Novel metabolic phenotypes in lecithin cholesterol acyltyransferase-deficient mice
Bibliographic record
Abstract
PURPOSE OF REVIEW: Lecithin cholesterol acyltyransferase (LCAT) deficiency is a rare monogenic disorder causing lipoprotein dysregulation and multiple organ dysfunctions, including renal impairment. LCAT knockout mice have been shown informative in elucidating mechanisms of many major clinical morbid phenotypes. Extended characterization of the LDL receptor/LCAT double knockout (Ldlr/Lcat-DKO or DKO) mice had led to the discovery of a number of novel protective metabolic phenotypes, including resistance to obesity, nonalcoholic steatohepatitis (NASH) and insulin resistance. We seek to integrate the findings to explore novel pathogenic pathways. RECENT FINDINGS: The chow fed DKO mice were found more insulin sensitive than their Ldlr-KO controls. Joint analyses of the three strains (DKO, Ldlr-KO and wild-type) revealed differential metabolic responses to a high cholesterol diet (HCD) vs. high-fat diet (HFD). DKO mice are protected from HFD-induced obesity, hepatic endoplasmic reticulum (ER) stress, insulin resistance, ER cholesterol and NASH markers (steatosis and inflammasomes). Joint analysis revealed the HFD-induced NASH is dependent on de-novo hepatic cholesterol biosynthesis. DKO mice are protected from HCD-induced hepatic ER stress, ER cholesterol, but not NASH, the latter likely due to cholesterol crystal accumulation. DKO mice were found to develop ectopic brown adipose tissue (BAT) in skeletal muscle. Ectopic BAT derived in part from myoblast in utero and from adult satellite cells. Primed expression of PRDM16 and UCP in quiescent satellite cell caused by LCAT deficiency synergizes with cell cholesterol depletion to induce satellite cell-to-BAT transdifferentiation. SUMMARY: Metabolic phenotyping of selective LCAT null mice led to the discovery of novel metabolically protective pathways.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".