Objective:This study investigated the expression of C-X-C motif chemokine receptor 3 (CXCR3) on CD45RO? T cells in the peripheral blood of patients with Alzheimer′s disease (AD) and its association with clinical features.Methods:A total of 41 AD patients and 30 age-and sex-matched healthy controls (HCs) were recruited from the Department of Neurology at the Medical Division of PLA General Hospital between September 2022 and March 2024. Flow cytometry was used to quantify CXCR3 expression on CD45RO? T cell subsets in peripheral blood. Dementia severity in AD patients was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Spearman correlation analysis examined the relationship between CD45RO?CXCR3? T cell levels and cognitive function in the AD group. Receiver operating characteristic (ROC) curve analysis determined the predictive utility of CD45RO?CXCR3? T cells for AD, quantified by the area under the curve (AUC).Results:Compared to healthy controls, AD patients exhibited significantly elevated levels of CD8?CD45RO?CXCR3? T cells [17.8% (7.2%, 40.3%) vs. 8.2% (5.1%, 12.3%), Z=-2.59, P<0.05]. However, no significant differences were observed for CD4?CD45RO?CXCR3? T cells, CD4?CD45RO?CXCR3? T cells, or CD8?CD45RO?CXCR3? T cells ( P>0.05). Spearman correlation analysis revealed a negative correlation between CD8?CD45RO?CXCR3? T cell levels and cognitive scores (MMSE: r=-0.72, P<0.05; MoCA: r=-0.70, P<0.05). ROC analysis demonstrated an AUC of 0.81 for CD8?CD45RO?CXCR3? T cells in predicting AD, with a sensitivity of 59.0% and specificity of 93.3%. Conclusions:CXCR3 expression is significantly upregulated on CD8?CD45RO? T cells in AD patients, and its levels correlate with cognitive impairment severity. These findings suggest that CD8?CD45RO?CXCR3? T cells may serve as a potential biomarker for AD diagnosis and progression monitoring.

Objective:This study investigated the expression of C-X-C motif chemokine receptor 3 (CXCR3) on CD45RO? T cells in the peripheral blood of patients with Alzheimer′s disease (AD) and its association with clinical features.Methods:A total of 41 AD patients and 30 age-and sex-matched healthy controls (HCs) were recruited from the Department of Neurology at the Medical Division of PLA General Hospital between September 2022 and March 2024. Flow cytometry was used to quantify CXCR3 expression on CD45RO? T cell subsets in peripheral blood. Dementia severity in AD patients was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Spearman correlation analysis examined the relationship between CD45RO?CXCR3? T cell levels and cognitive function in the AD group. Receiver operating characteristic (ROC) curve analysis determined the predictive utility of CD45RO?CXCR3? T cells for AD, quantified by the area under the curve (AUC).Results:Compared to healthy controls, AD patients exhibited significantly elevated levels of CD8?CD45RO?CXCR3? T cells [17.8% (7.2%, 40.3%) vs. 8.2% (5.1%, 12.3%), Z=-2.59, P<0.05]. However, no significant differences were observed for CD4?CD45RO?CXCR3? T cells, CD4?CD45RO?CXCR3? T cells, or CD8?CD45RO?CXCR3? T cells ( P>0.05). Spearman correlation analysis revealed a negative correlation between CD8?CD45RO?CXCR3? T cell levels and cognitive scores (MMSE: r=-0.72, P<0.05; MoCA: r=-0.70, P<0.05). ROC analysis demonstrated an AUC of 0.81 for CD8?CD45RO?CXCR3? T cells in predicting AD, with a sensitivity of 59.0% and specificity of 93.3%. Conclusions:CXCR3 expression is significantly upregulated on CD8?CD45RO? T cells in AD patients, and its levels correlate with cognitive impairment severity. These findings suggest that CD8?CD45RO?CXCR3? T cells may serve as a potential biomarker for AD diagnosis and progression monitoring.

Objective:To analyze the influencing factors of achieving textbook outcome (TO) after pancreaticoduodenectomy (PD) in patients with pancreatic ductal adenocarcinoma, and to construct a nomograph model to explore its predictive value in TO.Methods:The clinical data of 205 patients with pancreatic ductal adenocarcinoma treated by PD in Henan University People's Hospital from January 2019 to December 2022 were analyzed retrospectively, including 88 males and 117 females with the age of (61.3±9.8) years old. Patients were divided into two groups based on whether they achieved TO after surgery: TO group ( n=113) and non-TO group ( n=92). Clinical data such as age, gender, intraoperative blood loss, operation time, blood transfusion volume, pancreatic CT value, and tumor differentiation degree were collected. Logistic regression analysis screened the influencing factors of PD postoperative TO and built a nomogram model. The performance of the nomogram model was evaluated using receiver operating characteristic (ROC) curve, calibration diagram, and decision curve analysis. Results:Multivariate logistic regression analysis showed that the higher the degree of tumor differentiation was in patients with pancreatic ductal adenocarcinoma (high differentiation to medium differentiation: OR=7.20, 95% CI: 1.20-43.28; high differentiation to low differentiation: OR=16.55, 95% CI: 2.01-136.11), CT value>38.45 Hu ( OR=0.29, 95% CI: 0.13-0.65), blood transfusion volume ≤350 ml ( OR=8.05, 95% CI: 2.94-22.01) and operative time ≤407.5 min ( OR=10.88, 95% CI: 3.90-30.41), the easier it was to achieve TO after PD (all P<0.05). Based on the above influencing factors, a nomogram model of the postoperative effect of PD on TO was established, and the consistency index of this column graph model was 0.863 (95% CI: 0.816-0.911). The sensitivity and specificity of ROC curve were 0.804 and 0.752, respectively. The calibration diagram showed that the calibration curve fits well with the ideal curve, and the decision curve showed that the model had obvious positive net benefit. Conclusion:The degree of tumor differentiation, CT value, blood transfusion volume, and operation time are independent influencing factors for the achievement of TO after PD in patients with pancreatic ductal adenocarcinoma, and the nomogram model constructed based on which has good predictive performance for TO.