Steroids

The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray features extracted by deep learning to alert high-risk osteoporosis populations.

Rapid Stability Indicating HPLC Method for the Analysis of Leflunomide and Its Related Impurities in Bulk Drug and Formulations.

OBJECTIVES: Leflunomide (LFNM) is a drug that belongs to isoxazole derivatives and has immunosuppressive and anti-inflammatory activities. A literature search confirms that there is no method reported for the simultaneous estimation of LFNM and its related impurities A and B in pharmaceutical dosage forms or in bulk drug. Hence the present work aimed to develop a simple stability indicating RP-HPL...

Steroid identification via deep learning retention time predictions and two-dimensional gas chromatography-high resolution mass spectrometry.

Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromat...

The Use of Transdermal Estrogen in Castrate-resistant, Steroid-refractory Prostate Cancer.

BACKGROUND: Androgen-deprivation therapy is the mainstay of treatment for metastatic prostate cancer. Corticosteroids and estrogens are also useful ag...

Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

The goal of this study is to estimate micro-architectural parameters of cortical porosity such as pore diameter (φ), pore density (ρ) and porosity (ν)...

Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry.

Background Detection of vertebral fractures (VFs) aids in management of osteoporosis and targeting of fracture prevention therapies. Purpose To determ...

Supplementation of OmniGen-AF improves the metabolic response to a glucose tolerance test in beef heifers.

This study determined whether feeding the immunomodulating supplement, OmniGen-AF, to feedlot heifers would alter metabolic profiles to a glucose tole...

Screening and Assessment of Bone Health in Indian Women Using an Indigenous ELISA of Human Osteocalcin a Bone Turnover Marker.

Osteoporosis a major public health problem of the elderly, is associated with substantial morbidity and socio economic burden. The aim of the study wa...

Artificial neural network optimizes self-examination of osteoporosis risk in women.

OBJECTIVE: This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool f...

Non-steroid anti-inflammatory drugs reduce the efficacy of autologous blood pleurodesis.

BACKGROUND: This study aims to perform autologous blood pleurodesis in an animal model and investigate the effects of paracetamol and diclofenac on au...

HTR2C Gene Variant and Salivary Cortisol Levels after Endurance Physical Activity: A Pilot Study.

INTRODUCTION: The 5-hydroxytryptamine 2C receptor (HTR2C) rs6318 polymorphism has been associated with increased sensitivity to stress. This study inv...

Deep Learning-Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational Study.

BACKGROUND AND PURPOSE: 3D reconstruction of a targeted area ("safe" triangle and Kambin triangle) may benefit the viability assessment of transforami...

Artificial Intelligence based facial recognition for Mood Charting among men on life style modification and it's correlation with cortisol.

UNLABELLED: Today, clinicians and researchers believe that mood disorders in children and adolescents remain one of the most under diagnosed mental he...

Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade.

PURPOSE: Osteoporosis is an underdiagnosed condition despite effective screening modalities. Dual-energy x-ray absorptiometry (DEXA) screening, althou...

Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods.

Saponins are a type of compounds bearing a hydrophobic steroid/triterpenoid moiety and hydrophilic carbohydrate branches. The majority of the saponins...

Machine Learning Based Real-Time Image-Guided Cell Sorting and Classification.

Cell classification based on phenotypical, spatial, and genetic information greatly advances our understanding of the physiology and pathology of biol...

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk ...

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for r...

Job interview training targeting nonverbal communication using an android robot for individuals with autism spectrum disorder.

Job interviews are significant barriers for individuals with autism spectrum disorder because these individuals lack good nonverbal communication skil...

Prevalence of Vitamin D Inadequacy Among Chinese Postmenopausal Women: A Nationwide, Multicenter, Cross-Sectional Study.

We aimed to investigate the status of serum 25-hydroxyvitamin D [25(OH)D] among Chinese postmenopausal women in a multicenter cross-sectional study. ...