Advances in biomarker sciences and technology最新文献

{"title":"Biomarker-guided analysis of metabolic and inflammatory pathway modulation by Nigella sativa bioactive constituents","authors":"Muhammad Waqas ,&nbsp;Iqra Akram ,&nbsp;Aena Yasin ,&nbsp;Tehmina Saddique ,&nbsp;Romaisha Kanwal ,&nbsp;Khadija Munir ,&nbsp;Razia Bashir","doi":"10.1016/j.abst.2026.03.007","DOIUrl":"10.1016/j.abst.2026.03.007","url":null,"abstract":"<div><div><em>Nigella sativa</em> is a medicinal plant rich in bioactive constituents, particularly thymoquinone, with reported metabolic and anti-inflammatory activities. However, mechanistic evidence linking its phytochemical composition to defined molecular biomarkers remains limited. This study adopted a biomarker-centered approach to evaluate the effects of <em>Nigella sativa</em> ethanolic extract and thymoquinone on metabolic, inflammatory, and oxidative stress pathways using RAW 264.7 macrophages and HepG2 hepatocytes as complementary in vitro models of immunometabolic regulation. Cells were exposed to non-cytotoxic concentrations of the extract (25–100 μg/mL) and thymoquinone (10–25 μg/mL) following lipopolysaccharide stimulation in RAW 264.7 macrophages or high-glucose challenge in HepG2 hepatocytes. In RAW 264.7 cells, treatment significantly reduced the secretion of TNF-α, IL-6, and IL-1β and suppressed NF-κB protein expression. Oxidative stress was attenuated through a marked decrease in intracellular reactive oxygen species and upregulation of Nrf2 protein levels. In HepG2 cells, high-glucose–induced impairment of metabolic signaling was reversed by restoration of AMPK activation, GLUT4 expression, and PPARγ levels. Molecular docking analysis predicted stable interactions of thymoquinone with NF-κB, AMPK, Nrf2, and PPARγ, supporting its multi-target potential. The study provides mechanistic insight into immunometabolic pathway regulation and supports the use of biomarker-guided strategies for the translational evaluation of plant-derived pharmaceutical leads.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"8 ","pages":"Pages 412-424"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147991506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of a disease trigger prediction model using AIML for early diagnosis of epilepsy","authors":"Aarohi Deshpande ,&nbsp;Aarohi Gherkar ,&nbsp;Avni Bhambure ,&nbsp;Girish Shivhare ,&nbsp;Shreyash Kolhe ,&nbsp;Bhupendra Prajapati ,&nbsp;Shama Mujawar","doi":"10.1016/j.abst.2025.07.001","DOIUrl":"10.1016/j.abst.2025.07.001","url":null,"abstract":"<div><div>Epilepsy is one of the most prevalent neurological disorders that negatively impacts patients' quality of life and poses a severe health risk. It is often characterized by recurrent brain seizures. A current method that involves monitoring these seizures is Electroencephalography, which allows for the scientific investigation of electrical impulses within the brain. In this research, we have used Artificial Intelligence and Machine Learning in the management of Epilepsy to evaluate electrical impulses within the brain, emphasizing the potential to significantly improve the quality of life of those who suffer from this disorder. The goal of this study is to propose a Deep Neural Network model that can predict early seizure detection of Epilepsy using Electroencephalography data from a control group in order to anticipate the frequency of episodes of the patient and provide accurate insights into when they might experience their symptoms. Additionally, our research aims to identify particular genes of interest with specific protein targets that are directly responsible for the changes in EEG values in the epileptic patients. After thorough examination of these proteins' therapeutic targets and ligands, a suitable ligand and protein were identified and docked. The purpose of the docking studies in the Machine Learning model gains valuable information about the genetic origin for the change in EEG values in Epileptic patients.</div><div>The integration of predictive modeling with in-silico drug discovery enhances both the diagnostic and therapeutic dimensions of epilepsy care. This dual-layered approach not only supports early warning systems but also opens avenues for personalized treatment strategies. Our study thus represents a step toward a more holistic, computationally driven framework for neurological disorder management. By bridging data-driven seizure prediction with molecular-level therapeutic exploration, this research contributes to precision medicine and highlights the potential of interdisciplinary computational approaches in tackling complex, treatment-resistant forms of epilepsy.