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Record W2992936829 · doi:10.1016/j.actbio.2019.11.047

Glycaemic control in diabetic rats treated with islet transplantation using plasma combined with hydroxypropylmethyl cellulose hydrogel

2019· article· en· W2992936829 on OpenAlexfundno aff
Anaïs Schaschkow, S. Sigrist, Carole Mura, Julien Barthès, Nihal Engin Vrana, Elodie Czuba, Florent Lemaire, Romain Neidl, C. Dissaux, Anne Lejay, Philippe Lavall�e, Catherine Bruant‐Rodier, Karim Bouzakri, M. Pinget, Élisa Maillard

Bibliographic record

VenueActa Biomaterialia · 2019
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersConseil Régional d'AlsaceQuébec Consortium for Drug Discovery
KeywordsIsletMaterials scienceCelluloseTransplantationPlasma glucoseDiabetes mellitusBiomedical engineeringInternal medicineMedicineEndocrinologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

Islet transplantation is one of the most efficient cell therapies used in clinics and could treat a large proportion of patients with diabetes. However, it is limited by the high requirement of pancreas necessary to provide the sufficient surviving islet mass in the hepatic tissue and restore normoglycaemia. Reduction in organ procurement requirements could be achieved by extrahepatic transplantation using a biomaterial that enhances islet survival and function. We report a plasma-supplemented hydroxypropyl methylcellulose (HPMC) hydrogel, engineered specifically using a newly developed technique for intra-omental islet infusion, known as hOMING (h-Omental Matrix Islet filliNG). The HPMC hydrogel delivered islets with better performance than that of the classical intrahepatic infusion. After the validation of the HPMC suitability for islets in vivo and in vitro, plasma supplementation modified the rheological properties of HPMC without affecting its applicability with hOMING. The biomaterial association was proven to be more efficient both in vitro and in vivo, with better islet viability and function than that of the current clinical intrahepatic delivery technique. Indeed, when the islet mass was decreased by 25% or 35%, glycaemia control was observed in the group of plasma-supplemented hydrogels, whereas no regulation was observed in the hepatic group. Plasma gelation, observed immediately post infusion, decreased anoïkis and promoted vascularisation. To conclude, the threshold mass for islet transplantation could be decreased using HPMC-Plasma combined with the hOMING technique. The simplicity of the hOMING technique and the already validated use of its components could facilitate its transfer to clinics. STATEMENT OF SIGNIFICANCE: One of the major limitations for the broad deployment of current cell therapy for brittle type 1 diabetes is the islets' destruction during the transplantation process. Retrieved from their natural environment, the islets are grafted into a foreign tissue, which triggers massive cell loss. It is mandatory to provide the islets with an 3D environment specifically designed for promoting isletimplantation to improve cell therapy outcomes. For this aim, we combined HPMC and plasma. HPMC provides suitable rheological properties to the plasma to be injectable and be maintained in the omentum. Afterwards, the plasma polymerises around the graft in vivo, thereby allowing their optimal integration into their transplantation site. As a result, the islet mass required to obtain glycaemic control was reduced by 35%.

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)0.000
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 score0.067
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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

Citations22
Published2019
Admission routes1
Has abstractyes

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