Food toxicology: quantitative analysis of the research field literature

Bibliometric analysis and research trends of artificial intelligence in lung cancer

Background

Due to the rapid advancement of technology, artificial intelligence (AI) has become extensively used for the diagnosis and prognosis of various diseases, such as lung cancer. Research in the field of literature has demonstrated that artificial intelligence (AI) can be valuable in the timely detection of lung cancer and the formulation of an effective treatment plan. This study aims to conduct a bibliometric analysis to examine and illustrate the specific areas of focus, research frontiers, evolutionary processes, and trends in existing research on artificial intelligence in the context of lung cancer.

Methods

Publications on AI in lung cancer were selected from the SCIE and ESCI indexes on September 19, 2023. The examination of nations, academic publications, organizations, writers, citations, and terms in this domain was visually analyzed with InCites and VOSviewer.

Results

In this study, a total of 4275 publications were selected and analyzed. Artificial intelligence-related lung cancer publications have increased significantly in the last 5 years. China and the USA have contributed the most to the literature in this field (1418 publications with 13.92 citation impacts and 1117 publications with 37.34 citation impacts, respectively). The institution with the highest contribution was "Chinese Academy of Sciences," with 118 publications and 29.09 citation impacts. Among the research categories, "Radiology, Nuclear Medicine & Imaging", "Oncology", and "Engineering, Biomedical" were in first place.

Conclusion

The USA and China have always been leaders in this field and will continue to be for some time. Research in countries such as the Netherlands is increasing. However, research collaboration has to be strengthened in developing countries.

Global Scientific Trends in Virtual Reality for Pain Treatment From 2000 to 2022: Bibliometric Analysis

Background

Virtual reality (VR) is a computer simulation technique that has been increasingly applied in pain management over the past 2 decades.

Objective

In this study, we used bibliometrics to explore the literature on VR and pain control, with the aim of identifying research progress and predicting future research hot spots.

Methods

We extracted literature on VR and pain control published between 2000 and 2022 from the Web of Science Core Collections and conducted bibliometric analyses. We analyzed the publication and citation trends in the past 2 decades, as well as publication and citation analyses of different countries, institutions, journals, and authors. For references, we conducted cocitation and burst analyses. For keywords, we conducted co-occurrence, clustering, timeline view, and citation burst analyses.

Results

Based on 1176 publications, we found that there was a continuous increase in publication and citation volumes, especially in the last 5 years. The United States was the most representative country, and the University of Washington was the most representative institution, with both having the most publications and citations. The most popular journal in this field was Burns, and Hoffman HG was the most productive author, leading many studies on patients with burn pain. The reference with the most citation burst was a study on the verification of new hardware in pain control. The keywords with the highest citation bursts related to various situations of pain such as "burn pain," "wound care," "low back pain," and "phantom limb."

Conclusions

VR has been applied in various clinical situations for pain management, among which burns and pediatric surgery have achieved satisfactory results. We infer that VR will be extended to more clinical pain situations in the future, such as pain control in wound care, low back pain, and phantom limb pain. New research hot spots will include the development of software and hardware to improve the immersive experience of VR for pain control. However, our work was based solely on English literature from the Web of Science database. For future studies, we recommend that researchers explore literature from multiple databases to enhance the scope of their research.

Global Trends in Research of Pain-Gut-Microbiota Relationship and How Nutrition Can Modulate This Link

INTRODUCTION

The link between gut microbiota and chronic painful conditions has recently gained attention. Nutrition, as a common intervention in daily life and medical practice, is closely related to microbiota and pain. However, no published bibliometric reports have analyzed the scientific literature concerning the link.

METHODS AND RESULTS

We used bibliometrics to identify the characteristics of the global scientific output over the past 20 years. We also aimed to capture and describe how nutrition can modulate the abovementioned link. Relevant papers were searched in the Web of Science database. All necessary publication and citation data were acquired and exported to Bibliometrix for further analyses. The keywords mentioned were illustrated using visualization maps. In total, 1551 papers shed light on the relationship from 2003 to 2022. However, only 122 papers discussed how nutritional interventions can modulate this link. The citations and attention were concentrated on the gut microbiota, pain, and probiotics in terms of the pain-gut relationship. Nutritional status has gained attention in motor themes of a thematic map.

