Standard liver weight model in adult deceased donors with fatty liver: A prospective cohort study

BACKGROUND Standard liver weight(SLW)is frequently used in deceased donor liver transplantation to avoid size mismatches with the recipient.However,some deceased donors(DDs)have fatty liver(FL).A few studies have reported that FL could impact liver size.To the best of our knowledge,there are no relevant SLW models for predicting liver size.AIM To demonstrate the relationship between FL and total liver weight(TLW)in detail and present a related SLW formula.METHODS We prospectively enrolled 212 adult DDs from West China Hospital of Sichuan University from June 2019 to February 2021,recorded their basic information,such as sex,age,body height(BH)and body weight(BW),and performed abdominal ultrasound(US)and pathological biopsy(PB).The chi-square test and kappa consistency score were used to assess the consistency in terms of FL diagnosed by US relative to PB.Simple linear regression analysis was used to explore the variables related to TLW.Multiple linear regression analysis was used to formulate SLW models,and the root mean standard error and interclass correlation coefficient were used to test the fitting efficiency and accuracy of the model,respectively.Furthermore,the optimal formula was compared with previous formulas.RESULTS Approximately 28.8%of DDs had FL.US had a high diagnostic ability(sensitivity and specificity were 86.2%and 92.9%,respectively;kappa value was 0.70,P<0.001)for livers with more than a 5%fatty change.Simple linear regression analysis showed that sex(R2,0.226;P<0.001),BH(R2,0.241;P<0.001),BW(R2,0.441;P<0.001),BMI(R2,0.224;P<0.001),BSA(R2,0.454;P<0.001)and FL(R2,0.130;P<0.001)significantly impacted TLW.In addition,multiple linear regression analysis showed that there was no significant difference in liver weight between the DDs with no steatosis and those with steatosis within 5%.Furthermore,in the context of hepatic steatosis,TLW increased positively(nonlinear);compared with the TLW of the non-FL group,the TLW of the groups with hepatic steatosis within 5%,between 5%and 20%and more than 20%increased by 0 g,90 g,and 340 g,respectively.A novel formula,namely,-348.6+(110.7 x Sex[0=Female,1=Male])+958.0 x BSA+(179.8 x FLUS[0=No,1=Yes]),where FL was diagnosed by US,was more convenient and accurate than any other formula for predicting SLW.CONCLUSION FL is positively correlated with TLW.The novel formula deduced using sex,BSA and FLUS is the optimal formula for predicting SLW in adult DDs.

An Al-12Si/ZnS powder inoculant for eutectic silicon in Al-12Si alloy

To obtain high-performance Al-Si-based cast alloys,refinement and modification of Si phases are required.An Al-12Si/ZnS powder inoculant was designed and fabricated using a chemical bath deposition method.The efficiency of the inoculant for modifying the eutectic Si phase in as-cast Al-12Si alloy was studied.Results show that Al-12Si/ZnS powder can significantly refine the eutectic Si in Al-Si cast alloys.The best refinement effect for eutectic Si is achieved with 17.5wt.%Al-12Si/ZnS powder.Coarse long needle-shaped eutectic Si with a length of 18μm was modified into approximately spherical shape with a diameter of 6.53μm,which is evenly distributed throughout the alloy.The E2EM model calculation indicates that the inter-plane misfit(F_(p))and inter-atomic spacing misfit(F_(r))between ZnS and Si are all less than 0.5%,which confirms that ZnS is a potential nucleation site for Si phase.The hardness,tensile strength,and elongation of Al-12Si alloys modified with 17.5%Al-12Si/ZnS powder increase 6.30%,16.18%and 55.45%,respectively,compared to the unmodified Al-12Si alloy.The fracture behavior of the alloy with 17.5wt.%Al-12Si/ZnS powder is dominated by transgranular fracture supplemented by intergranular fracture.

Machine learning-based prediction of pregnancy outcomes in couples with non-obstructive azoospermia using micro-TESE for ICSI: a retrospective cohort study

Objective:To develop a clinically applicable tool for predicting clinical pregnancy,providing individualized patient counseling,and helping couples with non-obstructive azoospermia(NOA)decide whether to use fresh or cryopreserved spermatozoa for oocyte insemination before microdissection testicular sperm extraction(mTESE).Methods:A total of 240 couples with NOA who underwent mTESE-ICSI were divided into two groups based on the type of spermatozoa used for intracytoplasmic sperm injection(ICSI):the fresh and cryopreserved groups.After evaluating several machine learning algorithms,logistic regression was selected.Using LASSO regression and 10-fold cross-validation,the factors associated with clinical pregnancy were analyzed.Results:The area under the curves(AUCs)for the fresh and cryopreserved groups in the Logistic Regression-based prediction model were 0.977 and 0.759,respectively.Compared with various modeling algorithms,Logistic Regression outperformed machine learning in both groups,with an AUC of 0.945 for the fresh group and 0.788 for the cryopreserved group.Conclusion:The model accurately predicted clinical pregnancies in NOA couples.