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Record W4408498000 · doi:10.1080/19382014.2025.2479911

The effects of free fatty acid-free bovine serum albumin and palmitate on pancreatic β-cell function

2025· article· en· W4408498000 on OpenAlexafffund
Katherine Sentjens, Renjitha Pillai, Jamie W. Joseph

Bibliographic record

VenueIslets · 2025
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBovine serum albuminInternal medicineEndocrinologyFatty acidChemistryAlbuminPalmitic acidFree formBiochemistryBiologyMedicine

Abstract

fetched live from OpenAlex

Pancreatic β-cells release insulin in response to fluctuations in plasma glucose, amino acids, and free fatty acids (FFA). Clonal cell lines and isolated islets serve as essential early models for studying the impact of nutrients and evaluating potential therapies to address β-cell dysfunction. Acute and chronic changes in FFA levels have been shown to have positive and negative effects on β-cell function both in vivo and in vitro. A key problem in comparing islet lipid studies from different laboratories is that a wide variety of methods are used to isolate, culture, and assess islet function. The current study compares bovine serum albumin (BSA) types and lipid preparation methods in clonal 832/13 cells and human islets. Changing the percentage and culture conditions when using FFA-free BSA can negatively affect β-cell function compared to regular BSA. Preparing palmitate with FFA-free BSA can rescue insulin secretion compared to treating cells alone with FFA-free BSA. Different methods of preparing palmitate can have unique effects on insulin secretion. Overall, interpreting the effects of lipids on β-cell function is complicated by a number of variables that need to be controlled for in islet experiments.

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)0.001
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 score0.291
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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