METHOD OF AUTOMATED DEVELOPMENT AND EVALUATION OF ONTOLOGIES’ QUALITIES OF KNOWLEDGE BASES

The process of automated development of base ontology is considered. It has been offered to consider the concepts and elements of ontologies for increasing the effectiveness of knowledge bases, the core of which is the ontology. Methods of specifying the weights of the relevant elements and optimization the structure of knowledge base of ontologies has been elaborated. It has been offered to evaluate the quality of the ontologies based on ISO 9126

Characteristics of COVID-19 in pediatric patients with hematological malignancies

Introduction: As more data is collected, hematologists will be able to gain more insight into the impact of coronavirus disease 2019 (COVID-19) on pediatric patients with hematological malignancies. Material and methods: We analysed 21 cases of COVID-19 in pediatric patients with onco-hematological diseases treated in the Western Ukrainian Pediatric Medical Center from March 2020 through May 2021. The majority of patients (71.4%) were diagnosed with acute lymphoblastic leukemia. All patients from the analyzed cohort had an asymptomatic, mild or moderate course of coronavirus-19 infection. The most common symptoms of COVID-19 were fever, cough, gastrointestinal symptoms, and dermatitis. Severe severe acute respiratory syndrome coronavirus 2 increased the risk of liver toxicity and venous thrombosis. Results and conclusion: Our analysis showed that pediatric patients with hematological malignancies need the same treatment approach for COVID-19 as for other infective complications

Incongruence between transcriptional and vascular pathophysiological cell states

Research in R.B.’s laboratory was supported by the European Research Council Starting Grant AngioGenesHD (638028) and Consolidator Grant AngioUnrestUHD (101001814), the CNIC Intramural Grant Program Severo Ochoa (11-2016-IGP-SEV-2015-0505), the Ministerio de Ciencia e Innovación (MCIN) (SAF2013-44329-P, RYC-2013- 13209, and SAF2017-89299-P) and ‘La Caixa’ Banking Foundation (HR19-00120). J.V.’s laboratory was supported by MCIN (PGC2018- 097019-B-I00 and PID2021-122348NB-I00) and La Caixa (HR17-00247 and HR22-00253). K.G.’s laboratory was supported by Knut and Alice Wallenberg Foundation (2020.0057) and Vetenskapsrådet (2021-04896). The CNIC is supported by Instituto de Salud Carlos III, MCIN, and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MCIN/ AEI/10.13039/501100011033). Microscopy experiments were performed at the Microscopy and Dynamic Imaging Unit, CNIC, ICTS-ReDib, co-funded by MCIN/AEI/10.13039/501100011033 and FEDER ‘Una manera de hacer Europa’ (ICTS-2018-04-CNIC-16). M.F.-C. was supported by PhD fellowships from La Caixa (CX_E-2015-01) and Boehringer Ingelheim travel grants. S.M. was supported by the Austrian Science Fund (J4358). A.R. was supported by the Youth Employment Initiative (PEJD-2019-PRE/BMD-16990). L.G.-O. was supported by the Spanish Ministry of Economy and Competitiveness (PRE2018-085283). We thank S. Bartlett (CNIC) for English editing, as well as the members of the Transgenesis, Microscopy, Genomics, Citometry and Bioinformatic units at CNIC. We also thank F. Radtke (Swiss Institute for Experimental Cancer Research), R. H. Adams (Max Planck Institute for Molecular Biomedicine), F. Alt (Boston Children’s Hospital, Harvard Medical School), T. Honjo (Kyoto University Institute for Advanced Studies), I. Flores (CNIC), J. Lewis (Cancer Research UK London Research Institute), S. Habu (Tokai University School of Medicine), T. Gridley (Maine Health Institute for Research) and C. Brakebusch (Biotech Research and Innovation Centre) for sharing the Dll4floxed, Notch1floxed, Notch2floxed, Cdh5(PAC)-creERT2, Myc floxed, Rbpj floxed, p21−/−, Jag1floxed, Dll1floxed, Jag2floxed and Rac1floxed mice.S

