The Biodiversity and Climate Change Virtual Laboratory: Where ecology meets big data

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met

An Overview of Massive MIMO Research at the University of Bristol

Massive MIMO has rapidly gained popularity as a technology crucial to the capacity advances required for 5G wireless systems. Since its theoretical conception six years ago, research activity has grown exponentially, and there is now a developing industrial interest to commercialise the technology. For this to happen effectively, we believe it is crucial that further pragmatic research is conducted with a view to establish how reality differs from theoretical ideals. This paper presents an overview of the massive MIMO research activities occurring within the Communication Systems & Networks Group at the University of Bristol centred around our 128-antenna real-time testbed, which has been developed through the BIO programmable city initiative in collaboration with NI and Lund University. Through recent preliminary trials, we achieved a world first spectral efficiency of 79.4 bits/s/Hz, and subsequently demonstrated that this could be increased to 145.6 bits/s/Hz. We provide a summary of this work here along with some of our ongoing research directions such as large-scale array wave-front analysis, optimised power control and localisation techniques.Comment: Presented at the IET Radio Propagation and Technologies for 5G Conference (2016). 5 page

Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Objective. Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI). We trained and evaluated computed tomography (CT) and MRI OAR autosegmentation models in RayStation. To ascertain clinical usability, we investigated the geometric impact of contour editing before training on model quality. Approach. Retrospective glioma cases were randomly selected for training (n = 32, 47) and validation (n = 9, 10) for MRI and CT, respectively. Clinical contours were edited using international consensus (gold standard) based on MRI and CT. MRI models were trained (i) using the original clinical contours based on planning CT and rigidly registered T1-weighted gadolinium-enhanced MRI (MRIu), (ii) as (i), further edited based on CT anatomy, to meet international consensus guidelines (MRIeCT), and (iii) as (i), further edited based on MRI anatomy (MRIeMRI). CT models were trained using: (iv) original clinical contours (CTu) and (v) clinical contours edited based on CT anatomy (CTeCT). Auto-contours were geometrically compared to gold standard validation contours (CTeCT or MRIeMRI) using Dice Similarity Coefficient, sensitivity, and mean distance to agreement. Models' performances were compared using paired Student's t-testing. Main results. The edited autosegmentation models successfully generated more segmentations than the unedited models. Paired t-testing showed editing pituitary, orbits, optic nerves, lenses, and optic chiasm on MRI before training significantly improved at least one geometry metric. MRI-based DL-AC performed worse than CT-based in delineating the lacrimal gland, whereas the CT-based performed worse in delineating the optic chiasm. No significant differences were found between the CTeCT and CTu except for optic chiasm. Significance. T1w-MRI DL-AC could segment all brain OARs except the lacrimal glands, which cannot be easily visualized on T1w-MRI. Editing contours on MRI before model training improved geometric performance. MRI DL-AC in RT may improve consistency, quality and efficiency but requires careful editing of training contours

The benefit of MR-only radiotherapy treatment planning for anal and rectal cancers: A planning study

Introduction: Limited evidence exists showing the benefit of magnetic resonance (MR)-only radiotherapy treatment planning for anal and rectal cancers. This study aims to assess the impact of MR-only planning on target volumes (TVs) and treatment plan doses to organs at risks (OARs) for anal and rectal cancers versus a computed tomography (CT)-only pathway. Materials and methods: Forty-six patients (29 rectum and 17 anus) undergoing preoperative or radical external beam radiotherapy received CT and T2 MR simulation. TV and OARs were delineated on CT and MR, and volumetric arc therapy treatment plans were optimized independently (53.2 Gy/28 fractions for anus, 45 Gy/25 fractions for rectum). Further treatment plans assessed gross tumor volume (GTV) dose escalation. Differences in TV volumes and OAR doses, in terms of Vx Gy (organ volume (%) receiving x dose (Gy)), were assessed. Results: MR GTV and primary planning TV (PTV) volumes systematically reduced by 13 cc and 98 cc (anus) and 44 cc and 109 cc (rectum) respectively compared to CT volumes. Statistically significant OAR dose reductions versus CT were found for bladder and uterus (rectum) and bladder, penile bulb, and genitalia (anus). With GTV boosting, statistically significant dose reductions were found for sigmoid, small bowel, vagina, and penile bulb (rectum) and vagina (anus). Conclusion: Our findings provide evidence that the introduction of MR (whether through MR-only or CT-MR pathways) to radiotherapy treatment planning for anal and rectal cancers has the potential to improve treatments. MR-related OAR dose reductions may translate into less treatment-related toxicity for patients or greater ability to dose escalate

The Biodiversity and Climate Change Virtual Laboratory: How Ecology and Big Data can be utilised in the fight against vector-borne diseases

