Role of microglial NMDA receptor-initiated PARP-1/TRPM2 signaling in driving chronic neuroinflammation
Bibliographic record
Abstract
An important component of neurodegenerative disorders, like Alzheimer’s disease (AD), is the prolonged inflammatory response driven by continuous microglial poly (ADP-ribose) polymerase-1 (PARP-1) activation. However, mechanisms that promote sustained microglial PARP-1 activation and maintaining microglial activity remains elusive. But we know that PARP-1 enzymatic activity requires Ca2+ influx, a process that is independent of DNA damage, and this could be through microglial N-methyl D-aspartate receptors (NMDARs). Notably, PARP-1 mediated ADP-ribose production causes activation of Ca2+ permeable non-selective cation channel, transient receptor potential melastatin-2 (TRPM2). Hence, we hypothesize that NMDAR activation by amyloid beta oligomers (AβO) or NMDA initiates PARP-1 mediated ADPR production and TRPM2 activation. This in-turn leads to TRPM2-dependent, self-sustaining PARP-1 activation, which promotes pro-inflammatory responses. Primary microglia treated with AβO and NMDA were assessed for functional TRPM2 currents using whole cell voltage-clamp electrophysiology. Using nitric oxide assay and qRT-PCR, AβO/NMDA treated microglia were also evaluated to identify the contribution of NMDAR/PARP-1/TRPM2 in promoting pro-inflammatory responses. Our findings, demonstrates that glutamate signaling via NMDARs, promoting detrimental microglial responses, suggests a unifying mechanism linking elevated glutamate levels, associated for example with AD, hypoxic-ischemic injury, or traumatic brain injury, to chronic neuroinflammation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".