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Record W4281802716 · doi:10.3390/materproc2022008048

Gastroretentive Electrospun Nanofibers Used in Gastric Wall Wound Healing

2022· article· en· W4281802716 on OpenAlexaboutno aff
Sara F. C. Guerreiro, A.G. Dias, Pedro L. Granja, Juliana R. Dias

Bibliographic record

VenueMATERIAIS 2022 · 2022
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCancerMedicineDownloadInternal medicineLibrary scienceWorld Wide WebComputer science

Abstract

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first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessAbstract Gastroretentive Electrospun Nanofibers Used in Gastric Wall Wound Healing † by Sara F. C. Guerreiro 1,2,3,*, Anabela G. Dias 2, Pedro L. Granja 3 and Juliana R. Dias 1 1 Centre for Rapid and Sustainable Product Development, Polytechnic Institute of Leiria, 2430-028 Marinha Grande, Portugal 2 Medical Physics Department, Portuguese Institute of Oncology (IPO-Porto), 4200-072 Porto, Portugal 3 Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal * Author to whom correspondence should be addressed. † Presented at the Materiais 2022, Marinha Grande, Portugal, 10–13 April 2022. Mater. Proc. 2022, 8(1), 48; https://doi.org/10.3390/materproc2022008048 Published: 27 May 2022 (This article belongs to the Proceedings of MATERIAIS 2022) Download Download PDF Download XML Download Epub Versions Notes Gastric cancer is the third leading cause of death by cancer worldwide [1]. Among all the stomach cancer types, 90% correspond to gastric adenocarcinoma. In most of these epithelial tumors, a close association to Helicobacter pylori infection has been found [2]. Consequently, most of the associated therapies, namely, surgery for tumor resection and antibiotic therapy for the eradication of bacteria, usually result in the pathological healing of gastric tissues and long recovery times. This inevitably led to a significant hospitalization stay, postoperative changes in biomechanical properties of the gastric wall and difficulties in bacteria eradication [3].Hence, the demand for innovative solutions led to the development of tissue-engineered electrospun nanofibers (eNFs) as gastric wall substitutes capable of promoting the healing of the gastric wall. In fact, eNFs with a thickness of up to 1mm provide support for cell proliferation, as well as a high surface area for the efficient delivery of proteins or antibiotic agents.Electrospinning, being a versatile and low-cost technique, was used here to obtain an interconnected network of eNFs, composed of blended polycaprolactone (PCL)/gelatin, and crosslinked polyvinyl alcohol (PVA)/chitosan using 1,4-butanediol diglycidyl ether (BDDGE) as the crosslinking agent [4,5,6]. Hybrid eNF performance was evaluated regarding biodegradation, mucoadhesion, mechanical properties and as a drug delivery system. Considering the peristaltic movements of the stomach during the digestive process, PCL allowed to increase the tensile strength and elasticity of the whole hybrid structure. Additionally, to simulate the protein release-controlled delivery of therapeutic agents through the PCL/gelatin eNFs, protein bovine serum albumin (BSA) was successfully released with an efficiency of over 60% during the first 24 h. The inclusion of PVA/chitosan eNFs also increased the mucoadhesive properties of the membrane. Finally, the degradation profile of eNFs proved to be compatible for long-term applications (over one month). Overall, hybrid eNFs demonstrated biodegradability and a mucoadhesive capacity, as well as promising mechanical characteristics and suitable antibiotic delivery properties to work as gastric wall substitutes. Author ContributionsConceptualization, S.F.C.G., A.G.D., P.L.G. and