Tuberculosis

Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins.

Mycobacterium is a pathogenic bacterium, which is a causative agent of tuberculosis (TB) and leprosy. These diseases are very crucial and become the cause of death of millions of people every year in the world. So, the characterize structure of membrane proteins of the protozoan play a vital role in the field of drug discovery because, without any knowledge about this Mycobacterium's membrane prot...

The Cost-effectiveness of a Point-of-Care Paper Transaminase Test for Monitoring Treatment of HIV/TB Co-Infected Persons.

BACKGROUND: Persons with HIV and tuberculosis (TB) co-infection require transaminase monitoring while on hepatotoxic medications. A novel paper-based, point-of-care transaminase test is in development at an anticipated cost of $1 per test.

A New Hybrid Model Using an Autoregressive Integrated Moving Average and a Generalized Regression Neural Network for the Incidence of Tuberculosis in Heng County, China.

It is a daunting task to eradicate tuberculosis completely in Heng County due to a large transient population, human immunodeficiency virus/tuberculos...

Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most of them in developing countries. Many of those deat...

Efficient and robust cell detection: A structured regression approach.

Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnos...

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for detecting tuberculosis (TB) on chest radiographs. Materials and Met...

A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty.

The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and ...

Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for th...

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium ...

Diaryltriazenes as antibacterial agents against methicillin resistant Staphylococcus aureus (MRSA) and Mycobacterium smegmatis.

Diaryltriazene derivatives were synthesized and evaluated for their antimicrobial properties. Initial experiments showed some of these compounds to ha...

Improving Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) Treatment Monitoring in South Africa: Evaluation of an Advanced TB/HIV Course for Healthcare Workers.

BACKGROUND: South Africa has dual epidemics of human immunodeficiency virus (HIV) and tuberculosis (TB). Nurse-focused training was combined with onsi...

Use of quantum dot beads-labeled monoclonal antibody to improve the sensitivity of a quantitative and simultaneous immunochromatographic assay for neuron specific enolase and carcinoembryonic antigen.

Detection of multiplex tumor markers was of great importance for cancer diagnosis. Immunochromatographic test strip (ICTS) was the most frequently-use...

Optimization of an Anti-poly(ethylene glycol) (anti-PEG) Cell-Based Capture System To Quantify PEG and PEGylated Molecules.

Sensitive determination of the pharmacokinetics of PEGylated molecules can accelerate the process of drug development. Here, we combined different ant...

Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients.

Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin c...

Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015).

The renewed urgency to develop new treatments for Mycobacterium tuberculosis (Mtb) infection has resulted in large-scale phenotypic screening and thou...

Synthesis, identification and in vitro biological evaluation of some novel quinoline incorporated 1,3-thiazinan-4-one derivatives.

The present study describes the synthesis of two new series of 3-hydroxy-N-(4-oxo-2-phenyl-1,3-thiazinan-3-yl)-8-(trifluoromethyl)quinoline-2-carboxam...

Effect of goat milk on hepatotoxicity induced by antitubercular drugs in rats.

Aim of the present study was to assess the hepatoprotective activity of goat milk on antitubercular drug-induced hepatotoxicity in rats. Hepatotoxicit...

An Imbalanced Learning based MDR-TB Early Warning System.

As a man-made disease, multidrug-resistant tuberculosis (MDR-TB) is mainly caused by improper treatment programs and poor patient supervision, most of...

Learning With Jensen-Tsallis Kernels.

Jensen-type [Jensen-Shannon (JS) and Jensen-Tsallis] kernels were first proposed by Martins et al. (2009). These kernels are based on JS divergences t...

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for...