Calcified amorphous tumors (CATs) of the heart are rare non-neoplastic cardiac masses primarily found in the mitral valve or annulus. However, their exact pathogenesis remains unknown. In this case report, we describe the CT and MRI findings and differentiating features of cardiac a CAT in the left atrium of a 79-year-old female.

Calcified amorphous tumors (CATs) of the heart are rare non-neoplastic cardiac masses primarily found in the mitral valve or annulus. However, their exact pathogenesis remains unknown. In this case report, we describe the CT and MRI findings and differentiating features of cardiac a CAT in the left atrium of a 79-year-old female.

Calcified amorphous tumors (CATs) of the heart are rare non-neoplastic cardiac masses primarily found in the mitral valve or annulus. However, their exact pathogenesis remains unknown. In this case report, we describe the CT and MRI findings and differentiating features of cardiac a CAT in the left atrium of a 79-year-old female.

Background: Despite the extraordinary speed of mass vaccination efforts, an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant in a vaccinee with coronavirus disease 2019 (COVID-19) mRNA vaccine was identified in an adult day service center (ADSC) of Jeju, South Korea. The primary objective of this study was to investigate the epidemiologic features in infection-vulnerable facilities with a high vaccination rate of BNT162b2 mRNA COVID-19 vaccine. The second was to estimate the secondary transmission prevention effect of the vaccine in the household members by vaccination status. Methods: We included all ADSC participants, staff and their household members. All COVID-19 infected cases were confirmed by reverse transcriptase polymerase chain reaction.We calculated attack rate in ADSC and the secondary attack rate (SAR) in household members by vaccination status. Results: Among a total of 42 participants and 16 staff, of which 96.6% were fully vaccinated with BNT162b2 mRNA COVID-19 vaccine, 12 symptomatic cases and 13 asymptomatic confirmed cases of COVID-19 were found. The attack rate was 43.1%, with 13 isolates identified as SARS-CoV-2 virus, delta variant. The SAR in unvaccinated and partially vaccinated household members were 27.8% (5/18) and 25.0% (5/20), respectively, while the SAR in fully vaccinated household members was 12.5% (1/8). Conclusion We describe a SARS-CoV-2 delta variant outbreak in ADSC with high vaccine coverage rate, characterized by high infection rate, high transmissibility, and low clinical severity. The outbreak proceeded to unvaccinated or partially vaccinated household members, emphasizing the need for immunizing close contacts of high-risk groups.

Tamsulosin, an alpha-1 adrenoreceptor antagonist, has been used as a primary option for medical treatment of benign prostate hyperplasia. An open-label, single-dose, randomized, three-treatment, three-period, three sequence crossover study was conducted to evaluate the pharmacokinetics (PKs) of 0.2 and 0.4 mg tamsulosin hydrochloride (HCl) in the fed versus the fasted state. Subjects were randomly assigned to three sequences and received one of the following treatments at each period: tamsulosin HCl 0.2 or 0.4 mg in the fed state with a high-fat meal, or tamsulosin HCl 0.4 mg in the fasted state. Blood samples for the PK analysis were collected at pre-dose and up to 48 h post-dose. The PK parameters were calculated by a non-compartmental method. The geometric mean ratio (GMR) and its 90% confidence intervals (CIs) of the plasma maximum concentration (C max ) and area under concentration curve from time zero to last measurable concentration (AUClast) were calculated. Twenty-two subjects completed the study. The systemic exposure of tamsulosin 0.4 mg decreased approximately 9% in the fed state compared to the fasted state, and the time to reach peak concentration was slightly delayed in the fed state. The dose normalized GMR and its 90% CIs of C max and AUClast for 0.2 and 0.4 mg tamsulosin in the fed state were within 0.8 and 1.25 range. Systemic exposure of tamsulosin was decreased in the fed condition compared to the fasted condition. Linear PK profiles were observed between 0.2 and 0.4 mg tamsulosin in the fed state.

Purpose: This study explored the association between workplace discrimination and violence and depressive symptoms among Korean employees. Methods: Data were obtained from the 4th Korean Working Condition Survey of 2014, which included 21,902 Korean employees. Depressive symptoms were measured using the WHO-5 Well-Being Index questionnaire scales. Results: A statistically significant relationship between workplace discrimination and workplace violence was found, and these two variables were also associated with depressive symptoms. After adjusting for variables such as sociodemographic characteristics, physical risk, and psychosocial working environment, workplace discrimination (OR=1.22, p<.001) and workplace violence (OR=1.69, p<.001) were both significantly associated with depressive symptoms. Conclusion This study indicates that to promote employees’ psychological health, systems and programs to prevent workplace discrimination and violence are needed. Development of these systems and programs should consider employees’ experiences of workplace discrimination and workplace violence, sociodemographic characteristics, physical risk, and psychosocial working environments.

