Developmental changes in the association of NMDA receptors with lipid rafts
Bibliographic record
Abstract
Lipid rafts (LR) are lipid microdomains present in the cell surface membrane that are organizational platforms involved in protein trafficking and formation of cell signaling complexes. In the adult brain, NMDA receptors (NMDAR) and receptor-associated proteins such as membrane-associated guanylate kinases (PSD-95 and SAP102), are distributed between the postsynaptic density (PSD) and lipid rafts. However, the time course of the association of NMDAR with LR during neural development is not known. We therefore investigated the effect of development on the association of NMDAR with LR prepared from rat brains ranging in postnatal age from 1-35 days and compared this with their expression in PSDs. LR and PSD fractions were prepared by extraction of P2 membranes with Tx-100 followed by sucrose density gradient centrifugation. The yield of LR, as reflected by levels of protein, Thy-1, and flotillin-1 increased during postnatal development. NR2A was associated predominantly with the lipid raft fraction at all ages examined whereas NR2B underwent a gradual shift from PSDs to lipid rafts during the first 3 weeks after birth. These changes in the distribution of NR2A and NR2B were paralleled by changes in the distribution of PSD-95 and SAP102 respectively. Tyrosine-phosphorylated proteins, including NR2A and NR2B, were preferentially associated with lipid rafts in older, as compared to younger, animals. These results show that the association of NMDAR with LR is regulated developmentally.
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) | 0.000 | 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 | 0.001 |
| 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".