The Ca<sup>2+</sup>-Activated K<sup>+</sup>Channel<i>KCNN4</i>/KCa3.1 Contributes to Microglia Activation and Nitric Oxide-Dependent Neurodegeneration
Bibliographic record
Abstract
Brain damage and disease involve activation of microglia and production of potentially neurotoxic molecules, but there are no treatments that effectively target their harmful properties. We present evidence that the small-conductance Ca2+/calmodulin-activated K+ channel KCNN4/ KCa3.1/SK4/IK1 is highly expressed in rat microglia and is a potential therapeutic target for acute brain damage. Using a Transwell cell-culture system that allows separate treatment of the microglia or neurons, we show that activated microglia killed neurons, and this was markedly reduced by treating only the microglia with a selective inhibitor of KCa3.1 channels, triarylmethane-34 (TRAM-34). To assess the role of KCa3.1 channels in microglia activation and key signaling pathways involved, we exploited several fluorescence plate-reader-based assays. KCa3.1 channels contributed to microglia activation, inducible nitric oxide synthase upregulation, production of nitric oxide and peroxynitrite, and to consequent neurotoxicity, protein tyrosine nitration, and caspase 3 activation in the target neurons. Microglia activation involved the signaling pathways p38 mitogen-activated protein kinase (MAPK) and nuclear factor kappaB (NF-kappaB), which are important for upregulation of numerous proinflammatory molecules, and the KCa3.1 channels were functionally linked to activation of p38 MAPK but not NF-kappaB. These in vitro findings translated into in vivo neuroprotection, because we found that degeneration of retinal ganglion cells after optic nerve transection was reduced by intraocular injection of TRAM-34. This study provides evidence that KCa3.1 channels constitute a therapeutic target in the CNS and that inhibiting this K+ channel might benefit acute and chronic neurodegenerative disorders that are caused by or exacerbated by inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".