Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided into five phases: preflight, take off, cruise, landing, and postflight. Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and highest in the landing phase (86 bpm). Landing phase showed the highest values in standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular interpolation of NN interval (195 ms), while the postflight phase had highest root mean square of successive difference (20.5 ms) and proportion of successive RR interval (3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/high-frequency ratio of 5.33. Among the non-linear HRV measures, the landing phase presented the lowest SD1/SD2 ratio (0.15). Conclusion We observed the relative increase of mean HR and change of HRV in the landing phase, indicating elevated sympathetic nervous tone. Further studies should be considered to evaluate specific changes of ECG signals in flight phases and confirm the clinical use of the MATLAB signal analysis tools.

Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided into five phases: preflight, take off, cruise, landing, and postflight. Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and highest in the landing phase (86 bpm). Landing phase showed the highest values in standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular interpolation of NN interval (195 ms), while the postflight phase had highest root mean square of successive difference (20.5 ms) and proportion of successive RR interval (3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/high-frequency ratio of 5.33. Among the non-linear HRV measures, the landing phase presented the lowest SD1/SD2 ratio (0.15). Conclusion We observed the relative increase of mean HR and change of HRV in the landing phase, indicating elevated sympathetic nervous tone. Further studies should be considered to evaluate specific changes of ECG signals in flight phases and confirm the clinical use of the MATLAB signal analysis tools.

Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided into five phases: preflight, take off, cruise, landing, and postflight. Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and highest in the landing phase (86 bpm). Landing phase showed the highest values in standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular interpolation of NN interval (195 ms), while the postflight phase had highest root mean square of successive difference (20.5 ms) and proportion of successive RR interval (3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/high-frequency ratio of 5.33. Among the non-linear HRV measures, the landing phase presented the lowest SD1/SD2 ratio (0.15). Conclusion We observed the relative increase of mean HR and change of HRV in the landing phase, indicating elevated sympathetic nervous tone. Further studies should be considered to evaluate specific changes of ECG signals in flight phases and confirm the clinical use of the MATLAB signal analysis tools.

Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided into five phases: preflight, take off, cruise, landing, and postflight. Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and highest in the landing phase (86 bpm). Landing phase showed the highest values in standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular interpolation of NN interval (195 ms), while the postflight phase had highest root mean square of successive difference (20.5 ms) and proportion of successive RR interval (3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/high-frequency ratio of 5.33. Among the non-linear HRV measures, the landing phase presented the lowest SD1/SD2 ratio (0.15). Conclusion We observed the relative increase of mean HR and change of HRV in the landing phase, indicating elevated sympathetic nervous tone. Further studies should be considered to evaluate specific changes of ECG signals in flight phases and confirm the clinical use of the MATLAB signal analysis tools.

Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided into five phases: preflight, take off, cruise, landing, and postflight. Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and highest in the landing phase (86 bpm). Landing phase showed the highest values in standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular interpolation of NN interval (195 ms), while the postflight phase had highest root mean square of successive difference (20.5 ms) and proportion of successive RR interval (3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/high-frequency ratio of 5.33. Among the non-linear HRV measures, the landing phase presented the lowest SD1/SD2 ratio (0.15). Conclusion We observed the relative increase of mean HR and change of HRV in the landing phase, indicating elevated sympathetic nervous tone. Further studies should be considered to evaluate specific changes of ECG signals in flight phases and confirm the clinical use of the MATLAB signal analysis tools.

A 14-year-old, spayed female, poodle was presented with dysuria and hematuria. A mass that appeared hypoechoic on ultrasound and hypoattenuating on computed tomography (CT) extended from the bladder neck to the urethra. Magnetic resonance imaging (MRI) showed the mass invading the muscular layer of the bladder, urethra, and prostate with distinct margins. Transitional cell carcinoma (TCC) was confirmed with the CADET-BRAF test. This study describes the CT and MRI features of suspected TCC lesions involving the bladder, prostate, and urethra. MRI showed superior soft tissue contrast resolution, enabling evaluation of invasion of the muscular layer of the bladder and urethra.

