Ultrasound wavelet spectra enable direct tissue recognition and full-color visualization.

Traditional brightness-mode ultrasound imaging is primarily constrained by the low specificity among tissues and the inconsistency among sonographers. The major cause is the imaging method that represents the amplitude of echoes as brightness and ignores other detailed information, leaving sonographers to interpret based on organ contours that depend highly on specific imaging planes. Other ultrasound imaging modalities, color Doppler imaging or shear wave elastography, overlay motion or stiffness information to brightness-mode images. However, tissue-specific scattering properties and spectral patterns remain unknown in ultrasound imaging. Here we demonstrate that the distribution (size and average distance) of scattering particles leads to characteristic wavelet spectral patterns, which enables tissue recognition and high-contrast ultrasound imaging. Ultrasonic wavelet spectra from similar particle distributions tend to cluster in the eigenspace according to principal component analysis, whereas those with different distributions tend to be distinguishable from one another. For each distribution, a few wavelet spectra are unique and act as a fingerprint to recognize the corresponding tissue. Illumination of specific tissues and organs with designated colors according to the recognition results yields high-contrast ultrasound imaging. The fully-colorized tissue-specific ultrasound imaging potentially simplifies the interpretation and promotes consistency among sonographers, or even enables the applicability for non-professionals.

A comprehensive review of the "black gold catalysts" in wastewater treatment: Properties, applications and bibliometric analysis.

A significant amount of effort has been devoted to the utilization of biochar-based catalysts in the treatment of wastewater. By virtue of its abundant functional groups and high specific surface area, biochar holds significant promise as a catalyst. This article presents a comprehensive systematic review and bibliometric analysis covering the period from 2009 to 2024, focusing on the restoration of wastewater through biochar catalysis. The production, activation, and functionalization techniques employed for biochar are thoroughly examined. In addition, the application of advanced technologies such as advanced oxidation processes (AOPs), catalytic reduction reactions, and biochemically driven processes based on biochar are discussed, with a focus on elucidating the underlying mechanisms and how surface functionalities influence the catalytic performance of biochar. Furthermore, the potential drawbacks of utilizing biochar are also brought to light. To emphasize the progress being made in this research field and provide valuable insights for future researchers, a scientometric analysis was conducted using CiteSpace and VOSviewer software on 595 articles. Hopefully, this review will enhance understanding of the catalytic performance and mechanisms pertaining to biochar-based catalysts in pollutant treatment while providing a perspective and guidelines for future research and development efforts in this area.

IMU Data-Driven and PCA-Based Approach to Establish Quantifiable and Practically Applicable Measures for V2 Technique Elements in Cross-Country Skiing.

Quantifying movement coordination in cross-country (XC) skiing, specifically the technique with its elemental forms, is challenging. Particularly, this applies when trying to establish a bidirectional transfer between scientific theory and practical experts' knowledge as expressed, for example, in ski instruction curricula. The objective of this study was to translate 14 curricula-informed distinct elements of the V2 ski-skating technique (horizontal and vertical posture, lateral tilt, head position, upper body rotation, arm swing, shoulder abduction, elbow flexion, hand and leg distance, plantar flexion, ski set-down, leg push-off, and gliding phase) into plausible, valid and applicable measures to make the technique training process more quantifiable and scientifically grounded. Inertial measurement unit (IMU) data of 10 highly experienced XC skiers who demonstrated the technique elements by two extreme forms each (e.g., anterior versus posterior positioning for the horizontal posture) were recorded. Element-specific principal component analyses (PCAs)-driven by the variance produced by the technique extremes-resulted in movement components that express quantifiable measures of the underlying technique elements. Ten measures were found to be sensitive in distinguishing between the inputted extreme variations using statistical parametric mapping (SPM), whereas for four elements the SPM did not detect differences (lateral tilt, plantar flexion, ski set-down, and leg push-off). Applicability of the established technique measures was determined based on quantifying individual techniques through them. The study introduces a novel approach to quantitatively assess V2 ski-skating technique, which might help to enhance technique feedback and bridge the communication gap that often exists between practitioners and scientists.

From Imaging to Visualization: Seeing the Future of Endometriosis Care.

