ArticleTheranostics2016
Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses.
Article in Theranostics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed.
- A smartphone-based particle diffusometry platform for sub-attomolar detection of Vibrio cholerae in environmental water.Biosensors & bioelectronics · 2020Trial
- Clinical evaluation of rapid fluorescent diagnostic immunochromatographic test for influenza A virus (H1N1).Scientific reports · 2018Trial
- Advances in Portable Optical Microscopy Using Cloud Technologies and Artificial Intelligence for Medical Applications.Sensors (Basel, Switzerland) · 2024Review
- Advancing Point-of-Care Diagnosis: Digitalizing Combinatorial Biomarker Signals for Lupus Nephritis.Biosensors · 2024Article
- Article
- Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection.Sensors (Basel, Switzerland) · 2023Review
- Fluorophore-encapsulated nanobeads for on-site, rapid, and sensitive lateral flow assay.Sensors and actuators. B, Chemical · 2023Article
- Article
- Cysteamine-Gold Coated Carboxylated Fluorescent Nanoparticle Mediated Point-of-Care Dual-Modality Detection of the H5N1 Pathogenic Virus.International journal of molecular sciences · 2022Article
- Virus Detection: From State-of-the-Art Laboratories to Smartphone-Based Point-of-Care Testing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- A generalizable one health framework for the control of zoonotic diseases.Scientific reports · 2022Article
- Photoluminescent Molecules and Materials as Diagnostic Reporters in Lateral Flow Assays.ACS applied bio materials · 2022Article
- Development of a Rapid Fluorescent Diagnostic System to Detect Subtype H9 Influenza A Virus in Chicken Feces.International journal of molecular sciences · 2021Article
- Avian Influenza in Wild Birds and Poultry: Dissemination Pathways, Monitoring Methods, and Virus Ecology.Pathogens (Basel, Switzerland) · 2021Review
- Optical Biosensors for Virus Detection: Prospects for SARS-CoV-2/COVID-19.Chembiochem : a European journal of chemical biology · 2021Review
- Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures.Biosensors & bioelectronics · 2021Review
- Recent trends in smartphone-based detection for biomedical applications: a review.Analytical and bioanalytical chemistry · 2021Review
- Review
- Integrated, Automated, Fast PCR System for Point-Of-Care Molecular Diagnosis of Bacterial Infection.Sensors (Basel, Switzerland) · 2021Article
- A Cross-Disciplinary View of Testing and Bioinformatic Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings.IEEE access : practical innovations, open solutions · 2021Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.