npj Biosensing最新文献

{"title":"Future directions in all-optical label-free single-molecule sensing","authors":"Koji Masuda, Reuven Gordon, Philipp Kukura, Christoph Langhammer, Sang-Hyun Oh, Frank Vollmer, Peter Zijlstra","doi":"10.1038/s44328-025-00069-4","DOIUrl":"https://doi.org/10.1038/s44328-025-00069-4","url":null,"abstract":"This perspective discusses the future role of all-optical label-free single-molecule sensing. After summarizing the core working principles of the different detection modalities we discuss future research directions in terms of technology development and applications. In terms of future technologies we address research directions in the areas of multi-parametric and interaction free sensors, integration and miniaturization, and advanced data analysis. We further describe potential applications towards probing of protein interactions, DNA and protein sequencing, and molecular diagnostics.","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44328-025-00069-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147903302","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":"Circulating tumor cell detection in cancer patients using in-flow deep learning holography.","authors":"Kevin Mallery, Nathaniel R Bristow, Nicholas Heller, Yash Travadi, Ali Arafa, Kaylee Kamalanathan, Catalina Galeano-Garces, Mahdi Ahmadi, Grant Schaap, Alexa Hesch, Olivia Hedeen, Zikora Izuora, Joel Hapke, Jeffrey Miller, Arjun Viswanathan, Ivo Babris, Songyi Bae, Baisali Bhattacharya, Tuan Le, Tony Clacko, Emmanuel S Antonarakis, Badrinath R Konety, Justin M Drake, Jiarong Hong","doi":"10.1038/s44328-026-00084-z","DOIUrl":"10.1038/s44328-026-00084-z","url":null,"abstract":"<p><p>Circulating tumor cells (CTCs) are cancer cells found in the bloodstream that serve as biomarkers for early cancer detection, prognostication, and disease monitoring. However, CTC detection remains challenging due to low cell abundance and heterogeneity. Digital holographic microscopy (DHM) offers a promising, label-free method for high-throughput CTC identification by capturing superior morphological information compared to traditional imaging methods, while remaining compatible with in-flow data acquisition. We present a streamlined DHM-based system that integrates microfluidic enrichment with deep learning-driven image analysis, supplemented by immunofluorescent profiling, to improve sensitivity and specificity of CTC enumeration. Specifically, our platform combines inertial microfluidic preprocessing with dual-modality imaging, integrating holography with fluorescence sensing of up to two markers. A deep learning model, trained on a diverse set of healthy blood samples and cancer cell lines, and executed in real-time, provides a morphological confidence on a cell-by-cell basis that may then be combined with immunofluorescence criteria for enumeration. In a pilot study, we demonstrate higher CTC counts in patients with late-stage prostate cancer (<i>n</i> = 13) compared to healthy controls (<i>n</i> = 8), with a patient-level false positive rate of 1 cell/mL. Notably, nearly two-thirds of identified CTCs were EpCAM-negative but PSMA positive (a prostate specific epithelial marker), suggesting that traditional use of EpCAM as an epithelial marker for CTCs may lead to false negatives. These findings highlight the potential of DHM for applications including but not limited to screening, diagnostics, and precision oncology.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"23"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13079088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147701421","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":"Biocoin: an open-source wearable platform for multiplexed and multimodal biosensing.","authors":"Tyler Hack, Drew A Hall","doi":"10.1038/s44328-026-00103-z","DOIUrl":"10.1038/s44328-026-00103-z","url":null,"abstract":"<p><p>Wearable biosensors promise proactive, precision medicine by enabling continuous biochemical monitoring, yet their clinical translation remains hindered by high-performance hardware accessibility barriers. Practical on-body operation demands stringent miniaturization, multiplexing, multi-method sensing, iontophoresis, and ultra-low power wireless operation - challenges that force researchers to remain in vitro or engineer tailored hardware. Unfortunately, prior systems rarely satisfy these requirements simultaneously, proliferating inadaptable designs that prevent reuse across applications. We introduce Biocoin, the first fully open-source, open-hardware wearable biosensing platform that unifies these needs in a reconfigurable, general-purpose framework. The 530 mm² wireless device demonstrates >10 multiplexed sensor inputs, broad physicochemical sensing (amperometry, voltammetry, potentiometry, impedimetry, temperature) with benchtop-comparable performance, current-monitored iontophoresis for biofluid extraction, and extensive power optimizations enabling months-long, µA-level multimodal sensing. All hardware, firmware, and software are publicly released, providing a turnkey platform that removes long-standing hardware barriers to on-body biosensor validation and accelerates their translation into clinically actionable wearables.