Glutamate Attenuates the Survival Property of IGFR through NR2B Containing N-Methyl-D-aspartate Receptors in Cortical Neurons
Bibliographic record
Abstract
Glutamate-induced neurotoxicity is involved in various neuronal diseases, such as Alzheimer's disease. We have previously reported that glutamate attenuated the survival signaling of insulin-like growth factor-1 (IGF-1) by N-methyl-D-aspartate receptors (NMDARs) in cultured cortical neurons, which is viewed as a novel mechanism of glutamate-induced neurotoxicity. However, the phosphorylation sites of IGF-1 receptor (IGF-1R) affected by glutamate remain to be elucidated, and importantly, which subtype of NMDARs plays a major role in attenuating the prosurvival effect of IGF-1 is still unknown. In the present study, glutamate was found to attenuate the tyrosine phosphorylation of the IGF-1R and the prosurvival effect of IGF-1 in primary cultured cortical neurons. NMDAR inhibitors, MK801 and AP-5, blocked the inhibitory effect of glutamate on the phosphorylation of IGF-1R and increased cell survival, while DNQX, LY341495, and CPCCOEt had no effect. Interestingly, we found that glutamate decreased the phosphorylation of tyrosine residues 1131, 1135/1136, 1250/1251, and 1316, while it had no effect on tyrosine 950 in cortical neurons. Moreover, using specific antagonists and siRNA to downregulate individual NMDAR subunits, we found that the activation of NR2B-containing NMDARs was essential for glutamate to inhibit IGF-1 signaling. These findings indicate that the glutamate-induced attenuation of IGF-1 signaling is mediated by NR2B-containing NMDARs. Our study also proposes a novel mechanism of altering neurotrophic factor signaling by the activation of NMDARs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".