MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework

As large amounts of heterogeneous biomedical data become available, numerous methods for integrating such datasets have been developed to extract complementary knowledge from multiple domains of sources. Recently, a deep learning approach has shown promising results in a variety of research areas. However, applying the deep learning approach requires expertise for constructing a deep architecture that can take multimodal longitudinal data. Thus, in this paper, a deep learning-based python package for data integration is developed. The python package deep learning-based multimodal longitudinal data integration framework (MildInt) provides the preconstructed deep learning architecture for a classification task. MildInt contains two learning phases: learning feature representation from each modality of data and training a classifier for the final decision. Adopting deep architecture in the first phase leads to learning more task-relevant feature representation than a linear model. In the second phase, linear regression classifier is used for detecting and investigating biomarkers from multimodal data. Thus, by combining the linear model and the deep learning model, higher accuracy and better interpretability can be achieved. We validated the performance of our package using simulation data and real data. For the real data, as a pilot study, we used clinical and multimodal neuroimaging datasets in Alzheimer's disease to predict the disease progression. MildInt is capable of integrating multiple forms of numerical data including time series and non-time series data for extracting complementary features from the multimodal dataset

Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease

Genetic variation in cis-regulatory elements related to splicing machinery and splicing regulatory elements (SREs) results in exon skipping and undesired protein products. We developed a splicing decision model to identify actionable loci among common SNPs for gene regulation. The splicing decision model identified SNPs affecting exon skipping by analyzing sequence-driven alternative splicing (AS) models and by scanning the genome for the regions with putative SRE motifs. We used non-Hispanic Caucasians with neuroimaging, and fluid biomarkers for Alzheimer's disease (AD) and identified 17,088 common exonic SNPs affecting exon skipping. GWAS identified one SNP (rs1140317) in HLA-DQB1 as significantly associated with entorhinal cortical thickness, AD neuroimaging biomarker, after controlling for multiple testing. Further analysis revealed that rs1140317 was significantly associated with brain amyloid-f deposition (PET and CSF). HLA-DQB1 is an essential immune gene and may regulate AS, thereby contributing to AD pathology. SRE may hold potential as novel therapeutic targets for AD

Ethanol Extract of Dianthus chinensis L. Induces Apoptosis in Human Hepatocellular Carcinoma HepG2 Cells In Vitro

Dianthus chinensis L. is used to treat various diseases including cancer; however, the molecular mechanism by which the ethanol extract of Dianthus chinensis L. (EDCL) induces apoptosis is unknown. In this study, the apoptotic effects of EDCL were investigated in human HepG2 hepatocellular carcinoma cells. Treatment with EDCL significantly inhibited cell growth in a concentration- and time-dependent manner by inducing apoptosis. This induction was associated with chromatin condensation, activation of caspases, and cleavage of poly (ADP-ribose) polymerase protein. However, apoptosis induced by EDCL was attenuated by caspase inhibitor, indicating an important role for caspases in EDCL responses. Furthermore, EDCL did not alter the expression of bax in HepG2 cells but did selectively downregulate the expression of bcl-2 and bcl-xl, resulting in an increase in the ratio of bax:bcl-2 and bax:bcl-xl. These results support a mechanism whereby EDCL induces apoptosis through the mitochondrial pathway and caspase activation in HepG2 cells

Gender Differences and Relationships among Lifestyle and Reproductive Health in University Students

PURPOSE: University students happen to be in a transitional period at the beginning of one's adult life and thereby establish the basis for their health care. The negative lifestyles followed by students during this period can also affect their reproductive health. The purpose of this study was to identify lifestyle, reproductive health, gender differences and relationships between lifestyle and reproductive health in university students. METHODS: We used a descriptive cross-sectional design. A total of 300 subjects were enrolled. Data were collected using structured questionnaires between October 11 and 25, 2017 and analyzed using SPSS 25.0. Subjects agreed to undergo a face-to-face interview, including administration of the Health Promotion Lifestyle Profile II (HPLP-II) and reproductive health (knowledge, attitude, and behaviors). RESULTS: The mean age of the subjects was 21.4 years. HPLP-II and reproductive health behaviors were significantly different between the genders. The scores of physical activity and nutrition in females were significantly lower than males. The scores of safe sex and sexual responsibility in females were significantly higher than males, and the score of genital health management was significantly lower in females than males. High HPLP-II score was observed to be in correlation with high reproductive health attitudes and behaviors. CONCLUSION: The result revealed differences in lifestyle and reproductive health between both the genders. For improvement of reproductive health of university students, provision of lifestyle intervention including healthy nutritional habits and physical activity is imperative

