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Differential regulation of multiple populations of granules in rat adrenal chromaffin cells by culture duration and cyclic AMP

2005· article· en· W1871216002 on OpenAlexafffund
Kim San Tang, Amy Tse, Frederick W. Tse

Bibliographic record

VenueJournal of Neurochemistry · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsGranule (geology)CatecholamineChromaffin cellEndocrinologyInternal medicineBiologyAdrenal medullaBiophysicsChemistryCell biologyMedicine

Abstract

fetched live from OpenAlex

We employed carbon fiber amperometry to measure the amount of catecholamine released from individual granules (i.e. the quantal size, Q) of rat chromaffin cells. The distribution of Q1/3 of amperometric events could be reasonably described by the summation of at least three Gaussians, suggesting that rat chromaffin cells contained at least three distinct populations of granules, with a small, medium or large modal Q. After 3 days of culture, the mean cellular Q reduced by approximately 14%, which did not arise from a uniform percentage decrease in the Q of every granule. Instead, the rundown involved a > 11% decrease in the proportional release from large Q granules and a > 19% decrease in the modal Q-value of small Q granules. In contrast, when cells were cultured with dibutyryl-cAMP (dBcAMP) for 3 days, their mean cellular Q increased by approximately 38% (relative to time-matched controls). This increase in Q was not associated with any shift in the proportional release from the three populations of granules. Instead, cAMP increased the average amount of catecholamines released from all three populations of granules. Our data raise the possibility that distinct populations of granules in rat chromaffin cells can be regulated either differentially or uniformly.

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 score0.003

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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

Citations24
Published2005
Admission routes2
Has abstractyes

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