Reply to Lee and colleagues—Viral posterior uveitis

No abstract available

Translating policy to place: exploring cultural ecosystem services in areas of Green Belt through participatory mapping

\ua9 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Green Belts are longstanding planning designations, which primarily seek to prevent urban sprawl. Importantly, they form the open spaces close to where most people live, but we lack clarity over how Green Belts are used and valued by publics, and the cultural ecosystem services they provide. To address this policy and research gap, a public participatory mapping survey was conducted on the North-East England Green Belt, with 779 respondents plotting 2388 points. The results show for the first time that in addition to being a planning policy zone, Green Belts are important, and widely used open spaces for ‘everyday nature’, providing several cultural ecosystem services including recreation, connection with nature, sense of place and aesthetic value. Several factors were found to influence the supply of cultural ecosystem services in Green Belts, including proximity to urban areas, woodland land cover and access designations. Whereas most demand pressures on Green Belts were on public rights-of-way, nature designations and deciduous woodlands. Pervasive barriers inhibiting Green Belt’s full potential were identified including management issues, concerns over personal safety and lack of access. We argue that opportunities to further enhance the cultural ecosystem services provided Green Belts and peri-urban landscapes more broadly, not only come from planning policies themselves, but from the design and delivery of approaches integrating urban, rural and land-use policy silos. The findings have wider implications for policy including potential conflict with future development, and opportunities for greater access to greenspace

Mary Scott (Art forum)

Mary Scott's art practice is based in images; she has exhibited her art nationally since 1990. In this lecture she endeavours to unravel the intricacies of the abstract processes through which she makes these 'found' images her own

Comparison of I-131 Radioimmunotherapy Tumor Dosimetry: Unit Density Sphere Model Versus Patient-Specific Monte Carlo Calculations

High computational requirements restrict the use of Monte Carlo algorithms for dose estimation in a clinical setting, despite the fact that they are considered more accurate than traditional methods. The goal of this study was to compare mean tumor absorbed dose estimates using the unit density sphere model incorporated in OLINDA with previously reported dose estimates from Monte Carlo simulations using the dose planning method (DPMMC) particle transport algorithm. The dataset (57 tumors, 19 lymphoma patients who underwent SPECT/CT imaging during I-131 radioimmunotherapy) included tumors of varying size, shape, and contrast. OLINDA calculations were first carried out using the baseline tumor volume and residence time from SPECT/CT imaging during 6 days post-tracer and 8 days post-therapy. Next, the OLINDA calculation was split over multiple time periods and summed to get the total dose, which accounted for the changes in tumor size. Results from the second calculation were compared with results determined by coupling SPECT/CT images with DPM Monte Carlo algorithms. Results from the OLINDA calculation accounting for changes in tumor size were almost always higher (median 22%, range -1%-68%) than the results from OLINDA using the baseline tumor volume because of tumor shrinkage. There was good agreement (median -5%, range -13%-2%) between the OLINDA results and the self-dose component from Monte Carlo calculations, indicating that tumor shape effects are a minor source of error when using the sphere model. However, because the sphere model ignores cross-irradiation, the OLINDA calculation significantly underestimated (median 14%, range 2%-31%) the total tumor absorbed dose compared with Monte Carlo. These results show that when the quantity of interest is the mean tumor absorbed dose, the unit density sphere model is a practical alternative to Monte Carlo for some applications. For applications requiring higher accuracy, computer-intensive Monte Carlo calculation is needed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90433/1/cbr-2E2011-2E0965.pd

Protection against Experimental Melioidosis with a Synthetic manno-Heptopyranose Hexasaccharide Glycoconjugate

This is the final version of the article. Available from the publisher via the DOI in this record.Melioidosis is an emerging infectious disease caused by Burkholderia pseudomallei and is associated with high morbidity and mortality rates in endemic areas. Antibiotic treatment is protracted and not always successful; even with appropriate therapy, up to 40% of individuals presenting with melioidosis in Thailand succumb to infection. In these circumstances, an effective vaccine has the potential to have a dramatic impact on both the scale and the severity of disease. Currently, no vaccines are licensed for human use. A leading vaccine candidate is the capsular polysaccharide consisting of a homopolymer of unbranched 1→3 linked 2-O-acetyl-6-deoxy-β-d-manno-heptopyranose. Here, we present the chemical synthesis of this challenging antigen using a novel modular disaccharide assembly approach. The resulting hexasaccharide was coupled to the nontoxic Hc domain of tetanus toxin as a carrier protein to promote recruitment of T-cell help and provide a scaffold for antigen display. Mice immunized with the glycoconjugate developed IgM and IgG responses capable of recognizing native capsule, and were protected against infection with over 120 × LD50 of B. pseudomallei strain K96243. This is the first report of the chemical synthesis of an immunologically relevant and protective hexasaccharide fragment of the capsular polysaccharide of B. pseudomallei and serves as the rational starting point for the development of an effective licensed vaccine for this emerging infectious disease.This work was funded by the United Kingdom Ministry of Defence. The mass spectral data described here were acquired on an Orbitrap Fusion mass spectrometer funded by National Institutes of Health grant 1S10OD010645-01A1