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Development of the Korean Developmental Screening Test for Infants and Children (K-DST)
Chung, Hee Jung,Yang, Donghwa,Kim, Gun-Ha,Kim, Sung Koo,Kim, Seoung Woo,Kim, Young Key,Kim, Young Ah,Kim, Joon Sik,Kim, Jin Kyung,Kim, Cheongtag,Sung, In-Kyung,Shin, Son Moon,Oh, Kyung Ja,Yoo, Hee-Jeo The Korean Pediatric Society 2020 Clinical and Experimental Pediatrics (CEP) Vol.63 No.11
Background: Most developmental screening tools in Korea are adopted from foreign tests. To ensure efficient screening of infants and children in Korea, a nationwide screening tool with high reliability and validity is needed. Purpose: This study aimed to independently develop, standardize, and validate the Korean Developmental Screening Test for Infants and Children (K-DST) for screening infants and children for neurodevelopmental disorders in Korea. Methods: The standardization and validation conducted in 2012-2014 of 3,284 subjects (4-71 months of age) resulted in the first edition of the K-DST. The restandardization and revalidation performed in 2015-2016 of 3.06 million attendees of the National Health Screening Program for Infants and Children resulted in the revised K-DST. We analyzed inter-item consistency and test-retest reliability for the reliability analysis. Regarding the validation of K-DST, we examined the construct validity, sensitivity and specificity, receiver operating characteristic curve analysis, and a criterion-related validity analysis. Results: We ultimately selected 8 questions in 6 developmental domains. For most age groups and each domain, internal consistency was 0.73-0.93 and test-retest reliability was 0.77-0.88. The revised K-DST had high discriminatory ability with a sensitivity of 0.833 and specificity of 0.979. The test supported construct validity by distinguishing between normal and neurodevelopmentally delayed groups. The language and cognition domain of the revised K-DST was highly correlated with the K-Bayley Scales of Infant Development-II's Mental Age Quotient (r=0.766, 0.739), while the gross and fine motor domains were highly correlated with Motor Age Quotient (r=0.695, 0.668), respectively. The Verbal Intelligence Quotient of Korean Wechsler Preschool and Primary Scales of Intelligence was highly correlated with the K-DST cognition and language domains (r=0.701, 0.770), as was the performance intelligence quotient with the fine motor domain (r=0.700). Conclusion: The K-DST is reliable and valid, suggesting its good potential as an effective screening tool for infants and children with neurodevelopmental disorders in Korea.
A zero-thermal-quenching phosphor
Kim, Yoon Hwa,Arunkumar, Paulraj,Kim, Bo Young,Unithrattil, Sanjith,Kim, Eden,Moon, Su-Hyun,Hyun, Jae Young,Kim, Ki Hyun,Lee, Donghwa,Lee, Jong-Sook,Im, Won Bin Nature Publishing Group, a division of Macmillan P 2017 NATURE MATERIALS Vol.16 No.5
<P>Phosphor-converted white light-emitting diodes (pc-WLEDs) are efficient light sources used in lighting, high-tech displays, and electronic devices. One of the most significant challenges of pc-WLEDs is the thermal quenching, in which the phosphor suffers from emission loss with increasing temperature during high-power LED operation. Here, we report a blue-emitting Na3-2xSc2(PO4)(3):xEu(2+) phosphor (lambda(em) = 453 nm) that does not exhibit thermal quenching even up to 200 degrees C. This phenomenon of zero thermal quenching originates from the ability of the phosphor to compensate the emission losses and therefore sustain the luminescence with increasing temperature. The findings are explained by polymorphic modification and possible energy transfer from electron-hole pairs at the thermally activated defect levels to the Eu2+ 5d-band with increasing temperature. Our results could initiate the exploration of phosphors with zero thermal quenching for high-power LED applications.</P>
Nuri Tchah(Nuri Tchah ),Donghwa Yang(Donghwa Yang),Heung Dong Kim(Heung Dong Kim),Joon Soo Lee(Joon Soo Lee),Se Hee Kim(Se Hee Kim),Hoon-Chul Kang(Hoon-Chul Kang) 대한소아신경학회 2022 대한소아신경학회지 Vol.30 No.4
