Objective:To explore the relevant risk factors and prognosis of patients with intrahepatic cholangiocarcinoma (ICC) who experienced recurrence within 6 months after surgeryMethods:This retrospective study included a total of 259 patients with ICC a treated at He'nan Provincial People's Hospital and He'nan Cancer Hospital from Jan 2018 to Jan 2020. The clinical and pathological data ,differences between the group with recurrence within 6 months and the group without recurrence within 6 months were compared using the chi-square test. Logistic regression analysis was used to determine the relevant risk factors for recurrence within 6 months. Kaplan-Meier method was used to construct survival and recurrence curves, and survival rates were calculated.Results:The overall survival and recurrence-free survival of patients in the group with recurrence within 6 months were significantly shorter. CA19-9, tumor longitudinal diameter, microvascular invasion, and neural invasion were identified as independent risk factors for recurrence within 6 months after ICC surgery ( P<0.001). Conclusion:The patient population experiencing recurrence within 6 months after ICC surgery has an extremely poor prognosis and possesses a specific tumor microenvironment. CA19-9, tumor longitudinal diameter, microvascular invasion, and neural invasion were identified as independent risk factors for recurrence within 6 months after ICC surgery.

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 construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.

Objective:To explore the prognostic value of systemic immune-inflammatory index(SII)combined with tumor burden score (TBS) (hereinafter referred to as STS) in patients with intrahepatic cholangiocarcinoma (ICC) after radical resection, and to construct a nomogram model.Methods:The clinical data (including the degree of tumor differentiation, vascular cancer thrombus, and lymph node metastasis, etc.) of 258 ICC patients who received radical resection at People′s Hospital of Zhengzhou University (170 cases, training set) and Cancer Hospital of Zhengzhou University (88 cases, validation set) from January 1, 2016 to January 31, 2020 were retrospectively analyzed and graded by SII, TBS and STS. Multivariate Cox regression analysis were used to identify independent factors affecting the prognosis of patients with ICC. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC) were drawn to evaluate the predictive efficiency of SII, TBS and STS in the overall survival of patients with ICC after radical resection. The nomogram prediction model was constructed and evaluate the performance of nomogram model using consistency index (C-index) and calibration curve.Results:Among 170 ICC patients in the training set, there were 106 cases of SII grade 1 and 64 cases of SII grade 2; 137 cases of TBS grade 1 and 33 cases of TBS grade 2; and 98 cases of STS grade 1, 47 cases of STS grade 2, and 25 cases of STS grade 3. Among 88 ICC patients in the validation set, there were 33 cases of SII grade 1 and 55 cases of SII grade 2; 66 cases of TBS grade 1 and 22 cases of TBS grade 2; and 30 case of STS grade 1, 39 cases of TBS grade 2, and 19 cases of TBS grade 3.The multivariate Cox regression analysis showed that tumor differentiation degree (highly differentiated vs. moderately differentiated HR=0.157, 95% confidence interval(95% CI) 0.045 to 0.546, highly differentiated vs. poorly differentiated HR=0.452, 95% CI 0.273 to 0.750), STS (grade 3 vs. grade 2 HR=1.966, 95% CI 1.148 to 3.469; grade 3 vs. grade 1 HR=1.405, 95% CI 0.890 to 2.216), vascular cancer thrombus ( HR=2.006, 95% CI 1.313 to 3.066), nerve invasion ( HR=1.865, 95% CI 1.221 to 2.850), and lymph node metastasis ( HR=1.802, 95% CI 1.121 to 2.896) were independent influencing factors of overall survival in ICC patients after radical resection (all P<0.05). The Kaplan-Meier survival curve showed that SII, TBS, and STS were independent influencing factors of overall survival in ICC patients (all P<0.05). The results of ROC analysis showed that the areas under the curve of SII, TBS and STS in predicting overall survival of ICC patients after radical resection were 0.566 (95% CI 0.479 to 0.652), 0.585 (95% CI 0.499 to 0.672), and 0.657 (95% CI 0.522 to 0.692), respectively. Tumor differentiation, vascular tumor thrombus, nerve invassion, lymph node metastasis, and STS were included to constract the nomogram model. The C-indexes of the training set and validation set based on the nomogram model were 0.792 (95% CI 0.699 to 0.825) and 0.776 (95% CI 0.716 to 0.833), respectively. The calibration curves of the survival rate of the training set and the validation set were close to the reference lines, and the nomogram model had better predictive ability in both the training set and the validation set. Conclusions:Preoperative STS grading is an effective and practical predictor of overall survival in ICC patients after radical section. Compared with SII and TBS alone, it has better predictive value for the prognosis of patients with ICC.