Factors Affecting Psychosocial Adjustment in Patients with Surgical Removal of Benign Breast Tumor

PURPOSE: To identify factors influencing psychosocial adjustment in patients with surgical removal of benign breast tumor. METHODS: With a survey design, data were collected using the Psychosocial Adjustment to Illness Scale-Self Report (PAIS-SR), Body Image Scale, Physical Discomfort Scale, and Family Support Scale with patients who had had surgical removal of a benign breast tumor from September to November 2017. Data were analysed with descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and stepwise multiple regression. RESULTS: The mean scores for physical discomfort, body image, family support, and psychosocial adjustment were 1.57±0.51, 0.37±0.64, 3.62±0.67, and 4.00±0.45, respectively. Family support, body image, physical discomfort, number of surgical removal of benign breast tumor (twice), and cancer insurance status (yes) were verified as factors influencing psychosocial adjustment. These factors accounted for 57.4% of psychosocial adjustment. CONCLUSION: In this study, family support, body image, and physical discomfort were identified as significant predictors of psychosocial adjustment. Therefore, this study can be used as fundamental data to develop nursing intervention strategies in order to increase psychosocial adjustment in patients with surgical removal of a benign breast tumor

Trajectories of subjective health status among married postmenopausal women based on the ecological system theory: a longitudinal analysis using a latent growth model

Purpose This study investigated the trajectory of subjective health status in married postmenopausal women and aimed to identify predictive factors affecting subjective health status. Methods Data were obtained from women who participated in wave 4 (2012) of the Korean Longitudinal Survey of Women & Families Longitudinal Study and continued to the latest phase (wave 7, 2018). A latent growth model (LGM) was used to analyze data from 1,719 married postmenopausal women in the framework of the ecological system theory. Results The mean age of the participants at wave 4 was 56.39±4.71 years, and the average subjective health status was around the midpoint (3.19±0.84). LGM analysis confirmed that subjective health status decreased over time (initial B=3.21, slope B=–0.03). The factors affecting initial subjective health were age, body mass index, frequency of vigorous physical activity (microsystem level), marital satisfaction (mesosystem level), and medical service utilization (macrosystem level). Medical service utilization and the frequency of vigorous physical activity were identified as predictive factors affecting the slope in subjective health status. The model fit was satisfactory (TLI=.92, CFI=.95, and RMSEA=.04). Conclusion This analysis of the trajectory of subjective health status of married postmenopausal women over time confirmed that subjective health is influenced by overall ecological system factors, including the microsystem, mesosystem, exosystem, macrosystem, and chronosystem. Therefore, it is necessary to assess physical activity and support policies promoting access to medical services in order to improve the subjective health status of married postmenopausal women

Factors influencing infertility-related quality of life in infertile women

Purpose Infertile women experience various physical, psychological, and relational problems that affect their infertility–related quality of life (QoL). This study investigated infertile women's infertility-related QoL with the goal of identifying how it is influenced by fatigue, depression, and marital intimacy. Methods A sample of 140 infertile women was surveyed in a cross-sectional study. Data were collected from February to April 2018 using self-report structured questionnaires at three infertility clinics located in Jeonju, Korea. Data were analyzed using the independent t-test, analysis of variance, Pearson correlation coefficients, and stepwise multiple regression analysis in SPSS for Windows version 25.0. The subjects agreed to complete a face-to-face interview, including administration of the Fatigue Severity Scale, Depression Anxiety Stress Scale-21, Marital Intimacy Scale, and the Fertility Quality of Life tool. Results The mean age of the participants was 35.6±4.3 years. Infertility-related QoL was negatively correlated with fatigue (r=–.42, p<.001) and depression (r=–.56, p<.001), and positively correlated with marital intimacy (r=.30, p<.001). Multiple regression analysis showed that depression (β=–0.44, p<.001), fatigue (β=–0.27, p<.001), and husband's attitude (β=–0.19, p=.007) had significant effects on the QoL of infertile women, accounting for 40.5% of the variance in infertility-related QoL. Conclusion The study provides insights into how infertile women's infertility-related QoL was influenced by depression, fatigue, and their husbands' attitudes regarding infertility treatment. To improve infertile women's infertility-related QoL, healthcare providers should consider developing strategies to decrease depression and fatigue in infertile women and to address their husbands' attitudes

