Visual analysis of research status and hotspots of Pinellia ternata from 2004 to 2025: A bibliometric review

Abstract

Pinellia ternata has been widely recognized as a traditional Chinese medicine for its use in digestive system diseases and cancers. Furthermore, its good clinical efficacy, excellent safety, and limited side effects have attracted growing interest from research institutions in China, South Korea, the United States, and Japan, resulting in a surge of associated studies. However, the information remains scattered, lacking systematic summaries. This makes it challenging to consolidate the extent of the research progress. Thus, in this study, data from published literature were obtained and assessed to assist researchers in comprehending the current research landscape in the field and to investigate research hotspots and emerging frontiers. Two English databases were employed to search and download the literature on P ternata research published from 2004 to 2025. We used VOSviewer, Microsoft Excel, and CiteSpace to visually analyze annual publishing trends, publishing countries, institutions, authors, journals, keywords, and references in the field. We retrieved 488 papers. Publications have increased annually, particularly in 2024. China, South Korea, the United States, and Japan take the lead in this field of research. Nanjing University of Chinese Medicine produced the largest number of papers. The Journal of Ethnopharmacology contained the most publications. The most prolific authors are Xue Jianping and Xue Tao. Keywords with the highest frequency were P. ternata, expression, banxia xiexin decoction, and network pharmacology. Twelve clusters and twenty-five burst keywords were generated. To date, 3 areas have been the primary subject of this field’s research: research on related classic prescriptions and their applications, research on pharmacological components and mechanisms of action, and research on cultivation and quality control. Furthermore, research on microscopization, normalization, standardization, and objectification of traditional Chinese medicine has also been developing.

1. Introduction

Pinellia ternata (Thunb.) Breit or banxia is a widely utilized Chinese herb initially documented in the^[1] Shennong Herbal Classic.^[2] In traditional Chinese medicine (TCM), it is traditionally recognized for its therapeutic role in drying out dampness, transforming phlegm, descending counterflow to alleviate vomiting, and relieving distension and dissolving nodules.^[1] According to the latest medical research, it offers pharmacological benefits that include the reduction of blood lipids, relieving cough, expectorant, antitumor, and anti-gastric ulcer.^[2] Furthermore, due to its good clinical efficacy, excellent safety, and limited side effects, it is often used to treat gastrointestinal diseases and cancer.^[3] In addition, its application has drawn more attention in the US, Japan, South Korea, Australia, and other nations.^[4–6] Pinellia ternata (P. ternate) can also be used for various other diseases, such as ulcerative colitis,^[7] polycystic ovary syndrome,^[8] gastric cancer,^[9] Alzheimer’s disease,^[10] and non-small cell lung cancer.^[11] As recent pharmacological investigations have confirmed, P ternata is rich in various compounds like alkaloids, iridoid glycosides, anthraquinones, iridoids, anthraquinone glycosides, fatty acids, and their derivatives.^[12] Further research indicates that its potential medical applications include acting as an antidepressant, anti-inflammatory, and anticancer agent, and as a treatment for cough, vomiting, and certain gastrointestinal disorders.^[12]

Extensive research on P ternata over the past 2 decades reveals research frontiers focusing on clinical trials,^[13] cell experiments,^[14] animal experiments,^[15] toxicology research,^[16] cultivation studies,^[17] and reviews.^[18] However, research on this topic is scattered and disorganized, with only a limited number of systematic summaries and thorough analyses performed. Consequently, utilizing bibliometrics and visual analysis technology, this study aims to gather and examine data from the published literature to assist researchers in comprehending the present state of research in this domain and to investigate research frontiers and hot spots.

The term bibliometrics was first introduced in a 1969 paper as a replacement for the older term statistical bibliography. This field examines academic publishing through the use of statistics to illustrate publishing trends and emphasizes the connections among published works.^[19] Based on the research, visualization software such as CiteSpace can objectively and fully reflect the development of related fields.^[20]

Using a bibliometric approach, we examined P ternata publications. We also systematically assessed the state of recent P. ternata, current research priorities, and emerging research trends for systematic evaluation, highlighting significant findings and suggesting future research avenues. Moreover, we aim to serve as a resource and guidance for upcoming scientific and clinical investigations.

2. Methods

2.1. Search strategies

It is well known that the WOS core collection and PubMed database are the most authoritative English literature databases in the world, with high-quality literature included. At the same time, the citation information in these 2 databases is complete, standardized, and the export format is standard, which is suitable for visualization analysis software such as CiteSpace and VOSviewer. However, the Chinese databases have variable quality of the included literature and incomplete citation information, making it impossible to conduct reference literature analysis. Therefore, a literature search on P ternata was conducted in the Web of Science Core Collection and PubMed databases. The search formula of the WOS Core Collection database is: TS = (P ternata OR Pinelliae Rhizoma OR Pinellia OR Ban xia OR BanXia OR tuber of Pinellia OR Pinellia tuber OR Rhizoma Pinelliae OR Ternate Pinellia). The search formula in the PubMed database is: P. ternata[Title/Abstract] OR Pinelliae Rhizoma[Title/Abstract] OR Pinellia[Title/Abstract] OR Ban xia[Title/Abstract] OR BanXia[Title/Abstract] OR tuber of Pinellia[Title/Abstract] OR Pinellia tuber[Title/Abstract] OR Rhizoma Pinelliae[Title/Abstract] OR Ternate Pinellia[Title/Abstract]. The search was restricted to published English-language articles from January 1, 2004, to September 30, 2025, published only in English. The retrieved literature was exported in “full records and cited literature” format.^[21] The first author and the second author independently screened the literature based on the predefined inclusion and exclusion criteria. After the screening process, they compared the results. In case of disagreement, they sought the opinion of the corresponding author.

