and respiratory symptom domain scores （P<0.05， P<0.01）， and a declined TNF-α level （P<0.01）. Moreover， the BPQF group had lower TCM symptom （except chest tightness） scores （P<0.05， P<0.01）， higher QOL-B （except treatment burden） scores （P<0.05， P<0.01）， and lower levels of interleukin-6 and TNF-α （P<0.05） than the PC group. Neither group showed serious adverse reactions during the treatment process. ConclusionBPQF can ameliorate the clinical symptoms of stable bronchiectasis patients who have lung-spleen Qi deficiency or phlegm-heat accumulation in the lungs by regulating the immune balance and inhibiting airway inflammatory responses.

Objective: To propose an improved method for constructing the internal quality control (IQC) framework for ELISA assays and validate its efficacy by statistically analyzing IQC data from nine blood center laboratories. Methods: 1) IQC data was collected from nine blood centers and analyzed using a domestic HBsAg ELISA detection kit as an example. 2) Differences between IQC values across batches within Blood Center 1 were assessed. 3) Statistical analyses were performed on batch usage, number of batches used, days of use, number of QC points, batch-specific means, and coefficients of variation (CV) across all nine centers. 4) Using the improved construction method for IQC framework, provisional and permanent frames were established for batches within Blood Center 1 and Blood Center 9, followed by outlier determination. Results: 1) Statistically significant differences were observed in IQC data between batches within Blood Center 1 (P<0.01). It is recommended that both the control material/reagents and the control chart framework be replaced simultaneously. 2) There were substantial differences among 9 blood centers regarding the control material/reagent lot numbers used, the number of QC runs per batch, and the QC values for identical lots. Therefore, individual laboratories should establish their own IQC chart frameworks. 3) The improved IQC framework construction method for ELISA assays is as follows: provisional frames are established via frame-shifting, using the pre-experimental mean and cumulative coefficient of variation (CV) from the preceding batch. For batches used >20 days with >20 QC points, permanent frames are constructed by aggregating in-control data accumulated over ≥20 days with ≥20 points to calculate cumulative mean and standard deviation. The provisional and permanent frames constructed by this method identified all 26 extreme outliers across Blood Centers 1 and 9 as out-of-control. Among the 218 general outliers, 10 were classified as normal by the provisional frames, while the remainder were designated as warnings or out-of-control. This method effectively monitors assay stability. Conclusion: Based on the statistical analysis of IQC practices across blood centers of varying scales, combined with the inherent characteristics of ELISA assays and the batch-to-batch instability of reagents/QC materials, it is recommended to reconstruct QC charts upon lot changes. The proposed method—utilizing frame-shifting for provisional frames and establishing permanent frames based on cumulative data—is applicable to blood center laboratories of differing sizes and effectively monitors the stability of the ELISA assay process.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Objective:The purpose of this study was to analyze the influencing factors of readmission after percutaneous coronary intervention(PCI)in patients with coronary heart disease and type 2 diabetes(T2DM),and to build a nomogram model.Methods:A retrospective study was conducted on 260 patients with coronary heart disease and T2DM who received PCI treatment in Yancheng Third People's Hospital from May 2019 to May 2023,clinical data were collected and followed up for 1 year.They were divided into on readmission group and unreadmission group based on their readmission after 1 year.Multivariate logistic regression analysis was conducted to determine risk factors,and a nomogram model was constructed using R software to evaluate its predictive efficiency.Results:Among the 260 patients,65 were readmitted after surgery,with a readmission rate of 25.00％(65/260).Univariate analysis showed that,left ventricular ejection fraction(LVEF),age,left main artery disease,hypertension history,number of coronary artery lesions,dyslipidemia,glycosylated hemoglobin(HbA1c),course of diabetes,fasting blood glucose(FBG),number of stents,and regular postoperative medication were related to readmission 1 year after PCI(P＜0.05).Age ≥ 70 years,hypertension history,coronary artery multi