Research Hotspot Research Articles

Cancer phenomics research hotspots and development trends: a bibliometric analysis from 2000 to 2023

The emerging field of cancer phenomics provides comprehensive insights into tumor heterogeneity, promoting advances in personalized oncology. This study explores current research hotspots and future development trends in cancer phenomics through a bibliometric analysis of research from 2000 to 2023. Using data from the Web of Science Core Collection, we analyzed 1260 publications to identify global contributions and collaborative networks. Employing CiteSpace and VOSviewer tools, we examined research trends, highlighting disease progression, multi-omics integration, and phenotypic drug discovery as major focus areas. Key findings reveal that the United States, China, and the United Kingdom are leading contributors, with top institutions such as Harvard Medical School advancing research and fostering international collaboration. Additionally, the analysis underscores the prominence of double-positive (DP) T cells and natural killer (NK) cells in cancer immunology, showcasing their potential roles in phenotypic screening and cancer therapeutics. Despite advancements, the study notes ongoing challenges in translating phenomics research to clinical applications, suggesting that enhanced global partnerships and technological integration are essential. This analysis offers valuable perspectives for future research and highlights phenomics' transformative potential in precision oncology, advocating for its role in advancing cancer diagnosis, treatment, and prevention.

Review of the unified theory of acceptance and use of technology (UTAUT) in education: A bibliometric visual analysis based on CiteSpace

This paper conducts a bibliometric visual analysis of the application of the Unified Theory of Acceptance and Use of Technology (UTAUT) in education, using CiteSpace software. Drawing on data from the Web of Science, the study explores research trends and influential works related to UTAUT from 2008 to 2023. It highlights the growing use of educational technologies such as mobile learning and virtual reality tools. The analysis reveals the most cited articles, journals, and key institutions involved in UTAUT research. Furthermore, keyword analysis identifies research hot spots, such as artificial intelligence and behavioral intentions. This study contributes to the understanding of how UTAUT has been used to predict technology adoption in education and provides recommendations for future research directions based on emerging trends in the digital learning environment.

Trends in exercise therapy research for neurological diseases: a bibliometric and visualization approach from 2000 to 2024

BackgroundNeurological disorders are one of the major global health burdens, and exercise therapy has been widely recognized as a beneficial intervention. However, the existing literature has primarily focused on summarizing the interventions, complications, and influencing factors, with relatively limited systematic comparisons and summaries.MethodsThis study employed a bibliometric analysis approach, using VOSviewer and CiteSpace software to analyze the literature on the application of exercise therapy in neurological disorders from 2000 to 2024, including annual publication volumes, countries/regions, institutions, authors, journals, keyword co-occurrences, keyword clustering, keyword timelines, and keyword bursts.ResultsThe study found that the United States is the leading contributor in this field, and the University of Toronto and the University of Illinois are the most active research institutions. Keyword analysis revealed that the research hotspots in this field are concentrated on the role of exercise therapy in the prevention, treatment, rehabilitation, and improvement of quality of life for neurological disorders, and are gradually delving into its potential physiological mechanisms.ConclusionThis study provides valuable references for subsequent research in this field, helping to track the research frontiers and predict future research directions. Future research could further explore the specific mechanisms and clinical efficacy for different neurological diseases, providing more targeted evidence for clinical practice.

Online Worker Scheduling for Maximizing Long-Term Utility in Crowdsourcing with Unknown Quality

Spatiotemporal Mobile CrowdSourcing (MCS) is a new intelligent sensing paradigm for large-scale data acquisition where requesters can recruit a crowd of workers to perform data collection tasks. How to recruit suitable workers in a dynamic environment to maximize platform utility is a key issue and has become a research hotspot. Many past studies have made great efforts in this regard, but most of them either assume that the worker quality is known in advance or ignore the limitations of workers’ short-term ability to provide resources. In this paper, we consider a platform-centered online spatiotemporal MCS system where mobile workers have both long-term and short-term constraints for providing resources, and their quality is unknown to the platform, while the platform has a long-term budget constraint for recruiting workers. We aim to find an online worker scheduling scheme to maximize the platform’s long-term utility without violating the constraints of both workers and the platform. To address this problem, we first transform the long-term utility maximization problem into a real-time utility maximization problem by leveraging the Lyapunov optimization, then design algorithms based on the Upper Confidence Bound (UCB) and Markov approximation to solve each real-time utility maximization problem with unknown worker quality. We demonstrate that our UCB-based algorithm has a sublinear regret and prove that our proposed framework has a performance guarantee for the addressed problem. Finally, we evaluate our design through numerical simulation experiments, and the results demonstrate the effectiveness of our algorithm.

