Evidence map›Paper›PMID 36557474›Full record

ArticleMicromachines2022

A Study on the Uniform Distribution and Counting Method of Raw Cow's Milk Somatic Cells.

Wei Zhou, Xingyu Li, Wanyun Su, Hongbiao Zheng, Guangxin An, Zhilin Li, Shanshan Li

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Wei ZhouSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
Xingyu LiSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.ORCID 0000-0002-3066-3580
Wanyun SuSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
Hongbiao ZhengSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
Guangxin AnSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
Zhilin LiSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
Shanshan LiSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.ORCID 0000-0001-8293-9676

Funding

Department of Human Resources and Social Security of Hebei Province C20200314Department of Human Resources and Social Security of Hebei Province C20210337Distinguish Young Scholars in Tianjin 2018 3rd Round 180191Hebei Natural Science Foundation E2020202101Hebei Natural Science Foundation F2021202001Hebei Provincial Natural Science Fund Project B2021202038Hebei Science and Technology Foundation 19271707D
6 · The paper itself

Abstract

The somatic cell count (SCC) in raw milk is an important basis for determining whether a cow is suffering from mastitis. To address the problem of an uneven distribution of somatic cells due to cell-adherent sedimentation, among other reasons, during milk sampling, which in turn results in unrepresentative somatic cell counting, a method is proposed for obtaining a uniform distribution of somatic cells and improving the counting accuracy based on a nine-cell grid microfluidic chip. Firstly, a simulation was performed to verify the uniformity of the somatic cell distribution within the chip observation cavities. Secondly, a nine-cell grid microfluidic chip was prepared and a negative-pressure injection system integrating staining and stirring was developed to ensure that the somatic cells were uniformly distributed and free from air contamination during the injection process. As well as the structure of the chip, a microscopic imaging system was developed, and the nine chip observation cavities were photographed. Finally, the somatic cells were counted and the uniformity of the somatic cell distribution was verified using image processing. The experimental results show that the standard deviation coefficient of the SCC in each group of nine images was less than 1.61%. The automatic counting accuracy of the system was between 97.07% and 99.47%. This research method lays the foundation for the detection and prevention of mastitis in cows.

Indexed as

cell countingdairy mastitisimage processingmicrofluidic chipstandard deviation coefficient

Identifiers

PMID36557474
PMCPMC9784796

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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.