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Record W2575387033

DESIGN, DEVELOPMENT AND VALIDATION OF A NEW COMPOSITE HYDROGEL FOR BONE TISSUE ENGINEERING

2017· article· en· W2575387033 on OpenAlexaboutno aff
Mathieu Maisani, Reine Bareille, L. Levesque, Joëlle Amédée, Diego Mantovani, Olivier Chassande

Bibliographic record

VenueJournal of Bone and Joint Surgery-british Volume · 2017
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsSelf-healing hydrogelsBiomedical engineeringTissue engineeringMaterials scienceMesenchymal stem cellBiomaterialRegeneration (biology)Regenerative medicineStem cellCell biologyNanotechnologyBiologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

First works focuses on the characterization (physical and biological) of this biomaterial. Current work had studied osteoinductive and osteoconductive capacity of these hydrogels. In vivo results highlight a significant bone reconstruction two months after implantations on bone lesions in mice. Bone is a dynamic and vascularized tissue that has the ability of naturally healing upon damage. Nevertheless, in the case of critical size defects this potential is impaired. Present approaches mainly consider autografts and allografts, which presents several limitations. Bone Tissue Engineering (BTE) is based on the use of 3D matrices to guide both cellular growth, differentiation to promote bone regeneration. Hence, matrices can contain biological materials such as cells and growth factors. Our project aims to design a hydrogel for BTE, particularly for bone lesion filling. We previously showed that a porous 3D hydrogel, Glycosyl-Nucleoside-Fluorinated (GNF) is: 1) non-cytotoxic to clustered human Adipose Mesenchymal Stem Cells (hASCs), 2) bioinjectable and 3) biodegradable. Therefore, this novel class of hydrogels show promise for the development of therapeutic solutions for BTE [1]. The hypothesis of this research was that improving the capacity to promote the adhesion of cells by adding collagen gel matrices and bone morphogenic protein 2 (BMP-2) to improve the bone regenerative potential of this gel. Collagen is a protein matrix well known for its cytocompatibility [2]. BMP-2, have been shown ability to induce bone formation in combination with an adequate matrix [3]. Thereby, the overall aim of this work was to design, develop and validate a new composite hydrogel for BTE. GNF was prepared as previously described in detail[1], at a concentration of 3% (w/v). Type I-collagen gel was prepared from rat-tail tendons at a concentration of 4 g/L [2]. hASCs were isolated from human adipose tissue in our laboratory. To establish a suitable microenvironment for cell proliferation and differentiation cells were seeded in collagen and then GNF gel was added and the resulting mixture was blended, BMP-2 (InductOs ® Kit) is added to this preparation (5µm BMP-2/ml). Fluorometry was used to follow BMP2 release in vitro and in vivo (NOG mices;n=6), orthotopic calvarium bone critical defect (3.3 mm) has been selected to challenge the bone repair. Adding collagen hydrogel improve cell adhesion, survivals and proliferation rather than simple GNF hydrogel. This novel gel composite has the ability to sustain hASCs adhesion and differentiation towards the osteoblastic lineage (positive ALP cells). Fluorometry showed the ability of our hydrogel to prolong the residence of BMP-2 ( in vitro and in vivo ) compared to collagen hydrogel sponges. Implantation of hydrogel containing hASC and BMP-2 has shown encouraging results in bone reconstruction: 2 months after implantation of biomaterials a significant bone reconstruction can be observed using X-Ray imaging. Adding collagen to GNF allowed to obtain gels showing satisfactory cell-behaviour. In parallel, the presence of GNF hydrogel helps to improve mechanical properties of the biomaterial (hydrogel stability and controlled release of BMP-2). The first in vivo studies have shown encouraging bone regeneration capacity of these hydrogels. The implantation performed on a larger number of animals and quantitative microCT analysis will enable us to judge the effectiveness of this hydrogel as a new injectable biomaterial for BTE. This work was partially supported by NSERC-Canada, FRQ-NT-Quebec, FRQ-S- Quebec, and CFI-Canada. Mathieu Maisani was awarded of a NSERC CREATE Program in Regenerative Medicine (www.ncprm.ulaval.ca) .

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.043
GPT teacher head0.272
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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Same venueJournal of Bone and Joint Surgery-british VolumeSame topicDental Implant Techniques and OutcomesFrench-language works237,207