Instance-based concept learning from multiclass DNA microarray data

BACKGROUND: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as nearest neighbor (NN) approaches perform remarkably well in comparison to more complex models, and are currently experiencing a renaissance in the analysis of data sets from biology and biotechnology. While binary classification of microarray data has been extensively investigated, studies involving multiclass data are rare. The question remains open whether there exists a significant difference in performance between NN approaches and more complex multiclass methods. Comparative studies in this field commonly assess different models based on their classification accuracy only; however, this approach lacks the rigor needed to draw reliable conclusions and is inadequate for testing the null hypothesis of equal performance. Comparing novel classification models to existing approaches requires focusing on the significance of differences in performance. RESULTS: We investigated the performance of instance-based classifiers, including a NN classifier able to assign a degree of class membership to each sample. This model alleviates a major problem of conventional instance-based learners, namely the lack of confidence values for predictions. The model translates the distances to the nearest neighbors into 'confidence scores'; the higher the confidence score, the closer is the considered instance to a pre-defined class. We applied the models to three real gene expression data sets and compared them with state-of-the-art methods for classifying microarray data of multiple classes, assessing performance using a statistical significance test that took into account the data resampling strategy. Simple NN classifiers performed as well as, or significantly better than, their more intricate competitors. CONCLUSION: Given its highly intuitive underlying principles – simplicity, ease-of-use, and robustness – the k-NN classifier complemented by a suitable distance-weighting regime constitutes an excellent alternative to more complex models for multiclass microarray data sets. Instance-based classifiers using weighted distances are not limited to microarray data sets, but are likely to perform competitively in classifications of high-dimensional biological data sets such as those generated by high-throughput mass spectrometry

Revisions to rationality:the translation of ‘new knowledges’ into policy under the Coalition Government

This article gives an account of the use of knowledges from emerging scientific fields in education and youth policy making under the Coalition government (2010–15) in the UK. We identify a common process of ‘translation’ and offer three illustrations of policy-making in the UK that utilise diverse knowledges produced in academic fields (neuroscience, network theory and well-being). This production of ‘new knowledges’ in policy contexts allows for the identification of sites of policy intervention. This process of translation underlies a series of diverse revisions of the rational subject of policy. Collectively, these revisions amount to a change in policy-making and the emergence of a different subject of neoliberal policy. This subject is not an excluded alterity to an included rational subject of neoliberalism, but a ‘plastic subject’ characterised by its multiplicity. The plastic subject does not contradict the rational subject as central to neoliberal policy-making, but diversifies it

Beta-cyclodextrin (CD) inclusion complexes of disconnected synthetic cannabinoid molecules

SERS has proven to be a powerful screening technique for synthetic cannabinoids. Research shows successful capping of silver nanoparticles with thiolated CDfor the detection of polycyclic aromatic hydrocarbons for SERS enhancement. CD is an oligosaccharide composed of seven α-D-glucopyranoside units and is commonly used in pharmaceuticals and drug delivery as its cavity can be used to form inclusion complexes with hydrophobic molecules

How, why, for whom and in what context, do sexual health clinics provide an environment for safe and supported disclosure of sexual violence: protocol for a realist review

Introduction Supporting people subjected to sexual violence includes provision of sexual and reproductive healthcare. There is a need to ensure an environment for safe and supported disclosure of sexual violence in these clinical settings. The purpose of this research is to gain a deeper understanding of how, why, for whom and in what circumstances safe and supported disclosure occurs in sexual health services. Methods and analysis To understand how safe and supported disclosure of sexual violence works within sexual health services a realist review will be undertaken with the following steps: (1) Focussing of the review including a scoping literature search and guidance from an advisory group. (2) Developing the initial programme theories and a search strategy using context-mechanism-outcome (CMO) configurations. (3) Selection, data extraction and appraisal based on relevance and rigour. (4) Data analysis and synthesis to further develop and refine programme theory, CMO configurations with consideration of middle-range and substantive theories. Data analysis A realist logic of analysis will be used to align data from each phase of the review, with CMO configurations being developed. Programme theories will be sought from the review that can be further tested in the field. Ethics and dissemination This study has been approved by the ethics committee at University of Birmingham, and has Health Research Authority approval. Findings will be disseminated through knowledge exchange with stakeholders, publications in peer-reviewed journals, conference presentations and formal and informal reports. In addition, as part of a doctoral study, the findings will be tested in multisite case studies. PROSPERO registration details CRD4201912998. Dates of the planned realist review, from protocol design to completion, January 2019 to July 2020