CONCLUSIONS

This bibliometric analysis was applied to identify the scientific literature linking gut microbiota, chronic painful conditions, and nutrition, revealing the popular research topics and authors, scientific institutions, countries, and journals in this field. This study enriches the evidence moving boundaries of microbiota medicine as a clinical medicine.

COVID-19 Rapid Antigen Tests: Bibliometric Analysis of the Scientific Literature

As the COVID-19 pandemic continues to disrupt health systems worldwide, conducting Rapid Antigen Testing (RAT) at specified intervals has become an essential part of many people's lives around the world. We identified and analyzed the academic literature on COVID-19 RAT. The Web of Science electronic database was queried on 6 July 2022 to find relevant publications. Publication and citation data were retrieved directly from the database. VOSviewer, a bibliometric software, was then used to relate these data to the semantic content from the titles, abstracts, and keywords. The analysis was based on data from 1000 publications. The most productive authors were from Japan and the United States, led by Dr. Koji Nakamura from Japan (n = 10, 1.0%). The most academically productive countries were in the North America, Europe and Asia, led by the United States of America (n = 266, 26.6%). Sensitivity (n = 32, 3.2%) and specificity (n = 23, 2.3%) were among the most frequently recurring author keywords. Regarding sampling methods, "saliva" (n = 54, 5.4%) was mentioned more frequently than "nasal swab" (n = 32, 3.2%) and "nasopharyngeal swab" (n = 22, 2.2%). Recurring scenarios that required RAT were identified: emergency department, healthcare worker, mass screening, airport, traveler, and workplace. Our bibliometric analysis revealed that COVID-19 RAT has been utilized in a range of studies. RAT results were cross-checked with RT-PCR tests for sensitivity and specificity. These results are consistent with comparable exchanges of methods, results or discussions among laboratorians, authors, institutions and publishers in the involved countries of the world.

Research on Digital Technology Use in Cardiology: Bibliometric Analysis

Background

Digital technology uses in cardiology have become a popular research focus in recent years. However, there has been no published bibliometric report that analyzed the corresponding academic literature in order to derive key publishing trends and characteristics of this scientific area.

Objective

We used a bibliometric approach to identify and analyze the academic literature on digital technology uses in cardiology, and to unveil popular research topics, key authors, institutions, countries, and journals. We further captured the cardiovascular conditions and diagnostic tools most commonly investigated within this field.

Methods

The Web of Science electronic database was queried to identify relevant papers on digital technology uses in cardiology. Publication and citation data were acquired directly from the database. Complete bibliographic data were exported to VOSviewer, a dedicated bibliometric software package, and related to the semantic content of titles, abstracts, and keywords. A term map was constructed for findings visualization.

Results

The analysis was based on data from 12,529 papers. Of the top 5 most productive institutions, 4 were based in the United States. The United States was the most productive country (4224/12,529, 33.7%), followed by United Kingdom (1136/12,529, 9.1%), Germany (1067/12,529, 8.5%), China (682/12,529, 5.4%), and Italy (622/12,529, 5.0%). Cardiovascular diseases that had been frequently investigated included hypertension (152/12,529, 1.2%), atrial fibrillation (122/12,529, 1.0%), atherosclerosis (116/12,529, 0.9%), heart failure (106/12,529, 0.8%), and arterial stiffness (80/12,529, 0.6%). Recurring modalities were electrocardiography (170/12,529, 1.4%), angiography (127/12,529, 1.0%), echocardiography (127/12,529, 1.0%), digital subtraction angiography (111/12,529, 0.9%), and photoplethysmography (80/12,529, 0.6%). For a literature subset on smartphone apps and wearable devices, the Journal of Medical Internet Research (20/632, 3.2%) and other JMIR portfolio journals (51/632, 8.0%) were the major publishing venues.

Conclusions

Digital technology uses in cardiology target physicians, patients, and the general public. Their functions range from assisting diagnosis, recording cardiovascular parameters, and patient education, to teaching laypersons about cardiopulmonary resuscitation. This field already has had a great impact in health care, and we anticipate continued growth.

The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis

Background

With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer.

