We selected the WoSCC database for our research. The researchers conducted a search and downloaded the data from the database on 22 July 2024. The search strategy was as follows: TS = (“soluble guanylate cyclase stimulator”) OR TS = (“sGC stimulator”) OR TS = (“soluble guanylate stimulator”) OR TS = (“sGC activator”) OR TS = (“soluble guanylate cyclase activator”) OR TS = (“soluble guanylate activator”) OR TS = (“soluble guanylate cyclase stimulators”) OR TS = (“sGC stimulators”) OR TS = (“soluble guanylate stimulators”) OR TS = (“sGC activators”) OR TS = (“soluble guanylate cyclase activators”) OR TS = (“soluble guanylate activators”) OR TS = (“vericiguat”) OR TS = (“riociguat”) OR TS = (“praliciguat”) OR TS = (“cinaciguat”)OR TS = (“mosliciguat”) OR TS = (“avenciguat”) OR TS = (“runcaciguat”) OR TS = (“olinciguat”) OR TS = (“zagociguat”) OR TS = (“BAY-747”) OR TS = (“YC-1”) OR TS = (“BAY-412272”) OR TS = (“BAY41-8543”) OR TS = (“lificiguat”) OR TS = (“ataciguat”) OR TS = (“CFM-1571”) OR TS = (“A-350619”) OR TS = (“BAY 58-2667”) OR TS = (“HMR-1766”) OR TS = (“BAY 63-2521”) OR TS = (“IW-1973”) OR TS = (“K-5475”). Only the English papers published before 2024 with the type of article or review article were selected, and a total of 1,879 papers were retrieved for follow-up research. The specific process and filtering procedure are shown in Figure 1.

Data collection is primarily conducted through database searches. Directly query in WOSCC for the following information: publication volume, annual publication volume, citation frequency, citations per article, and the H index of the top 10 countries, institutions, authors, and journals, and so on. The H-index indicates that within a specific subject’s published papers, there are H papers with a citation frequency of at least H times (Hirsch, 2005; Alonso et al., 2009). Simultaneously, we also conducted a search for the annual citations of highly cited papers and the impact factors of journals. The Impact Factor (IF) is an internationally recognized index for evaluating journals. It was first proposed by Eugene Garfield, the founder of the American Institute for Scientific Information (ISI), in the 1960s (Garfield, 2006). In general, a high impact factor indicates that the academic influence of a journal is substantial and the quality of papers is relatively high.

The analysis of data primarily utilizes VOS viewer 1.6.20.0, CiteSpace 6.3R1 Advanced, and an online tool (WeShengXin) for visual analysis. The VOS viewer is capable of visualizing the critical points within a cluster and illustrating the collaboration between these points (van Eck and Waltman, 2010). Due to the advantages of simple operation and good visualization effect of this software, this study mainly uses it to conduct collaborative analysis of countries, authors or institutions, present the co-occurrence of keywords, and intuitively illustrate the co-citation relationship between authors, journals or references. CiteSpace is a robust tool for analyzing scientific literature, offering excellent visualization effects, strong operability, high interactivity, and a user-friendly interface (Chen, 2006). It has extensive applications in scientometrics and data visualization, making it an essential tool for researchers to analyze literature and construct knowledge maps. At the same time, because the software has multidimensional literature analysis, custom analysis function, efficient cluster analysis and other highlights, our researchers use it to generate keyword and reference keyword burst, reference burst, cluster analysis and time line cluster analysis. These analyses are employed to examine research hotspots, comprehend research trends, and assist researchers in understanding changes in research hotspots and trends over time. Weishengxin (https://www.bioinformatics.com.cn/) is a powerful, easy-to-operate, practical, efficient, and convenient online bioinformatics analysis and visualization cloud platform, which is a handy tool for scientific research workers. This online platform has gained the favor of many researchers due to its advantages of having numerous drawing templates and easy operation. In this analysis process, we mainly used it to visualize the world’s publication volume and display the annual publication volume of the top ten countries and the annual citation status of highly cited literature. R software is an open-source and powerful mathematical programming language that can be used for statistical analysis, data mining, machine learning, data visualization, and many other aspects. Especially its bibliometrix package is very convenient and comprehensive for bibliometric analysis.

