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Record W1149724364 · doi:10.1089/ten.tec.2013.0147

Novel and Simple Alternative to Create Nanofibrillar Matrices of Interest for Tissue Engineering

2013· article· en· W1149724364 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 C Methods · 2013
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsNanofiberExtracellular matrixRegenerative medicineMaterials scienceNanometrePorosityMatrix (chemical analysis)PolymerNanotechnologyTissue engineeringMesenchymal stem cellNatural polymersBiomedical engineeringComposite materialChemistryStem cellEngineeringBiology

Abstract

fetched live from OpenAlex

Synthetic analogs to natural extracellular matrix (ECM) at the nanometer level are of great potential for regenerative medicine. This study introduces a novel and simple method to produce polymer nanofibers and evaluates the properties of the resulting structures, as well as their suitability to support cells and their potential interest for bone and vascular applications. The devised approach diffracts a polymer solution by means of a spraying apparatus and of an airstream as sole driving force. The resulting nanofibers were produced in an effective fashion and a factorial design allowed isolating the processing parameters that control nanofiber size and distribution. The nanofibrillar matrices revealed to be of very high porosity and were effectively colonized by human bone marrow mesenchymal cells, while allowing ECM production and osteoblastic differentiation. In vivo, the matrices provided support for new bone formation and provided a good patency as small diameter vessel grafts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.098
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.353
Teacher spread0.311 · 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