HIV/AIDS

Basal and Infectious Enteritis in Broilers Under the I See Inside Methodology: A Chronological Evaluation.

Recently, the inflammation of the intestinal mucosa has been related to many diseases in humans and animals. The concept of Microscopic Enteritis (ME) used in human pathology through the Marsh classification system has no counter-part in veterinary medicine. In poultry science, the I See Inside (ISI) methodology, unlike the current linear measures of villi and crypts, generates possibilities to de...

Cenicriviroc, a dual CCR2 and CCR5 antagonist leads to a reduction in plasma fibrotic biomarkers in persons living with HIV on antiretroviral therapy.

Chronic HIV is associated with increased inflammation and tissue fibrosis despite suppressive antiretroviral therapy (ART). Monocytes and macrophages have been implicated in the pathogenesis of fibrosis, facilitated by chemokine receptor interactions. We assessed systemic fibrotic biomarkers (transforming growth factor beta-1 [TGF-β1], thrombospondin-1 [TSP-1], C-terminal pro-peptide of collagen ...

Prediction of Contact Residues in Anti-HIV Neutralizing Antibody by Deep Learning.

The monoclonal antibody 1C10 targets the V3 loop of HIV-1 and neutralizes a broad range of clade B viruses. However, the mode of interaction between 1...

Characterization of low level viraemia in HIV-infected patients receiving boosted protease inhibitor-based antiretroviral regimens.

To understand the pathogenesis of low level viraemia (LLV) in HIV-infected patients on boosted protease inhibitors (PI/b), we enrolled 34 subjects wit...

Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have pro...

Improved protein structure prediction using potentials from deep learning.

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence. This problem is of fundam...

SVM-Enabled Intelligent Genetic Algorithmic Model for Realizing Efficient Universal Feature Selection in Breast Cyst Image Acquired via Ultrasound Sensing Systems.

In recent years, there are several cost-effective intelligent sensing systems such as ultrasound imaging systems for visualizing the internal body str...

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by...

Drug resistance patterns in HIV patients with virologic failure in Iran.

We reviewed the medical charts of 1,700 patients diagnosed with HIV who referred to a central HIV clinic in Tehran between 2004 and 2017. Participants...

A comparison of machine learning techniques for classification of HIV patients with antiretroviral therapy-induced mitochondrial toxicity from those without mitochondrial toxicity.

BACKGROUND: Antiretroviral therapy (ART) has significantly reduced HIV-related morbidity and mortality. However, therapeutic benefit of ART is often l...

Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5.

Sirtuin 5 is a class III histone deacetylase that, unlike its classification, mainly catalyzes desuccinylation and demanoylation reactions. It is an i...

On semiparametric estimation of a path-specific effect in the presence of mediator-outcome confounding.

Path-specific effects constitute a broad class of mediated effects from an exposure to an outcome via one or more causal pathways along a set of inter...

Abstract art paintings, global image properties, and verbal descriptions: An empirical and computational investigation.

While global image properties (GIPs) relate to preference ratings in many categories of visual stimuli, this relationship is typically not seen for ab...

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection...

Object detection and recognition: using deep learning to assist the visually impaired.

BACKGROUND: Deep learning systems have improved performance of devices through more accurate object detection in a significant number of areas, for me...

White blood cells detection and classification based on regional convolutional neural networks.

White blood cells (WBC) are important parts of our immune system and they protect our body against infections by eliminating viruses, bacteria, parasi...

Virological Outcome Measures During Analytical Treatment Interruptions in Chronic HIV-1-Infected Patients.

BACKGROUND: Analytical treatment interruptions (ATIs) are essential in research on HIV cure. However, the heterogeneity of virological outcome measure...

The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach.

Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicin...

CD4+ versus CD8+ T-lymphocyte identification in an integrated microfluidic chip using light scattering and machine learning.

T lymphocytes are a group of cells representing the main effectors of human adaptive immunity. Characterization of the most representative T-lymphocyt...

A SEMIPARAMETRIC MODELING APPROACH USING BAYESIAN ADDITIVE REGRESSION TREES WITH AN APPLICATION TO EVALUATE HETEROGENEOUS TREATMENT EFFECTS.

Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and covariat...