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Record W2097584742 · doi:10.1177/2041731413492741

Cellular distribution and gene expression profile during flexor tendon graft repair: A novel tissue engineering approach <sup>*</sup>

2013· article· en· W2097584742 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

VenueJournal of Tissue Engineering · 2013
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsTendonScarsTissue engineeringMedicineAdhesionScar tissueFlexor Digitorum LongusAnatomySurgeryPathologyChemistryBiomedical engineering

Abstract

fetched live from OpenAlex

To understand scar and adhesion formation during postsurgical period of intrasynovial tendon graft healing, a murine model of flexor digitorum longus tendon graft repair was developed, by utilizing flexor digitorum longus tendon allograft from donor Rosa26/+ mouse, and the healing process at days 3, 7, 14, 21, 28, and 35 post surgery of host wild-type mouse was followed. Using X-gal staining, β-galactosidase positive cells of allograft origin were detectable in tissue sections of grafted tendon post surgery. Graft healing was assessed for the cellular density, scar and adhesion formation, and their interaction with surrounding tissue. From histological analysis, it was evident that the healing of intrasynovial flexor digitorum longus tendon graft takes place in an interactive environment of donor graft, host tendon, and host surrounding tissue. A total of 32 genes, analyzed by RNA analysis, expressed during healing process. Particularly, Alk1, Postn, Tnc, Tppp3, and Mkx will be further investigated for therapeutical value in reducing scars and adhesions.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.984

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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