2.2. Data inclusion and exclusion criteria

The inclusion criteria encompassed both articles and review articles related to P ternata research. The criteria for exclusion included the following: letters, notes, and corrections; literature not related to the subject of this study; repeated publications; retracted articles; studies with incomplete or unidentifiable information, such as title, abstract, keywords, and author.

2.3. Data standardization

The complete and thorough research literature was integrated with synonymous keywords, in accordance with the established standards of traditional Chinese medicine terminology.^[22] The names of institutions were processed according to the information available on their official websites. In cases where authors shared the same surname, the decision for their inclusion was determined by factors such as their affiliated institution and the content of their research.

2.4. Data analysis and mapping

We exported the final documents and named the file “download.” CiteSpace 6.4.R2 software was utilized for complete data conversion and creating the visualization map. The parameters were established as follows: time slicing = January 2004 to September 2025, selection criteria = top 50, and years per slice = 1. For pruning, we used Pruning Tender Networks, Pathfinder, with the remainders of the sections left as default. Based on the purpose of this research, we selected “country or keyword” for the node type area. We used keyword select burst detection from the “Keyword Analysis” submenu. Centrality is a crucial metric in network analysis used to quantify the impact of a node within a network. The higher the centrality of a node, the greater its function within the network structure.^[23,24]

VOSviewer 1.6.18.0 software parameters included: institution publications ≥3, journal publications ≥2, journal citations ≥20, author publications ≥3, author citations ≥10, reference citations ≥5, while all other settings remained at their default values.^[25,26]

We also use Bioinformatics (www.bioinformatics.com.cn) and Bibliometrics (bibliometric.com) for the analysis and drawing of the data. Data statistics and tabulation were conducted using Microsoft Office Excel 2019.^[25,26]

3. Results

3.1. General information

The total count of articles on this subject has reached 1640 since 2004 across these 2 databases. Following the application of the inclusion and exclusion criteria, the final articles included in this study were 488 articles. The literature selection and processing flowchart is depicted in Figure 1.

Figure 1.

Flowchart of literature selection.

3.2. Annual publication output and the distribution of countries or territories

The annual publication count of papers serves as a significant indicator of the developmental trend within the field and, to a degree, reflects the rising interest and knowledge progress of the discipline.^[27,28] As illustrated in Figure 2A, 454 articles and 34 reviews were ultimately included in this study. The annual publication numbers for the past 22 years are graphically represented in a histogram, as depicted in Figure 2B, with various colors employed to distinguish annual publication numbers for different countries or territories. Between 2004 and 2025, the number of publications increased, with China as the primary authorship country. The trend in the publication in this field can be broadly classified into 2 phases. The initial phase, spanning from 2004 to 2017, exhibited a relatively stable trend with a slight increase. Conversely, the second phase, from 2018 to 2025, demonstrated a pronounced upward trend in the volume of published articles. An overall analysis of the trend reveals that research related to P ternata is progressing and garnering more attention, having entered a phase of rapid development, particularly over the last 8 years.

Figure 2.

(A) Types and proportions of literature, (B) Annual number of publications, (C) Distribution of P ternata studies worldwide, (D) Map of cooperation of countries/territories, (E) Countries/territories collaboration map.

Collaboration maps can show the collaboration between countries or regions in the research field, to provide a reference for evaluating the academic influence of a country or region.^[29,30] Nineteen countries and territories have participated in the research of P. ternata, with the number of publications issued by each country or territory illustrated in Figure 2C. Four countries/territories have published more than 10 papers, namely, China (n = 445), South Korea (n = 25), the United States (n = 14), and Japan (n = 14). The top 5 countries are displayed in Table 1.

Table 1.

The top 5 countries/territories with the highest P. ternata-related research productivity.

Rank	Country	Yr	Publications (%)	Centrality
1	China	2004	445 (91.19)	1.09
2	South Korea	2005	25 (5.12)	0.32
3	Japan	2005	14 (2.87)	0
4	USA	2008	14 (2.87)	0.04
5	Canada	2012	3 (0.61)	0

Figures 2D and 2E illustrate the collaborations and research duration between different countries. The research in this field was first carried out in countries/territories such as the People’s Republic of China and England in 2004, followed by related studies beginning in South Korea and Japan in 2005. The highest centrality ranking was noted in China (1.09), followed by South Korea (0.32) and Japan (0.04).

3.3. Distribution of institutions

Figure 3A illustrates that 478 institutions have carried out research in this area, with 16 of those institutions publishing more than 10 papers each. Nanjing University of Chinese Medicine (n = 28) published the most papers, followed by Chengdu University of Traditional Chinese Medicine (n = 23), China Academy of Chinese Medical Sciences (n = 23), Chinese Academy of Sciences (n = 22), and Zhejiang Sci-Tech University (n = 21). Chinese Academy of Sciences has the highest centrality (0.24), followed by China Academy of Chinese Medical Sciences (0.17), Nanjing University of Chinese Medicine (0.15), and Zhejiang Sci-Tech University (0.10). The top 10 institutions by publication volume are displayed in Table 2. The publication status of various institutions over time is displayed in Figure 3B. The density diagram of the number of articles published by the institutions is displayed in Figure 3C. The warmer the color, the higher the volume of articles issued by the institutions.

