Evidence map›Paper›PMID 31142683›Full record

ArticleThe Journal of veterinary medical science2019

Wall thickness and mucous cell distribution in the rabbit large intestine.

Ahmad Faisal Amiry, Tetsuhito Kigata, Hideshi Shibata

Open access · diamondAbstract read
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Article in The Journal of veterinary medical science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 96% 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

4 citing papers in PubMed, 10 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

3 authors at 2 institutions in 1 country.

Ahmad Faisal AmiryLaboratory of Veterinary Anatomy, Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Tokyo 183-8509, Japan.
Tetsuhito KigataLaboratory of Veterinary Anatomy, Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Tokyo 183-8509, Japan.
Hideshi ShibataLaboratory of Veterinary Anatomy, Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Tokyo 183-8509, Japan.
Tokyo University of Agriculture and Technology · JPGifu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To achieve a better understanding of rabbit large intestinal functions, such as production of hard and soft feces and cecal fermentation, knowledge of the intestinal wall structure is essential. However, such knowledge is far from complete. Therefore, the aims of this study were to measure the thickness of the wall and its constituent layers and describe distribution of mucous cells in each segment of the large intestine in New Zealand White rabbits. Results showed that the cecum had the thinnest entire wall throughout the large intestine, and the fusus coli and rectum had a thicker entire wall in comparison to the cecum, the first segment of the proximal colon, the second segment of the proximal colon, and the distal colon. Moreover, the thickness of the mucosa in the fusus coli and that of the inner and outer layers of the tunica muscularis in the rectum were greater than that of the other segments. Mucous cells in the mucosa were the fewest in the cecum and most numerous in the fusus coli. This study provides detailed knowledge of the wall thickness and distribution of mucous cells in the large intestine of the rabbit. These findings are important for improving our understanding of rabbit intestinal physiology and pathology.

Indexed as

AnimalsIntestinal MucosaIntestine, LargeMaleRabbitslarge intestinemucous cell distributionrabbitwall thickness

Identifiers

PMID31142683
PMCPMC6656812
OpenAlexW2947197093

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.