Molecular mechanisms of neurodegeneration in the entorhinal cortex that underlie its selective vulnerability during the pathogenesis of Alzheimer's disease
Bibliographic record
Abstract
The entorhinal cortex (EC) is a vital component of the medial temporal lobe, and its contributions to cognitive processes and memory formation are supported through its extensive interconnections with the hippocampal formation. During the pathogenesis of Alzheimer's disease (AD), many of the earliest degenerative changes are seen within the EC. Neurodegeneration in the EC and hippocampus during AD has been clearly linked to impairments in memory and cognitive function, and a growing body of evidence indicates that molecular and functional neurodegeneration within the EC may play a primary role in cognitive decline in the early phases of AD. Defining the mechanisms underlying molecular neurodegeneration in the EC is crucial to determining its contributions to the pathogenesis of AD. Surprisingly few studies have focused on understanding the mechanisms of molecular neurodegeneration and selective vulnerability within the EC. However, there have been advancements indicating that early dysregulation of cellular and molecular signaling pathways in the EC involve neurodegenerative cascades including oxidative stress, neuroinflammation, glia activation, stress kinases activation, and neuronal loss. Dysfunction within the EC can impact the function of the hippocampus, which relies on entorhinal inputs, and further degeneration within the hippocampus can compound this effect, leading to severe cognitive disruption. This review assesses the molecular and cellular mechanisms underlying early degeneration in the EC during AD. These mechanisms may underlie the selective vulnerability of neuronal subpopulations in this brain region to the disease development and contribute both directly and indirectly to cognitive loss.This paper has an associated Future Leader to Watch interview with the first author of the article.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".