Radiotherapy is widely used in the management of advanced colorectal cancer (CRC). However, the clinical efficacy is limited by the safe irradiated dose. Sensitizing tumor cells to radiotherapy via interrupting DNA repair is a promising approach to conquering the limitation. The BRCA1-BARD1 complex has been demonstrated to play a critical role in homologous recombination (HR) DSB repair, and its functions may be affected by HERC2 or BAP1. Accumulated evidence illustrates that the ubiquitination-deubiquitination balance is involved in these processes; however, the precise mechanism for the cross-talk among these proteins in HR repair following radiation hasn't been defined. Through activity-based profiling, we identified PT33 as an active entity for HR repair suppression. Subsequently, we revealed that BAP1 serves as a novel molecular target of PT33 via a CRISPR-based deubiquitinase screen. Mechanistically, pharmacological covalent inhibition of BAP1 with PT33 recruits HERC2 to compete with BARD1 for BRCA1 interaction, interrupting HR repair. Consequently, PT33 treatment can substantially enhance the sensitivity of CRC cells to radiotherapy in vitro and in vivo. Overall, these findings provide a mechanistic basis for PT33-induced HR suppression and may guide an effective strategy to improve therapeutic gain.

Objective:To establish and validate a preoperative differentiateon model of intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular carcinoma (CHC) based on the inflammatory markers and conventional clinical indicators.Methods:The clinical data of 116 patients with ICC or CHC admitted to Henan Provincial People's Hospital from January 2018 to March 2023 were retrospectively analyzed, including 74 males and 42 females, aged (58.5±9.4) years old. The data of 83 patients were used to establish the differentiation model as the training group, including 50 cases of ICC and 33 cases of CHC. The data of 33 patients were used to validate the model as the validation group, including 20 cases of ICC and 13 cases of CHC. The clinical data including the platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), prognostic inflammatory index (PII), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were collected and analyzed. The receiver operating characteristic (ROC) curve was used to analyze the best cut-off values of PLR, SII, PII, PNI, NLR and LMR. Univariate and multivariate logistic regression analysis were used to determine the differential factors between ICC and CHC. The R software was used to draw the nomogram, calculate the area under the curve (AUC) to evaluate the model accuracy, and draw the calibration chart and the decision curve to evaluate the predictive efficacy of the model.Results:Univariate logistic regression analysis showed that liver cirrhosis, history of hepatitis, alpha fetoprotein, carbohydrate antigen 199, gamma-glutamyltransferase (GGT), PLR, PNI and inflammation score (IS) could be used to differentiate ICC from CHC (all P<0.05). The indicators identified in univariate analysis were included in multivariate logistic regression analysis. The results showed that absence of liver cirrhosis, GGT>60 U/L, PNI>49.53, and IS<2 indicated the pathology of ICC (all P<0.05). Based on the above four factors, a nomogram model was established to differentiate the ICC and CHC. The AUC of ROC curve of the nomogram model in the training and validation groups were 0.851 (95% CI: 0.769-0.933) and 0.771 (95% CI: 0.594-0.949), respectively. The sensitivities were 0.760 and 0.750, and the specificities were 0.818 and 0.769, respectively. The calibration chart showed that the predicted curve fitted well to the reference line. The decision curve showed that the model has a clear positive net benefit. Conclusion:The nomogram model based on inflammatory markers showed a good differentiation performance of ICC and CHC, which could benefits the individualized treatment.

Parkinson's disease (PD) is the most common neurodegenerative movement disease. It is featured by abnormal alpha-synuclein (α-syn) aggregation in dopaminergic neurons in the substantia nigra. Macroautophagy (autophagy) is an evolutionarily conserved cellular process for degradation of cellular contents, including protein aggregates, to maintain cellular homeostasis. Corynoxine B (Cory B), a natural alkaloid isolated from Uncaria rhynchophylla (Miq.) Jacks., has been reported to promote the clearance of α-syn in cell models by inducing autophagy. However, the molecular mechanism by which Cory B induces autophagy is not known, and the α-syn-lowering activity of Cory B has not been verified in animal models. Here, we report that Cory B enhanced the activity of Beclin 1/VPS34 complex and increased autophagy by promoting the interaction between Beclin 1 and HMGB1/2. Depletion of HMGB1/2 impaired Cory B-induced autophagy. We showed for the first time that, similar to HMGB1, HMGB2 is also required for autophagy and depletion of HMGB2 decreased autophagy levels and phosphatidylinositol 3-kinase III activity both under basal and stimulated conditions. By applying cellular thermal shift assay, surface plasmon resonance, and molecular docking, we confirmed that Cory B directly binds to HMGB1/2 near the C106 site. Furthermore, in vivo studies with a wild-type α-syn transgenic drosophila model of PD and an A53T α-syn transgenic mouse model of PD, Cory B enhanced autophagy, promoted α-syn clearance and improved behavioral abnormalities. Taken together, the results of this study reveal that Cory B enhances phosphatidylinositol 3-kinase III activity/autophagy by binding to HMGB1/2 and that this enhancement is neuroprotective against PD.