Figure 3.

(A) Map of institutional partnerships, (B) Overlay map of the institutions, (C) Density map of the institutions.

Table 2.

Top 10 institutions by publications.

Rank	Institutions	Yr	Publications (%)	Centrality
1	Nanjing University of Chinese Medicine	2009	28 (5.74)	0.15
2	Chengdu University of Traditional Chinese Medicine	2006	23 (4.71)	0.04
3	China Academy of Chinese Medical Sciences	2011	23 (4.71)	0.17
4	Chinese Academy of Sciences	2005	22 (4.51)	0.24
5	Zhejiang Sci-Tech University	2008	21 (4.30)	0.10
6	Huaibei Normal University	2013	20 (4.10)	0.03
7	Shandong University of Traditional Chinese Medicine	2010	18 (3.69)	0.02
8	Shanghai University of Traditional Chinese Medicine	2014	18 (3.69)	0.03
9	Guangzhou University of Chinese Medicine	2013	17 (3.48)	0.07
10	Hubei University of Chinese Medicine	2016	17 (3.48)	0.04

3.4. Productive journals and co-cited journals

We examined the journals and co-cited journals to determine the ones with the greatest number of publications and co-citations related to P. ternata. As shown in Figure 4A, the results indicated that out of 231 journals related to the research literature on P. ternata, 76 journals published more than 2 articles: Journal of Ethnopharmacology (n = 45), followed by Medicine (n = 18), Evidence-Based Complementary and Alternative Medicine (n = 17), and Phytomedicine (n = 11). Figure 4B illustrates the publication trends of various journals throughout the years. Figure 4C presents the density diagram depicting the quantity of articles issued by these journals. The greater the number of articles published, the more intense the color.

Figure 4.

(A) Map of the journals, (B) Overlay map of the journals, (C) Density map of the journals.

A total of 4831 journals were cited, with 184 of them being cited more than 20 times. Figure 5A shows the status of the co-cited journals, while Figure 5B shows the density of the co-cited journals. The Journal of Ethnopharmacology has the highest number of co-citations (n = 611), next is the International Journal of Molecular Sciences (n = 280), Scientific Reports (n = 248), Frontiers in Plant Science (n = 240), and Nucleic Acids Research (n = 240). Table 3 lists the top 10 journals based on the quantity of citations or publications.

Figure 5.

(A) Map of co-cited journals, (B) Density map of the co-cited journals, (C) Dual-map overlay of journals.

Table 3.

The top 10 journals and co-cited journals related to Pinellia ternata.

Rank	Journal	Publications (%)	IF/JCR (2025)	Co-cited journal	citations	IF/JCR (2025)
1	Journal of Ethnopharmacology	45 (9.22)	5.4/Q1	Journal of Ethnopharmacology	611	5.4/Q1
2	Medicine	18 (3.69)	1.4/Q2	International Journal of Molecular Sciences	280	4.9/Q1
3	Evidence-Based Complementary and Alternative Medicine	17 (3.48)	2.65/Q3	Scientific Reports	248	3.9/Q1
4	Phytomedicine	11 (2.25)	8.3/Q1	Frontiers in Plant Science	240	4.8/Q1
5	Frontiers in Plant Science	10 (2.05)	4.8/Q1	Nucleic Acids Research	240	13.1/Q1
6	Frontiers in Pharmacology	8 (1.64)	4.8/Q1	PLOS ONE	215	2.6/Q2
7	International Journal of Molecular Sciences	8 (1.64)	4.9/Q1	Evidence-Based Complementary and Alternative Medicine	193	2.65/Q3
8	Molecules	8 (1.64)	4.6/Q2	Plant Physiology	168	6.9/Q1
9	Scientific Reports	8 (1.64)	3.9/Q1	Frontiers in Pharmacology	157	4.8/Q1
10	Chinese Journal of Integrative Medicine	7 (1.43)	2.5/Q2	International Journal of Biological Macromolecules	152	8.5/Q1

Data obtained from https://www.iikx.com.

Figure 5C presents a dual-map overlay of journals. The subject areas of this study cited in the journals are positioned on the left of the graph, while the subject areas of the cited journals are positioned on the right The curve in the figure illustrates the trajectory of literature in the field of P ternata research across disciplines. As depicted in the figure, there are 3 main reference tracks: veterinary/animal/science to environmental/ toxicology/ nutrition, veterinary/ animal/ science to molecular/ biology/ genetics, and molecular/ biology/ immunology to molecular/ biology/ genetics.

3.5. Analysis of authors and co-cited authors

There were studies published by 2581 authors in the final literature included in the study, with 150 of them having published over 3 articles. Table 4 presents the 10 authors who published the most papers. As shown, Xue Jianping and Xue Tao published the most articles with a total of 17, followed by Duan Yongbo (n = 15), Chen Jishuang (n = 10), Liu Dahui (n = 10), Miao Yuhuan (n = 10), and Yao Xiaoqin (n = 10). According to the network of authors participating in the study of P ternata (Fig. 6A), it was observed that there were more small teams of researchers, yet there was a reduced level of cooperation between these teams, and the researchers exhibited a low degree of centrality. Figure 6B presents a time series diagram of researchers, depicting their status across various periods. Red in the diagram represents recent researchers, such as Luo Ming, Zhang Lulu, and Ji Ensheng. Figure 6C shows the density diagram of the number of articles issued by the authors. A higher number of articles published by the authors corresponds to a more intense color.

