Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

Inspiratory muscle training reduces blood lactate concentration during volitional hyperpnoea

Although reduced blood lactate concentrations ([lac−]B) have been observed during whole-body exercise following inspiratory muscle training (IMT), it remains unknown whether the inspiratory muscles are the source of at least part of this reduction. To investigate this, we tested the hypothesis that IMT would attenuate the increase in [lac−]B caused by mimicking, at rest, the breathing pattern observed during high-intensity exercise. Twenty-two physically active males were matched for 85% maximal exercise minute ventilation (V˙Emax) and divided equally into an IMT or a control group. Prior to and following a 6 week intervention, participants performed 10 min of volitional hyperpnoea at the breathing pattern commensurate with 85% V˙Emax

Graphene plasmonics

Two rich and vibrant fields of investigation, graphene physics and plasmonics, strongly overlap. Not only does graphene possess intrinsic plasmons that are tunable and adjustable, but a combination of graphene with noble-metal nanostructures promises a variety of exciting applications for conventional plasmonics. The versatility of graphene means that graphene-based plasmonics may enable the manufacture of novel optical devices working in different frequency ranges, from terahertz to the visible, with extremely high speed, low driving voltage, low power consumption and compact sizes. Here we review the field emerging at the intersection of graphene physics and plasmonics.Comment: Review article; 12 pages, 6 figures, 99 references (final version available only at publisher's web site

Can-Pain-a digital intervention to optimise cancer pain control in the community : development and feasibility testing

Purpose: To develop a novel digital intervention to optimise cancer pain control in the community. This paper describes intervention development, content/rationale and initial feasibility testing. Methods: Determinants of suboptimal cancer pain management were characterised through two systematic reviews; patient, caregiver and healthcare professional (HCP) interviews (n = 39); and two HCP focus groups (n = 12). Intervention mapping was used to translate results into theory-based content, creating the app “Can-Pain”. Patients with/without a linked caregiver, their general practitioners and community palliative care nurses were recruited to feasibility test Can-Pain over 4 weeks. Results: Patients on strong opioids described challenges balancing pain levels with opioid intake, side effects and activities and communicating about pain management problems with HCPs. Can-Pain addresses these challenges through educational resources, contemporaneous short-acting opioid tracking and weekly patient-reported outcome monitoring. Novel aspects of Can-Pain include the use of contemporaneous breakthrough analgesic reports as a surrogate measure of pain control and measuring the level at which pain becomes bothersome to the individual. Patients were unwell due to advanced cancer, making recruitment to feasibility testing difficult. Two patients and one caregiver used Can-Pain for 4 weeks, sharing weekly reports with four HCPs. Can-Pain highlighted unrecognised problems, promoted shared understanding about symptoms between patients and HCPs and supported shared decision-making. Conclusions: Preliminary testing suggests that Can-Pain is feasible and could promote patient-centred pain management. We will conduct further small-scale evaluations to inform a future randomised, stepped-wedge trial

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

HGS-ETR1, a fully human TRAIL-receptor 1 monoclonal antibody, induces cell death in multiple tumour types in vitro and in vivo

Tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) induces apoptosis in a variety of tumour cells through activation of TRAIL-R1 and TRAIL-R2 death signalling receptors. Here, we describe the characterisation and activity of HGS-ETR1, the first fully human, agonistic TRAIL-R1 mAb that is being developed as an antitumour therapeutic agent. HGS-ETR1 showed specific binding to TRAIL-R1 receptor. HGS-ETR1 reduced the viability of multiple types of tumour cells in vitro, and induced activation of caspase 8, Bid, caspase 9, caspase 3, and cleavage of PARP, indicating activation of TRAIL-R1 alone was sufficient to induce both extrinsic and intrinsic apoptotic pathways. Treatment of cell lines in vitro with HGS-ETR1 enhanced the cytotoxicity of chemotherapeutic agents (camptothecin, cisplatin, carboplatin, or 5-fluorouracil) even in tumour cell lines that were not sensitive to HGS-ETR1 alone. In vivo administration of HGS-ETR1 resulted in rapid tumour regression or repression of tumour growth in pre-established colon, non-small-cell lung, and renal tumours in xenograft models. Combination of HGS-ETR1 with chemotherapeutic agents (topotecan, 5-fluorouracil, and irinotecan) in three independent colon cancer xenograft models resulted in an enhanced antitumour efficacy compared to either agent alone. Pharmacokinetic studies in the mouse following intravenous injection showed that HGS-ETR1 serum concentrations were biphasic with a terminal half-life of 6.9–8.7 days and a steady-state volume of distribution of approximately 60 ml kg−1. Clearance was 3.6–5.7 ml−1 day−1 kg−1. These data suggest that HGS-ETR1 is a specific and potent antitumour agent with favourable pharmacokinetic characteristics and the potential to provide therapeutic benefit for a broad range of human malignancies

