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Record W2031297275 · doi:10.1002/jemt.10114

Response of donor and recipient cells after transplantation of cells to the ligament and tendon

2002· review· en· W2031297275 on OpenAlexaff
Kevin A. Hildebrand, Fengyan Jia, Savio L‐Y. Woo

Bibliographic record

VenueMicroscopy Research and Technique · 2002
Typereview
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMesenchymal stem cellTendonTransplantationLigamentWound healingStem cellGene transferTissue engineeringGenetic enhancementCell biologyMedicineAnatomyPathologyBiologyGeneBiomedical engineeringSurgery

Abstract

fetched live from OpenAlex

The mechanical properties of healing ligaments and tendons are not comparable to those of normal tissue. To improve the quality of the ligament healing, therapeutic strategies include gene transfer or placement of mesenchymal stem cells at the healing site. Studies show that marker genes, growth factors, and antisense oligonucleotides can be delivered to both normal and healing ligaments and tendons by gene transfer. Cells with and without genetic modification have been successfully transplanted to ligaments and tendons and remain viable. Tendon healing can be improved using collagen gel implants seeded with autologous mesenchymal stem cells. Even though these early results are encouraging, more work is required regarding the response of the recipient site to donor cells or vectors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.400
Teacher spread0.349 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations46
Published2002
Admission routes1
Has abstractyes

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