Table 4.

Top 10 authors by publication or cited authors by count.

Rank	Authors	Publications (%)	Institutions	Cited authors	Citations
1	Xue Jianping	17 (3.48)	Huaibei Normal University	Wang Y	61
2	Xue Tao	17 (3.48)	Huaibei Normal University	Li Y	52
3	Duan Yongbo	15 (3.07)	Huaibei Normal University	Ji X	51
4	Chen Jishuang	10 (2.05)	Nanjing Tech University/Zhejiang Sci-Tech University	Zhang Y	51
5	Liu Dahui	10 (2.05)	Hubei University of Chinese Medicine	Mao Rj	49
6	Miao Yuhuan	10 (2.05)	Hubei University of Chinese Medicine	Yao Jh	48
7	Yao Xiaoqin	10 (2.05)	Hebei University	Xue T	43
8	Chu Jianzhou	9 (1.84)	Hebei University	Liu Y	40
9	Zhu Yanfang	9 (1.84)	Huaibei Normal University	Zhang Zh	40
10	Luo Ming	8 (1.64)	Hubei University of Chinese Medicine	Wang J	39

Figure 6.

(A) Map of authors, (B) Overlay map of the authors, (C) Density map of the authors.

Co-cited authors denote two or more authors whose works are cited together in the reference list of a third, later publication. There are 13,107 co-cited authors in this field, with 177 authors cited more than 10 times, as Figure 7A illustrates. In Figure 7B, a brighter red indicates a greater number of citations. The author who had the most co-citations was Wang Y (n = 61), followed by Li Y (n = 52), Ji X (n = 51), and Zhang Y (n = 51). Table 4 lists the top 10 authors with the most citations overall.

Figure 7.

(A) Map of co-cited authors, (B) Density map of the co-cited authors.

3.6. Analysis of keywords

3.6.1. Co-occurrence of keywords analysis

Keywords represent both the paper’s central idea and encapsulate the most important concepts of a research paper.^[31,32] Therefore, analyzing keywords is fundamental to understanding a research field’s themes, identifying core topics, and pinpointing emerging trends and frontiers.^[33] After replacing synonyms or similar words, we obtained a keyword co-occurrence graph.

Figure 8A shows that there were 535 keywords and 1552 lines, and the density value was 0.0109. Each node signifies a keyword, with the size of the circle indicating the frequency of that keyword. Each circle consists of several concentric color rings; the color of these rings denotes the publication time of papers that include the relevant keywords, while the width of the color ring reflects the quantity of papers published over time. The thickness of the line reveals how often 2 keywords appear together. The keywords with the highest frequency include P ternata (n = 129), expression (n = 59), banxia xiexin decoction (n = 54), and network pharmacology (n = 38). Keywords with high centricity were P ternata (0.51), expression (0.22), acid (0.21), cells (0.17), gene (0.15), accumulation (0.13), and apoptosis (0.12). The top 20 keywords with the most frequency are listed in Table 5. As shown in Figure 8B, it presents the prevalence of a few high-frequency keywords in different years.

Figure 8.

(A) Map of keywords co-occurrence, (B) The occurrence of keywords in different years.

Table 5.

The top 20 keywords associated with the Pinellia ternata.

Rank	Keywords	Count	Centrality	Rank	Keywords	Count	Centrality
1	Pinellia ternata	129	0.51	11	Activation	18	0.07
2	Expression	59	0.22	12	Stress	16	0.03
3	Banxia xiexin decoction	54	0.08	13	Acid	16	0.21
4	Network pharmacology	38	0.03	14	Molecular docking	15	0.01
5	Traditional Chinese medicine	31	0.07	15	Mechanisms	14	0.08
6	Apoptosis	27	0.12	16	Arabidopsis	12	0.06
7	Growth	27	0.09	17	Accumulation	12	0.13
8	Gene	22	0.15	18	Inflammation	12	0.02
9	Cells	21	0.17	19	Disease	12	0.08
10	Tolerance	18	0.05	20	Identification	11	0.11

3.6.2. Keyword cluster analysis

Figure 9A depicts the keywords in a clustering graph. The research in this area can be roughly categorized into 12 clusters. The keywords time graph, which illustrates the evolution trajectory of high-frequency keywords in each cluster, is provided in Figure 9B. Furthermore, the graph can aid in identifying the development trajectory of research periods and research directions related to particular subjects. Table 6 shows the detailed information and representative keywords of each cluster.

Figure 9.

(A) Keywords clustering graph, (B) Timeline view of keywords.

Table 6.

Keyword clustering data sheet.

ClusterID	Size	Silhouette	Mean (Yr)	Representative keywords
#0	78	0.836	2015	Pinellia ternata, toxicity, quality evaluation, biological control, morphological characteristics
#1	67	0.749	2019	Banxia xiexin decoction, molecular docking, network pharmacology, performance liquid chromatography, quantitative analysis
#2	58	0.809	2016	Arabidopsis, gene expression, drought, tolerance, biosynthesis
#3	46	0.861	2013	Autophagy, apoptosis, inflammation, oxidative stress, gut microbiota
#4	39	0.923	2012	Pinellia ternata agglutinin, molecular mechanisms, berberine, baicalein, ephedrine
#5	33	0.868	2017	Antioxidant, antibacterial activity, signaling pathway, cardiac hypertrophy, acetylcholinesterase biosensor
#6	32	0.933	2009	MicroRNA, biological control, microarray, complementary, prevention
#7	31	0.802	2017	Brassinolide, quercetin, cells, mice, rats
#8	29	0.947	2011	Banxia houpu decoction, mechanisms, neurotransmitter levels, orthogonal array design, dementia
#9	28	0.948	2011	Functional dyspepsia, cancer, gastric cancer, ulcerative colitis, colorectal cancer
#10	21	0.928	2009	Extracts, constituents, acid, polysaccharide, constituents
#11	20	0.873	2019	Banxia baizhu tianma decoction, traditional Chinese medicine, gualou xiebai banxia decoction, gansui banxia decoction, classical prescription