OBJECTIVE: To describe how the knowledge from standard imaging practices can be translated into three-dimensional visualization techniques and utilized in the surgical planning and management of endometriosis. SETTING: Tertiary care academic centre. PARTICIPANTS: Two case studies of patients with endometriosis are described. INTERVENTIONS: Transvaginal ultrasound (1), magnetic resonance imaging, three-dimensional printing (2), and three-dimensional virtual reality modeling (3) were utilized during patient workup and preparation. Three-dimensional modeling was performed by a virtual reality technician and verified for accuracy by a fellowship trained radiologist. Surgical management for endometriosis was performed. CONCLUSION: While expert transvaginal ultrasound and/or magnetic resonance imaging suffice for the majority of cases, three-dimensional printing and virtual reality modeling are a novel adjunct to standard imaging modalities. Rendering two-dimensional images into a three-dimensional representation allows users to interact with the anatomy and is particularly useful when distorted by complex pathology. These techniques contributed to improved patient understanding and experience, and helped medical learners better grasp regular imaging techniques and its translation to pelvic anatomy. Last, it augmented surgeon comprehension of the relationship between the pelvic structures, allowing for enhanced surgical planning and intraoperative decision making. Further study is being performed to quantify these effects.

An examination of global research trends for exploring the associations between the gut microbiota and nonalcoholic fatty liver disease through bibliometric and visualization analysis.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is increasingly recognized as a significant health issue. Emerging research has focused on the role of the gut microbiota in NAFLD, emphasizing the gut-liver axis. This study aimed to identify key research trends and guide future investigations in this evolving area. METHODS: This bibliometric study utilized Scopus to analyze global research on the link between the gut microbiota and NAFLD. The method involved a search strategy focusing on relevant keywords in article titles, refined by including only peer-reviewed journal articles. The data analysis included bibliometric indicators such as publication counts and trends, which were visualized using VOSviewer software version 1.6.20 for network and co-occurrence analysis, highlighting key research clusters and emerging topics. RESULTS: Among the 479 publications on the gut microbiota and NAFLD, the majority were original articles (n = 338; 70.56%), followed by reviews (n = 119; 24.84%). The annual publication count increased from 1 in 2010 to 118 in 2022, with a significant growth phase starting in 2017 (R2 = 0.9025, p < 0.001). The research was globally distributed and dominated by China (n = 231; 48.23%) and the United States (n = 90; 18.79%). The University of California, San Diego, led institutional contributions (n = 18; 3.76%). Funding was prominent, with 62.8% of the articles supported, especially by the National Natural Science Foundation of China (n = 118; 24.63%). The average citation count was 43.23, with an h-index of 70 and a citation range of 0 to 1058 per article. Research hotspots shifted their focus post-2020 toward the impact of high-fat diets on NAFLD incidence. CONCLUSIONS: This study has effectively mapped the growing body of research on the gut microbiota-NAFLD relationship, revealing a significant increase in publications since 2017. There is significant interest in gut microbiota and NAFLD research, mainly led by China and the United States, with diverse areas of focus. Recently, the field has moved toward exploring the interconnections among diet, lifestyle, and the gut-liver axis. We hypothesize that with advanced technologies, new opportunities for personalized medicine and a holistic understanding of NAFLD will emerge.

pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection.

Background: Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies are underway globally. Accurate identification and prioritization of neoantigens is highly relevant to designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. Results: We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates across three different levels, including variant, transcript and peptide information. Conclusions: pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org.

Proceedings of the EuBIC-MS developers meeting 2023.

The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.

Research hotspots and trends of spinal cord stimulation for neuropathic pain: a bibliometric analysis from 2004 to 2023.

The purpose of this study is to systematically analyze the development trend, research hotspots, and future development direction on the treatment of neuropathic pain (NP) with spinal cord stimulation through bibliometric method. We extracted the literature related to the treatment of NP with spinal cord stimulation from January 2004 to December 2023 from the Web of Science database. As a result, a total of 264 articles were retrieved. By analyzing the annual published articles, authors, countries, institutions, journals, co-cited literature, and keywords, we found that the count of publication in this field has been experiencing an overall growth, and the publications within the past 5 years accounted for 42% of the total output. Experts from the United States and the UK have made significant contributions in this field and established a stable collaborative team, initially establishing an international cooperation network. Pain is the frequently cited journal in this field. The study on spinal cord stimulation therapy for NP especially the study on spinal cord stimulation therapy for back surgery failure syndrome (FBSS) and its potential mechanisms are the research hotspots in this field, while the study on novel paradigms such as high-frequency spinal cord stimulation and spinal cord burst stimulation represents the future development directions. In short, spinal cord stimulation has been an effective treatment method for NP. The novel paradigms of spinal cord stimulation are the key point of future research in this field.