We have analyzed 1,582 articles and 297 review articles that were published in English before the year of 2024. To comprehend the overall development trend of publications, we have created a scatter plot illustrating the annual publication volume (Figure 2) and indicated the trend line. It is apparent from the graph that there is a strong correlation between the annual publication volume and year of papers on sGC stimulators or activators, as indicated by a trend line with an R² value of 0.961. Especially since riociguat became the first approved sGC stimulator in 2013, the research in this field has entered a stage of rapid development. The number of publications in the decade following 2013 is two times that of the years preceding 2013, accounting for nearly 66.5% of the total number of publications.

The researchers have conducted an analysis and organization of the top 10 productive countries/regions and co-authorship countries, which are listed in Table 1. It can be found that United States, Germany, China, England, Japan, Italy, Canada, France, Netherlands and Poland are among the top 10 countries in terms of publication volume. Germany is the country with the most frequent cooperation with other countries, publishing a total of 482 papers on sGC stimulants or activators, with a total link strength of 948. The United States cooperated with other countries slightly less frequently than Germany, ranking second. Although China and Japan have published a significant number of articles, their collaboration with other countries is not frequent. This suggests that there is a need for them to enhance their international cooperation in order to promote further development in this field. The researchers also used WeShengXin, an online tool, to draw a global distribution map of publication volume (Figure 3A) and a bubble chart of annual publication volume for the top 10 productive countries (Figure 3B). Figure 3A provides a rough representation of the publication status of countries worldwide. Different fill colors indicate varying publication volumes, with dark red indicating countries with a total publication volume exceeding 600. In Figure 3B, it is evident that the United States and Germany have significantly outpaced other countries in the annual number of publications, establishing themselves as key pioneers and leaders in this field. In addition, we can also see from the figure that China has been in a state of rapid development in this field in recent years.

The top 10 prolific institutions and co-authorship institutions are shown in Table 2. The institution with the highest number of publications is Bayer AG located in Germany, which has published a total of 255 papers on sGC stimulators or activators. At the same time, Bayer AG is also the institution that engages in the most frequent collaborations with others, thereby significantly advancing academic exchange and development in this field. In addition, seven of the top 10 prolific institutions belong to Germany. This indicates that Germany’s prosperous development in this field is closely related to its having more mature research institutions.

In this study, 8,968 authors participated in the publication of the papers we collected. The top 10 productive authors and co-cited authors are shown in Table 3. If several authors are cited concurrently in subsequent literature, they are considered to have a co-cited relationship. Researchers applied VOS viewer to visualize the network of co-cited authors (Figure 4A), including 150 authors that are cited at least 50 times. The same color represents the same cluster, while the size of the node indicates the cited frequencies. The line between two nodes signifies a co-cited relationship, with the thickness of the lines representing the degree of connection closeness. Professor Stasch, JP has published the highest number of papers, with a total of 86 papers. Following closely behind is Professor Sandner, P, who has published 45 papers, and Professor Hoeper, MM, who has published 41 papers. The most frequently cited author is Professor Stasch, JP, who has been cited 934 times and has a total link strength of 13,806. There are three authors who are part of both the top 10 productive authors and the top 10 co-cited authors, namely, Stasch, JP, Hoeper, MM, and Ghofrani, HA. This indicates that they not only produce a large number of articles but also have high-quality papers, which are generally recognized by the industry. Furthermore, we also conducted research on the collaborative relationships of the authors and created a network visualization of co-authorship authors (Figure 4B). It comprises 100 authors who have published at least 8 papers. The size of the nodes represents the frequency of cooperation, and the line between the two nodes signifies the cooperative relationship. It is evident that collaboration within the cluster occurs frequently, while collaboration between clusters is less common. At the same time, we have observed that Professor Stasch, JP and Professor Ghofrani, HA frequently collaborate with other authors and hold central positions within their respective clusters.

Figure 4C is a sankey map of the top 50 authors’ institutions and countries in terms of publication volume, drawn by researchers using the R software bibliometrix package. Different nodes in the picture represent different authors, institutions, or countries, and lines in the picture represent relationships to which they belong. The width of the line represents the strength of the attribution, and the wider the line, the stronger the attribution. It can be found that the top ranked institutions and countries of these 50 authors are Bayer AG and Germany, respectively, which once again confirms the important position of Bayer AG and Germany in this field mentioned earlier.

