PURPOSE: Indoor risk factors for allergic diseases in low-income households in Korea have been characterized only partially. We evaluated the prevalences of atopic dermatitis, asthma, and allergic rhinitis in Seoul, Korea, to identify key housing and behavioral risk factors of low-income households. METHODS: Statistical analysis of the prevalence of these diseases and various risk factors was conducted using data from a 2010 Ministry of Environment household survey. Logistic regression models were generated using data from 511 low-income household apartments in districts of Seoul. RESULTS: In general, housing factors such as renovation history (P<0.1) and crowding status (P<0.01) were associated with allergic rhinitis, whereas behavioral factors such as frequency of indoor ventilation (P<0.05) and cleaning (P<0.1) were inversely correlated with atopic dermatitis. Indoor smoking was a major trigger of asthma and atopic dermatitis in low-income households (P<0.05). The presence of mold and water leakage in houses were the most important risk factors for all three diseases (P<0.05). CONCLUSIONS: Various risk factors play a role in triggering allergic diseases among low-income households in Seoul, and health or environmental programs mitigating allergic diseases should be tailored to address appropriate housing or behavioral factors in target populations.
Asthma ; Crowding ; Dermatitis, Atopic ; Family Characteristics* ; Fungi ; Health Services Needs and Demand ; Housing ; Korea ; Logistic Models ; Poverty ; Prevalence* ; Rhinitis ; Risk Factors* ; Seoul ; Smoke ; Smoking ; Ventilation ; Water

PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.
Air Pollution ; Asthma ; Dermatitis ; Dermatitis, Atopic ; Education ; Environmental Policy* ; Epidemiologic Studies ; Humans ; Inpatients ; Korea ; Outpatients ; Particulate Matter ; Poverty ; Public Health ; Rhinitis ; Risk Factors ; Seoul* ; Socioeconomic Factors ; Spatial Analysis

Adenoid cystic carcinoma is a relatively rare tumor that usually arises in the parotid and submandibular salivary glands. The initial management is surgical, and this is often combined with post-operative radiotherapy, but local relapse is common and distant metastasis is not infrequent. We experienced the case of a 59 years old male who had been previously operated on for a primary submandibular salivary cyst, and he then had a distant pulmonary metastasis 9 years later. We operated on him with performing a wedge resection on the left lower lobe for the metastatic lesion, and he hasn't had any evidence of tumor recurrence for 84 months after the second operation.
Adenoids ; Carcinoma, Adenoid Cystic ; Humans ; Male ; Neoplasm Metastasis ; Recurrence ; Salivary Glands

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by selective death of motor neurons in the central nervous system. The main cause of the disease remains elusive, but several mutations have been associated with the disease process. In particular, mutant superoxide dismutase 1 (SOD1) protein causes oxidative stress by activating glia cells and contributes to motor neuron degeneration. KCHO-1, a novel herbal combination compound, contains 30% ethanol and the extracts of nine herbs that have been commonly used in traditional medicine to prevent fatigue or inflammation. In this study, we investigated whether KCHO-1 administration could reduce oxidative stress in an ALS model. KCHO-1 administered to ALS model mice improved motor function and delayed disease onset. Furthermore, KCHO-1 administration reduced oxidative stress through gp91(phox) and the MAPK pathway in both classically activated microglia and the spinal cord of hSOD1(G93A) transgenic mice. The results suggest that KCHO-1 can function as an effective therapeutic agent for ALS by reducing oxidative stress.
Amyotrophic Lateral Sclerosis* ; Animals* ; Central Nervous System ; Ethanol ; Fatigue ; Inflammation ; Medicine, Traditional ; Mice ; Mice, Transgenic ; Microglia ; Models, Animal* ; Motor Neurons ; Neurodegenerative Diseases ; Neuroglia ; Oxidative Stress* ; Spinal Cord ; Superoxide Dismutase

