Table 1_Trained immunity in inflammatory bone disease: a bibliometric and literature-level

A bibliometric and literature-level text-mining analysis of research on trained immunity in inflammatory bone disease. The analysis includes a core corpus of 83 records and an extended corpus of 301 records, sourced from Web of Science Core Collection, Scopus, and PubMed. The dataset was created by Zihang Zhao and last updated in May 2026.

Use Cases

• Identify key disease contexts like periodontitis and osteoarthritis based on the disease-context mapping results.
• Analyze literature-level patterns involving myeloid-cell reprogramming and epigenetic remodeling based on the semantic screening.
• Track publication trends and cross-database concordance for the field from 2013 to 2025.
• Explore bridge-network mappings to understand connections between trained immunity concepts and bone disease pathways.

Strengths

• Includes a defined temporal comparison window from 2013 to 2025, with publication output quantified.
• Uses a two-corpus design with 83 core and 301 extended records for robust analysis.
• Performs cross-database comparison across three major sources (WoSCC, Scopus, PubMed) showing concordant trends.
• Applies multiple analytical methods including topic modeling, TF-IDF screening, and bridge-network mapping.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 21.0 KB, indicating limited raw data scope.

Provenance

Source

figshare

Collection Method

Bibliometric and literature-level text-mining analysis using Web of Science Core Collection as primary source, with queries to Scopus and PubMed.

Time Range

2013-2025

Freshness

Last updated 2026-05 20 04:33:05; freshness should be verified.

Geography

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