Glutamate mobilizes [Zn<sup>2+</sup>]<sub>i</sub> through Ca<sup>2+</sup>‐dependent reactive oxygen species accumulation
Bibliographic record
Abstract
Liberation of zinc from intracellular stores contributes to oxidant-induced neuronal injury. However, little is known regarding how endogenous oxidant systems regulate intracellular free zinc ([Zn(2+)](i)). Here we simultaneously imaged [Ca(2+)](i) and [Zn(2+)](i) to study acute [Zn(2+)](i) changes in cultured rat forebrain neurons after glutamate receptor activation. Neurons were loaded with fura-2FF and FluoZin-3 to follow [Ca(2+)](i) and [Zn(2+)](i), respectively. Neurons treated with glutamate (100 microM) for 10 min gave large Ca(2+) responses that did not recover after termination of the glutamate stimulus. Glutamate also increased [Zn(2+)](i), however glutamate-induced [Zn(2+)](i) changes were completely dependent on Ca(2+) entry, appeared to arise entirely from internal stores, and were substantially reduced by co-application of the membrane-permeant chelator TPEN during the glutamate treatment. Pharmacological maneuvers revealed that a number of endogenous oxidant producing systems, including nitric oxide synthase, phospholipase A(2), and mitochondria all contributed to glutamate-induced [Zn(2+)](i) changes. We found no evidence that mitochondria buffered [Zn(2+)](i) during acute glutamate receptor activation. We conclude that glutamate-induced [Zn(2+)](i) transients are caused in part by [Ca(2+)](i)-induced reactive oxygen species that arises from both cytosolic and mitochondrial sources.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".