A nonparametric framework for inferring orders of categorical data from category-real pairs

Seizure-related stress and arousal responses mediate a relationship between anxiety trait and state in epilepsy

BACKGROUND

Epilepsy causes substantial psychological distress and anxiety, primarily due to seizures. However, the impact of stress responses and changes in arousal and their association with anxiety patterns in patients with epilepsy (PWE) remains unclear. This study aimed to investigate the relationships among seizures, stress and arousal characteristics, and trait and state anxiety characteristics in PWE.

METHODS

Our sample consisted of 159 outpatients with epilepsy recruited from five institutions in Japan in 2020. Participants completed the State-Trait Anxiety Inventory-Form JYZ (STAI) and the Japanese-Stress Arousal Check List (J-SACL). We analyzed the correlations between inventory scores and clinical information. Using principal component analysis (PCA), we derived epilepsy-specific stress/arousal characteristics, which accounted for high arousal and low-stress levels, termed epilepsy-specific stress or arousal response (ESAR), from the J-SACL scores. We conducted a mediation analysis to assess the mediating role of ESAR in the relationship between traits and state anxiety.

RESULTS

We found significant correlations between J-SACL stress and arousal factors (r = -0.845, p < 0.001), ESAR and seizure frequency (r = -0.29, p < 0.001), ESAR and trait anxiety scores on the STAI (r = -0.77, p < 0.0001), and ESAR and state anxiety scores on the STAI (r = -0.60, p < 0.0001). Mediation analysis supported by the Monte Carlo method revealed that ESAR significantly mediated the association between trait and state anxiety.

CONCLUSIONS

These findings elucidate the epilepsy-specific stress and arousal characteristics and their roles in mediating traits and state anxiety. These results may reflect the long-term clinical course and unique emotion recognition tendencies in epilepsy.

Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis

Poverty is one of the fundamental issues that mankind faces. To solve poverty issues, one needs to know how severe the issue is. The Multidimensional Poverty Index (MPI) is a well-known approach that is used to measure a degree of poverty issues in a given area. To compute MPI, it requires information of MPI indicators, which are binary variables collecting by surveys, that represent different aspects of poverty such as lacking of education, health, living conditions, etc. Inferring impacts of MPI indicators on MPI index can be solved by using traditional regression methods. However, it is not obvious that whether solving one MPI indicator might resolve or cause more issues in other MPI indicators and there is no framework dedicating to infer empirical causal relations among MPI indicators. In this work, we propose a framework to infer causal relations on binary variables in poverty surveys. Our approach performed better than baseline methods in simulated datasets that we know ground truth as well as correctly found a causal relation in the Twin births dataset. In Thailand poverty survey dataset, the framework found a causal relation between smoking and alcohol drinking issues. We provide R CRAN package'BiCausality' that can be used in any binary variables beyond the poverty analysis context.

Hyperfocus symptom and internet addiction in individuals with attention-deficit/hyperactivity disorder trait

Background

Hyperfocus symptom is the intense concentration on a certain object. It is a common but often overlooked symptom in those with attention-deficit/hyperactivity disorder (ADHD). Hyperfocus disrupts attention control and results in a focus on inappropriate behaviors. It allows individuals to focus on internet use and make them use internet excessively. This excessive internet use can lead to an addiction. This study investigated the status of IA and hyperfocus, the mediation effect of hyperfocus in relation to IA, and the relationship between ADHD subtypes and hyperfocus in those with ADHD symptoms.

Methods

This web-based cross-sectional study included 3,500 Japanese adults who completed internet-based questionnaires, which included the Adult ADHD Self-Report Scale (ASRS), Internet Addiction Test (IAT), and Hyperfocus Scale (HFS) to assess ADHD symptoms, internet dependence, and hyperfocus symptoms, respectively. The mediating role of HFS in the relationship between ASRS and IAT was assessed by mediation analysis. To analyze the relationship between hyperfocus symptoms and ADHD subtypes, we compared the correlation of HFS with the Inattention and Hyperactive Scores of ASRS.

Results

ADHD traits were associated with higher IAT scores (p &lt; 0.001) and higher HFS scores (p &lt; 0.001). Mediation analysis and bootstrap testing showed that HFS significantly mediated the association between ASRS and IAT. Analyses of ADHD subtypes demonstrated that HFS was significantly correlated with the Inattention (R = 0.597, p &lt; 0.001) and Hyperactive (R = 0.523, p &lt; 0.001) Scores. The correlation between HFS and the Inattention Score was significantly higher than that between HFS and the Hyperactive Score (p &lt; 0.001).

Conclusion

Our findings suggest that hyperfocus may play an important role in addictive behavior in ADHD as a manifestation of attentional control malfunction.

Population Structure of Nation-Wide Rice in Thailand

BACKGROUND

Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored.

RESULTS

The result of inferred population structure from admixture and clustering analysis illustrated strong evidence of substructure in each geographical region. The results of phylogenetic tree, PCA analysis, and machine learning on population identifying SNPs also supported the inferred population structure.

CONCLUSION

The population structure inferred in this study contains five subpopulations that tend to group individuals based on location. So, each subpopulation has unique genetic patterns, agronomic traits, as well as different environmental conditions. This study can serve as a reference point of the nation-wide population structure for supporting breeders and researchers who are interested in Thai rice.