Objective: To explore the mechanism of action of hepatic leukemia factor (HLF) in diabetes mellitus and to construct a conditional animal model of mice with islet β ⁃cell⁃specific HLF gene knockout. Methods: At the cellular level , the effects of HLF inhibition or overexpression on the proliferation of MIN6 cells was verified by the CCK⁃8 assay. The effects of HLF inhibition or overexpression were detected at the mRNA level and protein level by Cre + / - mice (C57BL/6J) to obtain offspring mice. The genotypes of the mice were identified by the PCR method.The differences in the expression levels of the HLF gene at the mRNA and protein levels in islet β ⁃cell knockout mice (HLFflox/flox Cre + / - ) and control mice (HLFflox/flox ) were detected by RT⁃qPCR technology and Western blot technology to verify the knockout effect. At the same time , the islet tissues of the mice in two groups were taken to make paraffin sections and analyzed by hematoxylin⁃eosin (HE) staining. Results: HLF gene inhibition or overex⁃pression had no significant effect on the proliferation of MIN6 cells. When the HLF gene was inhibited in MIN6 cells , the mRNA expression level decreased by 74% compared with the control group , and the protein expression level decreased by 60% compared with the control group. After overexpressing the HLF gene , the mRNA expres⁃sion level was 2. 13 times compared with that of the control group , and the protein expression level was 1. 8 times compared with that of the control group. The mRNA expression level of the HLF gene in the knockout mice de⁃creased by 89% compared with the control group , and the protein expression level decreased by 65% compared with the control group. The results of HE staining showed that there was no significant difference in the cell mor⁃phology in the islet tissues between the knockout mice and the control mice. Inhibiting HLF increased the glycogen content in MIN6 cells by approximately 20% . Conclusion The HLF gene knockout mice are successfully con⁃structed , providing an animal model for studying the role of HLF in the pathogenesis of diabetes mellitus.

Objectives:Using data from the heart transplant patient dataset of our center,we aimed to develop a preoperative risk scoring model specifically suitable for the Chinese population undergoing heart transplantation.This model was established to predict the likelihood of graft failure within the first year post-surgery and classify recipients according to their risk level.Methods:A retrospective study was conducted at a single center on 1 210 consecutive heart transplant recipients between June 2004 and December 2022.Risk factor screening was performed using univariate and multivariate logistic regression analyses.Variable selection was carried out through a stepwise backward procedure based on the Akaike Information Criterion(AIC).The regression coefficients obtained from the final model were employed as weighting factors in the multifactor analysis.The study utilized the area under the receiver operating characteristic(ROC)area under curve(AUC)as a metric to evaluate the performance of the model.Patients were stratified into low,medium,and high-risk groups based on the distribution of the calculated scores.Survival analysis was conducted on the various risk groups using the Kaplan-Meier method,with statistical comparisons performed using the log-rank test.A significance level of P<0.05 was deemed statistically significant.Results:A risk scoring model,denoted as the heart transplant(HTx)score,was developed,comprising 11 variables and yielding a total score of 20.6 points.In comparison to the low-risk group,the OR for 1-year graft failure in the medium-risk group was 2.0(95%CI:1.1-3.6,P=0.02),while the high-risk group had an OR of 9.8(95%CI:5.4-17.7,P<0.01).The risk scoring model exhibited strong discriminative ability with an AUC of 0.712(95%CI:0.646-0.778)and an internally validated bias-corrected AUC of 0.713.The results of the Hosmer-Lemeshow goodness-of-fit test indicated that the predictive model demonstrated a strong calibration ability(Hosmer-Lemeshow χ2=2.92,P=0.71).Within the cohort,the AUC values for the IMPACT score,UNOS score,RSS score,Mayo score,BO score,and TRS score models were 0.645,0.651,0.632,0.589,0.610,and 0.604,respectively.These findings suggest that the HTx scoring model exhibited superior predictive performance compared to the aforementioned models in forecasting outcomes within our cohort.The Kaplan-Meier survival analysis revealed statistically significant differences in long-term survival rates between the three risk groups,a noticeable decrease in long-term survival rates were observed with increasing levels of HTx risk stratification(P<0.05).Conclusions:Present results indicate a significant association between the developed HTx risk scores and graft failure within the initial year post-surgery,present model effectively categorizes the heart transplant recipients into low,medium,and high-risk groups and is valuable for risk stratification.

