The Neuroplastin Adhesion Molecules Are Accessory Proteins That Chaperone the Monocarboxylate Transporter MCT2 to the Neuronal Cell Surface
Bibliographic record
Abstract
BACKGROUND: The neuroplastins np65 and np55 are two synapse-enriched immunoglobulin (Ig) superfamily adhesion molecules that contain 3 and 2 Ig domains respectively. Np65 is implicated in long term, activity dependent synaptic plasticity, including LTP. Np65 regulates the surface expression of GluR1 receptor subunits and the localisation of GABA(A) receptor subtypes in hippocampal neurones. The brain is dependent not only on glucose but on monocarboxylates as sources of energy. The. monocarboxylate transporters (MCTs) 1-4 are responsible for the rapid proton-linked translocation of monocarboxylates including pyruvate and lactate across the plasma membrane and require association with either embigin or basigin, proteins closely related to neuroplastin, for plasma membrane expression and activity. MCT2 plays a key role in providing lactate as an energy source to neurons. METHODOLOGY/FINDINGS: Here we use co-transfection of neuroplastins and monocarboxylate transporters into COS-7 cells to demonstrate that neuroplastins can act as ancillary proteins for MCT2. We also show that Xenopus laevis oocytes contain endogenous neuroplastin and its knockdown with antisense RNA reduces the surface expression of MCT2 and associated lactate transport. Immunocytochemical studies show that MCT2 and the neuroplastins are co-localised in rat cerebellum. Strikingly neuroplastin and MCT2 are enriched in the same parasagittal zebrin II-negative stripes. CONCLUSIONS: These data strongly suggest that neuroplastins act as key ancillary proteins for MCT2 cell surface localisation and activity in some neuronal populations, thus playing an important role in facilitating the uptake of lactate for use as a respiratory fuel.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".