Evidence map›Paper›PMID 32373070›Full record

ArticleFrontiers in endocrinology2020

Assessing Urinary Metabolomics in Giant Pandas Using Chromatography/Mass Spectrometry: Pregnancy-Related Changes in the Metabolome.

Maosheng Cao, Chunjin Li, Yuliang Liu, Kailai Cai, Lu Chen, Chenfeng Yuan, Zijiao Zhao, Boqi Zhang, Rong Hou, Xu Zhou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 39 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

10 authors at 2 institutions in 1 country.

Maosheng CaoCollege of Animal Sciences, Jilin University, Changchun, China.
Chunjin LiCollege of Animal Sciences, Jilin University, Changchun, China.
Yuliang LiuChengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda, Chengdu, China.
Kailai CaiChengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda, Chengdu, China.
Lu ChenCollege of Animal Sciences, Jilin University, Changchun, China.
Chenfeng YuanCollege of Animal Sciences, Jilin University, Changchun, China.
Zijiao ZhaoCollege of Animal Sciences, Jilin University, Changchun, China.
Boqi ZhangCollege of Animal Sciences, Jilin University, Changchun, China.
Rong HouChengdu Research Base of Giant Panda Breeding, Sichuan Key Laboratory of Conservation Biology for Endangered Wildlife, Sichuan Academy of Giant Panda, Chengdu, China.
Xu ZhouCollege of Animal Sciences, Jilin University, Changchun, China.
Jilin University · CNChengdu Research Base of Giant Panda Breeding · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Giant pandas represent one of the most endangered species worldwide, and their reproductive capacity is extremely low. They have a relatively long gestational period, mainly because embryo implantation is delayed. Giant panda cubs comprise only a small proportion of the mother's body weight, making it difficult to determine whether a giant panda is pregnant. Timely determination of pregnancy contributes to the efficient breeding and management of giant pandas. Meanwhile, metabolomics studies the metabolic composition of biological samples, which can reflect metabolic functions in cells, tissues, and organisms. This work explored the urinary metabolites of giant pandas during pregnancy. A sample of 8 female pandas was selected. Differences in metabolite levels in giant panda urine samples were analyzed via ultra-high-performance liquid chromatography/mass spectrometry comparing pregnancy to anoestrus. Pattern recognition techniques, including partial least squares-discriminant analysis and orthogonal partial least squares-discriminant analysis, were used to analyze multiple parameters of the data. Compared with the results during anoestrus, multivariate statistical analysis of results obtained from the same pandas being pregnant identified 16 differential metabolites in the positive-ion mode and 43 differential metabolites in the negative-ion mode. The levels of tryptophan, choline, kynurenic acid, uric acid, indole-3-acetaldehyde, taurine, and betaine were higher in samples during pregnancy, whereas those of xanthurenic acid and S-adenosylhomocysteine were lower. Amino acid metabolism, lipid metabolism, and organic acid production differed significantly between anoestrus and pregnancy. Our results provide new insights into metabolic changes in the urine of giant pandas during pregnancy, and the differential levels of metabolites in urine provide a basis for determining pregnancy in giant pandas. Understanding these metabolic changes could be helpful for managing pregnant pandas to provide proper nutrients to their fetuses.

Indexed as

MetabolomeAnimalsBiomarkersChromatography, High Pressure LiquidDiscriminant AnalysisFemaleMass SpectrometryPregnancyUrsidaeBiomarkerscholinegiant pandaskynurenic acidmetabolomicstryptophan

Identifiers

PMID32373070
PMCPMC7176934
OpenAlexW3017017915

What Socratic 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 Socratic graph.