Constructing Accessible Closed Nanopores in Coal-Derived Hard Carbon for Sodium-Ion Batteries.

Hard carbon (HC) materials are suitable anodes for sodium-ion batteries (SIBs) but still suffer from insufficient initial Coulombic efficiency (ICE). Promoting sodium storage via the pore filling mechanism is an effective way to improve the ICE, and the key here is regulating the pore structures of HC. In this work, coal-derived HC is successfully engineered with abundant accessible closed nanopores by treating the coal precursors with a facile destructive oxidation strategy.

The Inactivated ISKNV-I Vaccine Confers Highly Effective Cross-Protection against Epidemic RSIV-I and RSIV-II from Cultured Spotted Sea Bass Lateolabrax maculatus.

The genus of the family is composed of two distinct species, namely, infectious spleen and kidney necrosis virus (ISKNV) and scale drop disease virus (SDDV), and both are important causative agents in a variety of bony fish worldwide. Of them, the ISKNV species is subdivided into three genotypes, namely, red seabream iridovirus (RSIV), ISKNV, and turbot reddish body iridovirus (TRBIV), and a further six subgenotypes, RSIV-I, RSIV-II, ISKNV-I, ISKNV-II, TRBIV-I, and TRBIV-II. Commercial vaccines derived from RSIV-I , RSIV-II and ISKNV-I have been available to several fish species.

Production and characterization of monoclonal antibodies against mandarinfish ranavirus and first identification of pyloric caecum as the major target tissue.

Mandarinfish ranavirus (MRV), also known as a variant of largemouth bass virus (LMBV), is an emerging pathogen in mandarinfish aquaculture. In this study, monoclonal antibodies (mAbs) against MRV were produced and characterized, and 7 mAbs were obtained through Western blotting screening and all 7 mAbs specifically recognized MRV/LMBV but not several piscine iridoviruses as ISKNV, GIV and TFV. By LC MS/MS analysis, the recognized viral proteins by seven mAbs were identified as MRV-pORF47L, MRV-pORF55R, MRV-pORF57L, MRV-pORF77L and MRV-pORF78L, respectively, and all five viral proteins are late expression structural proteins by Western blotting.

Novel ATXN1/ATXN1L::NUTM2A fusions identified in aggressive infant sarcomas with gene expression and methylation patterns similar to CIC-rearranged sarcoma.

CIC-rearranged sarcomas are newly defined undifferentiated soft tissue tumors with CIC-associated fusions, and dismal prognosis. CIC fusions activate PEA3 family genes, ETV1/4/5, leading to tumorigenesis and progression. We report two high-grade CNS sarcomas of unclear histological diagnosis and one disseminated tumor of unknown origin with novel fusions and similar gene-expression/methylation patterns without CIC rearrangement.

PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods.

Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that provide rapid access to many of these datasets through a standardized, user-friendly interface that integrates well with popular data science workflows.

Results: This release of PMLB (Penn Machine Learning Benchmarks) provides the largest collection of diverse, public benchmark datasets for evaluating new machine learning and data science methods aggregated in one location.

Scale Drop Disease Virus Associated Yellowfin Seabream () Ascites Diseases, Zhuhai, Guangdong, Southern China: The First Description.

Scale drop disease virus (SDDV), an emerging piscine iridovirus prevalent in farmed Asian seabass in Southeast Asia, was firstly scientifically descripted in Singapore in 2015. Here, an SDDV isolate ZH-06/20 was isolated by inoculating filtered ascites from diseased juvenile yellowfin seabream into MFF-1 cell. Advanced cytopathic effects were observed 6 days post-inoculation.

Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection.

Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-based Pipeline Optimization Tool (TPOT), have been developed to take some of the guesswork out of ML thus making this technology available to users from more diverse backgrounds.

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses.

Background: A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimization Tool (TPOT) constitute an appealing approach to this end. However, in biomedical data, there are often baseline characteristics of the subjects in a study or batch effects that need to be adjusted for in order to better isolate the effects of the features of interest on the target.

Evaluating recommender systems for AI-driven biomedical informatics.

Motivation: Many researchers with domain expertise are unable to easily apply machine learning (ML) to their bioinformatics data due to a lack of ML and/or coding expertise. Methods that have been proposed thus far to automate ML mostly require programming experience as well as expert knowledge to tune and apply the algorithms correctly. Here, we study a method of automating biomedical data science using a web-based AI platform to recommend model choices and conduct experiments.

Correction to: Investigating the parameter space of evolutionary algorithms.

[This corrects the article DOI: 10.1186/s13040-018-0164-x.].

Immunological ignorance is an enabling feature of the oligo-clonal T cell response to melanoma neoantigens.

