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Exploring the prognosis, immune response, and therapeutic prospects of Parthanatos-related miRNAs in low-grade gliomas
No full textThe low-grade gliomas (LGG) are chronic aggressive brain tumors that often result in shortened survival rates due to recurrences and disease progression. Parthanatos, a programmed cell death pathway associated with PARP-1 activation and AIF, is potentially instrumental in tumor development. miRNAs play a key role in regulating tumourigenesis and progression, but few studies have been conducted on Parthanatos-associated miRNAs. We collected miRNA and mRNA datasets from LGG patients from TCGA and CGGA databases and corresponding clinical information. Gene sets related to Parthanatos were obtained through the Genecard database. We used IHC data to validate the differences in Parthanatos-related genes (PRGs) expression in glioma and normal brain tissue. A protein-protein interaction network of PRGs was established using the STRING database, and significantly related miRNAs were screened by Spearman correlation analysis. NMF clustering analysis and a Parthanatos-related miRNA-based prognostic index (PCMI) explored the heterogeneity of miRNA expression patterns. In addition, we assessed the potential role of miRNAs in immune invasion and therapeutic response in the tumor microenvironment and predicted the sensitivity of common chemotherapeutic and targeted therapeutic agents by prophetic and OncoPredict using the CMap database to identify possible therapeutic agents. The miRNAs associated with Parthanatos were successfully identified, and a prognostic model consisting of 9 miRNAs was constructed. The model showed good predictive efficacy in both training and validation datasets. Significant differences in survival, clinicopathological characteristics, and immune microenvironment invasion were observed between patients in the high-risk and low-risk groups. Drugs such as Fasudil were identified as possible therapeutic candidates by drug sensitivity analysis and CMap prediction. The miRNAs associated with Parthanatos were successfully identified, and a prognostic model consisting of 9 miRNAs was constructed. The model showed good predictive efficacy in both training and validation datasets. In the low-risk group, immune microenvironment invasion and survival differed significantly from the high-risk group . Drugs such as Fasudil were identified as possible therapeutic candidates by drug sensitivity analysis and CMap prediction
Replication Dofile for: Unequal and Unsupportive: Exposure to Poor People Weakens Support for Redistribution among the Rich
No full textOur analyses are mainly based on administrative registry data. These data contain confidential information and are therefore not publicly available. The combined survey and registry data are stored at Statistics Denmark and can only be accessed by researchers affiliated with a permanent Danish research institution/environment using Statistics Denmark remote server system (for further information about the Danish administrative registries, including access, see http://www.dst.dk/en/TilSalg/Forskningsservice.aspx). Accordingly, we cannot make replication data for our analyses available. However, the do-file used to produce the analyses, as well as a file containing the actual output from the statistical software regarding the main analyses, can be found here
The Role of Interface Design in Shaping Consumptive Curation Affordances on Social Media Platforms: TikTok as a Case Study
No full textSocial media transition into algorithmic content recommendations has reshaped platforms’ consumptive curation affordances, reducing users’ explicit curation tools. In this article I interrogate the role of platforms’ interface design in shaping these new affordances. Building on existing literature on digital curation, social media affordances and mediation theory, I present affordances as relational, shaped by the interplay between social media technology, user practices, and social arrangements. Platforms’ software interface acts as a mediator between consumptive curation practices and algorithmic recommendations, establishing an initial environment that attempts to shape user practices.
To illustrate this, I analyse TikTok’s interface through a walkthrough method, organised according to the algorithmic experience framework. Findings show the dominant role of the For You Page, how TikTok encourages passive consumption through watching and scrolling and how it discourages disabling data sources, among others. These insights serve as a foundation for future user-centred studies on how users react to and reappropriate TikTok’s interface to fulfil their consumptive curation goals
Replication Data for: Technological and Financial Drivers of Green Marine Industry: Insight from Green Economic Efficiency in Fishing Sector
No full textChina's marine fisheries, 2009-202
Replication Data for: Does America's Failure in Afghanistan Reveal any Truths about Democracy?
No full textThis contains the script and source information for "Does America's Failure in Afghanistan Reveal any Truths about Democracy?
Emotional analysis of bilingual lexical acquisition for Chinese preschoolers
No full textBilingual lexical acquisition is a common event for young learners all over the world. Previous studies have primarily focused on lexical acquisition from a linguistic or cognitive perspective, neglecting the emotional aspect and its impact on process of lexical acquisition. This study aims to explore emotional features and influences on L2 lexical acquisition in bilingual children. Data were collected from 46 Chinese learners, aged 3 to 4, attending three preschools emphasizing the English education. The study employed Bivariate DeFries- Fulker (DF) extremes analysis to gather information from the Vocabulary Learning Questionnaire (VLQ), Infant-Toddler Social and Emotional Assessment (ITSPA), and Depression Anxiety Stress Scales (DASS). The findings indicate that emotional analysis can reveal correlations between lexical acquisition and emotional features. Moreover, subtle differences were observed in the reciprocal interactions between bilingual lexical acquisition. Additionally, the Bivariate DF extremes analyses demonstrated a significant correlation (r=.71) between L1 lexical acquisition and emotion, while the correlation between bilingual lexical acquisition was significant (r=.79). These results further reinforce the significance of emotional impact on supporting bilingual cognition and learning
Complete metrics tables for "Goal Question Metrics" modeling
No full textThe final step in GQM modeling was determining the 80 metrics in the multivocal literature to be used according to the raised questions. Each table lists the metric name, descriptions (when necessary) and the formulas or data that quantify them
Replication Data for: Využití víceúrovňových modelů při analýze kontextuálních efektů míry ekonomické aktivity na podporu přerozdělování v komparativních longitudinálních datech
No full textThis article studies the links between a country’s labour force participation rate and attitudes towards income redistribution. The article also demonstrates how to specify a multilevel model when analysing contextual effects and it presents several types of random effects structures and options for centering explanatory variables in comparative longitudinal survey data. The contextual effect is decomposed into longitudinal and cross-sectional components for time-varying contextual variables, such as the labour force participation rate. The analysis of redistribution support based on ESS data from 27 countries and nine rounds shows how fundamentally the mentioned properties can influence substantive conclusions. The analyses presented in this article do not provide any evidence for a link between redistribution support and the labour force participation rate. However, the hypothetical configurations of multilevel models presented here cover all possible substantive effects of the labour force participation rate. Contextual effects analysis may thus lead to highly unreliable results when a multilevel model fails to control for the compositional effects of individual-level predictors, when it does not specify random effects at the level to which a substantial variation of the outcome variable may be attributed, and when it does not distinguish between the longitudinal and cross-sectional effects of time-varying variables