THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits

A Unified Framework Integrating Parent-of-Origin Effects for Association Study

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat- POE and Func-POE models under HWE for quantitative traits

Chinese language training for Indonesian workers = 印尼外勞的中文培訓班

This social activity program is geared to the Indonesian labour who will work in Mandarin Chinese speaking regions, organized by the Chinese department of UK Petra, benefit to both the major study students and the local labour. Indonesia is one of the conventional labour-export country in Southeast Asia. Huge amount of labour working in the Chinese speaking regions such as Taiwan, Hong Kong etc. Language communication had been the biggest problem for these people. The solution previously was hiring the returned one as the trainer, but they are lack in general grammar and incorrect in most of the pronunciation, which make the study quality poor. The learner who accomplish the training cannot explain clearly and cannot understand the employer\u27s instructions, the problem still occupy. With this program, we can use the social resource effectively. The major study students got a chance to practice their professional skill to make the learner have a systematic and standard basic train, to reach a win-win aspect. We divided 10 students into three groups, each group is responsible for teaching different topics in 9 teaching sessions. The topics is: Introduction, food, shopping, learning, health, entertainment, family, work and farewell. By interacting directly with the prospective workers who will work in China, Taiwan or Hong Kong, it is expected the students also understand the difficulties that come by the prospective migrant workers in real life, so that students are able to develop a sense of empathy and concern for others

A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP

Mechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little interest in the intelligent fault diagnosis. The objective of this study is to develop the products quality intelligent analysis and management system based on Rough Set (RS) and Analytic Hierarchy Process (AHP). Firstly, this paper reviews the principle of hardware, software design, monitoring platform and quality analysis system to reduce the number of information transfer with computer technology. Secondly, the fault types and feature extractions of different faults of elevators are presented and simplified by using RS theory. Then, the objective weight of level index model can be obtained by AHP method, and the comprehensive analysis weight of each index is obtained by using the value of subjective and objective weight coefficients with the golden ratio. Finally, a comprehensive decision weight of the major index for quality control analysis system of many vertical elevators is presented. The results show that the data-driven condition monitoring and quality analysis system is a kind of important means to prevent a disaster of complex mechanical and electrical products

Mitigating Biased Activation in Weakly-supervised Object Localization via Counterfactual Learning

In this paper, we focus on an under-explored issue of biased activation in prior weakly-supervised object localization methods based on Class Activation Mapping (CAM). We analyze the cause of this problem from a causal view and attribute it to the co-occurring background confounders. Following this insight, we propose a novel Counterfactual Co-occurring Learning (CCL) paradigm to synthesize the counterfactual representations via coupling constant foreground and unrealized backgrounds in order to cut off their co-occurring relationship. Specifically, we design a new network structure called Counterfactual-CAM, which embeds the counterfactual representation perturbation mechanism into the vanilla CAM-based model. This mechanism is responsible for decoupling foreground as well as background and synthesizing the counterfactual representations. By training the detection model with these synthesized representations, we compel the model to focus on the constant foreground content while minimizing the influence of distracting co-occurring background. To our best knowledge, it is the first attempt in this direction. Extensive experiments on several benchmarks demonstrate that Counterfactual-CAM successfully mitigates the biased activation problem, achieving improved object localization accuracy.Comment: 13 pages, 5 figures, 4 table

Changes in 5-HT1A Receptor Expression in the Oculomotor Nucleus in a Rat Model of Post-traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is an anxiety disorder that develops after exposure to a life-threatening traumatic experience. Mental disorder appears after the traumatic stress incident and affects the movement of the eye muscle dominated by the oculomotor nucleus, an important nuclear group of the brainstem. It has been reported that dysfunction of the neurotransmitter 5-hydroxytryptamine (5-HT) can lead to the instability of the internal environment in response to stress and plays an important role in the pathology of PTSD and that the 5-HT1A receptor (5-HT1AR) is critically involved in regulating mood and anxiety levels. In this study, the 5-HT1AR expression in the oculomotor nucleus was examined in rats with single-prolonged stress (SPS), a well established post-traumatic stress disorder animal model. Our results show that the expression of 5-HT1AR in the oculomotor nucleus neurons gradually increased 1, 4, and 7 days after exposure to SPS in comparison to the normal control group, measured by immunohistochemistry, western blotting, and reverse transcription polymerase chain reaction (RT-PCR). The expression of 5-HT1AR reached its peak 7 days after the SPS exposure and then decreased 14 days after. There is also a change in the ultrastructure in the oculomotor nucleus neuron upon SPS treatment which was observed by transmission electron microscopy. These results suggest that SPS can induce a change of the 5-HT1AR expression in the oculomotor nucleus, which may be one of the molecular mechanisms that lead to PTSD

miRecords: an integrated resource for microRNA–target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords

Population Effect Model Identifies Gene Expression Predictors of Survival Outcomes in Lung Adenocarcinoma for Both Caucasian and Asian Patients

Background: We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods: We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results: Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions: This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied

Construction and Properties of Polyvinyl Alcohol/Chitosan Electrospun Film Loaded with Catechins

In order to develop a new bio-based food packaging material and improve the bioavailability of natural phenolic compounds, an electrospinning film loaded with Catechin was prepared by electrospinning using catechin (CT), polyvinyl alcohol (PVA) and chitosan (CS) as substrates. The microstructure and diameter distribution of the electrospun films were analyzed by scanning electron microscopy. The interaction between CT and film forming substrate was studied by Fourier infrared spectroscopy, X-ray diffraction and thermal analysis. The effects of CT addition on the physical and chemical properties of the electrospun film were investigated by taking the mechanical properties, gas permeability and antioxidant activity of the film as parameters. Finally, the preservation effect of electrospun film was analyzed by sensory evaluation, water loss rate and titrable acid content. The results showed that the intermolecular hydrogen bond was formed between CT and CS, and the hydrophobic property was improved. When the concentration of CT was 0.8%, the comprehensive performance of the electrospun film was the best. It had good morphology, dense structure and good thermal stability. At this point, the tensile strength and elongation at break reached the maximum, which were 12.89 MPa and 62.45% respectively. The water solubility, water vapor transmittance and CO2 transmittance were the lowest, which were 29.51%, 0.1532 g·mm·(m2·h·kPa)−1 and 5.9 g·(m2·h)−1, respectively. Besides, the scavenging rate of DPPH free radical also reached the maximum value, which was 71.02%. Moreover, the electrospun membrane had sustained release effect. When the CT concentration was 0.8%, its cumulative release rate was the highest. The preservation research results showed that the electrospun film could effectively delay the deterioration of strawberry, and the electrospun film with 0.8% CT concentration had the best preservation effect. In conclusion, the electrospun film with 0.8% CT concentration had the best comprehensive performance, and it had certain antioxidation and fresh-keeping ability