J.R.D.; methodology, S.F.C.G., A.G.D., P.L.G. and J.R.D.; validation, S.F.C.G., A.G.D., P.L.G. and J.R.D.; formal analysis, S.F.C.G., A.G.D., P.L.G. and J.R.D.; investigation, S.F.C.G., A.G.D., P.L.G. and J.R.D.; resources, S.F.C.G., A.G.D., P.L.G. and J.R.D.; data curation, S.F.C.G., A.G.D., P.L.G. and J.R.D.; writing—original draft preparation, S.F.C.G.; writing—review and editing, A.G.D., P.L.G. and J.R.D.; visualization, S.F.C.G., A.G.D., P.L.G. and J.R.D.; supervision, A.G.D., P.L.G. and J.R.D.; project administration, A.G.D., P.L.G. and J.R.D.; funding acquisition, A.G.D., P.L.G. and J.R.D. All authors have read and agreed to the published version of the manuscript.FundingThis research was funded by Fundação para a Ciência e Tecnologia (FCT) grant number 2021.05893.BD, UIDB/04044/2020 and UIDP/04044/2020. This study was also supported by PAMI-ROTEIRO/0328/2013 (Nº 022158), MATIS (CENTRO-01-0145-FEDER-000014-3362).Institutional Review Board StatementNot applicable.Informed Consent StatementNot applicable.Data Availability StatementNot applicable.Conflicts of InterestThe authors declare no conflict of interest.ReferencesRawla, P.; Barsouk, A. Epidemiology of gastric cancer: Global trends, risk factors and prevention. Gastroenterology Rev. 2019, 14, 26–38. [Google Scholar] [CrossRef] [PubMed]Alipour, M. Molecular Mechanism of Helicobacter pylori-Induced Gastric Cancer. J. Gastrointest. Cancer 2021, 52, 23–30. [Google Scholar] [CrossRef] [PubMed]Ajani, J.A.; Lee, J.; Sano, T.; Janjigian, Y.Y.; Fan, D.; Song, S. Gastric adenocarcinoma. Nat. Rev. Dis. Primers 2017, 3, 1–19. [Google Scholar] [CrossRef] [PubMed]Guerreiro, S.F.C.; Valente, J.F.A.; Dias, J.R.; Alves, N. Box-Behnken Design a Key Tool to Achieve Optimized PCL/Gelatin Electrospun Mesh. Macromol. Mater. Eng. 2021, 306, 2000678. [Google Scholar] [CrossRef]Juliana, D.; Pedro, G.; Paulo, B. Internal crosslinking evaluation of gelatin electrospinning fibers with 1,4 butanediol Diglycidyl ether (Bddge) for skin regeneration. In Proceedings of the 10th World Biomaterials Congress, Montréal, Canada, May 17–22 2016; Frontiers in Bioengineering and Biotechnology: Lausanne, Switzerland, 2016. [Google Scholar] [CrossRef]Dias, J.R.; dos Santos, C.; Horta, J.; Granja, P.L.; Bártolo, P.J. A new design of an electrospinning apparatus for tissue engineering applications. Int. J. Bioprinting 2017, 3, 121–129. [Google Scholar] [CrossRef] [PubMed]Publisher's Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style Guerreiro, S.F.C.; Dias, A.G.; Granja, P.L.; Dias, J.R. Gastroretentive Electrospun Nanofibers Used in Gastric Wall Wound Healing. Mater. Proc. 2022, 8, 48. https://doi.org/10.3390/materproc2022008048 AMA Style Guerreiro SFC, Dias AG, Granja PL, Dias JR. Gastroretentive Electrospun Nanofibers Used in Gastric Wall Wound Healing. Materials Proceedings. 2022; 8(1):48. https://doi.org/10.3390/materproc2022008048 Chicago/Turabian Style Guerreiro, Sara F. C., Anabela G. Dias, Pedro L. Granja, and Juliana R. Dias. 2022. "Gastroretentive Electrospun Nanofibers Used in Gastric Wall Wound Healing" Materials Proceedings 8, no. 1: 48. https://doi.org/10.3390/materproc2022008048 Find Other Styles Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here. Article Metrics No No Article Access Statistics Multiple requests from the same IP address are counted as one view.

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 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 score0.005
Threshold uncertainty score0.015

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)0.0050.001

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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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