Steroids

Predicting long-term kidney graft failure using novel multi-omic blood-based biomarkers and artificial intelligence tools.

Kidney transplantation (KT) remains the preferred treatment for end-stage renal disease. With advancements in immunosuppressive regimens and KT surveillance, graft survival has improved, though mainly in short-term. Meanwhile, aging populations with multimorbidity and expanding donor criteria shape a new landscape for KT management. Numerous prediction tools, including genomic, transcriptomic and/...

Brainstem noradrenergic modulation of the kisspeptin neuron GnRH pulse generator in mice.

Brainstem noradrenaline (NA) neurons modulate the activity of many neural networks including those responsible for the control of fertility. Using brain slice electrophysiology, we demonstrate that the arcuate nucleus kisspeptin (ARN) neurons, recently identified to be the gonadotropin-releasing hormone (GnRH) pulse generator, are directly hyperpolarized by NA through both alpha 2- and beta-adrene...

BGATT-GR: accurate identification of glucocorticoid receptor antagonists based on data augmentation combined with BiGRU-attention.

The glucocorticoid receptor (GR) is a critical nuclear receptor that regulates a broad spectrum of physiological functions, including stress adaptatio...

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...

Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning.

BACKGROUND: Acute graft-versus-host disease (aGVHD) is a major post-transplantation complication and one of the most significant causes of non-relapse...

Boosting Checkpoint Blockade Immunotherapy with T Cell Membrane Redox Homeostasis Regulation and Deep Learning Enhanced NIR-II Imaging.

Immune checkpoint blockade therapy has revolutionized clinical oncotherapy by intercepting immunosuppressive pathways in tumor tissues. Nevertheless, ...

Should We Use Behavioural Predictions in Organ Allocation?

Medical predictions, for example, concerning a patient's likelihood of survival, can be used to efficiently allocate scarce resources. Predictions of ...

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. ...

Integrating ocular and clinical features to enhance intravenous glucocorticoid response prediction in thyroid eye disease: a machine learning approach.

PURPOSES: Predicting intravenous glucocorticoid (IVGC) efficacy in thyroid eye disease (TED) is vital for personalized treatment and minimizing side e...

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...

A multidimensional prediction model for overtraining risk in youth soccer players: Integrating physiological and psychological markers.

Overtraining syndrome (OTS) poses a critical challenge in youth soccer, particularly during periods of rapid physiological maturation combined with hi...

Understanding stress-induced illegitimate aggression: the role of physiological and psychological factors in police cadets.

To better understand the consequences of stress in realistic scenarios, police cadets were tasked with performing a police intervention under differin...

An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.

Artificial Intelligence (AI) offers a revolutionary approach to improve decision-making in medicine through the use of advanced computational tools. I...

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 ...

Machine learning using serial changes in proteinuria during initial steroid therapy to predict treatment response and immunosuppressant use in pediatric idiopathic nephrotic syndrome.

BACKGROUND: Epidemiological studies on idiopathic nephrotic syndrome (INS) in children have identified no definitive factors predicting steroid-resist...

Machine learning is changing osteoporosis detection: an integrative review.

Machine learning drives osteoporosis detection and screening with higher clinical accuracy and accessibility than traditional osteoporosis screening t...

Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based Risk Calculator with Explainable Artificial Intelligence (XAI).

BACKGROUND: Tuberculosis spondylitis (TS), also known as Pott's disease, is the most common destructive form of musculoskeletal tuberculosis and poses...

Development of an immune scoring system based on exosome-related gene expression for prognosis and treatment response prediction in breast cancer.

Breast cancer (BC) is a heterogeneous disease with diverse subtypes that influence prognosis and treatment outcomes. While advances have been made in ...