An increasing number of young patients who suffer from endometrial carcinoma (atypical hyperplasia of endometrium) succeed in childbirth.However,some young patients have to receive surgery due to resistance and prognosis and so on.Here we make a brief revicw of the failure-related issues and subsequent treatment of young patients of endometrial carcinomas (atypical hyperplasia of endometrium) who fail in conservative treatments.

Objective To evaluate the molluscicidal effect of black plastic mulching in mountainous areas of Yunnan Prov-ince. Methods In Leqiu Village,Nanjian County,Yunnan Province,the terraced fields with Oncomelania hupensis snails were divided into A,B,C,D,E groups,and of which,A,B,C,D groups,as the experimental groups,were administered with sim-ple black plastic mulching for 30 days,60 days,90 days and 120 days respectively;Group E,as the control group,was adminis-tered with 50%niclosamide ethanolamine salt wettable powder spraying. Results In Group C and D(simple black film mulching for 90 days and 120 days),no snails were found after the administration,the average density of living snails decreased by 100%, and the cost of one year was similar to that of the control group. Conclusion The molluscicidal effect of black plastic mulching is good in mountainous areas.

Objective:To explore the value of the age, atrial fibrillation, dysphagia, sex, stroke severity (A2DS2) score, the prestroke independence, sex, age, National Institutes of Health stroke scale (ISAN) score, acute ischemic stroke-associated pneumonia score (AIS-APS), and intracerebral hemorrhage associated pneumonia score without hematoma volume included (ICH-APS-A) in predicting risk of stroke-associated pneumonia (SAP).Methods:From January to June 2019, 304 patients with acute stroke who were hospitalized in the Lianyungang Hospital Affiliated to Xuzhou Medical University were analyzed retrospectively. There were 164 patients with acute ischemic stroke (AIS), including 82 patients with SAP. And there were 140 patients with intracerebral hemorrhage (ICH), including 70 patients with SAP. They were divided into SAP group (152 cases) and non-SAP group (152 cases) depending on whether they had SAP. The area under the receiver operating characteristic curve (AUC) was used to compare the predictive value of the four scores.Results:When predicting risk of SAP in patients with the stroke, the A2DS2 score had the largest AUC compared to the ISAN score, AIS-APS score, and ICH-APS-A score. When predicting risk of SAP in patients with AIS, the AUC (0.875, 95% CI 0.815 to 0.922) of the A2DS2 score was greater than the AIS-APS score and the ISAN score. When predicting risk of SAP in patients with ICH, the AUC (0.950, 95% CI 0.900 to 0.980) of the A2DS2 score was greater than the ICH-APS-A score and the ISAN score. When predicting risk of SAP in patients with AIS and ICH: 0.911 (95% CI 0.873 to 0.94) vs. 0.882 (95% CI 0.840 to 0.916), Z = 2.319, P = 0.020, the A2DS2 score was significantly better than the ISAN score ( P<0.05). When predicting risk of SAP in patients with AIS, the A2DS2 score, ISAN score, and AIS-APS score all have good predictive value ( P>0.05). When predicting SAP in patients with ICH, the A2DS2 score, ISAN score, and ICH-APS-A score all have good predictive value ( P>0.05). Conclusions:When predicting risk of SAP in patients, the A2DS2 score is a reliable prediction tool, with good predictive value.

Background: The mitogen-activated extracellular signal-regulated kinase 1/2 (MEK1/2) inhibitor trametinib has shown promising therapeutic effects on melanoma, but its efficacy on colorectal cancer (CRC) is limited. Synthetic lethality arises with a combination of two or more separate gene mutations that causes cell death, whereas individual mutations keep cells alive. This study aimed to identify the genes responsible for resistance to trametinib in CRC cells, using a synthetic lethal short hairpin RNA (shRNA) screening approach. Methods: We infected HT29 cells with a pooled lentiviral shRNA library and applied next-generation sequencing to identify shRNAs with reduced abundance after 8-day treatment of 20 nmol/L trametinib. HCT116 and HT29 cells were used in validation studies. Stable ring finger protein 183 (RNF183)-overexpressing cell lines were generated by pcDNA4-myc/his-RNF183 transfection. Stable RNF183-knockdown cell lines were generated by infection of lentivi-ruses that express RNF183 shRNA, and small interference RNA (siRNA) was used to knock down RNF183 transiently. Quantitative real-time PCR was used to determine the mRNA expression. Western blotting, immunohistochemical analysis, and enzyme-linked immunosorbent assay (ELISA) were used to evaluate the protein abundance. MTT assay, colony formation assay, and subcutaneous xenograft tumor growth model were used to evaluate cell proliferation. Results: In the primary screening, we found that the abundance of RNF183 shRNA was markedly reduced after treatment with trametinib. Trametinib induced the expression of RNF183, which conferred resistance to drug-induced cell growth repression and apoptotic and non-apoptotic cell deaths. Moreover, interleukin-8 (IL-8) was a downstream gene of RNF183 and was required for the function of RNF183 in facilitating cell growth. Additionally, elevated RNF183 expression partly reduced the inhibitory effect of trametinib on IL-8 expression. Finally, xenograft tumor model showed the synergism of RNF183 knockdown and trametinib in repressing the growth of CRC cells in vivo. Conclusion: The RNF183-IL-8 axis is responsible for the resistance of CRC cells to the MEK1/2 inhibitor trametinib and may serve as a candidate target for combined therapy for CRC.

With the optimization of surgical technologies and postoperative management regimens, the number of lung transplantation has been significantly increased, which has become an important treatment for patients with end-stage lung disease. However, due to the impact of comprehensive factors, such as bronchial ischemia and immunosuppression, the incidence of airway stenosis after lung transplantation is relatively high, which severely affects postoperative survival and quality of life of lung transplant recipients. In recent years, with the improvement of perioperative management, organ preservation and surgical technologies, the incidence of airway stenosis after lung transplantation has been declined, but it remains at a high level. Early diagnosis and timely intervention play a significant role in enhancing clinical prognosis of patients with airway stenosis. In this article, the general conditions, diagnosis, treatment and prevention of airway stenosis after lung transplantation were reviewed, aiming to provide reference for comprehensive management of airway stenosis after lung transplantation and improving clinical prognosis of lung transplant recipients.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.