Evidence map›Paper›PMID 39747135›Full record

ArticleNature communications2025

Attomolar-sensitive milk fever sensor using 3D-printed multiplex sensing structures.

Matin Ataei Kachouei, Jacob Parkulo, Samuel D Gerrard, Tatiane Fernandes, Johan S Osorio, Md Azahar Ali

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Matin Ataei KachoueiSchool of Animal Sciences, Virginia Tech, Blacksburg, USA.ORCID 0000-0002-2917-6961
Jacob ParkuloBiological Systems Engineering, Virginia Tech, Blacksburg, USA.
Samuel D GerrardSchool of Animal Sciences, Virginia Tech, Blacksburg, USA.ORCID 0009-0009-8345-9637
Tatiane FernandesSchool of Animal Sciences, Virginia Tech, Blacksburg, USA.
Johan S OsorioSchool of Animal Sciences, Virginia Tech, Blacksburg, USA.
Md Azahar AliSchool of Animal Sciences, Virginia Tech, Blacksburg, USA. azahar@vt.edu.ORCID 0000-0001-5752-8808

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diagnosis of milk fever or hypocalcemia in lactating cows has a significant economic impact on the dairy industry. It is challenging to identify asymptomatic subclinical hypocalcemia (SCH) in transition dairy cows. Monitoring subclinical hypocalcemia in milk samples can expedite treatment and improve the health, productivity, and welfare of dairy cows. In this study, an attomolar-sensitive sensor is developed using extrusion-based 3D-printed sensing structures to detect the ratio of ionized calcium to phosphate levels in milk samples. The unique geometries of the lateral structure of 3D-printed sensors, along with the wrinkled surfaces, provide a limit of detection down to the attomole (138 aM) concentration of the target analyte. The calcium-to-phosphate ratio in milk samples not only provides early disease indications but also enables on-site testing. This highly selective test is validated using real milk and blood samples, and the results are compared with those of commercial meters. This fast response (~10 s) low-cost sensor opens a promising tool for the farm-side diagnostic of dairy cows that can promote best practice management of dairy cows.

Indexed as

CalciumMilkPrinting, Three-DimensionalAnimalsBiosensing TechniquesCattleCattle DiseasesDairyingFemaleHypocalcemiaLactationPhosphatesCalciumPhosphates

Identifiers

PMID39747135
PMCPMC11696081

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.