Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

Background: This study aimed to differentiate video nystagmography (VNG) characteristics, including the video head impulse test (vHIT), in patients with idiopathic rapid eye movement behavior disorder (RBD) from healthy controls, which is considered a precursor to degenerative diseases. Methods: One hundred eighty-five patients underwent overnight polysomnography (PSG) and VNG. Based on overnight PSG, 27 patients with RBD or REM sleep without atonia (RWA) and AHI<15 were categorized into the RBD group, 34 patients with RBD/RWA and AHI≥15 were grouped into the combined group. Sixty patients with AHI≥15 and no RBD/RWA were included in the obstructive sleep apnea (OSA) group, and 64 negative participants were assigned to the control group. In VNG, we measured the gain of vHIT in each canal, with the latency, amplitude, and velocity of horizontal saccades and smooth pursuit. We compared the results between groups using ANOVA, after normalization and adjustment for age and sex. Results: The gain of vHIT in the left horizontal canal was decreased in the RBD group, but it was more pronounced in the OSA group. Elevated gain of the left posterior canal was seen in the RBD group, but technical errors were attributable. The RBD group displayed prolonged latency of saccade on the left side and slowed saccade on the right side, but these were statistically insignificant. Conclusions The VNG study revealed differences between the sleep disorders, potentially reflecting brainstem function in each disorder. However, these differences lacked statistical significance. We anticipate that significant results could be obtained with more controlled conditions.

Background and Objectives: It is well recognized that early detection and intervention are most important for the prevention of neonatal hearing loss. The national support policy in Korea for newborn hearing screening has been changed since October 2018; however, parent awareness of the change still needs to be increased. This study investigated how well parents, who have underwent national infant checkups of their children, were aware of the Korean national policy for neonatal and infant hearing loss in parents.Subjects and Method A survey of neonatal hearing tests and national support policies conducted for 353 parents was analyzed. The survey included questions about parent awareness of the neonatal hearing screening test period, confirmatory test period, national support for these expenses, and hearing aid support. Also evaluated were the necessity of national guidance and management system for neonatal hearing. Results: The test time of neonatal hearing screening was correctly recognized by 82.2% of the parents. The percentage increased after the national insurance coverage started in October 2018 in Korea, and the rate was higher for parents who visited an otolaryngology clinic rather than a pediatric clinic. The test time of the confirmatory test was correctly recognized only by 20.4%. National support policy for neonatal hearing screening tests, confirmatory hearing tests, and hearing aids were acknowledged by 50.7%, 43.1%, and 56.1% of the parents, respectively. Conclusion These results indicate the necessity of efforts to increase the awareness of neonatal hearing tests and relevant support policies in Korea to ultimately achieve early hearing detection and intervention of neonates and infants in Korea.

Nephrectomy is performed for the treatment of kidney cancer or for the purpose of kidney transplantation. Generally, kidney function decreases after nephrectomy. It is well known that the incidence of cardiovascular disease increases and ultimately the mortality rate increases when kidney function decreases. Therefore, when renal mass is detected, partial nephrectomy (PN) is preferred over radical nephrectomy (RN) to preserve kidney function as much as possible. However, recent studies have shown that PN does not have a survival benefit in all patients compared to RN. Meanwhile, numerous studies for living kidney donors showed that kidney donation itself did not increase the risk of diabetes, high blood pressure, cardiovascular disease, and mortality. However, recent studies have shown that kidney donors have higher incidence of cardiovascular disease and higher mortality rates than the general populations. It is yet difficult to find a conclusion in these debates. We have to make a clinical decision rest on the balance of potential benefits and harms of competing treatments, personalized to the individual patient.

The mosquito-borne pathogen Zika virus may result in neurological disorders such as Guillain–Barré syndrome and microcephaly. The virus is classified as a member of the Flaviviridae family and its wide spread in multiple continents is a significant threat to public health. So has created a need to develop animal models to examine the pathogenesis of the disease and develop vaccines. To examine the clinical profile during Zika virus infection, we infected neonatal and adult wild-type mice (C57BL/6 and Balb/c) and compared the clinical signs of African-lineage strain (MR 766) and Asian-lineage strain (PRVABC59, MEX2-81) of Zika virus. Consistent with previous reports, eight-week-old female Balb/c mice infected with these viral strains showed no changes in body weight, survival rate, and no neurologic signs, but demonstrated increases in the weights of spleens and hearts. However, one-day-old neonates showed significantly lower survival rate and body weight with the African-lineage strain than the Asian-lineage strain. These results confirmed the pathogenic differences between Zika virus strains. We also evaluated the clinical responses in neonatal and adult mice of different strains. Our findings suggest that these are useful mouse models for characterization of Zika virus for vaccine development.

To evaluate avian hepatitis E virus (aHEV) as an RNA vaccine platform, open reading frame 2 (ORF2) of aHEV was replaced by heterologous genes, such as enhanced green fluorescent protein (eGFP) and hemagglutinin (HA)-tag, in aHEV infectious cDNA clones. eGFP and HA-tag replicons were expressed in leghorn male hepatoma (LMH) cells. To confirm expression of the heterologous protein, ORF2 was replaced with the antigenic S1 gene of infectious bronchitis virus (IBV). The IBVS1 replicon was expressed in LMH cells. To our knowledge, this is the first investigation showing potential as a RNA vaccine platform using an aHEV. In the future, it may be used in the development of RNA vaccines against various pathogens.

The mosquito-borne pathogen Zika virus may result in neurological disorders such as Guillain–Barré syndrome and microcephaly. The virus is classified as a member of the Flaviviridae family and its wide spread in multiple continents is a significant threat to public health. So has created a need to develop animal models to examine the pathogenesis of the disease and develop vaccines. To examine the clinical profile during Zika virus infection, we infected neonatal and adult wild-type mice (C57BL/6 and Balb/c) and compared the clinical signs of African-lineage strain (MR 766) and Asian-lineage strain (PRVABC59, MEX2-81) of Zika virus. Consistent with previous reports, eight-week-old female Balb/c mice infected with these viral strains showed no changes in body weight, survival rate, and no neurologic signs, but demonstrated increases in the weights of spleens and hearts. However, one-day-old neonates showed significantly lower survival rate and body weight with the African-lineage strain than the Asian-lineage strain. These results confirmed the pathogenic differences between Zika virus strains. We also evaluated the clinical responses in neonatal and adult mice of different strains. Our findings suggest that these are useful mouse models for characterization of Zika virus for vaccine development.

To evaluate avian hepatitis E virus (aHEV) as an RNA vaccine platform, open reading frame 2 (ORF2) of aHEV was replaced by heterologous genes, such as enhanced green fluorescent protein (eGFP) and hemagglutinin (HA)-tag, in aHEV infectious cDNA clones. eGFP and HA-tag replicons were expressed in leghorn male hepatoma (LMH) cells. To confirm expression of the heterologous protein, ORF2 was replaced with the antigenic S1 gene of infectious bronchitis virus (IBV). The IBVS1 replicon was expressed in LMH cells. To our knowledge, this is the first investigation showing potential as a RNA vaccine platform using an aHEV. In the future, it may be used in the development of RNA vaccines against various pathogens.