Monoamine oxidase is a source of oxidative stress in obese patients with chronic inflammation
Bibliographic record
Abstract
Obesity is an important preventable risk factor for morbidity and mortality from cardiometabolic disease. Oxidative stress (including in visceral adipose tissue) and chronic low-grade inflammation are the major underlying pathomechanisms. Monoamine oxidase (MAO) has recently emerged as an important source of cardiovascular oxidative stress. The present study was conducted to evaluate the role of MAO as contributor to reactive oxygen species (ROS) production in white adipose tissue and vessels harvested from patients undergoing elective abdominal surgery. To this aim, visceral adipose tissue and mesenteric artery branches were isolated from obese patients with chronic inflammation and used for organ bath, ROS production, quantitative real-time PCR, and immunohistology studies. The human visceral adipose tissue and mesenteric artery branches contain mainly the MAO-A isoform, as shown by the quantitative real-time PCR and immunohistology experiments. A significant upregulation of MAO-A, the impairment in vascular reactivity, and increase in ROS production were found in obese vs. non-obese patients. Incubation of the adipose tissue samples and vascular rings with the MAO-A inhibitor (clorgyline, 30 min) improved vascular reactivity and decreased ROS generation. In conclusion, MAO-A is the predominant isoform in human abdominal adipose and vascular tissues, is overexpressed in the setting of inflammation, and contributes to the endothelial dysfunction.
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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) | 0.001 | 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".