METTL3-mediated m6A RNA methylation was involved in aluminum-induced neurotoxicity.

Aluminum (Al) exposure has been linked to the development of a variety of neurodegenerative diseases. However, whether m6A RNA methylation participated in Al-induced neurotoxicity remain to be defined. In this study, mice were administrated with aluminum-lactate at dose of 220 mg/kg. bw by gavage for 3 months. Meanwhile, the primary hippocampal neurons were isolated and treated with 0, 50, 100, 150 µM aluminum-lactate, respectively for 7 days. Al exposure caused neuronal shrinkage, decreased Nissl bodies, and increased apoptosis. In accordance, in vitro studies also showed that Al exposure led to neuronal apoptosis in a dose-dependent manner, together with the decline in m6A RNA methylation levels. Moreover, the mRNA expression of Mettl3, Mettl14, Fto, and Ythdf2 were decreased upon Al exposure. Notably, the protein expression of METTL3 was dramatically down-regulated by 42% and 35% in Al-treated mice and neurons, suggesting METTL3 might exert a crucial role in Al-induced neurotoxicity. We next established a mouse model with hippocampus-specific overexpressing of Mettl3 gene to confirm the regulatory role of RNA methylation and found that METTL3 overexpression relieved the neurological injury induced by Al. The integrated MeRIP-seq and RNA-seq analysis elucidated that 631 genes were differentially expressed at both m6A RNA methylation and mRNA expression. Notably, EGFR tyrosine kinase inhibitor resistance, Rap1 signaling pathway, protein digestion and absorption might be involved in Al-induced neurotoxicity. Moreover, VEGFA, Thbs1, and PDGFB might be the central molecules. Collectively, our findings provide the novel sight into the role of m6A RNA methylation in neurodegenerative disease induced by Al.

Metabolomic analyses reveal new stage-specific features of COVID-19.

The current pandemic of coronavirus disease 2019 (COVID-19) has affected >160 million individuals to date, and has caused millions of deaths worldwide, at least in part due to the unclarified pathophysiology of this disease. Identifying the underlying molecular mechanisms of COVID-19 is critical to overcome this pandemic. Metabolites mirror the disease progression of an individual and can provide extensive insights into their pathophysiological significance at each stage of disease. We provide a comprehensive view of metabolic characterisation of sera from COVID-19 patients at all stages using untargeted and targeted metabolomic analysis. As compared with the healthy controls, we observed different alteration patterns of circulating metabolites from the mild, severe and recovery stages, in both the discovery cohort and the validation cohort, which suggests that metabolic reprogramming of glucose metabolism and the urea cycle are potential pathological mechanisms for COVID-19 progression. Our findings suggest that targeting glucose metabolism and the urea cycle may be a viable approach to fight COVID-19 at various stages along the disease course.

Targeted Next-Generation Sequencing of Circulating Tumor DNA Mutations among Metastatic Breast Cancer Patients.

Liquid biopsy through the detection of circulating tumor DNA (ctDNA) has potential advantages in cancer monitoring and prediction. However, most previous studies in this area were performed with a few hotspot genes, single time point detection, or insufficient sequencing depth. In this study, we performed targeted next-generation sequencing (NGS) with a customized panel in metastatic breast cancer (MBC) patients. Fifty-four plasma samples were taken before chemotherapy and after the third course of treatment for detection and analysis. Paired lymphocytes were also included to eliminate clonal hematopoiesis (CH)-related alternatives. A total of 1182 nonsynonymous mutations in 419 genes were identified. More ctDNA mutations were detected in patients with tumors > 3 cm (p = 0.035) and HER2(-) patients (p = 0.029). For a single gene, the distribution of ctDNA mutations was also correlated with clinical characteristics. Multivariate regression analysis revealed that HER2 status was significantly associated with mutation burden (OR 0.02, 95% CI 0-0.62, p = 0.025). The profiles of ctDNA mutations exhibited marked discrepancies between two time points, and baseline ctDNA was more sensitive and specific than that after chemotherapy. Finally, elevated ctDNA mutation level was positively correlated with poor survival (p < 0.001). Mutations in ctDNA could serve as a potential biomarker for the evaluation, prediction, and clinical management guidance of MBC patients with chemotherapy.

