Clinical evaluation of a matrix metalloproteinase-12 cleaved fragment of titin as a cardiovascular serological biomarker
Bibliographic record
Abstract
BACKGROUND: Titin is a muscle-specific protein found in cardiac and skeletal muscles which is responsible for restoring passive tension. Levels and functioning of titin have been shown to be affected by cardiac damage. Due to the inherent difficulty of measuring titin levels in vivo in a clinical setting, we aimed to develop an assay that could reliably measure fragments of degraded titin in serum and potentially be used in the assessment of cardiac muscle damage. METHODS: A competitive ELISA was developed to specifically measure levels of the titin sequence 12670' NVTVEARLIK 12679', derived by the degradation of titin by matrix metalloproteinase (MMP)-12. Serum samples from 90 individuals were divided into 3 equally sized groups. One group had been diagnosed with acute myocardial infarction (AMI) while the remaining two were asymptomatic individuals either with CT-scan signs of coronary calcium (CT-plusCa) or without coronary calcium (CT-noCa). RESULTS: Mean geometric levels of the titin fragment in the CT-noCa group were 506.5 ng/ml (± 43.88). The CT-plusCa group showed 50.6% higher levels of the marker [763 ng/ml (± 90.14)] (P < 0.05). AMI patients showed 56.3% higher levels [792 ng/ml (± 149)] (P < 0.05). CONCLUSIONS: The titin-12670 fragment is present in both individuals with undiagnosed and diagnosed CVD. The statistically significant increase in level of the marker in the AMI group is indicative that this neoepitope biomarker may be a useful serological marker in AMI.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".