The impact of intratumoral heterogeneity (ITH) and the resultant neoantigen landscape on T cell immunity are poorly understood. ITH is a widely recognized feature of solid tumors and poses distinct challenges related to the development of effective therapeutic strategies, including cancer neoantigen vaccines. Here, we performed deep targeted DNA sequencing of multiple metastases from melanoma patients and observed ubiquitous sharing of clonal and subclonal single nucleotide variants (SNVs) encoding putative HLA class I-restricted neoantigen epitopes.

Comparison of protective efficacy between two DNA vaccines encoding DnaK and GroEL against fish nocardiosis.

Fish nocardiosis is a chronic granulomatous bacterial disease mainly caused by three pathogenic bacteria, including Nocardia seriolae, N. asteroids and N. salmonicida.

Author Correction: ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression.

The c-Myc oncogene drives malignant progression and induces robust anabolic and proliferative programmes leading to intrinsic stress. The mechanisms enabling adaptation to MYC-induced stress are not fully understood. Here we reveal an essential role for activating transcription factor 4 (ATF4) in survival following MYC activation.

Scaling tree-based automated machine learning to biomedical big data with a feature set selector.

Motivation: Automated machine learning (AutoML) systems are helpful data science assistants designed to scan data for novel features, select appropriate supervised learning models and optimize their parameters. For this purpose, Tree-based Pipeline Optimization Tool (TPOT) was developed using strongly typed genetic programing (GP) to recommend an optimized analysis pipeline for the data scientist's prediction problem. However, like other AutoML systems, TPOT may reach computational resource limits when working on big data such as whole-genome expression data.

Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a compendium of systemic lupus erythematous () patients, we applied the Integrated machine learning pipeline for aberrant biomarker enrichment () to profile gene expression features affecting CD20, CD22 and CD30 gene aberrance.

Investigating the parameter space of evolutionary algorithms.

Evolutionary computation (EC) has been widely applied to biological and biomedical data. The practice of EC involves the tuning of many parameters, such as population size, generation count, selection size, and crossover and mutation rates. Through an series of experiments over multiple evolutionary algorithm implementations and 25 problems we show that parameter space tends to be rife with viable parameters, at least for the problems studied herein.

Detection of genomic signatures of recent selection in commercial broiler chickens.

Background: Identification of the genomic signatures of recent selection may help uncover causal polymorphisms controlling traits relevant to recent decades of selective breeding in livestock. In this study, we aimed at detecting signatures of recent selection in commercial broiler chickens using genotype information from single nucleotide polymorphisms (SNPs). A total of 565 chickens from five commercial purebred lines, including three broiler sire (male) lines and two broiler dam (female) lines, were genotyped using the 60K SNP Illumina iSelect chicken array.

Characterization of a novel chicken muscle disorder through differential gene expression and pathway analysis using RNA-sequencing.

Background: Improvements in poultry production within the past 50 years have led to increased muscle yield and growth rate, which may be contributing to an increased rate and development of new muscle disorders in chickens. Previously reported muscle disorders and conditions are generally associated with poor meat quality traits and have a significant negative economic impact on the poultry industry. Recently, a novel myopathy phenotype has emerged which is characterized by palpably "hard" or tough breast muscle.

Linkage disequilibrium in crossbred and pure line chickens.

Background: Both genome-wide association (GWA) studies and genomic selection depend on the level of non-random association of alleles at different loci, i.e. linkage disequilibrium (LD), across the genome.

Single-nucleotide polymorphisms in CD8A and their associations with T lymphocyte subpopulations in pig.

Findings from previous studies suggested that the cluster of the differentiation 8 alpha (CD8A) gene plays a prominent role in human T lymphocyte subpopulations. However, the evidence from pig population is still rare. To determine whether the important role of the CD8A gene is conserved in pig, a candidate gene analysis was performed herein through genotype-phenotype associations.

A multiple-SNP approach for genome-wide association study of milk production traits in Chinese Holstein cattle.

The multiple-SNP analysis has been studied by many researchers, in which the effects of multiple SNPs are simultaneously estimated and tested in a multiple linear regression. The multiple-SNP association analysis usually has higher power and lower false-positive rate for detecting causative SNP(s) than single marker analysis (SMA). Several methods have been proposed to simultaneously estimate and test multiple SNP effects.

Genome-wide association study for pigmentation traits in Chinese Holstein population.

With the Illumina BovineSNP50K BeadChip, we performed a genome-wide association study (GWAS) for two pigmentation traits in a Chinese Holstein population: proportion of black (PB) and teat colour (TC). A case-control design was used. Cases were the cows with PB <0.

Genome-wide association study for cytokines and immunoglobulin G in swine.

Increased disease resistance through improved immune capacity would be beneficial for the welfare and productivity of farm animals. To identify genomic regions responsible for immune capacity traits in swine, a genome-wide association study was conducted. In total, 675 pigs were included.