Evidence map›Paper›PMID 31089317›Full record

ArticleVeterinary world2019

Clinical-histopathological and molecular study of ovine pulmonary adenocarcinoma in Awassi sheep in Al-Qadisiyah Province, Iraq.

Khalefa Ali Mansour, Saad Hashim Al-Husseiny, Qassim Haleem Kshash, Asaad Jassim

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Article in Veterinary world, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 22% of its field
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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Khalefa Ali MansourDepartment of Veterinary Internal Medicine, College of Veterinary Medicine, University of Al-Qadisiyah, Iraq.
Saad Hashim Al-HusseinyDepartment of Veterinary Internal Medicine, College of Veterinary Medicine, University of Al-Qadisiyah, Iraq.
Qassim Haleem KshashDepartment of Veterinary Internal Medicine, College of Veterinary Medicine, University of Al-Qadisiyah, Iraq.
Asaad JassimDepartment of Veterinary Internal Medicine, College of Veterinary Medicine, University of Al-Qadisiyah, Iraq.
University of Al-Qadisiyah · IQ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study aimed to conduct a clinical-histopathological and molecular evaluation of ovine pulmonary adenocarcinoma (OPA) in Awassi sheep in various regions of Al-Qadisiyah Province, Iraq. MATERIALS AND

methodsA total of 150 sheep were clinically evaluated, and the wheelbarrow test was performed. 100 samples (35 blood, 25 lung tissue, 20 lymph node, and 20 lung fluid samples) were randomly selected from living and slaughtered sheep. All samples were subjected to polymerase chain reaction (PCR). Histopathological examinations were performed for four lung tissue and two lymph node samples.

resultsA diagnosis of OPA was made based on the results of the clinical examination and the clinical signs shown by the animals, such as dyspnea, polypnea, coughing, mucous nasal discharge, moist rales on auscultation of the affected lungs, and emaciation. Interestingly, the animals tested positive for the wheelbarrow test, with frothy nares accompanied by profuse and clear lung fluid. Histopathological examination showed various lesions such as glandular transformation in the lung tissues and emphysema. Moreover, lymph nodes showed marked follicular atrophy and necrosis-associated lymphocyte infiltration in the affected tissues. PCR revealed that 25% of the samples including eight (22.8%) blood, five (20%) lung tissue, five (25%) lymph node, and seven (35%) lung fluid samples were positive for Jaagsiekte sheep retrovirus; this result was highly significant.

conclusionThe results of our study indicated that in Iraq, OPA diagnosis should be based on pathological findings and results of advanced procedures such as PCR.

Indexed as

Jaagsiekte sheep retrovirusovine pulmonary adenocarcinomapolymerase chain reaction

Identifiers

PMID31089317
PMCPMC6487251
OpenAlexW2923315195

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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.