Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3412519PMC
http://dx.doi.org/10.1016/j.jaci.2009.12.983DOI Listing

Publication Analysis

Top Keywords

biomarkers predict
4
predict presence
4
presence fas
4
fas mutations
4
mutations patients
4
patients features
4
features autoimmune
4
autoimmune lymphoproliferative
4
lymphoproliferative syndrome
4
biomarkers
1

Similar Publications

Background: Benign and malignant breast tumors differ in their microvasculature morphology and distribution. Histologic biomarkers of malignant breast tumors are also correlated with the microvasculature. There is a lack of imaging technology for evaluating the microvasculature.

View Article and Find Full Text PDF

Background: Gene signatures derived from transcriptomic-causal networks offer potential for tailoring clinical care in cancer treatment by identifying predictive and prognostic biomarkers. This study aimed to uncover such signatures in metastatic colorectal cancer (CRC) patients to aid treatment decisions.

Methods: We constructed transcriptomic-causal networks and integrated gene interconnectivity into overall survival (OS) analysis to control for confounding genes.

View Article and Find Full Text PDF

This study addresses the limited noninvasive tools for Head and Neck Squamous Cell Carcinoma (HNSCC) progression-free survival (PFS) prediction by identifying Computed Tomography (CT)-based biomarkers for predicting prognosis. A retrospective analysis was conducted on data from 203 HNSCC patients. An ensemble feature selection involving correlation analysis, univariate survival analysis, best-subset selection, and the LASSO-Cox algorithm was used to select functional features, which were then used to build final Cox Proportional Hazards models (CPH).

View Article and Find Full Text PDF

Clinical decision-making is driven by multimodal data, including clinical notes and pathological characteristics. Artificial intelligence approaches that can effectively integrate multimodal data hold significant promise in advancing clinical care. However, the scarcity of well-annotated multimodal datasets in clinical settings has hindered the development of useful models.

View Article and Find Full Text PDF

Sleep is essential for brain development and overall health, particularly in children with neurodevelopmental disorders (NDDs). Sleep disruptions can considerably impact brain structure and function, leading to dysfunction of neurotransmitter systems, metabolism, hormonal balance and inflammatory processes, potentially contributing to the pathophysiology of NDDs. This Review examines the prevalence, types and mechanisms of sleep disturbances in children with NDDs, including autism spectrum disorder, attention-deficit hyperactivity disorder and various genetic syndromes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!