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection. We adopted machine learning methods for training different classifiers with a clinical-metabolomic database from sepsis cases to identify the pathogen of sepsis. Records of clinical indicators and concentration of metabolites were obtained for each patient upon their arrival at the hospital. Machine learning algorithms were used in 100 patients with clear infection and corresponding 29 controls to select specific biosignatures to discriminate microorganism in septic patients. The sensitivity, specificity, and AUC value of clinical and metabolomic characteristics in predicting diagnostic outcomes were determined at admission. Our analyses demonstrate that the biosignatures selected by machine learning algorithms could have diagnostic value on the identification of infected patients and Gram-positive from Gram-negative; related AUC values were 0.94 ± 0.054 and 0.80 ± 0.085, respectively. Pathway and blood disease enrichment analyses of clinical and metabolomic biomarkers among infected patients showed that sepsis disease was accompanied by abnormal nitrogen metabolism, cell respiratory disorder, and renal or intestinal failure. The panel of selected clinical and metabolomic characteristics might be powerful biomarkers to discriminate patients with sepsis.

Prognostic value of perioperative NT-proBNP after corrective surgery for pediatric congenital heart defects.

BACKGROUND: It is critically important to assess the prognostic value of NT-proBNP in the form of repeated measures among children undergoing surgery for congenital heart defects (CHD). The aim of the present study is to assess the value of repeated perioperative NT-proBNP in evaluating the time dependent and temporal trajectory in prognostics diagnosis during the perioperative period in a large series of children with CHD. METHODS: Repeated measures of NT-proBNP from 329 consecutive children with CHD were obtained before and 1, 12, and 36 h after surgery, respectively. For fully utilizing longitudinal characteristics, we employed parallel cross-sectional logistic regression, a two stage mixed effect model and trajectories over time analysis to mine the predictive value of perioperative NT-proBNP on the binary outcome of prolonged intensive care unit (ICU) stay. RESULTS: The two stage mixed effects model confirmed that both the mean NT-proBNP level (aOR = 1.46, P = 0.001) and the time trends had prognostic value on the prediction of prolonged ICU stay. In the fully adjusted logistic regression analyses based on gaussian distributions, "rapidly rising NT-proBNP" put the subjects at 5.4-times higher risk of prolonged ICU stay compared with "slowly rising" group (aOR = 5.40, P = 0.003). CONCLUSIONS: Comprehensive assessment of the time dependent and temporal trajectory in perioperative NT-proBNP, indicated by repeated measurements, can provide more accurate identification of children with higher risk of prolonged ICU stay after CHD surgery.

DNA methylation profile is a quantitative measure of biological aging in children.

DNA methylation changes within the genome can be used to predict human age. However, the existing biological age prediction models based on DNA methylation are predominantly adult-oriented. We established a methylation-based age prediction model for children (9-212 months old) using data from 716 blood samples in 11 DNA methylation datasets. Our elastic net model includes 111 CpG sites, mostly in genes associated with development and aging. The model performed well and exhibited high precision, yielding a 98% correlation between the DNA methylation age and the chronological age, with an error of only 6.7 months. When we used the model to assess age acceleration in children based on their methylation data, we observed the following: first, the aging rate appears to be fastest in mid-childhood, and this acceleration is more pronounced in autistic children; second, lead exposure early in life increases the aging rate in boys, but not in girls; third, short-term recombinant human growth hormone treatment has little effect on the aging rate of children. Our child-specific methylation-based age prediction model can effectively detect epigenetic changes and health imbalances early in life. This may thus be a useful model for future studies of epigenetic interventions for age-related diseases.

Semiconductor Sequencing Analysis of Chromosomal Copy Number Variations in Spontaneous Miscarriage.

