Advances in biomarker sciences and technology最新文献

{"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":"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":"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":"Bringing lab to the field: Exploring innovations in point-of-care diagnostics for the rapid detection and management of tropical diseases in resource-limited settings","authors":"Abdullahi Tunde Aborode ,&nbsp;Ridwan Olamilekan Adesola ,&nbsp;Godfred Yawson Scott ,&nbsp;Emele Arthur-Hayford ,&nbsp;Oche Joseph Otorkpa ,&nbsp;Somuah Daniel Kwaku ,&nbsp;Emmanuel Ebuka Elebesunu ,&nbsp;Eghaghe Osadebamwen Nibokun ,&nbsp;Ibude Jane Aruorivwooghene ,&nbsp;Adetolase A. Bakre ,&nbsp;Oluwaseun Adeolu Ogundijo ,&nbsp;Olamilekan Gabriel Banwo ,&nbsp;Oluwatobiloba Ige ,&nbsp;Ibrahim O. Adelakun ,&nbsp;Isreal Ayobami Onifade ,&nbsp;Segun E. Ogungbemi ,&nbsp;Boluwatife T. Dosunmu ,&nbsp;Oluwaseunayo Deborah Ayando ,&nbsp;Nike Idowu ,&nbsp;Grace A. Adegoye ,&nbsp;Olusegun Oluwaseun Jimoh","doi":"10.1016/j.abst.2025.01.001","DOIUrl":"10.1016/j.abst.2025.01.001","url":null,"abstract":"<div><div>Tropical diseases present major health challenges in regions with limited resources, where access to advanced laboratory facilities is often scarce. This study explores the innovative techniques emerging in point-of-care (POC) diagnostics that are transforming the detection and treatment of tropical diseases. These advancements aim to provide faster diagnosis, better medical care, and ongoing monitoring in areas where traditional diagnostic methods are not practical, combining the precision of laboratory testing with the accessibility of field-based solutions. The review focuses on rapid diagnostic tests, molecular diagnostic tools, and smartphone-based applications, analyzing their advantages, limitations, and potential impact on healthcare delivery. It also addresses the challenges and opportunities involved in deploying these technologies in resource-constrained environments. Key to their success is the need for interdisciplinary collaboration, sustainable funding models, and strong regulatory frameworks to ensure their effective integration into healthcare systems. The review emphasizes how point-of-care diagnostics can play a crucial role in reducing the burden of tropical diseases and advancing health equity on a global scale.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 28-43"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098985","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":"Etiological connections between initial COVID-19 and two rare infectious diseases","authors":"Zhengjun Zhang","doi":"10.1016/j.abst.2024.12.001","DOIUrl":"10.1016/j.abst.2024.12.001","url":null,"abstract":"<div><div>The origin of COVID-19 remains unclear despite extensive research. Theoretical models can simplify complex epigenetic landscapes by reducing vast methylation sites into manageable sets, revealing fundamental pathogen interactions that leap medical advances for the first time in tracing virus origin in the literature and practices. In our study, a max-logistic intelligence classifier analyzed 865,859 Infinium MethylationEPIC sites (CpGs), identifying eight CpGs that achieved 100 % accuracy in distinguishing COVID-19 patients from other respiratory disease patients and healthy controls. One CpG, cg07126281, linked to the SAMM50 gene, shares genetic ties with rare infectious diseases like Sennetsu fever and glanders, suggesting a potential connection between COVID-19 and these diseases, possibly transmitted through contaminated seafood or glanders-infected individuals. Identifying such links among 865,859 CpG sites is challenging, with a random correlation probability of less than one in ten million. However, the likelihood of finding meaningful associations with rare diseases lowers this probability to one in one hundred million, reinforcing the credibility of our findings. These results highlight the importance of investigating seafood markets and global supply chains in tracing COVID-19's origins and emphasize the need for ongoing biosafety and biosecurity measures to prevent future outbreaks.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 8-20"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099112","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":"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}