The earliest detected cluster of keywords showed that #6 microRNA and #8 banxia houpu decoction first appeared in 2004. The latest and shortest cluster detected was #11 banxia baizhu tianma decoction, which appeared in 2017 and lasted for 9 years until 2025. The longest-lasting clusters were #0 p.ternata, #1 banxia xiexin decoction, #2 arabidopsis, #9 functional dyspepsia, and #8 banxia houpu decoction, which all lasted for 21 years. Among them, the clustering association of Arabidopsis and P ternata reflects the core paradigm in medicinal plant research that uses model plants to analyze gene functions. This clustering methodologically established a replicable path for the functional research of non-model medicinal plants, focusing on the analysis of stress resistance mechanisms for industrial bottlenecks such as “reversal of growth” in Gastrodia, promoting the interdisciplinary integration of traditional Chinese medicine and molecular plant science, and providing gene targets for molecular breeding of medicinal plants. The initial 4 clusters lasted from 2005 to 2025, while the final cluster lasted from 2004 to 2024. The clusters projected to extend until 2025 include #0 p. ternata, #1 banxia xiexin decoction, #2 arabidopsis, #3 autophagy, #4 P ternata agglutinin, #5 antioxidant, #7 brassinolide, #9 functional dyspepsia, and #11 banxia baizhu tianma decoction, indicating that they have notable research prospects.

3.6.3. Burst keywords analysis

Burst detection algorithms identify periods of unusually high activity or frequency of an event within a stream of data. In the context of research content and keywords, this involves analyzing the temporal distribution of keywords to pinpoint significant shifts in their prevalence over time.^[31,34] The intensity value serves as an index that quantifies the severity of the citation outbreak; thus, a higher intensity value indicates a more significant outbreak. Figure 10 illustrates the top 25 keywords associated with outbreak value. The length of the outbreak ranged from 2 to 8 years, and the intensity ranged from 1.63 to 4.57. Oxidative stress had the highest intensity (4.57). The longest duration was p.ternata agglutinin (n = 8). Keywords like tolerance, oxidative stress, network pharmacology, traditional Chinese medicine, molecular docking, berberine, and gualou xiebai banxia decoction continue to persist to today, suggesting that they remain a focal point for future research.

Figure 10.

Top 25 keywords with the strongest citation bursts.

3.7. Analysis of references

Figure 11A illustrates the map of co-cited references. Figure 11B depicts the density of references that have received a significant number of citations. The more times they are cited, the redder the color. The citations that were referenced most often were found in the paper authored by Ji X, which was published in Fitoterapia in 2014. The 10 most cited articles are sorted as shown in Table 7.^{[1,12,35–42]} Citation bursts are sudden, significant surges in the number of times a paper, author, or keyword is cited during a specific time period. Figure 11C depicts the top 25 most cited references. In the results of explosion intensity, Bai J^[1] had the highest explosion intensity, which was 8.65. In addition, Mao RJ,^[12] Sun LM,^[43] Peng W,^[18] Wang WW,^[44] Tian C^[45] and so on received more attention.

Figure 11.

(A) Map of co-cited references, (B) Density map of the co-cited references, (C) Top 25 co-cited references with the strongest citation bursts.

Table 7.

Top 10 most cited publications.

Rank	First author	Title	Journal	Yr	Citation	References
1	Ji X	The ethnobotanical, phytochemical and pharmacological profile of the genus Pinellia	Fitoterapia	2014	51	[35]
2	Mao RJ	Pinellia ternata (Thunb.) Breit: A review of its germplasm resources, genetic diversity and active components	J Ethnopharmacol	2020	46	[12]
3	Bai J	A comprehensive review on ethnopharmacological, phytochemical, pharmacological and toxicological evaluation, and quality control of Pinellia ternata (Thunb.) Breit	J Ethnopharmacol	2022	36	[1]
4	Wu XY	Sedative, hypnotic and anticonvulsant activities of the ethanol fraction from Rhizoma Pinelliae Praeparatum	J Ethnopharmaco	2011	32	[36]
5	Chen JH	Pinelloside, an antimicrobial cerebroside from Pinellia ternata	Phytochemistry	2003	30	[37]
6	Kim YJ	Anti-obesity effect of Pinellia ternata extract in Zucker rats	Biol Pharm Bull	2006	27	[38]
7	Ru JL	TCMSP: a database of systems pharmacology for drug discovery from herbal medicines	J Cheminform	2014	27	[39]
8	Chen G	Banxia xiexin decoction protects against dextran sulfate sodium-induced chronic ulcerative colitis in mice	J Ethnopharmacol	2015	22	[40]
9	Livak KJ	Analysis of relative gene expression data using real-time quantitative PCR and the 2 (-Delta Delta C(T)) Method	Methods	2001	22	[41]
10	Luo L	Antidepressant effects of Banxia Houpu decoction, a traditional Chinese medicinal empirical formula	J Ethnopharmacol	2000	22	[42]

