Evidence map›Paper›PMID 36483914›Full record

ArticleEXCLI journal2022

Comparative histological analysis of the skin for forensic investigation of some animal species.

Elsayed S I Mohammed, Fatma A Madkour, Mohammed Zayed, Rasha Radey, Ahmed Ghallab, Reham Hassan

Open access · greenAbstract read
In one paragraph

Article in EXCLI journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

6 authors at 1 institution in 1 country.

Elsayed S I MohammedDepartment of Histology and Cytology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
Fatma A MadkourDepartment Anatomy and Embryology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
Mohammed ZayedDepartment of Surgery, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
Rasha RadeyAnimal Health Research Institute, Qena Branch, Qena, Egypt.
Ahmed GhallabDepartment of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
Reham HassanDepartment of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
South Valley University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macroscopical and histological analysis of the skin is fundamental in both human and veterinary forensic investigations. However, databases of differential skin histology of various animal species are rare. The aim of the present study is to identify species-specific differential histological features of the skin that could be used in forensic investigations including animal identification. For this purpose, skin specimens were collected from the neck region of various farm animals including buffalo, cow, camel, sheep, goat, dog, and donkey, and were processed for histological analysis. Our comparative analysis revealed specific histological features in the skin that could differentiate between the studied animal species. The epidermis layer of the skin was very thick in buffalo, intermediate in cow, sheep, goat, dog, and donkey, but very thin in camel. The papillomatous epidermis was very frequent in buffalo, but very rare in cow. In the dermis layer of the skin, four structures were located which showed differential features between the studied animal species:

Indexed as

differential histologyepidermisforensic medicineskin histology

Identifiers

PMID36483914
PMCPMC9727269
OpenAlexW4311028541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.