Utility of the web excision with pre-membranous incision for congenital intestinal atresia-type I and stenosis.

PURPOSE: This study analyzed the efficacy of web excision combined with a pre-membranous incision on the dilated proximal segment for congenital intestinal atresia with type I and stenosis (CIA-I/S). PATIENTS AND METHODS: Twenty-six patients underwent surgery for CIA-I/S from January 1990 to June 2022. Patients were categorized into 3 groups according to the surgical procedure: Group A, web excision with pre-membranous incision of the dilated intestine (n = 14); Group B, enteroplasty with a trans-membranous vertical incision (n = 7) and Group C, diamond-shaped anastomosis (n = 5). To minimize the impact of obstruction location on outcomes, we specifically examined 17 cases of duodenal atresia/stenosis: Group D-A, (n = 6); Group D-B, (n = 6) and Group D-C, (n = 5). We retrospectively compared the operative and postoperative parameters among the three groups. RESULTS: No patient experienced anastomotic leakage or obstruction. There were no significant differences in operative duration or blood loss among the 3 Groups. The median time to feeding initiation was 4, 6.5, and 5 days in Groups A, B, and C, respectively (p = 0.04) and was 4, 6.5, and 5 days in Groups D-A, D-B, and D-C, respectively (p = 0.04). CONCLUSION: Web excision, when compared to enteroplasty and diamond-shaped anastomosis, showed comparable results in terms of the operative duration and postoperative complications. However, it may allow for an earlier initiation of enteral nutrition.

Effect of web-based health education on nursing students' knowledge, adaptive healthy measures and attitudes regarding polycystic ovary syndrome: a randomized controlled trial.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder affecting women of reproductive age, and it has emerged as a significant global public health issue. This study aimed to investigate the effects of web-based health education on nursing students' knowledge, adaptive healthy measures, and attitudes toward PCOS. METHODS: A two-group randomized controlled trial (RCT) with pre-test and immediate post-test assessments was conducted. Study participants were recruited using a simple random sampling method from the Faculty of Nursing, Mansoura University, Egypt. A questionnaire consisting of six sections was developed to collect data, which was analyzed with the SPSS 23.0 using Student's t-test, Pearson's correlation test, and chi-square test analysis of variance. RESULTS: The analysis revealed a significant increase in knowledge scores post-intervention, with the web-based learning groups (32.2 ± 10.5) outperforming the traditional learning group (22.1 ± 10.2), with (p < 0.05). Similarly, there was a notable improvement in adaptive healthy measures scores post-intervention, with the web-based learning group (8.9 ± 2.4) showing better results than the traditional group (6.5 ± 2.9), with (p < 0.05). In terms of attitudes toward PCOS, the web-based group (18.2 ± 4.9) displayed a significant improvement compared to the traditional group (11.7 ± 5.2), with (p < 0.05). CONCLUSIONS: The findings suggest that web-based learning is more effective than traditional methods in enhancing nursing students' knowledge, adaptive healthy measures, and attitudes toward PCOS. TRIAL REGISTRATION: This study was registered by Clinical Trials.gov Identifier: (NCT06192381|| https://www. CLINICALTRIALS: gov/ ) on 5-1-2024.

Bibliometric and visual analysis of immunisation associated with acute kidney injury from 2003 to 2023.

Objective: This study aims to conduct a detailed bibliometric and visual analysis of acute kidney injury (AKI) and immune-related research conducted over the past two decades, focusing on identifying emerging trends and key areas of interest. Methods: The Web of Science Core Collection (WoSCC) was utilised for the meticulous examination of various parameters including publication volume, authorship, geographic distribution, institutional contributions, journal sources, prevalent keywords and citation frequencies. Data were intricately visualised and interpreted using VOSviewer, CiteSpace and Excel 365 software. Results: Analysis of the WoSCC database revealed 3,537 articles on AKI and immunisation, originating from 94 countries and regions, involving 3,552 institutions and authored by 18,243 individuals. Notably, the top five countries contributing to this field were the United States, China, Germany, Italy and the United Kingdom, with the United States leading with 35.76% of total publications. Among the 3,552 contributing institutions, those in the United States were predominant, with Harvard University leading with 134 papers and 3,906 citations. Key journals driving productivity included Frontiers in Immunology, Kidney International, Journal of the American Society of Nephrology and International Journal of Molecular Sciences, with Kidney International being the most cited, followed by Journal of the American Society of Nephrology and New England Journal of Medicine. Prominent authors in the field included Ronco Claudio, Okusa Mark D and Anders, Hans-Joachim. Co-citation clustering and timeline analysis highlighted recent research foci such as COVID-19, immune checkpoint inhibitors, regulated necrosis, cirrhosis and AKI. Keyword analysis identified "inflammation," "ischaemia-reperfusion injury," "sepsis," "covid-19," and "oxidative stress" as prevalent terms. Conclusion: This study provides the first bibliometric analysis of AKI and immune research, offering a comprehensive overview of research hotspots and evolving trends within the field.