4. Discussion

4.1. Hotspots and frontiers

Considering the restrictions imposed by elements such as geographical location and academic discipline, collaboration among authors is notably limited, leading to a relatively modest level of cooperation. It is recommended that in the future, scholars take the initiative to facilitate and engage in comprehensive exchanges across various regions and disciplines to advance the progress of related research and fields concerning the traditional Chinese medicine P. ternata. The main research directions of P ternata include active components, molecular targets, signaling pathways, core pharmacological effects, classical formulas, and clinical applications. The main chemical components contained in P ternata include alkaloids, volatile oils, organic acids, polysaccharides, amino acids, and proteases. It acts on multiple signaling pathways. The nuclear factor-kappa B pathway is the core regulatory pathway of inflammatory response, and P ternata exerts anti-inflammatory effects by inhibiting nuclear factor-kappa B activation. The mitogen-activated protein kinase pathway regulates cell proliferation, differentiation, and apoptosis. The PI3K/protein kinase B pathway is a key pathway for cell survival and metabolism, which is closely related to tumor occurrence and development. The wingless-related integration site/beta-catenin pathway regulates cell proliferation and tissue development. The Janus kinase/signal transducer and activator of transcription of transcription pathway mediates cytokine signal transduction and participates in immune regulation. The nuclear factor erythroid 2-related factor 2/Heme Oxygenase pathway is the core pathway of antioxidant stress. P ternata can regulate multiple targets, such as inflammatory factors including tumor necrosis factor-alpha, interleukin-6, and interleukin-1 beta, apoptosis-related proteins including B-cell lymphoma-2, B-cell lymphoma-2 associated X protein, and cysteine-aspartate protease-3, nervous system regulation-related targets including 5-Hydroxytryptamine, dopamine, and gamma-aminobutyric acid, regulatory enzymes including cyclooxygenase, inducible nitric oxide synthase, and angiotensin-converting enzyme, immune-related targets including T helper 1 cell, T helper 2 cell, and Interferon-gamma, and oxidative stress-related indicators including SOD, Catalase, and malondialdehyde.

The pharmacological effects of P ternata include antitussive and expectorant effects, antiemetic effects, anti-inflammatory andanti-swelling effects, immune regulation, antitumor effects, and blood lipid reduction. Traditional Chinese medicine has the characteristic of syndrome differentiation and treatment, and P ternata can be used to compose multiple classical formulas, such as Banxia Xiexin Decoction, Banxia Houpu Decoction, Banxia Baizhu Tianma Decoction, Xiao Banxia Decoction, Gualou Xiebai Banxia Decoction, and Wendan Decoction. It can be widely applied to multi-system diseases. Respiratory system diseases include cough, asthma, and bronchitis. Digestive system diseases include vomiting, gastritis, and dyspepsia. Nervous system diseases include vertigo, insomnia, and epilepsy. Cardiovascular system diseases include hypertension and coronary heart disease. Tumor-related diseases can be used as adjuvant therapeutic drugs. We mainly sorted out the mechanism of action, target sites, classic formulas and clinical applications of P ternata as shown in Figure 12. At the same time, we have found that the researchers in this field mainly conduct their work around the following 4 aspects.

Figure 12.

The mechanism of action, target sites, classic prescriptions and clinical applications of P. ternata.

• (1)Research on related classic prescriptions and their applications.

The theory of TCM emphasizes the importance of syndrome differentiation and treatment, which involves selecting prescriptions based on specific methods and administering treatments according to those prescriptions. P ternata is a TCM herb with documented toxicity when unprocessed. Proper processing and formulation with other herbs are essential to decrease its toxicity and enhance its therapeutic effects. Classic prescriptions containing P. ternata, such as Banxia Xiexin Decoction, Banxia Houpu Decoction, Banxia Baizhu Tianma Decoction, Gualou Xiebai Banxia Decoction, and Gansui Banxia Decoction, are widely used in clinical practice. Zhang^[46] found that Gualou Xiebai Banxia Decoction alleviates metabolic syndrome in mice fed a high-fat diet by regulating the liver-gut axis. The study concluded that its effects are mediated by improving hepatic lipid and glucose metabolism and modulating the composition of the gut microbiota. Banxia Houpu decoction has the potential to substantially reduce the impairment of cardiac function and the concentration of cardiac enzymes resulting from chronic intermittent hypoxia. It also lowers the levels of proinflammatory factors and prevents the conversion of macrophages from the M2 phenotype to the M1 phenotype.^[47]

Banxia Xiexin Decoction has been shown to significantly decrease the levels of inflammatory factors such as interleukin-1β, interleukin-5, and tumor necrosis factor-α in mice suffering from functional dyspepsia. It also inhibits the activation of the nuclear factor-κB signaling pathway, mitigates damage to the duodenal mucosal barrier, and enhances gastrointestinal motility function.^[48] In a mouse model of colorectal cancer, Banxia Xiexin Decoction can suppress inflammatory responses and tumor proliferation, preserve intestinal homeostasis, and inhibit the expression of signal transducer and activator of transcription 3, matrix metalloproteinase-9, and transforming growth factor β1.^[49] Additionally, Banxia Baizhu Tianma Decoction may control lipid metabolism via the associated signaling pathway, thereby lowering lipid accumulation in high-fat rat models and modulating the expression levels of genes and proteins linked to lipid metabolism.^[50] Moreover, Banxia Yiyiren Decoction is composed of amino acids, nucleotides, organic acids, flavonoids, fatty acids, and lipids, which can improve the intestinal flora of insomnia model rats by modulating the species, structure, abundance, and metabolites of intestinal flora.^[51]

In conclusion, P ternata is capable of being utilized to produce a range of traditional prescriptions and is extensively employed in the management of cancer, digestive system diseases, endocrine disorders, and cardiovascular diseases. However, there have been limited clinical studies in this area, primarily conducted through cell and animal experiments, network pharmacology, and molecular docking. Future efforts should aim to enhance the accumulation of evidence, establish a standardized system for diagnosis and treatment, and carry out high-quality multicenter controlled clinical trials with a large sample size.