The top 10 productive journals and co-cited journals are listed in Table 4. The journal that ranks first in terms of publication volume is PULMONARY CIRCULATION (IF 2.2), with 52 articles published. The journal with the most citations is CIRCULATION, with an impact factor of 35.5 and total link strength of 184,395. It has been cited 3404 times, followed by NEW ENGL J MED (IF 96.2) and EUR RESPIR J (IF 16.6). It is easy to observe that most journals with highly cited frequency are distributed in Q1. The network visualization of co-cited journals is depicted in Figure 5A, encompassing 100 journals cited at least 140 times. The larger and more prominent points on the diagram represent several journals that are cited more frequently. Figure 5B is the density visualization of co-cited journals. The warmer the color and the larger the font, the higher the cited frequency. It is obvious from Figures 5A,B that CIRCULATION and NEW ENGL J MED are the most frequently cited journals. In addition, researchers also utilized CiteSpace software to create a dual journal overlay map (Figure 5C). The Double journal overlay map has the capability to generate new spatial relationships and attribute feature relationships through the superposition analysis of multi-layer data. This process allows for a more comprehensive understanding of the data and can reveal insights that may not be apparent when analyzing individual layers separately. Simultaneously, the double journal overlay map can uncover the flow of knowledge between disciplines and serve as a foundation for evaluating and selecting periodicals. The left part of Figure 5C pertains to the citing journals, which represent the knowledge frontier, while the right part depicts the cited journals, representing the knowledge base of the field. The different colors in the graph indicate different journal clusters, and the lines between the left and right sides signify citation relationships. From the image, it is apparent that “2 MEDICINE, MEDICAL, CLINICAL” and “4 MOLECULAR, BIOLOGY, IMMUNOLOGY” stand out as the most influential citing journal clusters in the knowledge frontier. In the knowledge base, the most influential cited journal clusters are the clusters marked as “5 HEALTH, NURSING, MEDICINE” and marked as “8 MOLECULAR, BIOLOGY, GENETICS”. The research findings published in these journals serve as the essential cornerstones of the field, playing a crucial role in its development and serving as necessary prerequisites for the smooth conduct of subsequent research. Also, in this study, there are four main citation paths, and each citing journal has multiple citation paths, showing an aggregation relationship with the cited journals.

Highly cited papers refer to papers published within the past 10 years that have been cited in the top 1% of the world rankings in the discipline. Our researchers have compiled the top ten highly cited papers in this field and listed them in Table 5. These 10 highly cited papers include 6 articles and 4 review articles. The top ranked highly cited paper is a review article, published by Kowal Bielecka, O et al. in ANN RHEUM DIS in 2017. This article suggests that the use of riociguat should be considered when treating systemic sclerosis (SSc) associated pulmonary arterial hypertension (PAH) (Kowal-Bielecka et al., 2017). So far, this paper has been cited 716 times. Figure 6 is a bubble chart of the annual citation frequency of highly cited papers ranked 10, drawn by researchers. The “2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension, developed by the task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS), and endorsed by the International Society for Heart and Lung Transplantation (ISHLT) and the European Reference Network on rare respiratory diseases (ERN-LUNG)”, was published by Humbert, M et al. in the EUROPEAN HEART JOURNAL in 2022 (Humbert et al., 2022). It was explicitly stated that riociguat has a significant effect on chronic thromboembolic pulmonary hypertension (CTEPH), leading to a reduction in 6-min walk distance (6mwd) and a decrease in pulmonary vascular resistance by 31% compared with the control group. Upon publication, it immediately garnered significant attention from researchers and has been widely referenced due to its strong value as a reference. Meanwhile, the study “Vericiguat in Patients with Heart Failure and Reduced Ejection Fraction”, authored by Armstrong, PW et al. and published in the NEW ENGL J MED in 2020, has had a significant impact and has been frequently cited since its release. The authors demonstrated the clinical efficacy of vericiguat in patients with HFrEF, thus making a substantial contribution to the approval and launch of vericiguat in the market (Armstrong et al., 2020b). Besides, we also found that 4 out of these 10 highly cited papers were about the application and efficacy of riociguat in PAH or PH, while the remaining 6 focused on the application and efficacy of vericiguat in patients with HF, including heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). These are likely concrete manifestations of current research hotspots.

