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8% of asymptomatic persons by neutralization test and real-time RT-PCR. CONCLUSIONS We conclude that ZIKV infection was increasing among asymptomatic persons in the same area in Myanmar during 2018 compared with 2017. It is highly recommended to strengthen the surveillance system for ZIKV to prevent possible outbreaks. © The Author(s) 2020. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.Abnormal aggregation of pathological tau protein is a neuropathological feature of Alzheimer's disease (AD). In the AD patients, the abnormal tau accumulation first appeared in entorhinal cortex (EC) and then propagated to the hippocampus with microglia activation and inflammation, but the mechanism is elusive. Here, we studied the role and mechanisms underlying periphery inflammation on brain tau transmission. By intraperitoneal injection of lipopolysaccharide (LPS) with brain medial entorhinal cortex (MEC)-specific overexpressing P301L human tau (P301L-hTau), we found that both acute and chronic administration of LPS remarkably promoted P301L-hTau transmission from MEC to the hippocampal subsets. Interestingly, the chronic LPS-induced P301L-hTau transmission was still apparent after blocking microglia activation. Further studies demonstrated that LPS disrupted the integrity of blood-brain barrier (BBB) and simultaneous intraperitoneal administration of glucocorticoid (GC) attenuated LPS-promoted P301L-hTau transmission. These data together suggest that a non-microglia-dependent BBB disruption contributes to peripheral LPS-promoted brain P301L-hTau transmission, therefore, maintaining the integrity of BBB can be a novel strategy for preventing pathological tau propagation in AD and other tauopathies. © 2020 The Author(s).Military service presents unique challenges and opportunities for health care and public health. In the USA, there are over 2 million military servicemembers, 20 million veterans, and millions more military and veteran family members. Military servicemembers and eligible family members, many veterans, and retirees receive health care through the two largest learning health care systems in the USA, managed and delivered through the Departments of Defense (DoD), Veterans Affairs (VA), and contracted health care organizations. Through a network of collaborative relationships, DoD, VA, and partnering health care and research organizations (university, corporate, community, and government) accelerate research translation into best practices and policy across the USA and beyond. APR-246 This article outlines military and veteran health research translation as summarized from a collaborative workshop led by experts across health care research, practice, and administration in DoD, VA, the National Institutes of Health, and affiliated universities. Key themes and recommendations for research translation are outlined in areas of (a) stakeholder engagement and collaboration; (b) implementation science methods; and (c) funding along the translation continuum. Overall, the ability to rapidly translate research into clinical practice and policy for positive health outcomes requires collaborative relationships among many stakeholders. This includes servicemembers, veterans, and their families along with researchers, health care clinicians, and administrators, as well as policymakers and the broader population. © Published by Oxford University Press on behalf of the Society of Behavioral Medicine 2020.This study aimed to examine the efficacy of semantic segmentation implemented by deep learning and to confirm whether this method is more effective than a commercially dominant auto-segmentation tool with regards to delineating normal lung excluding the trachea and main bronchi. A total of 232 non-small-cell lung cancer cases were examined. The computed tomography (CT) images of these cases were converted from Digital Imaging and Communications in Medicine (DICOM) Radiation Therapy (RT) formats to arrays of 32 × 128 × 128 voxels and input into both 2D and 3D U-Net, which are deep learning networks for semantic segmentation. The number of training, validation and test sets were 160, 40 and 32, respectively. Dice similarity coefficients (DSCs) of the test set were evaluated employing Smart SegmentationⓇ Knowledge Based Contouring (Smart segmentation is an atlas-based segmentation tool), as well as the 2D and 3D U-Net. The mean DSCs of the test set were 0.964 [95% confidence interval (CI), 0.960-0.968], 0.990 (95% CI, 0.989-0.992) and 0.990 (95% CI, 0.989-0.991) with Smart segmentation, 2D and 3D U-Net, respectively. Compared with Smart segmentation, both U-Nets presented significantly higher DSCs by the Wilcoxon signed-rank test (P  less then  0.01). There was no difference in mean DSC between the 2D and 3D U-Net systems. The newly-devised 2D and 3D U-Net approaches were found to be more effective than a commercial auto-segmentation tool. Even the relatively shallow 2D U-Net which does not require high-performance computational resources was effective enough for the lung segmentation. Semantic segmentation using deep learning was useful in radiation treatment planning for lung cancers. © The Author(s) 2020. Published by Oxford University Press on behalf of The Japanese Radiation Research Society and Japanese Society for Radiation Oncology.BACKGROUND Polyploidy, or whole-genome duplications (WGDs), repeatedly occurred during green plant evolution. To examine the evolutionary history of green plants in a phylogenomic framework, the 1KP project sequenced >1,000 transcriptomes across the Viridiplantae. The 1KP project provided a unique opportunity to study the distribution and occurrence of WGDs across the green plants. As an accompaniment to the capstone publication, this article provides expanded methodological details, results validation, and descriptions of newly released datasets that will aid researchers who wish to use the extended data generated by the 1KP project. RESULTS In the 1KP capstone analyses, we used a total evidence approach that combined inferences of WGDs from Ks and phylogenomic methods to infer and place 244 putative ancient WGDs across the Viridiplantae. Here, we provide an expanded explanation of our approach by describing our methodology and walk-through examples. We also evaluated the consistency of our WGD inferences by comparing them to evidence from published syntenic analyses of plant genome assemblies.