{"title":"Review on zebra fish as an alternative animal model for neurological studies","authors":"Khode Aniket Prakash ,&nbsp;Darshana Sunil Nagmoti ,&nbsp;Manali Sanjayswami Borkar ,&nbsp;Hiray Kuldeep Pannalal ,&nbsp;Nagaraju Bandaru","doi":"10.1016/j.abst.2025.08.005","DOIUrl":"10.1016/j.abst.2025.08.005","url":null,"abstract":"<div><div>Zebrafish (<em>Danio rerio</em>) have emerged as a powerful alternative animal model in neurological research due to their unique combination of genetic, anatomical, and physiological characteristics. Their transparent embryonic development, high genetic homology with humans, and well-characterized nervous system make them invaluable for studying neurological diseases and disorders. Zebrafish offer practical advantages such as rapid reproduction, cost-effectiveness, and suitability for high-throughput screening. They have been extensively utilized to investigate neurodevelopmental disorders, neurodegenerative diseases like Parkinson's and Alzheimer's, and epilepsy. Moreover, their amenability to genetic manipulation enables precise modeling of human neurological conditions. Behavioral assays in zebrafish provide insights into cognitive, motor, and emotional functions, which can be quantified to study disease phenotypes and therapeutic interventions. Recent advances in imaging techniques, such as live imaging of neuronal activity using calcium indicators, have further enhanced their utility. This review highlights the advantages of zebrafish as an alternative model system, discusses key findings from zebrafish-based neurological studies, and outlines challenges such as translating findings to mammalian systems. By consolidating current knowledge, this article emphasizes the pivotal role of zebrafish in advancing our understanding of neurological mechanisms and in developing novel treatments for brain disorders.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010287","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":"Bridging traditional risk factors and genetic insights: A review on polygenic risk scores in cardiovascular diseases","authors":"Abhishek Gupta ,&nbsp;Komal Shah ,&nbsp;Aakansha Shukla","doi":"10.1016/j.abst.2025.09.002","DOIUrl":"10.1016/j.abst.2025.09.002","url":null,"abstract":"<div><div>Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, with traditional risk models often falling short in predicting individual susceptibility-especially among diverse populations. Recent advances in genomics have led to the development of polygenic risk scores (PRS), which aggregate the effects of multiple single nucleotide polymorphisms (SNPs) to estimate genetic predisposition to CVD. This review explores the scientific evolution, clinical relevance, and limitations of PRS in CVD prediction. Evidence shows that integrating PRS with conventional risk factors significantly improves risk stratification, aiding in early detection and personalized prevention strategies. Notably, ethnicity-specific PRS models are being developed to enhance predictive accuracy for non-European populations, including South Asians. Despite its promise, PRS implementation faces challenges, such as Eurocentric bias in genome-wide association studies (GWAS), limited accessibility in low- and middle-income countries, and ethical concerns regarding equity and data privacy. Future research should emphasize multi-ethnic datasets, integration with clinical and lifestyle data, and development of equitable policies. As PRS continues to be effective in refining cardiovascular risk stratification, its integration into public health frameworks could revolutionize risk assessment and drive the shift toward precision medicine.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 365-377"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048295","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":"CAR-T and nanotechnology: A comparative Perspective on autoimmune disease and cancer","authors":"A. Pavithra ,&nbsp;C. Ragavendran","doi":"10.1016/j.abst.2025.03.002","DOIUrl":"10.1016/j.abst.2025.03.002","url":null,"abstract":"<div><div>Nanotechnology has emerged as a key transformative force in upgrading Chimeric Antigen Receptor T-cell (CAR-T) from generation to generation in cancer and autoimmune treatment. Nanotechnology-aided CAR-T therapy has shown its ability to overcome various challenges in contemporary CAR-T therapy. The comparative analysis of CAR-T and its applications in cancer and autoimmune diseases focuses on target specificity, with immune cells being used as “chaperones” for nanoparticles, Immunosuppressibility by modifying microarchitecture, prolonged cell viability, and other nanotechnological modifications has been briefly discussed. The latest and smartest innovations, such as nano-enzymes linked CAR, stimuli-responsive nanoparticles, nano-based dual-targeting CAR structures, and nano-cargos, have upgraded CAR-T therapy to its latest advancements. Despite regulatory compliance, and cost of production and utility of Nano-CAR-T can be overcome by the use of green nanotechnology. The aid of advancements in AIs, software, MLs etc offers promising solutions to hurdles in scalability. A number of clinical and preclinical trials in the last few years have been explained to highlight the current status of Nano-CAR-T in present-day treatment and for a promising future. This review emphasizes the novel role of nanotechnology in shaping the future of advanced CAR-T therapy, paving the way for milestones in medical research.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 124-137"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143790815","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}