Serum amyloid A1 levels and amyloid deposition following a high-fat diet challenge in transgenic mice overexpressing hepatic serum amyloid A1
Bibliographic record
Abstract
Serum amyloid A (SAA) is an acute-phase response protein in the liver, and SAA1 is the major precursor protein involved in amyloid A amyloidosis. This amyloidosis has been reported as a complication in chronic inflammatory conditions such as arthritis, lupus, and Crohn's disease. Obesity is also associated with chronic, low-grade inflammation and sustained, elevated levels of SAA1. However, the contribution of elevated circulating SAA1 to metabolic disturbances and their complications is unclear. Furthermore, in several recent studies of transgenic (TG) mice overexpressing SAA1 that were fed a high-fat diet (HFD) for a relatively short period, no relationship was found between SAA1 up-regulation and metabolic disturbances. Therefore, we generated TG mice overexpressing SAA1 in the liver, challenged these mice with an HFD, and investigated the influence of elevated SAA1 levels. Sustained, elevated levels of SAA1 were correlated with metabolic parameters and local cytokine expression in the liver following 16 weeks on the HFD. Moreover, prolonged consumption (52 weeks) of the HFD was associated with impaired glucose tolerance and elevated SAA1 levels and resulted in systemic SAA1-derived amyloid deposition in the kidney, liver, and spleen of TG mice. Thus, we concluded that elevated SAA1 levels under long-term HFD exposure result in extensive SAA1-derived amyloid deposits, which may contribute to the complications associated with HFD-induced obesity and metabolic disorders.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".