PURPOSE: There are inconsistencies in the results reported in a small number of previous studies into growth hormone (GH) treatment in Korean children with idiopathic short stature (ISS) and idiopathic growth hormone deficiency (IGHD). Thus, the authors retrospectively compared the effects of GH in ISS and IGHD. METHODS: From the medical records of 26 ISS and 30 IGHD children, auxological and biochemical changes including chronologic age (CA), bone age (BA), height standard deviation score (HT-SDS), predicted adult height (PAH), midparental height (MPH), insulin-like growth factor-1 (IGF-1), and insulin-like growth factor binding protein-3 (IGFBP-3) were compared. RESULTS: Before treatment, IGHD group had younger BA, lower BA/CA ratio, and lower IGF-1 level than those in the ISS group. During GH treatment, the levels of IGF-1 and IGFBP-3 were not different. Although annual BA increment was higher in IGHD group, and annual PAH-SDS increment was higher in ISS group, annual HT-SDS increments were not different. Both HT-SDS and PAH-SDS in the ISS group increased significantly until the end of the second year, and then those were not significantly different from MPH-SDS. In the IGHD group, the HT-SDS showed a significant increase till the end of the second year, and the PAH-SDS was not significantly changed at each year, but both HT-SDS and PAH-SDS were not significantly different from MPH-SDS at the end of the third year. CONCLUSION: During GH treatment, both HT-SDS and PAH-SDS approached the genetic target range of MPH-SDS after 2 years in ISS children and 3 years in IGHD children.
Adult ; Child* ; Growth Hormone* ; Humans ; Insulin-Like Growth Factor Binding Protein 3 ; Insulin-Like Growth Factor I ; Medical Records ; Retrospective Studies

PURPOSE: The prevalence rates of metabolic syndrome (MetS) and percentile distribution of insulin resistance (IR) among Korean children and adolescents were investigated. The cutoff values of IR were calculated to identify high-risk MetS groups. METHODS: Data from 3,313 Korean subjects (1,756 boys and 1,557 girls, aged 10–18 years) were included from the Korean National Health and Nutrition Examination Survey conducted during 2007–2010. Three different sets of criteria for MetS were used. Indirect measures of IR were homeostasis model assessment (HOMA-IR) and triglyceride and glucose (TyG) index. The cutoff values of the HOMA-IR and TyG index were obtained from the receiver operation characteristic curves. RESULTS: According to the MetS criteria of de Ferranti el al., Cook et al., and the International Diabetes Federation, the prevalence rates in males and females were 13.9% and 12.3%, 4.6% and 3.6%, and 1.4% and 1.8%, respectively. Uses these 3 criteria, the cutoff values of the HOMA-IR and TyG index were 2.94 and 8.41, 3.29 and 8.38, and 3.54 and 8.66, respectively. The cutoff values using each of the 3 criteria approximately corresponds to the 50th–75th, 75th, and 75th–90th percentiles of normal HOMA-IR and TyG index levels. CONCLUSION: This study describes the prevalence rates of MetS in Korean children and adolescents, an index of IR, and the cutoff values for MetS with the aim of detecting high-risk groups. The usefulness of these criteria needs to be verified by further evaluation.
Adolescent* ; Child* ; Female ; Glucose ; Homeostasis ; Humans ; Insulin Resistance* ; Insulin* ; Korea ; Male ; Nutrition Surveys ; Prevalence ; Triglycerides

PURPOSE: The prevalence rates of metabolic syndrome (MetS) and percentile distribution of insulin resistance (IR) among Korean children and adolescents were investigated. The cutoff values of IR were calculated to identify high-risk MetS groups. METHODS: Data from 3,313 Korean subjects (1,756 boys and 1,557 girls, aged 10–18 years) were included from the Korean National Health and Nutrition Examination Survey conducted during 2007–2010. Three different sets of criteria for MetS were used. Indirect measures of IR were homeostasis model assessment (HOMA-IR) and triglyceride and glucose (TyG) index. The cutoff values of the HOMA-IR and TyG index were obtained from the receiver operation characteristic curves. RESULTS: According to the MetS criteria of de Ferranti el al., Cook et al., and the International Diabetes Federation, the prevalence rates in males and females were 13.9% and 12.3%, 4.6% and 3.6%, and 1.4% and 1.8%, respectively. Uses these 3 criteria, the cutoff values of the HOMA-IR and TyG index were 2.94 and 8.41, 3.29 and 8.38, and 3.54 and 8.66, respectively. The cutoff values using each of the 3 criteria approximately corresponds to the 50th–75th, 75th, and 75th–90th percentiles of normal HOMA-IR and TyG index levels. CONCLUSION: This study describes the prevalence rates of MetS in Korean children and adolescents, an index of IR, and the cutoff values for MetS with the aim of detecting high-risk groups. The usefulness of these criteria needs to be verified by further evaluation.
Adolescent* ; Child* ; Female ; Glucose ; Homeostasis ; Humans ; Insulin Resistance* ; Insulin* ; Korea ; Male ; Nutrition Surveys ; Prevalence ; Triglycerides

