A Miniaturized Column Chromatography Method for Measuring Receptor-Mediated Inositol Phosphate Accumulation
Bibliographic record
Abstract
Inositol phosphates (IPs), such as 1,4,5-inositol-trisphosphate (IP(3)), comprise a ubiquitous intracellular signaling cascade initiated in response to G protein-coupled receptor-mediated activation of phospholipase C. Classical methods for measuring intracellular accumulation of these molecules include time-consuming high-performance liquid chromatography (HPLC) separation or large-volume, gravity-fed anion-exchange column chromatography. More recent approaches, such as radio-receptor and AlphaScreen assays, offer higher throughput. However, these techniques rely on measurement of IP(3) itself, rather than its accumulation with other downstream IPs, and often suffer from poor signal-to-noise ratios due to the transient nature of IP(3). The authors have developed a miniaturized, anion-exchange chromatography method for measuring inositol phosphate accumulation in cells that takes advantage of signal amplification achieved through measuring IP(3) and downstream IPs. This assay uses centrifugation of 96-well-formatted anion-exchange mini-columns for the isolation of radiolabeled inositol phosphates from cell extracts, followed by low-background dry-scintillation counting. This improved assay method measures receptor-mediated IP accumulation with signal-to-noise and pharmacological values comparable to the classical large-volume, column-based methods. Assay validation data for recombinant muscarinic receptor 1, galanin receptor 2, and rat astrocyte metabotropic glutamate receptor 5 are presented. This miniaturized protocol reduces reagent usage and assay time as compared to large-column methods and is compatible with standard 96-well scintillation counters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".