{"title":"Biofluid-based biosensors: Analyzing biomarkers for disease detection.","authors":"Hossein Chenani, Mohsen Saeidi, Abdolreza Simchi","doi":"10.1016/bs.pmbts.2025.04.001","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2025.04.001","url":null,"abstract":"<p><p>The advancement of biofluid-based biosensors (BBs) generates significant interest owing to their capacity for non-invasive, real-time health assessment. These biosensors, proficient in assessing biomarkers in body fluids like sweat, saliva, interstitial fluid, tears, blood, and urine, provide significant benefits in illness detection and individualized healthcare. Recent breakthroughs in sensor technology, encompassing the incorporation of nanomaterials, microfluidics, and wearable electronics, have markedly enhanced the sensitivity, specificity, and portability of biosensors. This chapter examines different types of biosensors, elucidating their functions and applications in the monitoring of various diseases, including metabolic disorders, infectious diseases, and cancer. It also tackles critical issues in the development and implementation of BBs, including attaining long-term stability, standardizing sampling techniques, and confirming their clinical diagnostic efficacy. Current trends are examined, especially the use of artificial intelligence and data analytics for biosensor data interpretation. Finally, the chapter provides some thoughts on the possible integration of these technologies into telemedicine and wearable health devices and their prospects for the future of digital healthcare.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"215 ","pages":"63-99"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clara R Pereira, André M Pereira, Joana S Teixeira, Ana R Sousa, Gabriela P Queirós, Rui S Costa, Marta S Nunes, Mariana Rocha
{"title":"Advanced energy storage systems as power sources for biosensing technologies.","authors":"Clara R Pereira, André M Pereira, Joana S Teixeira, Ana R Sousa, Gabriela P Queirós, Rui S Costa, Marta S Nunes, Mariana Rocha","doi":"10.1016/bs.pmbts.2025.05.012","DOIUrl":"10.1016/bs.pmbts.2025.05.012","url":null,"abstract":"<p><p>In recent years, the pursuit of efficient, reliable, customizable and sustainable power sources for wearable, ingestible and implantable (WII) biosensing technologies has intensified, aiming at effective energy management. This chapter overviews the recent developments on advanced energy storage systems for application as power sources in WII biosensing technologies. The progress in energy storage and harvesting technologies will be highlighted, ranging from batteries, supercapacitors and biofuel cells to wireless power transfer systems and self-powered energy harvesting/storage devices. Lastly, the key conclusions, current challenges, and future perspectives will be presented.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"215 ","pages":"181-235"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Peptides on patrol: Carrier systems for targeted delivery.","authors":"Vivek P Chavda, Joanna Bojarska","doi":"10.1016/bs.pmbts.2024.11.001","DOIUrl":"10.1016/bs.pmbts.2024.11.001","url":null,"abstract":"<p><p>The peptide is a small unit of protein that exhibits a diverse range of therapeutic applications, including but not limited to respiratory, inflammatory, oncologic, metabolic and neurological disorders. Peptides also play a significant role in signal transduction in cells. This chapter focuses on the delivery of peptides through the utilization of various carrier molecules, including liposomes, micelles, polymeric nanoparticles, and inorganic materials. These carriers facilitate targeted delivery and site-specific delivery of peptides. Different nanocarriers and therapeutic drug molecules also help with the delivery of peptides. Application to various diseases and different routes of delivery are described in this manuscript, along with current limitations and future prospects.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"212 ","pages":"129-161"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143693170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alice Romagnoli, Jesmina Rexha, Nunzio Perta, Samuele Di Cristofano, Noemi Borgognoni, Gloria Venturini, Francesco Pignotti, Domenico Raimondo, Tiziana Borsello, Daniele Di Marino
{"title":"Peptidomimetics design and characterization: Bridging experimental and computer-based approaches.","authors":"Alice Romagnoli, Jesmina Rexha, Nunzio Perta, Samuele Di Cristofano, Noemi Borgognoni, Gloria Venturini, Francesco Pignotti, Domenico Raimondo, Tiziana Borsello, Daniele Di Marino","doi":"10.1016/bs.pmbts.2024.07.002","DOIUrl":"10.1016/bs.pmbts.2024.07.002","url":null,"abstract":"<p><p>Peptidomimetics, designed to mimic peptide biological activity with more drug-like properties, are increasingly pivotal in medicinal chemistry. They offer enhanced systemic delivery, cell penetration, target specificity, and protection against peptidases when compared to their native peptide counterparts. Already utilized in treating diverse diseases like neurodegenerative disorders, cancer and infectious diseases, their future in medicine seems bright, with many peptidomimetics in clinical trials or development stages. Peptidomimetics are well-suited for addressing disturbed protein-protein interactions (PPIs), which often underlie various pathologies. Structural biology and computational methods like molecular dynamics simulations facilitate rational design, whereas machine learning algorithms accelerate protein structure prediction, enabling efficient drug development. Experimental validation via various spectroscopic, biophysical, and biochemical assays confirms computational predictions and guides further optimization. Peptidomimetics, with their tailored constrained structures, represent a frontier in drug design focused on targeting PPIs. In this overview, we present a comprehensive landscape of peptidomimetics, encompassing perspectives on involvement in pathologies, chemical strategies, and methodologies for their characterization, spanning in silico, in vitro and in cell approaches. With increasing interest from pharmaceutical sectors, peptidomimetics hold promise for revolutionizing therapeutic approaches, marking a new era of precision drug discovery.