Illegal Online Gambling Site Detection using Multiple Resource-Oriented Machine Learning.

The COVID-19 pandemic has led to faster digitalization and illegal online gambling has become popular. As illegal online gambling brings not only financial threats but also breaches in overall cyber security, this study defines the concept of absolute illegal online gambling (AIOG) using a machine-learning-driven approach with information gathered from public webpages. By analysing 11,172 sites to detect illegal online gambling, the proposed model classifies key features such as URLs (Uniform Resource Locator), WHOIS, INDEX, and landing page information. With a combination of text and image analyses with machine learning-driven approach, the proposed model offers the ensemble combination of attributes for high detection performance with the verification of common attributes from metadata in online gambling. This study suggests a strategy for dynamic resource utilization to increase the classification accuracy of the current environment. As a result, this research expands the scope of hybrid web mining through constant updating of data to achieve content-based filtering.

Noncarious cervical lesions: A bibliometric analysis and future research trends.

OBJECTIVE: The present bibliometric review analyzed the literature on non-carious cervical lesions (NCCLs) to explore the current state and propose future research topics. DATA: An electronic search was performed, only full scientific papers published in English were included. SOURCES: A search was conducted of all databases in the Web of Science (WOS) platform for available publications on the topic of NCCLs. STUDY SELECTION: 959 publications were retrieved, and the following data were extracted and analyzed: number of publications, study topics, keywords, study type, authors, affiliations, countries, funding agencies, journals and citations. Articles on NCCLs have been increasing in count, ever since they were first mentioned in the literature. Therapy alternatives account for 628 with few on prevention, and the majority were clinical. Brazil has published the most on NCCLs as well as has the highest number of authors and the most funded articles. The three journals that published the most on the topic were Operative Dentistry, Journal of Dentistry and Clinical Oral Investigations. CONCLUSION: The findings of this study provide a full picture of the current literature on NCCLs, research trends, knowledge gaps, and areas requiring further investigation. CLINICAL SIGNIFICANCE: By highlighting evolving treatment strategies and potential gaps in prevention, researchers can contribute to the advancement of clinical practice. This can improve patient care and outcomes in the management of NCCLs, while also providing valuable insights for policymakers to prioritize research funding and policy initiatives.

EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure. The chemical shift of the resonance frequency reflects the effect of the protons in a molecule producing distinct NMR signals in different chemical environments. Apprehending chemical shifts from NMR signals can be challenging since having an NMR structure does not necessarily provide all the required chemical shift information, making predictive models essential for accurately deducing chemical shifts, either from protein structures or, more ideally, directly from amino acid sequences. Here, we present EFG-CS, a web server that specializes in chemical shift prediction. EFG-CS employs a machine learning-based transfer prediction model for backbone atom chemical shift prediction, using ESMFold-predicted protein structures. Additionally, ESG-CS incorporates a graph neural network-based model to provide comprehensive side-chain atom chemical shift predictions. Our method demonstrated reliable performance in backbone atom prediction, achieving comparable accuracy levels with root mean square errors (RMSE) of 0.30 ppm for H, 0.22 ppm for Hα, 0.89 ppm for C, 0.89 ppm for Cα, 0.84 ppm for Cß, and 1.69 ppm for N. Moreover, our approach also showed predictive capabilities in side-chain atom chemical shift prediction achieving RMSE values of 0.71 ppm for Hß, 0.74-1.15 ppm for Hδ, and 0.58-0.94 ppm for Hγ, solely utilizing amino acid sequences without homology or feature curation. This work shows for the first time that generative AI protein models can predict NMR shifts nearly comparable to experimental models. This web server is freely available at https://biosig.lab.uq.edu.au/efg_cs, and the chemical shift prediction results can be downloaded in tabular format and visualized in 3D format.