The Global Research Trends on Intrinsic Capacity of Older Adults: A Bibliometric and Visual Analysis of Papers Published During 2015-2023.

Objective: The concept of intrinsic capacity (IC) revolves around healthy aging and active aging. Since the Introduction of the concept by the World Health Organization in 2015, a series of studies have been conducted by scholars from multiple fields. However, no bibliometric analysis has systematically investigated this issue. We aim to identify the current landscape and frontier trends of scientific achievements on IC in older adults through bibliometric approaches. Methods: Quantitative analysis of publications relating to IC in older adults from 2015 to 2023 was interpreted and graphed through the Web of Science Core Collection database on December 5, 2023. A variety of quantitative variables was analyzed, including publication and citation counts, H-index, and journal citation reports. Co-authorship, citation, co-citation, and co-occurrence analyses were performed for countries/regions, institutions, authors, and keywords using the VOSviewer and CiteSpace. Results: A total of 952 original and review articles in English were identified. The European countries possessed an absolute advantage in this field. The most contributive institution was the University of São Paulo. The most productive author is Cesari Matteo from France, followed by Qaisar Rizwan from the United Arab Emirates. However, a relatively low level of research cooperation existed between institutions and authors. Important topics mainly include the connotations, theoretical framework models, evaluation, screening tools, and application scenarios of IC. Among the promising hotspots, "biological aging", "ICOPE", "Covid-19", "prevention", "inflammation", "caf22", "prevalence", and "randomized controlled trial" displayed relatively latest average appearing year. Conclusion: Global trends indicate a growing scientific output on IC in older adults, and developed countries are leading the way. There is still room for improvement in research team collaboration. The focus gradually shifts from theoretical research to empirical research. It is recommended to pay attention to the latest hot spots, such as "biological aging", "ICOPE implementation", "post-COVID-19 syndrome", and "biomarkers".

DNA structural features and variability of complete MHC locus sequences.

The major histocompatibility (MHC) locus, also known as the Human Leukocyte Antigen (HLA) genes, is located on the short arm of chromosome 6, and contains three regions (Class I, Class II and Class III). This 5 Mbp locus is one of the most variable regions of the human genome, yet it also encodes a set of highly conserved and important proteins related to immunological response. Genetic variations in this region are responsible for more diseases than in the entire rest of the human genome. However, information on local structural features of the DNA is largely ignored. With recent advances in long-read sequencing technology, it is now becoming possible to sequence the entire 5 Mbp MHC locus, producing complete diploid haplotypes of the whole region. Here, we describe structural maps based on the complete sequences from six different homozygous HLA cell lines. We find long-range structural variability in the different sequences for DNA stacking energy, position preference and curvature, variation in repeats, as well as more local changes in regions forming open chromatin structures, likely to influence gene expression levels. These structural maps can be useful in visualizing large scale structural variation across HLA types, in particular when this can be complemented with epigenetic signals.

Research on ultrasound-based radiomics: a bibliometric analysis.

