Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

Comparison of non-invasive peripheral venous saturations with venous blood co-oximetry

The estimation of venous oxygen saturations using photoplethysmography (PPG) may be useful as a noninvasive continuous method of detecting changes in regional oxygen supply and demand (e.g. in the splanchnic circulation). The aim of this research was to compare PPG-derived peripheral venous oxygen saturations directly with venous saturation measured from co-oximetry blood samples, to assess the feasibility of non-invasive local venous oxygen saturation. This paper comprises two similar studies: one in healthy spontaneously-breathing volunteers and one in mechanically ventilated anaesthetised patients. In both studies, PPG-derived estimates of peripheral venous oxygen saturations (SxvO2) were compared with co-oximetry samples (ScovO2) of venous blood from the dorsum of the hand. The results were analysed and correlation between the PPG-derived results and co-oximetry was tested for. In the volunteer subjects,moderate correlation (r = 0.81) was seen between SxvO2 values and co-oximetry derived venous saturations (ScovO2), with a mean (±SD) difference of +5.65 ± 14.3% observed between the two methods. In the anaesthetised patients SxvO2 values were only 3.81% lower than SpO2 and tended to underestimate venous saturation (mean difference = –2.67 ± 5.89%) while correlating weakly with ScovO2 (r = 0.10). The results suggest that significant refinement of the technique is needed to sufficiently improve accuracy to produce clinically meaningful measurement of peripheral venous oxygen saturation. In anaesthetised patients the use of the technique may be severely limited by cutaneous arteriovenous shunting

A Computational Framework Discovers New Copy Number Variants with Functional Importance

Structural variants which cause changes in copy numbers constitute an important component of genomic variability. They account for 0.7% of genomic differences in two individual genomes, of which copy number variants (CNVs) are the largest component. A recent population-based CNV study revealed the need of better characterization of CNVs, especially the small ones (<500 bp).We propose a three step computational framework (Identification of germline Changes in Copy Number or IgC2N) to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias. This computational approach is applied to genome-wide data from 1250 HapMap individuals. Novel variants were discovered and characterized in terms of size, minor allele frequency, type of polymorphism (gains, losses or both), and mechanism of formation. Using data generated for a subset of individuals by a 42 million marker platform, we validated the majority of the variants with the highest validation rate (66.7%) was for variants of size larger than 1 kb. Finally, we queried transcriptomic data from 129 individuals determined by RNA-sequencing as further validation and to assess the functional role of the new variants. We investigated the possible enrichment for variant's regulatory effect and found that smaller variants (<1 Kb) are more likely to regulate gene transcript than larger variants (p-value = 2.04e-08). Our results support the validity of the computational framework to detect novel variants relevant to disease susceptibility studies and provide evidence of the importance of genetic variants in regulatory network studies

Direct gating and mechanical integrity of Drosophila auditory transducers require TRPN1

The elusive transduction channels for hearing are directly gated mechanically by the pull of gating springs. We found that the transient receptor potential (TRP) channel TRPN1 (NOMPC) is essential for this direct gating of Drosophila auditory transduction channels and that the channel-spring complex was disrupted if TRPN1 was lost. Our results identify TRPN1 as a mechanical constituent of the fly's auditory transduction complex that may act as the channel and/or gating spring

Cytochrome P450 1 genes in birds : evolutionary relationships and transcription profiles in chicken and Japanese quail embryos

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 6 (2011): e28257, doi:10.1371/journal.pone.0028257.Cytochrome P450 1 (CYP1) genes are biomarkers for aryl hydrocarbon receptor (AHR) agonists and may be involved in some of their toxic effects. CYP1s other than the CYP1As are poorly studied in birds. Here we characterize avian CYP1B and CYP1C genes and the expression of the identified CYP1 genes and AHR1, comparing basal and induced levels in chicken and quail embryos. We cloned cDNAs of chicken CYP1C1 and quail CYP1B1 and AHR1. CYP1Cs occur in several bird genomes, but we found no CYP1C gene in quail. The CYP1C genomic region is highly conserved among vertebrates. This region also shares some synteny with the CYP1B region, consistent with CYP1B and CYP1C genes deriving from duplication of a common ancestor gene. Real-time RT-PCR analyses revealed similar tissue distribution patterns for CYP1A4, CYP1A5, CYP1B1, and AHR1 mRNA in chicken and quail embryos, with the highest basal expression of the CYP1As in liver, and of CYP1B1 in eye, brain, and heart. Chicken CYP1C1 mRNA levels were appreciable in eye and heart but relatively low in other organs. Basal transcript levels of the CYP1As were higher in quail than in chicken, while CYP1B1 levels were similar in the two species. 3,3′,4,5,5′-Pentachlorobiphenyl induced all CYP1s in chicken; in quail a 1000-fold higher dose induced the CYP1As, but not CYP1B1. The apparent absence of CYP1C1 in quail, and weak expression and induction of CYP1C1 in chicken suggest that CYP1Cs have diminishing roles in tetrapods; similar tissue expression suggests that such roles may be met by CYP1B1. Tissue distribution of CYP1B and CYP1C transcripts in birds resembles that previously found in zebrafish, suggesting that these genes serve similar functions in diverse vertebrates. Determining CYP1 catalytic functions in different species should indicate the evolving roles of these duplicated genes in physiological and toxicological processes.Funding to MEJ and BB was from the Carl Tryggers Stiftelse and The Swedish Research Council Formas. Funding for BRW and JJS was from the United States National Institutes of Health (National Institute of Environmental Health Sciences), grants R01ES015912 and P42ES007381 to JJS

