Evidence map›Paper›PMID 37514169›Full record

ArticlePharmaceutics2023

Lipid Nanoparticles as a Shuttle for Anti-Adipogenic miRNAs to Human Adipocytes.

Anna-Laurence Schachner-Nedherer, Julia Fuchs, Ivan Vidakovic, Oliver Höller, Gebhard Schratter, Gunter Almer, Eleonore Fröhlich, Andreas Zimmer, Martin Wabitsch, Karin Kornmueller and 1 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. New Mediators in the Crosstalk between Different Adipose Tissues.International journal of molecular sciences · 2024
    Pooled it
  2. Review
  3. Review
  4. Review
  5. Pulling the trigger: Noncoding RNAs in white adipose tissue browning.Reviews in endocrine & metabolic disorders · 2024
    Review
  6. Article
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 2 institutions in 1 country.

Anna-Laurence Schachner-NedhererGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0002-4122-5762
Julia FuchsGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0003-4576-615X
Ivan VidakovicGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.
Oliver HöllerGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.
Gebhard SchratterGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.
Gunter AlmerClinical Institute for Medical and Chemical Laboratory Diagnostics, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0003-3574-538X
Eleonore FröhlichCenter for Medical Research, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0002-6056-6829
Andreas ZimmerDepartment of Pharmaceutical Technology and Biopharmacy, Institute of Pharmaceutical Sciences, University of Graz, 8010 Graz, Austria.ORCID 0000-0003-3127-287X
Martin WabitschDivision of Pediatric Endocrinology, Diabetes Department of Pediatrics and Adolescent Medicine, University Medical Center Ulm, 89075 Ulm, Germany.ORCID 0000-0001-6795-8430
Karin KornmuellerGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0003-1039-9732
Ruth PrasslGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Medical Physics and Biophysics, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0002-1010-9494
Medical University of Graz · ATUniversity of Graz · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity and type 2 diabetes are major health burdens for which no effective therapy is available today. One treatment strategy could be to balance the metabolic functions of adipose tissue by regulating gene expressions using miRNAs. Here, we have loaded two anti-adipogenic miRNAs (miR26a and miR27a) into a pegylated lipid nanoparticle (PEG-LNP) formulation by a single-step microfluidic-assisted synthesis step. For the miRNA-loaded LNPs, the following system properties were determined: particle size, zeta potential, miRNA complexation efficiency, and cytotoxicity. We have used a human preadipocyte cell line to address the transfection efficiency and biological effects of the miRNA candidates at the gene and protein level. Our findings revealed that the upregulation of miR27a in preadipocytes inhibits adipogenesis by the downregulation of PPARγ and the reduction of lipid droplet formation. In contrast, miR26a transfection in adipocytes induced white adipocyte browning detected as the upregulation of uncoupling protein 1 (UCP1) as a marker of non-shivering thermogenesis. We conclude that the selective delivery of miRNAs by PEG-LNPs to adipocytes could offer new perspectives for the treatment of obesity and related metabolic diseases.

Indexed as

adipogenesisautomated quantitative image analysislipid nanoparticlesmicroRNA

Identifiers

PMID37514169
PMCPMC10384627
OpenAlexW4384821674

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.