Background: A large number of studies related to ultrasound-based radiomics have been published in recent years; however, a systematic bibliometric analysis of this topic has not yet been conducted. In this study, we attempted to identify the hotspots and frontiers in ultrasound-based radiomics through bibliometrics and to systematically characterize the overall framework and characteristics of studies through mapping and visualization. Methods: A literature search was carried out in Web of Science Core Collection (WoSCC) database from January 2016 to December 2023 according to a predetermined search formula. Bibliometric analysis and visualization of the results were performed using CiteSpace, VOSviewer, R, and other platforms. Results: Ultimately, 466 eligible papers were included in the study. Publication trend analysis showed that the annual publication trend of journals in ultrasound-based radiomics could be divided into three phases: there were no more than five documents published in this field in any year before 2018, a small yearly increase in the number of annual publications occurred between 2018 and 2022, and a high, stable number of publications appeared after 2022. In the analysis of publication sources, China was found to be the main contributor, with a much higher number of publications than other countries, and was followed by the United States and Italy. Frontiers in Oncology was the journal with the highest number of papers in this field, publishing 60 articles. Among the academic institutions, Fudan University, Sun Yat-sen University, and the Chinese Academy of Sciences ranked as the top three in terms of the number of documents. In the analysis of authors and cocited authors, the author with the most publications was Yuanyuan Wang, who has published 19 articles in 8 years, while Philippe Lambin was the most cited author, with 233 citations. Visualization of the results from the cocitation analysis of the literature revealed a strong centrality of the subject terms papillary thyroid cancer, biological behavior, potential biomarkers, and comparative assessment, which may be the main focal points of research in this subject. Based on the findings of the keyword analysis and cluster analysis, the keywords can be categorized into two major groups: (I) technological innovations that enable the construction of radiomics models such as machine learning and deep learning and (II) applications of predictive models to support clinical decision-making in certain diseases, such as papillary thyroid cancer, hepatocellular carcinoma (HCC), and breast cancer. Conclusions: Ultrasound-based radiomics has received widespread attention in the medical field and has been gradually been applied in clinical research. Radiomics, a relatively late development in medical technology, has made substantial contributions to the diagnosis, prediction, and prognostic evaluation of diseases. Additionally, the coupling of artificial intelligence techniques with ultrasound imaging has yielded a number of promising tools that facilitate clinical decision-making and enable the practice of precision medicine. Finally, the development of ultrasound-based radiomics requires multidisciplinary cooperation and joint efforts from the field biomedicine, information technology, statistics, and clinical medicine.

Current research status and future prospects of NLRP3 inflammasome in cardiovascular diseases: a bibliometric and visualization analysis.

Background: Cardiovascular disease (CVD) is a leading cause of global mortality, with atherosclerosis (AS) contributing to its pathological basis. Inflammation plays a critical role in the pathophysiological process of AS, and the NOD-like receptor protein 3 (NLRP3) inflammasome has been extensively studied in this context. This study aimed to analyze the research status of the NLRP3 inflammasome in cardiovascular disease and provide research directions for further exploration in this field. Methods: Using the "Bibliometrix" and "CiteSpace" software, a total of 516 articles were retrieved from the Web of Science (WoS) database published between 2012 and 2023. The search query used the keywords "["CVD" OR "cardiovascular disease"] AND ["NLRP3 inflammasome "OR "NLRP3"]". Visual analysis was performed on authors, countries, institutions, journal sources, keywords, references, and future trends. Results: A total of 516 English articles were retrieved, showing an overall upward trend in annual publication volume with slight fluctuations. China, the United States, and Europe were the countries and regions with the highest number of published articles. Among them, China had the highest article count (170), while the United States had the highest citation count (18,664), centrality score (0.43), and h-index (90), indicating its influential role in this research area. These countries also possessed elite institutions, professional researchers, and high-impact journals, making them leading contributors in this field. The main pathogenic mechanisms of the NLRP3 inflammasome in CVD were identified as "oxidative stress", "pyroptosis", and "inflammation". The most frequently studied signaling pathways included "NF-κB", "IL-1", and "C-reactive protein". The most studied disease types were coronary heart disease, atherosclerosis, metabolic syndrome, and myocardial infarction. Additionally, research on the correlation between cholesterol markers and inflammatory indicators associated with NLRP3 inflammasome in CVD risk assessment has gained significant momentum, with the main mechanism being NLRP3/IL-6/hs-CRP and cholesterol lipoproteins emerging as a major keyword in this context. Conclusion: This study provides valuable insights into the research hotspots and emerging trends of the NLRP3 inflammasome in cardiovascular disease. The findings offer guidance for researchers and scholars in this field and facilitate the exploration of new research directions.

Describing and Sharing Molecular Visualizations Using the MolViewSpec Toolkit.