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"44"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13433255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148674733","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":"Label-free optical observation of disordered-to-ordered transitions in single intrinsically disordered proteins.","authors":"Saaman Zargarbashi, Cyril Dominguez, Matthew Peters, Arman Yousefi, Sharon Munday, Yanhong Wang, Shreyasi Chatterjee, Andrew J Hudson, Reuven Gordon, Christopher J Mellor, Lei Xu, Mohsen Rahmani, Cuifeng Ying","doi":"10.1038/s44328-026-00098-7","DOIUrl":"10.1038/s44328-026-00098-7","url":null,"abstract":"<p><p>Intrinsically disordered proteins (IDPs) and structured proteins with intrinsically disordered regions (IDRs) lack a definitive tertiary structure and contribute to the onset of diseases such as Alzheimer's and cancer. To date, experimental observation of single, label-free IDPs/IDRs poses a significant challenge due to their structural heterogeneity, limiting ensemble techniques from fully capturing their properties, whilst single-molecule measurements require site-specific modifications or non-physiological conditions, perturbing their native biophysics. Here, we demonstrate the first experimental observation of unmodified IDP/IDR conformational dynamics at the single-molecule level, achieved by optical trapping and investigation of individual IDPs/IDRs using nanoaperture optical tweezers. Our results reveal that IDPs/IDRs exhibit significantly larger conformational variations compared to globular proteins of similar size. We demonstrate that phosphorylation of native tau-441 by glycogen synthase kinase 3-beta (GSK3β-tau) induces compaction and reduced conformational dynamics. We further observed a disorder-to-order transition during the binding of the N-terminal region of the Src-associated protein in mitosis of 68 kDa (Sam68) to G8.5 RNA. These findings present nanoaperture optical tweezers as a powerful approach to advance our understanding of IDPs/IDRs and further decode their roles in associated diseases.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"33"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13246436/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221575","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":"Biosensors in dental, oral and craniofacial applications.","authors":"Yongchen Tai, Yunshen Li, Kayla M Mornay, Madison K Woodard, Wenting Wang, Xianrui Yang, Jing Pan","doi":"10.1038/s44328-026-00079-w","DOIUrl":"10.1038/s44328-026-00079-w","url":null,"abstract":"<p><p>Oral and dental health is an important indicator and determinant of an individual's overall well-being. Untreated oral diseases can lead to severe systemic complications. Monitoring the oral environment and identifying biochemical and physiological patterns associated with disease states, such as periodontitis, gingivitis, caries, and oral cancers, is essential for early diagnosis and effective intervention. This review evaluates the current clinical needs in biochemical and physiological monitoring for oral healthcare and state-of-the-art biosensors capable of continuous analyte measurement. We surveyed the relevant biomarkers for common oral and dental diseases in patients compared to healthy controls. The design and performance of recent biosensing devices for these target analytes are reviewed and evaluated. For biochemical sensing, we found intraoral biosensors for high-abundance small molecules, such as ions and metabolites, have advanced significantly in recent years. However, robust sensing technologies for low-abundance analytes, including cytokines and other inflammatory biomarkers, remain limited and require further development in sensing mechanisms, bio-interfaces, and device integration. For physiological sensing, particularly the measurement of forces in tooth movement, recent developments in force sensor technologies have substantially improved measurement accuracy over traditional techniques. Despite these advancements, current platforms still face limitations in achieving long-term, real-time monitoring of mechanical conditions within the oral cavity due to challenges related to biocompatibility and device miniaturization. In conclusion, while notable progress has been made in biosensing for oral applications, continued research in device integration with clinical practices is essential to realize robust and clinically deployable biosensor systems that can advance precision oral healthcare.