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Record W2095885541 · doi:10.1186/1742-2094-2-11

Platelet-activating factor enhancement of calcium influx and interleukin-6 expression, but not production, in human microglia

2005· article· en· W2095885541 on OpenAlexafffund
Prasongchai Sattayaprasert, Hyun B. Choi, Sukumal Chongthammakun, James G. McLarnon

Bibliographic record

VenueJournal of Neuroinflammation · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia
FundersAlzheimer's SocietyHeart and Stroke Foundation of British Columbia and YukonAlzheimer SocietyHeart and Stroke Foundation of Canada
KeywordsMicrogliaPlatelet-activating factorCytokineCalcium in biologyStimulationCalciumChemistryCell biologyIntracellularInterleukinImmunologyEndocrinologyMolecular biologyInflammationInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Calcium-sensitive fluorescence microscopy and molecular biology analysis have been used to study the effects of platelet-activating factor (PAF) on intracellular calcium [Ca2+]i and IL-6 expression in human microglia. PAF (applied acutely at 100 nM) elicited a biphasic response in [Ca2+]i consisting of an initial rapid increase of [Ca2+]i due to release from internal stores, followed by a sustained influx. The latter phase of the [Ca2+]i increase was blocked by SKF96365, a non-selective store-operated channel (SOC) inhibitor. RT-PCR analysis showed PAF treatment of microglia induced expression of the pro-inflammatory cytokine IL-6 in a time-dependent manner which was blocked in the presence of SKF96365. However, ELISA assay showed no production of IL-6 was elicited at any time point (1-24 h) for microglial exposures to PAF. These findings suggest that PAF stimulation of human microglia induces expression, but not production, of IL-6 and that SOC-mediated [Ca2+]i influx contributes to the enhanced expression of the cytokine.

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 score0.005
Threshold uncertainty score0.737

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 communication0.0000.001
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 head0.046
GPT teacher head0.294
Teacher spread0.247 · 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

Citations23
Published2005
Admission routes2
Has abstractyes

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