The Role of Reticulons in Neurodegenerative Diseases
Bibliographic record
Abstract
Reticulons (RTNs) are a group of membrane-associated proteins mainly responsible for shaping the tubular endoplasmic reticulum network, membrane trafficking, inhibition of axonal growth, and apoptosis. These proteins share a common sequence feature, the reticulon homology domain, which consists of paired hydrophobic stretches that are believed to induce membrane curvature by acting as a wedge in bilayer membranes. RTNs are ubiquitously expressed in all tissues, but each RTN member exhibits a unique expression pattern that prefers certain tissues or even cell types. Recently, accumulated evidence has suggested additional and unexpected roles for RTNs, including those on DNA binding, autophagy, and several inflammatory-related functions. These manifold actions of RTNs account for their ever-growing recognition of their involvement in neurodegenerative diseases like Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, as well as hereditary spastic paraplegia. This review summarizes the latest discoveries on RTNs in human pathophysiology, and the engagement of these in neurodegeneration, along with the implications of these findings for a better understanding of the molecular events triggered by RTNs and their potential exploitation as next-generation therapeutics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".