Sepsis

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, and hence it remains to be a severe threat to the health of female. Based on drug repositioning strategy, we trained and benchmarked multiple machine l...

A Preliminary Investigation on the Antiviral Activities of the Philippine Marshmint (Mentha arvensis) Leaf Extracts against Dengue Virus Serotype 2 In Vitro.

In this study, we investigated the antiviral activity of lyophilized crude leaf extracts of the Philippine marshmint (Mentha arvensis L., commonly called yerba buena) against DENV-2 in vitro. The plant specimen was authenticated by DNA barcoding analysis using standard primers for amplification of rbcL, matK, ITS1, ITS2 and trnH-psbA. Aqueous, methanol and ethanol leaf extracts were prepared, and ...

SERS and advanced chemometrics - Utilization of Siamese neural network for picomolar identification of beta-lactam antibiotics resistance gene fragment.

The enormous development and expansion of antibiotic-resistant bacterial strains impel the intensive search for new methods for fast and reliable dete...

Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.

Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progressi...

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergenc...

Transfer learning based novel ensemble classifier for COVID-19 detection from chest CT-scans.

Coronavirus Disease 2019 (COVID-19) is a deadly infection that affects the respiratory organs in humans as well as animals. By 2020, this disease turn...

A Deep Learning Framework Integrating the Spectral and Spatial Features for Image-Assisted Medical Diagnostics.

The development of a computer-aided disease detection system to ease the long and arduous manual diagnostic process is an emerging research interest. ...

An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19.

A high-performing interpretable model is proposed to predict the risk of deterioration in coronavirus disease 2019 (COVID-19) patients. The model was ...

Optimizing Lipofectamine LTX Complex and G-418 Concentration for Improvement of Transfection Efficiency in Human Mesenchymal Stem Cells.

Conventional cancer therapies, including surgery, radiotherapy, and chemotherapy, are not tumor site-specific and have cytotoxic and harmful side effe...

Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning.

Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae s...

Biomimetic sharkskin surfaces with antibacterial, cytocompatible, and drug delivery properties.

Fighting with the infection is one of the most challenging and costly burdens of the healthcare system. Several types of antibiotics and antibacterial...

Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection.

The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity convolution U-Net algorithm for patients with sever...

Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI.

This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpret...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was ...

A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.

COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country's economy due to forced lockdowns. Its ...

Adrenal Insufficiency in Septic Patients Admitted to Intensive Care Unit: Prevalence and Associated Factors.

Adrenal insufficiency (AI) is associated with an increase in the risk of mortality in ICU-admitted septic patients. It should be suspected not only i...

Lactate levels as a prognostic predict in cardiogenic shock under venoarterial extracorporeal membrane oxygenation support.

INTRODUCTION AND OBJECTIVES: Lactate and its evolution are associated with the prognosis of patients in shock, although there is little evidence in th...

Structure-Based Drug Design Using Deep Learning.

In recent years, deep learning-based methods have emerged as promising tools for drug design. Most of these methods are ligand-based, where an initia...

Injectable conductive gelatin methacrylate / oxidized dextran hydrogel encapsulating umbilical cord mesenchymal stem cells for myocardial infarction treatment.

Umbilical cord mesenchymal stem cells (UCMSCs) transplantation has been proposed as a promising treatment modality for myocardial infarction (MI), but...

Proteome-Informed Machine Learning Studies of Cocaine Addiction.

No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate ...