ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

Objective To analyze survival outcomes and influencing factors among patients with colorectal cancer in Yunnan Province. Methods Clinical data were retrospectively collected from 4 892 patients with colorectal cancer. Survival data were obtained through follow-up. Overall survival (OS) was calculated by using the Kaplan-Meier method. Univariate analysis was performed by applying the log-rank test. Meanwhile, multivariate analysis employed the Cox proportional hazards regression model. Results The 1-, 3-, 5-, and 10-year OS rates for the entire cohort were 91.90%, 74.40%, 64.40%, and 28.70%, respectively. Univariate analysis revealed that age, ethnicity, region, differentiation grade, TNM stage, clinical stage, metastatic status, histological type, and treatment modality (chemotherapy, radiotherapy, and surgery) were associated with patient prognosis (all P<0.05). Multivariate analysis identified age (HR=1.250), region (HR=1.262), differentiation grade (HR=0.761), clinical stage (HR=3.128), and treatment modality (chemotherapy, HR=0.644; radiotherapy, HR=1.605; surgery, HR=0.384) as independent factors affecting survival prognosis in patients with colorectal cancer (all P<0.001). Conclusion Age, region, clinical stage, and treatment modality are independent factors influencing survival among patients with colorectal cancer in Yunnan Province. In clinical practice, these factors should be integrated to develop individualized prevention and treatment strategies, thereby improving patient outcomes.

ObjectiveTo systematically evaluate the measurement content, psychometric properties and quality of evidence of patient-reported outcome measures (PROMs) for adolescents with spinal dysfunction based on International Classification of Functioning, Disability and Health-Children and Youth (ICF-CY) framework, Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) and modified GRADE approach. MethodsDatabases including CNKI, Wanfang Data, PubMed, Embase and Web of Science were systematically searched for studies assessing psychometric properties of PROMs targeting adolescents with spinal dysfunction. The methodological quality of included studies was evaluated using COSMIN Risk of Bias checklist, the psychometric properties were rated according to COSMIN criteria, and evidence quality was graded using modified GRADE approach. Item content of each PROM was coded following the ICF-CY linking rules. ResultsA total of 23 studies involving eight PROMs were included. Brace Questionnaire (BrQ), Italian Spine Youth Quality of Life Questionnaire (ISYQOL), Quality of Life Profile for Spinal Deformities (QLPSD), Spinal Appearance Questionnaire (SAQ), Scoliosis Japanese Questionnaire-27 (SJ-27) and Scoliosis Research Society-22 Revised Questionnaire (SRS-22r) were rated as grade B, while EuroQol Five-Dimension Youth Five-Level Questionnaire (EQ-5D-Y-5L) and Young Spine Questionnaire (YSQ) were rated as grade C. The eight PROMs were linked to six to 24 ICF-CY categories. BrQ covered the largest number of categories (n = 24), followed by SJ-27 (n = 19) and SRS-22r (n = 16). Except for SAQ which mainly focused on dimension of body functions and structures, all other PROMs covered both dimension of body functions and structures, and activities and participation, while BrQ, ISYQOL, SRS-22r and YSQ also covered dimension of environmental factors. Major methodological limitations included insufficient evidence for content validity, inappropriate factor-analysis approaches, incomplete reporting for test-retest reliability, and overall scarcity of evidence concerning measurement error, minimal important change (MIC) and responsiveness. ConclusionThe quality of PROMs in adolescents with spinal dysfunction varies. BrQ, ISYQOL, QLPSD, SAQ, SJ-27 and SRS-22r show application potential, yet further high-quality studies are required to supplement their psychometric evidence. EQ-5D-Y-5L and YSQ exist high-quality insufficient evidence. Selection of PROMs should comprehensively consider target population, measurement purpose, content coverage and quality of evidence. Further researches are needed to improve reporting quality.

A scientific and efficient comprehensive operation system for the transformation of clinical research achievements is an important guarantee to fully release the capability of public hospitals of the achievement transformation. A public hospital, focusing on the bottleneck problems faced in the process of transforming scientific and technological achievements, began to explore the construction of a comprehensive operation system for the transformation of clinical research achievements and implemented it throughout the hospital from October 2023. By improving the organizational structure and setting up full-time management positions; formulating supporting policies and perfecting the incentive mechanism; drawing a systematic portrait and creating a standard pathway; expanding the transformation platform and promoting coordinated development; innovating management services and strengthening digital empowerment; and highlighting publicity and education to enhance the capability of transformation, the hospital has effectively promoted the transformation of clinical research achievements. This practice can provide a reference for other hospitals to improve the management of clinical research achievements transformation and promote high-quality hospital development.