Population-Specific Responses to Interspecific Competition in the Gut Microbiota of Two Atlantic Salmon (Salmo salar) Populations

The gut microbial community in vertebrates plays a role in nutrient digestion and absorption, development of intestine and immune systems, resistance to infection, regulation of bone mass and even host behavior and can thus impact host fitness. Atlantic salmon (Salmo salar) reintroduction efforts into Lake Ontario, Canada, have been unsuccessful, likely due to competition with non-native salmonids. In this study, we explored interspecific competition effects on the gut microbiota of two Atlantic salmon populations (LaHave and Sebago) resulting from four non-native salmonids. After 10 months of rearing in semi-natural stream tanks under six interspecific competition treatments, we characterized the gut microbiota of 178 Atlantic salmon by parallel sequencing the 16S rRNA gene. We found 3978 bacterial OTUs across all samples. Microbiota alpha diversity and abundance of 27 OTUs significantly differed between the two populations. Interspecific competition reduced relative abundance of potential beneficial bacteria (six genera of lactic acid bacteria) as well as 13 OTUs, but only in the LaHave population, indicating population-specific competition effects. The pattern of gut microbiota response to interspecific competition may reflect local adaptation of the host-microbiota interactions and can be used to select candidate populations for improved species reintroduction success

Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

BACKGROUND: In order to detect potential disease clusters where a putative source cannot be specified, classical procedures scan the geographical area with circular windows through a specified grid imposed to the map. However, the choice of the windows' shapes, sizes and centers is critical and different choices may not provide exactly the same results. The aim of our work was to use an Oblique Decision Tree model (ODT) which provides potential clusters without pre-specifying shapes, sizes or centers. For this purpose, we have developed an ODT-algorithm to find an oblique partition of the space defined by the geographic coordinates. METHODS: ODT is based on the classification and regression tree (CART). As CART finds out rectangular partitions of the covariate space, ODT provides oblique partitions maximizing the interclass variance of the independent variable. Since it is a NP-Hard problem in R(N), classical ODT-algorithms use evolutionary procedures or heuristics. We have developed an optimal ODT-algorithm in R(2), based on the directions defined by each couple of point locations. This partition provided potential clusters which can be tested with Monte-Carlo inference. We applied the ODT-model to a dataset in order to identify potential high risk clusters of malaria in a village in Western Africa during the dry season. The ODT results were compared with those of the Kulldorff' s SaTScan™. RESULTS: The ODT procedure provided four classes of risk of infection. In the first high risk class 60%, 95% confidence interval (CI95%) [52.22–67.55], of the children was infected. Monte-Carlo inference showed that the spatial pattern issued from the ODT-model was significant (p < 0.0001). Satscan results yielded one significant cluster where the risk of disease was high with an infectious rate of 54.21%, CI95% [47.51–60.75]. Obviously, his center was located within the first high risk ODT class. Both procedures provided similar results identifying a high risk cluster in the western part of the village where a mosquito breeding point was located. CONCLUSION: ODT-models improve the classical scanning procedures by detecting potential disease clusters independently of any specification of the shapes, sizes or centers of the clusters