• Childhood Kidney Diseases
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• 제14권2호
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• pp.120-131
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• 2010

Renal tubular acidosis (RTA) is a metabolic acidosis due to impaired excretion of hydrogen ion, or reabsorption of bicarbonate, or both by the kidney. These renal tubular abnormalities can occur as an inherited disease or can result from other disorders or toxins that affect the renal tubules. Disorders of bicarbonate reclamation by the proximal tubule are classified as proximal RTA, whereas disorders resulting from a primary defect in distal tubular net hydrogen secretion or from a reduced buffer trapping in the tubular lumen are called distal RTA. Hyperkalemic RTA may occur as a result of aldosterone deficiency or tubular insensitivity to its effects. The clinical classification of renal tubular acidosis has been correlated with our current physiological model of how the nephron excretes acid, and this has facilitated genetic studies that have identified mutations in several genes encoding acid and base ion transporters. Growth retardation is a consistent feature of RTA in infants. Identification and correction of acidosis are important in preventing symptoms and guide approved genetic counseling and testing.

• Molecular & Cellular Toxicology
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• 제3권2호
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• pp.113-118
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• 2007

Chlorobenzenes due to their acute toxicity and the capability of bioaccumulating are of great health and environmental concern. Especially, 1, 2-dichlorobenzene (CAS No. 95-50-1) is used for organic synthesis, dye manufacture, as a solvent and for other applications in chemical industry. Adverse effects of 1, 2-dichlorobenzene includes increases in liver and kidney weights and hepatotoxicity. In this study, we evaluated the genetic toxicity of 1, 2-dichlorobenzene with more advanced methods, in vitro mouse lymphoma assay $tk^{+/-}$ gene assay (MLA) and in vitro mouse supravital micronucleus (MN) assay. 1, 2-Dichlorobenzene appeared the significantly positive results and the induction of large mutant colonies only in the presence of metabolic activation system with MLA. But in vitro testing of 1, 2-dichlorobenzene yielded negative results with supravital MN assay. These results suggest that 1, 2-dichlorobenzene may play a mutagen rather than clastogen in vitro mammalian system.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

• Journal of Genetic Medicine
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• 제9권1호
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• pp.31-34
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• 2012

Spondyloepiphyseal dysplasia tarda (SEDT) is an X-linked skeletal dysplasia. Patients show disproportionate short stature with short trunk and barrel-shaped chest, which usually become pronounced in late childhood. The radiologic findings are characterized by narrow intervertebral disc spaces and moderate epiphyseal dysplasia of long bones. Here we report a case of SEDT with a novel frameshift mutation in TRAPPC2, the disease-causing gene of SEDT. This is the first Korean report with SEDT confirmed by genetic testing.

• 비파괴검사학회지
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• 제35권6호
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• pp.414-420
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• 2015

Concrete undergoes significant phase changes from liquid to solid states as hydration progresses. These phase changes are known as the setting process. A liquid state concrete is electrically conductive because of the presence of water and ions. However, since the conductive elements in the liquid state of concrete are consumed to produce non-conductive hydration products, the electrical conductivity of hydrating concrete decreases during the setting process. Therefore, the electrical properties of hydrating concrete can be used to monitor the setting process of concrete. In this study, a parameter identification method to estimate electrical parameters such as ohmic resistance of concrete is proposed. The effectiveness of the proposed method for monitoring the setting process of concrete is experimentally validated.

• Tuberculosis and Respiratory Diseases
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• 제75권5호
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• pp.181-187
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• 2013

The emergence of new therapeutic agents for non-small cell lung cancer (NSCLC) implies that histologic subtyping and molecular predictive testing are now essential for therapeutic decisions. Histologic subtype predicts the efficacy and toxicity of some treatment agents, as do genetic alterations, which can be important predictive factors in treatment selection. Molecular markers, such as epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement, are the best predictors of response to specific tyrosine kinase inhibitor treatment agents. As the majority of patients with NSCLC present with unresectable disease, it is therefore crucial to optimize the use of tissue samples for diagnostic and predictive examinations, particularly for small biopsy and cytology specimens. Therefore, each institution needs to develop a diagnostic approach requiring close communication between the pulmonologist, radiologist, pathologist, and oncologist in order to preserve sufficient biopsy materials for molecular analysis as well as to ensure rapid diagnosis. Currently, personalized medicine in NSCLC is based on the histologic subtype and molecular status. This review summarizes strategies for tissue acquisition, histologic subtyping and molecular analysis for predictive testing in NSCLC.