BACKGROUND Array CGH is the criterion standard for identifying copy number variations (CNV), but the restrictive requirement of DNA quality and relatively high cost prevent the use of this method as a general assay in hospitals in developing countries. Our principal objective was to determine whether the semiconductor sequencing platform (SSP) could be an alternative method in CNV detection for spontaneous miscarriage. MATERIAL AND METHODS A total of 443 spontaneous miscarriage samples were collected and subjected to low-coverage (0.1X) whole-genome analysis by SSP. These samples were verified by array CGH and 8 low-quality DNA samples were analyzed by SSP and validated by MLPA. RESULTS SSP detected 195 chromosomal numerical abnormalities, 74 CNVs, and 9 mosaicisms among the 435 samples. Among 74 CNV abnormalities, SSP detected an equal number (56) of CNVs 56 >1 Mb with array CGH. However, SSP missed more 6 cases CNVs <1 Mb than array CGH (12 vs. 18). SSP detected more mosaicisms than array CGH (9 vs. 7, p=0.5). Interestingly, SSP detected the mosaicism which had only 8% X monosomy, which was much lower than the minimal percentage of monosomy that was detected by array CGH. CONCLUSIONS SSP is of equivalent efficacy as array CGH in detecting CNVs >1 Mb, and performs better in identifying mosaicism. With the merits of low cost and less demand of input DNA, SSP is a good alternative for use in genetic diagnosis.

Developing a Machine Learning System for Identification of Severe Hand, Foot, and Mouth Disease from Electronic Medical Record Data.

Children of severe hand, foot, and mouth disease (HFMD) often present with same clinical features as those of mild HFMD during the early stage, yet later deteriorate rapidly with a fulminant disease course. Our goal was to: (1) develop a machine learning system to automatically identify cases with high risk of severe HFMD at the time of admission; (2) compare the effectiveness of the new system with the existing risk scoring system. Data on 2,532 HFMD children admitted between March 2012 and July 2015, were collected retrospectively from a medical center in China. By applying a holdout strategy and a 10-fold cross validation method, we developed four models with the random forest algorithm using different variable sets. The prediction system HFMD-RF based on the model of 16 variables from both the structured and unstructured data, achieved 0.824 sensitivity, 0.931 specificity, 0.916 accuracy, and 0.916 area under the curve in the independent test set. Most remarkably, HFMD-RF offers significant gains with respect to the commonly used pediatric critical illness score in clinical practice. As all the selected risk factors can be easily obtained, HFMD-RF might prove to be useful for reductions in mortality and complications of severe HFMD.

Machine learning applications for prediction of relapse in childhood acute lymphoblastic leukemia.

The prediction of relapse in childhood acute lymphoblastic leukemia (ALL) is a critical factor for successful treatment and follow-up planning. Our goal was to construct an ALL relapse prediction model based on machine learning algorithms. Monte Carlo cross-validation nested by 10-fold cross-validation was used to rank clinical variables on the randomly split training sets of 336 newly diagnosed ALL children, and a forward feature selection algorithm was employed to find the shortest list of most discriminatory variables. To enable an unbiased estimation of the prediction model to new patients, besides the split test sets of 150 patients, we introduced another independent data set of 84 patients to evaluate the model. The Random Forest model with 14 features achieved a cross-validation accuracy of 0.827 ± 0.031 on one set and an accuracy of 0.798 on the other, with the area under the curve of 0.902 ± 0.027 and 0.904, respectively. The model performed well across different risk-level groups, with the best accuracy of 0.829 in the standard-risk group. To our knowledge, this is the first study to use machine learning models to predict childhood ALL relapse based on medical data from Electronic Medical Record, which will further facilitate stratification treatments.

Formation of the calcarine sulcus: a potential marker to predict the progression in utero of isolated mild fetal ventriculomegaly.

