Producción Científica

 

 

Objective Intervertebral disc degeneration (IVDD) constitutes a crucial pathological foundation for spinal degenerative diseases (SDD) and stands as a primary contributor to both low back pain (LBP) and disability. The progression of IVDD is linked to structural and functional alterations in tissues, where an imbalance in the inflammatory microenvironment can induce extracellular matrix (ECM) degradation, senescence, and apoptosis. This imbalance is a key pathomechanism in the disease’s development, gaining considerable attention in recent years. This study aims to conduct a bibliometric analysis of publications pertaining to the inflammatory mechanisms of IVDD to quantitatively assess current research hotspots and directions. Methods In this study, we queried the Web of Science Core Collection (WOSCC) database covering the period from January 1, 2001, to November 7, 2023. Content in this area was analyzed and visualized using software such as Citespace, Vosviewer, and the bibliometrix package. Results Findings indicate a consistent annual increase in the number of publications, highlighting the widespread attention garnered by research on the inflammatory mechanisms of IVDD. In terms of journal research, Spine emerged with the highest number of publications, along with significantly elevated total citations and average citations compared to other journals. Regarding country analysis, China led in the number of publications, while the USA claimed the highest number of citations and total link strength. Institutional analysis revealed Sun Yat-sen University as having the highest number of publications and total link strength, with Thomas Jefferson University securing the highest total citations. Author analysis identified Ohtori, S. with the highest number of publications, Risbud, M.V. with the highest number of citations, and Inoue, G. with the highest total link strength, all of whom have made significant contributions to the field’s development. Citation and co-citation analyses indicated that highly cited documents primarily focused on classical studies exploring inflammatory mechanisms in IVDD pathogenesis. Keyword analysis showcased the ongoing research hotspot as the further investigation of mechanisms and treatment studies. Recent years have seen a shift towards exploring pyroptosis, necrotic apoptosis, autophagy, ferroptosis, oxidative stress, and bacterial infection, among other mechanisms. In terms of treatment, alongside traditional monomer, drug, and compound therapies for IVDD, research is increasingly concentrating on stem cell therapy, exosomes, hydrogels, and scaffolds. Conclusion This bibliometric analysis of research on inflammatory mechanisms in IVDD provides insights into the current status, hotspots, and potential future trends. These findings can serve as a valuable reference and guide for researchers in the field.

 

 

Nowadays, NPS abuse are continuing to expand in terms of harm and scope, due to its cheap and easy to manufacture anywhere in the world. This study reviewed articles related to seven heavily abused NPS to analyze the structure and trends of NPS abuse. A total of 2476 articles were retrieved based on the search strategy for bibliometric analysis. A significant trend of research in recent years was the increasing number of research on synthetic opioids and designer benzodiazepines, but synthetic cannabinoid and synthetic cathinone still dominate, which were mainly concerned with the development of metabolic models and determining methods as well as their abuse characteristics and reasons. However, with the introduction of class-wide ban on synthetic cannabinoid in China and a series of enhancements in other countries, the abuse of it might decrease to some extent, but more than 20 kinds of synthetic cannabinoid beyond the scope of ban in China still reminded researchers of their potential threats. As for synthetic cathinone, an important phenomenon was some of the drugs first identified during certain period might be more widely distributed in the future. Besides, several problems such as the regulation and prevention mode of emerging NPS, development of testing technologies as well as the interpretation and identification of multiple NPS combinations were also worth paying attention to. This study could help entrants better understand the structure of NPS abuse and provided direction for future research in forensic toxicology.

 

 

The purpose of this study is to analyze the development of research publications on leadership implementation in MSMEs over the last five years. This research used a bibliometric analysis approach with VOSviewer software to develop and visualize the bibliometric network. This research conducted screening based on leadership keywords in MSMEs in the SCOPUS database in the vulnerable years 2018-2023. Publications according to keywords initially amounted to 90 articles, after which 33 articles were filtered. The development of leadership publications in MSMEs in the last 5 years has experienced ups and downs in the number of publications per year, with an increasing trend occurring in 2023, when there were many publications in the field of business, management and accounting, with 33 documents (47.8%). The results of the analysis with VOSviewer and visualization of co-occurrence networks based on leadership keywords in MSMEs revealed 174 items with a division of 12 clusters marked with different colors. The interrelated factors include entrepreneurial leadership, entrepreneurship, entrepreneurial motivation, quality management, digital transformation, competition, and others. The results of the analysis using the VOSviewer application show that there is a relationship between leadership and MSMEs with other networks; thus, additional research could be interesting.

