npj Biosensing最新文献

{"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":"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":"https://doi.org/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":"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":"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}

{"title":"Direct observation of small molecule activator binding to single PR65 protein.","authors":"Annie Yang-Schulz, Maria Zacharopoulou, Sema Zeynep Yilmaz, Anupam Banerjee, Satyaki Saha, Daniel Nietlispach, Michael Ohlmeyer, Mert Gur, Laura S Itzhaki, Ivet Bahar, Reuven Gordon","doi":"10.1038/s44328-024-00018-7","DOIUrl":"10.1038/s44328-024-00018-7","url":null,"abstract":"<p><p>The reactivation of heterotrimeric protein phosphatase 2A (PP2A) through small molecule activators is of interest to therapeutic intervention due to its dysregulation, which is linked to chronic conditions. This study focuses on the PP2A scaffold subunit PR65 and a small molecule activator, ATUX-8385, designed to bind directly to this subunit. Using a label-free single-molecule approach with nanoaperture optical tweezers (NOT), we quantify its binding, obtaining a dissociation constant of 13.6 ± 2.5 μM, consistent with ensemble fluorescence anisotropy results but challenging to achieve with other methods due to low affinity. Single-molecule NOT measurements reveal that binding increases optical scattering, indicating PR65 elongation. This interpretation is supported by all-atom molecular dynamics simulations showing PR65 adopts more extended conformations upon binding. This work highlights NOT's utility in quantifying binding kinetics and structural impact, offering insights valuable for drug discovery.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11738983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143019735","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 method for blood pressure hydrostatic pressure correction using wearable inertial sensors and deep learning.","authors":"David A M Colburn, Terry L Chern, Vincent E Guo, Kennedy A Salamat, Daniel N Pugliese, Corey K Bradley, Daichi Shimbo, Samuel K Sia","doi":"10.1038/s44328-024-00021-y","DOIUrl":"10.1038/s44328-024-00021-y","url":null,"abstract":"<p><p>Cuffless noninvasive blood pressure (BP) measurement could enable early unobtrusive detection of abnormal BP patterns, but when the sensor is placed on a location away from heart level (such as the arm), its accuracy is compromised by variations in the position of the sensor relative to heart level; such positional variations produce hydrostatic pressure changes that can cause swings in tens of mmHg in the measured BP if uncorrected. A standard method to correct for changes in hydrostatic pressure makes use of a bulky fluid-filled tube connecting heart level to the sensor. Here, we present an alternative method to correct for variations in hydrostatic pressure using unobtrusive wearable inertial sensors. This method, called IMU-Track, analyzes motion information with a deep learning model; for sensors placed on the arm, IMU-Track calculates parameterized arm-pose coordinates, which are then used to correct the measured BP. We demonstrated IMU-Track for BP measurements derived from pulse transit time, acquired using electrocardiography and finger photoplethysmography, with validation data collected across 20 participants. Across these participants, for the hand heights of 25 cm below or above the heart, mean absolute errors were reduced for systolic BP from 13.5 ± 1.1 and 9.6 ± 1.1 to 5.9 ± 0.7 and 5.9 ± 0.5 mmHg, respectively, and were reduced for diastolic BP from 15.0 ± 1.0 and 11.5 ± 1.5 to 6.8 ± 0.5 and 7.8 ± 0.8, respectively. On a commercial smartphone, the arm-tracking inference time was ~134 ms, sufficiently fast for real-time hydrostatic pressure correction. This method for correcting hydrostatic pressure may enable accurate passive cuffless BP monitors placed at positions away from heart level that accommodate everyday movements.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11785522/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082651","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 passive blood separation sensing platform for point-of-care devices.","authors":"Cameron Gilroy, Callum D Silver, Casper Kunstmann-Olsen, Lisa M Miller, Steven D Johnson, Thomas F Krauss","doi":"10.1038/s44328-025-00038-x","DOIUrl":"https://doi.org/10.1038/s44328-025-00038-x","url":null,"abstract":"<p><p>The blood test is one of the most performed investigations in clinical practice, with samples typically analysed in a centralised laboratory. Many of these tests monitor routine conditions that would benefit from a point-of-care approach, reducing the burden on practitioners, patients and healthcare systems. Such a decentralised model requires the development