Dataset Information

Full-scale network analysis reveals properties of the FV protein structure organization.

ABSTRACT: Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, the Coagulation factor V (FV) is a master regulator, coordinating critical steps of this process. Mutations to this factor result in spontaneous bleeding episodes and prolonged hemorrhage after trauma or surgery. Although the role of FV is well characterized, it is unclear how single-point mutations affect its structure. In this study, to understand the effect of mutations, we created a detailed network map of this protein, where each node is a residue, and two residues are connected if they are in close proximity in the three-dimensional structure. Overall, we analyzed 63 point-mutations from patients and identified common patterns underlying FV deficient phenotypes. We used structural and evolutionary patterns as input to machine learning algorithms to anticipate the effects of mutations and anticipated FV-deficiency with fair accuracy. Together, our results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance treatment and diagnosis of coagulation disorders.

SUBMITTER: Ferreira-Martins AJ

PROVIDER: S-EPMC10260930 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Full-scale network analysis reveals properties of the FV protein structure organization.

Ferreira-Martins André J AJ Castaldoni Rodrigo R Alencar Brenno M BM Ferreira Marcos V MV Nogueira Tatiane T Rios Ricardo A RA Lopes Tiago J S TJS

Scientific reports 20230612 1

Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, the Coagulation factor V (FV) is a master regulator, coordinating critical steps of this process. Mutations to this factor result in spontaneous bleeding episodes and prolonged hemorrhage afte ...[more]

PMID: 37308572

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Project description:BackgroundSelf-absorption refers an excessive, persistent, and rigid preoccupation with information regarding the self. This study aims to introduce the Self-Absorption Scale (SAS) into China with an assessment of its latent variable structure, network structure, psychometric properties, and clinical utility in a nonclinical Chinese sample.Methods209 participants completed the translated SAS as well as the Short General Health Questionnaire (GHQ-12), rumination subscale of the Rumination-Reflection Questionnaire (RRQ), the Mindful Attention Awareness Scale (MAAS), the Private Self-Consciousness Scale (PrSCS), the Obsessive-Compulsive Inventory-Revised (OCI-R) and the Dissociative Experiences Scale (DES-II). In addition, 30 respondents completed the Chinese version of the SAS and retested it 2 weeks later.ResultsThe Chinese version of the SAS (CH-SAS) had a desirable two-correlated-factor structure with the reverse scored item removed, which was invariant across different genders. The core items in the network structure of the CH-SAS were related to excessive self-immersion, uncontrollability and anxiety aspects of self-absorption. The Cronbach's alpha coefficient for the CH-SAS was 0.903 while the McDonald's omega coefficient was 0.916 and the test-retest reliability was 0.908. The CH-SAS and its two subscales had moderate positive correlations with the rumination subscale of the RRQ (ranging from 0.474 to 0.616; p < .001) and the GHQ-12 (ranging from 0.479 to 0.538; p < .001), and moderate negative correlations with the MAAS (ranging from - 0.413 to - 0.360; p < .001). The PrSCS has almost no correlation with the CH-SAS and PrSAS (p > .05), and its correlation with the PubSAS was significant at the 0.05 level, with a remarkably low correlation coefficient (r = .157). The hierarchical regression analysis suggested that the CH-SAS can significantly predict the severity of OCD beyond factors such as depression, anxiety, rumination, dissociation, and mindful attention awareness.ConclusionsThe CH-SAS demonstrates excellent reliability, including internal consistency and test-retest reliability. Additionally, it exhibits favorable structural validity, as well as strong evidence of convergent and divergent validity. Furthermore, the self-absorption measured using the CH-SAS contributed significantly to the prediction of OCD beyond other relevant psychological factors, suggesting its clinical utility.

Dataset Information

Full-scale network analysis reveals properties of the FV protein structure organization.

Publications

Full-scale network analysis reveals properties of the FV protein structure organization.

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