Sepsis

Cholecalciferol, Ergosterol, and Cholesterol Enhance the Antibiotic Activity of Drugs.

UNLABELLED: Background: This is the first report demonstrating the antibiotic-modifying activity of cholecalciferol.

Estimating the association between antibiotic exposure and colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria using machine learning methods: a multicentre, prospective cohort study.

OBJECTIVES: The aim of the study was to measure the impact of antibiotic exposure on the acquisition of colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria (ESBL-GNB) accounting for individual- and group-level confounding using machine-learning methods.

A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity.

Reservoir computing is a biologically inspired class of learning algorithms in which the intrinsic dynamics of a recurrent neural network are mined to...

Weekly ILI patient ratio change prediction using news articles with support vector machine.

BACKGROUND: Influenza continues to pose a serious threat to human health worldwide. For this reason, detecting influenza infection patterns is critica...

A machine learning approach for predicting urine output after fluid administration.

BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.

Multiple tracking and machine learning reveal dopamine modulation for area-restricted foraging behaviors via velocity change in Caenorhabditis elegans.

Food exploration is an essential survival behavior in organisms. To find food efficiently, many organisms use a foraging strategy called area-restrict...

Streptococcus Gallolyticus endocarditis in patient with liver cirrhosis: a case report.

Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and diseases of gastrointestinal tract, especially wi...

Construction and optimization of a 'NG Morbidostat' - An automated continuous-culture device for studying the pathways towards antibiotic resistance in .

To obtain a detailed picture of the dynamics of antibiotic resistance development in , we built a morbidostat according to the protocol of Toprak ., a...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning systems can increase timely sepsis detection using e...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scie...

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed ...

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms.

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics...

Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs.

The emergence of microbes resistant to common antibiotics represent a current treat to human health. It has been recently recognized that non-antibiot...

In vitro anti-Trichomonas vaginalis activity of Haplophyllum myrtifolium.

INTRODUCTION: In the classic treatment of Trichomonas vaginalis infection, although metronidazole has been used since the 1960s, there has been an inc...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form requires monitoring and repeat serological and molec...

Dissecting the Catecholamines: How New Approaches Will Facilitate the Distinction between Noradrenergic and Dopaminergic Systems.

To overcome the limitations of fast scan cyclic voltammetry (FSCV) to discriminate between catecholamines, we discuss new approaches to monitor the dy...

Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.

BACKGROUND AND AIM: We recently reported the role of artificial intelligence in the diagnosis of Helicobacter pylori (H. pylori) gastritis on the basi...

Interpretable genotype-to-phenotype classifiers with performance guarantees.

Understanding the relationship between the genome of a cell and its phenotype is a central problem in precision medicine. Nonetheless, genotype-to-phe...

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Emotional arousal often facilitates memory for some aspects of an event while impairing memory for other aspects of the same event. Across three exper...

Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI.

Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in identifying abnormalities in the substantia nigra pars compacta (SNc) ...