Evidence map›Paper›PMID 40768948›Full record

ArticleBiosensors & bioelectronics2025

Point-of-need one-pot multiplexed RT-LAMP test for detecting three common respiratory viruses in saliva.

Aneesh Kshirsagar, Dean DeRosa, Anthony J Politza, Tianyi Liu, Ming Dong, Weihua Guan

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Aneesh KshirsagarDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA, 16802, United States.
Dean DeRosaDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA, 16802, United States.
Anthony J PolitzaDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, United States.
Tianyi LiuDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA, 16802, United States.
Ming DongDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA, 16802, United States.
Weihua GuanDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47408, United States. Electronic address: guanw@iu.edu.

Funding

Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)R33HD105610 · NICHD · CENTRAL MICHIGAN UNIVERSITY · PI HICKS, STEVEN DANIEL, SETHURAMAN, USHA · 2023 to 2023
$1.4M
Home Fingerprick Blood-Based HIV Self-Test For Quantitative Monitoring Of Viral ReboundR33AI147419 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI GUAN, WEIHUA · 2023 to 2024
$1.3M
Home Fingerprick Blood-Based HIV Self-Test For Quantitative Monitoring Of Viral ReboundR61AI147419 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI GUAN, WEIHUA · 2020 to 2022
$1.0M
NIAID NIH HHS R33 AI147419NIAID NIH HHS R61 AI147419NICHD NIH HHS R33 HD105610
6 · The paper itself

Abstract

Respiratory viral infections pose a significant global public health challenge, partly due to the difficulty in rapidly and accurately distinguishing between viruses with similar symptoms at the point of care, hindering timely and appropriate treatment and limiting effective infection control and prevention efforts. Here, we developed a multiplexed, non-invasive saliva-based, reverse transcription loop-mediated isothermal amplification (RT-LAMP) test that enables the simultaneous detection of three of the most common respiratory infections, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Influenza (Flu), and respiratory syncytial virus (RSV), in a single reaction via specific probes and monitored in real-time by a machine-learning-enabled compact analyzer. Our results demonstrate that the multiplexed assay can effectively detect three target RNAs with high accuracy. Further, testing with spiked saliva samples showed strong agreement with reverse transcription polymerase chain reaction (RT-PCR) assay, with area under the curve (AUC) values of 0.82, 0.93, and 0.96 for RSV, Influenza, and SARS-CoV-2, respectively. By enabling the rapid detection of respiratory infections from easily collected saliva samples at the point of care, the device presented here offers a practical and efficient tool for improving outcomes and helping prevent the spread of contagious diseases.

Indexed as

Biosensing TechniquesCOVID-19Influenza, HumanMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesRespiratory Syncytial VirusesRespiratory Syncytial Virus InfectionsSalivaSARS-CoV-2HumansPoint-of-Care SystemsPoint-of-Care TestingRespiratory Syncytial Virus, HumanRNA, ViralRNA, ViralMachine learningMultiplexed RT-LAMPPoint-of-careRespiratory virus detectionSaliva

Identifiers

PMID40768948
PMCPMC12395363

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Registered trials

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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.