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Record W3095884171 · doi:10.1002/adbi.202000094

Effects of Oxygen and Glucose on Bone Marrow Mesenchymal Stem Cell Culture

2020· article· en· W3095884171 on OpenAlexafffund
Fiona Lau, Benjamin Dalisson, Yu Ling Zhang, Jing Zhao, Nicoletta Eliopoulos, Jake E. Barralet

Bibliographic record

VenueAdvanced Biosystems · 2020
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsJewish General HospitalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMesenchymal stem cellViability assayAndrologyAnoxic watersAdipogenesisBiologyStem cellErythropoietinDoubling timeChemistryCellCell biologyBiochemistryEndocrinologyMedicine

Abstract

fetched live from OpenAlex

This study determines whether the viability of mesenchymal stem cell (MSC) in vitro is most sensitive to oxygen supply, energetic substrate supply, or accumulation of lactate. Mouse unmodified (wild type (WT)) and erythropoietin (EPO) gene-modified MSC is cultured for 7 days in normoxic (21%) and anoxic conditions. WT-MSC is cultured in anoxia for 45 days in high and regular glucose media and both have similar viability when compared to their normoxic controls at 7 days. Protein production of EPO-MSC is unaffected by the absence of oxygen. MSC doubling time and post-anoxic exposure is increased (WT: 32.3-73.3 h; EPO: 27.2-115 h). High glucose leads to a 37% increase in cell viability at 13 days and 17% at 30 days, indicating that MSC anoxic survival is affected by supply of metabolic substrate. However, after 30 days, little difference in viability is found, and at 45 days, complete cell death occurs in both the conditions. This death cannot be attributed to lack of glucose or lactate levels. MSC stemness is retained for both osteogenic and adipogenic differentiations. The absence of oxygen increases the doubling time of MSC but does not affect their viability, protein production, or differentiation capacity.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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