Novel Biomarkers in Histopathology: Implications for Diagnosis and Prognosis DOI

Noor Kadhim Yousif,

Saad Ahmed

European Journal of Medical and Health Research, Journal Year: 2024, Volume and Issue: 2(6), P. 44 - 57

Published: Nov. 1, 2024

Identification of new biomarkers in histopathology for better understanding disease diagnosis and outcome has received interest. Significant progresses have been achieved these fronts cancer through different tumors including Ki-67. Ki-67 is a biomarker that used to support its diagnostic prognostic cost showing potential diseases like gliomas, meningiomas, medulloblastomas, ependymomas. HER2 overexpressed the predictability breast cancer, while MSMB PSG2 are ideal prostate adenocarcinoma. Cancer dominated most study conducted within this field, therefore it important research go on apply clinical facilities enhancement prediction other diseases. It noteworthy directions, instance therapeutic response, reveal considerable rise comparison with indicators last year. Some require additional complex costly technology, but researchers agree discoveries practising should help clinicians make decision depending correct assessment patient’s state. Moreover, many still need confirming samples as examinations. Today, applied diagnostics based availability simple sweat, urine, blood, cerebrospinal fluid, saliva. increase use such since obtaining them easy, subject can be sampled little or no interferences at all terms invasiveness. The convenience not only increases willingness patient compliance process, also delivers far enhanced healthcare experience results. Therefore, presented earlier implementing together innovative state art techniques detection identification, process revolutionized. They possess remarkable features essential owing fact molecules cannot identified by routine modalities because structural molecular weight differences well highlighted. In words, provided first-of-its-kind approach recognising identifying evaluation analysis biomarkers. However, imperative strategies come related costs expenses order executed. relying mentioned considerations, mass spectrometry invariably recognized probably advisable definitely preferred option implement laboratories commercial medical facilities. Over implication somewhat high they offset advantages accuracy, sensitivity specificity technique. evolved critical asset use, which long run results prognosis precise therapy intercession. add ongoing upgrade technologies produce advances analysis, thus maintaining focus biomarker.

Language: Английский

Uracil Biomarker for Pyrimidine Metabolism in OSCC: Leveraging AI and Machine Learning for Improved Diagnosis DOI Creative Commons

Sesuraj Balasamy,

Dhanraj Ganapathy,

Deepak Nallaswamy

et al.

The Open Dentistry Journal, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 30, 2025

Language: Английский

Citations

0
Machine learning models and AI in predicting diagnosis and prognosis in alcohol-related and metabolic dysfunction-associated steatotic liver disease DOI Open Access
Akash Roy, Nipun Verma

Metabolism and Target Organ Damage, Journal Year: 2025, Volume and Issue: 5(1)

Published: Feb. 25, 2025

Steatotic liver disease (SLD) is the most common cause of globally, with an ever-increasing burden. The two primary components SLD are metabolic dysfunction-associated steatotic (MASLD) and Alcohol-Associated Liver Disease (ALD). Both entities have important knowledge gaps in differentiation, diagnosis, risk stratification, prognosis. Given enormous burden both MASLD ALD their diverse presentation, they form ideal ground for application artificial intelligence (AI) machine learning (ML) techniques algorithms. ML models can aid prediction among large populations estimate those at highest progression or mortality, while applications AI technology better detection monitored treatment approaches. use digital pathology therapeutics attractive options moving toward personalized medicine. This review briefly summarizes emerging literature on technologies across domains detection,

Language: Английский

Citations

0
Advancing the Metabolic Disfunction-Associated Steatotic Liver Disease Proteome: A Post-Translational Outlook DOI Open Access
Kushan Chowdhury, Debajyoti Das, Menghao Huang

et al.

