Nucleic Acids Res. 2023 Oct 25:gkad902. doi: 10.1093/nar/gkad902. Online ahead of print.

ABSTRACT

The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss/) is a federation of bioinformatics research and service groups. The international life science community in academia and industry has been accessing the freely available databases provided by SIB since its inception in 1998. In this paper we present the 11 databases which currently offer semantically enriched data in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as the Swiss Personalized Health Network initiative (SPHN) which also employs this enrichment. The semantic enrichment facilitates the manipulation of large data sets from public databases and private data sets. Examples are provided to illustrate that the data from the SIB databases can not only be queried using precise criteria individually, but also across multiple databases, including a variety of non-SIB databases. Data manipulation, be it exploration, extraction, annotation, combination, and publication, is possible using the SPARQL query language. Providing documentation, tutorials and sample queries makes it easier to navigate this web of semantic data. Through this paper, the reader will discover how the existing SIB knowledge graphs can be leveraged to tackle the complex biological or clinical questions that are being addressed today.

PMID:37878411 | DOI:10.1093/nar/gkad902

PLoS One. 2023 Oct 16;18(10):e0292446. doi: 10.1371/journal.pone.0292446. eCollection 2023.

ABSTRACT

Driven by internet technology, online has become the main way of news dissemination, but redundant information such as navigation bars and advertisements affects people's access to news content. The research aims to enable users to obtain pure news content from redundant web information. Firstly, based on the narrative characteristics of literary news, the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm is employed to extract pure news content from the analyzed web pages. The algorithm uses keyword matching, text analysis, and semantic processing to determine news content's boundaries and key information. Secondly, the news text classification algorithm (support vector machine, K-nearest neighbor, AdaBoost algorithm) is selected through comparative experiments. The news extraction system based on keyword feature and extended Document Object Model (DOM) tree is constructed. DOM technology analyzes web page structure and extracts key elements and information. Finally, the research can get their narrative characteristics by studying the narrative sequence and structure of 15 American literary news reports. The results reveal that the most used narrative sequence in American literary news is sequence and flashback. The narrative duration is dominated by the victory rate and outline, supplemented by scenes and pauses. In addition, 53.3% of the narrative structures used in literary news are time-connected. This narrative structure can help reporters have a clear conceptual structure when writing, help readers quickly grasp and understand the context of the event and the life course of the protagonists in the report, and increase the report's readability. This research on the narrative characteristics of American literature news can provide media practitioners with a reference on news narrative techniques and strategies.

PMID:37844094 | DOI:10.1371/journal.pone.0292446

Discourse Soc. 2023 Jan;34(1):96-119. doi: 10.1177/09579265221145098.

ABSTRACT

This paper discusses web-based public health discursive practices during the Coronavirus (COVID-19) pandemic in Nigeria. It utilises a multimodal discourse approach to explore how a combination of textual and visual resources was deployed to communicate informative and educative public health safety campaigns during the period. Essentially, this study discusses multimodal resources as a rhetorical technique for creating a public discursive engagement space designed to educate the public and mitigate the effect of the pandemic. The dataset was collected during and after the lockdown in 2020 (March-September) through media monitoring and manual downloading of relevant online COVID-19 posts, messages and public health advisories largely from WhatsApp platforms and the portals of some Nigerian national newspapers. Using insights from relevant approaches in discourse analysis (e.g. Multimodal Discourse and Critical Discourse Analysis), we adopted a qualitative content analysis approach to analyse on how online posts as multimodal resources amplify the role of social media affordances in producing and promoting public safety messages helped to control the spread and mitigate the effects of the pandemic. The study also shows that discursive and multimodal resources were deliberately deployed to increase the effectiveness of the technology-driven public health campaign. To a large extent, multimodal resources were found to complement lexico-semantic properties of online communication, where social media messages are created, crafted and reconstructed within a uniquely Nigerian public discourse context. The study further illustrates the increasing importance of web-based platforms as discursive sites for enacting and negotiating meanings during event-driven social activities and public engagement in the Global South.

