Evidence map›Paper›PMID 42523673›Full record

ArticleFrontiers in veterinary science2026

Microscopic and molecular detection of

Eman Sayed Mohammed, Ismail Elshahawy, Samia Fawy, Marwa Mohamed Fawaz, Qwait AlGabbani, Jamal Asseri, Manal F El-Khadragy, Mustafa Shukry, Ehab Kotb Elmahallawy

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 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

9 authors.

Eman Sayed MohammedDepartment of Parasitology, Faculty of Veterinary Medicine, Qena University, Qena, Egypt.
Ismail ElshahawyDepartment of Parasitology, Faculty of Veterinary Medicine, Qena University, Qena, Egypt.
Samia FawyDepartment of Parasitology, Faculty of Veterinary Medicine, Aswan University, Aswan, Egypt.
Marwa Mohamed FawazDepartment of Parasitology, Faculty of Veterinary Medicine, Qena University, Qena, Egypt.
Qwait AlGabbaniDepartment of Biology, College of Sciences and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Jamal AsseriDepartment of Biology, College of Science and Humanities, Shaqra University, Dawadmi, Saudi Arabia.
Manal F El-KhadragyDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Mustafa ShukryDepartment of Biomedical Sciences, College of Veterinary Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Ehab Kotb ElmahallawyDepartment of Zoonoses, Faculty of Veterinary Medicine, Sohag University, Sohag, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Goats constitute a fundamental component of the livestock sector in Egypt, contributing to rural livelihoods, food security, and national income. However, their productivity is increasingly affected by tick-borne diseases. Despite their importance, data on tick-borne pathogens affecting goats in Egypt are still lacking. Anaplasmosis and theileriosis are among the most important tick-borne diseases, posing serious threats to animal health and economic stability. Methods: This study investigated the microscopic and molecular detection of Results: Interestingly, microscopic examination of blood smears from 210 goats revealed an overall detection rate of Conclusion: Overall, this study provides the first molecular evidence of these pathogens in goats in Egypt, including detection of the emerging zoonotic pathogen

Indexed as

AnaplasmaEgyptgoatsmolecular detectionphylogenetic analysisTheileriatick-borne pathogens

Identifiers

PMID42523673
PMCPMC13407203

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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.