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Record W4323349615 · doi:10.1186/s13287-023-03250-6

Long non-coding RNA H19 regulates matrisome signature and impacts cell behavior on MSC-engineered extracellular matrices

2023· article· en· W4323349615 on OpenAlexfundno aff
Sara Reis Moura, Jaime Freitas, Cláudia Ribeiro-Machado, Jorge Lopes, Nuno Nevès, Helena Canhão, Ana Maria Rodrigues, Mário A. Barbosa, Maria Inês Almeida

Bibliographic record

VenueStem Cell Research & Therapy · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsnot available
FundersCentre hospitalier universitaire Sainte-Justine
KeywordsDecellularizationExtracellular matrixMesenchymal stem cellCell biologyStromal cellCollagen VIAdipogenesisRegenerative medicineBiologyChemistryStem cellCancer research

Abstract

fetched live from OpenAlex

BACKGROUND: The vast and promising class of long non-coding RNAs (lncRNAs) has been under investigation for distinct therapeutic applications. Nevertheless, their role as molecular drivers of bone regeneration remains poorly studied. The lncRNA H19 mediates osteogenic differentiation of Mesenchymal Stem/Stromal Cells (MSCs) through the control of intracellular pathways. However, the effect of H19 on the extracellular matrix (ECM) components is still largely unknown. This research study was designed to decode the H19-mediated ECM regulatory network, and to reveal how the decellularized siH19-engineered matrices influence MSC proliferation and fate. This is particularly relevant for diseases in which the ECM regulation and remodeling processes are disrupted, such as osteoporosis. METHODS: Mass spectrometry-based quantitative proteomics analysis was used to identify ECM components, after oligonucleotides delivery to osteoporosis-derived hMSCs. Moreover, qRT-PCR, immunofluorescence and proliferation, differentiation and apoptosis assays were performed. Engineered matrices were decellularized, characterized by atomic force microscopy and repopulated with hMSC and pre-adipocytes. Clinical bone samples were characterized by histomorphometry analysis. RESULTS: Our study provides an in-depth proteome-wide and matrisome-specific analysis of the ECM proteins controlled by the lncRNA H19. Using bone marrow-isolated MSC from patients with osteoporosis, we identified fibrillin-1 (FBN1), vitronectin (VTN) and collagen triple helix repeat containing 1 (CTHRC1), among others, as having different pattern levels following H19 silencing. Decellularized siH19-engineered matrices are less dense and have a decreased collagen content compared with control matrices. Repopulation with naïve MSCs promotes a shift towards the adipogenic lineage in detriment of the osteogenic lineage and inhibits proliferation. In pre-adipocytes, these siH19-matrices enhance lipid droplets formation. Mechanistically, H19 is targeted by miR-29c, whose expression is decreased in osteoporotic bone clinical samples. Accordingly, miR-29c impacts MSC proliferation and collagen production, but does not influence ALP staining or mineralization, revealing that H19 silencing and miR-29c mimics have complementary but not overlapping functions. CONCLUSION: Our data suggest H19 as a therapeutic target to engineer the bone ECM and to control cell behavior.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.316
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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