CARTAR: a comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data.

Chimeric antigen receptor (CAR) therapy has emerged as a ground-breaking advancement in cancer treatment, harnessing the power of engineered human immune cells to target and eliminate cancer cells. The escalating interest and investment in CAR therapy in recent years emphasize its profound significance in clinical research, positioning it as a rapidly expanding frontier in the field of personalized cancer therapies. A crucial step in CAR therapy design is choosing the right target as it determines the therapy's effectiveness, safety and specificity against cancer cells, while sparing healthy tissues. Herein, we propose a suite of tools for the identification and analysis of potential CAR targets leveraging expression data from The Cancer Genome Atlas and Genotype-Tissue Expression Project, which are implemented in CARTAR website. These tools focus on pinpointing tumor-associated antigens, ensuring target selectivity and assessing specificity to avoid off-tumor toxicities and can be used to rationally designing dual CARs. In addition, candidate target expression can be explored in cancer cell lines using the expression data for the Cancer Cell Line Encyclopedia. To our best knowledge, CARTAR is the first website dedicated to the systematic search of suitable candidate targets for CAR therapy. CARTAR is publicly accessible at https://gmxenomica.github.io/CARTAR/.

Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices.

BACKGROUND: This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements. METHODS: A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience. RESULTS: The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality. CONCLUSION: The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting.

Evolution of ambiguity tolerance research a scientometric and bibliometric analysis.

Introduction: The present study conducts a retrospective bibliometric analysis to examine the quantifiable and qualitative evolution of the concept of tolerance to ambiguity (TA) over time. Additionally, a scientometric analysis using quantitative methods on scientific measurements and trends aims to profile and identify the concept, as well as its development in research themes. The relevance of this study is underscored by the growing interest and development of research on TA, particularly in fields like entrepreneurship where psychological factors are significant. Methods: The research includes highly relevant literature, such as Budner and Frenkel-Brunswick, which define TA as a predisposition to perceive ambiguous situations as desirable and as a personality variable centered on the emotional and perceptual domain, respectively. Data was obtained from the eight indices comprising the main Web of Science collection, covering research from 1975 to December 2022. A total of 378 articles were identified. Results: The analysis reveals that scientific production peaked in 2022 with 45 articles. In terms of citations, 7,773 were found, with the highest concentration in 2022, totaling 1,203 citations. This indicates a significant increase in research interest and output related to TA. Discussion: The study highlights the growing exploration of the concept of TA, emphasizing its importance across multiple disciplines in dealing with uncertainty. The research demonstrates that TA significantly influences decision-making and adaptability, highlighting its value in business and educational settings. By analyzing leading publications, authors, and research centers, the study shows the diversity of approaches to understanding TA, indicating a promising direction for future research.

Patient and Provider Satisfaction With a Geomapping Tool for Finding Community Family Physicians in Ontario, Canada: Cross-Sectional Online Survey Study.

BACKGROUND: Language-concordant health care, or health care in a patient's language of choice, is an important element of health accessibility that improves patient safety and comfort and facilitates an increased quality of care. However, prior research has found that linguistic minorities often face higher travel burdens to access language-concordant care compared to the general population. OBJECTIVE: This study intended to assess patient experiences and satisfaction with an online interactive physician map that allows patients to find family physicians who speak their preferred language in and around Ottawa, Ontario, Canada, as a means of identifying areas of improvement. METHODS: This study used an online survey with questions related to user satisfaction. Responses to Likert-scale questions were compiled as summary statistics and short-answer responses underwent thematic analysis. The study setting was Ottawa and Renfrew County, Ontario, and the surrounding region, including the province of Quebec. RESULTS: A total of 93 respondents completed the survey and self-identified as living in Ontario or Quebec. Overall, 57 (61%) respondents were "very satisfied" or "somewhat satisfied" with the map, 16 (17%) were "neither satisfied nor dissatisfied," and 20 (22%) were "very dissatisfied" or "somewhat dissatisfied." We found no significant differences in satisfaction by preferred language, age group, physician attachment, or intended beneficiary. A total of 56 respondents provided short-answer responses to an open-ended question about map improvements. The most common specific suggestion was to show which physicians are accepting new patients (n=20). Other suggestions included data refreshes (n=6), user interface adjustments (n=23), and additional languages (n=2). Some participants also provided positive feedback (n=5) or expressed concern with their inability to find a family physician (n=5). Several comments included multiple suggestions. CONCLUSIONS: While most patients were satisfied with the online map, a significant minority expressed dissatisfaction that the map did not show which family physicians were accepting new patients. This suggests that there may be public interest in an accessible database of which family physicians in Ontario are currently accepting new patients.

