Phospholipase D2: A biomarker for stratifying disease severity in acute pancreatitis?

World Journal of Gastroenterology, Journal Year: 2025, Volume and Issue: 31(11)

Published: March 12, 2025

In this editorial, we critically evaluate the recent article by Niu et al , which explores potential of phospholipase D2 (PLD2) as a biomarker for stratifying disease severity in acute pancreatitis (AP). AP is clinically heterogeneous inflammatory condition that requires reliable biomarkers early and accurate classification severity. PLD2, an essential regulator neutrophil migration responses, has emerged promising candidate. Although current such C-reactive protein procalcitonin provide general indications inflammation, they lack specificity regarding molecular mechanisms underlying progression. Recent studies, including research conducted suggest inverse correlation between PLD2 expression severity, offering both diagnostic insights mechanistic understanding. This editorial evaluates role broader context research. Evidence indicates decreased levels are associated with increased chemotaxis cytokine release, contributing to pancreatic systemic inflammation. However, several challenges remain, need large-scale validation functional studies establish causation, standardization measurement protocols. Additionally, further investigation into temporal dynamics its variability across diverse populations warranted. Looking ahead, holds revolutionize management integrating diagnostics precision medicine. The utilization multi-omics approaches advancements platforms could position fundamental diagnosis, prognosis, potentially therapeutic targeting. While promising, it crucial conduct critical evaluations rigorous validations PLD2’s ensure efficacy improving patient outcomes.

Language: Английский

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SciLinker: a large-scale text mining framework for mapping associations among biological entities

Frontiers in Artificial Intelligence, Journal Year: 2025, Volume and Issue: 8

Published: March 19, 2025

Introduction The biomedical literature is the go-to source of information regarding relationships between biological entities, including genes, diseases, cell types, and drugs, but rapid pace publication makes an exhaustive manual exploration impossible. In order to efficiently explore up-to-date repository millions abstracts, we constructed efficient modular natural language processing pipeline applied it entire PubMed abstract corpora. Methods We developed SciLinker using open-source libraries pre-trained named entity recognition models identify human types normalizing these entities Unified Medical Language System (UMLS). implemented a scoring schema quantify statistical significance co-occurrences fine-tuned PubMedBERT model for gene-disease relationship extraction. Results identified analyzed over 30 million association sentences, more than 11 co-occurrence revealing 1.25 unique associations. demonstrate SciLinker’s ability extract specific osteoporosis as case study. show how such analysis benefits target identification clinically validated targets are enriched in SciLinker-derived disease-associated genes. Moreover, this data can be used construct disease-specific networks, providing insights into significant among from scientific literature. Conclusion represents novel text mining approach that extracts quantifies associations through extraction abstracts. Its design enables expansion additional corpora, making versatile tool transforming unstructured actionable drug discovery.

Language: Английский

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Integration of GWAS, QTLs and keratinocyte functional assays reveals molecular mechanisms of atopic dermatitis

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 1, 2025

Atopic dermatitis is a highly heritable and common inflammatory skin condition affecting children adults worldwide. Multi-ancestry approaches to atopic genetic association studies are poised boost power detect signal identify loci contributing risk. Here, we present multi-ancestry GWAS meta-analysis of twelve cohorts from five ancestral populations totaling 56,146 cases 602,280 controls. We report 101 genomic associated with dermatitis, including 16 that have not been previously or eczema. Fine-mapping, QTL colocalization, cell-type enrichment analyses identified genes cell types implicated in pathophysiology. Functional keratinocytes provide evidence for could play role through epidermal barrier function. Our study provides insights into the etiology by harnessing multiple functional unveil mechanisms which dermatitis-associated variants impact types. condition. authors perform carry out downstream experiments understand they identify.

Language: Английский

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Pancreatic cancer subtyping - the keystone of precision treatment

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 8, 2025

In recent years, the incidence and mortality rates of pancreatic cancer have been rising, posing a severe threat to human health. Tumor heterogeneity remains critical barrier advancing diagnosis treatment efforts. The lack specific early symptoms, limited diagnostic methods, high biological complexity, restricted therapeutic options contribute poor outcomes prognosis cancer. Therefore, there is an urgent need explore different subtypes in-depth develop personalized strategies tailored each subtype. Increasing evidence highlights pivotal role molecular subtyping in treating This review focuses on advancements classifying approaches, discussed from perspectives gene mutations, genomics, transcriptomics, proteomics, metabolomics, immunomics.

Language: Английский

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Harnessing the potential of multimodal EHR data: A comprehensive survey of clinical predictive modeling for intelligent healthcare

Information Fusion, Journal Year: 2025, Volume and Issue: unknown, P. 103283 - 103283

Published: May 1, 2025

Language: Английский

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Multi-Ancestry Genome-Wide Association Meta-Analysis Identifies Novel Loci in Atopic Dermatitis

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 19, 2024

ABSTRACT Atopic dermatitis (AD) is a highly heritable and common inflammatory skin condition affecting children adults worldwide. Multi-ancestry approaches to AD genetic association studies are poised boost power detect signal identify ancestry-specific loci contributing risk. Here, we present multi-ancestry GWAS meta-analysis of twelve cohorts from five ancestral populations totaling 56,146 cases 602,280 controls. We report 101 genomic associated with AD, including 15 that have not been previously or eczema. Fine-mapping, QTL colocalization, cell-type enrichment analyses identified genes cell types implicated in pathophysiology. Functional keratinocytes provide evidence for could play role through epidermal barrier function. Our study provides new insights into the etiology by harnessing multiple functional unveil mechanisms which AD-associated variants impact types. Disclosure Statement BRG, MO, CH, KMS employees AbbVie. FT was an employee AbbVie at time study. JEG (University Michigan) has received research support AbbVie, Janssen, Almirall, Prometheus Biosciences/Merck, BMS/Celgene, Boehringer Ingelheim, Galderma, Eli Lilly, advisor Sanofi, BMS, Ingelheim. MKS, RU, MTP, QL, RW, JMK, LCT University Michigan no funding disclose. MEM, AHS, FDM, DW, JTG, HH Children’s Hospital Philadelphia The design, conduct, financial this were provided participated interpretation data, review, approval publication.

Language: Английский

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