Altered cerebrovascular response to acute exercise in patients with Huntington’s Disease

Objective. To determine whether a single session of exercise is sufficient to induce cerebral adaptations in individuals with Huntington’s disease, and explore the time dynamics of any acute cerebrovascular response. Methods. In this case-control study we employed arterial-spin labelling magnetic resonance imaging in 19 HD gene-positive participants (32-65 years old, 13 males) and 19 controls (29-63 years old, 10 males) matched for age, gender, body mass index and self-reported activity levels, to measure global and regional perfusion in response to 20-minutes of moderate intensity cycling. Cerebral perfusion was measured at baseline and 15-, 40- and 60-minutes after exercise cessation. Results. Relative to baseline, cerebral perfusion increased in HD patients yet was unchanged in control participants in the precentral gyrus, middle frontal gyrus and hippocampus 40 minutes after exercise cessation (+15 to +32.5% change in HD participants, -7.7 to 0.8% change in controls). CAG repeat length predicted the change in the precentral gyrus, and the intensity of the exercise intervention predicted hippocampal perfusion change in HD participants. In both groups, exercise increased hippocampal blood flow 60-minutes after exercise cessation. Conclusions. Here we demonstrate the utility of acute exercise as a clinically sensitive experimental paradigm to modulate the cerebrovasculature. Twenty minutes of aerobic exercise induced transient cerebrovascular adaptations in the hippocampus and cortex selectively in HD participants and likely represents latent neuropathology not evident at rest

Automatic Radiometric Normalization of Multitemporal Satellite Imagery

The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat TM images over Nevada, Landsat ETM+ images over Morocco, and SPOT HRV images over Kenya. Results from this new automatic, combined MAD/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features. (C) 2004 Elsevier Inc. All rights reserved

Annual Forest Monitoring as part of Indonesia's National Carbon Accounting System

Land use and forest change, in particular deforestation, have contributed the largest proportion of Indonesia’s estimated greenhouse gas emissions. Indonesia’s remaining forests store globally significant carbon stocks, as well as biodiversity values. In 2010, the Government of Indonesia entered into a REDD+ partnership. A spatially detailed monitoring and reporting system for forest change which is national and operating in Indonesia is required for participation in such programs, as well as for national policy reasons including Monitoring, Reporting, and Verification (MRV), carbon accounting, and land-use and policy information. Indonesia’s National Carbon Accounting System (INCAS) has been designed to meet national and international policy requirements. The INCAS remote sensing program is producing spatially-detailed annual wall-to-wall monitoring of forest cover changes from time-series Landsat imagery for the whole of Indonesia from 2000 to the present day. Work on the program commenced in 2009, under the Indonesia-Australia Forest Carbon Partnership. A principal objective was to build an operational system in Indonesia through transfer of knowledge and experience, from Australia’s National Carbon Accounting System, and adaptation of this experience to Indonesia’s requirements and conditions. A semi-automated system of image pre-processing (ortho-rectification, calibration, cloud masking and mosaicing) and forest extent and change mapping (supervised classification of a ‘base’ year, semi-automated single-year classifications and classification within a multi-temporal probabilistic framework) was developed for Landsat 5 TM and Landsat 7 ETM+. Particular attention is paid to the accuracy of each step in the processing. With the advent of Landsat 8 data and parallel development of processing capability, capacity and international collaborations within the LAPAN Data Centre this processing is being increasingly automated. Research is continuing into improved processing methodology and integration of information from other data sources. This paper presents technical elements of the INCAS remote sensing program and some results of the 2000 – 2012 mapping

Oriented attachment of VNAR proteins, Q2 via site-selective modification, on PLGA–PEG nanoparticles enhances nanoconjugate performance

This work was partially funded through a US-Ireland R&D Partnership grant (STL/5010/14, MRC grant MC_PC_15013). JCFN is funded by the EU’s Horizon 2020 programme under Marie-Curie grant agreement 675007. We acknowledge UCL Chemistry Mass Spectrometry Facility (Dr K. Karu/Dr X. Yang).Peer reviewedPublisher PDFsupplementary_dat

Hippocampal blood flow is increased after 20 min of moderate-intensity exercise

Long-term exercise interventions have been shown to be a potent trigger for both neurogenesis and vascular plasticity. However, little is known about the underlying temporal dynamics and specifically when exercise-induced vascular adaptations first occur, which is vital for therapeutic applications. In this study, we investigated whether a single session of moderate-intensity exercise was sufficient to induce changes in the cerebral vasculature. We employed arterial spin labeling magnetic resonance imaging to measure global and regional cerebral blood flow (CBF) before and after 20 min of cycling. The blood vessels’ ability to dilate, measured by cerebrovascular reactivity (CVR) to CO2 inhalation, was measured at baseline and 25-min postexercise. Our data showed that CBF was selectively increased by 10–12% in the hippocampus 15, 40, and 60 min after exercise cessation, whereas CVR to CO2 was unchanged in all regions. The absence of a corresponding change in hippocampal CVR suggests that the immediate and transient hippocampal adaptations observed after exercise are not driven by a mechanical vascular change and more likely represents an adaptive metabolic change, providing a framework for exploring the therapeutic potential of exercise-induced plasticity (neural, vascular, or both) in clinical and aged populations

