HRT

Development of Artificial Intelligence-Assisted Lumbar and Femoral BMD Estimation System Using Anteroposterior Lumbar X-Ray Images.

The early detection and treatment of osteoporosis and prevention of fragility fractures are urgent societal issues. We developed an artificial intelligence-assisted diagnostic system that estimated not only lumbar bone mineral density but also femoral bone mineral density from anteroposterior lumbar X-ray images. We evaluated the performance of lumbar and femoral bone mineral density estimations a...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast cancer (BC) is unknown. We tested the hypothesis that inhibition of METTL3, the methyltransferase responsible for the mRNA modification N-6 methyladenosine (m6A), alters m6A modifications and differentially regulates the abundance of mRNA transcripts...

Exploring graph-based models for predicting active compounds against triple-negative breast cancer.

Breast cancer is among the most dominant and rapidly rising cancers, both in India and around the world. Triple-negative breast cancer (TNBC) is one o...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher...

Machine learning for predicting and optimizing the performance of a commercial-scale anaerobic digester with diverse feedstocks and operating conditions.

The improper disposal of food waste and livestock manure poses significant environmental risks, including nutrient pollution, water contamination, and...

Quantitative CT Imaging in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous condition characterized by diverse pulmonary and extrapulmonary manifestations....

Discovery of novel cathepsin K inhibitors for osteoporosis treatment using a deep learning-based strategy.

BACKGROUND: Cathepsin K (CTSK), a cysteine protease of the papain family, exhibits high expression in activated osteoclasts, making it a key therapeut...

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.

Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concern of women. Breast cancer etiology implicates nume...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans, but this approach introduces additional ionizing ...

Radiomics and machine learning for osteoporosis detection using abdominal computed tomography: a retrospective multicenter study.

OBJECTIVE: This study aimed to develop and validate a predictive model to detect osteoporosis using radiomic features and machine learning (ML) approa...

ERRα-Predictor: A Framework of Ensemble Models for Prediction of ERRα Binders, Antagonists, and Agonists Using Artificial Intelligence.

Estrogen-related receptor α (ERRα) is considered a promising target for the treatment of cancer and metabolic diseases. The development of comprehensi...

Machine Learning and Large Language Models for Modeling Complex Toxicity Pathways and Predicting Steroidogenesis.

High-throughput screening and computational models have been effective in predicting chemical interactions with estrogen and androgen receptors, but s...

3Mont: A multi-omics integrative tool for breast cancer subtype stratification.

Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types among women. Developing effective treatment strategi...

Aptamer-directed siRNA delivery systems for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the absence of estrogen, progesterone, and HER2 recept...

Artificial intelligence for predicting the risk of bone fragility fractures in osteoporosis.

Osteoporosis is widespread with a high incidence rate, resulting in fragility fractures which are a major contributor to mortality among the elderly. ...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools for effective disease management and fracture preve...

Droplet microfluidics integrated with machine learning reveals how adipose-derived stem cells modulate endocrine response and tumor heterogeneity in ER breast cancer.

Approximately 70% of breast cancer (BC) diagnoses are estrogen receptor positive (ER) with ∼40% of ER BC patients presenting resistance to endocrine ...

The role of tumor microenvironment and immune cell crosstalk in triple-negative breast cancer (TNBC): Emerging therapeutic opportunities.

Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by its lack of estrogen, progesterone, and HER2 receptors, leading to limi...

Investigating the potential risk of cadmium exposure on Osteoporosis: An integrated multi-omics approach.

Osteoporosis (OP) is a chronic progressive bone disease, and its occurrence and development under cadmium exposure remain unclear. This study aims to ...