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Record W4400933759 · doi:10.3390/cells13151241

Butyrate Increases Heparin Synthesis and Storage in Human Mast Cells

2024· article· en· W4400933759 on OpenAlexafffund
Syed Benazir Alam, Zhimin Yan, Nishita Hiresha Verma, Larry D. Unsworth, Marianna Kulka

Bibliographic record

VenueCells · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsUniversity of AlbertaNational Research Council CanadaNational Institute for Nanotechnology
FundersNational Research Council Canada
KeywordsHeparinGlycosaminoglycanMast cellChemistryHistamineBiochemistrySodium butyrateCell biologyButyrateCellBiologyImmunologyPharmacologyFermentation

Abstract

fetched live from OpenAlex

Sulphated glycosaminoglycans (GAGs) such as heparin are a major component of mast cell granules and form the matrix within which biogenic mediators are stored. Since GAGs released from mast cells also play an important role in helminth expulsion, understanding GAG storage can offer new insights into mast cell function. Sodium butyrate (NaBu), a short-chain fatty acid, causes ultrastructural changes within the granules of human mast cells (HMC-1) and increases their histamine content. Therefore, we hypothesized that NaBu treatment would also modify the storage of polysaccharides such as GAGs. NaBu (1 mM) significantly increased GAG content and granularity in a time- and concentration-dependent manner without affecting cell viability and metabolic activity. NaBu increased the expression of enzymes associated with heparin biosynthesis (GLCE, NDST1, NDST2, HS6ST1, and GALT1) in a time-dependent manner. A cholesteryl butyrate emulsion (CholButE) increased heparin content after 24 and 48 h and modestly altered the expression of genes involved in heparin biosynthesis. Similar to NaBu, CholButE reduced cell proliferation without significantly altering viability or metabolic activity. These data show that butyrate increases the synthesis and storage of heparin in human mast cells, perhaps by altering their metabolic pathways.

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 categoriesInsufficient payload (model declined to judge)
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 score0.198
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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)0.0020.001

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 head0.009
GPT teacher head0.212
Teacher spread0.204 · 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.

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

Citations2
Published2024
Admission routes2
Has abstractyes

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