In the postgenome era, proteomics has arisen as a promising tool for more complete comprehension of diseases and for biomarker discovery. Some of these objectives have already been partly achieved for illnesses such as cancer. In the case of psychiatric conditions, however, proteomic advances have had a less profound impact. Here, we outline the necessity of improving and applying proteomic methods for biomarker discovery and validation in the field of psychiatric disorders. While proteomic-based applications in neurosciences have increased in accuracy and sensitivity over the past 10 years, the development of orthogonal validation technologies has fallen behind. These issues are discussed along with the importance of integrating systems biology approaches and combining proteomics with other research approaches. The future development of such technologies may put proteomics closer to clinical applications in psychiatry.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/B978-0-12-387718-5.00004-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Fraxetin attenuates DNA damage and inflammation in cisplatin-induced nephrotoxicity via FoxO1 activation.
Int Immunopharmacol
January 2025
Department of Trauma Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China. Electronic address:
Background: Cisplatin-induced acute kidney injury (CKI) represents a severe renal dysfunction characterized by DNA damage and tubular injury. Fraxetin, derived from the Chinese herb Qinpi (Fraxinus bungeana A.DOC), is recognized for its neuroprotective effects and has been used for the prevention of various diseases.
View Article and Find Full Text PDFIntegration of gene expression and DNA methylation data using MLA-GNN for liver cancer biomarker mining.
Front Genet
December 2024
School of information engineering, Jingdezhen Ceramic University, Jingdezhen, China.
The early symptoms of hepatocellular carcinoma patients are often subtle and easily overlooked. By the time patients exhibit noticeable symptoms, the disease has typically progressed to middle or late stages, missing optimal treatment opportunities. Therefore, discovering biomarkers is essential for elucidating their functions for the early diagnosis and prevention.
View Article and Find Full Text PDFInflammatory discoveries two years after acute severe COVID-19: a longitudinal biomarker profile assessment in long COVID individuals in the Brazilian Amazon.
Front Immunol
January 2025
Diretoria de Ensino e Pesquisa, Fundação de Medicina Tropical Dr Heitor Vieira Dourado, Manaus, AM, Brazil.
Background: In SARS-CoV-2 infection, cytokines and laboratory biomarkers play a key role in disease progression and their long-term levels have been associated with the outcome of long COVID-19.
Objectives: I) study the levels of cytokines, hematological and biochemical biomarkers in the acute and post-acute phases of COVID-19 disease; and II) assess the impact of COVID-19 vaccine doses on fatigue symptoms.
Methods: This study is an exploratory cohort nested within a clinical and laboratory follow-up of surviving participants after pre-vaccine acute COVID-19 infection with severe clinical manifestations.
Background: Pulmonary arterial hypertension (PAH) is a rare but severe and life-threatening condition that primarily affects the pulmonary blood vessels and the right ventricle of the heart. The limited availability of human tissue for research ~most of which represents only end-stage disease~ has led to a reliance on preclinical animal models. However, these models often fail to capture the heterogeneity and complexity of the human condition.
View Article and Find Full Text PDFFuture of Artificial Intelligence (AI) - Machine Learning (ML) Trends in Pathology and Medicine.
Mod Pathol
January 2025
Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh, Pittsburgh, PA. Electronic address:
Artificial Intelligence (AI) and Machine Learning (ML) are transforming the field of medicine. Healthcare organizations are now starting to establish management strategies for integrating such platforms (AI-ML toolsets) which leverage the computational power of advanced algorithms to analyze data and to provide better insights which ultimately translates to enhanced clinical decision-making and improved patient outcomes. Emerging AI-ML platforms and trends in pathology and medicine are reshaping the field by offering innovative solutions to enhance diagnostic accuracy, operational workflows, clinical decision support, and clinical outcomes.
View Article and Find Full Text PDFWant 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!