Dead adipocytes, detected as crown-like structures, are prevalent in visceral fat depots of genetically obese mice
Bibliographic record
Abstract
Accumulation of visceral fat is a key phenomenon in the onset of obesity-associated metabolic disorders. Macrophage infiltration induces chronic mild inflammation widely considered as a causative factor for insulin resistance and eventually diabetes. We previously showed that >90% of macrophages infiltrating the adipose tissue of obese animals and humans are arranged around dead adipocytes, forming characteristic crown-like structures (CLS). In this study we quantified CLS in visceral and subcutaneous depots from two strains of genetically obese mice, db/db and ob/ob. In both strains, CLS were prevalent in visceral compared with subcutaneous fat. Adipocyte size and CLS density exhibited a positive correlation both in visceral and in subcutaneous depots; however, the finding that adipocyte size was smallest and CLS density highest in visceral fat suggests a different susceptibility of visceral and subcutaneous adipocytes to death. Visceral fat CLS density was 3.4-fold greater in db/db than in ob/ob animals, which at the age at which our experimental strain was used are more prone to glucose 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".