Applications of Artificial Intelligence in Live Action Role-Playing Games (LARP)

Live Action Role-Playing (LARP) games and similar experiences are becoming a popular game genre. Here, we discuss how artificial intelligence techniques, particularly those commonly used in AI for Games, could be applied to LARP. We discuss the specific properties of LARP that make it a surprisingly suitable application field, and provide a brief overview of some existing approaches. We then outline several directions where utilizing AI seems beneficial, by both making LARPs easier to organize, and by enhancing the player experience with elements not possible without AI.Comment: 8 pages, 2 figures. Published at IEEE Conference on Games, 202

Disfluency and ageing : a study of healthy older speakers of New Zealand English

The current study examined 115 New Zealand English speakers aged 64-91 years to obtain normative data on fluency. Stuttering-like and normal disfluencies were analysed in speaking tasks of conversation and reading to determine the frequency of disfluencies. Variables of age, sex, years of education, and cognitive functioning were also examined to determine whether these influenced disfluencies. Results indicated no change in stuttering-like and normal disfluencies across age in conversation, yet a small significant increase was found in reading for normal disfluencies. Sex and years of education revealed no significant relationship with total disfluencies produced across age, however there was a significant relationship between cognitive scores and total disfluencies – speakers with higher cognitive scores produced less disfluencies. Age, sex, years of education, and cognitive scores were not significant predictors of stuttering-like disfluencies, though normal disfluencies were. Within the fluency literature, normative data is limited for the ageing population 60+. This study provides normative data for older New Zealand speakers and valuable additional information to assist clinicians in assessment/diagnosis of acquired communication disorders

Gp130-Dependent Release of Acute Phase Proteins Is Linked to the Activation of Innate Immune Signaling Pathways

Background: Elevated levels of acute phase proteins (APP) are often found in patients with cardiovascular diseases. In a previous study, we demonstrated the importance of the IL-6-gp130 axis-as a key regulator of inflammatory acute phase signaling in hepatocytes-for the development of atherosclerosis. Background/Principal Findings: Gp130-dependent gene expression was analyzed in a previously established hepatocytespecific gp130 knockout mouse model. We performed whole transcriptome analysis in isolated hepatocytes to measure tissue specific responses after proinflammatory stimulus with IL-6 across different time points. Our analyses revealed an unexpected small gene cluster that requires IL-6 stimulus for early activation. Several of the genes in this cluster are involved in different cell defense mechanisms. Thus, stressors that trigger both general stress and inflammatory responses lead to activation of a stereotypic innate cellular defense response. Furthermore, we identified a potential biomarker Lipocalin (LCN) 2 for the gp130 dependent early inflammatory response. Conclusions/Significance: Our findings suggest a complex network of tightly linked genes involved in the early activatio

Transcriptomic stratification of late-onset Alzheimer\u27s cases reveals novel genetic modifiers of disease pathology.

Late-Onset Alzheimer\u27s disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value \u3c 5×10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways

Variable outcomes of human heart attack recapitulated in genetically diverse mice.

Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction

Variable outcomes of human heart attack recapitulated in genetically diverse mice

Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction

Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer\u27s disease progression.

Introduction: Genome-wide association studies (GWAS) for late onset Alzheimer\u27s disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity. Methods: We use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer\u27s Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression. Results: CNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, Discussion: This is the first attempt to show that non-invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring