Sepsis

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes mu...

Mapping the transmission risk of Zika virus using machine learning models.

Zika virus, which has been linked to severe congenital abnormalities, is exacerbating global public health problems with its rapid transnational expansion fueled by increased global travel and trade. Suitability mapping of the transmission risk of Zika virus is essential for drafting public health plans and disease control strategies, which are especially important in areas where medical resources...

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subj...

The comparison of pleural fluid TNF-α levels in tuberculous and nontuberculous pleural effusion.

BACKGROUND: Tuberculous pleural effusion is the manifestation of Mycobacterium tuberculosis infection in pleura. With existing means, it is difficult ...

Inhalable Fucoidan Microparticles Combining Two Antitubercular Drugs with Potential Application in Pulmonary Tuberculosis Therapy.

The pulmonary delivery of antitubercular drugs is a promising approach to treat lung tuberculosis. This strategy not only allows targeting the infecte...

Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions.

Hepatitis C virus (HCV) infection is a global public health problem. The implementation of public health interventions (PHI) to control HCV infection ...

Tracking antibiotic resistance gene pollution from different sources using machine-learning classification.

BACKGROUND: Antimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in a...

Ultrashort Self-Assembling Peptide Hydrogel for the Treatment of Fungal Infections.

The threat of antimicrobial resistance to society is compounded by a relative lack of new clinically effective licensed therapies reaching patients ov...

Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning.

This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum using Raman spectroscopy combined with pattern recognition ...

Improved prediction of fungal effector proteins from secretomes with EffectorP 2.0.

Plant-pathogenic fungi secrete effector proteins to facilitate infection. We describe extensive improvements to EffectorP, the first machine learning ...

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica.

Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to new niches remains a challenge. New methods are u...

Phenotypic Antimicrobial Susceptibility Testing with Deep Learning Video Microscopy.

Timely determination of antimicrobial susceptibility for a bacterial infection enables precision prescription, shortens treatment time, and helps mini...

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. I...

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is considered a degenerative disorder that affects the motor system, which may cause tremors, micro...

Electronic Surveillance For Catheter-Associated Urinary Tract Infection Using Natural Language Processing.

Catheter-associated urinary tract infection (CAUTI) is a common and costly healthcare-associated infection, yet measuring it accurately is challenging...

Leaf Extracts and Their Quercetin Protect HepG2 Cell Lines Against CCL Induced Cytotoxicity.

The present study was carried out to evaluate the in vitro cytoprotective effects of and their isolated quercetin fraction to reduce the CCl (carbon ...

Prevalence and genotypes of Giardia lamblia from stray dogs and cats in Guangdong, China.

Giardia lamblia is a worldwide zoonotic intestinal parasite that infects humans and a wide range of mammals including dogs and cats, causing giardiasi...

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical- Approach Combining Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in ...

Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.

BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essenti...

Predicting urinary tract infections in the emergency department with machine learning.

BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine c...