Data Sheet 1_Exploring the neuroprotective potential of ligustrazine: a preclinical meta-a

23 preclinical studies involving 381 animals in a meta-analysis and 321 animals in a machine learning component form this dataset. It was created by Lang Tu and uploaded to figshare on 2026-05-11. The data supports an assessment of ligustrazine's efficacy in treating cerebral ischemia-reperfusion injury.

Use Cases

• Validate neuroprotective drug efficacy based on meta-analysis results for neurological function scores and infarct volume.
• Train predictive models for neurofunctional improvement based on intervention timing, dose, and duration.
• Optimize preclinical study design parameters using the machine learning-derived framework for administration windows and dosages.

Strengths

• Includes results from a systematic search across four major databases (PubMed, Embase, Web of Science, Cochrane Library).
• Quantitative analysis provides specific effect sizes (SMD) and confidence intervals for key outcomes like neurological function scores.
• Machine learning component identifies precise, data-driven intervention parameters (e.g., optimal dose range of 23.53–34.69 mg/kg/day).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is a 28.6 MB DOCX file, which may require parsing to extract structured data.

Provenance

Source

figshare

Collection Method

Systematic review and data extraction from published preclinical animal studies, followed by meta-analysis and machine learning modeling.

Time Range

Studies published up to June 25, 2024.

Freshness

Last updated 2026-05-11 05:28:37; freshness should be verified.