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Record W2012889860 · doi:10.1002/masy.200900149

Application of Chitosan‐Based Biomaterials for Blood Vessel Regeneration

2010· article· en· W2012889860 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

VenueMacromolecular Symposia · 2010
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsChitosanExtracellular matrixTissue engineeringBiocompatibilityRegeneration (biology)AngiogenesisGlucosamineRegenerative medicineBiomedical engineeringChemistryMedicineBiologyCellCell biologyCancer researchBiochemistry

Abstract

fetched live from OpenAlex

Abstract Summary: Vascular diseases are the leading cause of morbidity and mortality in the western world. Autologous vessels remain the standard for coronary grafting and peripheral bypass surgery; however, their availability in patients can be limited. Therapeutic angiogenesis using growth factors, genes, or progenitor cells has been given considerable scientific attention over the last decade, but has not yet provided a definitive clinical benefit. Biomaterials could be developed to protect protein, DNA and cells against hostile conditions. Chitosan, a natural polymer of glucosamine and N‐acetyl glucosamine, has been widely studied in tissue engineering due to its biocompatibility, biodegradability, and muco‐adhesive and antimicrobial properties. Notably, the application of chitosan has been gaining attention in the vascular field due to its structural similarity to glycosaminoglycans, which are components of a tissue's extracellular matrix. In this review, chitosan‐based materials, and their use in tissue engineered blood vessels, and as protein, gene and cell vectors for angiogenic therapy are discussed.

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 score0.248
Threshold uncertainty score0.630

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 studies0.0000.000
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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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