PURPOSE: Recent data indicate that sensitization to mold contributes to the severity and persistence of asthma. In this study, we investigated the relationships between sensitization to mold and lung function parameters in children with asthma. METHODS: We retrospectively reviewed clinical data from 551 asthmatic subjects. We selected subjects who met clinical diagnostic criteria of asthma. Their spirometry, methacholine challenge tests, and measurements of blood eosinophils, serum IgE, eosinophil cationic protein (ECP) and fractional exhaled nitric oxide (FeNO) results were included. Skin prick testing (SPT) results with 13 common aeroallergens in Korea including house dust mites, animal dander, pollen, cockroach and mold were reviewed. Subjects were divided into 3 groups according to their SPT results. Subjects who showed no positive result to any aeroallergen were designated as group 1 (non-sensitized). Group 2 represented subjects who were sensitized to aeroallergens other than mold (other allergen-sensitized) and group 3 included subjects who were sensitized to mold allergens (mold-sensitized). RESULTS: Among the 551 asthmatic subjects, 67 (12.2%) were sensitized to mold and 366 (66.4%) were sensitized to other aeroallergens. The log mean IgE levels were higher in groups 2 (5.96±1.14 IU/mL) and 3 (5.81±0.97 IU/mL) compared to group 1 (3.88±1.68 IU/mL). Blood eosinophils, ECP and FeNO concentrations were significantly higher in groups 2 and 3, but no significant difference was found between the 2 groups. The mean FEV1 value was significantly lower in group 3 (86.9±12.1%pred) than in groups 2 (92.0±14.8%pred) and 1 (93.4±15.4%pred). The log mean methacholine PC20 was significantly lower in group 3 (0.08±1.91 mg/mL) than in groups 2 (1.31±1.69 mg/mL) and 1 (2.29±1.66 mg/mL). CONCLUSIONS: We observed a differential association between mold and other aeroallergen sensitization, and severity of asthma. Sensitization to mold is associated with lower lung function and increased airway hyper-responsiveness in children with asthma. Mold sensitization could be an important factor determining asthma severity particularly airflow limitation in children.
Allergens ; Animals ; Asthma* ; Child* ; Cockroaches ; Dander ; Eosinophil Cationic Protein ; Eosinophils ; Fungi* ; Humans ; Immunoglobulin E ; Korea ; Lung ; Methacholine Chloride ; Nitric Oxide ; Pollen ; Pyroglyphidae ; Respiratory Hypersensitivity ; Retrospective Studies ; Skin ; Spirometry

The purpose of this study was to measure bone age using an artificial intelligence program based on the Greulich-Pyle (GP) method to find out the bone age corresponding to each stage of cervical vertebral maturation (CVM) and the middle phalanx of the third finger (MP3). This study was conducted on 3,118 patients who visited pediatric dentistry at Kyung Hee University Dental Hospital and Pusan National University Dental Hospital from 2013 to 2021. The CVM stage was divided into 5 stages according to the classification by Baccetti, and the MP3 stage was divided into 5 stages according to the methods of Hägg and Taranger. Based on the GP method, bone age was evaluated using an artificial intelligence program. The pubertal growth spurt in the CVM stage was CVM II and III. The mean bone age in CVM II was 11.00 ± 1.81 years for males and 10.00 ± 1.49 years for females, and in CVM III, 13.00 ± 1.46 years for males and 12.00 ± 1.44 years for females (p < 0.0001). The pubertal growth spurt in the MP3 stage was MP3 - G stage. The bone age at the MP3 - G stage was 13.14 ± 1.07 years for males and 11.40 ± 1.09 years for females (p < 0.0001). Bone age evaluation using artificial intelligence is worth using in clinical practice, and it is expected that a faster and more accurate diagnosis will be possible.

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

Purpose: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of sentinel lymph nodes by a pathologist is not easy and is a tedious and time-consuming task. The purpose of this study is to review a challenge competition (HeLP 2018) to develop automated solutions for the classification of metastases in hematoxylin and eosin–stained frozen tissue sections of SLNs in breast cancer patients. Materials and Methods: A total of 297 digital slides were obtained from frozen SLN sections, which include post–neoadjuvant cases (n = 144, 48.5%) in Asan Medical Center, South Korea. The slides were divided into training, development, and validation sets. All of the imaging datasets have been manually segmented by expert pathologists. A total of 10 participants were allowed to use the Kakao challenge platform for six weeks with two P40 GPUs. The algorithms were assessed in terms of the AUC (area under receiver operating characteristic curve). Results: The top three teams showed 0.986, 0.985, and 0.945 AUCs for the development set and 0.805, 0.776, and 0.765 AUCs for the validation set. Micrometastatic tumors, neoadjuvant systemic therapy, invasive lobular carcinoma, and histologic grade 3 were associated with lower diagnostic accuracy. Conclusion In a challenge competition, accurate deep learning algorithms have been developed, which can be helpful in making frozen diagnosis of intraoperative sentinel lymph node biopsy. Whether this approach has clinical utility will require evaluation in a clinical setting