Scientific Landscape Research Articles

Computer Analysis of Scientific Texts to Identify Ideological Narratives

This article is devoted to the problem of identifying hidden ideological attitudes in scientific articles on economics, as well as defining methods for analyzing the ideological landscape of Russian economic science. The problem of this review article lies in the absence of a developed generally accepted approach to the textual analysis of scientific publications. Thus, there is an extremely wide list of methods that can be used in this case. Nevertheless, the development of the most effective methodology requires a comprehensive analysis of existing approaches individually and a comparison of each of them with the others. The authors associate the solution of the problem of choice in the presence of several approaches and a variety of methods with the definition of such a basis that would allow the formation of a methodology that includes ideological classification within the framework of economic scientific literature, the use of computational linguistics tools, in particular natural language processing, in addition to classical narrative analysis tools to identify "ideological narratives". In this regard, the methods of identifying implicit meanings in economic texts are considered in detail. The proposed tools can be used in further research on this or related topics.

Public management of scientists’ potential as a source of economic development: A bibliometric analysis

Particular hopes have always been placed on the potential of scientists because they can act as a driving force for effective government. Understanding the importance of scientists ensured progress and prosperity for leading civilizations. This study aims to identify an evolutionary-chronological, geographical, and contextual scientific landscape of the development and management of the potential of scientists through a comprehensive bibliometric analysis. Initially, 5619 publications in the Scopus database were selected from 1957 to 2023. The evolution of knowledge about the importance of public administration of scientific personnel began in 1957 and reached its peak in 2019. Authors from the USA, Great Britain, and Australia have published more about the significance of managing the potential of scientific personnel, and strong schools of knowledge about scientific personnel are concentrated in the USA, France, Canada, and Australia. The analysis of the research’s conceptual orientation shows that publications in environmental and social sciences dominate this sphere. In addition, the bibliometric analysis results show that public management of scientific personnel will bring benefits such as effective government policy decisions, increased innovation activity, commercialization, and improvement of the population’s social life. The results of this study lay the foundation for future research that should improve the management of scientific personnel’s potential. AcknowledgmentsThis study is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19579256 “Mechanisms for empowering women in scientific activity in the interests of the development of the innovative economy of Kazakhstan”, 2023–2025).

A Tale of Many Marine Stations: 150 Years of Marine Ecology in the Eastern English Channel

AbstractLong before marine laboratories were commonplace, a few visionary scientists created the first of a growing number of biological field stations in the second half of the 19th century. This article tells the 150‐year tale of the rise and fall of six marine stations that belonged to three different universities and were sometimes operated simultaneously along a stretch of merely ten kilometers of the French coastline of the eastern English Channel. Specifically, I focus on the intellectual lineages, sense of brotherhood, rivalries, and even the indifference between individuals and institutions that shaped the local scientific landscape and paved the way for what became modern marine biology and ecology, and oceanography.

Mapping the scientific landscape of knowledge management in IT SMEs: a bibliometric analysis

Mapping the scientific landscape of knowledge management in IT SMEs: a bibliometric analysis

How mentoring and a shift in mindset and practices can help navigate fast-paced science

Abstract In the competitive realm of academia, the pursuit of meaningful knowledge often collides with the imperative to publish quickly and frequently, sidelining patient investigation and deep understanding. This article aims to share critical insights into this issue, sparking further discussions about the challenges of fast-paced science and cultivating a more ethical scientific landscape, one that values exploration and ingenuity over rushed output and flashy headlines. The narrative traces the growing disillusionment of the first author with the prevailing publish-or-perish culture and her concerns about its impact on research quality and genuine collaboration. The article showcases how a mentoring programme for women postdoctoral researchers and network activities have aided her in navigating these challenges and carving out her career path. Her experiences are enriched by the perspectives of the second author, the coordinator of the mentoring programme. Through one-on-one mentoring, get-togethers, and workshops, the first author gained the inspiration, skills, and encouragement necessary to rekindle her commitment to science. The lesson learned is the importance of providing scientists with a guided, safe, and brave space for open dialogue about individual concerns and general working conditions in academia. Examples are provided that illustrate potential strategies and practices for challenging the status quo. By nurturing an environment that puts quality before quantity, academia can pave the way for transformative discoveries and profound understanding across all career levels.