The Land Monitor Project

The Land Monitor Project is providing information over the southwest agricultural region of WA. It is assembling and processing sequences of Landsat TM data, a new highresolution digital elevation model (DEM) and other spatial data to provide monitoring information on the area of salt-affected land, and on changes in the area and status of perennial vegetation over the period 1988-2000. Land Monitor is a multi-agency project of the Western Australian Salinity Action Plan supported by the Natural Heritage Trust. The Project will also providing estimates of areas at risk from secondary or future salinisation, based on the historical salinity maps and a set of landform variables derived from the high resolution DEM. Sequences of calibrated Landsat Thematic Mapper satellite images integrated with landform information derived from height data, ground truthing and other existing mapped data are used as the basis for monitoring changes in salinity and woody vegetation. Procedures for accurate registration and calibration were developed by CSIRO Mathematical and Information Sciences (CMIS), as were the data integration procedures for salinity mapping and prediction. For the DEM, heights are derived on a 10m grid from stereo aerial photography flown at 1:40,000 scale, using soft-copy automatic terrain extraction (image correlation) techniques. Land Monitor products include: high resolution DEMs; calibrated sequences of Landsat imgery; present and historical salinity maps; predicted salinity maps; maps of change in vegetation status and spectral/temporal statistics. These products are available in a range of formats and scales, from paddock to catchment and shire scales to suit customer needs

A multi-agency project of the Western Australian Salinity Action Plan supported by the Natural Heritage Trust

Land Monitor is a multi-agency project of the Western Australian Salinity Action Plan supported by the Natural Heritage Trust. It will provide land managers and administrators with baseline salinity and vegetation data for monitoring changes over time, and land height data from which contours accurate to two metre intervals can be produced. The Project will also provide estimates of areas at risk from secondary or future salinisation. Land Monitor will cover the 18 million hectares of agricultural area of south-west, Western Australia. Sequences of calibrated Landsat Thematic Mapper satellite images integrated with landform information derived from height data, ground truthing and other existing mapped data sets are used as the basis for monitoring changes in salinity and woody vegetation. Heights are derived on a 10m grid from stereo aerial photography flown at 1:40,000 scale, using soft-copy automatic terrain extraction (image correlation) techniques. Proposed Land Monitor products include salinity maps, predicted salinity maps, enhanced imagery, vegetation status maps and spectral / temporal statistics. These products will be available in a range of formats and scales, from paddock, farm to catchment and shire scales to suit customer needs

Oriented attachment of VNAR proteins, via site-selective modification, on PLGA-PEG nanoparticles enhances nanoconjugate performance

Herein we report the construction of a nanoparticle-based drug delivery system which targets a key regulator in tumour angiogenesis. We exploit a Variable New Antigen Receptor (VNAR) domain, conjugated using site-specific chemistry, to direct poly lactic acid-co-glycolic acid-polyethylene glycol (PLGA-PEG) nanoparticles to delta like canonical Notch ligand 4 (DLL4). The importance of site-specific chemistry is demonstrated

Physical activity monitoring to assess disability progression in multiple sclerosis

Background: Clinical outcome measurement in multiple sclerosis (MS) usually requires a physical visit. Remote activity monitoring (RAM) using wearable technology provides a rational alternative, especially desirable when distance is involved or in a pandemic setting. Objective: To validate RAM in progressive MS using (1) traditional psychometric methods (2) brain atrophy. Methods: 56 people with progressive MS participated in a longitudinal study over 2.5 years. An arm-worn RAM device measured activity over six days, every six months, and incorporated triaxial accelerometry and transcutaneous physiological variable measurement. Five RAM variables were assessed: physical activity duration, step count, active energy expenditure, metabolic equivalents and a composite RAM score incorporating all four variables. Other assessments every six months included EDSS, MSFC, MSIS-29, Chalder Fatigue Scale and Beck’s Depression Inventory. Annualized brain atrophy was measured using SIENA. Results: RAM was tolerated well by people with MS; the device was worn 99.4% of the time. RAM had good convergent and divergent validity and was responsive, especially with respect to step count. Measurement of physical activity over one day was as responsive as six days. The composite RAM score positively correlated with brain volume loss. Conclusion: Remote activity monitoring is a valid and acceptable outcome measure in MS