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12920093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147273868","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":"AI-assisted label-free single-particle analysis of milk-derived extracellular vesicles enabled by nanotweezers.","authors":"Ikjun Hong, Abayomi E Opadele, Guodong Zhu, Yuankai Huo, Justus C Ndukaife","doi":"10.1038/s44328-026-00104-y","DOIUrl":"10.1038/s44328-026-00104-y","url":null,"abstract":"<p><p>Milk-derived extracellular vesicles (mEVs) are promising drug carriers because they can survive the digestive tract, be engineered to avoid immune rejection, and deliver therapeutic cargo to the body. Fully realizing this potential requires precise, single-particle measurements of size, composition, and purity, yet current analytical tools are often slow, require chemical labels. Here we present an electrohydrodynamic nanotweezer platform that rapidly traps thousands of mEVs in parallel, enables label-free interferometric scattering imaging, and uses artificial intelligence for automated analysis. The device employs a thin gold film patterned with a 15 µm hole array that generates radially-converging AC-driven fluid flows to hold vesicles in place in parallel within seconds. By briefly releasing them, we track their Brownian motion to calculate their size from diffusion behavior and estimate refractive index from their interferometric contrast signals to assess sample purity and heterogeneity. This fast, non-perturbative workflow combines scalable trapping, real-time label-free imaging, and automated analysis, offering a powerful approach to studying mEVs and accelerate their use as therapeutic delivery vehicles.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"37"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13246505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221558","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":"Microfluidic nanomagnetically isolated neuron- and astrocyte-derived extracellular vesicles to differentiate Lewy body and Alzheimer's disease.","authors":"Stephanie J Yang, Andrew A Lin, Hanfei Shen, Laura W Pappalardo, Griffin B Spychalski, Jean Rosario, Leah K Forsberg, Kiera M Grant, Joshua R Buser, Rodolfo Savica, Sid O'Bryant, David T Jones, Dennis W Dickson, R Ross Reichard, Aivi T Nguyen, David F Meaney, Bradley F Boeve, Owen A Ross, Pamela J McLean, David Issadore","doi":"10.1038/s44328-026-00086-x","DOIUrl":"10.1038/s44328-026-00086-x","url":null,"abstract":"<p><p>Identifying plasma-based biomarkers that can accurately differentiate Lewy body disease (LBD) from Alzheimer's disease (AD) remains a major challenge. Extracellular vesicles (EVs), which carry molecular cargo from their parent cells and can cross the blood-brain barrier, offer a new path forward. We developed the multiplexed Track-Etch magnetic NanoPOre (mTENPO) platform, a highly parallelized microfluidic technology for cell-specific EV isolation, and demonstrated independent enrichment of GluR2+ (neuron-derived) and GLAST+ (astrocyte-derived) EVs from the antemortem plasma of 137 autopsy-confirmed LBD, AD, mixed pathology, and control subjects. By integrating miRNA sequencing of GluR2+ and GLAST + EV cargo with plasma measurements of Aβ40, Aβ42, tau, p-Tau181, and p-Tau231, we identified a multimodal 15-feature panel that more comprehensively reflects brain pathology than conventional biomarkers. Using tenfold cross-validation to mitigate overfitting, the panel achieved an accuracy of 0.95 and an area under the curve of 0.96 for distinguishing LBD versus AD.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12982126/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147470539","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":"Metal-phenolic networks improve interfacial electron transfer in bio-electrochemical systems.","authors":"Sunanda Dey, Madeleine E Laws, Songyi Yeon, Jesus M Lopez Baltazar, Chao-Chi Kuo, Ariel L Furst","doi":"10.1038/s44328-026-00100-2","DOIUrl":"10.1038/s44328-026-00100-2","url":null,"abstract":"<p><p>Multi-enzyme electrocatalytic cascades often suffer from poor electron-transfer efficiency, limiting their utility. We overcome this critical challenge by integrating an interfacial metal-phenolic network (MPN) layer with tunable properties based on the metal and polyphenol employed. Upon electropolymerization, MPNs provide a stable matrix for co-immobilizing glucose oxidase and horseradish peroxidase, enhancing their tandem activity. Through systematic evaluation of the impact of MPN composition on electron transfer, we demonstrate the tunability of these materials for cascade-specific optimization. This simple material is expected to support diverse enzymatic reactions important for technologies ranging from bioenergy to biosensing.