AI-assisted imaging screening reveals mechano-molecular tissue organizers and network of signaling hubs. DOI Creative Commons
Cristina Bertocchi,

Juan José Alegría,

Sebastián Vásquez-Sepúlveda

et al.

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

Published: Nov. 15, 2024

Abstract Cadherin-mediated adhesions are crucial mechanical and signaling hubs that connect cells within a tissue probe the mechanics of surrounding environment. They constitute physical link between actin cytoskeleton neighboring cells, providing coordination needed for morphogenetic processes, homeostasis, collective migration, regeneration. Disruptions in adhesion mechanisms closely linked to breakdown epithelial structure emergence disease-related traits characteristic cancer progression. The cadhesome network comprises over 170 structural regulatory proteins involved cadherin-mediated adhesion. While this is essential coordinating responses stress, its complexity has historically limited our understanding how individual components contribute force transmission homeostasis. Recent technological advances offer tools investigate large molecular networks cellular function pathology (functional omics). Leveraging these advances, we developed an experimental analytical platform combining high-throughput gene silencing, imaging, artificial intelligence (AI) systematically profile each role protein formation, stability, response induced tension. Using EpH4 as model, performed systematic silencing triplicate, capturing range phenotypes under baseline tension-inducing conditions. Machine learning methods were used analyze complex imaging data, quantify ruptures, characterize junctional organization, measure tension states tissue. By incorporating machine algorithms, automated image feature extraction, clustering, classification, enabling unprecedented quantitative evaluation at scale. Our models allowed us identify significant patterns, including protein-specific their roles tissue-level integrity. Finally, constructed interaction detailing protein, interactions, known links cancer. analysis revealed three prominent mechanotransductive subnetworks centered around E-cadherin, EGFR, RAC1. study provides foundational framework investigating mechanosensing it offers scalable blueprint discovering potential therapeutic targets diseases like cancer, where play role. Teaser AI-aided screening identifies key regulators mechanics, uncovering

Language: Английский

Exploring the intricacies of plant growth promoting rhizobacteria interactions: an omics review DOI Creative Commons

Kamogelo Mmotla,

Nompumelelo R. Sibanyoni,

Farhahna Allie

et al.

Annals of Microbiology, Journal Year: 2025, Volume and Issue: 75(1)

Published: Feb. 4, 2025

Language: Английский

Citations

1
Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies DOI Open Access
Maria V. Bourganou, Maria Chondrogianni, Ioannis Kyrou

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(4), P. 1589 - 1589

Published: Feb. 13, 2025

Non-alcoholic fatty liver disease (NAFLD), now referred to as metabolic dysfunction-associated steatotic (MASLD), is the most prevalent disorder globally, linked obesity, type 2 diabetes, and cardiovascular risk. Understanding its potential progression from simple steatosis cirrhosis hepatocellular carcinoma (HCC) crucial for patient management treatment strategies. The disease's complexity requires innovative approaches early detection personalized care. Omics technologies-such genomics, transcriptomics, proteomics, metabolomics, exposomics-are revolutionizing study of MASLD. These high-throughput techniques allow a deeper exploration molecular mechanisms driving progression. Genomics can identify genetic predispositions, whilst transcriptomics proteomics reveal changes in gene expression protein profiles during evolution. Metabolomics offers insights into alterations associated with MASLD, while exposomics links environmental exposures MASLD pathology. By integrating data various omics platforms, researchers map out intricate biochemical pathways involved This review discusses roles technologies enhancing understanding highlights diagnostic therapeutic targets within spectrum, emphasizing need non-invasive tools staging development.

Language: Английский

Citations

1
Machine learning in ocular oncology and oculoplasty: Transforming diagnosis and treatment DOI Open Access

Dipali Mane,

Khuspe Pankaj Ramdas

IP International Journal of Ocular Oncology and Oculoplasty, Journal Year: 2025, Volume and Issue: 10(4), P. 196 - 207