Our previous study confirmed the negative association between the development of calcarine sulcus and the width of lateral ventricles. The purpose of current study was to evaluate the reliability of calcarine sulcus depth in the 2nd trimester to predict the prenatal enlargement of lateral ventricle in fetuses with isolated mild fetal ventriculomegaly (IMVM).This study used a retrospective cohort study design. A total of 97 pregnant women with IMVM diagnosed between 20 and 26 weeks' gestation returned for a 2nd examination at 30 to 32 weeks. Lateral ventricular size and calcarine sulcus depth were acquired from ultrasonography and magnetic resonance imaging (MRI) scans, respectively. Progression was defined as the process of developing from a lower group toward a higher (<10 mm, 10-12 mm, 13-15 mm, and ≥16 mm).Significant correlation was observed between calcarine sulcus depth and ventricular measurements at the 2nd scan (r = -0.71, P < .0001). Receiver-operating characteristic curves showed that calcarine sulcus depth (area under curve [AUC] = 0.83, 95% confidence interval [CI] = 0.74-0.92) had the best diagnostic performance in predicting the prenatal progression, as compared with lateral ventricle width (AUC = 0.69, 95%CI = 0.54-0.84) and gestational age (AUC = 0.70, 95%CI = 0.57-0.83) at the initial scan. The cutoff value for calcarine sulcus depth was 3.3 mm, with the corresponding sensitivity and specificity were 75.0% and 81.3%, respectively. Multivariate analyses showed that calcarine sulcus depth ≥3.3 mm (odds ratio = 0.09, 95%CI = 0.02-0.38, P = .001) was an independent predictor of the prenatal progression.For IMVM, calcarine sulcus depth might be a powerful marker to identify subjects at higher risk for worse prenatal progression.

Short- and long-term outcomes after conversion of laparoscopic total gastrectomy for gastric cancer: a single-center study.

PURPOSE: Conversion of laparoscopic surgery for colorectal cancer has been fully studied. However, no study has investigated conversion of laparoscopic total gastrectomy for gastric cancer. We evaluated the effect of conversion to open total gastrectomy on short- and long-term outcomes among patients who underwent laparoscopic total gastrectomy for gastric cancer and identified factors predictive of survival. METHODS: A prospective database of consecutive laparoscopic total gastrectomies for gastric cancer was reviewed. Patients who required conversion (converted group) were compared with those who had completed laparoscopic total gastrectomy (completed group). Kaplan-Meier method was used to compare and analyze survival. Univariate and multivariate analyses were performed to identify predictors of poor survival. RESULTS: The conversion rate was 17.4%, and the most common reason for conversion was a locally advanced tumor. Conversion was associated with significantly longer operative time and greater blood loss. No differences were observed in terms of postoperative morbidity or mortality between the converted and completed patients. The converted group had significantly worse 5-year overall survival (OS) and disease-free survival (DFS). Univariate analysis showed that conversion to open total gastrectomy, pathological (p) T4 disease, and pathological N2-N3 disease were significant risk factors for OS and DFS. In multivariate analysis, pT4 cancer was the only independent predictor of DFS and OS. CONCLUSION: Conversion to open total gastrectomy per se was not associated with worse short-term outcomes or worse long-term survival.

Random X-chromosome inactivation dynamics in vivo by single-cell RNA sequencing.

BACKGROUND: Random X-chromosome inactivation (rXCI) is important for the maintenance of normal somatic cell functions in female eutherian mammals. The dynamics of X-chromosome inactivation initiation has been widely studied by assessing embryonic stem cell differentiation in vitro. To investigate the phenomenon in vivo, we applied RNA sequencing to single cells from female embryos obtained from a natural intercrossing of two genetically distant mouse strains. Instead of artificially assigning the parental origin of the inactive X chromosome, the inactive X chromosomes in this study were randomly selected from the natural developmental periods and thus included both paternal and maternal origins. RESULTS: The rXCI stages of single cells from the same developmental stage showed heterogeneity. The high resolution of the rXCI dynamics was exhibited. The inactivation orders of X chromosomal genes were determined by their functions, expression levels, and locations; generally, the inactivation order did not exhibit a parental origin preference. New escape genes were identified. Ohno's hypothesis of dosage compensation was refuted by our post-implantation stage data. CONCLUSIONS: We found the inactivation orders of X chromosomal genes were determined by their own properties. Generally, the inactivation order did not exhibit a parental origin preference. It provided insights into the gene silencing dynamics during rXCI in vivo.

