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Record W1591825399 · doi:10.1002/cbin.10394

Geniposide protects pancreatic INS‐1E β cells from hIAPP‐induced cell damage: Potential involvement of insulin degrading‐enzyme

2014· article· en· W1591825399 on OpenAlexaff
Yonglan Zhang, Fei Yin, Jianhui Liu, Yanwen Wang

Bibliographic record

VenueCell Biology International · 2014
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAmylinIsletCytotoxicityAmyloid (mycology)ChemistryInsulin-degrading enzymeDownregulation and upregulationInsulinEnzymePancreatic isletsPeptideCellBiochemistryCell biologyEndocrinologyIn vitroBiology

Abstract

fetched live from OpenAlex

Islet amyloid deposition is increasingly seen as a pathogenic feature of type 2 diabetes mellitus (T2DM), with the deposits containing the unique amyloidogenic peptide islet amyloid polypeptide (IAPP, also known as amylin). The fibril precursors of IAPP contribute to its cytotoxicity on pancreatic β cells and be important in causing β-cell dysfunction in T2DM. However, the development of effective this study, inhibitors against the toxicity of IAPP has been extremely challenging. We have found that pre-incubation with geniposide dose-dependently prevented human IAPP (hIAPP)-induced cell damage in INS-1E cells, and bacitracin, an inhibitor of IDE activity, prevented significantly the protective effects of geniposide in pancreatic INS-1E cells significantly. Geniposide induced the expression of insulin-degrading enzyme (IDE), a key degrading protein of hIAPP, but had no significant effect on the aggregation of hIAPP. These findings indicate that geniposide prevents hIAPP-induced cytotoxicity in INS-1E cells involving upregulation of IDE expression.

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 integrity0.0000.001
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 head0.021
GPT teacher head0.276
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".

Quick stats

Citations10
Published2014
Admission routes1
Has abstractyes

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