Polarized Targeting of Peripheral Membrane Proteins in Neurons
Bibliographic record
Abstract
Differential targeting of neuronal proteins to axons and dendrites is essential for directional information flow within the brain, however, little is known about this protein-sorting process. Here, we investigate polarized targeting of lipid-anchored peripheral membrane proteins, postsynaptic density-95 (PSD-95) and growth-associated protein-43 (GAP-43). Whereas the N-terminal palmitoylated motif of PSD-95 is necessary but not sufficient for sorting to dendrites, the palmitoylation motif of GAP-43 is sufficient for axonal targeting and can redirect a PSD-95 chimera to axons. Systematic mutagenesis of the GAP-43 and PSD-95 palmitoylation motifs indicates that the spacing of the palmitoylated cysteines and the presence of nearby basic amino acids determine polarized targeting by these two motifs. Similarly, the axonal protein paralemmin contains a C-terminal palmitoylated domain, which resembles that of GAP-43 and also mediates axonal targeting. These axonally targeted palmitoylation motifs also mediate targeting to detergent-insoluble glycolipid-enriched complexes in heterologous cells, suggesting a possible role for specialized lipid domains in axonal sorting of peripheral membrane proteins.
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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) | 0.000 | 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 | 0.000 |
| 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 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".