Bridging Quantum Mechanics and Hydrogen Technology: The MEQ Framework

The quest for sustainable and renewable energy sources has become a paramount objective in the contemporary scientific and technological landscape. Amidst various alternatives, hydrogen emerges as a promising candidate, offering a clean, efficient, and versatile fuel option. However, the efficient and cost-effective production of hydrogen, particularly through water splitting, presents significant scientific and engineering challenges. This article delves into the innovative convergence of theoretical physics and practical engineering through the lens of the McGinty Equation (MEQ). The MEQ framework, a novel integration of quantum field theory and fractal potentials, proposes groundbreaking approaches to optimize the water-splitting process at the atomic and molecular levels. This exploration is not merely an academic exercise but a step towards tangible solutions in the pursuit of sustainable energy, with the MEQ playing a pivotal role in enhancing hydrogen production technologies.

Prompt Engineering Paradigms for Medical Applications: Scoping Review.

Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance. Prompt engineering offers a novel approach by designing tailored prompts to guide models in exploiting clinically relevant information from complex medical texts. Despite its promise, the efficacy of prompt engineering in the medical domain remains to be fully explored. The aim of the study is to review research efforts and technical approaches in prompt engineering for medical applications as well as provide an overview of opportunities and challenges for clinical practice. Databases indexing the fields of medicine, computer science, and medical informatics were queried in order to identify relevant published papers. Since prompt engineering is an emerging field, preprint databases were also considered. Multiple data were extracted, such as the prompt paradigm, the involved LLMs, the languages of the study, the domain of the topic, the baselines, and several learning, design, and architecture strategies specific to prompt engineering. We include studies that apply prompt engineering-based methods to the medical domain, published between 2022 and 2024, and covering multiple prompt paradigms such as prompt learning (PL), prompt tuning (PT), and prompt design (PD). We included 114 recent prompt engineering studies. Among the 3 prompt paradigms, we have observed that PD is the most prevalent (78 papers). In 12 papers, PD, PL, and PT terms were used interchangeably. While ChatGPT is the most commonly used LLM, we have identified 7 studies using this LLM on a sensitive clinical data set. Chain-of-thought, present in 17 studies, emerges as the most frequent PD technique. While PL and PT papers typically provide a baseline for evaluating prompt-based approaches, 61% (48/78) of the PD studies do not report any nonprompt-related baseline. Finally, we individually examine each of the key prompt engineering-specific information reported across papers and find that many studies neglect to explicitly mention them, posing a challenge for advancing prompt engineering research. In addition to reporting on trends and the scientific landscape of prompt engineering, we provide reporting guidelines for future studies to help advance research in the medical field. We also disclose tables and figures summarizing medical prompt engineering papers available and hope that future contributions will leverage these existing works to better advance the field.

Uncovering the scientific landscape: A bibliometric and visualized analysis of artificial intelligence in traditional Chinese medicine

The emergence of artificial intelligence (AI) technology has presented new challenges and opportunities for Traditional Chinese Medicine (TCM), aiming to provide objective assessments and improve clinical effectiveness. However, there is a lack of comprehensive analyses on the research trajectory, key directions, current trends, and future perspectives in this field. This research aims to comprehensively update the progress of AI in TCM over the past 24 years, based on data from the Web of Science database covering January 1, 2000, to March 1, 2024. Using advanced analytical tools, we conducted detailed bibliometric and visual analyses. The results highlight China's predominant influence, contributing 54.35 % of the total publications and playing a key role in shaping research in this field. Significant productivity was observed at institutions such as the China Academy of Chinese Medical Sciences, Beijing University of Chinese Medicine, and Shanghai University of Traditional Chinese Medicine, with Wang Yu being the most prolific contributor. The journal Molecules contributed the most publications in this field. This study identified hepatocellular carcinoma, chemical and drug-induced liver injury, Papillon-Lefèvre disease, Parkinson's disease, and anorexia as the most significant disorders researched. This comprehensive bibliometric assessment benefits both seasoned researchers and newcomers, offering quick access to essential information and fostering the generation of innovative ideas in this field.

