Modern benchtop DNA synthesis techniques and increased concern of emerging pathogens have elevated the importance of screening oligonucleotides for pathogens of concern. However, accurate and sensitive characterization of oligonucleotides is an open challenge for many of the current techniques and ontology-based tools. To address this gap, we have developed a novel software tool, SeqScreen, that can accurately and sensitively characterize short DNA sequences using a set of curated Functions of Sequences of Concern (FunSoCs), novel functional labels specific to microbial pathogenesis which describe the pathogenic potential of individual proteins. We show that our ensemble machine learning model after training on these curations can label sequences with FunSoCs via an imbalanced multi-class and multi-label classification task with high accuracy. In summary, SeqScreen represents a first step towards a novel paradigm of functionally informed pathogen characterization from genomic and metagenomic datasets. SeqScreen is open-source and freely available for download at: https://www.gitlab.com/treangenlab/seqscreen .

No abstract

Background: Quantitative assessment of body fat is important for the diagnosis and treatment of diseases related to obesity, Computed tomography (CT) becoming the standard procedure for measuring the abdominal fat distribution. Material and method: The retrospective study included 111 inpatients, who underwent routine abdominal CT exams in the Radiology Laboratory of SCJU Tg.Mures (2013). MPR MDCT (SOMATOM AS 64) data was processed using a custom written MATLAB R2009b software, ImageJ being used for tracing of the visceral fat area (VFA). Patient data (including blood glucose, cholesterol and triglycerides) were analyzed using MO Excel and GraphPad Inprism5. Results: Visceral Fat percentage varied in population from 14.59-68.69 (SD = 11.83) with significant difference between sexes (male vs. female, 46.98 vs. 31.62, p <0.05). Cholesterol values >220 mg% and triglycerides >150 mg% are significantly associated with the VF percent (p <0.05). Overall there is a weak correlation between the lab variables and the measured fat, the strongest one being between triglycerides and the VFA (r = +0.23) and between age and VFA percentage (certain samples). Conclusions: The technique used should decreases the human error in marking of the fat areas providing a better estimation of the VF/VF percentage. CT measured VF relates with certain lab tests. Further analysis, is required for a better use of CT in obesity related pathology diagnosis and treatment

No abstract

No abstract