D-pinitol modulates the anti-emetic effects of aprepitant, domperidone, and ondansetron in chicks
Bibliographic record
Abstract
Naturally occurring substance, D-pinitol (DPL) belongs to the significant inositol family has numerous pharmacological activity. In this study we evaluated the anti-emetic effect as well as modulation activities of DPL on the recent market drugs aprepitant (APR), domperidone (DOM), hyoscine butyl bromide (HYS), and ondansetron (ODN) on emesis in the chick model. To highlight the possible anti-emetic activity in copper sulfate induced emesis chick models, we use several reference drugs, such as APR (26 mg/kg), DOM (7 mg/kg), OND (5 mg/kg), and HYS (21 mg/kg), as positive controls, while the vehicles serve as negative controls. All reference drugs are given alone or in combined groups to evaluate their anti-emetic and modulation effects. The results suggest DPL (25 or 50 mg/kg) increases the mean number of latency in the chicks compared to vehicles, and the combination groups, DPL (25 mg/kg) showed better anti-emetic effects with DOM and ODN while DPL (50 mg/kg) reduces the number of retches compared to vehicles and combined drug therapy with reference drugs. Additionally, A variety of computational algorithms were used to visualise ligand-receptor interactions and quantify the binding affinities of DPL and other ligands towards the dopamine receptors (D2 and D3), muscarinic acetylcholine receptors (M1-M5), and serotonin receptor (5HT3). The molecular docking study indicated that DPL exhibits the highest binding affinity towards subtypes M2 (having a docking score of -5.7 kcal/mol) and D3 (having a docking score of -5.7 kcal/mol) in comparison to certain standards for these receptors, which have docking scores of DOM (-9.7 kcal/mol) and HYS (-7.1 kcal/mol) for M2 and D3, respectively. Our findings suggest that DPL has anti-emetic properties in chicks, possibly through interactions with the M2 and D3 receptor pathways.
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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".