Objective:A predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma (ICC) patients after curative resection was constructed based on the albumin-bilirubin score and tumor burden score (ATS) grade, and the predictive performance of the nomogram model was evaluated.Methods:Retrospective analysis of clinical data was made, from ICC patients who underwent curative resection at Zhengzhou University People's Hospital and Zhengzhou University Cancer Hospital from January 2016 to January 2020. A total of 258 patients were included in the study, with 140 males and 118 females, with an average age of (56.5±9.5) years. The 258 ICC patients were randomly divided into a training set ( n=174) and a testing set ( n=84) in a 7∶3 ratio. Single-factor and multi-factor Cox regression analyses were performed to identify prognostic factors for ICC patients of the training set, and then a nomogram model was constructed. The performance of the nomogram model was evaluated by using the concordance index (C-index), calibration curve, and risky decision curve analysis. Results:In the training set, univariate Cox regression analysis indicated that albumin-bilirubin (ALBI), tumor burden score (TBS), carcinoembryonic antigen (CEA), tumor differentitation, lymphvascular invasion and ATS significantly influenced overall survival after radical resection for ICC (all P<0.05). Multifactorial Cox regression analysis revealed that ATS grade, CEA, tumor differentiation, lymphovascular invasion, and AJCC N stage are independent risk factors for the prognosis of ICC patients after curative resection (all P<0.05). Assessment of the postoperative survival prediction model based on multifactorial Cox regression yielded a C-index of 0.775(95% CI: 0.747-0.841) for the training set and 0.731(95% CI: 0.668-0.828) for the testing set. The calibration curves for both the training and testing sets indicated strong predictive capability of the model. Additionally, the risk decision curve also suggested high net benefit of the model. Conclusions:The preoperative ATS grade is an independent factor affecting the survival after ICC radical resection. The nomogram model constructed based on ATS grade demonstrates excellent predictive value for postoperative prognosis in ICC patients.

Objective:To systematically understand the reform progress of disease prevention and control system in China.Methods:The literature regarding the reform of China′s disease prevention and control system was searched by using the keywords including disease prevention and control, center for disease prevention and control (CDC), disease control, reform, and system from 2003 to 2020 in China CNKI, Wanfang Data knowledge service platform, VIP information and China biomedical literature database. The language is limited to Chinese. A total of 25 studies were included to analyze the information about the organizational structure, functional orientation, financing mechanism and personnel system of China′s disease prevention and control system.Results:The 25 studies described the specific changes and reform suggestions of China′s disease prevention and control system, including key policies (7 studies), organizational structure transformation (4 studies), institutional function transformation (7 studies), financing mechanism transformation (5 studies), personnel system reform (2 studies), and performance-based salary system reform (4 studies). Meanwhile, the reform suggestions were concluded at the top-level design system reform (two aspects), organization structure (three aspects), functioning (four aspects), and personnel guarantee mechanism (three aspects).Conclusions:This study indicates that there is a lack of empirical evidence regarding specific reform effects and content analysis at the micro level of disease prevention and control system in China. Future study should strengthen the rigorousness of study design and focus on the quantitative impacts of reform implementation in China.

Objective:To systematically understand the reform progress of disease prevention and control system in China.Methods:The literature regarding the reform of China′s disease prevention and control system was searched by using the keywords including disease prevention and control, center for disease prevention and control (CDC), disease control, reform, and system from 2003 to 2020 in China CNKI, Wanfang Data knowledge service platform, VIP information and China biomedical literature database. The language is limited to Chinese. A total of 25 studies were included to analyze the information about the organizational structure, functional orientation, financing mechanism and personnel system of China′s disease prevention and control system.Results:The 25 studies described the specific changes and reform suggestions of China′s disease prevention and control system, including key policies (7 studies), organizational structure transformation (4 studies), institutional function transformation (7 studies), financing mechanism transformation (5 studies), personnel system reform (2 studies), and performance-based salary system reform (4 studies). Meanwhile, the reform suggestions were concluded at the top-level design system reform (two aspects), organization structure (three aspects), functioning (four aspects), and personnel guarantee mechanism (three aspects).Conclusions:This study indicates that there is a lack of empirical evidence regarding specific reform effects and content analysis at the micro level of disease prevention and control system in China. Future study should strengthen the rigorousness of study design and focus on the quantitative impacts of reform implementation in China.