npj BiosensingPub Date : 2024-06-26DOI: 10.1038/s44328-024-00003-0
Peter R. Christenson, Hyeonjeong Jeong, Hyerim Ahn, Manci Li, Gage Rowden, Rachel L. Shoemaker, Peter A. Larsen, Hye Yoon Park, Sang-Hyun Oh
{"title":"Visual detection of misfolded alpha-synuclein and prions via capillary-based quaking-induced conversion assay (Cap-QuIC)","authors":"Peter R. Christenson, Hyeonjeong Jeong, Hyerim Ahn, Manci Li, Gage Rowden, Rachel L. Shoemaker, Peter A. Larsen, Hye Yoon Park, Sang-Hyun Oh","doi":"10.1038/s44328-024-00003-0","DOIUrl":"10.1038/s44328-024-00003-0","url":null,"abstract":"Neurodegenerative protein misfolding diseases impact tens of millions of people worldwide, contributing to millions of deaths and economic hardships across multiple scales. The prevalence of neurodegenerative disease is predicted to greatly increase over the coming decades, yet effective diagnostics for such diseases are limited. Most diagnoses come from the observation of external symptoms in clinical settings, which typically manifest during relatively advanced stages of disease, thus limiting potential therapeutic applications. While progress is being made on biomarker testing, the underlying methods largely rely on fragile and expensive equipment that limits their point-of-care potential, especially in developing countries. Here we present Capillary-based Quaking Induced Conversion (Cap-QuIC) as a visual diagnostic assay based on simple capillary action for the detection of neurodegenerative disease without necessitating expensive and complex capital equipment. We demonstrate that Cap-QuIC has the potential to be a detection tool for a broad range of misfolded proteins by successfully distinguishing misfolded versus healthy proteins associated with Parkinson’s disease (α-synuclein) and Chronic Wasting Disease (prions). Additionally, we show that Cap-QuIC can accurately classify biological tissue samples from wild white-tailed deer infected with Chronic Wasting Disease. Our findings elucidate the underlying mechanism that enables the Cap-QuIC assay to distinguish misfolded protein, highlighting its potential as a diagnostic technology for neurodegenerative diseases.","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44328-024-00003-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489095","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":"High-throughput light-induced immunoassay with milliwatt-level laser under one-minute optical antibody-coating on nanoparticle-imprinted substrate","authors":"Masatoshi Kanoda, Kota Hayashi, Yumiko Takagi, Mamoru Tamura, Shiho Tokonami, Takuya Iida","doi":"10.1038/s44328-024-00004-z","DOIUrl":"10.1038/s44328-024-00004-z","url":null,"abstract":"The efficient detection of protein biomarkers is critical for public health. However, the sensitivity of conventional antigen test kits is relatively low for early diagnosis, and laboratory immunoassays require complex pretreatment processes overnight. If target nanomaterials could be remotely guided to the detection site, simpler and faster methods would be developed. Here, we reveal the mechanism of light-induced immunoassay that anti-spike-protein antibodies for SARS-CoV-2 were coated on our developed nanoparticle-imprinted plasmonic substrate (NPI-PS) over the submillimeter area within one minute and nanoparticles modified with spike proteins can be selectively detected within a few minutes at one or two orders of higher sensitivity via a two-step optical condensation using NPI-PS. NPI-PS exhibits high-performance optical condensation with high photothermal properties even under milliwatt-class nonresonant laser irradiation, enabling a wide range of quantitative measurements. These findings support an innovative strategy to mitigate pandemic threats and various diseases through the high-throughput detection of protein biomarkers.","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44328-024-00004-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489064","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}
npj BiosensingPub Date : 2024-06-26DOI: 10.1038/s44328-024-00002-1
Mohamed Elgendi, Igor Martinelli, Carlo Menon
{"title":"Optimal signal quality index for remote photoplethysmogram sensing","authors":"Mohamed Elgendi, Igor Martinelli, Carlo Menon","doi":"10.1038/s44328-024-00002-1","DOIUrl":"10.1038/s44328-024-00002-1","url":null,"abstract":"Remote photoplethysmography (rPPG) enables non-invasive monitoring of circulatory signals using mobile devices, a crucial advancement in biosensing. Despite its potential, ensuring signal quality amidst noise and artifacts remains a significant challenge, particularly in healthcare applications. Addressing this, our study focuses on a singular signal quality index (SQI) for rPPG, aimed at simplifying high-quality video capture for heart rate detection and cardiac assessment. We introduce a practical threshold for this SQI, specifically the signal-to-noise ratio index (NSQI), optimized for straightforward implementation on portable devices for real-time video analysis. Employing (NSQI < 0.293) as our threshold, our methodology successfully identifies high-quality cardiac information in video frames, effectively mitigating the influence of noise and artifacts. Validated on publicly available datasets with advanced machine learning algorithms and leave-one-out cross-validation, our approach significantly reduces computational complexity. This innovation not only enhances efficiency in health monitoring applications but also offers a pragmatic solution for remote biosensing. Our findings constitute a notable advancement in rPPG signal quality assessment, marking a critical step forward in the development of remote cardiac monitoring technologies with extensive healthcare implications.","PeriodicalId":501705,"journal":{"name":"npj Biosensing","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44328-024-00002-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489093","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}
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