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209.1: Co-localized Immune Protection Using Cyclosporine A Eluting Micelles in a Murine Islet Allograft Model

2021· article· en· W3217661049 on OpenAlexaff
Purushothaman Kuppan, Sandra Kelly, Kateryna Polishevska, Karen Seeberger, Mandy Rosko, Gregory S. Korbutt, Andrew R. Pepper

Bibliographic record

VenueTransplantation · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImmunosuppressionIsletMicellePLGATransplantationImmune systemPharmacologyChemistryDrug deliveryTransplant rejectionMedicineDiabetes mellitusImmunologyInternal medicineEndocrinologyBiochemistry

Abstract

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Dr. Pepper and Dr. Korbutt. Introduction: Islet transplantation is a promising therapeutic strategy to restore physiologic glycemic control to patients with type 1 diabetes. However, factors such as chronic auto- and allo-immune responses and also, the diabetogenic effects of systemic immunosuppression contribute to long-term islet graft failure. Herein, we explore the utility of localized islet graft drug delivery to modulate the inflammatory and adaptive immune responses. Poly(lactic-co-glycolic acid) (PLGA)is an attractive biomaterial, which has widely been used to make drug delivery vehicles. Cyclosporine A (CsA) is a potent immunosuppressant, which is clinically used in the prevention of transplant rejection. Therefore, our aim is to encapsulate CsA in PLGA micelles as a means to deliver localized immunosuppression at the transplant site to improve the islet allograft function. Method: PLGA and CsA solution mixtures were emulsified using polyvinyl alcohol (PVA) and stirred for an hour to evaporate the organic solvent which allows the micelles particles to harden. Micelles were collected and freeze dried. Encapsulation efficiency and drug release kinetics were analyzed using high-performance liquid chromatography (HPLC). Further, the cytoprotective capacity of the CsA loaded micelles were tested in a syngeneic transplant study (500 BALB/c islets transplanted into the diabetic BALB/c mice) (n=3). Subsequently, a series of allogeneic mouse islet transplants were conducted by co-delivering BALB/c islets (500 islets) with either 4 mg (10 mg/kg of CsA) CsA micelles (n=7) or empty micelles (n=8) under the kidney capsule of diabetic C57BL/6 mice. In addition, CsA +/- micelles groups were administered with CTLA4-Ig (10 mg/kg) intraperitoneally on days 0, 2, 4, and 6 posttransplant. After transplantation, recipient’s blood glucose was monitored 3 times per week. Allograft rejection was defined as two consecutive readings ≥18.0 mmol/L. Results: All recipients from the syngeneic + CsA micelles group became euglycemic and demonstrated robust glucose clearance in response to a metabolic challenge; confirming that localized CsA micelles are non-toxic. Recipients of CsA micelles, had significantly delayed islet allograft rejection as a monotherapy compared to islets alone (p<0.05). Furthermore, 54% (6 out of 11) of CsA micelle recipients showed long-term (>214 days) allograft survival when combined with CTLA4-Ig therapy, compared to 25% (2 out of 8) of CTLA4-Ig alone (p=0.13). An intraperitoneal glucose tolerance test (IPGTT) at 100 days posttransplant demonstrated that the recipient’s of both CSA+CTLA4-Ig and CTLA4-Ig alone groups had a comparable glucose tolerance (p> 0.05,). Conclusion: Our study demonstrates that localized CsA drug delivery via micelles elution provides a feasible therapeutic platform to locally deliver immunomodulatory drugs in a controlled and favorable manner, thereby promoting a protective transplant niche for both syngeneic and allogeneic islets.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.291
Teacher spread0.256 · 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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Citations2
Published2021
Admission routes1
Has abstractyes

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