Determining an Appropriate Sample Size for Qualitative Interviews to Achieve True and Near Code Saturation: Secondary Analysis of Data.

BACKGROUND: In-depth interviews are a common method of qualitative data collection, providing rich data on individuals' perceptions and behaviors that would be challenging to collect with quantitative methods. Researchers typically need to decide on sample size a priori. Although studies have assessed when saturation has been achieved, there is no agreement on the minimum number of interviews needed to achieve saturation. To date, most research on saturation has been based on in-person data collection. During the COVID-19 pandemic, web-based data collection became increasingly common, as traditional in-person data collection was possible. Researchers continue to use web-based data collection methods post the COVID-19 emergency, making it important to assess whether findings around saturation differ for in-person versus web-based interviews. OBJECTIVE: We aimed to identify the number of web-based interviews needed to achieve true code saturation or near code saturation. METHODS: The analyses for this study were based on data from 5 Food and Drug Administration-funded studies conducted through web-based platforms with patients with underlying medical conditions or with health care providers who provide primary or specialty care to patients. We extracted code- and interview-specific data and examined the data summaries to determine when true saturation or near saturation was reached. RESULTS: The sample size used in the 5 studies ranged from 30 to 70 interviews. True saturation was reached after 91% to 100% (n=30-67) of planned interviews, whereas near saturation was reached after 33% to 60% (n=15-23) of planned interviews. Studies that relied heavily on deductive coding and studies that had a more structured interview guide reached both true saturation and near saturation sooner. We also examined the types of codes applied after near saturation had been reached. In 4 of the 5 studies, most of these codes represented previously established core concepts or themes. Codes representing newly identified concepts, other or miscellaneous responses (eg, "in general"), uncertainty or confusion (eg, "don't know"), or categorization for analysis (eg, correct as compared with incorrect) were less commonly applied after near saturation had been reached. CONCLUSIONS: This study provides support that near saturation may be a sufficient measure to target and that conducting additional interviews after that point may result in diminishing returns. Factors to consider in determining how many interviews to conduct include the structure and type of questions included in the interview guide, the coding structure, and the population under study. Studies with less structured interview guides, studies that rely heavily on inductive coding and analytic techniques, and studies that include populations that may be less knowledgeable about the topics discussed may require a larger sample size to reach an acceptable level of saturation. Our findings also build on previous studies looking at saturation for in-person data collection conducted at a small number of sites.

Knowledge Mapping of Macrophages in Osteoporosis: A Bibliometric Analysis (1999-2023).

BACKGROUND: Osteoporosis is a common metabolic disorder that significantly impacts quality of life in the elderly population. Macrophages play a crucial role in the development of osteoporosis by regulating bone metabolism through cytokine secretion. However, there is a lack of scholarly literature in the field of bibliometrics on this topic. OBJECTIVE: This study provides a detailed analysis of the research focus and knowledge structure of macrophage studies in osteoporosis using bibliometrics. METHODS: The scientific literature on macrophage research in the context of osteoporosis, retrieved from the Web of Science Core Collection (WoSCC) database spanning from January 1999 to December 2023, has been incorporated for bibliometric examination. The data is methodically analyzed and visually represented using analytical and visualization tools including VOSviewer, CiteSpace, Scimago Graphica, the Bibliometrix R package, and Pajek. RESULTS AND CONCLUSIONS: In the last quarter-century, there has been a consistent rise in the quantity of scholarly publications focusing on the relationship between macrophages and osteoporosis, resulting in a total of 1499 research documents. These studies have originated from 45 different countries, with China, South Korea, and the United States being the most prominent contributors, and the United States having the highest frequency of citations. Noteworthy research institutions involved in this field include Shanghai Jiao Tong University, Wonkwang University, Huazhong University of Science and Technology, and Seoul National University. The Journal of Bone and Mineral Research is widely regarded as the premier and most frequently referenced publication in the field. These publications involve the collaboration of 8744 authors, with Lee Myeung Su contributing the most articles, and Takayanagi being the most co-cited author. Key emerging research focal points are encapsulated in keywords such as "mTOR," "BMSCs," "bone regeneration," and "exosome." The relationships between exosome from macrophage sources and those from BMSCs, along with the regulatory role of the mTOR signaling pathway on macrophages, represent crucial directions for future development in this field. This study represents the inaugural comprehensive bibliometric analysis detailing trends and advancements in macrophage research within the osteoporosis domain. It delineates recent frontiers and hotspots, providing valuable insights for researchers in this particular area of study.

