No abstract available.
Neuromyelitis Optica* ; Pruritus* ; Recurrence*

Recently, neuromelanin and nigrosome imaging techniques have been developed to evaluate the substantia nigra in Parkinson’s disease. Previous studies have shown potential benefits of quantitative analysis of neuromelanin and nigrosome images in the substantia nigra, although visual assessments have been performed to evaluate structures in most studies. In this study, we investigate the potential of using deep learning based automatic region segmentation techniques for quantitative analysis of the substantia nigra. The deep convolutional neural network was trained to automatically segment substantia nigra regions on 3D nigrosome and neuromelanin sensitive MR images obtained from 30 subjects. With a 5-fold cross-validation, the mean calculated dice similarity coefficient between manual and deep learning was 0.70 ± 0.11. Although calculated dice similarity coefficients were relatively low due to empirically drawn margins, selected slices were overlapped for more than two slices of all subjects. Our results demonstrate that deep convolutional neural network-based method could provide reliable localization of substantia nigra regions on neuromelanin and nigrosome sensitive MR images.

Recently, neuromelanin and nigrosome imaging techniques have been developed to evaluate the substantia nigra in Parkinson’s disease. Previous studies have shown potential benefits of quantitative analysis of neuromelanin and nigrosome images in the substantia nigra, although visual assessments have been performed to evaluate structures in most studies. In this study, we investigate the potential of using deep learning based automatic region segmentation techniques for quantitative analysis of the substantia nigra. The deep convolutional neural network was trained to automatically segment substantia nigra regions on 3D nigrosome and neuromelanin sensitive MR images obtained from 30 subjects. With a 5-fold cross-validation, the mean calculated dice similarity coefficient between manual and deep learning was 0.70 ± 0.11. Although calculated dice similarity coefficients were relatively low due to empirically drawn margins, selected slices were overlapped for more than two slices of all subjects. Our results demonstrate that deep convolutional neural network-based method could provide reliable localization of substantia nigra regions on neuromelanin and nigrosome sensitive MR images.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Comprehensive chemical analysis of extracts and fractions of marine actinomycete strains led to the discovery of a new minor secondary metabolite, salternamide E (1), from a saltern-derived halophilic Streptomyces strain. The planar structure of salternamide E (1) was elucidated by a combinational analysis of spectroscopic data including NMR, MS, UV, and IR. The absolute configuration of salternamide E (1) was determined by circular dichroism spectroscopic analysis. Salternamide E displayed weak cytotoxicity against various human carcinoma cell lines.
Cell Line ; Circular Dichroism ; Humans ; Streptomyces*

Background: Topical corticosteroids (TCs) are available both as over-the-counter drugs and prescription medicines at pharmacies.Although they are generally safe drugs, inappropriate and excessive use could result in potential side effects. Thus, it is important to have appropriate knowledge regarding the use of TCs. We performed a cross-sectional survey to assess public knowledge and the potential misuse or overuse of TCs. Methods: A cross-sectional and nationwide online survey was conducted among participants who were aware of TCs. The survey items included sources of information, indications, potential side effects, and methods of application of TCs. A comparative analysis was conducted between those with (TC users) and without (TC non-users) an experience of using TCs. Results: Among 3,000 participants, 74.4% were TC users. The mass media was the most common information source of TCs, and only one-third of the surveyed people relied on pharmacists or doctors for information. Regarding indications and application methods, incorrect answer rate was high in some items, but respondents showed adequate knowledge. However, awareness of the safety of TCs was low. Overall, the TC users showed a higher knowledge of TCs than TC non-users. Conclusions Public knowledge of the use of TCs appears to be appropriate. However, we found potential misuse or overuse of some items and a lack of awareness of the side effects concerning TCs. Thus, healthcare professionals’ significant role is required.