Purpose: Despite enzyme replacement therapy (ERT) and/or allogeneic hematopoietic stem cell transplantation, individuals with mucopolysaccharidosis (MPS) I or II often experience significant growth deficiencies. This study aimed to assess the safety and efficacy of recombinant human growth hormone (hGH) treatment in children diagnosed with MPS I or II. Materials and Methods: A total of nine pediatric patients—four with MPS I and five with MPS II—underwent treatment with ERT and hGH at Samsung Medical Center. Results: The mean hGH dose administered was 0.26±0.03 mg/kg/week. In the MPS I group, three patients showed an increase in height Z-score from –4.09±0.83 to –3.68±0.43 after 1 year of hGH treatment, and to –3.10±0.72 by the end of the hGH regimen. In the MPS II group, while the height Z-score of four patients decreased according to standard growth charts, it improved from 1.61±1.79 to 2.71±1.68 based on the disease-specific growth chart through hGH treatment. Two patients discontinued hGH treatment due to lack of efficacy after 22 and 6 months each of treatment, respectively. No new-onset neurological symptoms or necessity for prosthetic or orthopedic surgery were reported during hGH treatment. Conclusion This study provides insights into the impact of hGH on MPS patients, demonstrating its potential to reverse growth deceleration in some cases. Further research is needed to explore the long-term effects of hGH on changes in body composition, muscle strength, and bone health in this population.

Pleurotus species are commercially essential mushrooms and widely cultivated throughout the world. The production of Pleurotus mushrooms alone accounts for around 25% of that total cultivated mushrooms globally. In America and Europe, Pleurotus species are considered specialty mushrooms, whereas, in Korea, their cultivation is economically profitable, and it is one of the highly consumed species. Pleurotus species are predominantly found in tropical forests and often grow on fallen branches, dead and decaying tree stumps, and wet logs. Biographical studies have shown that the Pleurotus genus is among the more conspicuous fungi that induce wood decay in terrestrial ecosystems worldwide due to its formidable lignin-modifying enzymes, including laccase and versatile peroxidases. Pleurotus species can be grown easily due to their fast colonization nature on diversified agro-substrates and their biological efficiency 100%. Pleurotus mushrooms are rich in proteins, dietary fiber, essential amino acids, carbohydrates, water-soluble vitamins, and minerals. These mushrooms are abundant in functional bioactive molecules, though to influence health. Pleurotus mushrooms are finding unique applications as flavoring, aroma, and excellent preservation quality. Apart from its unique applications, Pleurotus mushrooms have a unique status delicacy with high nutritional and medicinal values. The present review provides an insight into the cultivation of Pleurotus spp. using different agro-waste as growth substances paying attention to their effects on the growth and chemical composition.

Wilson disease (WD) is a relatively common genetic hepatic disease in children and is characterized by excessive copper accumulation, predominantly in the liver and brain. It is an autosomal recessive disease caused by an ATP7B mutation that causes brain degeneration and is potentially fatal if diagnosed late or untreated. In the early phase of WD, its initial presentation may include mild hepatic involvement. WD may be overlooked as a cause of liver disease due to severe obesity but should not be excluded from differential diagnosis. We report a case of WD with severe obesity and fatty liver diagnosed in the early phase by targeted gene panel sequencing and review the endocrine problems associated with WD. Early suspicion of WD is important for good prognosis.

Coffin-Lowry syndrome (CLS, OMIM # 303600) is a rare X-linked disorder caused by mutations in RPS6KA3. CLS is characterized by facial dysmorphism, digit abnormalities, developmental delays, growth retardation, and progressive skeletal changes in male patients. Females with CLS are variably affected, complicating diagnosis. Here, we describe the clinical and molecular findings in a female Korean child with CLS and review the associated literature. A 5-year-old girl presented with short stature and developmental delays. She had a coarse facial appearance characterized by a prominent forehead, hypertelorism, thick lips, and hypodontia. She also had puffy tapering fingers and pectus excavatum. We performed exome sequencing and identified a novel, likely pathogenic, heterozygous variant, c.326_338delinsCTCGAGAC (p.Val109Alafs*10), in RPS6KA3 (NM_004586.2). This is the first Korean female genetically diagnosed with CLS. In contrast to the delayed bone age reported in previous studies, our patient showed advanced bone age and central precocious puberty. CLS should be considered as a differential diagnosis of short stature, tapering fingers, and developmental delay. We suggest that molecular techniques can be a useful tool for diagnosis of rare disorders such as CLS because such conditions are not simple, and the associated spectrum of phenotypes can vary.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.