Semi-liquid metal-based highly permeable and adhesive electronic skin inspired by spider web.

Soft and stretchable electronics have garnered significant attention in various fields, such as wearable electronics, electronic skins, and soft robotics. However, current wearable electronics made from materials like conductive elastomers, hydrogels, and liquid metals face limitations, including low permeability, poor adhesion, inadequate conductivity, and limited stretchability. These issues hinder their effectiveness in long-term healthcare monitoring and exercise monitoring. To address these challenges, we introduce a novel design of web-droplet-like electronics featuring a semi-liquid metal coating for wearable applications. This innovative design offers high permeability, excellent stretchability, strong adhesion, and good conductivity for the electronic skin. The unique structure, inspired by the architecture of a spider web, significantly enhances air permeability compared to commercial breathable patches. Furthermore, the distribution of polyborosiloxane mimics the adhesive properties of spider web mucus, while the use of semi-liquid metals in this design results in remarkable conductivity (9 × 106 S/m) and tensile performance (up to 850% strain). This advanced electronic skin technology enables long-term monitoring of various physiological parameters and supports machine learning recognition functions with unparalleled advantages. This web-droplet structure design strategy holds great promise for commercial applications in medical health monitoring and disease diagnosis.

Real-Time Monitoring of Cable Sag and Overhead Power Line Parameters Based on a Distributed Sensor Network and Implementation in a Web Server and IoT.

Based on the need for real-time sag monitoring of Overhead Power Lines (OPL) for electricity transmission, this article presents the implementation of a hardware and software system for online monitoring of OPL cables. The mathematical model based on differential equations and the methods of algorithmic calculation of OPL cable sag are presented. Considering that, based on the mathematical model presented, the calculation of cable sag can be done in different ways depending on the sensors used, and the presented application uses a variety of sensors. Therefore, a direct calculation is made using one of the different methods. Subsequently, the verification relations are highlighted directly, and in return, the calculation by the alternative method, which uses another group of sensors, generates both a verification of the calculation and the functionality of the sensors, thus obtaining a defect observer of the sensors. The hardware architecture of the OPL cable online monitoring application is presented, together with the main characteristics of the sensors and communication equipment used. The configurations required to transmit data using the ModBUS and ZigBee protocols are also presented. The main software modules of the OPL cable condition monitoring application are described, which ensure the monitoring of the main parameters of the power line and the visualisation of the results both on the electricity provider's intranet using a web server and MySQL database, and on the Internet using an Internet of Things (IoT) server. This categorisation of the data visualisation mode is done in such a way as to ensure a high level of cyber security. Also, the global accuracy of the entire OPL cable sag calculus system is estimated at 0.1%. Starting from the mathematical model of the OPL cable sag calculation, it goes through the stages of creating such a monitoring system, from the numerical simulations carried out using Matlab to the real-time implementation of this monitoring application using Laboratory Virtual Instrument Engineering Workbench (LabVIEW).

The power of computational proteomics platforms to decipher protein-protein interactions.

Adopting computational tools for analyzing extensive biological datasets has profoundly transformed our understanding and interpretation of biological phenomena. Innovative platforms have emerged, providing automated analysis to unravel essential insights about proteins and the complexities of their interactions. These computational advancements align with traditional studies, which employ experimental techniques to discern and quantify physical and functional protein-protein interactions (PPIs). Among these techniques, tandem mass spectrometry is notably recognized for its precision and sensitivity in identifying PPIs. These approaches might serve as important information enabling the identification of PPIs with potential pharmacological significance. This review aims to convey our experience using computational tools for detecting PPI networks and offer an analysis of platforms that facilitate predictions derived from experimental data.

