ArticleBMC veterinary research2024
Early pregnancy diagnosis in cows using corpus luteum blood flow analysis based on colour Doppler ultrasonography and mRNA analysis.
Article in BMC veterinary research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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
2 citing papers in PubMed.
- A Narrative Review of Early Pregnancy Diagnosis Technologies for Livestock: From Conventional to Intelligent Systems.Animals : an open access journal from MDPI · 2026Review
- Early pregnancy detection in ruminants: challenges and innovations.The Journal of reproduction and development · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundReproductive efficiency is paramount in the dairy industry, where early pregnancy detection of dairy cows will allow to detect the non-pregnant animals early, thus enabling to re-synchronize them and getting them pregnant leading to decrease in calving interval, which, in turn, is critical for maximizing productivity and economic gain. The objective of this study was to evaluate the colour Doppler ultrasonography (CDUS) and peripheral blood leukocytes (PBLs)-based pregnancy-associated biomarker mRNAs expression for the earliest detection of pregnancy status in the dairy cows at post insemination. Intensively managed animals were ovulation synchronized and subjected to timed artificial insemination (TAI). On day 20, corpus luteum blood flow (CLBF) was evaluated using CDUS in 30 cows. The percentage of the incoming blood flow (as an area) of the corpus luteum (CL) was determined using an image analysis software. On day 35, the same operator performed a final pregnancy diagnosis using transrectal ultrasonography to confirm the pregnancy. Blood samples were collected on day 20 and 28 after TAI for biomarkers analysis. The mRNA expression levels of ISG15, MX1, MX2, and PAG9 genes in PBLs were determined by quantitative polymerase chain reaction (qPCR).
resultsThe identified CLBF cutoff point resulted 100% sensitivity and negative predictive value (NPV) in determining non-pregnant status on day 20 in the cows. Overall, MX2 and ISG15 mRNAs showed the most significant (P < 0.05) expression levels in pregnant animals on day 20 and 28 compared to non-pregnant animals. Among them, MX2 showed the highest expression levels on both days, ascertaining it as the better candidate biomarker for the earliest identification of pregnancy.
conclusionsThe CDUS-based CLBF analysis on day 20 after TAI can be potentially used for the early identification of non-pregnancy status in dairy cows and MX2 could be a potential mRNA candidate for the identification of pregnancy in cows. Further studies should be conducted in large scale to validate these findings due to the small sample number used in the current study.
Indexed as
Identifiers
What Socratic 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 Socratic graph.