Evidence map›Paper›PMID 36443830›Full record

ArticleBMC pharmacology & toxicology2022

The effect of tacrolimus-induced toxicity on metabolic profiling in target tissues of mice.

Dadi Xie, Jinxiu Guo, Ruili Dang, Yanan Li, Qingying Si, Wenxiu Han, Shan Wang, Ning Wei, Junjun Meng, Linlin Wu

Open access · goldAbstract read
In one paragraph

Article in BMC pharmacology & toxicology, 2022. 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
2.7field-weighted citation impact, top 10% 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, 13 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Tacrolimus and diabetic rodent models.Pharmacological reports : PR · 2025
    Review
  6. Article
  7. Review
  8. Article
  9. 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

10 authors at 3 institutions in 1 country.

Dadi Xie *Tengzhou Central People's Hospital, Tengzhou, 277500, China.
Jinxiu Guo *Translational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China.
Ruili Dang *Translational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China.
Yanan LiTranslational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China.
Qingying SiTengzhou Central People's Hospital, Tengzhou, 277500, China.
Wenxiu HanTranslational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China.
Shan WangTranslational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China.
Ning WeiDepartment of Gastroenterology, Shanting District People's Hospital, Zaozhuang, 277200, China.
Junjun MengTranslational Pharmaceutical Laboratory, Jining First People's Hospital, Jining, 272000, China. mengjunjunpku@163.com.
Linlin WuTengzhou Central People's Hospital, Tengzhou, 277500, China. linlinliff@163.com.
Jining First People's Hospital · CNTengzhou Central People's Hospital · CNLinzi District People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tacrolimus (Tac) is a common immunosuppressant that used in organ transplantation. However, its therapeutic index is narrow, and it is prone to adverse side effects, along with an increased risk of toxicity, namely, cardio-, nephro-, hepato-, and neurotoxicity. Prior metabolomic investigations involving Tac-driven toxicity primarily focused on changes in individual organs. However, extensive research on multiple matrices is uncommon. Hence, in this research, the authors systemically evaluated Tac-mediated toxicity in major organs, namely, serum, brain, heart, liver, lung, kidney, and intestines, using gas chromatography-mass spectrometry (GC-MS). The authors also employed multivariate analyses, including orthogonal projections to the latent structure (OPLS) and t-test, to screen 8 serum metabolites, namely, D-proline, glycerol, D-fructose, D-glucitol, sulfurous acid, 1-monopalmitin (MG (16:0/0:0/0:0)), glycerol monostearate (MG (0:0/18:0/0:0)), and cholesterol. Metabolic changes within the brain involved alterations in the levels of butanamide, tartronic acid, aminomalonic acid, scyllo-inositol, dihydromorphine, myo-inositol, and 11-octadecenoic acid. Within the heart, the acetone and D-fructose metabolites were altered. In the liver, D-glucitol, L-sorbose, palmitic acid, myo-inositol, and uridine were altered. In the lung, L-lactic acid, L-5-oxoproline, L-threonine, phosphoric acid, phosphorylethanolamine, D-allose, and cholesterol were altered. Lastly, in the kidney, L-valine and D-glucose were altered. Our findings will provide a systematic evaluation of the metabolic alterations in target organs within a Tac-driven toxicity mouse model.

Indexed as

GlycerolTacrolimusAnimalsFructoseInositolMiceSorbitolFructoseGlycerolInositolSorbitolTacrolimusCalcineurin inhibitorDrug toxicityGas chromatography−mass spectrometryMain tissuesMetabolome

Identifiers

PMID36443830
PMCPMC9703746
OpenAlexW4310197877

What OpenQuestion holds

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LicenceCC BY
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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.