Bibliometric analysis of global research on air pollution and cardiovascular diseases: 2012-2022.

Background: The relationship between air pollution and cardiovascular diseases (CVDs) has garnered significant interest among researchers globally. This study employed bibliometric analysis to provide an overview of current research on the association between air pollution and CVDs, offering a comprehensive analysis of global research trends in this area. Methods: An exhaustive scrutiny of literature pertaining to the nexus between air pollution and CVDs from 2012 to 2022 was conducted through rigorous screening of the Web of Science Core Collection (WoSCC). Publications were exclusively considered in English. Subsequently, sophisticated analytical tools including CiteSpace 6.2.4R, Vosviewer 1.6.19, HistCite 2.1, Python 3.7.5, Microsoft Charticulator, and Bibliometrix Online Analysis Platform were deployed to delineate research trends in this domain. Results: The analysis of the dataset, comprising 1710 documents, unveiled a consistent escalation in scientific publications, peaking in 2022 with a total of 248 publications. Moreover, Environmental Science and Toxicology stood out as the predominant categories. Examination of keyword frequency highlighted the terms 'air pollution', 'cardiovascular disease', and 'particulate matter' as the most prevalent. Notably, the most prolific entities, in terms of authors, journals, organizations, and countries, were identified as Robert D. Brook, Environmental Health Perspectives, Harvard University, and the United States, respectively. Conclusion: The findings presented a notable increase in high-quality publications on this topic over the past 11 years, suggesting a positive outlook for future research. The study concluded with an examination of three key themes in research trends related to air pollution and CVDs: the initial physiological response to pollutant exposure, the pathways through which pollutants are transmitted, and the subsequent effects on target organs. Additionally, various air pollutants, such as particulate matter, nitric dioxide, and ozone, could contribute to multiple CVDs, including coronary heart disease, hypertension, and heart failure. Although some hypotheses have been put forward, the mechanisms of air pollution-related CVDs still need to be explored in the future.

IMGT/mAb-KG: the knowledge graph for therapeutic monoclonal antibodies.

Introduction: Therapeutic monoclonal antibodies (mAbs) have demonstrated promising outcomes in diverse clinical indications, including but not limited to graft rejection, cancer, and autoimmune diseases lately.Recognizing the crucial need for the scientific community to quickly and easily access dependable information on monoclonal antibodies (mAbs), IMGT®, the international ImMunoGeneTics information system®, provides a unique and invaluable resource: IMGT/mAb-DB, a comprehensive database of therapeutic mAbs, accessible via a user-friendly web interface. However, this approach restricts more sophisticated queries and segregates information from other databases. Methods: To connect IMGT/mAb-DB with the rest of the IMGT databases, we created IMGT/mAb-KG, a knowledge graph for therapeutic monoclonal antibodies connected to IMGT structures and genomics databases. IMGT/mAb-KG is developed using the most effective methodologies and standards of semantic web and acquires data from IMGT/mAb-DB. Concerning interoperability, IMGT/mAb-KG reuses terms from biomedical resources and is connected to related resources. Results and discussion: In February 2024, IMGT/mAb-KG, encompassing a total of 139,629 triplets, provides access to 1,489 mAbs, approximately 500 targets, and over 500 clinical indications. It offers detailed insights into the mechanisms of action of mAbs, their construction, and their various products and associated studies. Linked to other resources such as Thera-SAbDab (Therapeutic Structural Antibody Database), PharmGKB (a comprehensive resource curating knowledge on the impact of genetic variation on drug response), PubMed, and HGNC (HUGO Gene Nomenclature Committee), IMGT/mAb-KG is an essential resource for mAb development. A user-friendly web interface facilitates the exploration and analyse of the content of IMGT/mAb-KG.

Endoscopic radial incision and cutting method for adult congenital duodenal webs: A case report.

