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Tuberculosis of the paranasal sinus is a rare disease caused by infection with Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis. Although the worldwide incidence of tuberculosis is declining, the diagnosis of primary paranasal tuberculosis remains challenging and cannot be ruled out in patients presenting with refractory chronic rhinosinusitis after adequate surgical and medical treatment. We experienced a case of paranasal tuberculosis with no evidence of previous tuberculosis infection. It was diagnosed after a surgical biopsy revealed granulomatous inflammation and caseous necrosis. The patient responded well to antituberculosis drug therapy and became free of symptoms after 7 months of treatment. We report our findings in this case with a review of the recent literature. [ABSTRACT FROM AUTHOR]

Background and Hypothesis The brain-predicted age difference (brain-PAD) may serve as a biomarker for neurodegeneration. We investigated the brain-PAD in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging (sMRI). Study Design We employed a convolutional network-based regression (SFCNR), and compared its performance with models based on three machine learning (ML) algorithms. We pretrained the SFCNR with sMRI data of 7590 healthy controls (HCs) selected from the UK Biobank. The parameters of the pretrained model were transferred to the next training phase with a new set of HCs (n  = 541). The brain-PAD was analyzed in independent HCs (n  = 209) and patients (n  = 233). Correlations between the brain-PAD and clinical measures were investigated. Study Results The SFCNR model outperformed three commonly used ML models. Advanced brain aging was observed in patients with SCZ, FE-SSDs, and TRS compared to HCs. A significant difference in brain-PAD was observed between FE-SSDs and TRS with ridge regression but not with the SFCNR model. Chlorpromazine equivalent dose and cognitive function were correlated with the brain-PAD in SCZ and FE-SSDs. Conclusions Our findings indicate that there is advanced brain aging in patients with SCZ and higher brain-PAD in SCZ can be used as a surrogate marker for cognitive dysfunction. These findings warrant further investigations on the causes of advanced brain age in SCZ. In addition, possible psychosocial and pharmacological interventions targeting brain health should be considered in early-stage SCZ patients with advanced brain age. [ABSTRACT FROM AUTHOR]

Earthquakes with magnitudes over 5.0 occurred near Gyeongju and Pohang in southern Korea in 2016 and 2017, respectively. These earthquakes had both low- and high-frequency components. Due to earthquakes with high-frequency motions, damage to nonstructural systems has been observed to be relatively more than that in structural systems. Consequently, the seismic design or performance evaluation of nonstructural components in critical facilities has emerged as a key research area in Korea. This study presents the results of experimental and numerical analyses using a high-fidelity finite element (FE) simulation in the ABAQUS platform for a press-to-connect piping system as a nonstructural component. Press-to-connect piping systems based on NFPA-13 with two elbows, a flexible coupling, and a T-joint were used. In addition, a cyclic loading protocol was applied using the KBC 2016 and IBC 2015. Based on the component-level experimental test, an FE model of the press-to-connect elbow was developed, and the high-fidelity large-scale piping system with an elbow was validated in this study. In both the experimental and analytical results, no leakage or plastic deformation of the piping system was observed under cyclic loading conditions. The results of the high-fidelity simulation model of the large-scale piping system were identical to those of the experimental test. More specifically, the error of the von-Mises stress at the upper and lower elbows was less than 9%, and the angle between the elbows was less than 2%, corresponding to the limit state of the drift ratio of the building system. Therefore, the high-fidelity simulation model of a large-scale piping system can have high application value. In addition, the design requirements and engineering demands of the piping system, such as the condition of ASME B and PV section III for service level D, were satisfied.

Numerical model updating using the data measured from the actual structure is required in order to minimize the error between the initial numerical model and the actual structure. Field load tests, which are conducted in order to assess the condition and safety of high-speed railway bridges, are generally expensive and restricted by railway control and weather conditions. Therefore, a method for evaluating the performance of high-speed railway bridges using updated numerical models without conducting field load tests is required. In this study, numerical model updating was performed by using the data measured from the ambient vibration test in order to assess the dynamic stability of high-speed railway bridges. In the ambient vibration test, the measurement point roaming method was applied in order to accurately measure high-speed railway bridges using a limited number of sensors. For numerical model updating, the univariate search method was used, and several measured parameters were updated and converted into the properties of the target bridges in the numerical models. The vertical and torsional modes of the updated numerical models differed by less than 5% from those estimated using the data measured from the target bridges. The responses of the updated numerical models were found to be similar to those measured from the high-speed railway bridges in operation. It was also shown that the updated numerical models could be used to assess the dynamic stability of the bridges.