Background: There is an immense debate about the factors that could limit the adoption of agroforestry systems. However, one of the most important is the generation of scientific information that supports the viability and benefits of the proposed techniques. Statistical analysis: This work used the Latent Dirichlet Allocation (LDA) modeling method to identify and interpret scientific information on topics in relation to existing categories in a set of documents. It also used the HJ-Biplot method to determine the relationship between the analyzed topics, taking into consideration the years under study. Results: A review of the literature was conducted in this study and a total of 9794 abstracts of scientific articles published between 1993 and 2022 were obtained. The United States, India, Brazil, the United Kingdom, and Germany were the five countries that published the largest number of studies about agroforestry, particularly soil organic carbon, which was the most studied case. The five more frequently studied topics were: soil organic carbon, adoption of agroforestry practices, biodiversity, climatic change global policies, and carbon and climatic change. Conclusion: the LDA and HJ-Biplot statistical methods are useful tools for determining topicality in text analysis in agroforestry and related topics.

Background: Neuroendocrine tumors (NETs) are severe and relatively rare and may affect any organ of the human body. The prevalence of NETs has increased in recent years; however, there seem to be more data on particular types, even though, despite the efforts of different guidelines, there is no consensus on how to identify different types of NETs. In this review, we investigated the countries that published the most articles about NETs, the most frequent organs affected, and the most common related topics. Methods: This work used the Latent Dirichlet Allocation (LDA) method to identify and interpret scientific information in relation to the categories in a set of documents. The HJ-Biplot method was also used to determine the relationship between the analyzed topics, by taking into consideration the years under study. Results: In this study, a literature review was conducted, from which a total of 7658 abstracts of scientific articles published between 1981 and 2020 were extracted. The United States, Germany, United Kingdom, France, and Italy published the majority of studies on NETs, of which pancreatic tumors were the most studied. The five most frequent topics were t_21 (clinical benefit), t_11 (pancreatic neuroendocrine tumors), t_13 (patients one year after treatment), t_17 (prognosis of survival before and after resection), and t_3 (markers for carcinomas). Finally, the results were put through a two-way multivariate analysis (HJ-Biplot), which generated a new interpretation: we grouped topics by year and discovered which NETs were the most relevant for which years. Conclusions: The most frequent topics found in our review highlighted the severity of NETs: patients have a poor prognosis of survival and a high probability of tumor recurrence.

Neuroendocrine tumors (NETs) represent a heterogeneous malignancy group of neoplasms, with a limited amount of data from Latin America. Thus, this observational study aimed to provide data about the prevalence, incidence, and survival rates for NET in Ecuadorian hospitals. The study was conducted using data from the Society for the Fight Against Cancer (SOLCA). We evaluated patients with NETs (2000–2020) using the HJ-Biplot method and Cox proportional hazards. Annual age-adjusted incidence and limited-duration prevalence in multivariable analyses as well as hazard ratios (HRs) for mortality and survival were obtained. In the years 2000–2020, the age-adjusted incidence rate increased by 9-fold in the stomach and by 7-fold in the breast. The incidence rates were 1.38 per 100,000 persons in the lung and at 1.79 per 100,000 persons in gastroenteropancreatic sites (rectum, stomach, and pancreas). The prevalence increased from 0.0027% in 2000 to 0.0736% in 2019 and 0.0245% in 2020. Overall survival was worse for metastatic NETs (HR, 4.061; 95% CI, 1.932–8.540; p < 0.001) and advanced local NETs (HR, 2.348; 95% CI, 1.007–5.475 p < 0.048) than for localized NETs. In conclusion, the NET incidence increased in the last 20 years and survival decreased over time, especially for metastatic tumors in the pancreas and the nostril.

Background: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery is effective for localized RCC, treatments for metastatic RCC have advanced significantly due to better diagnostic, prognostic, and predictive tools. Despite this progress, challenges remain, including long-term drug resistance and the complexity of RCC as a diverse group of diseases rather than a single entity. Objective: The aim of this bibliometric review was a comprehensive analysis of the topics and trends in RCC research, offering a foundation for future investigations. Methods: We used R “Bibliometrix” to conduct a bibliographic search in Scopus and PubMed covering publications from 1975 to 2023 to statistically assess the distribution of publications associated with RCC by year, journal, and country. Topic modeling of RCC research was conducted using latent Dirichlet allocation, a Bayesian network-based probabilistic algorithm that identifies unobserved thematic clusters in a collection of text documents. Trends in the retrieved themes were then characterized by using regression slopes over time, across countries, and in different journals. These trends were visualized as a heatmap, which was then used for hierarchical clustering to group similar topics based on their correlation strengths. Results: A total of 35,228 documents from 3070 sources were found, with a steady yearly growth of 9.86% and 118 participating countries. Thirty topics with the best coherence score were found in 8 crucial domains: treatment and therapies, biomolecular and genetic characteristics, disease characteristics and progression, diagnosis and evaluation, metastasis and dissemination, epidemiology and risk factors, related conditions, and pathological features. The pertinent clustergrams that resulted from the heatmaps mirrored the latent Dirichlet allocation’s algorithm identification of major RCC research subjects. Conclusions: Over 50 years, RCC research’s focus has shifted from diagnosis and assessment to a more thorough understanding of disease characteristics and progression. Because many patients are diagnosed with abdominal imaging studies, an emerging topic in RCC is diagnostic imaging and radiological evolution. The advances in omics technologies and the function of microRNA signature in the progression, diagnosis, therapy targeting, and prognosis of RCC have garnered a lot of attention. The discovery of the genetic background has enhanced our understanding of the growth of RCC. Drug resistance, local RCC ablation, and postoperative surveillance of RCC recurrence following nephrectomy are key future research avenues. The next generation of drug-targeted therapy and immunotherapy will make it possible to successfully treat metastatic RCC following nephrectomy. Neglected topics include the association between ferroptosis and RCC, the long-term assessment of novel treatments, and the application of artificial intelligence on RCC. Our bibliographic review delivered pertinent data for clinical decision-making and the planning of future RCC research.

Background: Patients with psoriasis often experience psychiatric comorbidities, such as depression and anxiety. These comorbidities can lead to poorer adherence to treatment regimens, reduced effectiveness of therapies, and a heightened disease burden. This study aims to explore the scientific output related to psoriasis, depression, and anxiety using a comprehensive analysis combining bibliometric statistical methods. Methods: The study performed a bibliometric analysis of publications related to psoriasis, depression, and anxiety between 1974 and December 2023. This study employed the Latent Dirichlet Allocation (LDA) algorithm to identify key research topics and used the HJ-Biplot technique to visualize the relationships between publications and research indicators. The inclusion criteria were limited to English-language research articles. Results: Over 49 years, the analysis identified 5059 documents published across 1151 sources. The annual growth rate for research was 12.26%. The Journal of the European Academy of Dermatology and Venereology and The British Journal of Dermatology were found to be the leading journals in this field. The United States emerged as the top contributor, followed by China, Italy, and Germany. The most prevalent research topics were inflammation and cellular function, with a significant focus on patient treatment and the impact of depression and anxiety. Conclusions: This bibliometric analysis underscores the increasing of studies on the comorbidities of depression and anxiety in patients with psoriasis. This study provides a comprehensive overview of research trends and emerging topics in this field, offering valuable insights for future investigations.