Genes, Journal Year: 2025, Volume and Issue: 16(3), P. 334 - 334

Published: March 12, 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent disorder with limited treatment options. This review explores the role of post-translational modifications (PTMs) in MASLD pathogenesis, highlighting their potential as therapeutic targets. We discuss impact PTMs, including phosphorylation, ubiquitylation, acetylation, and glycosylation, on key proteins involved MASLD, drawing studies that use both human subjects animal models. These influence various cellular processes, such lipid metabolism, inflammation, fibrosis, contributing to progression. Understanding intricate PTM network offers for developing novel strategies target specific PTMs modulate protein function alleviate pathology. Further research needed fully elucidate complexity translate these findings into effective clinical applications.

Language: Английский

Citations

0
Lactiplantibacillus plantarum FRT4 protects against fatty liver hemorrhage syndrome: regulating gut microbiota and FoxO/TLR-4/NF-κB signaling pathway in laying hens DOI Creative Commons

Daojie Li,

Kun Meng, Guohua Liu

et al.

Microbiome, Journal Year: 2025, Volume and Issue: 13(1)

Published: March 29, 2025

Fatty liver hemorrhage syndrome (FLHS) has become one of the major factors leading to death laying hen in caged egg production. FLHS is commonly associated with lipid peroxidation, hepatocyte injury, decreased antioxidant capacity, and inflammation. However, there are limited evidences regarding preventive effect Lactiplantibacillus plantarum on hens its mechanisms. Our previous results showed that Lp. FRT4 alleviated by regulating metabolism, but did not focus anti-inflammatory functions Therefore, this study aimed investigate mechanisms alleviating FLHS, a role activity inflammation regulation. Supplementation enhanced levels T-AOC, T-SOD, GSH-Px, while reducing TNF-α, IL-1β, IL-8, NLRP3 ovary hens. Additionally, upregulated mRNA expressions SOD1, SOD2, CAT, GPX1, downregulated pro-inflammatory IL-6, NLRP3, IL-4 IL-10. improved structure metabolic gut microbiota, regulated relative abundances dominant phyla (Bacteroidetes, Firmicute, Proteobacteria) genera (Prevotella Alistipes). it influenced key KEGG pathways, including tryptophan amino sugar nucleotide insulin signaling pathway, FoxO pathway. Spearman analysis revealed abundance microbiota at different taxonomic was closely related enzymes inflammatory factors. Furthermore, modulated FoxO/TLR-4/NF-κB pathway microbiota. Moreover, E2, FSH, VTG were significantly increased after intervention. effectively ameliorates This efficacy attributed properties, which mediated modulating function further intervening These actions enhance hepatic ovarian increase estrogen levels. Video Abstract.

Language: Английский

Citations

0
MASLD And MASH Risk: Does Losing Obesity Reverse the Metabolic Footprint? DOI
Mohamed El‐Kassas, Khalid Alswat, Khalid Al‐Naamani

et al.

Liver International, Journal Year: 2025, Volume and Issue: 45(5)

Published: April 12, 2025

Language: Английский

Citations

0
The current status and future directions of artificial intelligence in the prediction, diagnosis, and treatment of liver diseases DOI Creative Commons
Bo Gao, Wendu Duan

Digital Health, Journal Year: 2025, Volume and Issue: 11

Published: April 1, 2025

Early detection, accurate diagnosis, and effective treatment of liver diseases are paramount importance for improving patient survival rates. However, traditional methods frequently influenced by subjective factors technical limitations. With the rapid progress artificial intelligence (AI) technology, its applications in medical field, particularly prediction, diseases, have drawn increasing attention. This article offers a comprehensive review current AI hepatology. It elaborates on how is utilized to predict progression diagnose various conditions, assist formulating personalized plans. The emphasizes key advancements, including application machine learning deep algorithms. Simultaneously, it addresses challenges limitations within this domain. Moreover, pinpoints future research directions. underscores necessity large-scale datasets, robust algorithms, ethical considerations clinical practice, which crucial facilitating integration technology enhancing diagnostic therapeutic capabilities diseases.