of sophisticated, yet easy-to-use technology; however, platforms that combine high-performance with low-cost and simplicity remain scarce. Moreover, most research papers only address a subset of requirements and study specific aspects in isolation. A systems approach that considers the interplay between each element of the technology is clearly required to develop a coherent solution. Here, we present such a systems approach in the context of testing for C-reactive protein (CRP), a commonly requested test in clinical practise that indicates inflammation and is particularly relevant for monitoring patients with chronic diseases, e.g. those with rheumatoid arthritis or who are undergoing cancer therapy. The approach we take here features an entirely passive microfluidic cartridge for blood separation, integrated with a high-performance sensing platform which we have tested in a real-world context. The device is compatible with a handheld detection unit and is simple to use yet can accurately detect CRP levels at clinically relevant levels.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12048346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060139","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":"Metabolite microextraction on surface-enhanced Raman scattering nanofibres and D₂O probing accelerate antibiotic susceptibility testing.","authors":"Malama Chisanga, Claudèle Lemay-St-Denis, Xinran Wei, Yuzhang Liang, Mengdi Lu, Wei Peng, Joelle N Pelletier, Jean-Francois Masson","doi":"10.1038/s44328-025-00039-w","DOIUrl":"10.1038/s44328-025-00039-w","url":null,"abstract":"<p><p>Rapid antibiotic susceptibility tests (AST) are vital for the effective treatment of disease, necessitating the development of analytical tools to address unmet needs in healthcare. Leveraging the sensitivity of plasmonic nanosensors and isotopic labelling has the potential to accelerate AST. Here, we developed surface-enhanced Raman scattering (SERS)-based nanofibre sensors and heavy water [deuterium oxide (D₂O)] labelling (SERS-DIP) for detecting the minimum inhibitory concentration (MIC) and AST for trimethoprim (TMP) against <i>E. coli</i>. SERS-DIP rapidly detected the MIC of TMP for the susceptible strain in 2 h. TMP-resistant cells retained the metabolic activity regardless of TMP levels, confirming the resistance phenotype. Kinetic analysis of D uptake by resistant cells treated with TMP (2 × MIC) revealed increasing D levels proportional to peak redshifts over time, confirmed by machine learning-driven data exploration. Our results demonstrate the utility of nanofibre-enabled SERS-DIP for robust AST, uncovering new spectral biomarkers that may impact clinical medicine.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"21"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12129813/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228197","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":"Optical biosensors for diagnosing neurodegenerative diseases.","authors":"Khuong Duy Mac, Judith Su","doi":"10.1038/s44328-025-00040-3","DOIUrl":"10.1038/s44328-025-00040-3","url":null,"abstract":"<p><p>Neurodegenerative diseases involve the progressive loss of neurons in the brain and nervous system, leading to functional decline. Early detection is critical for improving outcomes and advancing therapies. Optical biosensors, some of which offer rapid, label-free, and ultra-sensitive detection, have been applied to early diagnosis and drug screening. This review examines the principles and performance of different optical biosensors used for diagnosing neurodegenerative diseases and discusses potential future advancements.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"20"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12048351/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144001666","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 in SERS sensing moving from discriminative to generative.","authors":"Steven M Quarin, Der Vang, Ruxandra I Dima, George Stan, Pietro Strobbia","doi":"10.1038/s44328-025-00033-2","DOIUrl":"10.1038/s44328-025-00033-2","url":null,"abstract":"<p><p>This perspective discusses the present and future role of artificial intelligence (AI) and machine learning (ML) in surface-enhanced Raman scattering (SERS) sensing. Our goal is to guide the reader through current applications, mainly focused on discriminative approaches aimed at developing new and improved SERS diagnostic capabilities, towards the future role of AI in SERS sensing, with the use of generative approaches to design new materials and biomaterials.</p>","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":"2 1","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11845314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485194","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}