The Importance of Statistics in Medical Healthcare

Abstract: Statistical principles play a fundamental role in shaping the landscape of medical science by providing a structured framework for analyzing data, drawing conclusions, and making informed decisions in healthcare settings. In the realm of medical research, statistical principles are crucial for designing experiments, interpreting results, and ensuring the reliability and validity of findings. Key statistical concepts like hypothesis testing, confidence intervals, regression analysis, and survival analysis are extensively utilized in medical studies to assess the effectiveness of treatments, understand disease patterns, and evaluate healthcare interventions. These principles enable healthcare professionals to make evidence-based decisions, tailor treatments to individual patient needs, and continuously improve the quality of care provided to patients. The role of statistics in medical research starts at the planning stage of a clinical trial or laboratory experiment to establish the design and size of an experiment that will ensure a good prospect of detecting effects of clinical or scientific interest. Statistics is again used during the analysis of data (sample data) to make inferences valid in a wider population. In simple situations computation of simple quantities such as P-values, confidence intervals, standard deviations, standard errors or application of some standard parametric or nonparametric tests may suffice.

THE ROLE OF STEM LAB EXPERIMENTS IN BUILDING SCIENCE LITERACY IN CHEMISTRY EDUCATION

This article brings out how much the role played by STEM laboratories boosts science literacy, with particular reference to chemistry. It looks at how this experiential learning reconciles the disparity that always exists between abstract theoretical views and practical understanding, hence enhancing effective appreciation of complex scientific principles. By conducting experiments in a laboratory, students receive the most crucial aspects to become successful in their academic and working career in STEM. This paper goes further to show an insight on how these hands-on experiences increase student involvement, motivation and create an environment that encourages working together; something taken to be parallel to what is involved in scientific research working. This paper also goes into how equipping STEM labs with cutting-edge technologies like virtual simulations and the corresponding digital tools would be like. These technologies do not only support learning but also fully prepare students for the now highly technological and digitized modern landscape of science and industry. It is about the creation of a scientific and creatively competent generation of thinkers who ought to provide a solution to most of the problems that face the globe in the 21st century. The global workforce requirements now carry new emphasis on science, technology, engineering, and mathematics. Therein, educational systems need to alter themselves to fit that bill. Without proper incorporation of lab-based learning, the paper argues, we cannot be in a position to prepare and equip our students for a future that will require both scientific knowledge and technological proficiency.

ANALYSIS OF RESEARCH TRENDS IN THE FIELD OF DIGITAL FINANCE BASED ON BIBLIOMETRIC DATA

The spread of digitalisation has led to the global penetration of digital finance in all sectors of the economy. The high relevance of the problem of digital finance necessitates deepening research in this area, in particular by carrying out a comprehensive analysis of the accumulated knowledge in it. The aim of the present research is to reveal the main trends and determinants of the evolution of scientific investigations in the field of digital finance by means of a bibliometric analysis of publications in the journals indexed by the Scopus scientometric database. This study was carried out in accordance with the traditional approach to bibliometric analysis and is aimed at the following objectives: determining the features of the scientific landscape in the field of digital finance by carrying out an evolutionary analysis of publication activity; identification of the main determinants for the development of research by mapping and clustering the existing array of publications using VOSviewer software. The time frame of the study was set as 2008 – 1st quarter of 2024. The results showed that the term «digital finance» is of an interdisciplinary nature. It is found that China is leading in the number of publications in this area, followed by the United States, Great Britain, and India by a notable margin. 8 clusters have been selected that characterise the key research areas. The results of the bibliometric analysis showed that the most significant development of research in the field of digital finance was in 2021-2023, with an emphasis on the development of fintech, banking services and cryptocurrencies. In 2023, it was found that the number of studies on the following issues increased: the Green Deal, COVID-19, ecosystem formation, and green energy. They are considered to be research areas that require further development in the near future.

Current status and trends of urinary incontinence research in recent 10 years based on VOSviewer visualized analysis: An observational study.

