Inter-battery topic representation learning

In this paper, we present the Inter-Battery Topic Model (IBTM). Our approach extends traditional topic models by learning a factorized latent variable representation. The structured representation leads to a model that marries benefits traditionally associated with a discriminative approach, such as feature selection, with those of a generative model, such as principled regularization and ability to handle missing data. The factorization is provided by representing data in terms of aligned pairs of observations as different views. This provides means for selecting a representation that separately models topics that exist in both views from the topics that are unique to a single view. This structured consolidation allows for efficient and robust inference and provides a compact and efficient representation. Learning is performed in a Bayesian fashion by maximizing a rigorous bound on the log-likelihood. Firstly, we illustrate the benefits of the model on a synthetic dataset,. The model is then evaluated in both uni- and multi-modality settings on two different classification tasks with off-the-shelf convolutional neural network (CNN) features which generate state-of-the-art results with extremely compact representations

Global parameter identification of stochastic reaction networks from single trajectories

We consider the problem of inferring the unknown parameters of a stochastic biochemical network model from a single measured time-course of the concentration of some of the involved species. Such measurements are available, e.g., from live-cell fluorescence microscopy in image-based systems biology. In addition, fluctuation time-courses from, e.g., fluorescence correlation spectroscopy provide additional information about the system dynamics that can be used to more robustly infer parameters than when considering only mean concentrations. Estimating model parameters from a single experimental trajectory enables single-cell measurements and quantification of cell--cell variability. We propose a novel combination of an adaptive Monte Carlo sampler, called Gaussian Adaptation, and efficient exact stochastic simulation algorithms that allows parameter identification from single stochastic trajectories. We benchmark the proposed method on a linear and a non-linear reaction network at steady state and during transient phases. In addition, we demonstrate that the present method also provides an ellipsoidal volume estimate of the viable part of parameter space and is able to estimate the physical volume of the compartment in which the observed reactions take place.Comment: Article in print as a book chapter in Springer's "Advances in Systems Biology

Molecular genetics of inherited retinal degenerations in Icelandic patients.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadThe study objective was to delineate the genetics of inherited retinal degenerations (IRDs) in Iceland, a small nation of 364.000 and a genetic isolate. Benefits include delineating novel pathogenic genetic variants and defining genetically homogenous patients as potential investigative molecular therapy candidates. The study sample comprised patients with IRD in Iceland ascertained through national centralized genetic and ophthalmological services at Landspitali, a national social support institute, and the Icelandic patient association. Information on patients' disease, syndrome, and genetic testing was collected in a clinical registry. Variants were reevaluated according to ACMG/AMP guidelines. Overall, 140 IRD patients were identified (point prevalence of 1/2.600), of which 70 patients had a genetic evaluation where two-thirds had an identified genetic cause. Thirteen disease genes were found in patients with retinitis pigmentosa, with the RLBP1 gene most common (n = 4). The c.1073 + 5G > A variant in the PRPF31 gene was homozygous in two RP patients. All tested patients with X-linked retinoschisis (XLRS) had the same possibly unique RS1 pathogenic variant, c.441G > A (p.Trp147X). Pathologic variants and genes for IRDs in Iceland did not resemble those described in ancestral North-Western European nations. Four variants were reclassified as likely pathogenic. One novel pathogenic variant defined a genetically homogenous XLRS patient group. Keywords: Iceland; eye diseases; genetics; hereditary; human genetics; population; retinitis pigmentosa.Icelandic Student Innovation Fund Icelandic Association of the Visually Impaired Richard P. Theodore and Dora Sigurjonsdottir Fund for improving scientific knowledge on blindnes

Integrating isotopes and documentary evidence : dietary patterns in a late medieval and early modern mining community, Sweden

We would like to thank the Archaeological Research Laboratory, Stockholm University, Sweden and the Tandem Laboratory (Ångström Laboratory), Uppsala University, Sweden, for undertaking the analyses of stable nitrogen and carbon isotopes in both human and animal collagen samples. Also, thanks to Elin Ahlin Sundman for providing the δ13C and δ15N values for animal references from Västerås. This research (Bäckström’s PhD employment at Lund University, Sweden) was supported by the Berit Wallenberg Foundation (BWS 2010.0176) and Jakob and Johan Söderberg’s foundation. The ‘Sala project’ (excavations and analyses) has been funded by Riksens Clenodium, Jernkontoret, Birgit and Gad Rausing’s Foundation, SAU’s Research Foundation, the Royal Physiographic Society of Lund, Berit Wallenbergs Foundation, Åke Wibergs Foundation, Lars Hiertas Memory, Helge Ax:son Johnson’s Foundation and The Royal Swedish Academy of Sciences.Peer reviewedPublisher PD

