Bibliographic record
Abstract
The concept of a metabolic syndrome (MetS), a cluster of pre-clinical metabolic alterations commonly associated with obesity, is the object of much debate. Genetic studies have the potential to contribute to some of the key questions, including the true nature of the cluster of pre-clinical features and whether it is associated with human genetic variation. This review summarizes the evidence for the presence of familial aggregation for the individual components of MetS and their heritability levels. It also provides an overview of the studies that have dealt with candidate genes for MetS. Potential leads from genome-wide linkage scans are also discussed. The assumption is made that obesity, ectopic fat deposition and abnormal adipose tissue metabolism are responsible for alterations in lipid metabolism, which in turn generates the commonly observed pre-clinical shifts in glucose tolerance, lipids and lipoprotein profile, blood pressure, inflammatory markers, endothelial function, and a prothrombotic state. Progress in the understanding of the genetic basis of MetS should occur as soon as a consensus is reached on the true nature of MetS, its components and diagnostic criteria.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".