Tocilizumab Increases Serum Adiponectin and Reduces Serum Fatty Acid Binding Protein 4 in Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
Background: Recently tocilizumab, a humanized anti-interleukin-6 receptor antibody (IL-6R Ab), was clinically demonstrated to ameliorate metabolic syndrome. However, it is unknown whether blocking the IL-6R with tocilizumab directly impacts the adiponectin and fatty acid-binding protein 4 (FABP4) levels. Methods: In this study, we measured the serum adiponectin and FABP4 levels in 18 patients with rheumatoid arthritis (RA) 3 months after treatment with tocilizumab. Results: Our study revealed that treatment with tocilizumab decreased serum FABP4 levels and increased serum adiponectin levels in patients with RA. We also assessed the production of adipocytokines stimulated by IL-6R Ab using adipocyte precursors obtained from human fat tissue. Tocilizumab did not increase local adiponectin levels; however, the suppression of adiponectin secretion by IL-6 was completely abolished. Tocilizumab also directly suppressed FABP4 in human adipocytes. Conclusion: This suggests that treatment with tocilizumab may be a novel approach to coordinately regulate adiponectin and FABP4 levels. J Endocrinol Metab. 2014;4(5-6):143-147 doi: http://dx.doi.org/10.14740/jem251w
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".