Published: Jan. 14, 2025

In the domains of ocular oncology and oculoplasty, machine learning (ML) has become a game-changing technology, providing previously unheard-of levels precision in diagnosis, treatment planning, outcome prediction. Using imaging modalities, genomic data, clinical characteristics, this chapter investigates integration algorithms detection tumours, including retinoblastoma uveal melanoma. Through predictive modelling real-time decision-making, it also emphasises how ML might improve surgical outcomes orbital reconstruction eyelid correction. Automated examination fundus photographs, histological slides, 3D been made possible by methods like deep natural language processing, which have improved individualised therapeutic approaches decreased diagnostic errors. Additionally, use augmented reality robotics surgery is significant development oculoplasty. Notwithstanding its potential, issues data heterogeneity, algorithm interpretability, ethical considerations are roadblocks that need to be addressed. This explores cutting-edge developments, real-world uses, potential future paths, offering researchers doctors thorough resource. Dipali Vikas Mane, Associate Professor, Shriram Shikshan Sanstha’s College Pharmacy, Paniv-413113

Language: Английский

Citations

0
Real-Time Genomic Analytics in Clinical Practice: A Framework for High-Throughput Data Processing and Decision Support DOI Open Access

Viswaketan Reddy Prodduturi

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Journal Year: 2025, Volume and Issue: 11(1), P. 908 - 915

Published: Jan. 20, 2025

Recent advances in genomic sequencing technologies have generated unprecedented volumes of clinical data, necessitating robust real-time analytics solutions for immediate decision support. This article presents a comprehensive framework implementing data processing settings, addressing the challenges high-throughput management while maintaining patient privacy and security. The examines integration distributed computing frameworks stream to facilitate rapid analysis alongside phenotypic information. reveals that modern healthcare informatics platforms can effectively manage multi-modal datasets through optimized pipelines, enabling faster diagnostic processes improved outcomes. demonstrates how enhance decision-making variant calling interpretation supporting larger population-scale studies. discusses critical quality management, preservation, computational resource optimization. findings suggest significantly improve speed accuracy advancing preventative strategies better identification genetic risk factors. contributes growing field precision medicine by providing scalable approach managing analyzing time-critical environments.

Language: Английский

Citations

0
Association between CAPN-10 gene variant and diabetes mellitus in Nigeria: a review DOI Creative Commons

David Olufemi Adebo,

Mathew Folaranmi Olaniyan,

Christian Onosetale Ugege

et al.

Egyptian Journal of Medical Human Genetics, Journal Year: 2025, Volume and Issue: 26(1)

Published: Feb. 7, 2025

Abstract Background Type 2 Diabetes Mellitus (T2DM) is a significant global health concern characterised by insulin resistance and chronic hyperglycemia. Genetic factors, particularly variations in the CAPN-10 gene, have been implicated T2DM susceptibility across diverse populations. Aim objective This study aimed to conduct meta-analysis investigate associations of single nucleotide polymorphisms (SNPs) gene with among various populations, focusing specifically on Nigerian cohorts. Materials methods A comprehensive literature search yielded 150 studies, from which 45 met inclusion criteria, encompassing approximately 25,000 individuals, including 10,000 diagnosed T2DM. Statistical analyses assessed association between SNPs (UCSNP-43, UCSNP-19, UCSNP-63) risk. Results was observed for UCSNP-43 (rs3792267) (OR 1.50; 95% CI 1.28–1.75; p < 0.001), urban UCSNP-19 (rs3842570) also showed moderate 1.35; 1.10–1.66; = 0.01), especially South-West Nigeria. No found UCSNP-63 1.15; 0.90–1.45; 0.30). Conclusion The findings indicate that SNPs, contribute emphasising importance genetic screening personalised interventions diabetes management.

Language: Английский

Citations

0
Circulating Microvesicles Enriched in miR–126–5p and miR–223–3p: Potential Biomarkers in Acute Coronary Syndrome DOI Creative Commons
José Rubicel Hernández-López, Mirthala Flores-García, Esbeidy García-Flores

et al.

