De novo 7q deletion with a positive maternal serum triple test screening

A 32-year-old woman at 17 weeks of gestation had a high possibility (1:82) of having a child with Down syndrome. Fetal chromosome according to amniocentesis revealed 46,XX,del(7)(q11.23q21.2). The fetus' chromosomal defect was not inherent because the chromosome analysis of the parents did not have any abnormal findings. We were regularly monitoring the pregnant woman by routine prenatal schedule and she had a normal spontaneous delivery. The baby showed a typical facial malformation, epicanthal fold, decreased muscle tone, and cardiac abnormalities. This is the first patient prenatally diagnosed with de novo 7q deletion by positive triple marker screening test. We consider the triple test, which is the most popular examination used to clarify the risk of chromosome abnormality in obstetrics, will be used not only for trisomy 21 and 18, but also for any other chromosome abnormalities.     

Al2O3-Coated Si-Alloy Prepared by Atomic Layer Deposition as Anodes for Lithium-Ion Batteries

Silicon-based anodes can increase the energy density of Li-ion batteries (LIBs) owing to their large weights and volumetric capacities. However, repeated charging and discharging can rapidly deteriorate the electrochemical properties because of a large volume change in the electrode. In this study, a commercial Fe-Si powder was coated with Al₂O₃ layers of different thicknesses via atomic layer deposition (ALD) to prevent the volume expansion of Si and suppress the formation of crack-induced solid electrolyte interfaces. The Al₂O₃ content was controlled by adjusting the trimethyl aluminum exposure time, and higher Al₂O₃ contents significantly improved the electrochemical properties. In 300 cycles, the capacity retention rate of a pouch full-cell containing the fabricated anodes increased from 69.8% to 72.3% and 79.1% depending on the Al₂O₃ content. The powder characterization and coin and pouch cell cycle evaluation results confirmed the formation of an Al₂O₃ layer on the powder surface. Furthermore, the expansion rate observed during the charging/discharging of the pouch cell indicated that the deposited layer suppressed the powder expansion and improved the cell stability. Thus, the performance of an LIB containing Si-alloy anodes can be improved by coating an ALD-synthesized protective Al₂O₃ layer.     

Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants

PurposeThe aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants.Materials and MethodsOf 10425 VLBW infants registered in the Korean Neonatal Network between 2013 and 2017, 7954 infants were included. PGF was defined as a decrease in Z score >1.28 at discharge, compared to that at birth. Six metrics [area under the receiver operating characteristic curve (AUROC), accuracy, precision, sensitivity, specificity, and F1 score] were obtained at five time points (at birth, 7 days, 14 days, 28 days after birth, and at discharge). Machine learning models were built using four different techniques [extreme gradient boosting (XGB), random forest, support vector machine, and convolutional neural network] to compare against the conventional multiple logistic regression (MLR) model.ResultsThe XGB algorithm showed the best performance with all six metrics across the board. When compared with MLR, XGB showed a significantly higher AUROC (p=0.03) for Day 7, which was the primary performance metric. Using optimal cut-off points, for Day 7, XGB still showed better performances in terms of AUROC (0.74), accuracy (0.68), and F1 score (0.67). AUROC values seemed to increase slightly from birth to 7 days after birth with significance, almost reaching a plateau after 7 days after birth.ConclusionWe have shown the possibility of predicting PGF through machine learning algorithms, especially XGB. Such models may help neonatologists in the early diagnosis of high-risk infants for PGF for early intervention.     

Initial Abdominal CT and Laboratory Findings Prior to Diagnosis of Crohn’s Disease in Children

PurposeTo identify initial abdominal computed tomography (CT) and laboratory findings prior to a diagnosis of Crohn’s disease (CD) in children.Materials and MethodsIn this retrospective study, patients (≤18 year-old) who were diagnosed with CD from 2004 to 2019 and had abdominal CT just prior to being diagnosed with CD were included in the CD group. Patients (≤18 years old) who were diagnosed with infectious enterocolitis from 2018 to 2019 and had undergone CT prior to being diagnosed with enterocolitis were included as a control group. We assessed the diagnostic performances of initial CT and laboratory findings for the diagnosis of CD using logistic regression and the area under the curve (AUC).ResultsIn total, 107 patients (50 CD patients, 57 control patients) were included, without an age difference between groups (median 13 years old vs. 11 years old, p=0.119). On univariate logistic regression analysis, multisegmental bowel involvement, mesenteric vessel engorgement, higher portal vein/aorta diameter ratio, longer liver longitudinal diameter, lower hemoglobin (≤12.5 g/dL), lower albumin (≤4 g/dL), and higher platelet (>320×10³/µL) levels were significant factors for CD. On multivariate analysis, multisegmental bowel involvement [odds ratio (OR) 111.6, 95% confidence interval (CI) 4.778–2605.925] and lower albumin levels (OR 0.9, 95% CI 0.891–0.993) were significant factors. When these two features were combined, the AUC value was 0.985 with a sensitivity of 96% and specificity of 100% for differentiating CD.ConclusionMultisegmental bowel involvement on CT and decreased albumin levels can help differentiate CD from infectious enterocolitis in children prior to a definite diagnosis of CD.