With the ever-expanding toolkit of molecular viewers, the ability to visualize macromolecular structures has never been more accessible. Yet, the idiosyncratic technical intricacies across tools and the integration complexities associated with handling structure annotation data present significant barriers to seamless interoperability and steep learning curves for many users. The necessity for reproducible data visualizations is at the forefront of the current challenges. Recently, we introduced MolViewSpec (homepage: https://molstar.org/mol-view-spec/, GitHub project: https://github.com/molstar/mol-view-spec), a specification approach that defines molecular visualizations, decoupling them from the varying implementation details of different molecular viewers. Through the protocols presented herein, we demonstrate how to use MolViewSpec and its 3D view-building Python library for creating sophisticated, customized 3D views covering all standard molecular visualizations. MolViewSpec supports representations like cartoon and ball-and-stick with coloring, labeling, and applying complex transformations such as superposition to any macromolecular structure file in mmCIF, BinaryCIF, and PDB formats. These examples showcase progress towards reusability and interoperability of molecular 3D visualization in an era when handling molecular structures at scale is a timely and pressing matter in structural bioinformatics as well as research and education across the life sciences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating a MolViewSpec view using the MolViewSpec Python package Basic Protocol 2: Creating a MolViewSpec view with reference to MolViewSpec annotation files Basic Protocol 3: Creating a MolViewSpec view with labels and other advanced features Support Protocol 1: Computing rotation and translation vectors Support Protocol 2: Creating a MolViewSpec annotation file.

spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis.

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

Investigation on the cavitation characteristic of a novel cylindrical rotational hydrodynamic cavitation reactor.

Hydrodynamic cavitation reactors are of great promise for the applications of chemical process intensification and water treatment. In this work, a novel cylindrical rotational hydrodynamic cavitation reactor (CRHCR) with rectangular grooves and oblique tooth protrusions on the rotor surface was studied. The three-dimensional characterization of cavitation within the CRHCR was observed from the front and left views by the high-speed camera experiments. Interestingly, a new phenomenon of simultaneous formation of the attached cavitation and shear cavitation was found in the CRHCR. The synergistic effect of attached cavitation and shear cavitation contributes to the enhancement of the cavitation performance of CRHCR. In addition, the evolution of attached cavitation is explored. It is found that attached cavitation forms a trapezoidal-shaped cavitation cloud in the groove, which undergoes three various stages: incipient, development, and collapse. Finally, the pulsation frequency and cavitation intensity of shear cavitation in the chamber were investigated. The results show that the cavitation pulsation frequency is the same at the same rotational speed in the chamber near diverse oblique teeth. As the rotational speed increases, the cavitation pulsation frequency increases linearly. These findings in this paper are of great benefit to understanding the mechanism of the cavitation effect of CRHCR.

A colorimetric/electrochemical microfluidic biosensor using target-triggered DNA hydrogels for organophosphorus detection.

Organophosphorus compounds are widely distributed and highly toxic to the environment and living organisms. The current detection of organophosphorus compounds is based on a single-mode method, which makes it challenging to achieve good portability, accuracy, and sensitivity simultaneously. This study designed a multifunctional microfluidic chip to develop a dual-mode biosensor employing a DNA hydrogel as a carrier and aptamers as recognition probes for the colorimetric/electrochemical detection of malathion, an organophosphorus compound. The biosensor balanced portability and stability by combining a microfluidic chip and target-triggered DNA hydrogel-sensing technologies. Moreover, the biosensor based on target-triggered DNA hydrogel modified microfluidic developed in this study exhibited a dual-mode response to malathion, providing both colorimetric and electrochemical signals. The colorimetric mode enables rapid visualization and qualitative detection and, when combined with a smartphone, allows on-site quantitative analysis with a detection limit of 56 nM. The electrochemical mode offers a broad linear range (0.01-3000 µM) and high sensitivity (a limit of detection of 5 nM). The two modes could validate each other and improve the accuracy of detection. The colorimetric/electrochemical dual-mode biosensor based on target-triggered DNA hydrogel modified microfluidic chip offers a portable, simple, accurate, and sensitive strategy for detecting harmful environmental and food substances.

Using large language model (LLM) to identify high-burden informal caregivers in long-term care.

BACKGROUND: The rising global elderly population increases the demand for caregiving, yet traditional methods may not fully assess the challenges faced by vital informal caregivers. OBJECTIVE: To investigate the efficacy of Large Language Model (LLM) in detecting overburdened informal caregivers, benchmarking against rule-based and machine learning methods. METHODS: 1,791 eligible informal caregivers from Southern Taiwan and utilized their textual case summary reports for the LLM. We also employed structured questionnaire results for machine learning models. Furthermore, we leveraged the visualization of the LLM's attention mechanisms to enhance our understanding of the model's interpretative capabilities. RESULTS: The LLM achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.84 and an Area Under the Precision-Recall Curve (AUPRC) of 0.70, marking an 8% and 14% improvement over traditional methods. The visualization of the attention mechanism accurately reflected the evaluations of human experts, concentrating on descriptions of high-burden descriptions and the relationships between caregivers and recipients. CONCLUSION: This research demonstrates the notable capability of LLM to accurately identify high-burden caregivers in Long-term Care (LTC) settings. Compared to traditional approaches, LLM offers an opportunity for the future of LTC research and policymaking.