The application of ChatGPT in nursing: a bibliometric and visualized analysis

ObjectiveWith the development of ChatGPT, the number of studies within the nursing field has increased. The sophisticated language capabilities of ChatGPT, coupled with its exceptional precision, offer significant support within the nursing field, which includes clinical nursing, nursing education, and the clinical decision-making process. Preliminary findings suggest positive outcomes, underscoring its potential as a valuable resource for enhancing clinical care. However, a comprehensive analysis of this domain is lacking, and the application of bibliometric methods remains rare. This study aims to describe and predict the developmental trajectory of the discipline, identify research hotspots and trends, and provide a comprehensive framework for the integration of ChatGPT in nursing.MethodsFollowing the development of a search strategy in collaboration with librarians, the implementation of this strategy occurred in the Web of Science Core Collection (WoSCC) on June 30, 2024. For bibliometric and visual analyses—including evaluations of sources, institutions, countries, author collaboration networks, and keywords—Bibliometrix (version 4.4.2) and CiteSpace (version 6.2.R2 Basic) were employed.ResultsA total of 81 articles published by 67 authors were retrieved from the Web of Science Core Collection database, covering the period of June 30, 2024. The number of published studies has exhibited an increasing trend. The “European Journal of Cardiovascular Nursing” emerged as the most productive journals, while the USA, the UK, and China were identified as the leading countries in terms of publication output. The top 10 keywords identified in this study include artificial intelligence, nursing education, large language models, ChatGPT, natural language processing, generative artificial intelligence, care, nursing practice, clinical decision-making, and deep learning.ConclusionChatGPT is an emerging tool in the nursing field, currently in the foundational research phase. While there is significant international collaboration, cooperation among author groups remains somewhat limited. Studies focusing on ChatGPT in nursing primarily concentrate on two key themes: (1) the deep learning of ChatGPT in nursing and (2) the feasibility of its application. It is essential for nurses across various specialties to collaborate in exploring the diverse applications of ChatGPT within their domains, thereby fostering the ongoing development and enhancement of this technology.

Developmental trends and knowledge frameworks in the application of radiomics in prostate cancer: a bibliometric analysis from 2000 to 2024

BackgroundThis research utilized the bibliometrics method to analyze the published literature related to prostate cancer (PCa) imaging. Furthermore, current knowledge and research hotspots of radiomics in PCa diagnosis and treatment were comprehensively reviewed, as well as progress and emerging trends in field were explored.MethodsIn this investigation, the relevant literature on radiomics, and PCa was retrieved from Web of Science Core Collection (WoSCC) databases from 2000 and 2024. Furthermore, a comprehensive bibliometric analysis was carried out using advanced tools like CiteSpace6.2, VOS viewer, and the 'bibliometrix' package of R software to visualize the annual distribution of publications across various aspects such as authors, countries, journals, institutions, and keywords.ResultsThis analysis included 593 from 58 countries including China and the United States. Chinese Academy of Sciences and Frontiers in Oncology were the institutions and journals that publish the most relevant articles, -while Radiology journal had the greatest number of co-cited publications. Furthermore, 3,621 authors published on this topic, of which Madabhushi Anant and Stoyanova Radka had the highest contributions. Moreover, Lambin, P. had the most co-citations. In addition, the diagnostic characteristics of radiomics in PCa imaging and treatment strategies are the current research focal points. The establishment of multi-functional imaging techniques and independent factor models warrants future investigation.ConclusionsIn summary, this analysis revealed that the research on PCa imaging is developing vigorously, focusing on the diagnostic methods and intervention measures of imaging in PCa diagnosis and treatment. In the future, there is an urgent need for improved collaboration and communication among countries and institutions.