Objective

This study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots.

Methods

The articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field.

Results

A total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: “Diagnosis and Prediction AI-related study”, “Non-surgery AI-related study”, and “Surgery AI-related study”. Meanwhile, the current research hotspots were “deep learning” and “multiparametric MRI”.

Conclusions

Artificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years.

Virtual and Augmented Reality Applications in Medicine: Analysis of the Scientific Literature

BACKGROUND

Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific literature in relation to the application of these technologies in medicine.

OBJECTIVE

We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research.

METHODS

The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts.

RESULTS

The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering.

CONCLUSIONS

The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients.

First, Do No Harm (Gone Wrong): Total-Scale Analysis of Medical Errors Scientific Literature

Objective: Medical errors represent a leading cause of patient morbidity and mortality. The aim of this study was to quantitatively analyze the existing scientific literature on medical errors in order to gain new insights in this important medical research area. Study Design: Web of Science database was used to identify relevant publications, and bibliometric analysis was performed to quantitatively analyze the identified articles for prevailing research themes, contributing journals, institutions, countries, authors, and citation performance. Results: In total, 12,415 publications concerning medical errors were identified and quantitatively analyzed. The overall ratio of original research articles to reviews was 8.1:1, and temporal subset analysis revealed that the share of original research articles has been increasing over time. The United States contributed to nearly half (46.4%) of the total publications, and 8 of the top 10 most productive institutions were from the United States, with the remaining 2 located in Canada and the United Kingdom. Prevailing (frequently mentioned) and highly impactful (frequently cited) themes were errors related to drugs/medications, applications related to medicinal information technology, errors related to critical/intensive care units, to children, and mental conditions associated with medical errors (burnout, depression). Conclusions: The high prevalence of medical errors revealed from the existing literature indicates the high importance of future work invested in preventive approaches. Digital health technology applications are perceived to be of great promise to counteract medical errors, and further effort should be focused to study their optimal implementation in all medical areas, with special emphasis on critical areas such as intensive care and pediatric units.

Neurotensins and their therapeutic potential: research field study

The natural tridecapeptide neurotensin has been emerged as a promising therapeutic scaffold for the treatment of neurological diseases and cancer. In this work, we aimed to identify the top 100 most cited original research papers as well as recent key studies related to neurotensins. The Web of Science Core Collection database was searched and the retrieved research articles were analyzed by using the VOSviewer software. The most cited original articles were published between 1973 and 2013. The top-cited article was by Carraway and Leeman reporting the discovery of neurotensin in 1973. The highly cited terms were associated with hypotension and angiotensin-converting-enzyme. The conducted analysis reveals the therapeutic potentials of neurotensin, and further impactful research toward its clinical development is warrantied.

Dechlorination and demethylation of ochratoxin A enhance blocking activity of PXR activation, suppress PXR expression and reduce cytotoxicity

The pregnane X receptor (PXR) has been established to induce chemoresistance and metabolic diseases. Ochratoxin A (OTA), a mycotoxin, decreases the expression of PXR protein in human primary hepatocytes. OTA is chlorinated and has a methylated lactone ring. Both structures are associated with OTA toxicity. The study was to test the hypothesis that structural modifications differentially impact PXR blocking activity over cytotoxicity. To test this hypothesis, OTA-M and OTA-Cl/M were synthesized. OTA-M lacked the methyl group of the lactone-ring, whereas OTA-Cl/M had neither the methyl group nor the chlorine atom. The blocking activity of PXR activation was determined in a stable cell line, harboring both PXR (coding sequence) and its luciferase element reporter. OTA-Cl/M showed the highest blocking activity, followed by OTA-M and OTA. OTA-Cl/M was 60 times as potent as the common PXR blocker ketoconazole based on calculated IC₅₀ values. OTA-Cl/M decreased by 90 % the expression of PXR protein and was the least cytotoxic among the tested compounds. Molecular docking identified that OTA and its derivatives interacted with different sets of residues in PXR, providing a molecular basis for selectivity. Excessive activation of PXR has been implicated in chemoresistance and metabolic diseases. Downregulation of PXR protein expression likely delivers an effective mechanism against structurally diverse PXR agonists.