PMID:37829509 | PMC:PMC9827133 | DOI:10.1177/09579265221145098

Front Psychol. 2023 Aug 30;14:1227123. doi: 10.3389/fpsyg.2023.1227123. eCollection 2023.

ABSTRACT

PURPOSE/SIGNIFICANCE: Humans understand, think, and express themselves through metaphors. The current paper emphasizes the importance of identifying the metaphorical language used in online health communities (OHC) to understand how users frame and make sense of their experiences, which can boost the effectiveness of counseling and interventions for this population.

METHODS/PROCESS: We used a web crawler to obtain a corpus of an online depression community. We introduced a three-stage procedure for metaphor identification in a Chinese Corpus: (1) combine MIPVU to identify metaphorical expressions (ME) bottom-up and formulate preliminary working hypotheses; (2) collect more ME top-down in the corpus by performing semantic domain analysis on identified ME; and (3) analyze ME and categorize conceptual metaphors using a reference list. In this way, we have gained a greater understanding of how depression sufferers conceptualize their experience metaphorically in an under-represented language in the literature (Chinese) of a new genre (online health community).

RESULTS/CONCLUSION: Main conceptual metaphors for depression are classified into PERSONAL LIFE, INTERPERSONAL RELATIONSHIP, TIME, and CYBERCULTURE metaphors. Identifying depression metaphors in the Chinese corpus pinpoints the sociocultural environment people with depression are experiencing: lack of offline support, social stigmatization, and substitutability of offline support with online support. We confirm a number of depression metaphors found in other languages, providing a theoretical basis for researching, identifying, and treating depression in multilingual settings. Our study also identifies new metaphors with source-target connections based on embodied, sociocultural, and idiosyncratic levels. From these three levels, we analyze metaphor research's theoretical and practical implications, finding ways to emphasize its inherent cross-disciplinarity meaningfully.

PMID:37829080 | PMC:PMC10566633 | DOI:10.3389/fpsyg.2023.1227123

Eur Arch Otorhinolaryngol. 2023 Oct 10. doi: 10.1007/s00405-023-08260-x. Online ahead of print.

ABSTRACT

PURPOSE: Executive functions (EF) play a fundamental role in planning and executing goal-driven behaviours. The purpose of this systematic review and meta-analysis was to investigate EF skills mastered by preschool/school-age cochlear implanted children (CIC) without morpho-functional abnormalities and to compare their outcomes with typically hearing children (THC).

METHODS: Bibliographic search for observational studies of any language/date up to 16 December 2022 was performed with the following electronic databases: PubMed, Scopus, and Web of Science. After removal of duplicates, 2442 records were subjected to a three-stage screening process and 83 potentially eligible articles were identified. A total of 15 studies was included in the final analysis: 9 articles directly meeting the eligibility criteria plus 6 more studies thanks to the authors sharing their data set, specifically for participants who met present inclusion criteria.

RESULTS: Meta-analysis showed a statistically significant difference only for verbal short-term memory, whereas group differences for visuospatial short-term memory and verbal/visuospatial working memory were not significant. For fluency skills, meta-analysis revealed statistical significance for the semantic fluency task but not for the rapid naming test. Qualitative analysis reflected group similarities in flexibility but CIC's difficulties in auditory attention/planning skills. Controversial findings for inhibitory control skills were observed.

CONCLUSIONS: EF performance comparisons between CIC and THC show inter-skill and inter-test variances. Due to the paucity of existing studies, present findings should be interpreted with caution. Future research in this domain is strongly recommended.

PMID:37816839 | DOI:10.1007/s00405-023-08260-x

BMC Public Health. 2023 Oct 9;23(1):1957. doi: 10.1186/s12889-023-16809-y.

ABSTRACT

BACKGROUND: Australian age-standardized incidence and death rates for liver cancer are lower than world averages, but increasing as in other economically advanced western countries. World Health Organization emphasizes the need to address sociodemographic disparities in cancer risk. A more detailed sociodemographic risk profiling was undertaken for liver cancer in New South Wales (NSW) by diagnostic stage, than possible with NSW Cancer Registry (NSWCR) alone, by incorporating linked data from the Australian Bureau of Statistics (ABS). The purpose was to inform targeting and monitoring of cancer services.

