Hyperdense Artery Sign in Patients With Acute Ischemic Stroke-Automated Detection With Artificial Intelligence-Driven Software.

Background: Hyperdense artery sign (HAS) on non-contrast CT (NCCT) can indicate a large vessel occlusion (LVO) in patients with acute ischemic stroke. HAS detection belongs to routine reporting in patients with acute stroke and can help to identify patients in whom LVO is not initially suspected. We sought to evaluate automated HAS detection by commercial software and compared its performance to that of trained physicians against a reference standard.

Textbook outcome among patients undergoing enhanced recovery after liver transplantation stratified by risk. A single-center retrospective observational cohort study.

Background & Aims: Liver transplantation (LT) is one of the most complex surgical procedures. Enhanced recovery after surgery (ERAS) aims to reduce the risk of postoperative complications. When patients achieve all desirable outcomes after a procedure, they are considered to have experienced a textbook outcome (TO).

Enhanced recovery after low- and medium-risk liver transplantation. A single-center prospective observational cohort study.

Background & Aims: Few studies have fully applied an enhanced recovery after surgery (ERAS) protocol to liver transplantation (LT). Our aim was to assess the effects of a comprehensive ERAS protocol in our cohort of low- and medium-risk LT patients.

Methods: The ERAS protocol included pre-, intra-, and post-operative steps.

Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows.

Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH yield (CH y = CH /DMI) per cow.

Differential expression of long non-coding RNAs are related to proliferation and histological diversity in follicular lymphomas.

Long non-coding RNAs (lncRNAs) comprise a family of non-coding transcripts that are emerging as relevant gene expression regulators of different processes, including tumour development. To determine the possible contribution of lncRNA to the pathogenesis of follicular lymphoma (FL) we performed RNA-sequencing at high depth sequencing in primary FL samples ranging from grade 1-3A to aggressive grade 3B variants using unpurified (n = 16) and purified (n = 12) tumour cell suspensions from nodal samples. FL grade 3B had a significantly higher number of differentially expressed lncRNAs (dif-lncRNAs) with potential target coding genes related to cell cycle regulation.

Unsupervised GRN Ensemble.

Inferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that different methods have some particular biases and strengths, and none of them is the best across all types of data and datasets. As a result, the idea of aggregating various network inferences through a consensus mechanism naturally arises.

Can Deep Learning Improve Genomic Prediction of Complex Human Traits?

The genetic analysis of complex traits does not escape the current excitement around artificial intelligence, including a renewed interest in "deep learning" (DL) techniques such as Multilayer Perceptrons (MLPs) and Convolutional Neural Networks (CNNs). However, the performance of DL for genomic prediction of complex human traits has not been comprehensively tested. To provide an evaluation of MLPs and CNNs, we used data from distantly related white Caucasian individuals ( ∼100k individuals, ∼500k SNPs, and = 1000) of the interim release of the UK Biobank.

Study of Meta-analysis strategies for network inference using information-theoretic approaches.

Background: Reverse engineering of gene regulatory networks (GRNs) from gene expression data is a classical challenge in systems biology. Thanks to high-throughput technologies, a massive amount of gene-expression data has been accumulated in the public repositories. Modelling GRNs from multiple experiments (also called integrative analysis) has; therefore, naturally become a standard procedure in modern computational biology.

NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.

Background: In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods.

Hierarchical clustering combining numerical and biological similarities for gene expression data classification.

High throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A wide variety of tools exist in the literature using biological knowledge to evaluate analysis results.

NCX-1000, a nitric oxide-releasing derivative of UDCA, does not decrease portal pressure in patients with cirrhosis: results of a randomized, double-blind, dose-escalating study.

Objectives: NCX-1000 (2(acetyloxy) benzoic acid-3(nitrooxymethyl)phenyl ester) is an nitric oxide (NO)-releasing derivative of ursodeoxycholic acid (UDCA), which showed selective vasodilatory effect on intrahepatic circulation in animal models of cirrhosis. This study was aimed at testing the efficacy and tolerability of this compound in patients with cirrhosis and portal hypertension.

Methods: This was a single-center, phase-2a, randomized (4:1), double-blind, parallel-group, dose-escalating study.

Influence of beta-2 adrenergic receptor gene polymorphism on the hemodynamic response to propranolol in patients with cirrhosis.

The beta-2-adrenergic receptor (beta(2-)-AR) has several single-nucleotide polymorphisms. These influence the functional response to adrenergic stimulation; genotypes homozygous for Gly16-Glu27 or Gly16-Gln27 alleles (Gly16-Glu/Gln27 haplotypes) are associated with enhanced response, whereas genotypes homozygous for Arg16-Gln27 alleles (Arg16-Gln27) show a decreased response. We hypothesized that gene polymorphisms at the beta2-AR may influence the hemodynamic response to propranolol in patients with cirrhosis.

[Usefulness of tomographic computer colonography for colorectal polyp detection].

Background And Objective: Colonoscopy is the procedure of choice for the diagnosis of colorectal neoplasms. CT colonography (CTC), a recently developed minimal invasive radiological technique, permits the identification of colorectal tumors. The aim of the present study was to evaluate the efficacy of CTC in the detection of colorectal polyps, and to establish the factors determining a diagnostic accuracy.