Аналіз статистичних методів визначення стійких словосполучень для ідентифікації ключових слів

The study has solved the task of making comparative analysis and choosing an optimal statistical method to determine stable word combinations while identifying keywords to process English-language and Ukrainian-language Web-resources. The effectiveness of the method directly proportionally depends on the quality of linguistic analysis, of Ukrainian and English texts, respectively, based on the technology of Web Mining and NLP. A decomposition of methods of linguistic analysis was performed to determine the impact on the quality of forming stable word combinations as keywords. The features of the method are the adaptation of the morphological and syntactic analyses of lexical units to the peculiarities of Ukrainian-language words/texts.To determine stable word combinations effectively, it is essential to exclude functional words (stops or references), pronouns, numerals and verbs because they are not related to the subject and content of a published work. A set of stable word combinations as keywords is determined by qualitative morphological and syntactic analyses of relevant texts. The set of the identified stable word combinations is used further to compare and determine the degree of the text relevance to a specific topic or user request. The internal “dynamics” of forming a set of stable word combinations as keywords was investigated in the study depending on the statistical method applied to the texts. The obtained results have been verified.The study has produced results of the experimental testing of the proposed content-monitoring method for determining stable word combinations to identify keywords in the processing of English-language and Ukrainian-language web-resources of the technical content based on Web Mining technology. It has been determined that the authors of published works often identify the keywords that are far from being considered. It has also been proven that the quality of the result is influenced by the quality of linguistic analysis of texts and subsequent filtering. Further experimental research requires approbation of the proposed method for determining keywords for other categories of texts – scientific, humanitarian, belletristic, journalistic, etc.Рассмотрены особенности применения технологий NLP, Information Retrieval, SEO и Web-mining для определения устойчивых словосочетаний при идентификации ключевых слов в разработке Web-ресурсов. Лингвостатистический анализ естественноязыкового текста использует преимущества контент-мониторинга на основе методов NLP для идентификации устойчивых словосочетаний. Квантитативный анализ устойчивых словосочетаний использован для определения степени принадлежности множеству ключевых слов. Предложен метод определения устойчивых словосочетаний при идентификации ключевых слов украиноязычного контентаРозглянуто особливості застосування технологій NLP, Information Retrieval, SEO та Web-mining для визначення стійких словосполучень при ідентифікації ключових слів в опрацюванні Web-ресурсів. Лінгвостатистичний аналіз природомовного тексту використовує переваги контент-моніторінгу на основі методів NLP для ідентифікації стійких словосполучень. Квантитативний аналіз стійких словосполучень використано для визначення степеня приналежності множині ключових слів. Запропоновано метод визначення стійких словосполучень при ідентифікації ключових слів україномовного контент

Аналіз статистичних методів визначення стійких словосполучень для ідентифікації ключових слів

