Bibliographic record
Abstract
Hutchinson-Gilford progeria syndrome (HGPS) is an extremely rare genetic disorder that causes premature, rapid aging shortly after birth. Recently, de novo point mutations in the Lmna gene have been found in individuals with HGPS. Lmna encodes lamin A and C, the A-type lamins, which are an important structural component of the nuclear envelope. The most common HGPS mutation is located at codon 608 (G608G). This mutation creates a cryptic splice site within exon 11, which deletes a proteolytic cleavage site within the expressed mutant lamin A. Incomplete processing of prelamin A results in nuclear lamina abnormalities that can be observed in immunofluorescent studies of HGPS cells. Mouse models, such as Lmna knockout, Zmpste24 knockout, and Lmna L530P knockin will help the study of progeria. Lmna mutations have also recently been found in patients with atypical forms of progeria. The discovery of the HGPS mutations brings the total number of diseases caused by mutant Lmna to nine, underscoring the astonishing spectrum of laminopathies. Future research into HGPS could also provide important clues about the general process of aging and aging-related diseases.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".