Evidence of clinical efficacy and pharmacological mechanism of N-butylphthalide in the treatment of delayed encephalopathy after acute carbon monoxide poisoning
Bibliographic record
Abstract
Objective: Based on network meta-analysis (NMA) and network pharmacology approaches, we explored the clinical efficacy of different regimens, and clarified the pharmacological mechanisms of N-butylphthalide (NBP) in the treatment of delayed encephalopathy after acute carbon monoxide poisoning (DEACMP). Methods: Firstly, NMA was conducted to obtain the ranking of the efficacy of different regimens for the treatment of DEACMP. Secondly, the drug with a relatively high efficacy ranking was selected and its mechanism of treatment for DEACMP was identified through a network pharmacology analysis. By the use of protein interaction and enrichment analysis, the pharmacological mechanism was predicted, and molecular docking was subsequently carried out to verify the reliability of the results. Results: A total of 17 eligible randomized controlled trials (RCTs) involving 1293 patients and 16 interventions were eventually included in our analysis from NMA. Mesenchymal stem cells (MSCs) + NBP significantly increased mini-mental state examination (MMSE) and Barthel index (BI) scores; NBP + dexamethasone (DXM) was the most effective treatment in improving the activity of daily living (ADL) scores; NBP significantly decreased national institutes of health stroke scale (NIHSS) scores; Xingzhi-Yinao granules (XZYN) had more advantages in improving Montreal cognitive assessment (MoCA) scores, translational direct current stimulation (tDCS) had a significant effect in improving P300 latency and P300 amplitude and Kinnado + Citicoline had the most obvious effect in improving malondialdehyde (MDA). Meanwhile, by network pharmacology analysis, 33 interaction genes between NBP and DEACMP were obtained, and 4 of them were identified as possible key targets in the process of MCODE analysis. 516 Gene ontology (GO) entries and 116 Kyoto Encyclopedia of Gene and Genome (KEGG) entries were achieved by enrichment analysis. Molecular docking showed that NBP had good docking activity with the key targets. Conclusion: signaling pathway.
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.020 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".