METHODS: The ABS manages the Multi-Agency Data Integration Project (MADIP) which includes a wide range of health, educational, welfare, census, and employment data. These data were linked at person level to NSWCR liver cancer registrations for the period post 2016 census to December 2018. De-identified data were analyzed. Sex-specific age-adjusted odds ratios (95%CIs) of liver cancer were derived using logistic regression by age, country of birth, residential remoteness, proficiency in spoken English, household income, employment status, occupation type, educational attainment, sole person household, joblessness, socioeconomic status, disability status, multimorbidity, and other health-related factors, including GP consultations. These data complement the less detailed sociodemographic data available from the NSWCR, with alignment of numerators and population denominators for accurate risk assessment.

RESULTS: Results indicate liver cancer disproportionately affects population members already experiencing excess social and health disadvantage. Examples where 95% confidence intervals of odds ratios of liver cancer were elevated included having poor English-speaking proficiency, limited education, housing authority tenancy, living in sole-person households, having disabilities, multiple medicated conditions, and being carers of people with a disability. Also, odds of liver cancer were higher in more remote regions outside major cities, and in males, with higher odds of more advanced cancer stages (degrees of spread) at diagnosis in more remote regions.

CONCLUSIONS: Linked data enabled more detailed risk profiling than previously possible. This will support the targeting of cancer services and benchmarking.

PMID:37814225 | PMC:PMC10563226 | DOI:10.1186/s12889-023-16809-y

Arch Clin Neuropsychol. 2023 Oct 8:acad067.340. doi: 10.1093/arclin/acad067.340. Online ahead of print.

ABSTRACT

OBJECTIVE: The systematic review aimed to understand and provide insight into the misdiagnosis of conduct disorder (CD) among Hispanic and Latino populations.

METHOD: A systematic review of current literature on Hispanic or Latino children diagnosed with CD was conducted from 2019 to 2023. Peer-reviewed empirical studies in English and Spanish were obtained through Google Scholar, PubMed, PsyArticles, Semantic Scholar, and PsychInfo, using keywords conduct disorder, Latinos, Hispanics, and ethnic minorities. The initial search yielded 50 articles, of which 8 were retained.

RESULTS: The literature presented a combination of 3488 participants aged between 5 and 18 years of age originating from various Hispanic and Latin American countries who participated in multimodal intervention approaches following psychodiagnostics testing, followed by a CD diagnosis. Such interventions included cognitive testing, computer or web-based testing, parental reports, and clinical interviews. While the sex of participants was not recorded throughout all studies, one study reported a higher prevalence of boys diagnosed with CD compared to girls, with 136 boys and 76 girls. Overall, mixed rates of prevalence and misdiagnoses of CD were found for Hispanic children in the literature.

CONCLUSIONS: While the literature has demonstrated that many Hispanic and Latino children have been diagnosed with CD, it fails to address the implementation of cultural implications prior to making the diagnosis. Limitations of the present review include that children diagnosed with CD were tested in English rather than their native tongue, leaving room for inadequate test interpretation and diagnosis.

PMID:37807579 | DOI:10.1093/arclin/acad067.340

ANZ J Surg. 2023 Dec;93(12):2928-2938. doi: 10.1111/ans.18713. Epub 2023 Oct 5.

ABSTRACT

BACKGROUND: This study aims to investigate the trends in UC surgery in New South Wales (NSW) at a population level.

METHODS: A retrospective data linkage study of the NSW population was performed. Patients of any age with a diagnosis of UC who underwent a total abdominal colectomy (TAC) ± proctectomy between Jul-2001 and Jun-2019 were included. The age adjusted population rate was calculated using Australian Bureau of Statistics data. Multivariable linear regression modelled the trend of TAC rates, and assessed the effect of infliximab (listed on the Pharmaceutical Benefits Scheme for UC in Apr-2014).