We utilized VOS viewer as an analytical tool to conduct a co-cited reference analysis on all the papers involved in this study and have presented the top 5 co-cited references in Table 6. The article authored by Ghofrani, HA et al. in 2013 is the most significant reference within this particular field of study. It has been experimentally demonstrated in this article that riociguat can markedly improve motor capacity and pulmonary vascular resistance in patients with CTEPH (Ghofrani et al., 2013a). The second co-cited reference was a review published by Evgenov, OV et al., in 2006. The authors systematically elaborated on the fundamental information and clinical potential of sGC stimulators and activators in a comprehensive manner (Evgenov et al., 2006). The publication of this review greatly facilitates subsequent researchers in gaining a comprehensive understanding of sGC stimulators or activators. This will enhance convenience and efficiency for future research endeavors in this area. The paper about YC-1 published by Ko FN et al. in 1994 in BLOOD is the third ranked reference in this field discovered in this study. Its authors pointed out through experimental data that YC-1 is a sGC activator in rabbit platelets and found that it may have the potential to inhibit thrombosis (Ko et al., 1994). The paper “Soluble Guanylate Cyclase as an Emerging Therapeutic Target in Cardiopulmonary Disease” was published in CIRCULATION in 2001 by Stasch, JP et al., and is the fourth co-cited reference (Stasch et al., 2011). It has extremely profound significance and influence, and to this day it is still in a constantly cited state. The fifth co-cited reference was published by Galiè, N et al. in the journal of EUR HEART J in 2016. It is a highly authoritative diagnostic and treatment guideline for PH (Galiè et al., 2016). Although the guidelines have been updated (Humbert et al., 2022), there is no doubt about the beneficial efficacy of sGC stimulators for PH.

We also created the co-cited reference cluster analysis using CiteSpace, shown in Figure 7A. The Modularity Q of this cluster analysis is high, which is 0.8156, and the Weighted Mean Silhouette S is 0.9344, indicating that the cluster structure is significant and convincing. The references are divided into 22 clusters (cluster #0-#21), and we have selected the top 10 of them for visualization. Different colors represent different clusters, and the size of the clusters indicates the volume of content contained within each cluster. Cluster #0, labeled as “yc-1”, is the largest cluster composed of 174 references, followed by cluster #1, labeled as “cinaciguat”, which contains 141 references. Cluster #2, named “balloon pulmonary angioplasty”, contains 139 references. The cluster #3, named “bay 41-2272”, contains 139 references; and cluster #4, named “vericiguat”, contains 135 references. The cluster #5, “pulmonary hypertension”, contains a total of 110 references. The next cluster #6 (including 88 references), cluster #7 (including 74 references), and cluster #8 (including 63 references), were respectively named “pulmonary arterial hypertension”, “riociguat” and “hypoxia”, while the cluster #9 is labeled as “oestradiol” and contains 42 references. Figure 7B is a timeline view of co-cited references, which effectively demonstrates both the outcomes of the clusters and the temporal evolution. Each data point on the graph represents a reference, while the curves between the points depict the co-cited relationships. The size of each data point reflects its cited frequency. It can be found that cluster #2, cluster #4, cluster #5, and cluster #7 emerge in recent years and have high citation frequency. The top 25 references with the strongest citation bursts are shown in Figure 7C. The period between the Begin and End years signifies the peak influence of the reference. The dark blue represents the year of publication, while red indicates the duration of impact. Among them, the strongest reference for explosive intensity is “Riociguat for the Treatment of Chronic Thromboembolic Pulmonary Hypertension”, published by Ghofrani, HA et al.in NEW ENGL J MED in 2013 (Ghofrani et al., 2013a), with a citation strength of 80.11. It has been highly influential and significant in promoting riociguat to become the first approved sGC stimulator. The last few references on the Figure are the ones that still have highly influence so far. They are the “A Multicenter, Randomized, Double-Blind, Placebo-Controlled Trial of the Efficacy and Safety of the Oral Soluble Guanylate Cyclase Stimulator The VICTORIA Trial”, published by Armstrong PW et al., in 2018 in JACC-HEART FAILURE (Armstrong et al., 2018), “Soluble Guanylate Cyclase Stimulators and Activators.” authored by Sandner, P in 2021in HANDB EXP PHARMACOL (Sandner et al., 2021b), “Vericiguat in Patients with Heart Failure and Reduced Ejection Fraction”, published by Armstrong PW et al. in 2020 in NEW ENGL J MED (Armstrong et al., 2020b), “Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction”, published by McMUrray JJV et al. in NEW ENGL J MED in 2019 (McMurray et al., 2019), “Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure”, published by Packer M et al., in 2020 in NEW ENGL J MED (Packer et al., 2020), “Effect of Vericiguat vs. Placebo on Quality of Life in Patients With Heart Failure and Preserved Ejection Fraction The VITALITY-HFpEF Randomized Clinical Trial”, which is published by Armstrong PW et al., in 2020 in JAMA-J AM MED ASSOC (Armstrong et al., 2020a), and “N-Terminal Pro-B-Type Natriuretic Peptide and Clinical Outcomes”, published by Ezekowitz JA et al. in JACC-HEART FAIL in 2020 (Ezekowitz et al., 2020). These findings suggest that current research is primarily focused on the clinical effectiveness and impact of several emerging drugs, such as riociguat and vericiguat. Specifically, there is a particular emphasis on evaluating the efficacy of sGC stimulators or activators in addressing pulmonary hypertension (PH) and heart failure (HF). This focus may be attributed to the successful listing of two drugs, riociguat in 2013 and vericiguat in 2021.

