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Record W2570852937 · doi:10.1089/ten.teb.2016.0280

Design and Use of Chimeric Proteins Containing a Collagen-Binding Domain for Wound Healing and Bone Regeneration

2016· review· en· W2570852937 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

VenueTissue Engineering Part B Reviews · 2016
Typereview
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRegeneration (biology)Wound healingBiomaterialFusion proteinTissue engineeringCell biologyRecombinant DNAChemistryBiomedical engineeringMaterials scienceBiochemistryBiologyNanotechnologyImmunologyMedicine

Abstract

fetched live from OpenAlex

Collagen-based biomaterials are widely used in the field of tissue engineering; they can be loaded with biomolecules such as growth factors (GFs) to modulate the biological response of the host and thus improve its potential for regeneration. Recombinant chimeric GFs fused to a collagen-binding domain (CBD) have been reported to improve their bioavailability and the host response, especially when combined with an appropriate collagen-based biomaterial. This review first provides an extensive description of the various CBDs that have been fused to proteins, with a focus on the need for accurate characterization of their interaction with collagen. The second part of the review highlights the benefits of various CBD/GF fusion proteins that have been designed for wound healing and bone regeneration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.122
GPT teacher head0.351
Teacher spread0.230 · 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