RESULTS: A total of 1365 patients underwent a TAC ± proctectomy (mean age 47.0 years (±18.6), 59% Male). Controlling for differences between age groups, the annual rate of UC TACs decreased by 2.4% each year (95% CI 1.4%-3.4%) over the 18-year period from 1.30/100000 (2002) to 0.84/100000 (2019). An additional incremental decrease in the rate of TACs was observed after 2014 (OR 0.83, 95% CI 0.69-1.00). There was no change in the proportion of TACs performed emergently over the study period (OR 1.02, 95% CI 0.998-1.04). The odds of experiencing any perioperative surgical complication (aOR 1.54, 95% CI 1.01-2.33, P = 0.043), and requiring ICU admission (aOR 1.85, 95% CI 1.24-2.76, P = 0.003) significantly increased in 2014-2019 compared to 2002-2007.

CONCLUSIONS: The rate of TACs for UC has declined over the past two decades. This rate decrease may have been further influenced by the introduction of biologics. Higher rates of complications and ICU admissions in the biologic era may indicate poorer patient physiological status at the time of surgery.

PMID:37795917 | DOI:10.1111/ans.18713

JNCI Cancer Spectr. 2023 Oct 31;7(6):pkad080. doi: 10.1093/jncics/pkad080.

ABSTRACT

Commission on Cancer (CoC) accreditation certifies facilities provide quality care. We assessed differences among patients who do and do not visit CoC facilities using Pennsylvania Cancer Registry data linked to facility records for patients diagnosed with cancer between 2018 and 2019 (n = 87 472). Predicted probabilities from multivariable logistic regression indicated patients in the most advantaged Area Deprivation Index quartiles were more likely to visit CoC facilities (78.0%, 95% confidence interval [CI] = 77.5% to 78.6%) compared with other quartiles. Urban patients (74.1%, 95% CI = 73.8% to 74.4%) were more likely than rural to be seen at a CoC facility (62.7%, 95% CI = 61.2% to 64.2%) as were Hispanic patients (88.0%, 95% CI = 86.7% to 89.3%) and non-Hispanic Black patients (79.1%, 95% CI = 78.1% to 80.0%) compared with White patients (72.0%, 95% CI = 71.7% to 72.4%). Differences in demographics suggest CoC data may underrepresent some groups, including low-income and rural patients.

PMID:37788093 | PMC:PMC10627003 | DOI:10.1093/jncics/pkad080

Int J Radiat Oncol Biol Phys. 2023 Oct 1;117(2S):e296. doi: 10.1016/j.ijrobp.2023.06.2305.

ABSTRACT

PURPOSE/OBJECTIVE(S): We hypothesized that racial and ethnic disparities exist in health-related quality of life (HRQOL) among older adults with colorectal cancer, both before and after diagnosis.

MATERIALS/METHODS: The Surveillance, Epidemiology, and End Results and Medicare Health Outcomes Survey (SEER-MHOS) linked data set was used to identify patients 65 years old and above who were diagnosed with colorectal cancer between 1996 and 2015. Self-reported race/ethnicity, the predictor of interest, was categorized as White (W), Asian/Pacific Islander (API), Black/African American (B), or Hispanic (H). HRQOL data from the 36-Item Short Form Survey and Veterans RAND 12-Item Health Survey were extracted within 24 months pre- and post-diagnosis. HRQOL was measured using the Physical Component Summary (PCS), Mental Component Summary (MCS), and Total Component Summary (TCS, a summation of PCS and MCS), which were the response variables. Associations were assessed via univariable (UVA) and multivariable (MVA) linear regression analysis, adjusting for age, sex, region, marital status, education, income, number of comorbidities, limitations in activities of daily living, stage, and histology. Pairwise comparisons were performed between all racial and ethnic groups.

