Flight Planning in the Cloud

This new interface will enable Principal Investigators (PIs), as well as UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) members to do their own flight planning and time estimation without having to request flight lines through the science coordinator. It uses an all-in-one Google Maps interface, a JPL hosted database, and PI flight requirements to design an airborne flight plan. The application will enable users to see their own flight plan being constructed interactively through a map interface, and then the flight planning software will generate all the files necessary for the flight. Afterward, the UAVSAR team can then complete the flight request, including calendaring and supplying requisite flight request files in the expected format for processing by NASA s airborne science program. Some of the main features of the interface include drawing flight lines on the map, nudging them, adding them to the current flight plan, and reordering them. The user can also search and select takeoff, landing, and intermediate airports. As the flight plan is constructed, all of its components are constantly being saved to the database, and the estimated flight times are updated. Another feature is the ability to import flight lines from previously saved flight plans. One of the main motivations was to make this Web application as simple and intuitive as possible, while also being dynamic and robust. This Web application can easily be extended to support other airborne instruments

A Socio-Ecological Assessment of the Potential for Vegetable Gardens in Elementary Schools Across an Urban Tropical Watershed in Puerto Rico

School vegetable gardens provide environmental services and social benefits that can have a wide impact in communities and cities, while preparing future generations for more sustainable ways of living. For a school to create and sustain a vegetable garden, both social and physical environment (soils) must be favorable. We evaluated 20 elementary schools in the Rio Piedras watershed of San Juan, Puerto Rico. At these schools, we surveyed school principals to identify social factors that are considered opportunities and constraints to establishing and sustaining a school garden. We also described the physical and chemical properties of the soils from the most suitable locations for vegetable gardens in the schoolyards. For social factors, some schools had discontinued gardening because of dwindling funding, waning interest of teachers and parents. Through in-person interviews, principals identified factors that help in implementing and sustaining long-term vegetable gardens: engagement of stakeholders, sponsorship, gardening skills and logistics, and curriculum integration. For ecological factors, the destruction of crops by exotic iguanas was also a reason that stopped school garden activities in some cases. Generally, school soils were highly disturbed, with high bulk density and low nutrient availability. The soils will require considerable remediation and management to sustain vegetable gardens in Rio Piedras schools. A social-ecological approach like that used here could be used to evaluate school gardens at other jurisdictions to increase the likelihood of success of gardening activities

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Fil: Dincer, Aylin. Washington University in St. Louis; Estados UnidosFil: Gordon, Brian A.. Washington University in St. Louis; Estados UnidosFil: Hari-Raj, Amrita. Ohio State University; Estados UnidosFil: Keefe, Sarah J.. Washington University in St. Louis; Estados UnidosFil: Flores, Shaney. Washington University in St. Louis; Estados UnidosFil: McKay, Nicole S.. Washington University in St. Louis; Estados UnidosFil: Paulick, Angela M.. Washington University in St. Louis; Estados UnidosFil: Shady Lewis, Kristine E.. University of Kentucky; Estados UnidosFil: Feldman, Rebecca L.. Washington University in St. Louis; Estados UnidosFil: Hornbeck, Russ C.. Washington University in St. Louis; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Ances, Beau M.. Washington University in St. Louis; Estados UnidosFil: Berman, Sarah B.. University of Pittsburgh; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Brooks, William S.. Neuroscience Research Australia; Australia. University of New South Wales; AustraliaFil: Cash, David M.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Farlow, Martin R.. Indiana University; Estados UnidosFil: Fougère, Christian la. German Center for Neurodegenerative Diseases; Alemania. University Hospital of Tübingen; AlemaniaFil: Fox, Nick C.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Fulham, Michael J.. Royal Prince Alfred Hospital; Australia. University of Sydney; AustraliaFil: Jack, Clifford R.. Mayo Clinic; Estados UnidosFil: Joseph-Mathurin, Nelly. Washington University in St. Louis; Estados UnidosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Lee, Athene. University Brown; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; Alemania. Munich Cluster for Systems Neurology; AlemaniaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: McDade, Eric M.. Washington University in St. Louis; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Perrin, Richard J.. Washington University in St. Louis; Estados Unido

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual\u27s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of \u27sporadic\u27 AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers

Two-dose ChAdOx1 nCoV-19 vaccine protection against COVID-19 hospital admissions and deaths over time : a retrospective, population-based cohort study in Scotland and Brazil