Urinary incontinence (UI) is prevalent and imposes significant social and economic burdens. This study reviews the literature on UI, assesses the current research status, and projects future trends. To visualize and analyze UI-related research, summarize and generalize the knowledge framework of the global UI field, and explore the current state of research and emerging trends, we conducted a comprehensive search of UI-related studies from 2014 to 2024 using the Web of Science Core Collection. Utilizing VOSviewer software, we mapped the scientific landscape and performed visual analytics on collaborative and co-citation networks, keyword co-occurrences, emergent clusters, and timeline mapping to elucidate the research dynamics. A total of 4326 publications were retrieved for further analysis. The United States ranked first in terms of the total number of publications, number of citations, and publication H-index. In terms of institutions, the University of California System had the most total citations and the highest H-index. Neurology and Urodynamics had the most articles published, the highest citation frequency, and the highest H-index. The author with the most citations and the highest average number of citations per article is Abrams P. The author with the highest H-index is Peyronnet B. Based on the keyword analysis, the articles were categorized into several main directions: epidemiological studies, diagnostic studies, treatment studies, female UI studies, and male UI studies. Epidemiology, treatment, and male UI are expected to continue as hot topics. This study demonstrates that UI research is more advanced in Europe and North America and that Neurourology and Urodynamics is the most influential journal in the field. In addition, epidemiology, treatment, and male UI will continue to be prominent topics. Our study contributes to a more comprehensive understanding of the current state of UI research and provides insights into future research directions in the field.

Beyond fidelity: unveiling the landscape of teacher adaptation in social and emotional learning programs

Despite the rapid growth of social and emotional learning (SEL) programs, research on program implementation has lagged behind. In the landscape of implementation science for SEL programs, fidelity and dosage are often emphasized, but important aspects like adaptation have largely been neglected. This qualitative study addresses three research questions: (1) do teachers make adaptations when implementing SEL programs? (2) how do teachers adapt these lessons? and (3) why do teachers adapt these lessons? Data on adaptation were obtained from 17 elementary and middle school teachers via interviews and open-ended responses from implementation diaries from two randomized controlled trials of SEL programs. Findings revealed that all teachers made at least one adaptation, including structural adaptations (i.e., changes to content, sequencing, and timing) and process adaptations (i.e., adaptations made to how the lesson was delivered and experienced). Teachers also described reasons for adapting that were broadly due to student factors, program factors, and contextual factors. These results shed light on the numerous ways in which teachers adapt SEL programs and the array of complex reasons that lead to the adaptation of lessons within these types of programs and highlight the critical need to consider teacher adaptations in SEL program implementation. Future research should explore the impact of these adaptations on student outcomes and develop robust methods to capture and analyze adaptations.

Monoterpenoid synergy: a new frontier in biological applications.

Monoterpenoids, compounds found in various organisms, have diverse applications in various industries. Their effectiveness is influenced by the oil's chemical composition, which in turn is influenced by plant genotype, environmental conditions, cultivation practices, and plant development stage. They are used in various industries due to their distinctive odor and taste, serving as ingredients, additives, insecticides, and repellents. These compounds have synergistic properties, resulting in superior combined effects over discrete ones, potentially beneficial for various health purposes. Many experimental studies have investigated their interactions with other ingredients and their antibacterial, insecticidal, antifungal, anticancer, anti-inflammatory, and antioxidant properties. This review discusses potential synergistic interactions between monoterpenoids and other compounds, their sources, and biological functions. It also emphasizes the urgent need for more research on their bioavailability and toxicity, underlining the importance and relevance of this comprehensive study in the current scientific landscape.

A dual methodology employing ion-pair chromatography and built-in UV spectrophotometry for quantifying recently approved combination of mometasone and indacaterol in a novel combined metered dose inhaler: assessing the greenness, carbon footprint, blueness, and whiteness

Developing analytical techniques that align with green and sustainable chemistry principles is crucial in today's scientific landscape. This work introduces two innovative approaches for the simultaneous quantification of indacaterol (IND) and mometasone (MOM), a recently approved combination therapy for chronic obstructive pulmonary disease. These methods—rapid isocratic ion pair chromatography (IPC) and UV–visible spectrophotometry—demonstrate improved environmental sustainability, cost-effectiveness, and versatility compared to existing techniques. The optimized 4-min IPC method achieved excellent resolution (retention times 2.18 ± 0.1 min for IND and 3.95 ± 0.1 min for MOM), peak symmetry, and sensitivity. It utilizes a low-cost ion pair mobile phase of acetonitrile and acidified water containing 0.025% sodium dodecyl sulfate (50:50% v/v), making it suitable for laboratories with standard chromatographic instruments. The spectrophotometric approach offers two procedures: first derivative and ratio derivative methods. These serve as simplified, low-cost alternatives for resource-limited laboratories without access to advanced instruments. Both techniques feature simplified protocols that minimize extraction and fractionation steps. Comprehensive validation confirmed outstanding accuracy (98–102%) and precision (%2 <). Sustainability assessments using ComplexGAPI, AGREE, carbon footprint, BAGI, and RGB12 tools demonstrated enhanced environmental performance compared to existing methods. The IPC and spectrophotometry methods achieved greenness scores of 0.81 and 0.85, respectively, surpassing the 0.63–0.67 range of reported techniques. Additionally, they showed lower carbon footprints of 0.035 and 0.022 kg CO2 equivalent emissions per sample, compared to 0.079–0.092 kg for conventional procedures. The application of novel "blueness" and "whiteness" concepts using BAGI and RGB12 algorithms further confirmed superior sustainability, with scores of 87.5 & 90 for blueness and 88.1 & 89.8 for whiteness. Successfully applied to quantify IND and MOM in combined capsules, this work provides a model for eco-friendly pharmaceutical analysis that maintains high analytical reliability while improving sustainability metrics.

