Acylation stimulating protein/C3adesArg in the metabolic states: role of adipocyte dysfunction in obesity complications
Bibliographic record
Abstract
Adipose tissue, as an endocrine organ, secretes several adipocyte-derived hormones named 'adipokines' that are implicated in regulating energy haemostasis. Substantial evidence shows that white adipose tissue-derived adipokines mediate the link between obesity-related exogenous factors (like diet and lifestyle) and various biological events (such as pre- and postmenopausal status) that have obesity consequences (cardiometabolic disorders). One of the critical aetiological factors for obesity-related diseases is the dysfunction of adipokine pathways. Acylation-stimulating protein (ASP) is an adipokine that stimulates triglyceride synthesis and storage in adipose tissue by enhancing glucose and fatty acid uptake. ASP acts via its receptor C5L2. The primary objective of this review is to address the existing gap in the literature regarding ASP by investigating its diverse responses and receptor interactions across multiple determinants of obesity. These determinants include diet composition, metabolic disorders, organ involvement, sex and sex hormone levels. Furthermore, this article explores the broader paradigm shift from solely focusing on adipose tissue mass, which contributes to obesity, to considering the broader implications of adipose tissue function. Additionally, we raise a critical question concerning the clinical relevance of the insights gained from this review, both in terms of potential therapeutic interventions targeting ASP and in the context of preventing obesity-related conditions, highlighting the potential of the ASP-C5L2 interaction as a pharmacological target. In conclusion, these findings validate that obesity is a low-grade inflammatory status with multiorgan involvement and sex differences, demonstrating dynamic interactions between immune and metabolic response determinants.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".