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Record W1752753008 · doi:10.25011/cim.v30i4.2870

Heparin induces amyloid formation in cultured human isletss

2007· article· en· W1752753008 on OpenAlexvenueno aff
Kathryn J. Potter, K Park

Bibliographic record

VenueClinical and investigative medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsIsletTransplantationHeparinAmyloid (mycology)MedicineImmune systemEndocrinologyInternal medicineInsulinDiabetes mellitusImmunologyPathology

Abstract

fetched live from OpenAlex

Background: Pancreatic islet transplantation offers improved glycemic control in type 1 diabetic patients above standard insulin therapy, ideally minimizing macro- and microvascular complications of diabetes mellitus. However success is limited thus far, with fewer than 10% of patients retaining insulin independence at two years post-transplantation. In addition to immune rejection, many non-immune factors may promote long-term graft secretory dysfunction and loss of viable graft mass. One such important non-immune factor may be the formation of islet amyloid, a pathologic lesion of the islet in type 2 diabetes that contributes to the progressive loss of b cells in that disease and that has been shown to form rapidly in human islets transplanted into NOD.scid mice. Amyloid deposits are composed primarily of the b cell secretory product islet amyloid polypeptide (IAPP), are cytotoxic, and develop in environments in which b cells are stressed. Heparin sulfate is used as an anti-coagulant in clinical islet transplantation and to prevent the instant blood-mediated inflammatory reaction (IBMIR), which occurs upon contact between islets and blood and may destroy a substantial proportion of the grafted islet mass. However, heparin is also known to stimulate amyloid fibril formation. Methods: To determine whether heparin may enhance amyloid formation in human islets and contribute to graft failure, we cultured isolated human islets in the presence or absence of heparin sulfate (42 and 420 units/ml) for 2 weeks in 11.1 mM glucose. Results: Histological assessment of sections of cultured islets for the presence of amyloid (by thioflavin S staining) revealed a marked, concentration-dependent increase in amyloid deposition following culture in the presence of heparin. Quantitative analysis of these sections showed that the proportion of islet area comprised of amyloid was increased approximately 2-fold (0.15%±0.12% vs 0.46%±0.15% of islet area) following culture in 42 units/ml heparin, and the proportion of islets in which amyloid was detectable (amyloid prevalence) was also increased (35%±24% vs 68%±10% of islets). At 420 units/ml heparin, the amyloid area was even greater (0.23%±0.15% vs 0.97%±0.42% of islet area) as was the amyloid prevalence (53%±29% vs 81%±14% of islets). To affirm that heparin can stimulate IAPP fibrillogenesis and enhance IAPP toxicity, we incubated synthetic human IAPP in the presence of heparin and measured amyloid formation in real time by thioflavin T fluorescence, and cell toxicity by Alamar blue viability assay in transformed rat (INS-1) ß-cell cultures. Heparin stimulated IAPP fibril formation and increased death of INS-1 cells exposed to IAPP (78.2%±10.9% vs 51.8%±12.2% of control viability), suggesting that heparin stimulates IAPP aggregation and toxicity. Remarkably, preliminary assessment of human islets cultured in heparin did not show increased islet cell death by TUNEL staining or loss of insulin immunostaining. Conclusion: In summary, heparin increases amyloid formation in cultured human islets. Although our preliminary data does not suggest that heparin-induced amyloid formation contributes to islet cell death, we speculate that heparin-induced amyloid formation may contribute to graft dysfunction and that caution should be used in the clinical application of this drug in islet transplantation.

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 score0.001
Threshold uncertainty score0.005

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 head0.189
GPT teacher head0.386
Teacher spread0.198 · 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".

Quick stats

Citations3
Published2007
Admission routes1
Has abstractyes

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