RESULTS: We identified a total of 1,204 evaluable patients, with 815 in the pre-diagnosis cohort and 562 in the post-diagnosis cohort, including 173 patients in both. With unadjusted p-values, pre-diagnosis UVA revealed a higher mean PCS in API patients compared to W, B, and H patients (p<0.001, p<0.001, p = 0.02) as well as in W compared to H patients (p = 0.002); a higher mean MCS in W and API patients compared to B (p<0.001, p = 0.002) and H patients (p<0.001, p = 0.002); and a higher mean TCS in API compared to W, B, and H patients (p = 0.027, p<0.001, p<0.001) as well as in W compared to B and H patients (p<0.001, p = 0.012). Pre-diagnosis MVA revealed a higher mean PCS in API compared to B patients (p = 0.028) and a higher mean MCS in W and B compared to H patients (p = 0.022, p = 0.021). Post-diagnosis UVA showed a higher mean MCS in W compared to B and H patients (p<0.001 for both) as well as in API compared to H patients (p = 0.002), and a higher mean TCS in W and API patients compared to B (p<0.001, p = 0.045) and H patients (p<0.001, p = 0.007). Post-diagnosis MVA showed a higher mean MCS in API compared to H patients (p = 0.035). Compared to pre-diagnosis, post-diagnosis mean TCS was numerically lower for all groups.

CONCLUSION: Among older adults with colorectal cancer, there appear to be racial and ethnic disparities in HRQOL. Before the cancer diagnosis, API patients had better physical HRQOL than B patients, while W and B patients had better mental HRQOL than H patients. After diagnosis, API patients had better mental HRQOL than H patients. For all groups, the cancer diagnosis seemed to have a negative impact on overall HRQOL.

PMID:37785087 | DOI:10.1016/j.ijrobp.2023.06.2305

Cancer Res Commun. 2023 Oct 19;3(10):2126-2132. doi: 10.1158/2767-9764.CRC-23-0263.

ABSTRACT

Cancer is the second leading cause of death in the United States, and breast cancer is the fourth leading cause of cancer-related death, with 42,275 women dying of breast cancer in the United States in 2020. Screening is a key strategy for reducing mortality from breast cancer and is recommended by various national guidelines. This study applies machine learning classification methods to the task of predicting which patients will fail to complete a mammogram screening after having one ordered, as well as understanding the underlying features that influence predictions. The results show that a small group of patients can be identified that are very unlikely to complete mammogram screening, enabling care managers to focus resources.

SIGNIFICANCE: The motivation behind this study is to create an automated system that can identify a small group of individuals that are at elevated risk for not following through completing a mammogram screening. This will enable interventions to boost screening to be focused on patients least likely to complete screening.

PMID:37782226 | PMC:PMC10586236 | DOI:10.1158/2767-9764.CRC-23-0263

BMC Health Serv Res. 2023 Sep 30;23(1):1047. doi: 10.1186/s12913-023-10047-z.

ABSTRACT

BACKGROUND: e-Health has played a crucial role during the COVID-19 pandemic in primary health care. e-Health is the cost-effective and secure use of Information and Communication Technologies (ICTs) to support health and health-related fields. Various stakeholders worldwide use ICTs, including individuals, non-profit organizations, health practitioners, and governments. As a result of the COVID-19 pandemic, ICT has improved the quality of healthcare, the exchange of information, training of healthcare professionals and patients, and facilitated the relationship between patients and healthcare providers. This study systematically reviews the literature on ICT-based automatic and remote monitoring methods, as well as different ICT techniques used in the care of COVID-19-infected patients.

OBJECTIVE: The purpose of this systematic literature review is to identify the e-Health methods, associated ICTs, method implementation strategies, information collection techniques, advantages, and disadvantages of remote and automatic patient monitoring and care in COVID-19 pandemic.

METHODS: The search included primary studies that were published between January 2020 and June 2022 in scientific and electronic databases, such as EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MEDLINE, Google Scholar, JMIR, Web of Science, Science Direct, and PubMed. In this review, the findings from the included publications are presented and elaborated according to the identified research questions. Evidence-based systematic reviews and meta-analyses were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Additionally, we improved the review process using the Rayyan tool and the Scale for the Assessment of Narrative Review Articles (SANRA). Among the eligibility criteria were methodological rigor, conceptual clarity, and useful implementation of ICTs in e-Health for remote and automatic monitoring of COVID-19 patients.