Keywords are core words or phrases in a particular field or topic that describe, summarize, or identify that field or topic. The change of keywords often represents a change in the research trend of a field. In the course of this analysis, the researchers mainly used three different analysis software for research and visualization, in order to eliminate the accidental errors that can occur in a single analysis software.

The co-occurrence network visualization of keywords, created using VOS viewer, is shown in Figure 8A. A total of 6,883 keywords appeared in this study. The network visualization includes 100 keywords that appeared at least 30 times. They are categorized into 3 clusters: red is the first cluster containing 43 keywords, green is the second cluster containing 37 keywords and blue is the third cluster containing 20 keywords. The node size indicates the occurrence frequency of keywords, while the connections between nodes represent co-occurrence relationships. In the overlay visualization of keywords (Figure 8B), the node color represents the average year in which the clustering keyword appeared. The warmer node color indicates a later appearance of the keyword. As observed in Figure 8, the keywords “nitric oxide”, “expression”, “yc-1” “cyclic-gmp” are the earlier appearing and influential terms, while “riociguat”, “chronic thromboembolic pulmonary hypertension” and “pulmonary hypertension” are the keywords that appear later and with the higher frequency of occurrence. And “vericiguat”, “heart failure” and “mortality” have emerged as newly prominent keywords in the field.

In addition to using VOS viewer for keyword co-occurrence analysis, the researchers also used CiteSpace software for keyword cluster analysis and visualized the cluster view (Figure 9A) and timeline view (Figure 9B). All of the keywords were divided into 12 clusters in cluster analysis (cluster #0-#11) with the Modularity Q of 0.4753 and the Weighted Mean Silhouette S of 0.7803. Only the top 10 keyword clusters are visualized in these figures. Cluster #0, labeled “nitric oxide”, contains 168 keywords, which is the largest and earliest keyword cluster. However, the occurrence frequency of keywords in this cluster has decreased in recent years. Cluster #1 is named “hif-1 alpha” and contains 146 keywords. Cluster #2, named “chronic thromboembolic pulmonary hypertension”, contains 142 keywords. The cluster #3, labeled “carbon monoxide”, contains 111 keywords. Cluster #4, “heart failure”, contains 73 keywords. Cluster #5, labeled “nitric oxide synthase”, contains 52 keywords, and cluster #6, which was named “cyclic amp”, contains 43 keywords. The following cluster #7 “zaprinast”, cluster #8 “hepatocellular carcinoma”, and cluster #9 “myenteric plexus” contain 30 keywords, 9 keywords, and 7 keywords, respectively. We also developed a landscape view of keywords (Figure 9C), which provides a clearer and more intuitive presentation of the appearance time and frequency of keywords. The height of the peaks indicates the frequency of occurrence of keywords. It can be found that cluster #0, cluster #1, cluster #3 and cluster #6 are the earliest keywords clusters, playing a vital role in developing this area. Cluster #2, named “chronic thromboembolic pulmonary hypertension” and Cluster #4, named “heart failure”, have exhibited a higher frequency of occurrence in recent years. The remaining cluster #5, cluster #7, cluster #8, and cluster #9 have hardly been seen in recent years, which seems to mean that research related to them is obsolete in the field. In addition, we also used CiteSpace to highlight the top 25 keywords with the strongest citation bursts (Figure 9D) so as to gain a better understanding of research hotspots and grasp development trends more effectively. It can be found that the top 1 keyword with the strongest CBs is “cyclic gmp”, with a strength of 30.02, which is the most influential keyword from 1993 to 2012. While “riociguat”, “outcome”, “guanylate cyclase stimulator”, “heart failure”, “natriuretic peptide”, “vericiguat”, “reduced ejection fraction”, “mortality” and “placebo” are the keywords that still have significant influence today.