BACKGROUND: Congenital duodenal webs are rare in adults and can lead to various symptoms such as nausea, vomiting, and postprandial fullness. The treatment for this disease is mostly surgical. Endoscopic treatment techniques have been developed and attempted for this disease. Endoscopic radial incision and cutting (RIC) techniques are reportedly very effective in benign anastomotic stricture. This case report highlights the effectiveness and safety of endoscopic RIC as a minimally invasive treatment for adult congenital duodenal webs. CASE SUMMARY: A 23-year-old female patient with indigestion was referred to a tertiary hospital. The patient complained of postprandial fullness in the epigastric region. Previous physical examinations or blood tests indicated no abnormalities. Computed tomography revealed an eccentric broad-based delayed-enhancing mass-like lesion in the second portion of the duodenum. Endoscopy showed an enlarged gastric cavity and a significantly dilated duodenal bulb; a very small hole was observed in the distal part of the second portion, and scope passage was not possible. Gastrografin upper gastrointestinal series was performed, revealing an intraduodenal barium contrast-filled sac with a curvilinear narrow radiolucent rim, a typical "windsock" sign. Endoscopic RIC was performed on the duodenal web. The patient recovered uneventfully. Follow-up endoscopy showed a patent duodenal lumen without any residual stenosis. The patient reported complete resolution of symptoms at the 18-month follow-up. CONCLUSION: Endoscopic RIC may be an effective treatment for congenital duodenal webs in adults.

The utility of website-based quality improvement tools for health professionals: a systematic review.

BACKGROUND: As technology continues to advance, it is important to understand how website-based tools can support quality improvement. Website-based tools refer to resources such as toolkits that users can access and use autonomously through a dedicated website. This review examined how website-based tools can support healthcare professionals with quality improvement, including the optimal processes used to develop tools and the elements of an effective tool. METHODS: A systematic search of seven databases was conducted to include articles published between January 2012 and January 2024. Articles were included if they were peer reviewed, written in English, based in health settings and reported the development or evaluation of a quality improvement website-based tool for professionals. A narrative synthesis was conducted using NVivo. Risk of bias was assessed using the Mixed Methods Appraisal Tool. All papers were independently screened and coded by two authors using a six-phase conceptual framework by Braun and Clarke. RESULTS: Eighteen studies met the inclusion criteria. Themes identified were tool development processes, quality improvement mechanisms and barriers and facilitators to tool usage. Digitalising existing quality improvement processes (n = 7), identifying gaps in practice (n = 6), and contributing to professional development (n = 3) were common quality improvement aims. Tools were associated with reported enhancement of accuracy and efficiency in clinical tasks, improvement in adherence to guidelines, facilitation of reflective practice and provision of tailored feedback for continuous quality improvement. Common features were educational resources (n = 7) and assisting the user to assess current practices against standards/recommendations (n = 6), which supported professionals in achieving better clinical outcomes, increased professional satisfaction and streamlined workflow in various settings. Studies reported facilitators to tool usage including relevance to practice, accessibility and facilitating multidisciplinary action, making these tools practical and time-efficient for healthcare. However, barriers such as being time consuming, irrelevant to practice, difficult to use and lack of organisational engagement were reported. Almost all tools were co-developed with stakeholders. The co-design approaches varied, reflecting different levels of stakeholder engagement and adoption of co-design methodologies. It is noted that the quality of included studies was low. CONCLUSIONS: These findings offer valuable insights for future development of quality improvement website-based tools in healthcare. Recommendations include ensuring tools are co-developed with healthcare professionals, focusing on practical usability and addressing common barriers to enhance engagement and effectiveness in improving healthcare quality. Randomised controlled trials are warranted to provide objective evidence of tool efficacy. FUNDING: This work was supported by the Prevention Research Support Program, funded by the New South Wales Ministry of Health, Australia. REGISTRATION: This review was registered with PROSPERO, no. CRD42023451346.

Co-designing the integration of voice-based conversational AI and web augmentation to amplify web inclusivity.

The Web has become an essential resource but is not yet accessible to everyone. Assistive technologies and innovative, intelligent frameworks, for example, those using conversational AI, help overcome some exclusions. However, some users still experience barriers. This paper shows how a human-centered approach can shed light on technology limitations and gaps. It reports on a three-step process (focus group, co-design, and preliminary validation) that we adopted to investigate how people with speech impairments, e.g., dysarthria, browse the Web and how barriers can be reduced. The methodology helped us identify challenges and create new solutions, i.e., patterns for Web browsing, by combining voice-based conversational AI, customized for impaired speech, with techniques for the visual augmentation of web pages. While current trends in AI research focus on more and more powerful large models, participants remarked how current conversational systems do not meet their needs, and how it is important to consider each one's specificity for a technology to be called inclusive.