Using principal component analysis to understand the variability of PDS 456

We present a spectral-variability analysis of the low-redshift quasar PDS 456 using principal component analysis. In the XMM-Newton data, we find a strong peak in the first principal component at the energy of the Fe absorption line from the highly blueshifted outflow. This indicates that the absorption feature is more variable than the continuum, and that it is responding to the continuum. We find qualitatively different behaviour in the Suzaku data, which is dominated by changes in the column density of neutral absorption. In this case, we find no evidence of the absorption produced by the highly ionized gas being correlated with this variability. Additionally, we perform simulations of the source variability, and demonstrate that PCA can trivially distinguish between outflow variability correlated, anti-correlated, and un-correlated with the continuum flux. Here, the observed anti-correlation between the absorption line equivalent width and the continuum flux may be due to the ionization of the wind responding to the continuum. Finally, we compare our results with those found in the narrow-line Seyfert 1 IRAS 13224-3809. We find that the Fe K UFO feature is sharper and more prominent in PDS 456, but that it lacks the lower energy features from lighter elements found in IRAS 13224-3809, presumably due to differences in ionization

A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders

Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using data from heterogeneous sources to estimate the evolu- tion of a given disease for the particular case of a certain patient. In recent years, next-generation sequencing data have boosted cancer prediction by supplying gene-expression information that has allowed diverse machine learning algorithms to supply valuable solutions to the problem of cancer subtype classification, which has surely contributed to better estimation of patient’s response to diverse treatments. However, the efficacy of these models is seriously affected by the existing imbalance between the high dimensionality of the gene expression feature sets and the number of sam- ples available for a particular cancer type. To counteract what is known as the curse of dimensionality, feature selection and extraction methods have been traditionally applied to reduce the number of input variables present in gene expression datasets. Although these techniques work by scaling down the input feature space, the prediction performance of tradi- tional machine learning pipelines using these feature reduction strategies remains moderate. In this work, we propose the use of the Pan-Cancer dataset to pre-train deep autoencoder architectures on a subset com- posed of thousands of gene expression samples of very diverse tumor types. The resulting architectures are subsequently fine-tuned on a col- lection of specific breast cancer samples. This transfer-learning approach aims at combining supervised and unsupervised deep learning models with traditional machine learning classification algorithms to tackle the problem of breast tumor intrinsic-subtype classification.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The World Hip Trauma Evaluation Study 3 HEMIARTHROPLASTY EVALUATION BY MULTICENTRE INVESTIGATION - WHiTE 3: HEMI - AN ABRIDGED PROTOCOL

Approximately half of all hip fractures are displaced intracapsular fractures. The standard treatment for these fractures is either hemiarthroplasty or total hip arthroplasty. The recent National Institute for Health and Care Excellence (NICE) guidance on hip fracture management recommends the use of 'proven' cemented stem arthroplasty with an Orthopaedic Device Evaluation Panel (ODEP) rating of at least 3B (97% survival at three years). The Thompsons prosthesis is currently lacking an ODEP rating despite over 50 years of clinical use, likely due to the paucity of implant survival data. Nationally, adherence to these guidelines is varied as there is debate as to which prosthesis optimises patient outcomes.This study design is a multi-centre, multi-surgeon, parallel, two arm, standard-of-care pragmatic randomised controlled trial. It will be embedded within the WHiTE Comprehensive Cohort Study (ISRCTN63982700). The main analysis is a two-way equivalence comparison between Hemi-Thompson and Hemi-Exeter polished taper with Unitrax head. Secondary outcomes will include radiological leg length discrepancy measured as per Bidwai and Willett, mortality, re-operation rate and indication for re-operation, length of index hospital stay and revision at four months. This study will be supplemented by the NHFD (National Hip Fracture Database) dataset.Evidence on the optimum choice of prosthesis for hemiarthroplasty of the hip is lacking. National guidance is currently based on expert opinion rather than empirical evidence. The incidence of hip fracture is likely to continue to increase and providing high quality evidence on the optimumCite this article: A. L. Sims. The World Hip Trauma Evaluation Study 3: Hemiarthroplasty Evaluation by Multicentre Investigation - WHITE 3: HEMI - An Abridged Protocol. Bone Joint Res 2016;5:18-25. doi: 10.1302/2046-3758.51.2000473

ImmunoCluster provides a computational framework for the non-specialist to profile high- dimensional cytometry data

High dimensional cytometry is an innovative tool for immune monitoring in health and disease, it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster) an R package for immune profiling cellular heterogeneity in high dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a non-specialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users' needs. The protocol consists of three core computational stages: 1, data import and quality control; 2, dimensionality reduction and unsupervised clustering; and 3, annotation and differential testing, all contained within an R-based open-source framework

Initial evidence that non-clinical autistic traits are associated with lower income

Among non-clinical samples, autistic traits correlate with a range of educational and social outcomes. However, previous work has not investigated the relationship between autistic traits and income, a key determinant of socio-economic status and wellbeing. In 5 studies (total N = 2491), we recruited participants without a diagnosis of autism from the general US population via an on-line platform, and administered the short-form Autism Spectrum Quotient (AQ) as well as asking a range of demographic questions. We found a negative association between AQ and household income, which remained robust after controlling for age, gender, education, employment status, ethnicity, and socially-desirable responding. The effect was primarily driven by the participant’s own income, and was mainly due to the social subscale of the AQ. These results provide initial evidence that income is negatively related to autistic traits among the general population, with potential implications for a range of social, psychological, and health outcomes.WJS was supported by Wellcome Trust grant RG76641 and Isaac Newton Trust grant RG70368. SBC was supported by the Autism Research Trust

Engineering Mesophase Stability and Structure via Incorporation of Cyclic Terminal Groups

We report on the characterisation of a number of liquid–crystalline materials featuring cyclic terminal groups, which lead to significant enhancements in the temperature range of the mesomorphic state. Materials with only short terminal chains are able to support lamellar mesophase formation by appending a large terminal cyclic unit at the end of a short spacer composed of methylene units. X-ray scattering experiments reveal that the layer spacings of the lamellar smectic phase are significantly larger when a cyclic end-group is present than for equivalent linear unsubstituted materials, but there is no effect on orientational order. Fully atomistic molecular dynamics simulations faithfully reproduce experimental layer spacings and orientational order parameters, and indicate that the cyclic terminal units spontaneously segregate into diffuse sub-layers and thus cause the increased layer spacing. This shape segregation predicted by molecular dynamics simulations is observed in the crystalline solid state by X-ray diffraction

Quantum systems in weak gravitational fields

Fully covariant wave equations predict the existence of a class of inertial-gravitational effects that can be tested experimentally. In these equations inertia and gravity appear as external classical fields, but, by conforming to general relativity, provide very valuable information on how Einstein's views carry through in the world of the quantum.Comment: 22 pages. To be published in Proceedings of the 17th Course of the International School of Cosmology and Gravitation "Advances in the interplay between quantum and gravity physics" edited by V. De Sabbata and A. Zheltukhin, Kluwer Academic Publishers, Dordrech

Delayed hospitalization increases mortality in displaced femoral neck fracture patients

Background and purpose Reports regarding the relationship between delayed surgery and mortality in femoral neck fracture patients are contradictory. We could not find any study in the literature investigating delayed arrival to hospital and delayed surgery as separate factors affecting mortality in femoral neck fracture patients, which was the purpose of our study

Biology and evolutionary games

This chapter surveys some evolutionary games used in biological sciences. These include the Hawk-Dove game, the Prisoner’s Dilemma, Rock–Paper–Scissors, the war of attrition, the Habitat Selection game, predatorprey games, and signalling games