AIMC Topic: Epithelial-Mesenchymal Transition

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Identification of LPCAT1 as a key biomarker for Crohn's disease based on bioinformatics and machine learnings and experimental verification.

Gene
Epithelial-mesenchymal transition (EMT) plays a crucial role in regulating inflammatory responses and fibrosis formation. This study aims to explore the molecular mechanisms of EMT-related genes in Crohn's disease (CD) through bioinformatics methods ...

Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
BACKGROUND: Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between th...

Deep-Learning-Based Nanomechanical Vibration for Rapid and Label-Free Assay of Epithelial Mesenchymal Transition.

ACS nano
Cancer is a profound danger to our life and health. The classification and related studies of epithelial and mesenchymal phenotypes of cancer cells are key scientific questions in cancer research. Here, we investigated cancer cell colonies from a mec...

Specneuzhenide improves bleomycin-induced pulmonary fibrosis in mice via AMPK-dependent reduction of PD-L1.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Pulmonary fibrosis (PF) is an escalating global health issue, characterized by rising rates of morbidity and mortality annually. Consequently, further investigation of potential damage mechanisms and potential preventive strategies for PF...

Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning.

Journal of advanced research
INTRODUCTION: Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select nodules for biopsy due to their association with tumor behavior. However, the molecular biological mechanisms that lead to the characteristic US featur...

Unraveling the Molecular Puzzle: Exploring Gene Networks across Diverse EMT Status of Cell Lines.

International journal of molecular sciences
Understanding complex disease mechanisms requires a comprehensive understanding of the gene regulatory networks, as complex diseases are often characterized by the dysregulation and dysfunction of molecular networks, rather than abnormalities in sing...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Translational research : the journal of laboratory and clinical medicine
Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensive research, there have been many clinical trial failures, and there is currently no effective treat...

Suspended particulate matter promotes epithelial-to-mesenchymal transition in alveolar epithelial cells via TGF-β1-mediated ROS/IL-8/SMAD3 axis.

Journal of environmental sciences (China)
Epidemiological evidence presents that dust storms are related to respiratory diseases, such as pulmonary fibrosis (PF). However, the precise underlying mechanisms of SPM-elicited adverse effects still need to be investigated. Epithelial-mesenchymal ...

Identifying key factors in cell fate decisions by machine learning interpretable strategies.

Journal of biological physics
Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it is important to identify the decision-making mechanisms and important individual molecules behind the fate decision processes. In this paper, we propo...

Unsupervised Learning Framework With Multidimensional Scaling in Predicting Epithelial-Mesenchymal Transitions.

IEEE/ACM transactions on computational biology and bioinformatics
Clustering tumor metastasis samples from gene expression data at the whole genome level remains an arduous challenge, in particular, when the number of experimental samples is small and the number of genes is huge. We focus on the prediction of the e...