Automatic Determination of the Greulich-Pyle Bone Age as an Alternative Approach for Chinese Children with Discordant Bone Age.

BACKGROUND: Automated bone age (BA) rating using BoneXpert is being adopted worldwide. This study investigated whether manual matching of hand radiographs could be replaced by BoneXpert for BA ratings of Chinese children with delayed or advanced BA. METHODS: 482 left-hand radiographs from 482 children (aged 2-16 years) with discordant BA were evaluated by BoneXpert and manually by 4 radiology residents using the Greulich and Pyle atlas. Radiographs whose BoneXpert BA deviated by >1 year from manual assessment were rerated by 2 attending radiologists in a blinded manner. RESULTS: Among all 482 radiographs, 46 (9.5%) radiographs were rerated and no radiographs were rejected. Differences between BoneXpert and manual rating of 28 (5.8%) cases were >1 year. The manual BAs of the 28 radiographs were all >10 years and greater than the BoneXpert BAs. The root mean square deviation between the residents and BoneXpert was 0.56 for these children (95% CI 0.53-0.61). CONCLUSION: BoneXpert agreed with manual BA rating in 94.2% of the images. Therefore, BoneXpert could be used as an alternative for the radiology residents to make an initial BA estimation. Modification of BoneXpert should provide greater accuracy for the estimation of BA in children aged >10 years with discordant BA.

Maturation Disparity between Hand-Wrist Bones in a Chinese Sample of Normal Children: An Analysis Based on Automatic BoneXpert and Manual Greulich and Pyle Atlas Assessment.

OBJECTIVE: To assess the maturation disparity of hand-wrist bones using the BoneXpert system and Greulich and Pyle (GP) atlas in a sample of normal children from China. MATERIALS AND METHODS: Our study included 229 boys and 168 girls aged 2-14 years. The bones in the hand and wrist were divided into five groups: distal radius and ulna, metacarpals, proximal phalanges, middle phalanges and distal phalanges. Bone age (BA) was assessed separately using the automatic BoneXpert and GP atlas by two raters. Differences in the BA between the most advanced and retarded individual bones and bone groups were analyzed. RESULTS: In 75.8% of children assessed with the BoneXpert and 59.4% of children assessed with the GP atlas, the BA difference between the most advanced and most retarded individual bones exceeded 2.0 years. The BA mean differences between the most advanced and most retarded individual bones were 2.58 and 2.25 years for the BoneXpert and GP atlas methods, respectively. Furthermore, for both methods, the middle phalanges were the most advanced group. The most retarded group was metacarpals for BoneXpert, while metacarpals and the distal radius and ulna were the most retarded groups according to the GP atlas. Overall, the BAs of the proximal and distal phalanges were closer to the chronological ages than those of the other bone groups. CONCLUSION: Obvious and regular maturation disparities are common in normal children. Overall, the BAs of the proximal and distal phalanges are more useful for BA estimation than those of the other bone groups.

Infant's DNA Methylation Age at Birth and Epigenetic Aging Accelerators.

Knowing the biological age of the neonates enables us to evaluate and better understand the health and maturity comprehensively. However, because of dearth of biomarkers, it is difficult to quantify the neonatal biological age. Here we sought to quantify and assess the variability in biological age at birth and to better understand how the aging rates before birth are influenced by exposure in intrauterine period by employing a novel epigenetic biomarker of aging (epigenetic clock). We observed that the methylation age at birth was independent of the infant's sex but was significantly influenced by race. Partial correlation analysis showed a significant negative relationship between maternal socioeconomic status and infants' methylation age (rs = -0.48, Ps = 0.005). A significant association with the risk of fast aging was observed for prenatal exposure to tobacco smoke with OR (95% CI) of 3.17 (1.05-9.56). Both estimated cell abundance measures and lymphocyte subpopulations in cord blood showed that tobacco exposed group exhibit an altered T cell compartment, specifically substantial loss of naive T cells. Present study provides the first evidence that common perinatal exposure (such as maternal smoking and lower socioeconomic status) may be important aging accelerators and substantial loss of naive T cells may play a role in the smoking-related fast aging phenomenon.

