Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood

We consider the problem of discriminative factor analysis for data that are in general non-Gaussian. A Bayesian model based on the ranks of the data is proposed. We first introduce a new {\em max-margin} version of the rank-likelihood. A discriminative factor model is then developed, integrating the max-margin rank-likelihood and (linear) Bayesian support vector machines, which are also built on the max-margin principle. The discriminative factor model is further extended to the {\em nonlinear} case through mixtures of local linear classifiers, via Dirichlet processes. Fully local conjugacy of the model yields efficient inference with both Markov Chain Monte Carlo and variational Bayes approaches. Extensive experiments on benchmark and real data demonstrate superior performance of the proposed model and its potential for applications in computational biology.Comment: 14 pages, 7 figures, ICML 201

Meiosis-specific gene discovery in plants: RNA-Seq applied to isolated Arabidopsis male meiocytes

<p>Abstract</p> <p>Background</p> <p>Meiosis is a critical process in the reproduction and life cycle of flowering plants in which homologous chromosomes pair, synapse, recombine and segregate. Understanding meiosis will not only advance our knowledge of the mechanisms of genetic recombination, but also has substantial applications in crop improvement. Despite the tremendous progress in the past decade in other model organisms (e.g., <it>Saccharomyces cerevisiae </it>and <it>Drosophila melanogaster</it>), the global identification of meiotic genes in flowering plants has remained a challenge due to the lack of efficient methods to collect pure meiocytes for analyzing the temporal and spatial gene expression patterns during meiosis, and for the sensitive identification and quantitation of novel genes.</p> <p>Results</p> <p>A high-throughput approach to identify meiosis-specific genes by combining isolated meiocytes, RNA-Seq, bioinformatic and statistical analysis pipelines was developed. By analyzing the studied genes that have a meiosis function, a pipeline for identifying meiosis-specific genes has been defined. More than 1,000 genes that are specifically or preferentially expressed in meiocytes have been identified as candidate meiosis-specific genes. A group of 55 genes that have mitochondrial genome origins and a significant number of transposable element (TE) genes (1,036) were also found to have up-regulated expression levels in meiocytes.</p> <p>Conclusion</p> <p>These findings advance our understanding of meiotic genes, gene expression and regulation, especially the transcript profiles of MGI genes and TE genes, and provide a framework for functional analysis of genes in meiosis.</p

A Metabolomic Endotype of Bioenergetic Dysfunction Predicts Mortality in Critically Ill Patients with Acute Respiratory Failure

Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors\u27 biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition

Worldwide Prevalence of Lentivirus Infection in Wild Feline Species: Epidemiologic and Phylogenetic Aspects

The natural occurrence of lentiviruses closely related to feline immunodeficiency virus (FIV) in nondomestic felid species is shown here to be worldwide. Cross-reactive antibodies to FIV were common in several free-ranging populations of large cats, including East African lions and cheetahs of the Serengeti ecosystem and in puma (also called cougar or mountain lion) populations throughout North America. Infectious puma lentivirus (PLV) was isolated from several Florida panthers, a severely endangered relict puma subspecies inhabiting the Big Cypress Swamp and Everglades ecosystems in southern Florida. Phylogenetic analysis of PLV genomic sequences from disparate geographic isolates revealed appreciable divergence from domestic cat FIV sequences as well as between PLV sequences found in different North American locales. The level of sequence divergence between PLV and FIV was greater than the level of divergence between human and certain simian immunodeficiency viruses, suggesting that the transmission of FIV between feline species is infrequent and parallels in time the emergence of HIV from simian ancestors

Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis.

Background: Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes. Methods: The cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated. Results: Two hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74. Conclusions: To our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool

Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis.

Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of human genetics, patient metabolite and cytokine measurements, and testing in a mouse model demonstrate that the methionine salvage pathway is a regulator of sepsis that can accurately predict prognosis in patients. Pathway-based genome-wide association analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide polymorphisms near the components of the methionine salvage pathway. Measurement of the pathway's substrate, methylthioadenosine (MTA), in two cohorts of sepsis patients demonstrated increased plasma MTA in nonsurvivors. Plasma MTA was correlated with levels of inflammatory cytokines, indicating that elevated MTA marks a subset of patients with excessive inflammation. A machine-learning model combining MTA and other variables yielded approximately 80% accuracy (area under the curve) in predicting death. Furthermore, mice infected with Salmonella had prolonged survival when MTA was administered before infection, suggesting that manipulating MTA levels could regulate the severity of the inflammatory response. Our results demonstrate how combining genetic data, biomolecule measurements, and animal models can shape our understanding of disease and lead to new biomarkers for patient stratification and potential therapeutic targeting

Discriminative Value of Inflammatory Biomarkers for Suspected Sepsis

Circulating biomarkers can facilitate sepsis diagnosis enabling early management and improved outcomes. Procalcitonin (PCT) has been suggested to have superior diagnostic utility compared to other biomarkers

Swift follow-up observations of candidate gravitational-wave transient events

We present the first multi-wavelength follow-up observations of two candidate gravitational-wave (GW) transient events recorded by LIGO and Virgo in their 2009-2010 science run. The events were selected with low latency by the network of GW detectors and their candidate sky locations were observed by the Swift observatory. Image transient detection was used to analyze the collected electromagnetic data, which were found to be consistent with background. Off-line analysis of the GW data alone has also established that the selected GW events show no evidence of an astrophysical origin; one of them is consistent with background and the other one was a test, part of a "blind injection challenge". With this work we demonstrate the feasibility of rapid follow-ups of GW transients and establish the sensitivity improvement joint electromagnetic and GW observations could bring. This is a first step toward an electromagnetic follow-up program in the regime of routine detections with the advanced GW instruments expected within this decade. In that regime multi-wavelength observations will play a significant role in completing the astrophysical identification of GW sources. We present the methods and results from this first combined analysis and discuss its implications in terms of sensitivity for the present and future instruments.Comment: Submitted for publication 2012 May 25, accepted 2012 October 25, published 2012 November 21, in ApJS, 203, 28 ( http://stacks.iop.org/0067-0049/203/28 ); 14 pages, 3 figures, 6 tables; LIGO-P1100038; Science summary at http://www.ligo.org/science/Publication-S6LVSwift/index.php ; Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p110003

Search for gravitational waves associated with the InterPlanetary Network short gamma ray bursts

We outline the scientific motivation behind a search for gravitational waves associated with short gamma ray bursts detected by the InterPlanetary Network (IPN) during LIGO's fifth science run and Virgo's first science run. The IPN localisation of short gamma ray bursts is limited to extended error boxes of different shapes and sizes and a search on these error boxes poses a series of challenges for data analysis. We will discuss these challenges and outline the methods to optimise the search over these error boxes.Comment: Methods paper; Proceedings for Eduardo Amaldi 9 Conference on Gravitational Waves, July 2011, Cardiff, U