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Record W4290188687

Design of graphene-like boron nitride/gelatin electro spun nanofibers as new bio nanocomposite material for tissue engineering

2016· article· en· W4290188687 on OpenAlexaboutno aff
Sakthivel Nagarajan, Mikhaël Bechelany

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGelatinBoron nitrideMaterials scienceElectrospinningNanofiberGrapheneNanocompositeGraphiteChemical engineeringDispersion (optics)NanotechnologyComposite materialPolymerChemistryOrganic chemistry
DOInot available

Abstract

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Event Abstract Back to Event Design of graphene-like boron nitride/gelatin electro spun nanofibers as new bio nanocomposite material for tissue engineering Sakthivel Nagarajan1, 2, Céline Pochat-Bohatier1, Sébastien Balme1, Philippe Miele1, Narayana Kalkura2 and Mikhael Bechelany1 1 Université Montpellier, Institut Européen des Membranes, UMR 5635 CNRS ENSCM, France 2 Anna University, Crystal Growth Centre, India Introduction: Improving the mechanical properties of biopolymers is very essential towards the fabrication of efficient nontoxic material for biomedical applications. To this aim, a novel mechanically stable graphene -like boron nitride (GBN) inorganic filler is introduced[1]. Boron nitride (h-BN) is isoelectric analogue of graphite and exfoliated h-BN (GBN), exhibits very high mechanical properties. Hence the h-BN is exfoliated using the lewis acid base interaction of h-BN and gelatin. GBN/gelatin is used for the fabrication of electrospun mats (ESM) through electrospinning technique. The effect of biomineralization and the toxicity of the ESM with GBN concentration are analyzed. Materials and Methods: Various concentration of h-BN (0.1, 1, 5 % (w/v)) were prepared using 20% of gelatin solution and sonicated for one hour. The solution is centrifuged at 500 rpm for 30 minutes to obtain the stable dispersion of gelatin/GBN in the supernatant. The ESM were fabricated using the stable dispersion of GBN/gelatin using an electrospinning system[2]. Fibers prepared using 20% gelatin were denoted as G and using various h-BN weight fraction, such as 0.1, 1 and 5% were referred as 0.1G, 1G 5G respectively. The electrospun mats were further cross-linked with 1% glutaradehyde, neutralized with 10% glycine solution and denoted as GC, 0.1GC, 1GC, 5GC. Results and Discussion: The X-ray diffraction patterns of ESM (figure 1c) shows 2 peaks at 2Ө= 26.6° and 55◦ corresponds to (002) and (004) planes of h-BN respectively. The peaks observed at 2Ө= 41.49°, 43.72° and 50◦ that corresponds to (100), (101) and (102) planes of h-BN respectively, disappears evidences of the efficient exfoliation of h-BN in ESM[3]. The Fourier transform infrared of ESM are showed in (figure (1(a,b)). Characteristic peaks of amide I, II and III demonstrates the presence of gelatin chains. The shift in the symmetric stretching of carboxylates from 1406 to 1385cm-1 in 1G, 5G and broadening of carboxylate symmetry stretching in 0.1G, 1G, and 5G respectively, depicts that carboxylates have strong interaction with the graphene like boron nitride nano-sheets and this interaction facilitates the exfoliation of BN[4]. The tensile strength studies of cross linked ESM shows, the uniform reinforcement of Gelatin by the exfoliated GBN and hence the improvement of the young’s modulus from 612 MPa to 1305 MPa. Beyond the optimal concentration of h-BN, GBN causes imperfect reinforcement and leads to sudden decrease to 218 MPa of young’s modulus. The biomineralization in simulated body fluids (figure 2 (a-d)) evidences the formation of bone like apatite with the increasing of the GBN concentration. The cell viability and alkaline phosphatase activity to Human HOS osteosarcoma cell lines evidences that addition of h-BN and the exfoliation into GBN does not affect the biocompatibility of gelatin. Conclusion: The h-BN is exfoliated into GBN using gelatin. GBN reinforced ESM were fabricated by electrospinning technique. The optimal concentration of GBN in ESM enhanced the mechanical properties and bone like apatite forming ability of the bionanocomposites. The ESM is nontoxic to osteoblast cell lines and possess alkaline phosphatase activity. Hence the ESM are highly suitable new class of bionanomaterial for orthopaedic application. S.N. acknowledges the financial support from Svagata-Erasmus mundus program.; The authors are thankful to Dr. Rajaram, central Leather Research Institute (CLRI), Chennai, India; N. Masquelez for valuable suggestions to DSC results.; The human HOS osteosarcoma cell line was kindly donated by Dr. Maurel, Institute of Functional Genomics (IGF), Montpellier, France.; The authors would like to acknowledge the “Institut Européen des Membranes (IEM)- UMR CNRS 5635” which supports this study through the project NewBone/Axe-health/2015”.; Dr.Vincent Cavaillès and Catherine Teyssier IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Université Montpellier, Montpellier F-34298, France for the valuable discussion.References:[1] Lee C, Wei X, Kysar JW, Hone J. Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene. Science. 2008;321(5887):385-8.[2] Chaaya, A. A.; Bechelany, M.; Balme, S.; Miele, P. ZnO 1D nanostructures designed by combining atomic layer deposition and electrospinning for UV sensor applications. Journal of Materials Chemistry A 2014, 2, 20650-20658.[3] Biscarat J, Bechelany M, Pochat-Bohatier C, Miele P. Graphene-like BN/gelatin nanobiocomposites for gas barrier applications. Nanoscale. 2015;7(2):613-8.[4] Chang M, Ikoma T, Kikuchi M, Tanaka J. Preparation of a porous hydroxyapatite/collagen nanocomposite using glutaraldehyde as a crosslinkage agent. Journal of Materials Science Letters. 2001;20(13):1199-201 Keywords: Bioactivity, Biocompatibility, Calcium phosphate, biomedical application Conference: 10th World Biomaterials Congress, Montréal, Canada, 17 May - 22 May, 2016. Presentation Type: Poster Topic: Electrospinning and related technologies Citation: Nagarajan S, Pochat-Bohatier C, Balme S, Miele P, Kalkura N and Bechelany M (2016). Design of graphene-like boron nitride/gelatin electro spun nanofibers as new bio nanocomposite material for tissue engineering. Front. Bioeng. Biotechnol. Conference Abstract: 10th World Biomaterials Congress. doi: 10.3389/conf.FBIOE.2016.01.01127 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 27 Mar 2016; Published Online: 30 Mar 2016. Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Sakthivel Nagarajan Céline Pochat-Bohatier Sébastien Balme Philippe Miele Narayana Kalkura Mikhael Bechelany Google Sakthivel Nagarajan Céline Pochat-Bohatier Sébastien Balme Philippe Miele Narayana Kalkura Mikhael Bechelany Google Scholar Sakthivel Nagarajan Céline Pochat-Bohatier Sébastien Balme Philippe Miele Narayana Kalkura Mikhael Bechelany PubMed Sakthivel Nagarajan Céline Pochat-Bohatier Sébastien Balme Philippe Miele Narayana Kalkura Mikhael Bechelany Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

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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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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 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".

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