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 189-203"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urine PD-L1 as a non-invasive biomarker for immune checkpoint inhibitor (ICI) therapy in bladder cancer","authors":"Qianyun Ge ,&nbsp;Peng Wang ,&nbsp;Shang-jui Wang ,&nbsp;Akshay Sood ,&nbsp;Lingbin Meng ,&nbsp;Cheryl Lee ,&nbsp;Anil V. Parwani ,&nbsp;Jenny Li ,&nbsp;Xuefeng Liu","doi":"10.1016/j.abst.2025.05.001","DOIUrl":"10.1016/j.abst.2025.05.001","url":null,"abstract":"<div><div>Bladder cancer (BCa) is a common urological malignancy with a high recurrence rate, often within 2 years of initial diagnosis and treatment. Due to this high recurrence, near all patients require cystoscopic surveillance, which is invasive, uncomfortable, and costly. The cost of surveillance makes this cancer the most expensive cancer per case among all cancer types in the US. Therefore, early detection of recurrence or assessment of patients’ response to treatment, particularly through non-invasive methods, is urgently needed. Since immune checkpoint inhibitors (ICIs) are widely used in many clinical trials for BCa treatment, having non-invasive and reliable biomarkers to select appropriate patients for ICI therapies or predict their treatment responses would be invaluable. Here we summarized the potential applications of programmed death-ligand 1 (PD-L1) from urine or urine BCa cell samples in BCa clinical settings. We discuss the use of both the free form of PD-L1 in urine samples and the expression levels of PD-L1 on the BCa cells shed in urine samples. Free PD-L1 can be measured with flow cytometry or ELISA-based approaches, while detecting PD-L1 on BCa cell surface requires isolating the urine-derived cancer cells and analyzing them via flow cytometry. Furthermore, we discuss the promising future research areas of urinary PD-L1 (uPD-L1) in bladder cancer, with a particular focus on the combination of conditional reprogramming cells (CRCs) technology and uPD-L1 studies, followed by an overview of several ongoing research topics. Based on current findings, uPD-L1 shows great potential as a versatile biomarker; however, further research is urgently needed to facilitate its translation into clinical applications.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 172-179"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Paper based molecularly imprinted SERS substrate for early detection of lysophosphatidic acid in ovarian cancer” [Advan Biomarker Sci Technol. 6 (2024) 46–58 https://doi.org/10.1016/j.abst.2024.03.001]","authors":"Nazia Tarannum ,&nbsp;Deepak Kumar ,&nbsp;Akanksha Yadav ,&nbsp;Anil K. Yadav","doi":"10.1016/j.abst.2025.09.003","DOIUrl":"10.1016/j.abst.2025.09.003","url":null,"abstract":"","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Page 394"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mini review: Role of novel biomarker for kidney disease of future study","authors":"Palash Mitra ,&nbsp;Sahadeb Jana ,&nbsp;Suchismita Roy","doi":"10.1016/j.abst.2025.02.002","DOIUrl":"10.1016/j.abst.2025.02.002","url":null,"abstract":"<div><div>In the world, kidney disease is most common cause of death. Primary care physicians must conduct appropriate diagnosis, and management in order to avoid detrimental consequences linked to death as well as end-stage kidney disease. In this scenario biomarkers can detect renal pathology more accurately and early than currently known biomarkers, including serum creatinine, estimated glomerular filtration rate and urine albumin, they hold out hope for bettering the care of individuals with kidney illnesses. Nowadays, nephrology is concentrating extensively on finding novel indicators of acute stage of kidney disease in order to prevent further complications from chronic kidney disease as well as end-stage renal disease. The best treatment targets for a particular patient or illness context may also be determined with the use of proteomic and genomic biomarkers. Therefore, current advancements in the study of important biomarkers including tumor necrosis factor, transforming growth factor, interleukin −1, interleukin-18, nephrin, uromodulin, collagen, osteopontin, NGAL and Dickkopf-3 are linked to different aspects of renal injury. Prognosis and risk classification can be enhanced by a variety of proteome and genome biomarkers that are linked to different pathophysiological processes that follow renal damage.