• Computers and Concrete
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• 제18권2호
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• pp.155-163
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• 2016

This paper, proposes 20 models for predicting compressive strength of recycled aggregate concrete (RAC) containing silica fume by using gene expression programming (GEP). To construct the models, experimental data of 228 specimens produced from 61 different mixtures were collected from the literature. 80% of data sets were used in the training phase and the remained 20% in testing phase. Input variables were arranged in a format of seven input parameters including age of the specimen, cement content, water content, natural aggregates content, recycled aggregates content, silica fume content and amount of superplasticizer. The training and testing showed the models have good conformity with experimental results for predicting the compressive strength of recycled aggregate concrete containing silica fume.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제35권1호
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• pp.15-21
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• 2024

Autism spectrum disorder (ASD) is diagnosed by the clinical decision of a trained professional based on the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition or International Classification of Diseases 11th Revision diagnostic criteria. To obtain information for diagnostic formulation, professionals should explore detailed developmental history, and can use structured or semi-structured assessment tools to observe interaction between the child and parents or strangers. Diagnostic assessment should include a profile of the strength and weaknesses of the individual and should be conducted using an optimal approach by a multidisciplinary team with appropriate techniques and experience. Assessment of language, cognitive, neuropsychological, and adaptive functioning should be conducted in ASD individuals prior to establishing an individualized treatment plan. Genetic testing, brain magnetic resonance imaging or electroencephalogram testing can be considered for identification of underlying causes.

• BMB Reports
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• 제42권9호
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• pp.617-622
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• 2009

We investigated the genetic associations of ischemic stroke by identifying epistasis of its heterogeneous subtypes such as small vessel occlusion (SVO) and large artery atherosclerosis (LAA). Epistasis was analyzed with 24 genes in 207 controls and 271 patients (SVO = 110, LAA = 95) using multifactor dimensionality reduction and entropy decomposition. The multifactor dimensionality reduction analysis with any of 1- to 4-locus models showed no significant association with LAA (P > 0.05). The analysis of SVO, however, revealed a significant association in the best 3-locus model with P10L of TGF-$\beta{1}$, C1013T of SPP1, and R485K of F5 (testing balanced accuracy = 63.17%, P < 0.05). Subsequent entropy analysis also revealed that such heterogeneity was present and quite a large entropy was estimated among the 3 loci for SVO (5.43%), but only a relatively small entropy was estimated for LAA (1.81%). This suggests that the synergistic epistasis model might contribute specifically to the pathogenetsis of SVO, which implies a different etiopathogenesis of the ischemic stroke subtypes.

• Journal of Computing Science and Engineering
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• 제10권4호
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• pp.118-127
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• 2016

An improved sample balanced genetic algorithm and Extreme Learning Machine (iSBGA-ELM) was designed for accurate diagnosis of Alzheimer disease (AD) and identification of biomarkers associated with AD in this paper. The proposed AD diagnosis approach uses a set of magnetic resonance imaging scans in Open Access Series of Imaging Studies (OASIS) public database to build an efficient AD classifier. The approach contains two steps: "voxels selection" based on an iSBGA and "AD classification" based on the ELM. In the first step, the proposed iSBGA searches for a robust subset of voxels with promising properties for further AD diagnosis. The robust subset of voxels chosen by iSBGA is then used to build an AD classifier based on the ELM. A robust subset of voxels keeps a high generalization performance of AD classification in various scenarios and highlights the importance of the chosen voxels for AD research. The AD classifier with maximum classification accuracy is created using an optimal subset of robust voxels. It represents the final AD diagnosis approach. Experiments with the proposed iSBGA-ELM using OASIS data set showed an average testing accuracy of 87%. Experiments clearly indicated the proposed iSBGA-ELM was efficient for AD diagnosis. It showed improvements over existing techniques.