The study has solved the task of making comparative analysis and choosing an optimal statistical method to determine stable word combinations while identifying keywords to process English-language and Ukrainian-language Web-resources. The effectiveness of the method directly proportionally depends on the quality of linguistic analysis, of Ukrainian and English texts, respectively, based on the technology of Web Mining and NLP. A decomposition of methods of linguistic analysis was performed to determine the impact on the quality of forming stable word combinations as keywords. The features of the method are the adaptation of the morphological and syntactic analyses of lexical units to the peculiarities of Ukrainian-language words/texts.To determine stable word combinations effectively, it is essential to exclude functional words (stops or references), pronouns, numerals and verbs because they are not related to the subject and content of a published work. A set of stable word combinations as keywords is determined by qualitative morphological and syntactic analyses of relevant texts. The set of the identified stable word combinations is used further to compare and determine the degree of the text relevance to a specific topic or user request. The internal “dynamics” of forming a set of stable word combinations as keywords was investigated in the study depending on the statistical method applied to the texts. The obtained results have been verified.The study has produced results of the experimental testing of the proposed content-monitoring method for determining stable word combinations to identify keywords in the processing of English-language and Ukrainian-language web-resources of the technical content based on Web Mining technology. It has been determined that the authors of published works often identify the keywords that are far from being considered. It has also been proven that the quality of the result is influenced by the quality of linguistic analysis of texts and subsequent filtering. Further experimental research requires approbation of the proposed method for determining keywords for other categories of texts – scientific, humanitarian, belletristic, journalistic, etc.Рассмотрены особенности применения технологий NLP, Information Retrieval, SEO и Web-mining для определения устойчивых словосочетаний при идентификации ключевых слов в разработке Web-ресурсов. Лингвостатистический анализ естественноязыкового текста использует преимущества контент-мониторинга на основе методов NLP для идентификации устойчивых словосочетаний. Квантитативный анализ устойчивых словосочетаний использован для определения степени принадлежности множеству ключевых слов. Предложен метод определения устойчивых словосочетаний при идентификации ключевых слов украиноязычного контентаРозглянуто особливості застосування технологій NLP, Information Retrieval, SEO та Web-mining для визначення стійких словосполучень при ідентифікації ключових слів в опрацюванні Web-ресурсів. Лінгвостатистичний аналіз природомовного тексту використовує переваги контент-моніторінгу на основі методів NLP для ідентифікації стійких словосполучень. Квантитативний аналіз стійких словосполучень використано для визначення степеня приналежності множині ключових слів. Запропоновано метод визначення стійких словосполучень при ідентифікації ключових слів україномовного контент

Analysis of Statistical Methods for Stable Combinations Determination of Keywords Identification

The study has solved the task of making comparative analysis and choosing an optimal statistical method to determine stable word combinations while identifying keywords to process English-language and Ukrainian-language Web-resources. The effectiveness of the method directly proportionally depends on the quality of linguistic analysis, of Ukrainian and English texts, respectively, based on the technology of Web Mining and NLP. A decomposition of methods of linguistic analysis was performed to determine the impact on the quality of forming stable word combinations as keywords. The features of the method are the adaptation of the morphological and syntactic analyses of lexical units to the peculiarities of Ukrainian-language words/texts.To determine stable word combinations effectively, it is essential to exclude functional words (stops or references), pronouns, numerals and verbs because they are not related to the subject and content of a published work. A set of stable word combinations as keywords is determined by qualitative morphological and syntactic analyses of relevant texts. The set of the identified stable word combinations is used further to compare and determine the degree of the text relevance to a specific topic or user request. The internal “dynamics” of forming a set of stable word combinations as keywords was investigated in the study depending on the statistical method applied to the texts. The obtained results have been verified.The study has produced results of the experimental testing of the proposed content-monitoring method for determining stable word combinations to identify keywords in the processing of English-language and Ukrainian-language web-resources of the technical content based on Web Mining technology. It has been determined that the authors of published works often identify the keywords that are far from being considered. It has also been proven that the quality of the result is influenced by the quality of linguistic analysis of texts and subsequent filtering. Further experimental research requires approbation of the proposed method for determining keywords for other categories of texts – scientific, humanitarian, belletristic, journalistic, etc

NF-kB signaling in cardiomyocytes is inhibited by sevoflurane and promoted by propofol.

Both inhalational and intravenous anesthetics affect myocardial remodeling, but the precise effect of each anesthetic on molecular signaling in myocardial remodeling is unknown. Here, we performed in silico analysis to investigate signaling alterations in cardiomyocytes induced by inhalational [sevoflurane (Sevo)] and intravenous [propofol (Prop)] anesthetics. Bioinformatics analysis revealed that nuclear factor-kappa B (NF-kB) signaling was inhibited by Sevo and promoted by Prop. Moreover, nuclear accumulation of p65 and transcription of NF-kB-regulated genes were suppressed in Sevo-administered mice, suggesting that Sevo inhibits the NF-kB signaling pathway. Our data demonstrate that NF-kB signaling is inhibited by Sevo and promoted by Prop. As NF-kB signaling plays an important role in myocardial remodeling, our results suggest that anesthetics may affect myocardial remodeling through NF-kB.This study was supported by grants from the Japan Society for the Promotion of Science (15K10073 and 16K19905). The CNIC is supported by the Ministerio de Ciencia, Innovación y Universidades and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505).S