 

 

This research aims to improve problem-solving abilities regarding the greenhouse effect using project-based learning methods supported by Science, Technology, Engineering, and Mathematics (STEM)-Education for Sustainable Development (ESD)-based teaching materials. The study was conducted in multiple phases: (i) utilizing a pretest to gauge students’ prior knowledge, (ii) employing the project-based learning approach to teach the greenhouse effect, and (iii) assessing students’ final knowledge (with a posttest). The research was completed with the observation of temperature variations in a greenhouse prototype. Students monitored and recorded temperature changes over time. Students’ problem-solving abilities increased significantly after being treated using project learning assisted by STEM-ESD teaching materials, imparting more information through the media by stimulating students’ curiosity and interest in science subjects.

 

 

Introduction: Women are underrepresented in the leadership of and participation in randomized controlled trials (RCTs). We conducted a bibliometric review of nephrology RCTs to examine trial leadership by women and participation of women in nephrology RCTs. Methods: A bibliometric review of RCTs published in top medical, surgical, or nephrology journals was conducted using MEDLINE and EMBASE from January 2011 to December 2021. Leadership by women as corresponding authors, women trial participation, and trial characteristics were examined with duplicate independent data extraction. Logistic regression was used to examine associations between trial characteristics and women leadership and trial participation. Results: A total of 1770 studies were screened and 395 RCTs met eligibility criteria. The number (%) of women in corresponding, first, and last authorship positions were as follows: 89 (22%), 109 (28%), and 74 (19%), respectively, without change over time (P = 0.94). The median percentage (interquartile range [IQR]) of women trial participants was 39.0% (13.5%) with no difference between women or men lead authors (P = 0.15). Men lead authors were statistically less likely to enroll women in RCTs. Women lead authors were less likely to be funded by industry (odds ratio [OR]: 0.30; 95% confidence interval [CI]: 0.14–0.63; P = 0.002) or lead international trials (OR: 0.11; 95% CI: 0.01–0.83; P = 0.03). Trials with sex-specific eligibility criteria were more likely to have women leaders (OR: 2.56; 95% CI: 1.19–5.49; P = 0.02) than those without. Discussion: Gender inequalities in RCT leadership and RCT participation exist in nephrology and did not improve over time. Strategies to improve inequalities need to be implemented and evaluated. © 2024 International Society of Nephrology

 

 

The language employed by researchers to define and discuss diseases can itself be a determinant of health. Despite this, the framing of diseases in medical research literature is largely unexplored. This scoping review examines a prevalent medical issue with social determinants influenced by the framing of its pathogenesis: obesity. Specifically, we compare the currently dominant framing of obesity as an addiction to food with the emerging frame of obesity developing from neuroinflammation. We triangulate both corpus linguistic and bibliometric analysis of the top 200 most engaging neuroscience journal articles discussing obesity that were published open access in the past 10 years. The constructed Neurobesity Corpus is available for public use. The scoping review analysis confirmed that neuroinflammation is an emerging way for obesity to be framed in medical research. Importantly, the articles analysed that discussed neuroinflammation were less likely to use crisis terminology, such as referring to an obesity “epidemic”. We highlight a potential relationship between the adoption of addiction frames and the use of stigmatising language in medical research.

 

 

Data-driven expert team formation is a complicated and multifaceted process that requires access to accurate information to identify researchers’ areas and level of expertise and their collaborative prospects. In this respect, bibliometric data represents a valuable and reliable source of information that can be effectively employed in revealing key insights regarding candidates. Due to its complex and complete structure of publication metadata records, IEEE Xplore database may offer the possibility to compute an extensive set of indicators about researchers’ publication production and how they have interacted during time. Considering the case of Politehnica University of Timisoara scholars for the interval 2010–2022, current dataset encapsulates relevant and rich information for assembling multidisciplinary research teams, being also a testing ground for experimenting and calibrating the expert team formation methods and mechanisms.