Biomedicines, Journal Year: 2025, Volume and Issue: 13(2), P. 510 - 510

Published: Feb. 18, 2025

Background. The molecular mechanisms underlying acute coronary syndrome (ACS) have been extensively investigated, with a particular focus on the role of circulating microvesicles (MVs) as carriers regulatory elements that influence hemodynamic changes and flow. Endothelial platelet dysfunction during ACS alters MV composition, impacting clinical outcomes. This study explores levels miR-126-5p miR-223-3p in MVs their association Thrombolysis Myocardial Infarction (TIMI) flow classification scale, proposing potential biomarkers. Methods. Bioinformatic tools identified miRNAs linked to ACS. Plasma were isolated from patients healthy controls through high-speed centrifugation. miRNA quantified using quantitative reverse transcription polymerase chain reaction (qRT-PCR) compared across TIMI 0 3 groups. Diagnostic efficacy was assessed via receiver operating characteristic (ROC) curve analysis. Results. bioinformatic analysis miR-126 miR-223 present significantly reduced 3. ROC showed high diagnostic accuracy for (AUC = 0.918; 95% CI: 0.818-1.00; p 0.001) 1.00; 1.00-1.00; < 0.001). Conclusions. Reduced are strongly associated impaired flow, positioning these biomarkers risk stratification therapeutic targeting.

Language: Английский

Citations

0
Unveiling the microbial influence: bacteria’s dual role in tumor metastasis DOI Creative Commons

Li-Ying Lin,

Dongyan Zhang

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 14, 2025

As cancer research advances, the intricate relationship between microbiome and is gaining heightened recognition, especially concerning tumor metastasis, where bacterial involvement becomes increasingly complex. This review seeks to systematically examine dual roles of bacteria in metastasis process, encompassing both mechanisms that facilitate inhibitory effects exerted by specific microorganisms. We explore through which influence cell migration inducing chronic inflammation, evading host immune responses, remodeling ECM. Moreover, immunomodulatory potential probiotics genetically engineered offers promising prospects for prevention treatment metastasis. article elucidates complexity emerging frontiers examining clinical significance as biomarkers evaluating antibiotic usage on metastatic process. posit comprehending biological characteristics bacteria, a critical component microenvironment, will offer innovative strategies theoretical foundations treatment. Furthermore, this explores future directions, including application technologies bacteria-based therapeutic strategies, thereby offering valuable perspective development novel anti-cancer approaches.

Language: Английский

Citations

0
Revolutionizing Implantation Studies: Uterine-Specific Models and Advanced Technologies DOI Creative Commons

Shuyun Li,

Francesco J. DeMayo

Biomolecules, Journal Year: 2025, Volume and Issue: 15(3), P. 450 - 450

Published: March 20, 2025

Implantation is a complex and tightly regulated process essential for the establishment of pregnancy. It involves dynamic interactions between receptive uterus competent embryo, orchestrated by ovarian hormones such as estrogen progesterone. These regulate proliferation, differentiation, gene expression within three primary uterine tissue types: myometrium, stroma, epithelium. Advances in genetic manipulation, particularly Cre/loxP system, have enabled vivo investigation role genes compartmental cell type-specific manner, providing valuable insights into biology during pregnancy disease. The development endometrial organoids has further revolutionized implantation research. They mimic native structure function, offering powerful platform studying hormonal responses, implantation, maternal-fetal interactions. Combined with omics technologies, these models uncovered molecular mechanisms signaling pathways that implantation. This review provides comprehensive overview uterine-specific tools, organoids, omics. We explore how advancements enhance our understanding biology, receptivity, decidualization reproductive

Language: Английский

Citations

0
A systematic mapping study of semantic technologies in multi-omics data integration DOI Creative Commons
Giovanni Maria De Filippis, Domenico Amalfitano, Cristiano Russo

et al.

Journal of Biomedical Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 104809 - 104809

Published: March 1, 2025

The integration of multi-omics data is essential for understanding complex biological systems, providing insights beyond single-omics approaches. However, challenges related to heterogeneity, standardization, and computational scalability persist. This study explores the interdisciplinary application semantic technologies enhance integration, analysis in research. We performed a systematic mapping assessing literature from 2014 2024, focusing on utilization ontologies, knowledge graphs, graph-based methods integration. Our findings indicate growing number publications this field, predominantly appearing high-impact journals. deployment has notably improved visualization, querying, management, thus enhancing gene pathway discovery, deeper disease more accurate predictive modeling. underscores significance overcoming challenges. Future research should focus integrating diverse types, developing advanced tools, incorporating AI machine learning foster personalized medicine applications.

Language: Английский

Citations

0
Omics metabolism tools in antiaging drug discovery DOI

Rafael Tibúrcio,

Jay Rappaport, Clovis S. Palmer

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 209 - 225

Published: Jan. 1, 2025

Language: Английский

Citations

0