Purpose: Developmental and/or epileptic encephalopathy with spike-and-wave activation in sleep (D/EE-SWAS) is a spectrum of conditions characterized by various phenotypes of cognitive, linguistic, and behavioral regression associated with spike-and-wave activation in sleep. We aimed to investigate the phenotypic spectrum and treatment outcomes of pediatric patients with D/EE-SWAS. Methods: We retrospectively analyzed the medical records of pediatric patients diagnosed with D/EE-SWAS and treated at Severance Children’s Hospital from 2006 to 2022. We extracted information from their medical records on electroencephalography before and after treatment, types of treatment, seizure frequency, and developmental profiles. The primary outcome was reduction of the spike-wave index on electroencephalography after treatment. Results: Twenty-one patients with a median age of 5.3 years (interquartile range, 4.1 to 6.6) at diagnosis were included. Ten patients had delayed development. The patients received various anti-seizure medications. Fourteen received long-term, high-dose steroid therapy, 10 were placed on a ketogenic diet, four received intravenous steroid pulse therapy, and one each was treated with intravenous immunoglobulin and cannabidiol. The most effective treatments were steroid therapy and a ketogenic diet, which were also effective in reducing seizures and improving cognition. Side effects during treatment were transient and treatable. Conclusion: We described the clinical spectrum of pediatric patients with D/EE-SWAS. Steroid therapy and a ketogenic diet can be considered effective therapeutic options for patients with D/EE SWAS.
The multiplex bead array approach to identifying serum biomarkers associated with breast cancer
Kim, Byoung Kwon,Lee, Jong Won,Park, Pil Je,Shin, Yong Sung,Lee, Won Young,Lee, Kyung Ae,Ye, Sena,Hyun, Heesun,Kang, Kyung Nam,Yeo, Donghwa,Kim, Youngdai,Ohn, Sung Yup,Noh, Dong Young,Kim, Chul Woo BioMed Central 2009 Breast cancer research Vol.11 No.2
<P><B>Introduction</B></P><P>Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population.</P><P><B>Methods</B></P><P>Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex™ bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls.</P><P><B>Results</B></P><P>Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity.</P><P><B>Conclusions</B></P><P>The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. Further validation is required before array-based technology is used routinely for early detection of breast cancer.</P>
Advanced Genetic Algorithm Using PSO and Euclidean Data Distance
Donghwa Kim 한국정보기술학회 2005 한국정보기술학회논문지 Vol.3 No.5
When we obtain an optimal solution using GA (Genetic Algorithm), operation such as crossover, reproduction, and mutation procedures is using to generate for the next generations. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent To improve an optimal learning solution of GA, this paper deal with applying PSO (Particle Swarm Optimization) and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.
Kim, Donghwa,Seo, Deokseong,Cho, Suhyoun,Kang, Pilsung Elsevier science 2019 Information sciences Vol.477 No.-
<P><B>Abstract</B></P> <P>The purpose of document classification is to assign the most appropriate label to a specified document. The main challenges in document classification are insufficient label information and unstructured sparse format. A semi-supervised learning (SSL) approach could be an effective solution to the former problem, whereas the consideration of multiple document representation schemes can resolve the latter problem. Co-training is a popular SSL method that attempts to exploit various perspectives in terms of feature subsets for the same example. In this paper, we propose multi-co-training (MCT) for improving the performance of document classification. In order to increase the variety of feature sets for classification, we transform a document using three document representation methods: term frequency–inverse document frequency (TF–IDF) based on the bag-of-words scheme, topic distribution based on latent Dirichlet allocation (LDA), and neural-network-based document embedding known as document to vector (Doc2Vec). The experimental results demonstrate that the proposed MCT is robust to parameter changes and outperforms benchmark methods under various conditions.</P>