Objective:To screen for microRNAs(miRNAs)highly expressed in the serum exosomes(Exo)of esophageal squamous cell carcinoma(ESCC)patients and analyze their relationship with the clinicopathological characteristics of the patients,and to explore the potential of Exo-derived miRNAs as clinical auxiliary diagnostic markers for ESCC.Methods:Serum and relevant clinical data of 50 healthy subjects and 45 newly diagnosed ESCC patients admitted to the Fourth Hospital of Hebei Medical University between December 2021 and June 2023 were collected,serving as the control group and the ESCC group respectively.The Gene Expression Omnibus(GEO)database and qPCR were used to screen and identify the candidate miRNA for increased expression in the serum of ESCC patients-miR-1246.The diagnostic efficacy of serum miR-1246 for ESCC was analyzed by the receiver operating characteristic curve.The relationship between miR-1246 and the clinical feature progression of ESCC patients was analyzed by Logistic regression,and the relationship between miR-1246 and the clinicopathological characteristics of ESCC patients was analyzed by the χ2 test.Exosomes in the serum of the subjects were isolated,purified and characterized for verification.The expression of miR-1246 in Exo was detected by qPCR.ESCC KYSE150 and KYSE30 cells were routinely cultured.mimics-NC and miR-1246 mimics were transfected respectively into KYSE150 cells using Lipofectamine 2000.Inhibitor-NC and miR-1246 inhibitor were transfected into KYSE30 cells,which were respectively denoted as the minics-NC,miR-1246 mimics,inhibitor-NC and miR-1246-inhibitor groups.KYSE150 and KYSE30 cells were treated with Exo derived from KYSE150 cells in the mimics-NC and miR-1246 mimics groups.The proliferation,migration and invasion abilities of cells in each group were detected by the CCK-8 assay,scratch wound healing assay and Transwell chamber assay respectively.The expressions of Exo markers,epithelial-mesenchymal transition-related proteins,TET family methylcytosine dioxygenase 2(TET2)and cell adhesion molecule 1(CADM1)proteins in each group of cells were detected by WB assay.The targeting binding relationship between miR-1246 and TET2 and CADM1 was verified by the dual-luciferase reporter gene assay.Results:Bioinformatics screening showed that the miRNA with the most significant differential expression in the serum of ESCC patients was miR-1246.The serum Exo extracted from the patients conformed to the typical Exo characteristics.The expression level of serum Exo-miR-1246 in ESCC patients at stages Ⅰ-Ⅱ was significantly higher than that in healthy subjects(P<0.01);the level of serum Exo-miR-1246 in ESCC patients at stages Ⅲ-Ⅳ was significantly higher than that in patients at stages Ⅰ-Ⅱ(P<0.01).ROC curve analysis showed that Exo-miR-1246 in serum had a high value for auxiliary differential diagnosis of ESCC(P<0.05),and the auxiliary diagnostic efficacy of Exo-miR-1246 for the clinical progression of ESCC patients was higher than that of CEA and SCC-Ag(P<0.05).The combined detection of the three could further improve the efficacy of auxiliary diagnosis of patient staging(P<0.01).Exo-miR-1246 might be an independent risk factor for the clinical progression of ESCC patients(P<0.05).The expression level of serum Exo-miR-1246 was associated with the T-stage,N-stage and clinical stage of ESCC(P<0.01).Overexpression of miR-1246 could promote the proliferation,migration,invasion,epithelial-mesenchymal transition and inhibit apoptosis of ESCC cells,while inhibition of miR-1246 had the opposite effect.Database data analysis found that TET2 and CADM1 were the target genes of miR-1246.The dual-luciferase reporter gene assay confirmed that miR-1246 could directly bind to TET2 and CADM1 mRNA and inhibit their expressions(P<0.01).Treatment of KYSE150 and KYSE30 cells with Exo derived from cells overexpressing miR-1246 had the same effect as overexpressing miR-1246 in these cells.Conclusion:Exo-derived miR-1246 has the potential to be a clinical auxiliary diagnostic marker for ESCC.It may affect the occurrence and development of ESCC by regulating the expression levels of TET2 and CADM1.