Research on the Construction of Intelligent System of Landscape in Science and Innovation Park of Smart City - Based on the Concept of Smart Garden Design

Research on the Construction of Intelligent System of Landscape in Science and Innovation Park of Smart City - Based on the Concept of Smart Garden Design

Current research status and emerging trends in wheat: An integrated scientometric analysis based on ploidy uncovers hidden footprints in the scientific landscape

Wheat, a highly versatile staple crop cultivated extensively for its grains on a global scale, is poised to experience increased demand to sustain the burgeoning population, owing to its superior nutritional potential. Modern wheat, a hexaploid species, has evolved through the introgression of numerous preceding ploidies, including Einkorn, Emmer, Aegilops, and others, each possessing distinct qualitative and quantitative traits. Scientometric and topical analyses serve as effective tools to quantitatively evaluate scientific research by measuring the knowledge expressed in scientific publications and keywords. Thus, comprehending the research status regarding wheat domestication events within primary, secondary, and tertiary gene pools is paramount for enhancing wheat production. In this study, we analyze data retrieved from PubMed to elucidate the research status and identify bottlenecks across different ploidy of genomic pools of wheat. The publication trends on wheat have experienced exponential growth over the past three decades, with China emerging as a leading center for publications. In contrast to the publication frequency observed in hexaploid common wheat, scholarly output concerning Einkorn and Aegilops is approximately tenfold lesser, with emmer trailing behind at three times fewer publications. This discrepancy underscores the prioritization of expedited research initiatives targeting these species, aimed at elucidating latent biological characteristics and optimizing their breeding capabilities. Keywords such as “stress,” “GWAS,” and “gene” are prominent, reflecting the challenges posed by climatic factors on wheat production and their mitigation through molecular breeding and gene manipulation. Notably, the keyword “einkorn” highlights its potential as a donor for fine-tuning traits related to wheat adaptation processes and quality, crucial for modern wheat’s survivability under adverse climates. Conversely, higher publication rates on emmer are primarily associated with Italy, possibly due to its favorable Mediterranean climate for tetraploid wheat. Keywords like “Pasta” and “Ochratoxin, DON” are prevalent, with the former being derived from durum wheat and the latter being reported in higher amounts in durum compared to other wheat species, rendering it less suitable for consumption. Enriched keywords such as “genome” and “resistance” underscore the critical characteristics of Aegilops. Other significant keywords like “Aceria tosichella” possibly indicate multiple stages of resistance conferred by Aegilops, while the presence of the grain softness protein “puroindoline” enhances its acceptability for donation by Aegilops. Spelt, a close relative of common wheat, exhibits a research trend with thousands of annual publications and enriched keywords such as “stress” and “yield” reflect the current scientific emphasis on wheat research. Furthermore, hierarchical keywords like “bio-control” and “celiac disease” merit consideration for future research on hexaploid wheat.