Objectives:Using data from the heart transplant patient dataset of our center,we aimed to develop a preoperative risk scoring model specifically suitable for the Chinese population undergoing heart transplantation.This model was established to predict the likelihood of graft failure within the first year post-surgery and classify recipients according to their risk level.Methods:A retrospective study was conducted at a single center on 1 210 consecutive heart transplant recipients between June 2004 and December 2022.Risk factor screening was performed using univariate and multivariate logistic regression analyses.Variable selection was carried out through a stepwise backward procedure based on the Akaike Information Criterion(AIC).The regression coefficients obtained from the final model were employed as weighting factors in the multifactor analysis.The study utilized the area under the receiver operating characteristic(ROC)area under curve(AUC)as a metric to evaluate the performance of the model.Patients were stratified into low,medium,and high-risk groups based on the distribution of the calculated scores.Survival analysis was conducted on the various risk groups using the Kaplan-Meier method,with statistical comparisons performed using the log-rank test.A significance level of P<0.05 was deemed statistically significant.Results:A risk scoring model,denoted as the heart transplant(HTx)score,was developed,comprising 11 variables and yielding a total score of 20.6 points.In comparison to the low-risk group,the OR for 1-year graft failure in the medium-risk group was 2.0(95%CI:1.1-3.6,P=0.02),while the high-risk group had an OR of 9.8(95%CI:5.4-17.7,P<0.01).The risk scoring model exhibited strong discriminative ability with an AUC of 0.712(95%CI:0.646-0.778)and an internally validated bias-corrected AUC of 0.713.The results of the Hosmer-Lemeshow goodness-of-fit test indicated that the predictive model demonstrated a strong calibration ability(Hosmer-Lemeshow χ2=2.92,P=0.71).Within the cohort,the AUC values for the IMPACT score,UNOS score,RSS score,Mayo score,BO score,and TRS score models were 0.645,0.651,0.632,0.589,0.610,and 0.604,respectively.These findings suggest that the HTx scoring model exhibited superior predictive performance compared to the aforementioned models in forecasting outcomes within our cohort.The Kaplan-Meier survival analysis revealed statistically significant differences in long-term survival rates between the three risk groups,a noticeable decrease in long-term survival rates were observed with increasing levels of HTx risk stratification(P<0.05).Conclusions:Present results indicate a significant association between the developed HTx risk scores and graft failure within the initial year post-surgery,present model effectively categorizes the heart transplant recipients into low,medium,and high-risk groups and is valuable for risk stratification.