A Method for Classification of Chest Motion base on Time-domain Signals of IR-UWB Radar

Abstract As an instrument for wireless sensing and measurement, radar is widely used in target tracking and localization. And Impulse Radio Ultra-Wideband (IR-UWB) radar, with its excellent characteristics of high resolution and large bandwidth, has become a research hotspot in the fields of perception and ranging, smart home and so on. However, when radar sampling rates are low, It's hard to recognize human activity only based on radar images. Also when the amplitude of human movement is too tiny, it is difficult to recognize the human activitise just by the energy amplitude of the echo. This paper proposes a novel method to classify small amplitude human chest motions by time-domain signal from Impulse Radio Ultra-Wideband (IR-UWB) radar with a low sampling rate. Based on the energy and phase of the radar echoes, our method can detect the onset of human's motion and differentiate between normal breathing and apnea. Additionally, the amplitude of human's motion can be distinguished based on the distance range spanned by the echoes. Finally, a two-step classification method is employed to distinguish between yawning and coughing in small motions. The paper reports a classification precision of 0.9186, recall rate of 0.9163, and F1 score of 0.9172 for the proposed method under experimental conditions. The experimental performance outperformed the adopted comparison method based on MobileNetV3. We also tested the performance of the proposed method under different angle and distance conditions, which demonstrates the feasibility of our method.

Global Research Trends and Future Directions for Buckwheat as a Smart Crop: A Bibliometric and Content Analysis

Buckwheat (Fagopyrum esculentum Moench) originates from Central Asia and is widely distributed around the world. It is recognized as a versatile food crop due to its nutritional richness. Conducting a systematic analysis of the literature on buckwheat research can help scientific researchers achieve a better understanding of the current state, hotspots, and trends in this field, thereby promoting the sustainable development of buckwheat. The study retrieved a total of 4512 articles related to buckwheat from the Web of Science Core Collection (WoSCC), involving 104 countries (regions), 3220 institutions, and 12,840 authors. The number of research papers on buckwheat is gradually increasing. China, Japan, Poland, the United States, and South Korea were the top five countries in terms of publication volume in this field. Among the top 10 institutions in terms of publication volume, Chinese institutions account for 60%. Northwest A & F University held a leading position in the number of papers published and cited. Research on buckwheat shows that both domestic and international research institutions tend to collaborate more with institutions within their own countries. A comprehensive analysis of journals with a high number of publications and citations in buckwheat research indicated that studies primarily focus on its use as food and its active substances. Analysis of the authors and cited authors indicated that Wu Qi and Zhu F, among others, have high reputations and significant influence in this field. Reference analysis has determined that early research primarily focused on buckwheat as a pseudo-cereal food; mid-term research mainly concentrated on its active substances and cultivation; later research became more comprehensive, focusing on its potential in food, biotechnology, and medical health, which gradually emerged as trends and hot topics. Keyword analysis indicates that buckwheat flour, antioxidant activity, protective biological control, and buckwheat husk are current research hotspots. This study systematically summarizes the current status of research in the field, identifies research hotspots and trends, and provides a reference for future investigations into buckwheat.

Research progress on acid mine drainage treatment based on CiteSpace analysis

Acid mine drainage has always been of global concern, primarily due to its low pH, high concentration of heavy metals and toxic substances, and serious impact on the surrounding environment and ecology of mines. However, the research progress and hotspots in this field of acid mine drainage processing are still unclear. To better understand the research hotspots and trends of acid mine drainage processing from 2004 to 2023, we used CiteSpace bibliometric software to visually analyze 1142 English-language research articles and reviews from the Web of Science core database. Results indicated that this field has received increas-ing attention from researchers worldwide, especially since 2017. The USA and China stand out as major contributors, yet their international collaboration doesn't match South Africa robust partnerships. Strengthening cooperation with other nations should be a priority for both the USA and China. The University of Quebec and University of South Africa were the most production institution. Vhahangwele Masindi from South Africa was the most active author. The top two core journals in this field were Science of the Total Environment and Water Re-search. Additionally, through keyword co-occurrence, clustering, and burst analysis, it is evi-dent that research on heavy metal mechanisms and resource recovery will be the future re-search hotspots in this field of acid mine drainage. This study provides researchers with an opportunity to understand the hotspots and trends in acid mine drainage research from a bibliometric perspective, and serves as a reference for future studies.

Research trends and frontiers on risk factors of urinary stones: a bibliometric analysis from 2010 to 2023

Background and objective The occurrence of urinary stone disease (USD) is associated with several factors. However, no conclusive results have been reached regarding the treatment of USD risk factors. This study conducted a detailed bibliometric analysis of USD risk factors to determine research hotspots and provide future development directions. Methods Articles and reviews on the USD risk factors published between 2010 and 2023 were retrieved from the Web of Science Core Collection. Co-occurrence and collaboration analyses of countries, institutions, authors, journals, references, and keywords were conducted using CiteSpace, VOSviewer, and R-Bibliometrix. Results A total of 436 articles on USD risk factors were included in the study. China and the United States have emerged as the leading countries in this field, with the Mayo Clinic having the highest amount of publication output. Among all the authors, Ferraro PM had the highest number of publications, while Taylor EN was the highly cited author. The journal with the highest number of publications was UROLITHIASIS. Scales reported the reference with the highest burst strength. The current citation themes in research on USD risk factors were ‘multifaceted relationship’ and ‘kidney stone disease recurrence’. ‘Medical-management’ was identified as a major keyword, indicating future research hotspots. Conclusion This study employed bibliometric methods to conduct a comprehensive visual analysis of USD risk factors to show publication trends and popular topics in this area over the past decade. The results provide a valuable reference for future research on the risk factors of USD.

