Accelerated Aging in Patients with Hutchinson-Gilford Progeria Syndrome: Clinical Signs, Molecular Causes, Treatments, and Insights into the Aging Process
Bibliographic record
Abstract
Hutchinson-Gilford Progeria Syndrome (HGPS) is a condition characterized by signs of accelerated aging that present within the first year of life. Notable characteristics of children with HGPS include prominent superficial veins, failure to thrive, alopecia, as well as various skeletal and cardiovascular pathologies normally associated with advanced age. The discovery of the lamin A (C to T) gene mutation at position 1824 of the coding sequence has ushered a greater understanding on the essential role of lamin A protein processing. In normal cells, processing prelamin A to mature lamin A is complete following the cleavage of end terminal amino acids. In HGPS, gene mutation results in the deletion of a Zmpste24/FACE1 splice site in prelamin A preventing end terminal cleavage. Thus, prelamin A remains anchored due to c-terminal farnesylation. Lamin A eventually accumulates within the inner nuclear membrane of cells, resulting in disease pathology. The generation of experimental mouse models to understand the role of lamin A in normal and HGPS cells have fostered the development of prospective HGPS treatments. Clinical trials investigating farnesyltransferase inhibitors (FTIs), statins, and bisphosphonates as HGPS treatments are currently underway. HGPS and the relationship to lamin A has also shed light on normal aging as accumulation of prelamin A has been revealed in aged (non-HGPS derived) cells.
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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".