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Record W2768408662 · doi:10.1016/j.jacbts.2017.07.014

Aged Human Multipotent Mesenchymal Stromal Cells Can Be Rejuvenated by Neuron-Derived Neurotrophic Factor and Improve Heart Function After Injury

2017· article· en· W2768408662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACC Basic to Translational Science · 2017
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMesenchymal stem cellNeurotrophic factorsMedicineStromal cellStem cellRegeneration (biology)Stem-cell therapySenescenceCancer researchCell biologyImmunologyPathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Reduced regenerative capacity of aged stem cells hampers the benefits of autologous cell therapy for cardiac regeneration. This study investigated whether neuron-derived neurotrophic factor (NDNF) could rejuvenate aged human bone marrow (hBM)- multipotent mesenchymal stromal cells (MSCs) and whether the rejuvenated hBM-MSCs could improve cardiac repair after ischemic injury. Over-expression of NDNF in old hBM-MSCs decreased cell senescence and apoptosis. Engraftment of NDNF over-expressing old hBM-MSCs into the ischemic area of mouse hearts resulted in improved cardiac function after myocardial infarction, while promoting implanted stem cell survival. Our findings suggest NDNF could be a new factor to rejuvenate aged stem cells and improve their capability to repair the aged heart after injury.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.274
Teacher spread0.258 · 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