Evidence map›Paper›PMID 40100054›Full record

ArticleAnnals of medicine2025

Exploring NamiRNA networks and time-series gene expression in osteogenic differentiation of adipose-derived stem cells.

Xin Jin, Yi Lu, Zhihong Fan

Abstract read
In one paragraph

Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Xin JinDepartment of Plastic Surgery, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0002-7840-9143
Yi LuDepartment of Plastic Surgery, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Zhihong FanDepartment of Plastic Surgery, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0009-0000-2042-9873

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdipose-derived stem cells (ADSCs) are a type of stem cell found in adipose tissue with the capacity to differentiate into multiple lineages, including osteoblasts. The differentiation of ADSCs into osteoblasts underlies osteogenic and pathological cellular basis in osteoporosis, bone damage and repair.

methodsFocused on ADSCs osteogenic differentiation, we conducted mRNA, microRNA expression and bioinformatics analysis, including gene differential expression, time series-based trend analysis, functional enrichment, and generates potential nuclear activating miRNAs (NamiRNA) regulatory network. The screened mRNAs in NamiRNA regulatory network were validated with correlation analysis.

resultsThe NamiRNA Regulatory Network reveals 4 mRNAs (C12orf61, MIR31HG, NFE2L1, and PCYOX1L) significantly downregulated in differentiated group and may be associated with ADSCs stemness. Furthermore, the significantly upregulated 10 genes (ACTA2, TAGLN, LY6E, IFITM3, NGFRAP1, TCEAL4, ATP5C1, CAV1, RPSA, and KDELR3) were significantly enriched in osteogenic-related pathways, and negatively correlated with ADSCs cell stemness

conclusionThese findings uncover potential genes related to ADSCs osteogenic differentiation, and provide theoretical basis for underlying ADSCs osteogenic differentiation and related diseases.

Indexed as

Adipose TissueMicroRNAsOsteogenesisStem CellsCell DifferentiationCells, CulturedComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansOsteoblastsRNA, MessengerMicroRNAsRNA, MessengerAdipose-derived stem cellsgenesNamiRNAosteogenic differentiationstemness

Identifiers

PMID40100054
PMCPMC11921168

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.