Immunoengineering strategies using nanoparticles for obesity treatment
Bibliographic record
Abstract
Obesity has emerged as a global epidemic, posing severe challenges to public health and contributing to various complications, including metabolic disorders, cardiovascular disease, and type 2 diabetes. This review provides a comprehensive overview of obesity, its associated comorbidities, and the limitations of conventional treatments. We explore the complex relationship between obesity-induced inflammation, immune dysregulation, and the pivotal role of adipose tissue macrophages (ATMs). Chronic low-grade inflammation in adipose tissues (AT) is a key driver of insulin resistance and metabolic dysfunction. As ATs expand, they undergo significant changes, including increased immune cell infiltration, particularly macrophages (MΦs), which shift from an anti-inflammatory towards a pro-inflammatory phenotype. This review aims to advance the understanding of immunomodulatory strategies by examining MΦ polarization and AT browning as promising therapeutic approaches. We focus on nanoparticles (NPs)-based strategies for immunomodulation, highlighting innovative engineering approaches designed to target the inflammatory pathways underlying obesity. By addressing these mechanisms, this review provides valuable insights into mitigating obesity-associated inflammation and related metabolic disorders, paving the way for novel therapeutic strategies in the fight against the global obesity epidemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".