• (2)Research on pharmacological components and mechanisms of action.

The development of Chinese medicine has largely been pushed toward objectification, standardization, and a microcosm of traditional Chinese medicine. This is a key aspect of its modernization, aligning its practices and principles with modern scientific methodology. The goal is to demystify and clarify the complex mechanisms of TCM, allowing for more precise and predictable.

P ternata mainly consists of alkaloids, polysaccharides, volatile oils, and various other components. It exhibits a range of pharmacological functions, including antitussive and expectorant effects, anti-inflammatory properties, antitumor effects, and sedative qualities. Wang conducted research and expounded the anti-inflammatory substance basis of P. ternata, and also established its quality evaluation method.^[52] Zhao^[53] has studied different extraction methods of P ternata polysaccharides, hoping to develop them into antitumor drugs. The research determined that the polysaccharide extract from P ternata exhibited certain in vivo antitumor properties, likely linked to the enhancement of the body’s capacity to eliminate excess free radicals through the improvement of enzymatic activity.^[54]

Through network pharmacology methods, Liu screened out 13 bioactive compounds and 68 co-targets of P ternata in the intervention of esophageal cancer, and verified them through cell experiments, providing ideas and a foundation for the experimental research on the treatment of esophageal cancer with P. ternata.^[55] Research has shown that this decoction extract can effectively suppress the proliferation of myeloid and lymphocytic leukemia cells and facilitate apoptosis of leukemia cells.^[56] Zhai^[57] employed network pharmacology and molecular docking techniques to investigate the mechanism by which P ternata aids in the treatment of hypertension, which may contribute to a more robust scientific foundation for the integrated application of traditional Chinese medicine alongside western medicine, ultimately enhancing the quality of P ternata and revealing its therapeutic direction.

At present, the biggest bottleneck in P ternata research is the inability to link specific monomers to therapeutic targets and precise biological mechanisms. While the anticough, antitumor, and sedative effects of complex extracts like total alkaloids and polysaccharides are known, the exact compounds responsible for these effects and how they function at a molecular level remain unclear. Moreover, the content of active ingredients such as alkaloids and organic acids, as well as toxic components in different batches of P. ternata, varies greatly, and there is a lack of quantitative detection indicators, which makes it impossible to standardize the material basis and quality evaluation. Additionally, the unclear link between toxicity and efficacy, as well as the detoxification processes during processing, has greatly impeded the current development and safe clinical application of P. ternata. Moving forward, comprehensive studies on the pharmacological constituents and their mechanisms of action in P ternata are essential to facilitate the modernization of traditional Chinese medicine.

• (3)Research on cultivation and quality control.

The increased demand for traditional Chinese medicine faces significant challenges from environmental pollution and land loss, which directly impact the growth environment of medicinal plants. These issues compromise the quality and safety of herbal materials, threatening the sustainable development of the traditional Chinese medicine industry. Studying P ternata cultivation and breeding techniques to boost the yield and content of beneficial components is extremely valuable and essential for the therapeutic effects of traditional Chinese medicine. Kang^[58] studied the taste quality indicators of P ternata and clear P. ternata, identifying 16 potential chemical markers in total. This research offers an objective and reproducible approach for assessing the processing effects, which holds considerable importance for the quality control of P ternata and other traditional Chinese medicines.

Chen^[59] found that chitosan can be used as an alternative and practical corrosion inhibitor to mediate consistent cropping challenges for P ternata. Chitosan enhances plant growth, improves photosynthesis, and increases resistance to stress. The study found that chitosan treatment effectively increased the leaf area and plant height of P ternata and reduced the seedling lodging rate. Furthermore, a study by Gao^[60] investigated how the protein HY5, a key regulator of light signals in plants, can be used to improve the quality of medicinal plants like P ternata. This research proposes targeted light regulation as a precise strategy for optimizing the cultivation of P ternata and other crops. Soft rot disease, which is caused by Pectobacterium carotovorum, represents a significant threat to P ternata plants.^[17] In their study, Guo^[61] proposed that brassinolide can help increase the harvest of P ternata and assist in determining the optimal harvest time.

The core problems currently faced by the research institute of P ternata cultivation and planting are mainly concentrated in the degradation of germplasm resources, the lack of high-quality varieties, continuous cropping obstacles, the low standardization degree of cultivation techniques, and the insufficient level of mechanization and intelligence. These factors substantially hinder the large-scale, standardized, and high-quality development of the P ternata industry.

In the future, efforts should be made to establish a systematic system for the selection and breeding of high-quality varieties, promote the integration and popularization of standardized and ecological cultivation techniques, strengthen the integration of agricultural machinery and agronomy, improve the quality of Chinese medicinal materials, and drive the transformation and upgrading of the P ternata industry towards high-quality varieties, mechanization, ecologicalization and branding.^[62]

• (4)Challenges and prospects for translating basic research into clinical application.

