African swine fever and swine erysipelas are two devastating diseases with similar manifestations ravaging the domestic pig industry.Only a single phylogenetic study has been carried out in Cameroon, and neither an extensive genotyping aimed at identifying the different serotypes nor has an appropriate differential diagnosis of different species of
Genome-wide analysis of PRR gene family uncovers their roles in circadian rhythmic changes and response to drought stress in Gossypium hirsutum L.
Background The circadian clock not only participates in regulating various stages of plant growth, development and metabolism, but confers plant environmental adaptability to stress such as drought.Pseudo-Response Regulators (PRRs) are important component of the central oscillator (the core of circadian clock) and play a significant role in plant p
SULPHIDE MINERALIZATION IN UPPER WESTPHALIAN COAL SEAMS FROM THE EASTERN PART OF THE UPPER SILESIAN COAL BASIN
Morphologically diversified sulphide mineralization has been found in No.301 and 302 coal seams (Westphalian B).The main sulphide is pyrite which forms veinlets cross-cutting the sedimentary fabrics of the coal, encrusts the cellular structures and intergrowths with oxysulphides.Two skylight quilt pattern generations of pyrites were observed: the p
A mitochondrial copyright transports glycolytic intermediates to link cytosolic and mitochondrial glycolysis in the human gut parasite Blastocystis
Stramenopiles form a clade of diverse eukaryotic organisms, including multicellular algae, the fish and plant pathogenic oomycetes, such as the potato blight Phytophthora, and the human intestinal protozoan Blastocystis.In most eukaryotes, glycolysis is a strictly cytosolic metabolic pathway that converts glucose to pyruvate, resulting in the produ
Reducing False-Positive Results in Newborn Screening Using Machine Learning
Newborn screening (NBS) for inborn metabolic disorders is a highly successful public health program that by design is accompanied by false-positive results.Here we trained a Random Forest machine learning classifier on screening data to improve prediction of true and false positives.Data included 39 metabolic analytes detected by tandem mass spectr