Conversational and generative artificial intelligence and human–chatbot interaction in education and research

AbstractArtificial intelligence (AI) as a disruptive technology is not new. However, its recent evolution, engineered by technological transformation, big data analytics, and quantum computing, produces conversational and generative AI (CGAI/GenAI) and human‐like chatbots that disrupt conventional operations and methods in different fields. This study investigates the scientific landscape of CGAI and human–chatbot interaction/collaboration and evaluates use cases, benefits, challenges, and policy implications for multidisciplinary education and allied industry operations. The publications trend showed that just 4% (n = 75) occurred during 2006–2018, while 2019–2023 experienced astronomical growth (n = 1763 or 96%). The prominent use cases of CGAI (e.g., ChatGPT) for teaching, learning, and research activities occurred in computer science (multidisciplinary and AI; 32%), medical/healthcare (17%), engineering (7%), and business fields (6%). The intellectual structure shows strong collaboration among eminent multidisciplinary sources in business, information systems, and other areas. The thematic structure highlights prominent CGAI use cases, including improved user experience in human–computer interaction, computer programs/code generation, and systems creation. Widespread CGAI usefulness for teachers, researchers, and learners includes syllabi/course content generation, testing aids, and academic writing. The concerns about abuse and misuse (plagiarism, academic integrity, privacy violations) and issues about misinformation, danger of self‐diagnoses, and patient privacy in medical/healthcare applications are prominent. Formulating strategies and policies to address potential CGAI challenges in teaching/learning and practice are priorities. Developing discipline‐based automatic detection of GenAI contents to check abuse is proposed. In operational/operations research areas, proper CGAI/GenAI integration with modeling and decision support systems requires further studies.

An Overview of Language Shift from French to English in Scientific Articles

The drastic language shift that Algeria has witnessed in recent years, notably towards English, has gained significant ground. This paper examines the evolving dynamics of scientific discourse translation in Algeria. Since gaining independence in 1962, Algeria has been closely associated with Francophone networks, with the French historically dominating scientific communication. However, in recent decades, English has gained predominance in scientific discourse, surpassing French. Through a comprehensive review of academic literature, this paper explores the historical context that has shaped Algeria’s linguistic landscape, leading to this significant transition. The study delves into concepts such as language shift, domain loss, terminology, and translation to understand their impact and relationship within multilingual research contexts. By examining these concepts, the paper seeks to illustrate how they have influenced the shift towards English in Algerian scientific communication. Additionally, the paper investigates the underlying motivations for the increased adoption of English as the primary language of scientific discourse among Algerian researchers and institutions. Key factors include the influence of international scientific norms, the availability of extensive English language resources, participation in global research collaborations, and the enhanced visibility that English provides in the global scientific arena. While this transition to English offers numerous opportunities for Algerian researchers, such as improved access to international research networks and increased publication potential, it also presents challenges. Linguistic and cultural barriers may hinder effective communication and collaboration, potentially impacting the quality of research and its dissemination. The paper concludes by analyzing the intricate ramifications of these translation trends and their implications for Algeria’s scientific research landscape. Understanding these dynamics is crucial for developing strategies to support researchers through this transition and ensuring their successful integration into the global scientific community.

A bibliometric analysis of light chain amyloidosis from 2005 to 2024: research trends and hot spots.

Light chain (AL) amyloidosis stands as the most prevalent subtype of systemic amyloidosis, encompassing a group of rare diseases. Here, we evaluated the scientific landscape of AL amyloidosis to investigate research trends and identify hotspots within the field. Relevant studies on AL amyloidosis published over the past two decades were retrieved from the Web of Science Core Collection. The publications between 2005 and 2024 were subjected to bibliometric analyses, leveraging tools including CiteSpace, VOSviewer, RStudio and MS Excel to analyse and visualize the annual publication trend, co-occurrence patterns, collaborative networks among countries, organizations, and authors. Burst keywords and references were also examined to obtain the research history, and emerging hotspots. The bibliometric analysis included 2,864 articles published between 2005 and 2024. The most productive journal is Amyloid-Journal of Protein Folding Disorders. The United States, along with several developed nations, emerges as a dominant force in international AL amyloidosis research. "AL amyloidosis" and "cardiac amyloidosis" were the primary hotspots over the past two decades, and "Biomarkers," "Cardiac amyloidosis," and "treatment" would be future trends. This bibliometric analysis examined the research developments in AL amyloidosis over the past two decades using bibliometric software. Recent research in this field primarily focuses on two main areas: clinical diagnosis and treatment of AL amyloidosis, as well as cardiac amyloidosis. Emphasis is placed on understanding the mechanisms underlying immunoglobulin light chain aggregation and deposition to mitigate organ involvement.