The Pandora software development kit for pattern recognition

The development of automated solutions to pattern recognition problems is important in many areas of scientific research and human endeavour. This paper describes the implementation of the Pandora Software Development Kit, which aids the process of designing, implementing and running pattern recognition algorithms. The Pandora Application Programming Interfaces ensure simple specification of the building-blocks defining a pattern recognition problem. The logic required to solve the problem is implemented in algorithms. The algorithms request operations to create or modify data structures and the operations are performed by the Pandora framework. This design promotes an approach using many decoupled algorithms, each addressing specific topologies. Details of algorithms addressing two pattern recognition problems in High Energy Physics are presented: reconstruction of events at a high-energy e+e- linear collider and reconstruction of cosmic ray or neutrino events in a liquid argon time projection chamber.This work was funded in part by the UK Science and Technology Facilities Council and by the European Union under the Advanced European Infrastructures for Detectors and Accelerators (AIDA) project.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1140/epjc/s10052-015-3659-

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction

Rapid Patient-Side Evaluation of Endothelial Glycocalyx Thickness in Healthy Sedated Cats Using GlycoCheck (R) Software

(c) The Author/sPublishe

Longitudinal study of the effect of sporidesmin toxicity on lamb production and serum biochemistry in a flock of 46 Romney ewes using a standardised measure of liver damage

CAUL Read and Publish Agreement.Publishe

Mapping quantitative trait loci (QTL) in sheep. IV. Analysis of lactation persistency and extended lactation traits in sheep

<p>Abstract</p> <p>Background</p> <p>In sheep dairy production, total lactation performance, and length of lactation of lactation are of economic significance. A more persistent lactation has been associated with improved udder health. An extended lactation is defined by a longer period of milkability. This study is the first investigation to examine the presence of quantitative trait loci (QTL) for extended lactation and lactation persistency in sheep.</p> <p>Methods</p> <p>An (Awassi × Merino) × Merino single-sire backcross family with 172 ewes was used to map QTL for lactation persistency and extended lactation traits on a framework map of 189 loci across all autosomes. The Wood model was fitted to data from multiple lactations to estimate parameters of ovine lactation curves, and these estimates were used to derive measures of lactation persistency and extended lactation traits of milk, protein, fat, lactose, useful yield, and somatic cell score. These derived traits were subjected to QTL analyses using maximum likelihood estimation and regression analysis.</p> <p>Results</p> <p>Overall, one highly significant (LOD > 3.0), four significant (2.0 < LOD < 3.0) and five suggestive (1.7 < LOD < 2.0) QTL were detected across all traits in common by both mapping methods. One additional suggestive QTL was identified using maximum likelihood estimation, and four suggestive (0.01 < P < 0.05) and two significant (P < 0.01) QTL using the regression approach only. All detected QTL had effect sizes in the range of 0.48 to 0.64 SD, corresponding to QTL heritabilities of 3.1 to 8.9%. The comparison of the detected QTL with results in cattle showed conserved linkage regions. Most of the QTL identified for lactation persistency and extended lactation did not coincide. This suggests that persistency and extended lactation for the same as well as different milk yield and component traits are not controlled by the same genes.</p> <p>Conclusion</p> <p>This study identified ten novel QTL for lactation persistency and extended lactation in sheep, but results suggest that lactation persistency and extended lactation do not have a major gene in common. These results provide a basis for further validation in extended families and other breeds as well as targeting regions for genome-wide association mapping using high-density SNP arrays.</p

Derivation, validation, and comparison of a new prognostic scoring system for acute lower gastrointestinal bleeding

\ua9 2023 The Authors. DEN Open published by John Wiley &amp; Sons Australia, Ltd on behalf of Japan Gastroenterological Endoscopy Society.Objectives: Lower gastrointestinal bleeding is a common presentation with little data concerning risk factors for adverse outcomes. The aim was to derive and validate a scoring system to stratify risk in lower gastrointestinal bleeding and compare it to the Oakland score. Methods: A total of 2385 consecutive patients (mean age 65 years, 1140 males) were used to derive the score using multivariate logistic regression modeling then internally and externally validated. The Oakland score was applied and area under receiver operating characteristic (AUROC) curves were calculated and compared. A score of &lt;1 was compared with an Oakland score of &lt;9 to assess 30-day rebleeding and mortality rates. Results: Rebleeding was associated with age, inpatient bleeding, syncope, malignancy, tachycardia, hypotension, lower hemoglobin and mortality with age, inpatient bleeding, liver/gastrointestinal disease, tachycardia, and hypotension. The area under the receiver operating characteristic curves was 0.742 for rebleeding and 0.802 for mortality. A score &lt;1 was associated with rebleeding (0.0%–2.2%) and mortality (0%). The Oakland score had a significantly lower area under the receiver operating characteristic curve for rebleeding of 0.687 but not for mortality; 0.757. A score &lt;1 was associated with a lower 30-day rebleeding risk compared to an Oakland score &lt;9 (4/379 vs. 15/355, p = 0.009) but not mortality (0/365 vs. 1/355, p = 0.493). Conclusions: Our score predicts 30-day rebleeding and mortality rate with low scores associated with very low risk. The Aberdeen score is superior to the Oakland score for predicting rebleeding. Prospective evaluation of both scores is required