Factors influencing quality of life in low-income women with young children in Korea: a cross-sectional study

Purpose This study aimed to investigate the effects of health-promoting behaviors (HPB), marital intimacy, and parenting stress on the quality of life (QoL) of low-income women with young children in Korea, an underserved group. Methods This cross-sectional survey employed a descriptive correlational design. Using convenience sampling, 123 low-income women with children younger than 6 years were recruited from 14 health and community centers in Jeonju, Korea, from June 2020 to May 2021. Participants completed a questionnaire on QoL, HPB, marital intimacy, and parenting stress. Data were analyzed using descriptive statistics, independent t-test, analysis of variance, Pearson correlation, and hierarchical regression analysis. Results Participants, who were on average 37.41±3.65 years old and had 1 to 2 children (n=98, 79.7%), reported a mid-level (3.14 out of 1–5) of QoL. Marital intimacy (β=.38, p<.001) was the most influential factor on the QoL of low-income women with young children. In descending order, HPB (β=.35, p<.001) and non-employment status (β=–.21, p=.003) had a significant influence on QoL (F=15.64, p<.001), and the overall explanatory power was 49.0%. Conclusion Considering the mid-level QoL of low-income women with young children, programs aimed at improving the QoL of low-income women need to promote marital intimacy and maintain HPB, while considering their employment status. Strategies that include couple counseling, health care to encourage healthy lifestyles, and reemployment education are needed

Health promoting behaviors in low-income overweight and obese women in Korea: an exploratory qualitative study

Purpose This study aimed to explore and understand the health promoting behaviors of low-income overweight and obese women in Korea. Methods Data were collected from 10 low-income overweight and obese women working at a community self-sufficiency center through semi-structured in-depth interviews. Individual interviews were conducted and transcribed. Deductive content analysis was done, using the MAXQDA program. Results The health promoting behaviors practiced by low-income overweight and obese women were affected by intrapersonal, interpersonal, and organizational/community factors. Six categories were identified and two category clusters were derived that could best describe their health promoting experiences. As main category clusters, despite “feeling that the body and mind are not healthy” participants noted “difficulty maintaining a healthy lifestyle.” Overall, the participants had poor nutritional status, lacked physical activity, experienced much stress in intrapersonal level, and faced intrapersonal-level barriers to health promoting behaviors. Moreover, participants had a lack of personal will, and lack of specific information to practice health promoting behaviors, a lack of time, and too many overall burdens to earn a living for their family while trying to maintain health promotion behaviors. Conclusion Lifestyle interventions for nutrition management, encouragement of physical activity, and stress management are needed for overweight and obese low-income women. In addition, social support and policies are needed to improve their living environment

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Motivation: Network-based genome-wide association studies (GWAS) aim to identify functional modules from biological networks that are enriched by top GWAS findings. Although gene functions are relevant to tissue context, most existing methods analyze tissue-free networks without reflecting phenotypic specificity. Results: We propose a novel module identification framework for imaging genetic studies using the tissue-specific functional interaction network. Our method includes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to incorporate network topological information and enhance the connectivity among top genes; (ii) detect densely connected modules based on interactions among top re-prioritized genes; and (iii) identify phenotype-relevant modules enriched by top GWAS findings. We demonstrate our method on the GWAS of [18F]FDG-PET measures in the amygdala region using the imaging genetic data from the Alzheimer's Disease Neuroimaging Initiative, and map the GWAS results onto the amygdala-specific functional interaction network. The proposed network-based GWAS method can effectively detect densely connected modules enriched by top GWAS findings. Tissue-specific functional network can provide precise context to help explore the collective effects of genes with biologically meaningful interactions specific to the studied phenotype