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"212 ","pages":"279-327"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143693174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tools and databases for non-coding RNAs.","authors":"Akshaykumar Zawar, Srinka Datta, Rishita Rathi, Rituja Shinde, Anushka Kalamkar, Neeraj Dangi, Poonam Deshpande","doi":"10.1016/bs.pmbts.2025.05.003","DOIUrl":"10.1016/bs.pmbts.2025.05.003","url":null,"abstract":"<p><p>Non-coding RNAs (ncRNAs) play a crucial role in various cellular processes, challenging the earlier notion that non-coding regions of the genome are merely \"junk DNA.\" Advances in molecular biology and sequencing technologies have revealed that these regions contain essential genetic elements, including ncRNAs, which influence gene regulation and other biological functions. As the significance of ncRNAs in human health and disease becomes increasingly clear, researchers have developed methods to identify, annotate, and classify these molecules into distinct types. Additionally, a growing interest has emerged in studying genetic variations within ncRNA genes and their potential implications in disease development. Understanding these variations can provide insights into how ncRNAs contribute to gene regulation and cellular function. This article explores the current landscape of ncRNA research, highlighting the latest techniques for detecting and identifying different classes of ncRNAs. Furthermore, it discusses computational tools and databases available for annotating ncRNAs and analyzing their functions across various biological processes. By integrating experimental and computational approaches, researchers can gain a deeper understanding of ncRNA roles, paving the way for potential therapeutic applications.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"214 ","pages":"163-178"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144340310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advancements in wearable biosensors: Transforming cardiovascular health monitoring and disease management.","authors":"Perla Boutros, Nour Kassem, Sandra Barteit","doi":"10.1016/bs.pmbts.2025.05.006","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2025.05.006","url":null,"abstract":"<p><p>Wearable biosensors enable continuous, non-invasive monitoring of cardiovascular parameters, including heart rate, heart rate variability, blood pressure, and thoracic fluid status. Utilizing technologies such as photoplethysmography, electrocardiography and piezoelectric sensing, these devices capture essential haemodynamic and arrhythmias data, facilitating early diagnosis and intervention. Advanced indices, such as pulse wave velocity and heart sounds, provide insights into arterial stiffness and valvular function, enhancing clinical assessment. Artificial intelligence and machine learning further refine data interpretation, generating predictive insights for personalized health. By integrating multiple sensors, these devices provide a comprehensive, individualized assessment, advancing personalized health and real-time disease management while empowering individuals with greater control over their health and enhancing data collection for improved diagnostics and treatment.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"215 ","pages":"279-310"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advances in materials for wearable biosensors.","authors":"Dhruvesh Maiya, Tvarit Patel, Alok Pandya","doi":"10.1016/bs.pmbts.2025.05.009","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2025.05.009","url":null,"abstract":"<p><p>Wearable biosensors have emerged as transformative instruments for continuous, non-invasive health monitoring, providing real-time analysis of biomarkers in biofluids such as sweat, interstitial fluid, and saliva. This chapter offers a comprehensive overview of the pivotal role of biomaterials in the design and functionality of wearable biosensors. It examines the selection criteria for biocompatible materials, emphasizing properties such as flexibility, stretchability, conductivity, and long-term stability. The discussion categorizes advanced materials, including hydrogels, polyurethanes, carbon-based nanomaterials, metallic nanoparticles, and microneedles, and evaluates their applications in biosensing platforms for glucose, pH, and metal ion detection. Through case studies and figure-integrated explanations, the chapter highlights innovations such as smart hydrogel contact lenses, self-powered alcohol biosensors, and closed-loop microneedle patches for autonomous insulin delivery. It further explores key challenges, including biofluid variability, sensor biocompatibility, and the correlation of biofluid biomarkers with blood concentrations. Finally, the chapter underscores future directions involving AI integration, federated learning, and next-generation biomaterials like biodegradable polymers and stretchable composites. By bridging materials science with digital health technologies, wearable biosensors are poised to revolutionize personalized medicine, enabling early diagnosis, disease prevention, and optimized therapeutic interventions.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"215 ","pages":"155-179"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Navid Kashaninejad, Prabuddha De Saram, Mohamed A Abdelfattah, Azeez Bakare, Hoang Huy Vu