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 65-75"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The diagnostic value of miRNAs combination for Kurdish NAFLD patients","authors":"Sarah Esmaeilpour ,&nbsp;Farshad Sheikhesmaili ,&nbsp;Mohammad Moradzad ,&nbsp;Bijan Noori ,&nbsp;Mohammad Abdi ,&nbsp;Zakaria Vahabzadeh","doi":"10.1016/j.abst.2025.11.004","DOIUrl":"10.1016/j.abst.2025.11.004","url":null,"abstract":"<div><h3>Background and objectives</h3><div>Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of liver disorders ranging from simple steatosis to steatohepatitis. The development of non-invasive diagnostic tools is crucial for management of liver diseases. MicroRNAs (miRNAs) have emerged as potential biomarkers for NAFLD diagnostic. This case–control pilot study included 30 patients with NAFLD and 30 healthy controls. Our findings indicate promising potential of miR-34a, miR-192, and miR-122 as non-invasive biomarkers for NAFLD.</div></div><div><h3>Materials and methods</h3><div>We enrolled 30 confirmed NAFLD patients (grade 3) and 30 healthy individuals as controls. General laboratory tests were assessed in both groups. MicroRNA expression levels were quantified using RT-qPCR, and data were analyzed using R software. Diagnostic table was assessed using the area under the ROC curve and 95 % confidence intervals.</div></div><div><h3>Results</h3><div>Significantly elevated serum levels of miR-34a and miR-192 were observed in NAFLD patients compared to controls (<em>P</em> = 0.002 and <em>P</em> &lt; 0.0001, respectively), whereas miR-122 was downregulated (<em>P</em> &lt; 0.001). The combination of miR-34a, miR-192, and miR-122 showed a high apparent diagnostic performance, which should be interpreted with caution given the limited sample size.</div></div><div><h3>Conclusion</h3><div>This pilot study suggests that serum miR-34a, miR-192, and miR-122 may serve as promising indicator for NAFLD patients.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 405-413"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and IoT in healthcare: Recent advancements, challenges & future direction","authors":"Md Zonayed ,&nbsp;Rumana Tasnim ,&nbsp;Sayma Sultana Jhara ,&nbsp;Mariam Akter Mimona ,&nbsp;Molla Rashied Hussein ,&nbsp;Md Hosne Mobarak ,&nbsp;Umme Salma","doi":"10.1016/j.abst.2025.08.006","DOIUrl":"10.1016/j.abst.2025.08.006","url":null,"abstract":"<div><h3>Background</h3><div>The integration of Machine Learning and Deep Learning with IoT-enabled devices for real-time health monitoring has significantly revolutionized healthcare. These technologies facilitate the analysis of intricate medical datasets, yielding actionable insights that promote evidence-based clinical decision-making. Although significant advancements have been made, there is still an absence of a thorough synthesis regarding current applications, primary challenges, and prospective research directions. This review aims to synthesize recent applications, identify significant gaps, and propose clear direction for future research.</div></div><div><h3>Methodology</h3><div>A comprehensive narrative review was performed where a systematic literature search was conducted in PubMed and Scopus for studies published between 2020 and 2025. A total of 300 pertinent papers on ML and IoT's applications in healthcare were selected and analyzed to synthesize technological advancements, trade-offs, practical implications, challenges, and potential directions for future research.</div></div><div><h3>Key findings</h3><div>Neural network models, such as CNNs and ANNs, along with ensemble methods like Random Forest and XGBoost, often attain predictive accuracies ranging from 85 % to 95 %. Advanced technique, like generative imaging models, reinforcement learning, and transformer-based architectures, improve diagnostics, chronic disease management, robotic-assisted surgery, and predictive analytics, while explainable AI promotes clinical trust. Cloud-edge integration utilizing lightweight machine learning models enables real-time, energy-efficient applications, enhancing diagnosis, decision support, personalization, and cost-effectiveness, notwithstanding current challenges.</div></div><div><h3>Conclusion</h3><div>To conclude, the integration of ML and IoT is transforming healthcare through enhanced monitoring, improved predictive capabilities, and tailored treatment approaches. Addressing persistent limitations is crucial for fully realizing its potential and directing future research in this evolving field.