Electronic Health Record-Oriented Knowledge Graph System for Collaborative Clinical Decision Support Using Multicenter Fragmented Medical Data: Design and Application Study.

BACKGROUND: The medical knowledge graph provides explainable decision support, helping clinicians with prompt diagnosis and treatment suggestions. However, in real-world clinical practice, patients visit different hospitals seeking various medical services, resulting in fragmented patient data across hospitals. With data security issues, data fragmentation limits the application of knowledge graphs because single-hospital data cannot provide complete evidence for generating precise decision support and comprehensive explanations. It is important to study new methods for knowledge graph systems to integrate into multicenter, information-sensitive medical environments, using fragmented patient records for decision support while maintaining data privacy and security. OBJECTIVE: This study aims to propose an electronic health record (EHR)-oriented knowledge graph system for collaborative reasoning with multicenter fragmented patient medical data, all the while preserving data privacy. METHODS: The study introduced an EHR knowledge graph framework and a novel collaborative reasoning process for utilizing multicenter fragmented information. The system was deployed in each hospital and used a unified semantic structure and Observational Medical Outcomes Partnership (OMOP) vocabulary to standardize the local EHR data set. The system transforms local EHR data into semantic formats and performs semantic reasoning to generate intermediate reasoning findings. The generated intermediate findings used hypernym concepts to isolate original medical data. The intermediate findings and hash-encrypted patient identities were synchronized through a blockchain network. The multicenter intermediate findings were collaborated for final reasoning and clinical decision support without gathering original EHR data. RESULTS: The system underwent evaluation through an application study involving the utilization of multicenter fragmented EHR data to alert non-nephrology clinicians about overlooked patients with chronic kidney disease (CKD). The study covered 1185 patients in nonnephrology departments from 3 hospitals. The patients visited at least two of the hospitals. Of these, 124 patients were identified as meeting CKD diagnosis criteria through collaborative reasoning using multicenter EHR data, whereas the data from individual hospitals alone could not facilitate the identification of CKD in these patients. The assessment by clinicians indicated that 78/91 (86%) patients were CKD positive. CONCLUSIONS: The proposed system was able to effectively utilize multicenter fragmented EHR data for clinical application. The application study showed the clinical benefits of the system with prompt and comprehensive decision support.

Mapping research trends regarding the mechanism of dysphagia from 1993 to 2023: a bibliometrics study and visualization analysis.

As a common consequence of various neurogenic disorders, dysphagia has a significant impact on the quality of life for patients. To promote the development the field of swallowing, it will be helpful to clarify the pathological and therapeutic mechanisms of dysphagia. Through visual analysis of related papers from 1993 to 2023 in the Web of Science Core Collection (WoSCC) database, the research status and development trend of the pathogenesis of dysphagia were discussed. The co-occurrence study was finished using CiteSpace 6.2 R4 software, including keywords, countries, institutions, and authors. Finally, 1,184 studies satisfied the inclusion requirements. The findings of the visualization analysis suggested that aspiration and gastroesophageal reflux disease would be the areas of greatest interest for researchers studying the mechanism of dysphagia. As for the latest occurred research trends, fMRI, signals and machine learning emerging into the field of view of researchers. Based on an analysis of country co-occurrence, United States, Japan and China rank the top three, in terms of the number of publications on dysphagia. University System of Ohio is the organization that has published the most amount of articles regarding the mechanism of dysphagia. Other highly published schools in the top three include State University System of Florida and Northwestern University. For the prolific authors, German, Rebecca Z published the most articles at present, whose own research team working closely together. Several closely cooperating research teams have been formed at present, including the teams centered around German, Rebecca Z, Warnecke, Tobias and Hamdy Shaheen. This study intuitively analyzed the current research status of the mechanism of dysphagia, provided researchers with research hotspots in this field.