Design of an imaging probe to monitor real-time redistribution of L-type voltage gated calcium channels in astrocytic glutamate signalling
Bibliographic record
Abstract
ABSTRACT Purpose In the brain, astrocytes are non-excitable cells that undergo rapid morphological changes when stimulated by the excitatory neurotransmitter glutamate. We developed a chemical probe to monitor how glutamate affects the density and distribution of astrocytic L-type voltage-gated calcium channels (LTCC). Procedures The imaging probe FluoBar1 was created from a barbiturate ligand modified with a fluorescent coumarin moiety. The probe selectivity was examined with colocalization analyses of confocal fluorescence imaging in U118-MG and transfected COS-7 cells. Living cells treated with 50 nM FluoBar1 were imaged in real time to reveal changes in density and distribution of astrocytic LTCCs upon exposure to glutamate. Results FluoBar1 was synthesized in ten steps. The selectivity of the probe was demonstrated with immunoblotting and confocal imaging of immunostained cells expressing the Ca V 1.2 isoform of LTCCs proteins. Applying FluoBar1 to astrocyte model cells U118-MG allowed us to measure a 5-fold increase in fluorescence density of LTCCs upon glutamate exposure. Conclusions Imaging probe FluoBar1 allows the real-time monitoring of LTCCs in living cells, revealing for first time that glutamate causes a rapid increase of LTCC membranar density in astrocyte model cells. FluoBar1 may help tackle previously intractable questions about LTCC dynamics in cellular events.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".