RESULTS: Our initial search identified 664 potential studies; 102 were assessed for eligibility in the pre-final stage and 65 articles were used in the final review with the inclusion and exclusion criteria. The review identified the following eHealth methods-Telemedicine, Mobile Health (mHealth), and Telehealth. The associated ICTs are Wearable Body Sensors, Artificial Intelligence (AI) algorithms, Internet-of-Things, or Internet-of-Medical-Things (IoT or IoMT), Biometric Monitoring Technologies (BioMeTs), and Bluetooth-enabled (BLE) home health monitoring devices. Spatial or positional data, personal and individual health, and wellness data, including vital signs, symptoms, biomedical images and signals, and lifestyle data are examples of information that is managed by ICTs. Different AI and IoT methods have opened new possibilities for automatic and remote patient monitoring with associated advantages and weaknesses. Our findings were represented in a structured manner using a semantic knowledge graph (e.g., ontology model).

CONCLUSIONS: Various e-Health methods, related remote monitoring technologies, different approaches, information categories, the adoption of ICT tools for an automatic remote patient monitoring (RPM), advantages and limitations of RMTs in the COVID-19 case are discussed in this review. The use of e-Health during the COVID-19 pandemic illustrates the constraints and possibilities of using ICTs. ICTs are not merely an external tool to achieve definite remote and automatic health monitoring goals; instead, they are embedded in contexts. Therefore, the importance of the mutual design process between ICT and society during the global health crisis has been observed from a social informatics perspective. A global health crisis can be observed as an information crisis (e.g., insufficient information, unreliable information, and inaccessible information); however, this review shows the influence of ICTs on COVID-19 patients' health monitoring and related information collection techniques.

PMID:37777722 | DOI:10.1186/s12913-023-10047-z

Sci Data. 2023 Sep 30;10(1):667. doi: 10.1038/s41597-023-02578-1.

ABSTRACT

Urban network analytics has become an essential tool for understanding and modeling the intricate complexity of cities. We introduce the Urbanity data repository to nurture this growing research field, offering a comprehensive, open spatial network resource spanning 50 major cities in 29 countries worldwide. Our workflow enhances OpenStreetMap networks with 40 + high-resolution indicators from open global sources such as street view imagery, building morphology, urban population, and points of interest, catering to a diverse range of applications across multiple fields. We extract streetscape semantic features from more than four million street view images using computer vision. The dataset's strength lies in its thorough processing and validation at every stage, ensuring data quality and consistency through automated and manual checks. Accompanying the dataset is an interactive, web-based dashboard we developed which facilitates data access to even non-technical stakeholders. Urbanity aids various GeoAI and city comparative analyses, underscoring the growing importance of urban network analytics research.

PMID:37777566 | DOI:10.1038/s41597-023-02578-1

IEEE J Biomed Health Inform. 2023 Sep 29;PP. doi: 10.1109/JBHI.2023.3320939. Online ahead of print.

ABSTRACT

In healthcare facilities, answering the questions from the patients and their companions about the health problems is regarded as an essential task. With the current shortage of medical personnel resources and an increase in the patient-to-clinician ratio, staff in the medical field have consequently devoted less time to answering questions for each patient. However, studies have shown that correct healthcare information can positively improve patients' knowledge, attitudes, and behaviors. Therefore, delivering correct healthcare knowledge through a question-answering system is crucial. In this paper, we develop an interactive healthcare question-answering system that uses attention-based models to answer healthcare-related questions. Attention-based transformer models are utilized to efficiently encode semantic meanings and extract the medical entities inside the user query individually. These two features are integrated through our designed fusion module to match against the pre-collected healthcare knowledge set, so that our system will finally give the most accurate response to the user in real-time. To improve the interactivity, we further introduce a recommendation module and an online web search module to provide potential questions and out-of-scope answers. Experimental results for question-answer retrieval show that the proposed method has the ability to retrieve the correct answer from the FAQ pairs in the healthcare domain. Thus, we believe that this application can bring more benefits to human beings.

PMID:37773912 | DOI:10.1109/JBHI.2023.3320939

J Biomed Semantics. 2023 Sep 28;14(1):15. doi: 10.1186/s13326-023-00295-7.

