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Record W4415269545 · doi:10.1016/j.omtm.2025.101616

Preconditioning with StemRegenin 1 enhances human adipose stromal/stem cells proliferation, migration, and protection against antimycin A

2025· article· en· W4415269545 on OpenAlexafffund
Jing Zhao, Bin Yu, Julie Fradette, Borhane Annabi, Maria Petropavlovskaia, Nicoletta Eliopoulos

Bibliographic record

VenueMolecular Therapy — Methods & Clinical Development · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsMcGill UniversityUniversité du Québec à MontréalUniversité LavalJewish General Hospital
FundersKidney Foundation of CanadaCanadian Institutes of Health ResearchCancer Research Society
KeywordsParacrine signallingAntimycin AAdipose tissueCellDegeneration (medical)Oxidative stressHaematopoiesisCell therapyRegeneration (biology)

Abstract

fetched live from OpenAlex

hematopoietic stem/progenitor cell expansion. We pretreated hASCs with SR1 and analyzed the resulting cells (SR1-hASCs) as compared to non-treated cells (NT-hASCs). We noted that treatment with SR1 significantly increased the proliferation and migration of hASCs, as well as their secretion of paracrine factors of interest, and did not affect their cell differentiation capacity. Furthermore, when these SR1-hASCs were subsequently exposed to antimycin A, a mitochondrial respiratory chain inhibitor, they showed significantly higher antioxidative, anti-apoptotic, and pro-survival abilities as compared to NT-hASCs. Since oxidative stress and other harsh environments result from tissue damage, our results support that the preconditioning of hASCs with SR1 may enhance their protective, reparative, and regenerative, and thus therapeutic, efficacy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.506
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.395
Teacher spread0.343 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes2
Has abstractyes

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