Sustained Elevated Blood Pressure Accelerates Atherosclerosis Development in a Preclinical Model of Disease

The continuous relationship between blood pressure (BP) and cardiovascular events makes the distinction between elevated BP and hypertension based on arbitrary cut-off values for BP. Even mild BP elevations manifesting as high-normal BP have been associated with cardiovascular risk. We hypothesize that persistent elevated BP increases atherosclerotic plaque development. To evaluate this causal link, we developed a new mouse model of elevated BP based on adeno-associated virus (AAV) gene transfer. We constructed AAV vectors to support transfer of the hRenin and hAngiotensinogen genes. A single injection of AAV-Ren/Ang (1011 total viral particles) induced sustained systolic BP increase (130 ± 20 mmHg, vs. 110 ± 15 mmHg in controls; p = 0.05). In ApoE−/− mice, AAV-induced mild BP elevation caused larger atherosclerotic lesions evaluated by histology (10-fold increase vs. normotensive controls). In this preclinical model, atheroma plaques development was attenuated by BP control with a calcium channel blocker, indicating that a small increase in BP within a physiological range has a substantial impact on plaque development in a preclinical model of atherosclerosis. These data support that non-optimal BP represents a risk for atherosclerosis development. Earlier intervention in elevated BP may prevent or delay morbidity and mortality associated with atherosclerosis.Sin financiación5.924 JCR (2020) Q1, 67/295 Biochemistry & Molecular Biology1.455 SJR (2020) Q1, 62/2196 Computer Science ApplicationsNo data IDRUE

SARS-CoV-2 protein Nsp1 alters actomyosin cytoskeleton and phenocopies arrhythmogenic cardiomyopathy-related PKP2 mutant

Mutations in desmosomal Plakophilin-2 (PKP2) are the most prevalent drivers of arrhythmogenic cardiomyopathy (ACM) and a common cause of sudden cardiac death in young athletes. However, partner proteins that elucidate PKP2 cellular mechanism to understand cardiac dysfunction in ACM are mostly unknown. Here we identify the actin-based motor proteins Myh9 and Myh10 as key PKP2 interactors, and demonstrate that the expression of the ACM-related PKP2 mutant R735X alters actin fiber organization and cell mechanical stiffness. We also show that SARS-CoV-2 Nsp1 protein acts similarly to this known pathogenic R735X mutant, altering the actomyosin component distribution on cardiac cells. Our data reveal that the viral Nsp1 hijacks PKP2 into the cytoplasm and mimics the effect of delocalized R735X mutant. These results demonstrate that cytoplasmic PKP2, wildtype or mutant, induces the collapse of the actomyosin network, since shRNA-PKP2 knockdown maintains the cell structure, validating a critical role of PKP2 localization in the regulation of actomyosin architecture. The fact that Nsp1 and PKP2 mutant R735X share similar phenotypes also suggests that direct SARS-CoV-2 heart infection could induce a transient ACM-like disease in COVID-19 patients, which may contribute to right ventricle dysfunction, observed in patients with poor survival prognosis.The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación (MCIN) and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505). This study was supported by MCIU grant BFU2016-75144-R. The study was also partially supported by the “Ayudas a la Investigación Cátedra Real Madrid-Universidad Europea” (2017/RM01). C.M-L. and S.S. hold MCIU predoctoral contracts BES-2017- 079715, and BES-2017-079707 respectively. RG acknowledges funding from the European Research Council under grant ERC-AG-340177 (3DNanoMech) and from the MCIU under grant MAT2016-76507-R.N