ABSTRACT

BACKGROUND: Ontologies play a key role in the management of medical knowledge because they have the properties to support a wide range of knowledge-intensive tasks. The dynamic nature of knowledge requires frequent changes to the ontologies to keep them up-to-date. The challenge is to understand and manage these changes and their impact on depending systems well in order to handle the growing volume of data annotated with ontologies and the limited documentation describing the changes.

METHODS: We present a method to detect and characterize the changes occurring between different versions of an ontology together with an ontology of changes entitled DynDiffOnto, designed according to Semantic Web best practices and FAIR principles. We further describe the implementation of the method and the evaluation of the tool with different ontologies from the biomedical domain (i.e. ICD9-CM, MeSH, NCIt, SNOMEDCT, GO, IOBC and CIDO), showing its performance in terms of time execution and capacity to classify ontological changes, compared with other state-of-the-art approaches.

RESULTS: The experiments show a top-level performance of DynDiff for large ontologies and a good performance for smaller ones, with respect to execution time and capability to identify complex changes. In this paper, we further highlight the impact of ontology matchers on the diff computation and the possibility to parameterize the matcher in DynDiff, enabling the possibility of benefits from state-of-the-art matchers.

CONCLUSION: DynDiff is an efficient tool to compute differences between ontology versions and classify these differences according to DynDiffOnto concepts. This work also contributes to a better understanding of ontological changes through DynDiffOnto, which was designed to express the semantics of the changes between versions of an ontology and can be used to document the evolution of an ontology.

PMID:37770956 | DOI:10.1186/s13326-023-00295-7

Sensors (Basel). 2023 Sep 21;23(18):8014. doi: 10.3390/s23188014.

ABSTRACT

The web application market has shown rapid growth in recent years. The expansion of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) has created new web-based communication and sensing frameworks. Current security research utilizes source code analysis and manual exploitation of web applications, to identify security vulnerabilities, such as Cross-Site Scripting (XSS) and SQL Injection, in these emerging fields. The attack samples generated as part of web application penetration testing on sensor networks can be easily blocked, using Web Application Firewalls (WAFs). In this research work, we propose an autonomous penetration testing framework that utilizes Generative Adversarial Networks (GANs). We overcome the limitations of vanilla GANs by using conditional sequence generation. This technique helps in identifying key features for XSS attacks. We trained a generative model based on attack labels and attack features. The attack features were identified using semantic tokenization, and the attack payloads were generated using conditional sequence GAN. The generated attack samples can be used to target web applications protected by WAFs in an automated manner. This model scales well on a large-scale web application platform, and it saves the significant effort invested in manual penetration testing.

PMID:37766067 | DOI:10.3390/s23188014

J Korean Med Sci. 2023 Sep 25;38(38):e294. doi: 10.3346/jkms.2023.38.e294.

ABSTRACT

BACKGROUND: Optimal antiplatelet strategy for patients with ischemic stroke who were already on single antiplatelet therapy (SAPT) remains to be elucidated. This study aimed to evaluate the effect of different antiplatelet regimens on vascular and safety outcomes at 1 year after non-cardioembolic stroke in patients previously on SAPT.

METHODS: We identified 9,284 patients with acute non-cardioembolic ischemic stroke that occurred on SAPT using linked data. Patients were categorized into three groups according to antiplatelet strategy at discharge: 1) SAPT; 2) dual antiplatelet therapy (DAPT); and 3) triple antiplatelet therapy (TAPT). One-year outcomes included recurrent ischemic stroke, composite outcomes (recurrent ischemic stroke, myocardial infarction, intracerebral hemorrhage, and death), and major bleeding.

RESULTS: Of 9,284 patients, 5,565 (59.9%) maintained SAPT, 3,638 (39.2%) were treated with DAPT, and 81 (0.9%) were treated with TAPT. Multiple antiplatelet therapy did not reduce the risks of 1-year recurrent stroke (DAPT, hazard ratio [HR], 1.08, 95% confidence interval [CI], 0.92-1.27, P = 0.339; TAPT, HR, 0.71, 95% CI, 0.27-1.91, P = 0.500) and 1-year composite outcome (DAPT, HR, 1.09, 95% CI, 0.68-1.97, P = 0.592; TAPT, HR, 1.46, 95% CI, 0.68-1.97, P = 0.592). However, the TAPT groups showed an increased risk of major bleeding complications (DAPT, HR, 1.23, 95% CI, 0.89-1.71, P = 0.208; TAPT, HR, 4.65, 95% CI, 2.01-10.74, P < 0.001).

