A Comprehensive Analysis of the Role of hnRNP A1 Function and Dysfunction in the Pathogenesis of Neurodegenerative Disease
Bibliographic record
Abstract
Heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) is a member of the hnRNP family of conserved proteins that is involved in RNA transcription, pre-mRNA splicing, mRNA transport, protein translation, microRNA processing, telomere maintenance and the regulation of transcription factor activity. HnRNP A1 is ubiquitously, yet differentially, expressed in many cell types, and due to post-translational modifications, can vary in its molecular function. While a plethora of knowledge is known about the function and dysfunction of hnRNP A1 in diseases other than neurodegenerative disease (e.g., cancer), numerous studies in amyotrophic lateral sclerosis, frontotemporal lobar degeneration, multiple sclerosis, spinal muscular atrophy, Alzheimer's disease, and Huntington's disease have found that the dysregulation of hnRNP A1 may contribute to disease pathogenesis. How hnRNP A1 mechanistically contributes to these diseases, and whether mutations and/or altered post-translational modifications contribute to pathogenesis, however, is currently under investigation. The aim of this comprehensive review is to first describe the background of hnRNP A1, including its structure, biological functions in RNA metabolism and the post-translational modifications known to modify its function. With this knowledge, the review then describes the influence of hnRNP A1 in neurodegenerative disease, and how its dysfunction may contribute the pathogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".