Integrative Profiling of Amyotrophic Lateral Sclerosis Lymphoblasts Identifies Unique Metabolic and Mitochondrial Disease Fingerprints

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with a rapid progression and no effective treatment. Metabolic and mitochondrial alterations in peripheral tissues of ALS patients may present diagnostic and therapeutic interest. We aimed to identify mitochondrial fingerprints in lymphoblast from ALS patients harboring SOD1 mutations (mutSOD1) or with unidentified mutations (undSOD1), compared with age/sex matched controls. Three groups of lymphoblasts, from mutSOD1 or undSOD1 ALS patients and age/sex-matched controls, were obtained from Coriell Biobank and divided into 3 age/sex-matched cohorts. Mitochondria-associated metabolic pathways were analyzed using Seahorse MitoStress and ATP Rate assays, complemented with metabolic phenotype microarrays, metabolite levels, gene expression, and protein expression and activity. Pooled (all cohorts) and paired (intra-cohort) analyses were performed by using bioinformatic tools, and the features with higher information gain values were selected and used for principal component analysis and Naïve Bayes classification. Pooled analysis revealed that undSOD1 patients had statistically higher glycolytic ATP production rate and lower Tfam protein content compared to controls, which were also the experimental features highlighted by multidimensional analysis. Metabolic phenotypic profiles in lymphoblasts from ALS patients with mutSOD1 and undSOD1 revealed unique age-dependent different substrate oxidation profiles. For most parameters, different patterns of variation were found between cohorts, which may be due to age or sex. In the present work, we investigated several metabolic and mitochondrial hallmarks in lymphoblasts from each donor and, although a high heterogeneity of results was found, we identified specific metabolic and mitochondrial fingerprints that may have a diagnostic and therapeutic interest.

Internet News Headlines: Ontological and Orthological Aspects

The author presents the results of a multidimensional analysis of Internet news headlines based on the headings of the Yandex news aggregator. The issue of the text status of news headlines is considered. When solving this problem, special attention is paid to the formation of correlative paradigms of headings, united by a common denotative meaning. Methods of semantic interaction of heading paradigms based on different types of topic-rhematic deployment are described. It is proved that the paradigms of headings, complementing each other in informational and pragmatic aspects, form the discourse of Internet headings. It is concluded that this way of functioning of headlines enhances their semantic and visual autonomy from the news text, which allows us to consider Internet news headlines as minitext. The frequency methods of lexico-syntactic transformations of the original headings are analyzed, on the basis of which the constituents of paradigms are formed. At the same time, attention is focused on the orthological aspect of Internet headers. The author comes to the conclusion that the focus on the variability and efficiency of headings leads not only to the appearance of lexical and grammatical errors, but also to their replication and consolidation in the mind of the addressee as a result of changes in the structure of cognitive models.

Social Practices and Cultural Contexts

This chapter builds on the assertion that spirituality is best understood as one dimension of the larger phenomenon of lived religious practice, rather than as a phenomenon separate from or opposed to religion. Spirituality is situated in a multidimensional analysis that also includes embodiment, materiality, emotion, aesthetics, morality, and narrative. By analyzing spirituality as a distinct dimension of religious practice, we can see the internal dynamics among all the dimensions. Understanding spirituality and religion at this micro level is incomplete, however, without attention to the distinct legal and cultural contexts around the world. This chapter elaborates on four ideal-typical macrosocial contexts that each shape quite differently the practice of religion and its spiritual dimensions: entangled, established, institutionalized, and interstitial contexts. These contexts identify differences in modal expectations for the fields within which religious practices will be found and the modes of regulation that will constrain religious action.

Multidimensional Analysis of Major Depression: Association Between BDNF Methylation, Psychosocial and Cognitive Domains

Major Depression is a complex disorder with a growing incidence worldwide and multiple variables have been associated with its etiology. Nonetheless, its diagnosis is continually changing and the need to understand it from a multidimensional perspective is clear. The purpose of this study was to identify risk factors for depression in a case-control study with 100 depressive inpatients and 87 healthy controls. A multivariate logistic regression analysis was performed including psychosocial factors, cognitive maladaptive schema domains, and specific epigenetic marks (BDNF methylation levels at five CpG sites in promoter IV). A family history of depression, the cognitive schemas of impaired autonomy/performance, impaired limits, other-directedness, and the methylation level of a specific CpG site were identified as predictors. Interestingly, we found a mediating effect of those cognitive schemas in the relationship between childhood maltreatment and depression. Also, we found that depressive patients exhibited hypomethylation in a CpG site of BDNF promoter IV, which adds to the current discussion about the role of methylation in depression. We highlight that determining the methylation of a specific region of a single gene offers the possibility of accessing a highly informative an easily measurable variable, which represents benefits for diagnosis. Following complete replication and validation on larger samples, models like ours could be applicable as additional diagnostic tools in the clinical context.

Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage

Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent development of secondary brain injury after ICH and multiple pathological mechanisms are involved in the development of the injury. In this study, we aimed to identify novel genes and proteins and integrated their molecular alternations to reveal key network modules involved in ICH pathology. A total of 30 C57BL/6 male mice were used for this study. The collagenase model of ICH was employed, 3 days after ICH animals were tested neurological. After it, animals were euthanized and perihematomal brain tissues were collected for transcriptome and TMT labeling-based quantitative proteome analyses. Protein-protein interaction (PPI) network, Gene Set Enrichment Analysis (GSEA), and regularized Canonical Correlation Analysis (rCCA) were performed to integrated multiomics data. For validation of hub genes and proteins, qRT-PCR and Western blot were carried out. The candidate biomarkers were further measured by ELISA in the plasma of ICH patients and the controls. A total of 2218 differentially expressed genes (DEGs) and 353 differentially expressed proteins (DEPs) between the ICH model group and control group were identified. GSEA revealed that immune-related gene sets were prominently upregulated and significantly enriched in pathways of inflammasome complex, negative regulation of interleukin-12 production, and pyroptosis during the ICH process. The rCCA network presented two highly connective clusters which were involved in the sphingolipid catabolic process and inflammatory response. Among ten hub genes screened out by integrative analysis, significantly upregulated Itgb2, Serpina3n, and Ctss were validated in the ICH group by qRT-PCR and Western blot. Plasma levels of human SERPINA3 (homologue of murine Serpina3n) were elevated in ICH patients compared with the healthy controls (SERPINA3: 13.3 ng/mL vs. 11.2 ng/mL, p = 0.015 ). Within the ICH group, higher plasma SERPINA3 levels with a predictive threshold of 14.31 ng/mL ( sensitivity = 64.3 % ; specificity = 80.8 % ; AUC = 0.742 , 95% CI: 0.567-0.916) were highly associated with poor outcome (mRS scores 4-6). Taken together, the results of our study exhibited molecular changes related to ICH-induced brain injury by multidimensional analysis and effectively identified three biomarker candidates in a mouse ICH model, as well as pointed out that Serpina3n/SERPINA3 was a potential biomarker associated with poor functional outcome in ICH patients.

Hesitant Fuzzy 2-Dimension Linguistic Programming Technique for Multidimensional Analysis of Preference for Multicriteria Group Decision Making

The hesitant fuzzy 2-dimension linguistic element (HF2DLE) allows decision makers to express the importance or reliability of each term included in a hesitant fuzzy linguistic element as a linguistic term. This paper investigates a programming technique for multidimensional analysis of preference for hesitant fuzzy 2-dimension linguistic multicriteria group decision making. Considering the flexibility of HF2DLEs in expressing hesitant qualitative preference information, we first adopt HF2DLEs to depict both the evaluation values of alternatives and the truth degrees of alternative comparisons. To calculate the relative closeness degrees (RCDs) of alternatives, the Euclidean distances between HF2DLEs are defined. Based on RCDs and preference relations on alternatives, the group consistency and inconsistency indices are constructed, and a bi-objective hesitant fuzzy 2-dimension linguistic programming model is established to derive the criteria weights and positive and negative ideal solutions. Since the objective functions and partial constraint coefficients of the established model are HF2DLEs, an effective solution is developed, through which the RCDs can be calculated to obtain the individual rankings of alternatives. Furthermore, a single-objective assignment model is constructed to determine the best alternative. Finally, a case study is conducted to illustrate the feasibility of the proposed method, and its effectiveness is demonstrated by comparison analyses.

Measuring engagement among older adults using a multidimensional analysis of communication: Method Design (Preprint)

BACKGROUND Characterising older adult engagement is important to determine the effectiveness of interventions. Engagement is the occupying of oneself in external stimuli and is observable across multiple dimensions of behaviour. Engagement of older adults is commonly investigated on a single behavioural dimension. OBJECTIVE In this article, we present a multidisciplinary approach for measuring and characterising engagement of older adults using techniques appropriate for people with varying degrees of dementia. METHODS Contexts for engagement included a dyadic reminiscence therapy interview and a 12-week technology driven group reminiscence therapy. Participants were older adults (8 female, 1 male, mean age: 79) who attended a day respite facility. Audio-visual recordings of the sessions were processed to analyse facial movement, lexical use, and prosodic patterns of speech. Facial movement was processed using OpenFace to measure the presence and intensity of facial movement. Lexical use was processed using the Linguistic Enquiry and Word Count to measure personal pronoun use, affective word use, and emotional tone of words in speech. Prosodic patterns of speech were processed using custom scripts written in Praat and Python, to measure mean duration of utterances, mean words per utterance, articulation rate and variability of F0. Mixed-effects modelling was used to assess effects of treatment conditions on dependent variable outcomes. RESULTS Results indicate measuring engagement through a multidimensional approach can sensitively capture older adults’ engagement. CONCLUSIONS Application of this method can enhance a researcher’s ability to measure older adult engagement, provide means to compare across interventions and contextual environments, and further develop the science of psychosocial intervention research.

Foreign Experience of CEOs and Managerial Risk Taking

Our paper uses a multidimensional analysis to provide a better insight on the relationship between CEO foreign experience and corporate risk-taking. By decomposing the foreign experience of CEOs from developing economies such as Malaysia, we find that CEOs who have studied in OECD countries undertake higher levels of risk-taking and CEOs’ foreign working experience may have an adverse effect on risk-taking behaviour especially if the working experience is obtained from non-OECD countries. Additional analysis reveals that younger CEOs and family CEOs with foreign working experience matter in reinforcing the firms’ risk-taking activities. Overall, our findings provide implication for researchers and policymakers seeking to nurture risk-taking behaviours and innovativeness in emerging countries.

Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data

The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.