Objective:To evaluate the efficacy of dexzopiclone combined with repetitive transcranial magnetic stimulation (rTMS) for post-stroke sleep disorders (PSSD) and its effects on sleep electroencephalography and neuroelectrophysiological parameters.Methods:180 PSSD patients admitted to Yulin First Hospital (December 2019-December 2020) were randomized into medication group ( n=90, dexzopiclone) and rTMS group ( n=90, dexzopiclone+rTMS). Outcomes included clinical efficacy, sleep quality [Pittsburgh Sleep Quality Index (PSQI), Self-Rating Scale for Sleep (SRSS)], electroencephalogram parameters [sleep latency (SL), total sleep time (TST), sleep efficiency], neuroelectrophysiological indices [bilateral motor thresholds], biochemical markers [S100β protein, brain-derived neurotrophic factor (BDNF)], adverse reactions, and 1-year recurrence rate. Results:After treatment, the rTMS group had a significantly higher efficacy (92.22%, 83/90) compared to the medication group (81.11%, 73/90) ( χ2=4.81, P=0.028). Compared to post-treatment, PSQI decreased to [7.47 (6.63,8.69) points vs. 13.56 (3.15,19.51) points] in the rTMS group and [9.56 (8.59,11.11) points vs. 14.01 (2.58,20.55) points] in the medication group ( U=8.82, 8.38; both P<0.001). SRSS scores decreased to [(15.23±2.88) points vs. (28.81±4.99) points) ( t=32.74, P<0.001) and (19.54±3.59) points vs. (28.15±4.71) points) ( t=19.68, P<0.001)], respectively. Compared to before treatment, the rTMS group had lower scores than the medication group ( U=7.80, t=8.88; P<0.01). SL reduced to (27.65±5.12) min vs. (44.92±8.21) min ( t=24.58, P<0.001) in rTMS group and (38.78±6.34) min vs. (45.23±8.56) min ( t=8.24, P<0.001) in medication groups. TST increased to (348.50±56.27) min vs. (299.21±52.14) min ( t=8.63, P<0.001) and (311.42±55.39) min vs. (275.65±52.23) min ( t=6.31, P<0.001), sleep efficiency improved to (70.96±12.33%) vs. (57.43±10.98%) ( t=11.01, P<0.001) and (62.37±11.28%) vs. (56.78±10.72%) ( t=4.82, P<0.001), while the rTMS group showed greater improvement ( t=4.46, 4.88; P<0.001). Compared to before treatment, left motor thresholds decreased to (55.65±2.48)% vs. (64.37±3.12)% and (61.76±3.17)% vs. (65.12±3.45)% post-treatment ( t=29.54, 9.63; P<0.001), with significant intergroup differences ( t=14.40, P<0.001). Right motor thresholds decreased to (56.28±3.45)% vs. (67.42±3.61)% and (60.89±3.39)% vs. (66.62±3.54)% ( t=29.94, 15.69; P<0.001), with intergroup differences ( t=9.04, P<0.01). Compared to before treatment, serum S100β levels decreased in both group post-treatment (23.65±3.23) ng/L vs. (65.37±7.89) ng/L and (29.76±3.61) ng/L vs. (63.48±7.34) ng/L ( t=71.19, 58.43; P<0.001), with lower levels in the rTMS group ( t=11.97, P<0.001). Compared to before treatment, BDNF increased to (554.48±69.78) ng/L vs. (502.82±64.11) ng/L and (524.90±67.66) ng/L vs. (505.12±64.45) ng/L post-treatment ( t=7.32, 2.84; P=0.001, 0.030), with higher levels in the rTMS group ( t=2.89, P=0.004). Adverse reaction rates were 4.44% (4/90) and 3.33% (3/90), respectively ( χ2=0.15, P=0.700). Recurrence rates were 1.18% (1/85) in the rTMS group and 3.90% (3/77) in the medication group ( χ2=0.37, P=0.544). Conclusion:The combination of dexzopiclone and repetitive transcranial magnetic stimulation (rTMS) demonstrates significant advantages and efficacy in treating post-stroke sleep disorders (PSSD). This approach comprehensively improves patients' sleep quality, EEG parameters and neuroelectrophysiological indicators while enhancing the regulatory effects of brain-derived neurotrophic factor (BDNF). Additionally, the therapy exhibits a favorable safety profile and prognosis.

