Menopause

Machine learning reveals sex-specific 17β-estradiol-responsive expression patterns in white perch (Morone americana) plasma proteins.

With growing abundance and awareness of endocrine disrupting compounds (EDCs) in the environment, there is a need for accurate and reliable detection of EDC exposure. Our objective in the present study was to observe differences within and between the global plasma proteomes of sexually mature male and female white perch (Morone americana) before (Initial Control, IC) and after 17β-estradiol (E2 )...

Using swing resistance and assistance to improve gait symmetry in individuals post-stroke.

A major characteristic of hemiplegic gait observed in individuals post-stroke is spatial and temporal asymmetry, which may increase energy expenditure and the risk of falls. The purpose of this study was to examine the effects of swing resistance/assistance applied to the affected leg on gait symmetry in individuals post-stroke. We recruited 10 subjects with chronic stroke who demonstrated a short...

Population pharmacokinetic/pharmacodynamic assessment of pharmacological effect of a selective estrogen receptor β agonist on total testosterone in healthy men.

BACKGROUND: LY500307 is a highly selective estrogen receptor β (ERβ) agonist, which loses its selectivity at high dose and leads to undesirable suppre...

Effect of uterine size on fertility of lactating dairy cows.

There are multiple reasons for reduced fertility in lactating dairy cows. We hypothesized that one cause of reduced fertility could be the overall siz...

Effects of xenoestrogens in human M1 and M2 macrophage migration, cytokine release, and estrogen-related signaling pathways.

Bisphenol A (BPA), bis(2-ethylhexyl)phthalate (DEHP) and di(n-butyl)phthalate (DBP) are environmental estrogens that have been associated with a wide ...

Recurrence quantification analysis and support vector machines for golf handicap and low back pain EMG classification.

The quantification of non-linear characteristics of electromyography (EMG) must contain information allowing to discriminate neuromuscular strategies ...

Efficient prediction of progesterone receptor interactome using a support vector machine model.

Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researcher...

Prediction and quantifying parameter importance in simultaneous anaerobic sulfide and nitrate removal process using artificial neural network.

The present investigation deals with the prediction of the performance of simultaneous anaerobic sulfide and nitrate removal in an upflow anaerobic sl...

Robust and Quality-of-Life-Aware Treatment Protocols in NSCLC using Deep Reinforcement Learning

Under current systemic treatment of metastatic cancer, a drug is frequently prescribed at maximum tolerable dose (MTD) until either unacceptable toxic...

Video-Based Palm-Vein Authentication under Challenging Conditions

Palm-vein biometrics are increasingly used for secure, contactless authentication. Yet real-world deployment exposes them to surface noise (sweat, dir...

Interpretable Symptom Vectors for Depression in a Large Language Model

Patients with depression present with diverse symptom profiles, yet clinical practice routinely reduces this variation to a single severity score. Lar...

Auditable CT Phenotyping Through Report-derived Radiological Observations

Medical image foundation models can predict clinical phenotypes from computed tomography (CT), but strong performance leaves open whether they read di...

MRI-based Deep Radiomic Phenotyping of Neuromuscular Disorders: A Topology-driven Characterization

Quantitative assessment of muscle MRI is crucial for monitoring neuromuscular disorders (NMD). This study introduces an automated radiomic phenotyping...

Development of a Deep Learning Model for Opportunistic Screening of Osteoporosis using Chest Radiographs

Purpose Prevention and early detection of osteoporosis remains a global challenge, more so in regions like the Philippines where screening barriers ex...

Classifying CRISPR-Cas9 Off-Target Cleavage Sites from GUIDE-seq Data: A Class-Imbalanced Machine Learning Benchmark

Off-target cleavage is a central safety concern for CRISPR-Cas9 genome editing, particularly in therapeutic applications where unintended double-stran...

TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters

Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and glo...

Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks

Bio-based alternatives for conventional rigid foams have proven to be good substituents owing to their enhanced sustainability and competitive perform...

MetaboLLM: a metabolomics-specialized large language model for biochemical knowledge integration and predictive metabolite graph construction

Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to translate into predictive representations. We developed ...

A systematic evaluation of machine learning classifiers for event-by-event background rejection in LAFOV PET scanners

The introduction of LAFOV PET scanners brings significant sensitivity gains but also a substantial increase in the background rate from accidental coi...

How does CBT work? Causal discovery modelling locates the mechanisms of change in cognitive behavioural treatment for eating disorders

Background: Cognitive behavioural therapy (CBT) is the most frequently used and recommended therapy program for mental health conditions, including fo...