G protein–coupled receptor kinase 2 and group I metabotropic glutamate receptors mediate inflammation‐induced sensitization to excitotoxic neurodegeneration
Bibliographic record
Abstract
OBJECTIVE: The concept of inflammation-induced sensitization is emerging in the field of perinatal brain injury, stroke, Alzheimer disease, and multiple sclerosis. However, mechanisms underpinning this process remain unidentified. METHODS: We combined in vivo systemic lipopolysaccharide-induced or interleukin (IL)-1β-induced sensitization of neonatal and adult rodent cortical neurons to excitotoxic neurodegeneration with in vitro IL-1β sensitization of human and rodent neurons to excitotoxic neurodegeneration. Within these inflammation-induced sensitization models, we assessed metabotropic glutamate receptors (mGluR) signaling and regulation. RESULTS: We demonstrate for the first time that group I mGluRs mediate inflammation-induced sensitization to neuronal excitotoxicity in neonatal and adult neurons across species. Inflammation-induced G protein-coupled receptor kinase 2 (GRK2) downregulation and genetic deletion of GRK2 mimicked the sensitizing effect of inflammation on excitotoxic neurodegeneration. Thus, we identify GRK2 as a potential molecular link between inflammation and mGluR-mediated sensitization. INTERPRETATION: Collectively, our findings indicate that inflammation-induced sensitization is universal across species and ages and that group I mGluRs and GRK2 represent new avenues for neuroprotection in perinatal and adult neurological disorders.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".