Pet population management and public health:A web service based tool for the improvement of dog traceability

The risks associated with zoonotic infections transmitted by companion animals are a serious public health concern: the control of zoonoses incidence in domestic dogs, both owned and stray, is hence important to protect human health. Integrated dog population management (DPM) programs, based on the availability of information systems providing reliable data on the structure and composition of the existing dog population in a given area, are fundamental for making realistic plans for any disease surveillance and action system. Traceability systems, based on the compulsory electronic identification of dogs and their registration in a computerised database, are one of the most effective ways to ensure the usefulness of DPM programs. Even if this approach provides many advantages, several areas of improvement have emerged in countries where it has been applied. In Italy, every region hosts its own dog register but these are not compatible with one another. This paper shows the advantages of a web-based-application to improve data management of dog regional registers. The approach used for building this system was inspired by farm animal traceability schemes and it relies on a network of services that allows multi-channel access by different devices and data exchange via the web with other existing applications, without changing the pre-existing platforms. Today the system manages a database for over 300,000 dogs registered in three different Italian regions. By integrating multiple Web Services, this approach could be the solution to gather data at national and international levels at reasonable cost and creating a traceability system on a large scale and across borders that can be used for disease surveillance and development of population management plans. © 2012 Elsevier B.V.

Tacrolimus is not associated with gingival overgrowth in renal transplant patients

BACKGROUND: Cyclosporin A is used extensively to prevent the rejection of allogenic renal transplants. However, it is associated with a variety of undesirable side effects including gingival overgrowth. Tacrolimus (FK506), has been marketed as an effective alternative immunosuppressant to cyclosporin A and recent subjective reports suggest patients taking it complain infrequently of gingival problems. This clinical investigation was undertaken to confirm whether or not tacrolimus adversely affected the gingival health of renal transplant recipients.

METHODS: Renal transplant patients (RTPs) under the care of the Renal Transplantation Service at the Manchester Royal Infirmary, who had received a renal allograft at least 18 months earlier, were recruited for this study. All but one of the RTPs had been taking tacrolimus since transplantation. The other had commenced tacrolimus therapy two months after receiving her allograft. A hospital based control group was recruited from non transplanted individuals attending the Turner Dental School, Manchester. Each patient underwent a detailed dental assessment and had dental impressions taken. The extent of gingival overgrowth was determined from plaster models.

RESULTS: 25 renal transplant recipients and 26 control patients were included in the study. None of the individuals in either the tacrolimus or control groups had clinically significant overgrowth. The patients in the tacrolimus group with the highest overgrowth scores were those also taking calcium antagonists as treatment for hypertension.

CONCLUSION: This study demonstrates that tacrolimus has no adverse effects on the gingival tissues and thus has potential as an alternative immunosuppressant for individuals susceptible to developing cyclosporin A-induced gingival overgrowth.

Adapting to time: duration channels do not mediate human time perception

Accurately encoding the duration and temporal order of events is essential for survival and important to everyday activities, from holding conversations to driving in fast flowing traffic. Although there is a growing body of evidence that the timing of brief events (< 1s) is encoded by modality-specific mechanisms, it is not clear how such mechanisms register event duration. One approach gaining traction is a channel-based model; this envisages narrowly-tuned, overlapping timing mechanisms that respond preferentially to different durations. The channel-based model predicts that adapting to a given event duration will result in overestimating and underestimating the duration of longer and shorter events, respectively. We tested the model by having observers judge the duration of a brief (600ms) visual test stimulus following adaptation to longer (860ms) and shorter (340ms) stimulus durations. The channel-based model predicts perceived duration compression of the test stimulus in the former condition and perceived duration expansion in the latter condition. Duration compression occurred in both conditions, suggesting that the channel-based model does not adequately account for perceived duration of visual events.

Appropriate complexity for the prediction of coastal and estuarine geomorphic behaviour at decadal to centennial scales

Coastal and estuarine landforms provide a physical template that not only accommodates diverse ecosystem functions and human activities, but also mediates flood and erosion risks that are expected to increase with climate change. In this paper, we explore some of the issues associated with the conceptualisation and modelling of coastal morphological change at time and space scales relevant to managers and policy makers. Firstly, we revisit the question of how to define the most appropriate scales at which to seek quantitative predictions of landform change within an age defined by human interference with natural sediment systems and by the prospect of significant changes in climate and ocean forcing. Secondly, we consider the theoretical bases and conceptual frameworks for determining which processes are most important at a given scale of interest and the related problem of how to translate this understanding into models that are computationally feasible, retain a sound physical basis and demonstrate useful predictive skill. In particular, we explore the limitations of a primary scale approach and the extent to which these can be resolved with reference to the concept of the coastal tract and application of systems theory. Thirdly, we consider the importance of different styles of landform change and the need to resolve not only incremental evolution of morphology but also changes in the qualitative dynamics of a system and/or its gross morphological configuration. The extreme complexity and spatially distributed nature of landform systems means that quantitative prediction of future changes must necessarily be approached through mechanistic modelling of some form or another. Geomorphology has increasingly embraced so-called ‘reduced complexity’ models as a means of moving from an essentially reductionist focus on the mechanics of sediment transport towards a more synthesist view of landform evolution. However, there is little consensus on exactly what constitutes a reduced complexity model and the term itself is both misleading and, arguably, unhelpful. Accordingly, we synthesise a set of requirements for what might be termed ‘appropriate complexity modelling’ of quantitative coastal morphological change at scales commensurate with contemporary management and policy-making requirements: 1) The system being studied must be bounded with reference to the time and space scales at which behaviours of interest emerge and/or scientific or management problems arise; 2) model complexity and comprehensiveness must be appropriate to the problem at hand; 3) modellers should seek a priori insights into what kind of behaviours are likely to be evident at the scale of interest and the extent to which the behavioural validity of a model may be constrained by its underlying assumptions and its comprehensiveness; 4) informed by qualitative insights into likely dynamic behaviour, models should then be formulated with a view to resolving critical state changes; and 5) meso-scale modelling of coastal morphological change should reflect critically on the role of modelling and its relation to the observable world.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.