Composition of the polysaccharide from Bupleurum scorzonerifolium Willd. was studiedby high resolution capillary gas chromatography after hydrolysis and followed by acetylation and esterifica-tion of the hydrolysate. The results showed that it is composed of arabinose, ribose, D-xylose, D-man-nose, D-glucose and D-galactose, with a molar ratio of 0. 106 : 2. 652 : 4. 070: 0. 519 : 0. 930 : 2. 518.

Objective To construct and explore the in vivo and in vitro D-galactose induced cognitive impairment models and evaluate the application value of the combined models in the study of cognitive impairments.Methods The cognitive impairment mice model induced by D-gal was prepared by continuous intraperitoneal injection of D-gal saline solution for 8weeks, followed by detection of learning and memory functions with Morris water maze.The related molecular markers in the brain tissue were assayed to evaluate the effect and application value.D-gal cell model was prepared by adding D-gal in different concentrations into the cell cultural medium of neurons harvested from the hippocampus of young mice.The effect and application value were evaluated by detecting the molecular markers related to the level of cell injury.Results The Morris water maze on the D-gal model showed that the learning and memory functions of mice in the model group were significantly lower than those in the control group.Meanwhile, the levels of apoptosis and oxidative stress in the model group were significantly higher than those in the control group.In the hippocampal neuron model of D-gal, the neurons showed a dose-dependent morphologic and functional change with the increase of D-gal dose and the levels of apoptosis and oxidative stress were significantly higher than those in the negative control.Conclusion D-galactose can be successfully used to induce cognitive impairment models both in vivo and in vitro through the decrease of the learning and memory functions of mice and induction of apoptosis and oxidative stress in neurons.Combined application of the two models of D-gal can be one of effective and promising tools for the study of cognitive impairment and pharmacodynamic evaluation.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

Objective To investigate the protective effects and mechanisms of sulodexide on renal fibrosis induced by prolonged warm ischemia. Methods An in vivo ischemia-reperfusion injury (IRI) model was established in rats, which were randomly divided into Sham group, IRI 60 min group (IRI group), and IRI 60 min + sulodexide group (IRI+SDX group), with 20 rats in each group. Pathological examination was used to evaluate renal tissue injury and fibrosis levels in each group. Immunohistochemistry was performed to detect the expression levels of kidney injury molecule (KIM)-1, intercellular adhesion molecule (ICAM)-1, von Willebrand factor (vWF), transforming growth factor (TGF)-β, α-smooth muscle actin (SMA), and type I collagen (COL-1). Immunofluorescence staining was used to detect CD31 expression. Real-time quantitative polymerase chain reaction was employed to measure the expression of KIM-1, ICAM-1, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 in renal tissues. Transmission electron microscopy was used to observe the structure of the renal glycocalyx. Evans blue dye was injected to assess renal vascular permeability. Rat survival was recorded, and serum levels of syndecan (SDC)-1, heparan sulfate (HS) and serum creatinine were measured. An ex vivo perfusion model was also established, with rats randomly assigned to either the hypothermic oxygenated machine perfusion (HOPE) group or the HOPE+SDX group (five rats per group). Perfusion parameters were recorded after 2 hours of ex vivo perfusion. Results One day after reperfusion, compared with the Sham group, the IRI group exhibited more severe renal tissue injury, higher tubular injury scores, increased expression of KIM-1, ICAM-1 and vWF, decreased CD31 expression, elevated serum levels of SDC-1 and HS, increased vascular permeability, and higher expression of TNF-α, IL-1β and IL-6. Compared with the IRI group, the IRI+SDX group showed reduced renal tissue injury, lower tubular injury scores, decreased expression of KIM-1, ICAM-1 and vWF, increased CD31 expression, lower serum levels of SDC-1 and HS, decreased vascular permeability, and reduced expression of TNF-α, IL-1β and IL-6 (all P < 0.05). Ten days after reperfusion, renal tissue injury was further alleviated in the IRI+SDX group. Twenty-five days after reperfusion, the IRI+SDX group exhibited decreased expression of TGF-β, α-SMA, and COL-1, as well as reduced collagen deposition area (all P < 0.05). Compared with the HOPE group, the HOPE+SDX group showed increased renal perfusion flow and decreased intrarenal vascular resistance (both P < 0.01). Conclusions Sulodexide may alleviates renal IRI and fibrosis caused by prolonged warm ischemia by inhibiting inflammatory responses and protecting vascular endothelial glycocalyx.

Objective To establish and optimize a mouse myocardial infarction (MI) model, and to use twice limb lead ECGs immediately after coronary ligation and 4 h after surgery to evaluate the occurrence of myocardial infarction. Methods Twenty-nine male C57BL/6J mice were anesthetized with isoflurane. then a myocardial infarction model was established by ligating the left anterior descending (LAD) coronary artery through the third/fourth intercostal space of left anterior chest. Immediate and 4 h postoperative limb lead ECGs were performed. Twenty-four hours after surgery, the chest was opened and the occurrence of myocardial infarction was evaluated. The heart samples were taken for TTC staining to determine the infarct area and calculate the infarct area. Results During the mice underwent coronary artery ligation the intraoperative mortality was 6.8% (2/29), and the early postoperative (<4 h) mortality was 10.3% (3/29). The 24 h survival rate was 82.8% (24/29). 24 hours after TTC staining confirmed the occurrence of infarction, the myocardial infarction model was established. The success rate of the model was 79.3% (23/29), and the average infarct size (infarcted myocardial weight / whole ventricular weight) was (28 ± 6)%; The mice successfully established by the model showed obvious ST-T changes in the ECG at 4 hours after surgery, suggesting that a myocardial infarction has occurred. Conclusions The mouse myocardial infarction model was successfully established. The combined use of ECG immediately after surgery and 4 h after surgery could be used as a rapid and non-invasive evaluation method for mouse myocardial infarction.

METRNL is a recently identified secreted protein with emerging functions. This study is to find major cellular source of circulating METRNL and to determine METRNL novel function. Here, we show METRNL is abundant in human and mouse vascular endothelium and released by endothelial cells using endoplasmic reticulum-Golgi apparatus pathway. By creating endothelial cell-specific Metrnl knockout mice, combined with bone marrow transplantation to produce bone marrow-specific deletion of Metrnl, we demonstrate that most of circulating METRNL (approximately 75%) originates from the endothelial cells. Both endothelial and circulating METRNL decrease in atherosclerosis mice and patients. By generating endothelial cell-specific Metrnl knockout in apolipoprotein E-deficient mice, combined with bone marrow-specific deletion of Metrnl in apolipoprotein E-deficient mice, we further demonstrate that endothelial METRNL deficiency accelerates atherosclerosis. Mechanically, endothelial METRNL deficiency causes vascular endothelial dysfunction including vasodilation impairment via reducing eNOS phosphorylation at Ser1177 and inflammation activation via enhancing NFκB pathway, which promotes the susceptibility of atherosclerosis. Exogenous METRNL rescues METRNL deficiency induced endothelial dysfunction. These findings reveal that METRNL is a new endothelial substance not only determining the circulating METRNL level but also regulating endothelial function for vascular health and disease. METRNL is a therapeutic target against endothelial dysfunction and atherosclerosis.