Language: Английский

Citations

0
Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma DOI Creative Commons
Adane Adugna, Gashaw Azanaw Amare, Mohammed Jemal

et al.

Cancer Informatics, Journal Year: 2025, Volume and Issue: 24

Published: Jan. 1, 2025

Hepatitis B virus (HBV) causes liver cancer, which is the third most common cause of cancer-related death worldwide. Chronic inflammation via HBV in host hepatocytes hepatocyte remodeling (hepatocyte transformation and immortalization) hepatocellular carcinoma (HCC). Recognizing cancer stages accurately to optimize early screening diagnosis a primary concern outlook HBV-induced cancer. Genomic signatures play important roles addressing this issue. Recently, machine learning (ML) models bioinformatics analysis have become very discovering novel genomic for diagnosis, treatment, prognosis hepatic cell HCC. We discuss recent literature on ML approach revealed diagnosing forecasting HBV-associated Various signatures, including various microRNAs their associated genes, long noncoding RNAs (lncRNAs), small nucleolar (snoRNAs), been discovered be involved upregulation downregulation HBV-HCC. Moreover, these genetic biomarkers also affect different biological processes, such as proliferation, migration, circulation, assault, dissemination, antiapoptosis, mitogenesis, transformation, angiogenesis HBV-infected hepatocytes.

Language: Английский

Citations

0
HCC in MASLD: radiological appearance, diagnosis and treatment DOI Open Access
Marco Dioguardi Burgio, Roberto Cannella, Federica Vernuccio

et al.

Hepatoma Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its inflammatory form, metabolic steatohepatitis (MASH), are emerging as leading causes of hepatocellular carcinoma (HCC) development. This has important implications for evaluating patients with these conditions, including the potential early diagnosis through screening techniques. Imaging techniques noninvasive HCC in context MASLD also present unique considerations. Notably, development without cirrhosis is more frequent compared to other chronic etiologies. Moreover, presence steatosis, a common feature patients, can modify radiological appearance liver, giving MASLD/MASH uncommon imaging characteristics. Additionally, certain histological subtypes, particularly steatohepatitic HCC, prevalent MASLD/MASH, which may influence both diagnostic strategies therapeutic decisions patients. review article focuses on characteristics developed MASLD/MASH. It specifically addresses roles surveillance, features subtypes associated impact treatment decisions. Finally, brief summary future directions role new technologies within provided.

Language: Английский

Citations

0
Preclinical liver toxicity models: advantages, limitations and recommendations DOI
Devaraj Ezhilarasan,

Sivanesan Karthikeyan,

Mustapha Najimi

et al.

Toxicology, Journal Year: 2024, Volume and Issue: unknown, P. 154020 - 154020

Published: Dec. 1, 2024

Language: Английский

Citations

2
Advancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease—Applications and Challenges in Personalized Care DOI Creative Commons
Naoshi Nishida

Bioengineering, Journal Year: 2024, Volume and Issue: 11(12), P. 1243 - 1243

Published: Dec. 9, 2024

Liver disease can significantly impact life expectancy, making early diagnosis and therapeutic intervention critical challenges in medical care. Imaging diagnostics play a crucial role diagnosing managing liver diseases. Recently, the application of artificial intelligence (AI) imaging analysis has become indispensable healthcare. AI, trained on vast datasets images, sometimes demonstrated diagnostic accuracy that surpasses human experts. AI-assisted are expected to contribute standardization quality. Furthermore, AI potential identify image features imperceptible humans, thereby playing an essential clinical decision-making. This capability enables physicians make more accurate diagnoses develop effective treatment strategies, ultimately improving patient outcomes. Additionally, is anticipated powerful tool personalized medicine. By integrating individual data with information, propose optimal plans for treatment, it component provision most appropriate care each patient. Current reports highlight advantages As technology continues evolve, advance treatments overall improvements healthcare

Language: Английский

Citations

1