Heart failure represents a significant public health challenge in China at present.The technology development of left ventricular assist device has become a therapy option for end-stage heart failure patients.The third generation left ventricular assist device has undergone significant improvements in its principle,structure,size,mechanical stability,biocompatibility,and many other aspects.In recent years,multiple products have been put into clinical application,meeting the need of heart failure patients with implantation indications.This article mainly reviews the technological development,clinical application,available domestic and abroad products,and future prospects of the third generation domestic left ventricular assist device.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective     To evaluate the risk factors for postoperative in-hospital mortality in elderly patients receiving cardiac valvular surgery, and develop a new prediction models using the least absolute shrinkage and selection operator (LASSO)-logistic regression. Methods     The patients≥65 years who underwent cardiac valvular surgery from 2016 to 2018 were collected from the Chinese Cardiac Surgery Registry (CCSR). The patients who received the surgery from January 2016 to June 2018 were allocated to a training set, and the patients who received the surgery from July to December 2018 were allocated to a testing set. The risk factors for postoperative mortality were analyzed and a LASSO-logistic regression prediction model was developed and compared with the EuroSCOREⅡ. Results     A total of 7 163 patients were collected in this study, including 3 939 males and 3 224 females, with a mean age of 69.8±4.5 years. There were 5 774 patients in the training set and 1 389 patients in the testing set. Overall, the in-hospital mortality was 4.0% (290/7 163). The final LASSO-logistic regression model included 7 risk factors: age, preoperative left ventricular ejection fraction, combined coronary artery bypass grafting, creatinine clearance rate, cardiopulmonary bypass time, New York Heart Association cardiac classification. LASSO-logistic regression had a satisfying discrimination and calibration in both training [area under the curve (AUC)=0.785, 0.627] and testing cohorts (AUC=0.739, 0.642), which was superior to EuroSCOREⅡ. Conclusion     The mortality rate for elderly patients undergoing cardiac valvular surgery is relatively high. LASSO-logistic regression model can predict the risk of in-hospital mortality in elderly patients receiving cardiac valvular surgery.

Objectives:To evaluate and predict the risk for in-hospital mortality in elderly patients receiving cardiac valvular surgery preferably,we developed a new prediction model using machine learning. Methods:Clinical data including baseline characteristics,peri-operative data and primary endpoint of 7 163 elderly patients aged 65 years or older undergoing cardiac valvular surgery from January 2016 to December 2018 from 87 hospitals were collected from the Chinese Cardiac Surgery Registry(CCSR).Patients from January 2016 to June 2018 were assigened to the training cohort(n=5 774)and patients from July to December 2018 were assigened to the validation cohort(n=1 389).The primary endpoint was in-hospital mortality.Machine learning algorithms were used to analyze risk factors and develop prediction model. Results:Overall in-hospital mortality was 4.1%.Linear discriminant analysis(LDA),support vector classification(SVC)and logistic regression(LR)models in the training cohort all have high AUCs and low Brier scores,with good discrimination and calibration.In validation cohort,the AUC of LDA,SVC and LR were 0.744,0.744 and 0.746 respectively,which were significantly better than that of 0.642 using the European System for Cardiac Operative Risk Evaluation II(EuroSCORE II)model(P<0.05). Conclusions:The mortality rate for elderly patients undergoing cardiac valvular surgery is relatively high.LDA,SVC and LR can predict the risk for in-hospital mortality in elderly patients receiving cardiac valvular surgery with high accuracy.

Objective To evaluate the effect of extracorporeal membrane oxygenation (ECMO) on early allograft dysfunction (EAD) after heart transplantation. Methods Clinical data of 614 heart transplant recipients were retrospectively analyzed. All recipients were divided into the ECMO group (n=43) and non-ECMO group (n=571) according to postoperative application of ECMO. In the ECMO group, the conditions of recipients undergoing ECMO after heart transplantation were summarized. Perioperative status and long-term prognosis of recipients were compared between two groups. Results Among 43 recipients undergoing ECMO, 17 cases underwent thoracotomy due to bleeding, 10 cases of infection, 4 cases of venous thrombosis of the lower limbs, and 1 case of stroke, respectively. Twenty-six recipients were recovered and discharged after successful weaning from ECMO, six died during ECMO support, six died after weaning from ECMO, five received retransplantation due to unsuccessful weaning from ECMO, and only one survived after retransplantation. Compared with the non-ECMO group, intraoperative cardiopulmonary bypass duration was significantly longer, the proportion of recipients requiring postoperative intra-aortic balloon pump (IABP), dialysis due to renal insufficiency, reoperation for hemostasis, infection, mechanical ventilation time≥96 h and tracheotomy was significantly higher, and the length of postoperative intensive care unit (ICU) stay was significantly longer in the ECMO group (all P < 0.05). The survival rate after discharge and 90-d survival rate in the ECMO group were 63% and 96%, significantly lower than 97% and 100% in the non-ECMO group (both P < 0.05). Survival analysis showed that the long-term survival rate in the ECMO group was significantly lower than that in the non-ECMO group (P < 0.05). After excluding the recipients who died within 90 d after heart transplantation, no significant difference was observed in the long-term survival rate (P > 0.05). Conclusions ECMO is an effective treatment of EAD after heart transplantation. The short-term survival rate of recipients using ECMO after heart transplantation is lower than that of those who do not use ECMO, and there is no significant difference in long-term survival of recipients surviving 90 d after heart transplantation.

