Apoptosis Related Protein Expression and Proteolytic Enzyme Activity Differ in Brown and White Adipose Tissue
Bibliographic record
Abstract
Adipocytes have now been recognized to undergo both necrotic and apoptotic cell death. Interestingly, adipocyte apoptosis has been shown to contribute to the pathophysiology of metabolic disorders and a number of cardiovascular diseases. Previous data has suggested that brown adipose tissue (BAT) may be more susceptible to apoptotic stress then white adipose tissue (WAT). However, there has been limited data examining pro- and anti-apoptotic proteins as well as proteolytic enzyme activity across BAT and WAT under healthy basal conditions. PURPOSE: To identify the levels of key apoptotic factors in BAT and WAT. METHODS: Western blot analysis was performed to identify the expression of AIF, Smac/DIABLO, cytochrome c, XIAP, Hsp70, Bax, Bcl-2, and ARC in BAT and WAT protein extracts from healthy male Sprague-Dawley rats. In addition, the activity of caspase-3 and -8 were identified in BAT and WAT. RESULTS: Relative to total protein content there was a greater expression of the pro-apoptotic proteins Bax, AIF, Smac/DIABLO and cytochrome c in BAT (p<0.05). Similarly, the expression of the anti-apoptotic proteins ARC and Hsp70 was significantly higher in BAT compared to WAT (p<0.05). Interestingly, the protein levels of anti-apoptotic Bcl-2 and XIAP were significantly higher in WAT (p<0.05). The activity of the proteolytic enzymes caspase -3 and -8 were also significantly greater in BAT compared to WAT (p<0.05). CONCLUSION: These results indicate a potentially higher level of apoptotic signaling in BAT. Furthermore, it appears that WAT may be more resistant to cell death compared to BAT at basal states given the higher Bcl-2:Bax ratio and XIAP levels; however, further investigation is needed. These results provide important insight into the apoptotic differences between BAT and WAT. In addition, this data may help elucidate potential mechanisms leading to BAT atrophy and WAT inflammation in metabolic and cardiovascular disease states.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".