ArticleACS central science2025
A Viral Neuraminidase-Specific Sensor for Taste-Based Detection of Influenza.
Article in ACS central science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Pre-Symptomatic Detection of Influenza with Taste.ACS central science · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Influenza has caused the deadliest pandemics in history, thereby prompting advances in our ability to ensure vigilance at all stages of future outbreaks. Quarantining patients early is crucial when it comes to preventing these outbreaks, but it is challenging with influenza due to presymptomatic transmission. Presymptomatic detection translates into massive screening needs, which necessitate cost-effective tools with access for anyone, anywhere, and at any time. We met these challenges by synthesizing sensors that respond to influenza infections with taste generation by using the tongue as an always-available detector. In doing so, we utilized the virus's need for neuraminidase cleavage of α-glycosidic bonds to detect its presence in patients. We synthesized
Identifiers
What OpenQuestion holds
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.