Iron metabolism and regulation by neutrophil gelatinase-associated lipocalin in cardiomyopathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it