Proteomic validation: Searching for a heart of gold
Bibliographic record
Abstract
Recent developments in proteomics techniques allow sensitive identification and relative quantitation of proteins in tissues and with increased sensitivity come the ability to detect small changes in protein expression. However, the means by which changes are validated remains incompletely defined. The proteome of mitochondria of hypertrophied hearts from rats with an abdominal aortic constriction (H) was quantitated using amine‐reactive isobaric tagging reagents (iTRAQ®) and tandem mass spectrometry. A small number (15 out of 250) were significantly increased and none decreased significantly. Increases ranged from 10 to 20%, as exemplified by voltage‐dependent anion channel‐1 (VDAC1), with only monoamine oxidase‐A (MAO‐A) showing a substantially greater increase (see table). Traditional immunoblot analysis revealed the significant increase in MAO‐A but not that of VDAC1. The discrepancy in results highlights the relative insensitivity of traditional immunoblot analysis and indicates that more sensitive approaches are essential. Supported by a grant from the Canadian Institutes for Health Research.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".