Iron metabolism and regulation by neutrophil gelatinase-associated lipocalin in cardiomyopathy
Bibliographic record
Abstract
Neutrophil gelatinase-associated lipocalin (NGAL) has recently become established as an important contributor to the pathophysiology of cardiovascular disease. Accordingly, it is now viewed as an attractive candidate as a biomarker for various disease states, and in particular has recently become regarded as one of the best diagnostic biomarkers available for acute kidney injury. Nevertheless, the precise physiological effects of NGAL on the heart and the significance of their alterations during the development of heart failure are only now beginning to be characterized. Furthermore, the mechanisms via which NGAL mediates its effects are unclear because there is no conventional receptor signalling pathway. Instead, previous work suggests that regulation of iron metabolism could represent an important mechanism of NGAL action, with wide-ranging consequences spanning metabolic and cardiovascular diseases to host defence against bacterial infection. In the present review, we summarize rapidly emerging evidence for the role of NGAL in regulating heart failure. In particular, we focus on iron transport as a mechanism of NGAL action and discuss this in the context of the existing strong associations between iron overload and iron deficiency with cardiomyopathy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".