ObjectiveTo clone the gene of Marmota himalayana type ‍Ⅰ interferon receptor β subunit （mhIFNAR2）， and to perform antibody preparation and functional identification. MethodsRT-PCR was used for amplification in the spleen tissue of Marmota himalayana to obtain the sequence， which was cloned to the prokaryotic expression vector pRSET-B to express the recombinant protein. Electrophoresis and Western blot were used for identification. BALB/c mice were immunized with the recombinant protein to prepare the polyclonal antibody of its extracellular domain； immunohistochemistry， immunofluorescence assay， and Western Blot were used for identification， and the method of siRNA blockade was used to investigate its function. An analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for comparison between two groups. ResultsA fragment of mhIFNAR2 （149‍ ‍—‍ ‍1 ‍300 bp） was obtained from spleen tissue， which showed the highest homology of 98.05% in marmot. A prokaryotic expression plasmid was successfully constructed for expression of the extracellular domain of the mhIFNAR2_{（50-181aa）} and was named pRSET-B.mhIFNAR2， and the recombinant protein expressed by this plasmid had a molecular weight of 27 kD， a purity of about 95% after purification， and a concentration of 160 μg/mL. After BALB/c mice were immunized with the purified recombinant protein， 1∶1 000 specific polyclonal antibodies were obtained， and immunohistochemistry and immunofluorescence assay showed the expression in cell membrane and cytoplasm. Among the three siRNAs synthesized， the siRNA starting from the 277 locus （siRNA277） could silence the expression of target genes and weaken the interferon signaling pathway compared with the blank control group and the negative control group （both P<0.05）. ConclusionThe fragment of mhIFNAR2 is obtained， and the polyclonal antibody for the extracellular domain of mhIFNAR2 is successfully prepared， with relatively high titer and specificity， and can be used for immunohistochemistry， immunofluorescence assay， and Western blot.

Objective::Older patients with comorbidity, such as coronary heart disease (CHD) and malignant gastrointestinal tumors, are at a high risk of bleeding events. However, risk prediction models based on risk factor assessment remain unclear. This study aimed to establish an individualized bleeding risk assessment system based on the analysis of 10-year inpatient clinical big data.Methods::Total clinical data of 56,819 patients with CHD and 25,988 patients with malignant digestive tract tumors (admitted from January 2008 to December 2017) were retrospectively collected at the First and Second Medical Centers of Chinese People’s Liberation Army General Hospital. Among them, 1307 patients with CHD and malignant digestive tract tumors were screened as the derivation cohort. The dependent variable was the occurrence of major clinical bleeding events. Baseline statistics and hypothesis tests of differences were performed for independent variables according to the occurrence of bleeding. Decision Tree, eXtreme Gradient Boosting (XGBoost), logistic regression, and random forest models were used for comparison. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC) were applied as the criteria for evaluating and verifying model performance. To evaluate this developed model, another cohort comprising 454 patients (admitted from January 2018 to December 2019) was prospectively enrolled as the validation cohort based on the same inclusion and exclusion criteria.Results::Among the 64 variables with <50% missing values, the recursive feature elimination method with a random forest model was used to screen the selected variables. The highest accuracy was obtained following the selection of 10 scalars, and the final model was constructed accordingly. XGBoost demonstrated the best performance comprehensively. The AUC-ROC of this model was 0.981, with an accuracy, sensitivity, and specificity of 0.939, 0.950, and 0.927, respectively. In the validation cohort, the AUC-ROC, accuracy, sensitivity, and specificity of the XGBoost model were 0.702, 0.718, 0.636, and 0.725, respectively. The rate of major bleeding events has a positive correlation with the bleeding risk score quintiles. To allow for convenient clinical application, a smartphone application was developed for easy access and calculation (http://fir.master-wx.com/sghr).Conclusion::We successfully established a risk model and score for predicting bleeding events in older patients with comorbidity, such as CHD and gastrointestinal cancer.