High Temperature Triggers Latent Variation among Individuals: Oviposition Rate and Probability for Outbreaks

It is anticipated that extreme population events, such as extinctions and outbreaks, will become more frequent as a consequence of climate change. To evaluate the increased probability of such events, it is crucial to understand the mechanisms involved. Variation between individuals in their response to climatic factors is an important consideration, especially if microevolution is expected to change the composition of populations.Here we present data of a willow leaf beetle species, showing high variation among individuals in oviposition rate at a high temperature (20 °C). It is particularly noteworthy that not all individuals responded to changes in temperature; individuals laying few eggs at 20 °C continued to do so when transferred to 12 °C, whereas individuals that laid many eggs at 20 °C reduced their oviposition and laid the same number of eggs as the others when transferred to 12 °C. When transferred back to 20 °C most individuals reverted to their original oviposition rate. Thus, high variation among individuals was only observed at the higher temperature. Using a simple population model and based on regional climate change scenarios we show that the probability of outbreaks increases if there is a realistic increase in the number of warm summers. The probability of outbreaks also increased with increasing heritability of the ability to respond to increased temperature.If climate becomes warmer and there is latent variation among individuals in their temperature response, the probability for outbreaks may increase. However, the likelihood for microevolution to play a role may be low. This conclusion is based on the fact that it has been difficult to show that microevolution affect the probability for extinctions. Our results highlight the urge for cautiousness when predicting the future concerning probabilities for extreme population events

Mutations in CEP78 Cause Cone-Rod Dystrophy and Hearing Loss Associated with Primary-Cilia Defects.

Cone-rod degeneration (CRD) belongs to the disease spectrum of retinal degenerations, a group of hereditary disorders characterized by an extreme clinical and genetic heterogeneity. It mainly differentiates from other retinal dystrophies, and in particular from the more frequent disease retinitis pigmentosa, because cone photoreceptors degenerate at a higher rate than rod photoreceptors, causing severe deficiency of central vision. After exome analysis of a cohort of individuals with CRD, we identified biallelic mutations in the orphan gene CEP78 in three subjects from two families: one from Greece and another from Sweden. The Greek subject, from the island of Crete, was homozygous for the c.499+1G>T (IVS3+1G>T) mutation in intron 3. The Swedish subjects, two siblings, were compound heterozygotes for the nearby mutation c.499+5G>A (IVS3+5G>A) and for the frameshift-causing variant c.633delC (p.Trp212Glyfs(∗)18). In addition to CRD, these three individuals had hearing loss or hearing deficit. Immunostaining highlighted the presence of CEP78 in the inner segments of retinal photoreceptors, predominantly of cones, and at the base of the primary cilium of fibroblasts. Interaction studies also showed that CEP78 binds to FAM161A, another ciliary protein associated with retinal degeneration. Finally, analysis of skin fibroblasts derived from affected individuals revealed abnormal ciliary morphology, as compared to that of control cells. Altogether, our data strongly suggest that mutations in CEP78 cause a previously undescribed clinical entity of a ciliary nature characterized by blindness and deafness but clearly distinct from Usher syndrome, a condition for which visual impairment is due to retinitis pigmentosa

Testing MOS precipitation downscaling for ENSEMBLES regional climate models over Spain

Model Output Statistics (MOS) has been recently proposed as an alternative to the standard perfect prognosis statistical downscaling approach for Regional Climate Model (RCM) outputs. In this case, the model output for the variable of interest (e.g. precipitation) is directly downscaled using observations. In this paper we test the performance of a MOS implementation of the popular analog methodology (referred to as MOS analog) applied to downscale daily precipitation outputs over Spain. To this aim, we consider the state‐of‐the‐art ERA40‐driven RCMs provided by the EU‐funded ENSEMBLES project and the Spain02 gridded observations data set, using the common period 1961–2000. The MOS analog method improves the representation of the mean regimes, the annual cycle, the frequency and the extremes of precipitation for all RCMs, regardless of the region and the model reliability (including relatively low‐performing models), while preserving the daily accuracy. The good performance of the method in this complex climatic region suggests its potential transferability to other regions. Furthermore, in order to test the robustness of the method in changing climate conditions, a cross‐validation in driest or wettest years was performed. The method improves the RCM results in both cases, especially in the former

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management