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"32"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13197222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148019803","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":"Interdigitated capacitive strain sensor enables precise yoga-inspired motion tracking.","authors":"Maria Papaefstathiou, Mohamed Elgendi, Carlo Menon","doi":"10.1038/s44328-026-00101-1","DOIUrl":"10.1038/s44328-026-00101-1","url":null,"abstract":"<p><p>We report a fully textile-based interdigitated capacitive (IDC) strain sensor for wearable posture recognition. The sensor is lightweight, comfortable, and washable, and maintained stable electromechanical performance during 6,500 strain cycles, with absolute value of the gauge factor ranging from 0.67 to 0.81 across the tested strain conditions. Integrated into clothing, the sensor captured multidimensional electrical responses, including capacitance-, resistance-, and phase-related signals, during four biomechanically distinct yoga postures: High Lunge, Lunge Forward, Squat, and Tree. Using a supervised machine-learning pipeline combining handcrafted sensor-channel features and MiniROCKET time-series features, record-level classification achieved an accuracy of 94.4% and a macro-averaged F1 score of 94.2%. Record-level five-fold cross-validation further showed stable performance across folds, supporting the robustness of the classification framework within the present controlled cohort. One-vs-rest receiver operating characteristic analysis yielded area under the curve values of 90%, 94%, 99%, and 99% for High Lunge, Lunge Forward, Squat, and Tree, respectively. Channel ablation analysis identified capacitance-derived features as the most informative predictors. Statistical and temporal analyses further showed posture-dependent differences in signal magnitude, normalized response, and waveform dynamics, while supervised low-dimensional projection revealed distinct class structure. These results demonstrate the feasibility of textile-based IDC sensing for wearable movement monitoring applications such as such digital fitness.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"39"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13282173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148298301","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":"A multi-readout photonic sensor for rapid diagnosis of Von Willebrand disease.","authors":"Jordan N Butt, Robert L Scott, Michael R Bryan, Daniel J Steiner, Rachele Bachmann, Bianca Santonastaso, Madelyn Gatchell, Majed Refaai, Benjamin L Miller","doi":"10.1038/s44328-025-00073-8","DOIUrl":"10.1038/s44328-025-00073-8","url":null,"abstract":"<p><p>Von Willebrand Disease (VWD) is characterized by improper blood clotting, resulting from qualitative or quantitative changes in Von Willebrand factor (VWF). Diagnosis of VWD currently relies on measuring both the concentration of VWF and its activity by the binding ability to several different proteins, each of which are currently quantified separately. As such, the current diagnosis of VWD is complex and expensive, requiring multiple tests for a positive clinical determination. To address this challenge, we report a multiplexed biosensor that simultaneously measures VWF concentration and binding activity in plasma, enabling rapid diagnosis of VWD and discrimination among multiple subtypes. Using an 18-plex photonic ring resonator in a disposable, lateral flow assay-like format as the core technology, capture of VWF by an immobilized monoclonal antibody results in a red shift in resonance, which is referenced to a nonspecific binding control. Other ring resonators on the chip, functionalized with binding partners of VWF, allow simultaneous measurement of VWF binding to collagen, Factor VIII, and the GP1b receptor. Evaluation of a panel of 37 single-donor human plasma samples previously analyzed using FDA clinically approved assays demonstrated that the sensor has comparable concentration results and was able to accurately identify several categories of VWD (type 1, 2 A, and type 3).</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"3 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12864038/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146121760","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}