Shared Pattern of Endocranial Shape Asymmetries among Great Apes, Anatomically Modern Humans, and Fossil Hominins

Anatomical asymmetries of the human brain are a topic of major interest because of their link with handedness and cognitive functions. Their emergence and occurrence have been extensively explored in human fossil records to document the evolution of brain capacities and behaviour. We quantified for the first time antero-posterior endocranial shape asymmetries in large samples of great apes, modern humans and fossil hominins through analysis of “virtual” 3D models of skull and endocranial cavity and we statistically test for departures from symmetry. Once based on continuous variables, we show that the analysis of these brain asymmetries gives original results that build upon previous analysis based on discrete traits. In particular, it emerges that the degree of petalial asymmetries differs between great apes and hominins without modification of their pattern. We indeed demonstrate the presence of shape asymmetries in great apes, with a pattern similar to modern humans but with a lower variation and a lower degree of fluctuating asymmetry. More importantly, variations in the position of the frontal and occipital poles on the right and left hemispheres would be expected to show some degree of antisymmetry when population distribution is considered, but the observed pattern of variation among the samples is related to fluctuating asymmetry for most of the components of the petalias. Moreover, the presence of a common pattern of significant directional asymmetry for two components of the petalias in hominids implicates that the observed traits were probably inherited from the last common ancestor of extant African great apes and Homo sapiens

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p

A Temporal Gate for Viral Enhancers to Co-opt Toll-Like-Receptor Transcriptional Activation Pathways upon Acute Infection

Viral engagement with macrophages activates Toll-Like-Receptors (TLRs) and viruses must contend with the ensuing inflammatory responses to successfully complete their replication cycle. To date, known counter-strategies involve the use of viral-encoded proteins that often employ mimicry mechanisms to block or redirect the host response to benefit the virus. Whether viral regulatory DNA sequences provide an opportunistic strategy by which viral enhancer elements functionally mimic innate immune enhancers is unknown. Here we find that host innate immune genes and the prototypical viral enhancer of cytomegalovirus (CMV) have comparable expression kinetics, and positively respond to common TLR agonists. In macrophages but not fibroblasts we show that activation of NFκB at immediate-early times of infection is independent of virion-associated protein, M45. We find upon virus infection or transfection of viral genomic DNA the TLR-agonist treatment results in significant enhancement of the virus transcription-replication cycle. In macrophage time-course infection experiments we demonstrate that TLR-agonist stimulation of the viral enhancer and replication cycle is strictly delimited by a temporal gate with a determined half-maximal time for enhancer-activation of 6 h; after which TLR-activation blocks the viral transcription-replication cycle. By performing a systematic siRNA screen of 149 innate immune regulatory factors we identify not only anticipated anti-viral and pro-viral contributions but also new factors involved in the CMV transcription-replication cycle. We identify a central convergent NFκB-SP1-RXR-IRF axis downstream of TLR-signalling. Activation of the RXR component potentiated direct and indirect TLR-induced activation of CMV transcription-replication cycle; whereas chromatin binding experiments using wild-type and enhancer-deletion virus revealed IRF3 and 5 as new pro-viral host transcription factor interactions with the CMV enhancer in macrophages. In a series of pharmacologic, siRNA and genetic loss-of-function experiments we determined that signalling mediated by the TLR-adaptor protein MyD88 plays a vital role for governing the inflammatory activation of the CMV enhancer in macrophages. Downstream TLR-regulated transcription factor binding motif disruption for NFκB, AP1 and CREB/ATF in the CMV enhancer demonstrated the requirement of these inflammatory signal-regulated elements in driving viral gene expression and growth in cells as well as in primary infection of neonatal mice. Thus, this study shows that the prototypical CMV enhancer, in a restricted time-gated manner, co-opts through DNA regulatory mimicry elements, innate-immune transcription factors to drive viral expression and replication in the face of on-going pro-inflammatory antiviral responses in vitro and in vivo and; suggests an unexpected role for inflammation in promoting acute infection and has important future implications for regulating latency