 

 

Three-dimensional food printing (3DFP) can produce foods with tailored nutritional content, complex shapes and textures. This technology requires food formulations (food inks) with specific rheological properties. Pickering emulsions (PE) have gained attention due to their long-term stability and desirable printable properties, making them an excellent candidate for 3DFP. The purpose of this study is to use bibliometric analysis to identify the most important scientific research on PE used in 3DFP. This includes identifying key authors, countries and universities or institutions where the research was conducted, as well as the primary journals that provide information on this topic. Our study provides insight into the relevance of food ink properties for next-generation 3DFP and the main raw materials used for the development of PE. Out of the 28 original research articles analysed, only 10 countries have studied the application of PE for 3DFP. China and the United Kingdom have been the primary leaders in researching this topic. The Food Hydrocolloids Journal has been the main source of scientific information. The studies cited Pickering stabiliser particles, including soy protein isolate, microcrystalline cellulose and acetylated microcrystalline cellulose, as well as oil phases based on sunflower, canola, olive and soybean oils. High internal phase Pickering emulsions (HIPPEs) have shown great thermal and conductive stability, making them a promising choice for 3DFP post-processing. Further studies should assess the bioavailability and bioaccessibility of the bioactive compounds that are encapsulated. It is also important to explore their potential use in real food systems and to integrate innovative packaging solutions.

 

 

A corncob-derived magnetic solid acid catalyst was synthesized through the sulfonation method and an impregnation process, respectively. In the sulfonation process, the concentrated H2SO4 was utilized as an activation agent to obtain acidic properties. The solution of ferric sulphate-ferrous sulphate was utilized for impregnation to generate the magnetic behaviour of the material. The prepared magnetic acid solid catalyst had a high saturation magnetisation value of 16.48 emu/g and a total acidity of 1.43 mmol/g. The performance of the catalyst was evaluated in the esterification reaction of waste cooking oil. The best result presented 86.12% FFA conversion under reaction conditions of 5% catalyst loading and a 1:15 oil-to-methanol molar ratio at 60oC for 4 h. The catalyst was separated magnetically from the reaction solution and exhibited a good reusability with 61% remaining active after 5 consecutive cycles of reaction. This study resulted in a promising method to obtain magnetic-sulfonated carbon-based catalyst from corncob residue, and it is economical potentially and environmentally friendly for the esterification of low-quality feedstock for biodiesel production.

 

 

Artificial intelligence (AI) has revolutionized many fields, and its potential in healthcare has been increasingly recognized. Based on diverse data sources such as imaging, laboratory tests, medical records, and electrophysiological data, diagnostic AI has witnessed rapid development in recent years. A comprehensive understanding of the development status, contributing factors, and their relationships in the application of AI to medical diagnostics is essential to further promote its use in clinical practice. In this study, we conducted a bibliometric analysis to explore the evolution of task-specific to general-purpose AI for medical diagnostics. We used the Web of Science database to search for relevant articles published between 2010 and 2023, and applied VOSviewer, the R package Bibliometrix, and CiteSpace to analyze collaborative networks and keywords. Our analysis revealed that the field of AI in medical diagnostics has experienced rapid growth in recent years, with a focus on tasks such as image analysis, disease prediction, and decision support. Collaborative networks were observed among researchers and institutions, indicating a trend of global cooperation in this field. Additionally, we identified several key factors contributing to the development of AI in medical diagnostics, including data quality, algorithm design, and computational power. Challenges to progress in the field include model explainability, robustness, and equality, which will require multi-stakeholder, interdisciplinary collaboration to tackle. Our study provides a holistic understanding of the path from task-specific, mono-modal AI toward general-purpose, multimodal AI for medical diagnostics. With the continuous improvement of AI technology and the accumulation of medical data, we believe that AI will play a greater role in medical diagnostics in the future.