Evidence map›Paper›PMID 39172629›Full record

ArticleACS applied materials & interfaces2024

Functionalized Graphene-Based Biosensors for Early Detection of Subclinical Ketosis in Dairy Cows.

Shannon Chick, Matin Ataei Kachouei, Katharine Knowlton, Md Azahar Ali

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shannon ChickSchool of Animal Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States.ORCID 0009-0005-9247-8806
Matin Ataei KachoueiSchool of Animal Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States.ORCID 0000-0002-2917-6961
Katharine KnowltonSchool of Animal Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States.
Md Azahar AliSchool of Animal Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States.ORCID 0000-0001-5752-8808

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision livestock farming utilizing advanced diagnostic tools, including biosensors, can play a key role in the management of livestock operations to improve the productivity, health, and well-being of animals. Detection of ketosis, a metabolic disease that occurs in early lactation dairy cows due to a negative energy balance, is one potential on-farm use of biosensors. Beta-hydroxybutyrate (βHB) is an excellent biomarker for monitoring ketosis in dairy cows because βHB is one of the main ketones produced during this metabolic state. In this report, we developed a low-cost, Keto-sensor (graphene-based sensor) for the detection of βHB concentrations in less than a minute. On this device, graphene nanosheets were layered onto a screen-printed electrode (SPE), and then, a stabilized enzyme (beta-hydroxybutyrate dehydrogenase, NAD

Indexed as

3-Hydroxybutyric AcidBiosensing TechniquesGraphiteKetosisAnimalsCattleCattle DiseasesElectrodesFemaleHydroxybutyrate DehydrogenaseLimit of Detection3-Hydroxybutyric AcidGraphiteHydroxybutyrate DehydrogenaseBiosensorGraphenePrecision livestock farmingStabilized enzymeSubclinical ketosis

Identifiers

PMID39172629
PMCPMC11450706

What OpenQuestion holds

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LicenceCC BY
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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.