Fusobacterium nucleatum (Fn) is an oral anaerobic bacterium that has recently been found to colonize on the surface of colorectal cancer cells in humans, and its degree of enrichment is highly negatively correlated with the prognosis of tumor treatment. Numerous studies have shown that Fn is involved in the occurrence and development of colorectal cancer (CRC), and Fn interacts with multiple components in the tumor microenvironment to increase tumor resistance. In recent years, researchers have begun using nanomedicine to inhibit Fn's proliferation at the tumor site or directly target Fn to treat CRC. This review summarizes the mechanism of Fn in promoting CRC and the latest research progress on Fn-related CRC therapy using different nanomaterials. Finally, the applications perspective of nanomaterials in Fn-promoted CRC therapy was prospected.
Humans ; Colorectal Neoplasms/pathology* ; Fusobacterium nucleatum/genetics* ; Base Composition ; RNA, Ribosomal, 16S ; Phylogeny ; Sequence Analysis, DNA ; Tumor Microenvironment

Objective:To study the cross-sectional morphology of root canal system of Tibetan mandibular incisors by micro-CT.Methods:From October 2019 to October 2020, one hundred and thirty-six mandibular incisors were collected from Tibetan patients [(51.9±16.4) years old, range from 25 to 80 years] who underwent teeth extraction due to severe periodontitis at the Department of Stomatology, Tibetan Hospital of Traditional Tibetan Medicine, including 84 mandibular central incisors and 52 mandibular lateral incisors. These teeth were scanned at 23 μm voxel size resolution. Root lengths from cemento-enamel junction (CEJ) to apex of mandibular incisors were measured. According to the length, the root was divided as cervical 1/3, middle 1/3 and apical 1/3, and the numbers of root canals were recorded simultaneously. The major diameter, minor diameter, and dimension were measured per millimeter in cross section for mandibular incisor with single root canal, and the ratio of major diameter to minor diameter (D max/D min) as well as roundness were calculated for morphological analysis. The diversions and conversions from CEJ to apex in cross section were recorded for mandibular incisor with multiple root canals. Results:For mandibular central incisors with single root canal, the D max/D min was highest in middle 1/3 of the root [1.99 (1.31, 2.79)], which was significantly higher than cervical 1/3 and apical 1/3 ( P=0.010, P=0.003). The roundness was least in middle 1/3 [0.47 (0.31, 0.66)], which was significantly lower than cervical 1/3 and apical 1/3 ( P=0.010, P=0.001). For mandibular central incisor with multiple root canals, the highest incidence of multiple root canals was 40.5% (34/84), and mainly detected in middle 1/3 of the root [32.1% (27/84)]. For mandibular lateral incisor with single root canal, the roundness was greatest in apical 1/3 of the root [0.61 (0.49, 0.71)], which was significantly higher than cervical 1/3 ( P=0.001) and middle 1/3 ( P=0.001). The highest incidence of multiple root canals was 34.6% (18/52), all of which were detected in apical 1/3. Conclusions:In Tibetan mandibular central incisors, the cross-sectional morphology of root canals was long and narrow in middle 1/3, and multiple root canals were more likely to be found here. In Tibetan mandibular lateral incisors, the cross-sectional anatomy of root canal was relatively close to circle in apical 1/3, but the shape was still so irregular that one root canal may divide into two here.