vessel disease,course of diabetes ≥ 10 years,HbA1c ≥7％,left main artery disease,dyslipidemia,LVEF＜50％,number of stents ≥3 were risk factor for readmission 1 year after PCI(P＜0.05).The nomogram model constructed based on the above risk factors has a C-index of 0.835 and an area under the receiver operating characteristic(ROC)the area under the curve(AUC)of 0.826.Conclusion:This study identified multiple risk factors for readmission in patients with coronary heart disease and T2DM 1 year after PCI.The constructed nomogram model can provide an effective tool for predicting the risk of readmission in clinical practice,and help medical staff develop personalized intervention measures to improve patient prognosis.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To calculate and analyze the research and development(R&D)efficiency,as well as the technological achievements transformation efficiency,of ten"Double First-Class"medical universities and ten medical universities in the accumulative science and technology evaluation metrics over the last five years,in order to make recommendations for improving technological achievements transformation management at these universities.Methods The study used both classic data envelopment analysis and super-effectiveness data envelopment analysis models to assess the effectiveness of the R&D stage and technological achievements transformation stage at the selected medical universities.Furthermore,the Malmquist model was used to measure the changes in the efficiency of the transformation of scientific and technological achievements of the medical universities as a whole.Results Among the 20 medical universities chosen,the output efficiency in the R&D stage was greater than that in the technological achievements transformation stage.Five medical universities were output-effective at the R&D stage,and two medical universities were in the technological achievements transformation stage.The overall efficiency of scientific and technological achievements transformation in medical universities was steadily improving.Conclusion Based on the current situation,medical universities in China should strengthen effective collaboration between industry,academia,and research,establish professional teams for technological achievements transformation,improve the technological achievements transformation management system,improve talent team construction,and increase technological achievements transformation efficiency.

Objective To discuss the potential mechanisms by which programmed cell death(PCD)might contribute to the pathogenesis of diabetic kidney disease(DKD).Methods Retrieve the datasets GSE30529 and GSE30122 from the Gene Expression Omnibus database and analyze them to obtain differentially expressed genes(DEGs)associated with DKD.Utilize the Gene Set Enrichment Analysis website,the ferroptosis database,and the autophagy database,along with relevant literature,to identify genes associated with apoptosis,necroptosis,pyroptosis,autophagy,and ferroptosis.Cross-reference these genes with the DKD DEGs to identify PCD-related genes that are differentially expressed in DKD.Perform Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses to explore the biological functions and potential pathways of the core genes.Conduct a protein-protein interaction network analysis to examine the interaction relationships of the target genes,and use the CytoHubba plugin in Cytoscape to screen for Hub genes.Results In the GSE30529 dataset,a total of 460 DEGs were identified,while the GSE30122 dataset yielded 992 DEGs.After merging and removing duplicates,932 DEGs were obtained.By intersecting these DEGs with PCD-related genes,61 apoptosis-related genes,7 necroptosis-related genes,39 pyroptosis-related genes,18 autophagy-related genes,and 16 ferroptosis-related genes associated with DKD were identified.The KEGG analysis results indicated that the DEGs related to apoptosis,necroptosis,pyroptosis,and autophagy in PCD were primarily enriched in pathways associated with diabetic complications,including the AGE-RAGE,IL-17,NF-κB,and TNF signaling pathways.In contrast,DEGs related to ferroptosis were mainly enriched in the fatty acid degradation pathway.GO enrichment analysis revealed that the biological processes of the differentially expressed PCD related genes in DKD were primarily involved in the regulation of signals such as NF-κB-inducing kinase/NF-κB,IL-1,and IL-17.Conclusions Differentially expressed PCD-related genes in DKD are mainly enriched in related signal pathways such as AGE-RAGE,IL-17,NF-κB and TNF,suggesting a critical role of PCD in the pathogenesis of DKD.