Purpose: This study aimed to identify differences in physical working environments, psychosocial working environments, and health outcomes according to the employment type of delivery workers. Methods: This study was a secondary analysis of data collected from the Fifth Korean Working Conditions Survey (KWCS). Participants were 84 Korean delivery workers. Data were analyzed using the SAS 9.4 Version, x 2 test and Fisher’s exact test. Results: Statistically significant differences were found according to the employment type of delivery workers (special types, wage) including “noise”, “vibrations”, “repetitive movements”, “supervisor support”, “colleague support”, “manuals on emotional expression”, “existence of trade union, works council or similar body”. Conclusion This study suggests the necessity of improving the working environment and health outcomes of delivery workers belonging to special employment types. In developing these, the laws and systems must be reorganized to enable the recognition of delivery workers as wage workers. In addition, delivery companies should be held responsible for managing delivery workers.

Tamsulosin, an alpha-1 adrenoreceptor antagonist, has been used as a primary option for medical treatment of benign prostate hyperplasia. An open-label, single-dose, randomized, three-treatment, three-period, three sequence crossover study was conducted to evaluate the pharmacokinetics (PKs) of 0.2 and 0.4 mg tamsulosin hydrochloride (HCl) in the fed versus the fasted state. Subjects were randomly assigned to three sequences and received one of the following treatments at each period: tamsulosin HCl 0.2 or 0.4 mg in the fed state with a high-fat meal, or tamsulosin HCl 0.4 mg in the fasted state. Blood samples for the PK analysis were collected at pre-dose and up to 48 h post-dose. The PK parameters were calculated by a non-compartmental method. The geometric mean ratio (GMR) and its 90% confidence intervals (CIs) of the plasma maximum concentration (C max ) and area under concentration curve from time zero to last measurable concentration (AUClast) were calculated. Twenty-two subjects completed the study. The systemic exposure of tamsulosin 0.4 mg decreased approximately 9% in the fed state compared to the fasted state, and the time to reach peak concentration was slightly delayed in the fed state. The dose normalized GMR and its 90% CIs of C max and AUClast for 0.2 and 0.4 mg tamsulosin in the fed state were within 0.8 and 1.25 range. Systemic exposure of tamsulosin was decreased in the fed condition compared to the fasted condition. Linear PK profiles were observed between 0.2 and 0.4 mg tamsulosin in the fed state.

PURPOSE: We developed predictive models using different programming languages and different computing platforms for machine learning (ML) and deep learning (DL) that classify clinical diagnoses in patients with epiphora. We evaluated the diagnostic performance of these models.METHODS: Between January 2016 and September 2017, 250 patients with epiphora who underwent dacryocystography (DCG) and lacrimal scintigraphy (LS) were included in the study. We developed five different predictive models using ML tools, Python-based TensorFlow, R, and Microsoft Azure Machine Learning Studio (MAMLS). A total of 27 clinical characteristics and parameters including variables related to epiphora (VE) and variables related to dacryocystography (VDCG) were used as input data. Apart from this, we developed two predictive convolutional neural network (CNN) models for diagnosing LS images. We conducted this study using supervised learning.RESULTS: Among 500 eyes of 250 patients, 59 eyes had anatomical obstruction, 338 eyes had functional obstruction, and the remaining 103 eyes were normal. For the data set that excluded VE and VDCG, the test accuracies in Python-based TensorFlow, R, multiclass logistic regression in MAMLS, multiclass neural network in MAMLS, and nuclear medicine physician were 81.70%, 80.60%, 81.70%, 73.10%, and 80.60%, respectively. The test accuracies of CNN models in three-class classification diagnosis and binary classification diagnosis were 72.00% and 77.42%, respectively.CONCLUSIONS: ML-based predictive models using different programming languages and different computing platforms were useful for classifying clinical diagnoses in patients with epiphora and were similar to a clinician's diagnostic ability.
Classification ; Dataset ; Diagnosis ; Humans ; Lacrimal Apparatus Diseases ; Learning ; Logistic Models ; Machine Learning ; Nuclear Medicine ; Programming Languages ; Radionuclide Imaging

PURPOSE: We developed predictive models using different programming languages and different computing platforms for machine learning (ML) and deep learning (DL) that classify clinical diagnoses in patients with epiphora. We evaluated the diagnostic performance of these models. METHODS: Between January 2016 and September 2017, 250 patients with epiphora who underwent dacryocystography (DCG) and lacrimal scintigraphy (LS) were included in the study. We developed five different predictive models using ML tools, Python-based TensorFlow, R, and Microsoft Azure Machine Learning Studio (MAMLS). A total of 27 clinical characteristics and parameters including variables related to epiphora (VE) and variables related to dacryocystography (VDCG) were used as input data. Apart from this, we developed two predictive convolutional neural network (CNN) models for diagnosing LS images. We conducted this study using supervised learning. RESULTS: Among 500 eyes of 250 patients, 59 eyes had anatomical obstruction, 338 eyes had functional obstruction, and the remaining 103 eyes were normal. For the data set that excluded VE and VDCG, the test accuracies in Python-based TensorFlow, R, multiclass logistic regression in MAMLS, multiclass neural network in MAMLS, and nuclear medicine physician were 81.70%, 80.60%, 81.70%, 73.10%, and 80.60%, respectively. The test accuracies of CNN models in three-class classification diagnosis and binary classification diagnosis were 72.00% and 77.42%, respectively. CONCLUSIONS ML-based predictive models using different programming languages and different computing platforms were useful for classifying clinical diagnoses in patients with epiphora and were similar to a clinician's diagnostic ability.