Objective::Older patients with comorbidity, such as coronary heart disease (CHD) and malignant gastrointestinal tumors, are at a high risk of bleeding events. However, risk prediction models based on risk factor assessment remain unclear. This study aimed to establish an individualized bleeding risk assessment system based on the analysis of 10-year inpatient clinical big data.Methods::Total clinical data of 56,819 patients with CHD and 25,988 patients with malignant digestive tract tumors (admitted from January 2008 to December 2017) were retrospectively collected at the First and Second Medical Centers of Chinese People’s Liberation Army General Hospital. Among them, 1307 patients with CHD and malignant digestive tract tumors were screened as the derivation cohort. The dependent variable was the occurrence of major clinical bleeding events. Baseline statistics and hypothesis tests of differences were performed for independent variables according to the occurrence of bleeding. Decision Tree, eXtreme Gradient Boosting (XGBoost), logistic regression, and random forest models were used for comparison. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC) were applied as the criteria for evaluating and verifying model performance. To evaluate this developed model, another cohort comprising 454 patients (admitted from January 2018 to December 2019) was prospectively enrolled as the validation cohort based on the same inclusion and exclusion criteria.Results::Among the 64 variables with <50% missing values, the recursive feature elimination method with a random forest model was used to screen the selected variables. The highest accuracy was obtained following the selection of 10 scalars, and the final model was constructed accordingly. XGBoost demonstrated the best performance comprehensively. The AUC-ROC of this model was 0.981, with an accuracy, sensitivity, and specificity of 0.939, 0.950, and 0.927, respectively. In the validation cohort, the AUC-ROC, accuracy, sensitivity, and specificity of the XGBoost model were 0.702, 0.718, 0.636, and 0.725, respectively. The rate of major bleeding events has a positive correlation with the bleeding risk score quintiles. To allow for convenient clinical application, a smartphone application was developed for easy access and calculation (http://fir.master-wx.com/sghr).Conclusion::We successfully established a risk model and score for predicting bleeding events in older patients with comorbidity, such as CHD and gastrointestinal cancer.

OBJECTIVE: To investigate the risk factors associated with early miscarriage among intrauterine singleton pregnancies after treatment with in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI).
 METHODS: A retrospective case-control study was performed on all singleton pregnancies underwent IVF/ICSI from January, 2013 to May, 2014, in Xiangya Hospital. Ninety-six early miscarriage patients served as a case group and 593 pregnancies with live birth served as a control group. We analyzed factors for early miscarriage after IVF/ICSI in two groups.
 RESULTS: Multivariate logistic regression analysis demonstrated that the women age, miscarriage history, and sperm DAN fragmentation index (DFI) were the risk factors for early miscarriage (P<0.05).
 CONCLUSION Miscarriage after treatment with IVF/ICSI is affected by multiple factors. Women at elder age (>30 years old), women with a history of miscarriage or men with higher sperm DFI (≥15%) are the risk.
Abortion, Spontaneous ; Case-Control Studies ; Female ; Fertilization in Vitro ; Humans ; Male ; Pregnancy ; Retrospective Studies ; Risk Factors ; Sperm Injections, Intracytoplasmic ; Spermatozoa

Previous studies have shown that expression of the interferon-sensitive gene (ISG)I5 protease UBP43 is increased in the liver biopsy specimens of patients who do not respond to interferon (IFN)-α therapy. We hypothesized that UBP43 might hinder the ability of IFN to inhibit HBV replication. In this study, we investigated whether vector-based siRNA promoted by Hi (psiUBP43) could enhance IFN inhibiting HBV replication in cell culture. UBP43 was specifically silenced using shRNA. In HepG2.2.15 cells, the HBeAg and HBV DNA levels were significantly reduced by IFN after transfection of shRNA, imphicated that vector-based siRNA promoted by HI (psiUBP43) could enhance IFN inhibiting HBV replication in cell culture. These data suggest that UBP43 modulates the anti-HBV type I IFN response, and is a possible therapeutic target for the treatment of HBV infection.