The reverse evolution from multicellularity to unicellularity during carcinogenesis.

Theoretical reasoning suggests that cancer may result from a knockdown of the genetic constraints that evolved for the maintenance of metazoan multicellularity. By characterizing the whole-life history of a xenograft tumour, here we show that metastasis is driven by positive selection for general loss-of-function mutations on multicellularity-related genes. Expression analyses reveal mainly downregulation of multicellularity-related genes and an evolving expression profile towards that of embryonic stem cells, the cell type resembling unicellular life in its capacity of unlimited clonal proliferation. Also, the emergence of metazoan multicellularity ~600 Myr ago is accompanied by an elevated birth rate of cancer genes, and there are more loss-of-function tumour suppressors than activated oncogenes in a typical tumour. These data collectively suggest that cancer represents a loss-of-function-driven reverse evolution back to the unicellular 'ground state'. This cancer evolution model may account for inter-/intratumoural genetic heterogeneity, could explain distant-organ metastases and hold implications for cancer therapy.

Comparative study of Gilsanz-Ratib digital atlas and Greulich-Pyle atlas for bone age estimation in a Chinese sample.

BACKGROUND: The applicability of the Gilsanz-Ratib (GR) digital atlas to bone age (BA) determination in China has not been evaluated. AIM: To compare the validity of GR and the Greulich-Pyle (GP) atlas in BA determination for children in Shanghai. SUBJECTS AND METHODS: Left-hand radiographs of 243 girls and 375 boys aged 0-13 years were obtained for suspected trauma. They were divided into eight sub-groups according to gender and age (0-3, 3-7, 7-10 and 10-13 years). Radiographs were read by two radiologists, using both GP and GR atlases. The differences between BA and calendar age (CA) were analysed. The inter- and intra-observer consistency was evaluated. RESULTS: Pearson's correlation coefficients indicated a strong positive correlation between methods and between raters. The differences between BA and CA of two sub-groups (10-13-year-old boys, GR; 0-3-year-old girls, GP) were not only statistically significant, but exceeded 1 SD, suggesting biological significance. CONCLUSION: Both atlases can be used on most age groups. However, the GR atlas is not recommended in boys aged 10-13 years, while the GP atlas is not suitable for girls aged 0-3 years. Therefore, the use of the GP or GR atlas is practical, depending on the age of the child.

Expression reduction in mammalian X chromosome evolution refutes Ohno's hypothesis of dosage compensation.

Susumu Ohno proposed in 1967 that, during the origin of mammalian sex chromosomes from a pair of autosomes, per-allele expression levels of X-linked genes were doubled to compensate for the degeneration of their Y homologs. This conjecture forms the foundation of the current evolutionary model of sex chromosome dosage compensation, but has been tested in mammals only indirectly via a comparison of expression levels between X-linked and autosomal genes in the same genome. The test results have been controversial, because examinations of different gene sets led to different conclusions that either support or refute Ohno's hypothesis. Here we resolve this uncertainty by directly comparing mammalian X-linked genes with their one-to-one orthologs in species that diverged before the origin of the mammalian sex chromosomes. Analyses of RNA sequencing data and proteomic data provide unambiguous evidence for expression halving (i.e., no change in per-allele expression level) of X-linked genes during evolution, with the exception of only ∼5% of genes that encode members of large protein complexes. We conclude that Ohno's hypothesis is rejected for the vast majority of genes, reopening the search for the evolutionary force driving the origin of chromosome-wide X inactivation in female mammals.