The “bibliometrix” package of R software is a powerful toolkit developed and maintained by Massimo Aria and Corrado Cuccurullo for bibliometric analysis, which enables multidimensional analysis of selected literature (Aria and Cuccurullo, 2017). Supplementary Figure S1A is the keyword tree view of the top 50 keywords that the researchers plotted using the R package. The figure shows the frequency and percentage of each of these 50 keywords. The larger the area of the square where the keyword is located, the higher the frequency of the keyword. It can be clearly seen that the keywords “nitric oxide”, “expression” and “activation” are the top three keywords in the frequency of occurrence, which is consistent with the above analysis results. The Sankey plot (Supplementary Figure S1B) clearly shows the flow of keywords within different time slices, reflecting the changing trend of research focus in this field. It can be observed that research on nitric oxide has been ongoing throughout the entire development process of this field. At the same time, the researchers also analyzed the keyword clustering in the fifth time slice (2017-2024) in detail on the basis of Supplementary Figure S1B, and visualized it in Supplementary Figure S1C. Supplementary Figure S1C contains four keyword clusters in total, and they are distributed in four quadrants. Clustering located in the first quadrant (related to research on nitric oxide, expression, and activation) has a high level of development and relevance, and can be considered as a key research direction in this field (Motor Themes). The cluster named “guanylate cyclase simulator, natriuretic peptide, reduced ejection fraction” is distributed in the second quadrant and has a high level of development in recent years but low correlation. It can be considered as a niche research direction in this field (Niche Themes). Keyword clustering located in the third quadrant has a low degree of development and relevance, and is likely to be emerging or declining Themes in this field. Clustering in the fourth quadrant is likely to be the basic research in this field, because this keyword clustering has a high degree of relevance but a low degree of development for the present. This indicates that for the present time slice, the research on riociguat, soluble guanylate-cyclase, double-blind and so on is likely to be a hot research topic before it has important research value for the present research.

To verify the accuracy of the above analysis results, the researchers also used the same search terms in Elsevier’s Scopus database for paper search screening and analysis verification. In this database, we retrieved a total of 3,037 papers or reviews published in English between 1989 and 2023. According to the annual publication volume obtained from the database, the number of papers published in this field is significantly correlated with the year (R² = 0.9536), which is very consistent with the research results of WoSCC data (Supplementary Figure S2). At the national level, the analysis results of both databases are highly consistent in terms of publication volume (Supplementary Figure S3) and cooperation (Supplementary Figure S4). The United States (USA), Germany and China are the top three countries in this field, especially the United States, whose number of publications is much higher than other countries, and is an important promoter of the development of this field. At the same time, Germany and the United States (USA) are also the countries that cooperate most closely with other countries, making great contributions to the exchange and collision of knowledge in this field. Supplementary Figure S5 and Supplementary Figure S6 are the author publication volume network views and co cited author network views visualized by researchers using VOS viewer based on the Scopus database.

Reference analysis based on the Scopus database are shown in Supplementary Figures S7-S10. Supplementary Figure S7 shows the clustering of references analyzed using CiteSpace software. The Modularity Q value of this clustering is 0.8595 and the Weighted Mean Silhouette S value is 0.9145, indicating that the classification of this clustering is very reasonable and the structure is very stable. The figure displays a total of 9 clusters from the top 10 reference clusters (cluster labeled #9 was not displayed due to insufficient content). Supplementary Figure S8 is a peak view corresponding to the reference clustering in Supplementary Figure S7. It can be observed that the cluster labeled #3 “yc-1” is the earliest reference clustering in this field, and has rarely appeared in recent years. Several reference clusters labeled as #1 “pulmonary arterial hypertension”, #2 “heart failure”, #4 “vericiguat”, #6 “chronic thromboembolic pulmonary hypertension”, and # 9 “worrying heart failure” still have a certain frequency of occurrence, indicating that research related to them is likely to be a current research hotspot. Supplementary Figure S9 and Supplementary Figure S10 respectively show the time zone distribution of the references (the references with high influence are marked in the figure) and the top 25 references with the strongest citation bursts. Comparing the reference studies based on the WoSCC database in the previous section, it is not difficult to find that although there are slight differences in the research results of the two databases, overall they show the same development trend and direction.