CONCLUSION: Additional use of antiplatelet agents in patients with non-cardioembolic ischemic stroke who were already on SAPT did not reduce the 1-year incidence of vascular outcomes, although it increased the risk of bleeding complications.

PMID:37750368 | PMC:PMC10519784 | DOI:10.3346/jkms.2023.38.e294

Behav Res Methods. 2023 Sep 25. doi: 10.3758/s13428-023-02212-3. Online ahead of print.

ABSTRACT

Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access to such large datasets. Moreover, theoretical developments lead to new dimensions being proposed, the norms for which are only partially available. In this paper, we propose a transformer-based neural network architecture for semantic and emotional norms extrapolation that predicts a whole ensemble of norms at once while achieving state-of-the-art correlations with human judgements on each. We improve on the previous approaches with regards to the correlations with human judgments by Δr = 0.1 on average. We precisely discuss the limitations of norm extrapolation as a whole, with a special focus on the introduced model. Further, we propose a unique practical application of our model by proposing a method of stimuli selection which performs unsupervised control by picking words that match in their semantic content. As the proposed model can easily be applied to different languages, we provide norm extrapolations for English, Polish, Dutch, German, French, and Spanish. To aid researchers, we also provide access to the extrapolation networks through an accessible web application.

PMID:37749424 | DOI:10.3758/s13428-023-02212-3

PLoS Comput Biol. 2023 Sep 21;19(9):e1011285. doi: 10.1371/journal.pcbi.1011285. eCollection 2023 Sep.

ABSTRACT

This article presents 14 quick tips to build a team to crowdsource data for public health advocacy. It includes tips around team building and logistics, infrastructure setup, media and industry outreach, and project wrap-up and archival for posterity.

PMID:37733682 | PMC:PMC10513213 | DOI:10.1371/journal.pcbi.1011285

Oral Maxillofac Surg. 2023 Sep 21. doi: 10.1007/s10006-023-01180-4. Online ahead of print.

ABSTRACT

INTRODUCTION: The use of alloplastic total temporomandibular joint reconstruction (TMJR) in growing patients is controversial, mainly due to immature elements of the craniomaxillofacial skeleton. The aim of this systematic review was to evaluate the use of alloplastic TMJR in growing patients, focusing on the patient's clinical presentation, surgical and medical history and efficacy of alloplastic TMJR implantation.

MATERIALS AND METHODS: The literature search strategy was based on the Population, Intervention, Comparator, Outcomes and Study type (PICOS) framework. We searched Pubmed, Google Scholar, Dimension, Web of Science, X-mol, Semantic Scholar and Embase to January 2023, without any restriction on the type of publication reporting alloplastic TMJR in growing patients (age ≤ 18 years for boys and age ≤ 15 years for girls).

RESULTS: A total of 15 studies (case reports: 09, case series: 02, cohort studies: 04) met the inclusion criteria, documenting 73 patients of growing age from 07 countries. Thirty-eight (~ 52%) cases were female. The mean ± SD (range) age and follow-up of patients in all studies was 13.1 ± 3.2 (0-17) years and 34.3 ± 21.5 (7-96) months, respectively. A total of 22 (30%) patients were implanted with bilateral alloplastic TMJR. Over half of the studies (n = 10) were published in the last 3 years. All patients underwent multiple surgeries prior to implantation of alloplastic TMJR. In extreme cases, patients underwent a total of 17 surgeries. Different types of studies reporting inconsistent variables restricted our ability to perform quality assessment measures for evidence building.

CONCLUSIONS: Clinical experience with alloplastic TMJR in growing patients is limited to cases showing poor prognosis with other types of reconstruction. Nevertheless, studies show promising results for the use of alloplastic TMJR in growing patients, highlighting the need for well-controlled prospective studies with long-term follow-up.

PMID:37733214 | DOI:10.1007/s10006-023-01180-4