{"title":"Wearable biosensors for cancer detection and monitoring.","authors":"Navid Kashaninejad, Prabuddha De Saram, Mohamed A Abdelfattah, Azeez Bakare, Hoang Huy Vu","doi":"10.1016/bs.pmbts.2025.05.005","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2025.05.005","url":null,"abstract":"<p><p>Wearable biosensors have emerged as game changers in healthcare, particularly for cancer detection and monitoring. Continuously sensing physiological and biochemical markers improves cancer diagnosis and treatment significantly. Conventional diagnostic methods, such as biopsies and imaging, are invasive, expensive, and logistically challenging, limiting their frequency and accessibility. Over the past decade, advances in microfluidics and surface engineering have expanded the capabilities of wearable biosensors. Readily accessible body fluids, such as sweat, saliva, tears, and interstitial fluid (ISF), are now recognized as valuable, non-invasive sources of tumor biomarkers. These fluids provide critical insights into tumor progression and therapy response, offering a patient-friendly alternative to traditional diagnostics. The integration of cutting-edge materials, advanced sensing technologies, and microfluidics has dramatically enhanced the sensitivity and specificity of wearable biosensors. This progress paves the way for personalized and preventive healthcare, improving patient convenience and reducing clinical visits and invasive procedures. This chapter explores the fundamental design principles, practical applications, and existing challenges of wearable biosensors. By addressing these issues, wearable biosensors can play a transformative role in early cancer detection and personalized treatment, ultimately improving patient outcomes.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"215 ","pages":"311-354"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Daptomycin: Mechanism of action, mechanisms of resistance, synthesis and structure-activity relationships.","authors":"Scott D Taylor, Ryan Moreira","doi":"10.1016/bs.pmbts.2024.04.003","DOIUrl":"10.1016/bs.pmbts.2024.04.003","url":null,"abstract":"<p><p>Daptomycin is a cyclic lipodepsipeptide antibiotic that is a mainstay for the treatment of serious infections caused by Gram-positive bacteria, including methicillin-resistant Streptococcus aureus and vancomycin resistant enterococci. It is one of the so-called last-resort antibiotics that are used to tackle life-threatening infections that do not respond to first-line treatments. However, resistance to daptomycin is eroding its clinical efficacy motivating the design and/or discovery of analogues that overcome resistance. The strategy of antibiotic analogue synthesis has been used to overcome bacterial resistance to many classes of antibiotics such as the β-lactams. Pursuing this strategy with daptomycin requires a detailed understanding of daptomycin's action mechanism and synthesis. Here, we discuss the action mechanism of daptomycin in a holistic manner and expand this discussion to rationalize conferred modes of resistance. Synthetic efforts, both chemical and biological, are discussed in detail and the structure-activity relationship emanating from these works is distilled into a usable model that can guide the design of new daptomycin analogues.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"212 ","pages":"163-234"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143693143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial intelligence and machine learning heuristics for discovery of ncRNAs.","authors":"Alfredo Benso, Gianfranco Politano","doi":"10.1016/bs.pmbts.2025.01.002","DOIUrl":"10.1016/bs.pmbts.2025.01.002","url":null,"abstract":"<p><p>Artificial intelligence (AI) has emerged as a powerful tool in molecular biology, significantly advancing the study of long non-coding RNAs (lncRNAs). This chapter examines the application of AI techniques, including machine learning (ML) and deep learning (DL), in predicting lncRNA functions, identifying disease associations, and annotating protein interactions. The discussion covers key methodologies such as supervised and unsupervised ML algorithms, recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformer-based models. A detailed description of a deep learning pipeline for functional annotation of lncRNA-binding proteins (lncRBPs) is provided, highlighting challenges in dataset preparation, model design, and usability. Integrating experimental validation with computational predictions is emphasized as a pathway to bridge AI-driven insights with biological understanding.</p>","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"214 ","pages":"145-162"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144340379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}