Individuals with obesity and type 2 diabetes have additional immune dysfunction compared with obese individuals who are metabolically healthy
Bibliographic record
Abstract
OBJECTIVE: The objective of the current study was to compare the responses to different ex vivo immunogenic challenges between immune cells derived from metabolically healthy subjects with obesity and subjects with obesity and type 2 diabetes. RESEARCH DESIGN AND METHODS: We recruited 10 metabolically healthy subjects with obesity (Edmonton Obesity Staging System (EOSS) stage 0) and 9 subjects with obesity and type 2 diabetes (EOSS stage 2) aged between 21 years and 70 years and matched for body mass index. Peripheral blood mononuclear cells (PBMCs) were isolated and immune cell phenotypes and ex vivo cytokine production after phytohaemagglutinin (PHA, a T cell mitogen) stimulation were determined. Neutrophil oxidative burst activity was assessed in whole blood. RESULTS: PBMCs from subjects with stage 2 obesity produced significantly less interleukin (IL)-2, IL-6 and tumour necrosis factor α after PHA stimulation than PBMCs from subjects with stage 0 obesity (all, p<0.05). Subjects with stage 2 obesity also had higher proportions of cytotoxic T cells, activated helper T cells (CD4+CD278+) and inflammatory monocytes (CD14+CRTh2+, all p<0.05). Poststimulation, neutrophils from subjects with stage 2 obesity produced significantly more free radicals, were larger and more granular and had a lower stimulation index (all p<0.05). CONCLUSIONS: Our results suggest that compared with obese individuals metabolically healthy individuals with obesity and type 2 diabetes have an impaired neutrophil function and T cell response on challenge despite having a T cell population expressing more activation markers which may be partly responsible for the increased prevalence of infection reported in this population.
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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 | 0.000 | 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) | 0.003 | 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".