Download full-text PDF

Source

Publication Analysis

Top Keywords

[good markers
4
markers tsh
4
tsh monitoring
4
monitoring autoimmune
4
autoimmune thyroid
4
thyroid diseases]
4
[good
1
tsh
1
monitoring
1
autoimmune
1

Similar Publications

Introduction: Chronic spontaneous urticaria (CSU) is defined as the appearance of itchy wheals and/or angioedema for at least 6 weeks. Cigarette smoking is one of the world's most common addictions. It is a cause of serious diseases such as renal cancer or thromboembolic incidents.

View Article and Find Full Text PDF

Background: Obesity plays a crucial role in the development of metabolic disorders including diabetes, coronary and renal diseases. There are several factors involved in the pathology of obesity, including chronic inflammation and exposure to environmental contaminants. Recently, the cholinergic co-hydrolyzing enzyme BChE has been associated with clinical conditions such as diabetes and obesity.

View Article and Find Full Text PDF

The constantly emerging evidence indicates a close association between coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD). However, the exact mechanisms underlying their mutual relationship remain undefined. This study aims to explore the common signature genes, potential mechanisms, diagnostic markers, and therapeutic targets for CAD and NAFLD.

View Article and Find Full Text PDF

Primary sclerosing cholangitis (PSC) is associated with a high risk of hepatobiliary malignancy, especially cholangiocarcinoma (CCA). There are no good tumor markers to screen for CCA, and current recommendations for PSC monitoring are mainly based on expert opinions. The optimal strategy to assess disease progression and screen for CCA - the main cause of death of PSC patients - remains unclear.

View Article and Find Full Text PDF

VAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes.

Comput Methods Programs Biomed

January 2025

Computational Biomedicine Unit, Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy.

Background And Objectives: Several computational pipelines for biomedical data have been proposed to stratify patients and to predict their prognosis through survival analysis. However, these analyses are usually performed independently, without integrating the information derived from each of them. Clustering of survival data is an underexplored problem, and current approaches are limited for biomedical applications, whose data are usually heterogeneous and multimodal, with poor scalability for high-dimensionality.

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!