There are a large number of research papers related to P. ternata, but the conversion efficiency is insufficient, and the international competitiveness is weak. A large number of studies remain at the basic research stage and have not effectively entered clinical application or industrialization. There is a phenomenon of disconnection between basic research and clinical research. Basic research focuses on exploring molecular mechanisms and concentrating on growth and apoptosis mechanisms at the cellular level, inflammation inhibition, and active component analysis. However, clinical research has mainly focused on the efficacy of classic prescriptions such as Banxia Xiexin Decoction and Banxia Baizhu Tianma Decoction. The bridge for transformation between these 2 has not been fully established yet. In addition, P ternata has stimulating toxicity, and the balance between reducing toxicity through processing and preserving its efficacy remains a key bottleneck for clinical transformation. The safety evaluation studies of raw P. ternata, such as its renal toxicity, still need to be deepened, which restricts its wide application in the expansion of new indications. At the same time, there are difficulties in authentic identification of P ternata medicinal materials, significant differences in quality among different origins, and genetic variations in germplasm resources. There is a lack of unified quality grade standards, which affects the stability and repeatability of clinical medication.

The application of cutting-edge technologies such as network pharmacology, molecular docking, metabolomics, and transcriptomics provides new tools for systematically analyzing the target disease pathways of P ternata drug components. This is expected to provide theoretical support for clinically precise medication at the molecular mechanism level.^[63–65] Classical formulas such as Banxia Xiexin Decoction, Banxia Baizhu Tianma Decoction, and Gualou Xiebai Banxia Decoction have demonstrated definite therapeutic effects in diseases such as coronary heart disease, hypertension, vertigo, and chronic gastritis. In the future, further verification through evidence-based medical research can be carried out to promote the development of standardized preparations. By deeply mining the compatibility rules and action targets of P ternata in ancient medical books and modern clinical literature using artificial intelligence technology, it can provide theoretical support for the development of innovative patent technologies and shorten the cycle from basic research to clinical application. It is necessary to establish an integrated layout of clinical needs, technological innovation, and industrial transformation, optimize research quality, explore an intellectual property protection model suitable for the characteristics of traditional Chinese medicine, and ultimately achieve a deep integration of industry-university-research-application.

4.2. Strengths and limitations

To our understanding, this constitutes the first literature evaluation and visual analysis of P. ternata. Thus, it offers a reference point and guidance for researchers to comprehend the current research landscape and key areas of interest in this domain. Nevertheless, this study does have certain limitations. First, when excluding irrelevant literature and combining synonymous keywords, there might have been a subjective understanding bias of the researchers. Second, when we merged the organizations, authors, and keywords, there were some cases in which some content appeared too infrequently to be merged. Third, an author who published 1 paper as the first author received a lower ranking than another author who published 2 papers as an intermediate author, regardless of how prestigious and significant the author’s contributions were. Finally, this article only includes the literature from 2 databases. These 2 databases collect the research results of scholars from all over the world and are universal and representative. However, literature from databases such as China National Knowledge Infrastructure, Wanfang Database, and VIP Network, which mainly collect Chinese literature, was not included. This may create some biases. Furthermore, this study focused solely on the maps and data generated by the software, which may have resulted in the omission of some research literature. Nevertheless, this visualization-based literature analysis assists in understanding the research trends and directions in the field, laying the foundation for subsequent research.

5. Conclusion

We included 488 articles closely related to the field and used visual analysis software and websites to assess the annual publishing trends, publishing countries or regions, institutions, authors, journals, keywords, and references in the field. The general upward trend in publications over the previous 22 years illustrates that this field is currently a research hotspot and that research in it is steadily growing. Through our analysis, we found that the People’s Republic of China, South Korea, and Japan were the main research and participating countries. Major research institutions include Nanjing University of Chinese Medicine, Chengdu University of Traditional Chinese Medicine, and China Academy of Chinese Medical Sciences. The main publications are the Journal of Ethnopharmacology, Medicine, and Evidence-Based Complementary and Alternative Medicine. Xue Jianping and Xue Tao were among the authors who published the most papers. There are currently 3 areas in which future research in this area is focused: Research on related classic prescriptions and their applications, research on pharmacological components and mechanisms of action, and research on cultivation and quality control. In addition, research on micro-standardization, standardization, and objectification of traditional Chinese medicine is also developing. We believe that the development of this field will improve in the future.

Acknowledgments

The authors would like to thank Hunan University of Chinese Medicine for its support of this work, and the editors and reviewers for their valuable comments and permission to improve the manuscript.

The authors thank 51runse (www.51runse.cn) for the English language editing during the preparation of this manuscript.

Author contributions

Conceptualization: Kun Lian.

Data curation: Kun Lian, Lichong Meng, Junxian Lei, Huifang Kuang, Songyan Tie, Lin Li.

Formal analysis: Kun Lian, Lichong Meng, Huifang Kuang.

Software: Kun Lian, Junxian Lei, Huifang Kuang, Songyan Tie.

Validation: Kun Lian, Zhixi Hu.

Project administration: Lichong Meng.

Resources: Lichong Meng, Huifang Kuang, Songyan Tie.

Supervision: Lichong Meng, Lin Li, Zhixi Hu.

Investigation: Junxian Lei, Songyan Tie.

Methodology: Junxian Lei, Lin Li.

Visualization: Lin Li.

Funding acquisition: Zhixi Hu.

Writing – original draft: Kun Lian.

Writing – review & editing: Zhixi Hu.