Evidence map›Paper›PMID 41745970›Full record

ArticleVeterinary sciences2026

Integrated Molecular and Hematobiochemical Biomarkers for the Detection of Bovine Babesiosis in Holstein Calves.

Haifa Ali Alqhtani, Mohamed Marzok, Rasha Yassin Elkhidr, Ahmed A Elsayed, Safaa M Barghash, Ahmed L El-Naggar, Mohamed T Ragab, Ahmed I Ateya, Fatmah Ahmed Safhi, Wafaa A Osman

Abstract read
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In one paragraph

Article in Veterinary sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Haifa Ali AlqhtaniDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Mohamed MarzokDepartment of Clinical Studies, College of Veterinary Medicine, King Faisal University, P.O. Box 400, Al Ahssaa 31982, Saudi Arabia.ORCID 0000-0002-7961-1247
Rasha Yassin ElkhidrDepartment of Clinical Studies, College of Veterinary Medicine, King Faisal University, P.O. Box 400, Al Ahssaa 31982, Saudi Arabia.
Ahmed A ElsayedAnimal and Poultry Nutrition Department, Desert Research Center, Mataria, Cairo 11753, Egypt.
Safaa M BarghashAnimal and Poultry Nutrition Department, Desert Research Center, Mataria, Cairo 11753, Egypt.
Ahmed L El-NaggarAnimal and Poultry Nutrition Department, Desert Research Center, Mataria, Cairo 11753, Egypt.
Mohamed T RagabAnimal and Poultry Nutrition Department, Desert Research Center, Mataria, Cairo 11753, Egypt.
Ahmed I AteyaDepartment of Development of Animal Wealth, Faculty of Veterinary Medicine, Mansoura University, Mansoura 35516, Egypt.
Fatmah Ahmed SafhiDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0000-0002-0533-614X
Wafaa A OsmanAnimal and Poultry Nutrition Department, Desert Research Center, Mataria, Cairo 11753, Egypt.

Funding

Princess Nourah bint Abdulrahman University PNURSP2026R458
6 · The paper itself

Abstract

Bovine babesiosis is a widespread tick-borne parasitic disease that compromises calf health and productivity, causing substantial economic losses. This study evaluated the potential of molecular and hematobiochemical biomarkers for the detection of babesiosis in Holstein calves by analyzing the expression dynamics of selected immune and antioxidant genes and their association with blood-based indicators. Blood samples were collected from 243 fattening calves, classified as healthy (

Indexed as

Babesia spp.calvesdiagnostic indicatorsgene expression profilinginflammatory responsePCR amplification

Identifiers

PMID41745970
PMCPMC12945156

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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.