Objectives: Tic disorders are highly heritable; however, growing evidence suggests that environmental factors play a significant role in their pathogenesis. Studies on these factors have been inconsistent, with conflicting results. Therefore, this study aimed to examine the associations of pre- and perinatal exposure to Tourette syndrome (TS) or chronic tic disorders (CTD) in Korean school-aged children. Methods: This case-control study used data from a large prospective cohort study. The primary outcome was TS/CTD diagnosis according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) criteria and Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version-Korean Version. Demographic, pre-, and perinatal information was obtained from the maternal questionnaires. Data between the TS/CTD and control groups were compared using the chi-squared or Student’s t-test, as appropriate. Two-step logistic regression analyses were used to test the association between TS/CTD and pre- and perinatal risk factors. Results: We included of 223 children (78 with TS/CTD and 145 controls). Significant differences in the demographic data between the two groups were observed. The male sex ratio, mean parental age, parental final education level, and family history of tics were included as confounders. In the final adjusted multivariable model, TS/CTD was significantly associated with antiemetic exposure during pregnancy (odds ratio [OR]=16.61, 95% confidence interval [CI] 1.49–185.22, p=0.02) and medically assisted reproduction (OR=7.89, 95% CI 2.28–27.28, p=0.01). Conclusion Antiemetic exposure and medically assisted reproduction are significantly associated with the risk of TS/CTD. These results should be replicated in future prospective and gene-by-environment studies.

Background: Inflammasomes are key in the initiation of inflammatory responses and serve to de-fend the organism. However, when the immune system is imbalanced, these complexes contribute to tumor progression. The purpose of this study was to investigate the effect of non-canonical inflammasomes on glioma malignancy. Methods: We performed bioinformatics analysis to confirm the expression of canonical andnon-canonical inflammasome-related molecules according to the degree of malignancy through immunohistochemical examination of glioma tissues obtained with patient consent from our institution. Results: Bioinformatics analysis confirmed that the expression levels of non-canonical inflam-masome-related molecules were significantly higher in tumor tissues than in normal tissues, and they also increased according to malignancy, which adversely affected the survival rate. Furthermore, in gliomas, positive correlations were found between N-form gasdermin-D, a key molecule associated with the non-canonical inflammasome, and other related molecules, including NLRP3, caspase-1, caspase-4, and caspase-5. These results were verified by immunohistochemical examination of glioma tissues, and the expression levels of these molecules also increased significantly with increasing grade.In addition, the features of pyroptosis were confirmed. Conclusion This study identified the potential of non-canonical inflammasomes as aggressiveness markers for gliomas and presented a perspective for improving glioma treatment.

Red ginseng (RG) exerts anti-inflammatory, anti-proliferative, and immunomodulatory effects on endometriosis through the regulation of microRNA (miRNA) expression. It may also ameliorate endometriosis by affecting the expression of multiple miRNAs simultaneously, rather than acting on a single miRNA at a given time. Since studies on the overall effects of RG on endometriosis via the regulation of miRNA expression are lacking, the current study aimed to explore the global effect of RG on miRNA expression in a mouse model of endometriosis. Methods: To establish the mouse model, the uterine horn of donor mice was implanted into the lateral side of the recipients’ peritoneum, followed by vehicle or RG treatment for 8 weeks. Results: To confirm the effects of RG on the established mouse model, the size of the implanted uterus was measured; it was found to be lower in mice from the RG group than in mice from the control group. miRNA expression profiles in the implanted uterus of the mouse model of endometriosis after vehicle or RG administration were analyzed using microarray technology. Thereafter, seven candidate miRNAs and 125 candidate genes (miRNA targets) were identified through a bioinformatics analysis. Conclusion: The present findings suggest that RG regulates the expression of multiple miRNAs and mRNAs, thereby alleviating endometriosis in a mouse model of the disease.

Identifying the patterns of gene expression in breast cancers is essential to understanding their pathophysiology and developing anticancer drugs. Breast cancer is a heterogeneous disease with different subtypes determined by distinct biological features. Luminal breast cancer is characterized by a relatively high expression of estrogen receptor (ER) and progesterone receptor (PR) genes, which are expressed in breast luminal cells. In ~25% of invasive breast cancers, human epidermal growth factor receptor 2 (HER2) is overexpressed; these cancers are categorized as the HER2 type. Triple-negative breast cancer (TNBC), in which the cancer cells do not express ER/PR or HER2, shows highly aggressive clinical outcomes. TNBC can be further classified into specific subtypes according to genomic mutations and cancer immunogenicity. Herein, we discuss the brief history of TNBC classification and its implications for promising treatments.