Global research trends in the relationship between influenza and CD4+ T/CD8+ T cells: A bibliometric analysis

ABSTRACT Influenza pathogens cause many illnesses and deaths yearly, posing a serious threat to global public health. As a result, most studies are increasingly focusing on the role of specific CD4+ T/CD8+ T cells in combating influenza. This study examines the key themes and trends in this field using bibliometric analysis. Literature on influenza and CD4+ T/CD8+ T cells were searched (from 1985 to 2023) in the Web of Science Core Collection (WoSCC) database. Eligible articles were screened according to the inclusion and exclusion criteria for bibliometric analysis using VOSviewer, CiteSpace, and the R package “bibliometrix.” A total of 1,071 publications from 47 countries or regions and 1,148 institutions associated with 5,728 authors in the disciplines of immunology, virology, biochemistry, and molecular biology were included. The findings indicate a yearly increase in publications related to influenza and CD4+ T/CD8+ T cells, with the United States, Australia, and China leading in publication volume. The University of Melbourne had the highest volume of publications. Only a few researchers collaborated, and the collaborations were mostly concentrated in the same countries/regions. Professor Katherine Kedzierska, associated with The Peter Doherty Institute for Infection and Immunity, was the most productive academic in this field. According to the analysis of highly cited literature and keywords, the application of cellular immunity in formulating pioneering influenza vaccines is a key direction for future research.The role of CD4+ T/CD8+ T cells in combating the influenza virus has emerged as a significant focus within influenza research literature. This article summarizes the research institutions, authors, journals, hotspots, and application trends of CD4+ T/CD8+ T cells in influenza.

Investigating Empirical evidence on the Epidemiology, Diagnosis and Bibliometric analysis of the 100 topmost cited publications on Tuberculosis Disease

Tuberculosis (TB) disease remains a growing threat in public health globally. This study explored the epidemiology, diagnosis, management, and bibliometric analysis of the top 100 most cited articles on TB. The study adopted a narrative review and bibliometric analysis to explore publications on TB disease. Publications in the Web of Science were retrieved to provide extensive selection process. The present study of top 100 articles which are mostly cited are reported between 1969 to 2018. Reported documents were published in 37 journals, and a total of 1058 authors contributed with 10.5 authors per document, and 12 countries contributed, with most of TB research originating from the US (N=51) articles. We found 1058 occasional authors, and of these, 971 authors (0.003%) presented only three articles, followed by 11 authors (0.010%) and 18 authors (0.017%), respectively. About (n=34) research was published in General & Internal Medicine and Science & Technology. New England Journal of Medicine with 14 was top journal. The lead research institution was the University of Cape Town. The significant correlations were found between the number of citations and documents per year (r=0.9579, p<0.0001), countries (r=0.9570, p<0.0001), article per journal (r=0.8721, p<0.0001), and authors (r=0.4601, p<0.0001), and documents per Institution (r=0.6159, p<0.0001). A new insight into TB scientific production was through social network. The evidence from this study provides a template for understanding the epidemiology of TB and the trends in research. It also exposes the hotspot of research along with research gaps for future studies.

Laser Cladding In Situ Carbide-Reinforced Iron-Based Alloy Coating: A Review

Laser cladding, as an advanced surface modification technology, has the advantages of a high energy density, controlled dilution rate and good metallurgical bonding between the coating and the substrate. Its rapid heating and cooling properties help to form a dense and fine coating structure on the surface of the substrate, thus enhancing wear and corrosion resistance. In recent years, the in situ generation of carbide-reinforced iron-based composite coatings has gradually become a research hotspot because it combines the high hardness values of carbide with the high toughness values of iron-based alloys, which significantly improves the comprehensive performance of the coatings. This paper reviews the research progress of laser cladding in situ carbide-reinforced iron-based alloy coatings and explores the role of different types of in situ synthesized carbides (TiC, NbC, WC, etc.) in the coatings and their effects on their wear resistance and mechanical properties. The distribution of carbides in the coatings and their morphological characteristics are also discussed, and the effects of laser power, scanning speed and auxiliary treatments (ultrasonic vibration, induction heating, etc.) on the microstructure and properties of the coatings are analyzed. Finally, the problems and future directions of development in this field are envisioned.