Funding Information: This study is part of the EAVE II project. EAVE II is funded by the MRC (MC_PC_19075) with the support of BREATHE—The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). Additional support has been provided through Public Health Scotland and Scottish Government Director General Health and Social Care. The original EAVE project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme (11/46/23). The views expressed are those of the authors and not necessarily those of the NIHR, the Department of Health and Social Care, or the UK government. The Brazilian component is part of the Fiocruz VigiVac project on continuous digital evaluation of the national anti-COVID-19 immunisation programme. SVK and SA acknowledge funding from an NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). This partnership between Brazil and Scotland was established through funding from the NIHR (GHRG /16/137/99) using UK aid from the UK Government to support global health research. This study was partially supported by a donation from the Fazer o Bem Faz Bem programme. The authors thank DATASUS for its excellent work in providing unidentified databases. GLW, MLB, and MB-N are research fellows from the Brazilian National Research Council. GLW acknowledges funding from FAPERJ (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; E-26/210.180/2020). We thank Dave Kelly from Albasoft (Inverness, UK) for his support with making primary care data available; Wendy Inglis-Humphrey, Vicky Hammersley, and Laura Brook (University of Edinburgh, Edinburgh, UK); and Pam McVeigh, Amanda Burridge, and Afshin Dastafshan (Public Health Scotland, Glasgow, UK) for their support with project management and administration. Funding Information: SVK is a member of the UK Government's Scientific Advisory Group on Emergencies subgroup on ethnicity, the Cabinet Office's International Best Practice Advisory Group, and was co-chair of the Scottish Government's Expert Reference Group on Ethnicity and COVID-19. CR reports grants from the Medical Research Council (MRC) and Public Health Scotland, during the conduct of the study, and is a member of the Scottish Government Chief Medical Officer's COVID-19 Advisory Group, Scientific Pandemic Influenza Group on Modelling, and Medicines and Healthcare products Regulatory Agency Vaccine Benefit and Risk Working Group. AS is a member of the Scottish Government Chief Medical Officer's COVID-19 Advisory Group and its Standing Committee on Pandemics; he is also a member of the UK Government's New and Emerging Respiratory Virus Threats Risk Stratification Subgroup and a member of AstraZeneca's Thrombotic Thrombocytopenic Taskforce. All roles are unremunerated. VdAO, VB, MLB, and MB-N are employees of Fiocruz, a federal public institution, which manufactures Vaxzevria in Brazil, through a full technology transfer agreement with AstraZeneca. Fiocruz allocates all its manufactured products to the Ministry of Health for the public health service use. All other authors declare no competing interests. Funding Information: This study is part of the EAVE II project. EAVE II is funded by the MRC (MC_PC_19075) with the support of BREATHE?The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). Additional support has been provided through Public Health Scotland and Scottish Government Director General Health and Social Care. The original EAVE project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme (11/46/23). The views expressed are those of the authors and not necessarily those of the NIHR, the Department of Health and Social Care, or the UK government. The Brazilian component is part of the Fiocruz VigiVac project on continuous digital evaluation of the national anti-COVID-19 immunisation programme. SVK and SA acknowledge funding from an NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). This partnership between Brazil and Scotland was established through funding from the NIHR (GHRG /16/137/99) using UK aid from the UK Government to support global health research. This study was partially supported by a donation from the Fazer o Bem Faz Bem programme. The authors thank DATASUS for its excellent work in providing unidentified databases. GLW, MLB, and MB-N are research fellows from the Brazilian National Research Council. GLW acknowledges funding from FAPERJ (Funda??o Carlos Chagas Filho de Amparo ? Pesquisa do Estado do Rio de Janeiro; E-26/210.180/2020). We thank Dave Kelly from Albasoft (Inverness, UK) for his support with making primary care data available; Wendy Inglis-Humphrey, Vicky Hammersley, and Laura Brook (University of Edinburgh, Edinburgh, UK); and Pam McVeigh, Amanda Burridge, and Afshin Dastafshan (Public Health Scotland, Glasgow, UK) for their support with project management and administration. Publisher Copyright: © 2022 The author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licensePeer reviewedPublisher PD

In vitro and in vivo modeling of lipid bioaccessibility and digestion from almond muffins: the importance of the cell-wall barrier mechanism

This study compares in vitro and in vivo models of lipid digestion from almond particles within a complex food matrix (muffins) investigating whether the cell-wall barrier regulates the bioaccessibility of nutrients within this matrix. Muffins containing small (AF) or large (AP) particles of almond were digested in triplicate using an in vitro dynamic gastric model (DGM, 1 h) followed by a static duodenal digestion (8 h). AF muffins had 97.1 ± 1.7% of their lipid digested, whereas AP muffins had 57.6 ± 1.1% digested. In vivo digestion of these muffins by an ileostomy volunteer (0–10 h) gave similar results with 96.5% and 56.5% lipid digested, respectively. The AF muffins produced a higher postprandial triacylglycerol iAUC response (by 61%) than the AP muffins. Microstructural analysis showed that some lipid remained encapsulated within the plant tissue throughout digestion. The cell-wall barrier mechanism is the main factor in regulating lipid bioaccessibility from almond particles

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin