Copaiba oil improves pulmonary nitric oxide bioavailability in monocrotaline-treated rats
Bibliographic record
Abstract
Oxidative stress is involved in increased pulmonary vascular resistance (PVR) and right ventricular (RV) hypertrophy, characteristics of pulmonary arterial hypertension (PAH). Copaiba oil, an antioxidant compound, could attenuate PAH damage. This study’s aim was to determine the effects of copaiba oil on lung oxidative stress, PVR, and mean pulmonary arterial pressure (mPAP) in the monocrotaline (MCT) model of PAH. Male Wistar rats (170 g, n = 7/group) were divided into four groups: control, MCT, copaiba oil, and MCT + copaiba oil (MCT-O). PAH was induced by MCT (60 mg/kg i.p.) and, after 1 week, the treatment with copaiba oil (400 mg/kg/day gavage) was started for 14 days. Echocardiographic and hemodynamic measurements were performed. RV was collected for morphometric evaluations and lungs and the pulmonary artery were used for biochemical analysis. Copaiba oil significantly reduced RV hypertrophy, PVR, mPAP, and antioxidant enzyme activities in the MCT-O group. Moreover, increased nitric oxide synthase and decreased NADPH oxidase activities were observed in the MCT-O group. In conclusion, copaiba oil was able to improve the balance between nitric oxide and reactive oxygen species in lungs and the pulmonary artery and to reduce PVR, which could explain a decrease in RV hypertrophy in this PAH model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".