Advances in biomarkers for immunotherapy in small-cell lung cancer

Small-cell lung cancer (SCLC) is a refractory cancer with rapid growth and high aggressiveness. Extensive-stage SCLC is initially sensitive to chemotherapy; however, drug resistance and recurrence occur rapidly, resulting in a poor survival outcome due to lack of subsequently efficient therapy. The emergence of immune checkpoint inhibitors (ICIs) generated a new landscape of SCLC treatment and significantly prolonged the survival of patients. However, the unselected immunotherapy restrains both beneficiary population and responsive period in SCLC compared to the other tumors. The complex tumor origin, high heterogeneity, and immunosuppressive microenvironment may disturb the value of conventional biomarkers in SCLC including programmed cell death 1 ligand 1 and tumor mutation burden. Transcriptional regulator–based subtypes of SCLC are current research hotspot, revealing that Y (I) subtype can benefit from ICIs. Additionally, molecules related to immune microenvironment, immunogenicity, epigenetics, and SCLC itself also indicated the therapeutic benefits of ICIs, becoming potential predictive biomarkers. In this review, we discussed the advances of biomarkers for prediction and prognosis of immunotherapy, promising directions in the future, and provide reference and options for precision immunotherapy and survival improvement in patients with SCLC.

Application and prospect of machine learning techniques in cost estimation of building projects

PurposeMachine learning (ML) technologies are increasingly being applied in building cost estimation as an advanced method to overcome the challenge of insufficient data and subjective effects of experts. To address the gap of lacking a review of ML applications in building cost estimation, this research aimed to conduct a systematic literature review to provide a robust reference and suggest development pathways for creating novel ML-based building cost prediction models, ultimately enhancing construction project management capabilities.Design/methodology/approachA systematic literature review according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) was adopted using quantitative bibliographic analysis and qualitative narrative synthesis based on the 70 screened publications from Web of Science (WOS) and Scopus databases. The VOSviewer software was used to prepare the thematic focus from the bibliographic data garnered.FindingsBased on the results of a bibliographic analysis, current research hotspots and future trends in the application of ML to building cost estimation have been identified. Additionally, the mechanisms behind existing ML models and other key points were analyzed using narrative synthesis. Importantly, the weaknesses of current applications were highlighted and recommendations for future development were made. These recommendations included defining the availability of building attributes, increasing the application of emerging ML algorithms and models to various aspects of building cost estimation and addressing the lack of public databases.Research limitations/implicationsThe findings are instrumental in aiding project management professionals in grasping current trends in ML for cost estimation and in promoting its adoption in real-world industries. The insights and recommendations can be utilized by researchers to refine ML-based cost estimation models, thereby enhancing construction project management. Additionally, policymakers can leverage the findings to advocate for industry standards, which will elevate technical proficiency and ensure consistency.Originality/valueCompared to previous research, the findings revealed research hotspots and future trends in the application of ML cost estimation models in only building projects. Additionally, the analysis of the establishment mechanisms of existing ML models and other key points, along with the developed recommendations, were more beneficial for developing improved ML-based cost estimation models, thereby enhancing project management capabilities.

Research trends and hotspots of intratumor microbiome: A comprehensive visualization and bibliometric study from 2012 to 2024.

Research trends and hotspots of intratumor microbiome: A comprehensive visualization and bibliometric study from 2012 to 2024.

Analysis of research trends and hotspots in emergency department overcrowding: A bibliometric study based on VOSview and Scimago Graphica

Objective Analyze the research trends and hotspots in emergency department overcrowding derived from the Web of Science Core Collection database. Methods The Web of Science Core Collection database was utilized as the search data source for the bibliometric analysis, and the associated articles published from January 1, 1990, to October 1, 2023.The search was executed using the following formula: TS = (crowded OR overcrowd OR crowding OR overcrowding) AND TS = (Emergency department). VOSviewer, Scimago Graphicaand and additional tools were utilized for bibliometric analysis, and visual knowledge graphs were created. Results A total of 1869 articles were included in this study. The country with the largest number of publications is the United States. The primary research institution is the University of Toronto. Jesse M. Pines and his group at George Washington University have the greatest influence in the field of emergency department overcrowding research. Carlos A. Camargo is the author with the highest h-index in this field. High-frequency keywords include “length-of-stay”, “impact”, “mortality”, “triage”, “association”, “outcomes”, “time”, “management”, “access block”, and “quality”. The clustering graph reveals that all keywords fall into seven categories. Conclusion We recommend intensifying research on emergency department overcrowding in more developing countries. In the future, the application of emerging technologies in emergency medicine as well as the mental health of emergency patients and medical staff may become research hotspots in this field.