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 335-364"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic analysis identifies an incipient signature to forecast imatinib resistance before start of treatment in patients with chronic myeloid leukemia","authors":"Rahul Mojidra ,&nbsp;Nilesh Gardi ,&nbsp;Bhausaheb Bagal ,&nbsp;Navin Khattry ,&nbsp;Anant Gokarn ,&nbsp;Sachin Punatar ,&nbsp;Rukmini Govekar","doi":"10.1016/j.abst.2025.01.004","DOIUrl":"10.1016/j.abst.2025.01.004","url":null,"abstract":"<div><div>The unprecedented success of tyrosine kinase inhibitor (TKI), imatinib, to induce remission in 86 % of chronic phase (CP) patients of chronic myeloid leukemia (CML) is undermined by drug resistance. Few patients have primary resistance and do not respond to imatinib, while majority of them who respond must continue treatment to sustain the remission. This continued treatment increases the possibility of developing secondary resistance and these resistant patients progress to the acute phase of blast crisis (BC) wherein the survival is 7–11 months. However, if the patients who are at risk of developing resistance, can be identified before start of treatment with imatinib, they can be assisted with better treatment strategies. To identify markers to forecast imatinib resistance we chose to study chromosomal aberrations (CAs), as they are associated with causation, progression as well as drug resistance in CML. In this study, genomic DNA from CD34⁺ cells, isolated from healthy controls and CML patients in CP and BC before start of treatment, were subjected to array comparative genomic hybridization (aCGH). The number of CAs on distinct chromosomes identified by genomic analysis in CML-CP and -BC patients, were able to segregate the patients as imatinib-sensitive and -resistant in cluster analysis. The CP patients who misclassified into predominantly imatinib-resistant BC cluster were found to develop resistance during treatment. We thus report an incipient genomic signature which can forecast development of secondary resistance and upon validation in large cohort of patients has the potential for clinical application.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 59-64"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum regarding “Declaration of Competing Interest statements in previously published articles”","authors":"","doi":"10.1016/j.abst.2025.11.006","DOIUrl":"10.1016/j.abst.2025.11.006","url":null,"abstract":"","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Page 395"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarkers in immunology: Their impact on immune function and response","authors":"Deepika Kaushik ,&nbsp;Baojun Xu ,&nbsp;Mukul Kumar","doi":"10.1016/j.abst.2025.03.001","DOIUrl":"10.1016/j.abst.2025.03.001","url":null,"abstract":"<div><div>The immune system is a complex network of organs, tissues, and cells that plays a critical role in defending the body against life-threatening diseases such as infections, cancer, Alzheimer's, and Crohn's disease. Biomarkers serve as valuable tools for assessing immune responses to these threats and evaluating the efficacy of interventions such as vaccines and immunotherapies. They are particularly useful in monitoring immune function in individuals with autoimmune disorders, where the immune system attacks the body's own tissues, or in immunodeficiencies, where immune responses are inadequate. Biomarkers provide a dynamic and comprehensive means of understanding disease mechanisms through observational and analytical epidemiology, randomized clinical trials, screening, diagnosis, and prognosis. However, despite their potential, the clinical application of biomarkers faces challenges, including sensitivity, reproducibility, and the complexity of multi-biomarker panels. Standardization of analytical techniques remains a critical hurdle, as variability in methodologies can impact the reliability and comparability of biomarker data. Addressing these challenges through improved analytical characterization, validation protocols, and integration of advanced technologies is essential to enhance the clinical utility of biomarkers in immune system assessment and disease management. Moreover, biomarkers offer critical insights into disease progression, from early onset to advanced stages, though their sensitivity and specificity may be influenced by various factors. In this review, we focus on the effect of biomarkers on the immune system.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 95-110"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}