Plant-Based Dairy Alternatives Contribute to a Healthy and Sustainable Diet

Plant-based foods are increasing in popularity as more and more people are concerned about personal and planetary health. The consumption of plant-based dairy alternatives (PBDAs) has assumed a more significant dietary role in populations shifting to more sustainable eating habits. Plant-based drinks (PBDs) made from soya and other legumes have ample protein levels. PBDs that are appropriately fortified have adequate levels of important vitamins and minerals comparable to dairy milk. For the PBDs examined, the greenhouse gas emissions were diminished by 59–71% per 250 mL, and the land use and eutrophication impact was markedly less than the levels displayed by dairy milk. The water usage for the oat and soya drinks, but not rice drinks, was substantially lower compared to dairy milk. When one substitutes the 250 mL serving of dairy milk allowed within the EAT Lancet Planetary Health Diet for a fortified plant-based drink, we found that the nutritional status is not compromised but the environmental footprint is reduced. Combining a nutrient density score with an environmental index can easily lead to a misclassification of food when the full nutrition profile is not utilized or only a selection of environmental factors is used. Many PBDAs have been categorized as ultra-processed foods (UPFs). Such a classification, with the implied adverse nutritional and health associations, is inconsistent with current findings regarding the nutritional quality of such products and may discourage people from transitioning to a plant-based diet with its health and environmental advantages

MEGASAT: automated inference of microsatellite genotypes from sequence data

MEGASAT is software that enables genotyping of microsatellite loci using next-generation sequencing data. Microsatellites are amplified in large multiplexes, and then sequenced in pooled amplicons. MEGASAT reads sequence files and automatically scores microsatellite genotypes. It uses fuzzy matches to allow for sequencing errors and applies decision rules to account for amplification artefacts, including nontarget amplification products, replication slippage during PCR (amplification stutter) and differential amplification of alleles. An important fea- ture of MEGASAT is the generation of histograms of the length–frequency distributions of amplification products for each locus and each individual. These histograms, analogous to electropherograms traditionally used to score microsatellite genotypes, enable rapid evaluation and editing of automatically scored genotypes. MEGASAT is written in Perl, runs on Windows, Mac OS X and Linux systems, and includes a simple graphical user interface. We demon- strate MEGASAT using data from guppy, Poecilia reticulata. We genotype 1024 guppies at 43 microsatellites per run on an Illumina MiSeq sequencer. We evaluated the accuracy of automatically called genotypes using two methods, based on pedigree and repeat genotyping data, and obtained estimates of mean genotyping error rates of 0.021 and 0.012. In both estimates, three loci accounted for a disproportionate fraction of genotyping errors; conversely, 26 loci were scored with 0–1 detected error (error rate ≤0.007). Our results show that with appropriate selection of loci, automated genotyping of microsatellite loci can be achieved with very high throughput, low genotyping error and very low genotyping costs

Using movement, diet, and genetic analyses to understand Arctic charr responses to ecosystem change

ACKNOWLEDGEMENTS The extensive datasets used in this study were reliant on the dedication and innovation of many residents of Nunatsiavut (Food Skills and Environmental Research Program), technicians and biologists from DFO (J. Seiden, D. Lancaster, M. Shears, M. Bloom, S. Duffy), the Nunatsiavut Government (P. McCarney, C. Andersen, L. Pijogge), Oceans North (S. Pain), and of the captains and crew of the What’s Happening and the Safe Passage. Suggestions by three anonymous reviewers also greatly improved the manuscript. Funding for this research was provided in part by ArcticNet and DFO Oceans.Peer reviewedPublisher PD

The timing of hypertonic saline (HTS) and airway clearance techniques (ACT) in adults with Cystic Fibrosis (CF) during pulmonary exacerbation: Pilot data form a randomised crossover study.

BACKGROUND: Streamlining the timing of treatments in cystic fibrosis (CF) is important to optimise adherence while ensuring efficacy. The optimal timing of treatment with hypertonic saline (HTS) and airway clearance techniques (ACT) is unknown. OBJECTIVES: This study hypothesised that HTS before ACT would be more effective than HTS during ACT as measured by Lung Clearance Index (LCI). METHODS: Adults with CF providing written informed consent were randomised to a crossover trial of HTS before ACT or HTS during ACT on consecutive days. ACT treatment consisted of Acapella Duet. Patients completed LCI and spirometry at baseline and 90 min post treatment. Mean difference (MD) and 95% CIs were reported. RESULTS: 13 subjects completed the study (mean (SD) age 33 (12) years, forced expiratory volume in 1second % (FEV1%) predicted 51% (22), LCI (no. turnovers) 14 (4)). Comparing the two treatments (HTS before ACT vs HTS during ACT), the change from baseline to 90 min post treatment in LCI (MD (95% CI) -0.02 (-0.63 to 0.59)) and FEV1% predicted (MD (95% CI) -0.25 (-2.50 to 1.99)) was not significant. There was no difference in sputum weight (MD (95% CI) -3.0 (-14.9 to 8.9)), patient perceived ease of clearance (MD (95% CI) 0.4 (-0.6 to 1.3) or satisfaction (MD (95% CI) 0.4 (-0.6 to 1.5)). The time taken for HTS during ACT was significantly shorter (MD (95% CI) 14.7 (9.8 to 19.6)). CONCLUSIONS: In this pilot study, HTS before ACT was no more effective than HTS during ACT as measured by LCI. TRIAL REGISTRATION NUMBER: NCT01753869; Pre-results