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets, as well as a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration and cross-fertilisation of ideas and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met. We present a case study that illustrates the utility of the BCCVL as a research tool that can be applied to the problem of vector borne diseases and the likelihood of climate change altering their future distribution across Australia. This case study presents the preliminary results of an ensemble modelling experiment which employs multiple (15) different species distribution modelling algorithms to model the distribution of one of the main mosquito vectors of the most common vector borne disease in Australia: Ross River Virus (RRV). We use the BCCVL to do future projection of these models with future climates based on two extreme emissions scenarios, for multiple years. Our results show a large range in both the modelled current distribution, and projected future distribution, of the mosquito species studied. Most models (that were built using different algorithms) show somewhat similar current distributions of the species however there are three models that are obvious outliers. The projected models show a similar range in the distribution of the species, with some models indicating a fewer areas (and also areas with a lower probability of occurrence in specific areas) where the species is likely to be found under a climate change scenario. However, a majority of models show an expanded distribution, with some areas that have a greater probability of the occurrence of this species; this will provide a more robust indication of future distribution for policy makers and planners, than if just one or a few models had been employed. The economic and human health impact of vector borne diseases underline the importance of scientifically sound projections of the future spread of common disease vectors such as mosquitos under various climate change scenarios. This is because such information is essential for policy–makers to identify vulnerable communities and to better manage outbreaks and potential epidemics of such diseases. The BCCVL has provided the means to effectively and robustly bracket multiple sources of uncertainty in the future spread of RRV: this study focuses on two of these - the future distribution of a primary mosquito vector of the disease under two extreme scenarios of climate change. Research is underway to expand our analysis to take into account more sources of uncertainty: more vector and amplifying host species, emissions scenarios, and future climate projections from a range of different global climate model

Patient position verification in magnetic-resonance imaging only radiotherapy of anal and rectal cancers

Background and Purpose: Magnetic resonance (MR)-only treatment pathways require either the MR-simulation or synthetic-computed tomography (sCT) as an alternative reference image for cone beam computed tomography (CBCT) patient position verification. This study assessed whether using T2 MR or sCT as CBCT reference images introduces systematic registration errors as compared to CT for anal and rectal cancers. Materials and Methods: A total of 32 patients (18 rectum,14 anus) received pre-treatment CT- and T2 MR- simulation. Routine treatment CBCTs were acquired. sCTs were generated using a validated research model. The local clinical registration protocol, using a grey-scale registration algorithm, was performed for 216 CBCTs using CT, MR and sCT as the reference image. Linear mixed effects modelling identified systematic differences between modalities. Results: Systematic translation and rotation differences to CT for MR were −0.3 to + 0.3 mm and −0.1 to 0.4° for anal cancers and −0.4 to 0.0 mm and 0.0 to 0.1° for rectal cancers, and for sCT were −0.4 to + 0.8 mm, −0.1 to 0.2° for anal cancers and −0.6 to + 0.2 mm, −0.1 to + 0.1° for rectal cancers. Conclusions: T2 MR or sCT can successfully be used as reference images for anal and rectal cancer CBCT position verification with systematic differences to CT <±1 mm and <±0.5°. Clinical enabling of alternative modalities as reference images by vendors is required to reduce challenges associated with their use

Costing conservation: an expert appraisal of the pollinator habitat benefits of England’s entry level stewardship

Pollination services provided by insects play a key role in English crop production and wider ecology. Despite growing evidence of the negative effects of habitat loss on pollinator populations, limited policy support is available to reverse this pressure. One measure that may provide beneficial habitat to pollinators is England’s entry level stewardship agri-environment scheme. This study uses a novel expert survey to develop weights for a range of models which adjust the balance of Entry Level Stewardship options within the current area of spending. The annual costs of establishing and maintaining these option compositions were estimated at £59.3–£12.4 M above current expenditure. Although this produced substantial reduction in private cost:benefit ratios, the benefits of the scheme to pollinator habitat rose by 7–140 %; significantly increasing the public cost:benefit ratio. This study demonstrates that the scheme has significant untapped potential to provide good quality habitat for pollinators across England, even within existing expenditure. The findings should open debate on the costs and benefits of specific entry level stewardship management options and how these can be enhanced to benefit both participants and biodiversity more equitably

Evaluation of integrin αvβ6 cystine knot PET tracers to detect cancer and idiopathic pulmonary fibrosis.

Advances in precision molecular imaging promise to transform our ability to detect, diagnose and treat disease. Here, we describe the engineering and validation of a new cystine knot peptide (knottin) that selectively recognizes human integrin αvβ6 with single-digit nanomolar affinity. We solve its 3D structure by NMR and x-ray crystallography and validate leads with 3 different radiolabels in pre-clinical models of cancer. We evaluate the lead tracer's safety, biodistribution and pharmacokinetics in healthy human volunteers, and show its ability to detect multiple cancers (pancreatic, cervical and lung) in patients at two study locations. Additionally, we demonstrate that the knottin PET tracers can also detect fibrotic lung disease in idiopathic pulmonary fibrosis patients. Our results indicate that these cystine knot PET tracers may have potential utility in multiple disease states that are associated with upregulation of integrin αvβ6