Bibliometric and visual analysis of human microbiome—breast cancer interactions: current insights and future directions

The composition of the gut microbiome differs from that of healthy individuals and is closely linked to the progression and development of breast cancer. Recent studies have increasingly examined the relationship between microbial communities and breast cancer. This study analyzed the research landscape of microbiome and breast cancer, focusing on 736 qualified publications from the Web of Science Core Collection (WoSCC). Publications in this field are on the rise, with the United States leading in contributions, followed by China and Italy. Despite this strong output, the centrality value of China in this field is comparatively low at ninth, highlighting a gap between the quantity of research and its global impact. This pattern is repetitively observed in institutional contributions, with a predominance of Western institutes among the top contributors, underscoring a potential research quality gap in China. Keyword analysis reveals that research hotspots are focused on the effect of microbiome on breast cancer pathogenesis and tumor metabolism, with risk factors and metabolic pathways being the most interesting areas. Publications point to a shift toward anti-tumor therapies and personalized medicine, with clusters such as “anti-tumor” and “potential regulatory agent” gaining prominence. Additionally, intratumor bacteria studies have emerged as a new area of significant interest, reflecting a new direction in research. The University of Helsinki and Adlercreutz H are influential institutions and researchers in this field. Current trends in microbiome and breast cancer research indicate a significant shift toward therapeutic applications and personalized medicine. Strengthening international collaborations and focusing on research quality is crucial for advancing microbiome and breast cancer research.

A Review of Perovskite Catalysts for the Simultaneous Elimination of Soot and NOx Emissions from Diesel Engine

The problem of removing NOx and carbon particle emissions from diesel engines has been a challenge in the field of environmental protection, which is prompting people to actively explore ways to improve the efficiency of pollutant emission treatment. Due to the high price of precious metals, developing an alternative catalytic material with high catalytic activity and stability is a difficult task. Perovskite, with its stable and flexibly variable crystal structure, has become a research hotspot in the field of catalysis. This paper discusses the structure of perovskite catalysts and the mechanism behind the simultaneous catalytic oxidation of diesel engine soot and NOx. Meanwhile, it provides a comprehensive review of the preparation methods and A/B site modification strategies, establishing a foundation for the synthesis and A/B site modification of perovskite catalysts capable of catalyzing the oxidation of soot and NOx simultaneously. Additionally, this article offers an outlook on the challenges and future development of perovskite catalysts in this field.

Chemodiversity and Molecular Mechanism Between Per-/Polyfluoroalkyl Substance Complexation Behavior of Humic Substances in Landfill Leachate

Landfill leachate contains a range of organic and inorganic pollutants, including per-/polyfluoroalkyl substances (PFASs), which can infiltrate into surrounding soil and groundwater through leaching processes, and can pose a threat to human health via food chains and drinking water processes. Thus, the transport of PFASs in landfill leachate is a research hotspot in environmental science. This study investigates the complexation and adsorption mechanisms between humic substances and PFASs in landfill leachate at the molecular level. Experimental results demonstrate that the binding constant logKsv of humic substances with PFASs correlates positively with specific ultraviolet absorbance (SUVA254), absorbance ratio (A250/A365), humification index (HIX), and fluorescence index (FI), while it exhibits a negative correlation with the biological index (BIX). These findings indicate that high aromaticity is a prerequisite for molecular interactions between humic substances and PFASs, with polar functional groups further facilitating the interaction. Molecular-level analysis revealed that humic substances undergo complexation and adsorption with PFASs through hydrophobic interactions, van der Waals forces, hydrogen bonding, ionic bonding, and covalent bonding, by functional groups such as hydroxyl, aliphatic C-H bonds, aromatic C=C double bonds, amides, quinones, and ketones. Future efforts should focus on enhanced co-regulation and mitigation strategies addressing the combined pollution of PFASs and humic substances in landfill leachate.