Lymphoma

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Arti...

Asparaginase-associated concurrence of hyperlipidemia, hyperglobulinemia, and thrombocytosis was successfully treated by centrifuge/membrane hybrid double-filtration plasmapheresis.

Asparaginase-associated concurrence of hyperlipidemia, hyperglobulinemia, and thrombocytosis is a rare complication requiring aggressive lipoprotein apheresis, but no one of currently available lipoprotein apheresis methods can simultaneously resolve the 3 abnormalities. Herein, we reported a construction of double-filtration plasmapheresis (DFPP) using a combination of centrifugal/membranous plas...

A Study on the Effects of Sympathetic Skin Response Parameters in Diagnosis of Fibromyalgia Using Artificial Neural Networks.

Fibromyalgia syndrome (FMS), usually observed commonly in females over age 30, is a rheumatic disease accompanied by extensive chronic pain. In the di...

Follicle-stimulating hormone-induced rescue of cumulus cell apoptosis and enhanced development ability of buffalo oocytes.

The effect of follicle-stimulating hormone (FSH) on apoptotic status of cumulus cells, expression of proapoptotic and antiapoptotic genes, and develop...

A case of primary adrenal diffuse large B cell lymphoma presenting with severe hyponatremia.

We herein report a case of primary adrenal lymphoma with severe hyponatremia. The patient was admitted for an evaluation of severe hyponatremia and an...

Ginsenoside Rg1 Improves In vitro-produced Embryo Quality by Increasing Glucose Uptake in Porcine Blastocysts.

Ginsenoside Rg1 is a natural compound with various efficacies and functions. It has beneficial effects on aging, diabetes, and immunity, as well as an...

Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of tw...

Application of artificial neural networks to co-combustion of hazelnut husk-lignite coal blends.

The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperatur...

Harnessing Computational Biology for Exact Linear B-Cell Epitope Prediction: A Novel Amino Acid Composition-Based Feature Descriptor.

Proteins embody epitopes that serve as their antigenic determinants. Epitopes occupy a central place in integrative biology, not to mention as targets...

Artificial Neural Network applied as a methodology of mosquito species identification.

There are about 200 species of mosquitoes (Culicidae) known to be vectors of pathogens that cause diseases in humans. Correct identification of mosqui...

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in o...

Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms.

We investigate a new method to place patients into risk groups in censored survival data. Properties such as median survival time, and end survival ra...

Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.

Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signalin...

ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.

The present study explores for the first time the possibility of modelling sediment concentration with artificial neural networks (ANNs) at Gangotri, ...

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-respon...

Application of neural networks with back-propagation to genome-enabled prediction of complex traits in Holstein-Friesian and German Fleckvieh cattle.

BACKGROUND: Recently, artificial neural networks (ANN) have been proposed as promising machines for marker-based genomic predictions of complex traits...

Evaluation of combinations of in vitro sensitization test descriptors for the artificial neural network-based risk assessment model of skin sensitization.

The skin sensitization potential of chemicals has been determined with the use of the murine local lymph node assay (LLNA). However, in recent years p...

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Col...

Correlation of plasma crizotinib trough concentration with adverse events in patients with anaplastic lymphoma kinase positive non-small-cell lung cancer.

BACKGROUND: Crizotinib, an ATP-competitive receptor tyrosine kinase inhibitor of both anaplastic lymphoma kinase (ALK) and the hepatocyte growth facto...

Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is pro...