Supplementary Figures S11, S12 are the co-occurrence network visualization and overlay visualization of author keywords drawn by VOS viewer software based on the search and screening of Scopus database. According to the figure drawn this time, it is very obvious that, “pulmonary hypertension”, “pulmonary arterial hypertension”, “nitric oxide”, “soluble guanylate cyclase” and “heart failure” are the most frequently used keywords in this field. Especially the keyword of “heart failure”, it has emerged in recent years and has a high frequency of occurrence. In addition to using the VOS viewer software, the researchers also used the CiteSpace software to perform a more comprehensive analysis of keywords. The timeline view of keyword clustering analysis is visualized in Supplementary Figure S13. In this analysis process, all keywords were divided into 11 clusters (with a Modularity Q value of 0.5847 and the Weighted Mean Silhouette S value of 0.8524). According to the visualization result, we find that the #0 marker labeled “soluble guanylyl cyclase” is the earliest keyword cluster in the field, and its occurrence frequency has decreased in recent years. The clusters named #8 “yc-1 activation”, #9 “drug administration”, and #10 “human erythrocyte” have hardly appeared in recent years, especially the cluster named #10 “human erythrocyte” which has not appeared for nearly 20 years. The remaining clusters have a certain frequency in recent years, which indicates that the current research focus is likely to focus on “pulmonary arterial hypertension”, “chronic thromboembolic pulmonary”, “heart failure”, “pulmonary angioplasty”, “systemic sclerosis”, “cardiovascular diseases” and “antiplatelet activity”. Supplementary Figure S14 reveals the top 25 keywords with the strongest citation bursts (sorted by starting year). As demonstrated in the figure, the three keywords (“Heart failure with reduced ejection fraction”, “hospitalization”, and “vericiguat”) continue to exert significant influence in contemporary research.

In summary, researchers found that although Scopus and WoSCC databases were slightly different in terms of analysis results, they were very consistent and compatible in general. This situation to some extent proves the accuracy of our research and reduces the occurrence of errors.

We collected a total of 1,879 papers for research spanning from 1989 to 2023. In the top 10 productive countries/regions, the United States occupies first place with 637 published papers, and Germany ranks second with 482 published papers. They contribute to 60% of the total number of publications, surpassing other countries worldwide by a large margin. There are seven institutions in the top 10 productive institutions belonging to Germany. Germany and the United States also rank first and second respectively among the top 10 countries with the highest collaboration frequency. In addition, seven of the top 10 productive authors are from Germany. Meanwhile, four of the top 10 co-cited authors are from Germany and two are from the United States. The aforementioned statement implies that in the field of research on sGC stimulators or activators, Germany and the United States have consistently held a dominant position, played a pivotal role, and served as pioneers. With their forward-thinking strategic vision, innovative scientific and technological prowess, and astute awareness of industry trends, they are spearheading the development direction of the field and setting a precedent for other nations. BAYER AG, located in Germany, is the most productive institution in this research field and has made a significant contribution to the field of research. Furthermore, several emerging drugs on the market have been developed by BAYER AG. The journal PULM CIRC (IF 2.2) has published the most papers in this field, with 52 papers. CIRCULATION (IF 35.5) was the most frequently cited journal in the study, with 3,404 citations. J BIOL CHEM (IF 4) is not only a journal with more published papers in this field, but also a journal with higher citation frequency in this study. Four of the top 10 highly cited papers were published in JAMA-J AM MED ASSOC (IF 63.1) and two in EUR HEART J (IF 37.6). This situation exemplifies the professionalism and industry recognition of high-quality journals. The papers published in these journals often wield significant influence and can assist researchers in gaining a deeper understanding of extensive research findings within a particular field.

Professor Stasch, JP is the most prolific author in the field and ranks first among the top 10 co-cited authors. He is a distinguished researcher with expertise spanning various fields, including pharmacology, cardiovascular system, respiratory system, biochemistry and molecular biology, and cell biology. Professor Stasch has played a significant role in advancing research on sGC stimulators or activators. In 1997, Professor Stasch, JP with his partners, through a large number of experiments, showed that YC-1 is a direct ionizing activator of sGC NO-independent and O₂− sensitivity, and it can play vasodilatory effects by increasing the body’s cGMP (Mulsch et al., 1997). In 2001, Professor Stasch, JP pointed out a novel compound capable of effectively stimulating sGC independent of the NO mechanism, suggesting a new potential for cardiovascular disease treatment (Stasch et al., 2001). In 2006, Professor Stasch, JP and his colleagues noted that compounds which activate sGC in a manner independent of nitric oxide (NO) offer significant therapeutic benefits (Evgenov et al., 2006). In 2011, he suggested that soluble guanylate cyclase could serve as a novel therapeutic target for cardiopulmonary diseases. This suggestion has significantly advanced the development of treatments for cardiopulmonary diseases (Stasch et al., 2011). In recent years, Professor Stasch, JP has been conducting research on a novel compound of sGC stimulator, BAY-747. It has the opportunity to become a research hotspot in the future.