Objective:To investigate whether paclitaxel (PTX) can induce immunogenic cell death (ICD) in vascular smooth muscle cells (VSMCs), and explore the new molecular mechanism of PTX-coated balloon angioplasty in intracranial atherosclerotic stenosis.Methods:(1) Cell culture and identification: VSMCs were induced into synthetic vascular smooth muscle cells (sVSMCs); the mRNA and protein expressions of smooth muscle protein 22-α (SM22-α) and α-smooth muscle actin (α-SMA) in VSMCsS and sVSMCs were detected by real-time fluorescent quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and Western blotting, respectively. Human acute monocytic leukemia cell line THP-1 was induced into dendritic cells (DCs); the CD86 and CD83 expressions in THP-1 and DCs were detected by flow cytometry. (2) Cell viability detection: cell counting kit-8 (CCK-8) assay was used to detect the cell viability of sVSMCs after 0, 0.01, 0.05, 0.5, 5, 10, 50, and 100 μmol/L PTX or under 0, 50, 100, 200, 400, and 600 mmHg (1 mmHg=0.133 kPa) pressures. (3) ICD marker detection: sVSMCs were collected and divided into blank-control group, dimethyl sulfoxide (DMSO) group and PTX group (cultured with 3.2 μmol/L PTX) at normal state and pressure procedure (188 mmHg), respectively; calreticulin (CRT) expression was detected by immunofluorescent staining; adenosine triphosphate (ATP) expression was detected by luciferase assay, and high mobility group protein B1 (HMGB1) expression was detected by enzyme-linked immunosorbent assay (ELISA). (4) ICD-related immune activation assay detection: sVSMCs and DCs were collected and divided into DCs group, PTX+DCs group (cultured with 3.2 μmol/L PTX), DCs+sVSMCs group, and PTX+DCs+sVSMCs group (cultured with 3.2 μmol/L PTX); CD86 and CD83 expressions were detected by flow cytometry; interleukin (IL)-2, IL-10 and interferon-γ (IFN-γ) levels were detected by ELISA. The sVSMCs, DCs and CD8 +T cells were collected and divided into sVSMCs group, sVSMCs+DCs group, sVSMCs+CD8 +T cell group, sVSMCs+DCs+CD8 +T cell group, PTX+sVSMCs group (cultured with 3.2 μmol/L PTX), and PTX+sVSMCs+DCs+CD8 +T cell group (cultured with 3.2 μmol/L PTX); proliferation of these cells was detected by cell clone formation assay. Results:(1) The SM22-α and α-SMA mRNA and protein expressions in the sVSMCs group were significantly lower than those in the VSMCs group ( P<0.05); rate of double-positive CD83 and CD86 in the DCs group was significantly higher than that in the THP-1 group ( P<0.05). (2) The sVSMCs viability decreased in a concentration-dependent manner after PTX treatment at concentrations of 0, 0.01, 0.05, 0.5, 5, 10, 50, and 100 μmol/L, respectively, with significant differences ( P<0.05); half maximal inhibitory concentration (IC 50) of PTX on sVSMCs was 3.2 μmol/L; no significant difference in sVSMCs viability after 3.2 μmol/L PTX treatment was noted under 0, 50, 100, 200, 400, and 600 mmHg pressures ( P>0.05). (3) Under normal state and pressure procedure, CRT fluorescent intensity of sVSMCs in the PTX group (42.00±3.50, 24.19±2.41) was significantly higher than that in the blank-control group (8.60±1.8, 8.42±1.7) and DMSO group (10.23±1.47, 9.71±1.01), ATP luminescence intensity (17 399.33±2 035.58, 17 445.67±2 449.34) was significantly higher than that in the blank-control group (9 021.33±726.84, 10 271.33±2 194.22) and DMSO group (11 977.33±960.91, 11 683.33±419.50), and HMGB1 concentration ([3 258.31±502.08] pg/mL, [3 265.27±246.06] pg/mL) was significantly higher than that in the blank-control group ([1 156.48±184.96] pg/mL, [1 205.20±196.36] pg/mL) and DMSO group ([1 309.59±75.03] pg/mL, [1 265.51±14.52] pg/mL, P<0.05). (4) The PTX+DCs+sVSMCs group had significantly higher CD83, CD86, IFN-γ and IL-2 expressions and lower IL-10 expression than the DCs group, PTX+DCs group, and DCs+sVSMCs group ( P<0.05); the PTX+sVSMCs group and PTX+sVSMCs+DCs+CD8 +T cell group had significantly lower clone formation rate compared with the sVSMCs group, sVSMCs+DCs group, sVSMCs+CD8 +T cell group, and sVSMCs+DCs+CD8 +T cell group ( P<0.05). Conclusion:PTX can promote ICD in VSMCs by promoting DCs activation and enhancing CD8 +T cell toxicity.

Objective To analyze the potential biological relationship between Alzheimer disease(AD)and chronic periodontitis(CP)by bioinformatics.Methods We analyzed two datasets of AD and CP from the Gene Expression Omnibus database,and differentially expressed genes(DEGs)were identified from these datasets.Weighted gene co-expression network analysis(WGCNA)was used to identify the most relevant modules.Functional enrichment analysis of shared genes was performed,and a protein-protein interaction(PPI)network was constructed.MCODE was used to identify key modules,and machine learning was used to discover key genes.In addition,Gene Set Enrichment Analysis(GSEA)and CIBERSORT were used to investigate KLRB1-related molecular pathways and immune cell distribu-tion.Results The study identified 18 genes common to both AD and CP.MCODE analysis revealed five pivotal genes,machine learning identified 13 genes for AD,eight for CP,and KLRB1 was determined as a common gene for AD and CP.GSEA demonstrated the intricate involvement of these genes in disease-related pathways.Immunocellular analysis underscored a significant association between KLRB1 and γδT cells.Conclusion This research highlighted KLRB1 as a key gene for AD and CP,providing new insights into their molecular linkages.