Visualization of the relationship between macrophage and wound healing from the perspective of bibliometric analysis

Abstract

Macrophages play a crucial role in aiding all phases of the wound-healing process and has garnered increasing attention recently. Although a substantial body of related studies has been published, there remains a lack of comprehensive bibliometric analysis. In this study, we collected 4296 papers from the Web of Science Core Collection database. Three tools including CiteSpace, VOSviewer and one online analytical platform were employed to conduct bibliometric analysis and data visualization. Our results revealed that the annual number of publications related to macrophage and wound healing has increased exponentially with the year. The United States and China stand as the primary driving forces within this field, collectively constituting 58.2% of the total publication output. The application of biomaterials was one of the most concerned research areas in this field. According to references analysis, the current research focus has shifted to diabetic wound healing and regulating macrophage polarization. Based on the keywords analysis, we identified the following research frontiers in the future: exosomes and other extracellular vesicles; bio-derived materials and drug delivery methods such as nanoparticles, scaffolds and hydrogels; immunomodulation and macrophage polarization in the M2-state; chronic wounds, particularly those associated with diabetes; antimicrobial peptides; and antioxidant. Additionally, TNF, IL-6, IL-10, TGF-β1 and VEGF ranked as the five genes that have garnered the most research attention in the intersection of macrophage and wound healing. All in all, our findings offered researchers a holistic view of the ongoing progress in the field of macrophages and wound healing, serving as a valuable reference for scholars and policymakers in this domain.

Keywords: CiteSpace; VOSviewer; bibliometrics; macrophage; wound healing.

FIGURE 1

Screening process and research framework.

FIGURE 2

The number of publication and citation frequency for each year from 1995 to 2023. The plot in the upper left showed the fitting curve of annual publication from 1995 to 2022, and the equation Y = 29.713e^0.0888X (R ² = 0.9582, X was the year, Y was the annual outputs).

FIGURE 3

(A) The leading 10 journals based on publication counts. (B) Network visualization map of 219 co‐cited journals with more than 200 citation times. The size of the nodes represents the number of citations acquired by these journals. (C) The top 10 research domains organized by their respective publication counts. (D) A dual‐map overlay depicting the journals involved with macrophage and wound healing research. The map reveals three primary citation paths including one green path and two orange paths.

FIGURE 4

(A) The top 10 most prolific countries/regions in this field. (B) The total and average counts of citations in these top 10 countries/regions. (C) The annual published studies of top 10 countries/regions from 1995 to 2023. (D) Multinational cooperations between different countries/regions. The connecting lines between countries/regions indicate their cooperation, and the thickness of these lines indicates the close degree of cooperation. (E) Overlay visualization map of multinational co‐authorship analysis generated by VOSviewer. The colour spectrum indicates the corresponding average appearing year (AAY) of each country from 2012 (blue) to 2018 (red).

FIGURE 5

(A) The top 8 funding agencies that have sponsored this area. (B) The top 10 most prolific institutions based on publication quantity. (C) The cooperation visualization map generated by CiteSpace. Nodes embellished with purple outer rings indicate institutions with significant centrality, characterized by the betweenness centrality value surpassing 0.1. (D) The top 10 institutions with the highest betweenness centrality values.

FIGURE 6

(A) A visualization map depicting author co‐authorship clusters generated by VOSviewer. In total, 16 distinct research clusters have been identified, each marked by a consistent colour on the visualization map. (B) The top 10 authors based on the number of publications in this domain. (C) Network visualization map of author co‐citation analysis with more than 100 citations. (D) The top 10 authors with the highest total link strength.

FIGURE 7

(A) The network visualization map for document citation analysis presents nodes of varying sizes, where larger nodes indicate higher citation counts. (B) The top 15 studies with the highest citation times in this area.

FIGURE 8

(A) The network visualization map of reference co‐citation analysis constructed using CiteSpace. (B) A timeline view network map of co‐cited references. The utilization of the clustering function resulted in the division of the network map into distinct clusters. References within each cluster exhibit comparable research directions in contrast to references from other clusters. (C) The top 30 references with citation bursts. The red segment corresponds to the initiation and end years of the burst duration.

FIGURE 9

The annual change trend of related keywords in this area.

FIGURE 10

(A) Density visualization map of keywords co‐occurrence analysis. The heat map visually represents the frequency of keywords by employing a range of colour shades. Intense red shades indicate active research areas with a higher frequency of keyword occurrence, while cooler yellow shades depict less active areas with a lower frequency of keyword occurrence. (B) The top 15 most frequently used keywords in the research field. (C) The overlay visualization map showcases the analysis of keyword co‐occurrence. The visualization of keywords is organized according to the average publication year. Distinct colours are employed to indicate the corresponding publication year. Keywords in red denote more recent publications, whereas blue keywords signify older publications. (D) The top 15 keywords with the largest average appearing year.

FIGURE 11

The top 40 keywords with the strongest citation explosion.

FIGURE 12

(A) The top 17 most studied genes in the intersection of macrophage and wound healing. (B) The gene‐interacting network by using STRING tool. (C) The bubble plot showing the GO enrichment analyses of these top related genes.