Hitting the Target: Developing High-quality Evidence for Proton Beam Therapy Through Randomised Controlled Trials

The National Health Service strategy for the delivery of proton beam therapy (PBT) in the UK provides a unique opportunity to deliver high-quality evidence for PBT through randomised controlled trials (RCTs). We present a summary of three UK PBT RCTs in progress, including consideration of their key design characteristics and outcome assessments, to inform and support future PBT trial development. The first three UK multicentre phase III PBT RCTs (TORPEdO, PARABLE and APPROACH), will compare PBT with photon radiotherapy for oropharyngeal squamous cell carcinoma, breast cancer and oligodendroglioma, respectively. All three studies were designed by multidisciplinary teams, which combined expertise from clinicians, clinical trialists and scientists with strong patient advocacy and guidance from national radiotherapy research networks and international collaborators. Consistent across all three studies is a focus on the reduction of long-term radiotherapy-related toxicities and an evaluation of patient-reported outcomes and health-related quality of life, which will address key uncertainties regarding the clinical benefits of PBT. Innovative translational components will provide insights into mechanisms of toxicity and help to frame the key future research questions regarding PBT. The UK radiotherapy research community is developing and delivering an internationally impactful PBT research portfolio. The combination of data from RCTs with prospectively collected data from a national PBT outcomes registry will provide an innovative, high-quality repository for PBT research and the platform to design and deliver future trials of PBT

TLR7-mediated skin inflammation remotely triggers chemokine expression and leukocyte accumulation in the brain

Background: The relationship between the brain and the immune system has become increasingly topical as, although it is immune-specialised, the CNS is not free from the influences of the immune system. Recent data indicate that peripheral immune stimulation can significantly affect the CNS. But the mechanisms underpinning this relationship remain unclear. The standard approach to understanding this relationship has relied on systemic immune activation using bacterial components, finding that immune mediators, such as cytokines, can have a significant effect on brain function and behaviour. More rarely have studies used disease models that are representative of human disorders. Methods: Here we use a well-characterised animal model of psoriasis-like skin inflammation—imiquimod—to investigate the effects of tissue-specific peripheral inflammation on the brain. We used full genome array, flow cytometry analysis of immune cell infiltration, doublecortin staining for neural precursor cells and a behavioural read-out exploiting natural burrowing behaviour. Results: We found that a number of genes are upregulated in the brain following treatment, amongst which is a subset of inflammatory chemokines (CCL3, CCL5, CCL9, CXCL10, CXCL13, CXCL16 and CCR5). Strikingly, this model induced the infiltration of a number of immune cell subsets into the brain parenchyma, including T cells, NK cells and myeloid cells, along with a reduction in neurogenesis and a suppression of burrowing activity. Conclusions: These findings demonstrate that cutaneous, peripheral immune stimulation is associated with significant leukocyte infiltration into the brain and suggest that chemokines may be amongst the key mediators driving this response

Applying the ROBINS-I tool to natural experiments: an example from public health

Background: A new tool to assess Risk of Bias In Non-randomised Studies of Interventions (ROBINS-I) was published in Autumn 2016. ROBINS-I uses the Cochrane-approved risk of bias (RoB) approach and focusses on internal validity. As such, ROBINS-I represents an important development for those conducting systematic reviews which include non-randomised studies (NRS), including public health researchers. We aimed to establish the applicability of ROBINS-I using a group of NRS which have evaluated non-clinical public health natural experiments. Methods: Five researchers, all experienced in critical appraisal of non-randomised studies, used ROBINS-I to independently assess risk of bias in five studies which had assessed the health impacts of a domestic energy efficiency intervention. ROBINS-I assessments for each study were entered into a database and checked for consensus across the group. Group discussions were used to identify reasons underpinning lack of consensus for specific questions and bias domains. Results: ROBINS-I helped to systematically articulate sources of bias in NRS. However, the lack of consensus in assessments for all seven bias domains raised questions about ROBINS-I’s reliability and applicability for natural experiment studies. The two RoB domains with least consensus were selection (Domain 2) and performance (Domain 4). Underlying the lack of consensus were difficulties in applying an intention to treat or per protocol effect of interest to the studies. This was linked to difficulties in determining whether the intervention status was classified retrospectively at follow-up, i.e. post hoc. The overall risk of bias ranged from moderate to critical; this was most closely linked to the assessment of confounders. Conclusion: The ROBINS-I tool is a conceptually rigorous tool which focusses on risk of bias due to the counterfactual. Difficulties in applying ROBINS-I may be due to poor design and reporting of evaluations of natural experiments. While the quality of reporting may improve in the future, improved guidance on applying ROBINS-I is needed to enable existing evidence from natural experiments to be assessed appropriately and consistently. We hope future refinements to ROBINS-I will address some of the issues raised here to allow wider use of the tool