Hippocampal metabotropic glutamate receptor long‐term depression in health and disease: focus on mitogen‐activated protein kinase pathways
Bibliographic record
Abstract
Group I metabotropic glutamate receptor (mGluR) dependent long-term depression (LTD) is a major form of synaptic plasticity underlying learning and memory. The molecular mechanisms involved in mGluR-LTD have been investigated intensively for the last two decades. In this 60th anniversary special issue article, we review the recent advances in determining the mechanisms that regulate the induction, transduction and expression of mGluR-LTD in the hippocampus, with a focus on the mitogen-activated protein kinase (MAPK) pathways. In particular we discuss the requirement of p38 MAPK and extracellular signal-regulated kinase 1/2 (ERK 1/2) activation. The recent advances in understanding the signaling cascades regulating mGluR-LTD are then related to the cognitive impairments observed in neurological disorders, such as fragile X syndrome and Alzheimer's disease. mGluR-LTD is a form of synaptic plasticity that impacts on memory formation. In the hippocampus mitogen-activated protein kinases (MAPKs) have been found to be important in mGluR-LTD. In this 60th anniversary special issue article, we review the independent and complementary roles of two classes of MAPK, p38 and ERK1/2 and link this to the aberrant mGluR-LTD that has an important role in diseases. This article is part of the 60th Anniversary special issue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".