Objective To construct programmed cell death protein-ligand 1(PD-LI)^hi tolerogenic dendritic cell (tol-DC) derived from bone marrow of DA rats and identify its immunological function. Methods DA rat bone marrow cells were extracted, combined with recombinant mouse granulocyte macrophage colony-stimulating factor and recombinant mouse interleukin (IL)-4, and cultured for 6 days in vitro to induce the differentiation of bone marrow cells into immature dendritic cells (imDC). Lipopolysaccharide was used to stimulate cell maturation and cultured for 2 days to collect mature dendritic cells (mDC). PD-L1 lentiviral vector virus stock solution or equivalent dose lentiviral stock solution was added, and PD-L1^hitol-DC and Lv-imDC were collected after culture for 2 days. The morphology of PD-L1^hitol-DC was observed by inverted phase contrast microscope and transmission electron microscope. Real-time fluorescence quantitative reverse transcription polymerase chain reaction, Western blotting and flow cytometry were used to detect the expression level of specific markers on cell surface. CD8⁺T cells derived from Lewis rat spleen were co-cultured with imDC, mDC, Lv-imDC and PD-L1^hitol-DC, respectively. The levels of inflammatory factors in the supernatant of each group were detected by enzyme-linked immunosorbent assay. The apoptosis of T cells and the differentiation of regulatory T cells (Treg) in each group were analyzed by flow cytometry. Results The morphology of PD-L1^hitol-DC modified by PD-L1 gene was consistent with tol-DC characteristics, and the expression levels of CD80, CD86 and major histocompatibility complex (MHC) on the surface were low. After mixed culture with CD8⁺ T cells, the levels of IL-10 and transforming growth factor (TGF) -β1 in the supernatant of PD-L1^hitol-DC group were higher, the levels of tumor necrosis factor (TNF) -α and IL-17A were lower, and the apoptosis of T cells and Treg differentiation were increased. Conclusions Overexpression of PD-L1 through lentiviral vectors may successfully induce the construction of bone-marrow derived PD-L1^hitol-DC in DA rats, promote the secretion of anti-inflammatory factors and T cell apoptosis, induce the differentiation of Treg, and inhibit the immune response of allogeneic CD8⁺T cells, which provides experimental basis for the next organ transplantation immune tolerance study.

OBJECTIVE To investigate the mechanism of the inhibitory effect of total flavonoids from Taraxacum mongolicum on high-fat diet-induced obesity in mice through modulation of intestinal flora. METHODS Twenty-four C57BL/6J mice were randomly divided into blank group， model group and T. mongolicum total flavonoid group， with 8 mice in each group. Except for the blank group， the other 2 groups were given a high-fat diet， while T. mongolicum total flavonoid group was given T. mongolicum total flavonoid [400 mg/（kg·d）] intragastrically， once a day， for 8 consecutive weeks. During the experiment， the food intake of each group of mice was recorded. After the last medication， the body mass， fat weight， blood lipid level and pathological changes of liver and epididymal fat in mice were evaluated to observe the effect of T. mongolicum total flavonoid on the treatment of obesity in mice. The changes in abundance and structure of intestinal flora in mice were detected by amplicon sequencing； the effects of T. mongolicum total flavonoids on fat metabolism related genes were analyzed by qPCR. RESULTS Compared with model group， the body weight of mice in T. mongolicum total flavonoids group was decreased significantly （P＜0.05）； the levels of total lipid cholesterol， triglycerides， and LDL cholesterol were all decreased significantly （P＜0.01）， and the level of HDL cholesterol was increased significantly （P＜0.01）； the fat indexes of inguinal white adipose tissue and epididymal white wind_lz@hactcm.edu.cn adipose tissue were significantly reduced （P＜0.05）； significant improvement in hepatocellular steatosis and adipose cytopathy were significantly improved； mRNA expressions of COX7A1 and COX8B were significantly upregulated （P＜0.05）. The results of bacterial colony detection showed that compared with the model group， there was a rising trend in the diversity of the bacterial colony in T. mongolicum total flavonoids group， and the Sobs index characterization and β diversity were increased significantly （P＜0.05）. Relative abundances of Blautia， norank_f_Ruminococcaceae， Bilophila， Alistipes， classified_f_Ruminococcaceae， Parabacteroides， norank_f_Desulfovibrionaceae， Anaerotruncus were significantly up-regulated（P＜0.05）， while those of Faecalibaculum， Erysipelatoclostridium， GCA-900066575， Tuzzerella， Lactobacillus， norank_f_norank_o_RF39， achnospiraceae_FCS020_group were significantly down-regulated （P＜0.05）. CONCLUSIONS T. mongolicum total flavonoids can reduce body mass， fat weight and blood lipid levels， and repair the pathological damage to liver and epididymal fat in obese mice， which is related to improving intestinal flora disorders caused by high-fat diet.

Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

The success of implementation research is closely tied to the institution's pre-implementation readiness. This study aims to explore the organizational readiness for change (ORC) and its influencing factors on primary healthcare settings in the implementation of the "Shared Medical Appointment for Diabetes (SMART) in China: design of an optimization trial" and to enhance ORC and provide insights to support the effective implementation of the program.

This study aimed to localize the workplace readiness questionnaire (WRQ) and validate its applicability for assessing readiness for implementation of evidence-based practices (EBP) in primary care settings in China. The localization of the instrument will provide a practical instrument for assessing organizational readiness for change (ORC).

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.