Professor Ghofrani, HA is the author with the second most cited frequency, and his research focus on the cardiovascular and respiratory systems, particularly on pulmonary hypertension (PH). In 2006, he participated in the publishing “Activation of soluble guanylate cyclase reverses experimental pulmonary hypertension and vascular remodeling”, which illustrated that bay41-2272 and bay58-2627 could significantly reverse pulmonary vascular remodeling in rats with severe pulmonary hypertension induced by monocrotaline injection (Dumitrascu et al., 2006). In 2010, Professor Ghofrani, HA and his collaborators conducted a 12-week Phase II clinical controlled trial. Their preliminary findings demonstrated that riociguat could enhance the exercise ability and alleviate clinical symptoms of chronic thromboembolic pulmonary hypertension (CTEPH) or pulmonary arterial hypertension (PAH) (Ghofrani et al., 2010). In particular, the “Riociguat for the Treatment of Chronic Thromboembolic Pulmonary Hypertension”, published in 2013 (Ghofrani et al., 2013a), has garnered significant attention from researchers and holds a pivotal position in this field. Professor Ghofrani, HA, has participated in and published a total of 683 papers so far, with a personal H-index of 95. It can be said that he is a scholar with great output and influence.

The study of mechanisms is a crucial prerequisite for the development of any field, as it can unveil the essence and internal connections of a subject. In the case of sGC, which serves as the target of sGC stimulators or activators, studying its physiological action and mechanism is an indispensable research foundation in this particular field.

In 1969, White, AA et al. detected sGC in mammals (Schultz et al., 1969; White and Aurbach, 1969). Of course, the presence of sGC was not detected by accident or whim, but after researchers first discovered cAMP in 1958, researchers began to study purposefully, thus discovering the existence of sGC. Around the 1990s, there was a general understanding of the signal transduction pathway of NO-sGC-cGMP. At that time, researchers discovered that the activation of sGC could increase the concentration of cGMP in organisms. Acting as a second messenger, cGMP can then target specific receptors and induce a series of subsequent physiological effects. This is the most important pathway for sGC to function (Denninger and Marletta, 1999). Additionally, the sGC also appears to have an inhibitory effect on the TGF-β signaling pathway, thereby carrying out additional functions (Beyer et al., 2015; Zenzmaier et al., 2015; Sandner and Stasch, 2017). These two pathways of action of sGC are the most fundamental research prerequisites in this field, as well as the fundamental foothold and important basis for research in this field.

Hypoxia is an important pathophysiological state in the body, which can inhibit the activity of sGC directly or indirectly. And the sGC activators or stimulators can effectively counteract the pathological effects of hypoxia by directly activating or enhancing NO signaling pathways. This provides strong research support for the development of subsequent drugs and the treatment of diseases. Estradiol enhances the efficacy of the sGC activator or stimulator by directly activating the sGC and the antioxidant mechanism. In the treatment of cardiovascular diseases and tumors, the combination of estradiol and sGC activators shows multi-target modulation and signal amplification effects, which has potential therapeutic advantages.

Based on the analysis of the aforementioned research findings, it is our belief that the current focal points of research in this field primarily revolve around the development of various pharmaceuticals and the investigation into their clinical effectiveness and safety.

Future research in this field is expected to continue its focus on the development of new drugs and the rigorous verification of their clinical efficacy and safety. It may be specifically reflected in the safety verification of riociguat, the effect of vericiguat on other types of heart failure, the clinical efficacy of praliciguat in diabetes nephropathy, and the efficacy and safety verification of several newly proposed compounds. Furthermore, actively exploring new therapeutic directions for sGC stimulators or activators may also emerge as a significant trend in the future development of this field.

We applied bibliometric analysis to analyze the research trends on sGC stimulators or activators systematically and then visualized the findings in order to draw necessary conclusions. However, the study has some limitations: Firstly, we used WoSCC as the database for data collection. Although it is widely regarded as the most authoritative database, relying solely on one source may result in insufficient research. Secondly, when querying and downloading data from the WoSCC database, only general information can be accessed, but the full text of all papers cannot be downloaded, which may lead to a deviation in the analysis results. Thirdly, when querying the data, we have excluded papers published in 2024, as this may potentially lead to a slight lag in the results.