Evidence map›Paper›PMID 32351908›Full record

ReviewInternational journal of molecular and cellular medicine2019

Metabolomics and Cell Therapy in Diabetes Mellitus.

Bagher Larijani, Parisa Goodarzi, Moloud Payab, Sepideh Alavi-Moghadam, Fakher Rahim, Nikoo Bana, Mina Abedi, Maryam Arabi, Hossein Adibi, Kambiz Gilany and 1 more

Open access · greenAbstract readReview
In one paragraph

Review in International journal of molecular and cellular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Metabolomics Signatures of SARS-CoV-2 Infection.Advances in experimental medicine and biology · 2022
    Review
  6. The Fingerprints of Biomedical Science in Internal Medicine.Advances in experimental medicine and biology · 2022
    Article
  7. Review
  8. Review
  9. Review
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

11 authors at 3 institutions in 2 countries.

Bagher LarijaniEndocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical sciences, Tehran, Iran.
Parisa GoodarziBrain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
Moloud PayabObesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Sepideh Alavi-MoghadamCell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Fakher RahimHealth Research Institute, Thalassemia and Hemoglobinopathies Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Nikoo BanaMetabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mina AbediCell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Maryam ArabiCell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Hossein AdibiDiabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Kambiz GilanyDepartment of Biomedical Sciences, University of Antwerp, Belgium.
Babak ArjmandCell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Tehran University of Medical Sciences · IRAcademic Center for Education, Culture and Research · IRAhvaz Jundishapur University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes with a broad spectrum of complications has become a global epidemic metabolic disorder. Till now, several pharmaceutical and non-pharmaceutical therapeutic approaches were applied for its treatment. Cell-based therapies have become promising methods for diabetes treatment. Better understanding of diabetes pathogenesis and identification of its specific biomarkers along with evaluation of different treatments efficacy, can be possible by clarification of specific metabolic modifications during the diabetes progression. Subsequently, metabolomics technology can support this goal as an effective tool. The present review tried to show how metabolomics quantifications can be useful for diabetic monitoring before and after cell therapy. Cell therapy is an alternative approach to achieve diabetes treatments goals including insulin resistance amelioration, insulin independence reparation, and control of glycemia. OMICs approaches provide a comprehensive insight into the molecular mechanisms of cells features and functional mechanism of their genomics, transcriptomics, proteomics, and metabolomics profile which can be useful for their therapeutic application. As a modern technology for the detection and analysis of metabolites in biological samples, metabolomica can identify many of the metabolic and molecular pathways associated with diabetes and its following complications.

Indexed as

Cell-based therapydiabetes mellitusmetabolic diseasesmetabolic pathwaysmetabolomics

Identifiers

PMID32351908
PMCPMC7175613
OpenAlexW2952283657

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.