Catecholamines?? Enhancement of Inducible Nitric Oxide Synthase-Induced Nitric Oxide Biosynthesis Involves CAT-1 and CAT-2A
Bibliographic record
Abstract
Catecholamines enhance inducible nitric oxide synthase (iNOS) expression that results in nitric oxide (NO) overproduction in lipopolysaccharide (LPS)-stimulated macrophages. L-arginine transport mediated by cationic amino acid transporters (including CAT-1, CAT-2, CAT-2A, and CAT-2B) is crucial in regulating iNOS activity. We sought to assess the effects of catecholamines on L-arginine transport and CAT isozyme expression in stimulated macrophages. Confluent RAW264.7 cells were cultured with LPS with or without catecholamines (epinephrine or norepinephrine, 5 x 10(-6) M) for 18 h. NO production, L-arginine transport, and enzyme expression were determined. Our data revealed that LPS co-induced iNOS, CAT-2, and CAT-2B expression, whereas CAT-1 and CAT-2A expression remained unaffected. Significant increases in NO production and L-arginine transport (approximately eight-fold and three-fold increases, respectively) were found in activated macrophages. Catecholamines significantly enhanced NO production and L-arginine transport (approximately 30% and 20% increases, respectively) in activated macrophages. Catecholamines also enhanced the expression of iNOS, CAT-1, and CAT-2A but not CAT-2 or CAT-2B in LPS-stimulated macrophages. Furthermore, the enhancement effects of catecholamines were inhibited by either dexamethasone or propranolol. We provide the first evidence to indicate that L-arginine transport in activated macrophages could be enhanced by catecholamines. Furthermore, this catecholamine-enhanced L-arginine transport might involve CAT-1 and CAT-2A but not CAT-2 or CAT-2B.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".