Major Histocompatibility Complex class I proteins are critical for maintaining neuronal structural complexity in the aging brain
Bibliographic record
Abstract
Major histocompatibility complex class I (MHCI) proteins have been implicated in neuronal function through the modulation of neuritogenesis, synaptogenesis, synaptic plasticity, and memory consolidation during development. However, the involvement of MHCI in the aged brain is unclear. Here we demonstrate that MHCI deficiency results in significant dendritic atrophy along with an increase in thin dendritic spines and a reduction in stubby spines in the hippocampus of aged (12 month old) mice. Ultrastructural analyses revealed a decrease in spine head diameter and post synaptic density (PSD) area, as well as an increase in overall synapse density, and non-perforated, small spines. Interestingly, we found that the changes in synapse density and morphology appear relatively late (after the age of 6 months). Finally, we found a significant age dependent increase in the levels of the glutamate receptor, GluN2B in aged MHCI knockout mice, with no change in GluA2/3, VGluT1, PSD95 or synaptophysin. These results indicate that MHCI may be also be involved in maintaining brain integrity at post-developmental stages notably in the modulation of neuronal and spine morphology and synaptic function during non-pathological aging which could have significant implications for cognitive function.
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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) | 0.001 | 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".