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Respiration experiments with high-yielding dairy cows in Northern Ireland have shown higher energy maintenance requirements than those used in the requirements standards of, e.g. France, UK, USA and Germany. Therefore, the current net energy for lactation (NEL) system of Germany was tested by comparing measured NEL intake with calculated NEL requirements based on a comprehensive dataset from feeding trials conducted at nine research institutions in Germany, Austria and Switzerland. The relationship between NEL requirements and NEL intake is described by the equation: NELrequirementsMJ/d=26.6±0.4+0.82±0.004⋅NELintakeMJ/dwithCoefficient of Determination R2=0.677,Root Mean Square Error RMSE =15.9 MJ NEL. The equation indicates a systematic over-estimation of NEL requirements in the lower performance range and an under-estimation at higher energy intake levels. A multiple regression analysis was conducted by calculating metabolisable energy (ME) requirements [MJ/d] using metabolic body size (MBS) [kg0.75], milk energy performance (LE) [MJ/d] and body weight change (BWC) [kg/d]: ​​​​​​​MEintake(MEI)[MJ]=0.651(±0.004)⋅MBS+1.37(±0.006)⋅LE+16.6(±0.31)⋅BWC withR2=0.717,RMSE=24.0 MJ. These results indicate that the energy maintenance requirements are markedly higher than presumed in the feed evaluation systems commonly in use but confirm the results from Northern Ireland (0.600-0.660 MJ ME/kg0.75 MBS). ME efficiency for lactation is also higher (kL = 1/1.37 = 0.73) than that used in the systems and is also similar to the results of Northern Ireland with 0.64-0.69. The energy contribution of BWC derived by this equation is 12.1 MJ/kg (16.6 · 0.73) and distinctly lower than that of 21-25 MJ/kg presumed by the feeding standards, e.g. in Germany. Further, maintenance requirements were linked to milk yield (energy corrected milk (ECM) [kg/d]), as is practiced in the standard Australian energy system: ​​​​​​​(MEI)[MJ]=0.640 +0.0070⋅ ECM)]⋅MBS+1.12)⋅LE +16.7⋅ BWC withR2=0.719,RMSE=24.0 MJ. These results demonstrate that maintenance energy requirements are partly dependent on milk yield. A differentiated analysis by stage of lactation showed that the regressions coefficients for MBS, LE and BWC change with lactation month; however, these findings apply especially to the first lactation months (i.e. in phases of intensive mobilisation).

Preimplantation embryos are sensitive to maternal hormones affecting embryonic signal transduction and metabolic functions. We examined whether adiponectin, the most abundantly secreted adipokine, can influence glucose transport in mouse embryonic cells. In mouse blastocysts full-length adiponectin stimulated glucose uptake, while no effect of globular adiponectin was found. Full-length adiponectin stimulated translocation of GLUT8 glucose transporter to the cell membrane; we did not detect significant changes in the intracellular localization of GLUT4 glucose transporter in adiponectin-treated blastocysts. To study adiponectin signaling in detail, we used embryoid bodies formed from mouse embryonic carcinoma cell (ECC) line P19. We confirmed the expression of adiponectin receptors in these cells. Similar to mouse blastocysts, full-length adiponectin, but not globular adiponectin, stimulated glucose uptake in ECC P19 embryoid bodies. Moreover, full-length adiponectin stimulated AMPK and p38 MAPK phosphorylation. These results indicate that besides AMPK, p38 MAPK is a potential target of adiponectin in mouse embryonic cells. AMPK inhibitor did not influence the adiponectin-stimulated p38 MAPK phosphorylation, indicating independent action of these two signaling pathways. In mouse embryos adiponectin acts as a hormonal regulator of glucose uptake, which becomes especially important in phases with reduced levels of circulating insulin. Our results suggest that adiponectin maintains the glucose supply for early embryos under hypoinsulinaemic conditions, for example, in mothers suffering from type 1 diabetes mellitus.

This white paper explores the considerations of standards-based interoperability of medical images between organizations, patients, and providers. In this paper, we will look at three different standards-based image exchange implementations that have been deployed to facilitate exchange of images between provider organizations. The paper will describe how each implementation uses applicable technology and standards; the image types that are included; and the governance policies that define participation, access, and trust. Limitations of the solution or non-standard approaches to solve challenges will also be identified. Much can be learned from successes elsewhere, and those learnings will point to recommendations of best practices to facilitate the adoption of image exchange.

Patient-derived organoids resemble the biology of tissues and tumors, enabling ex vivo modeling of human diseases. They have heterogeneous morphologies with unclear biological causes and relationship to treatment response. Here, we use high-throughput, image-based profiling to quantify phenotypes of over 5 million individual colorectal cancer organoids after treatment with >500 small molecules. Integration of data using multi-omics modeling identifies axes of morphological variation across organoids: Organoid size is linked to IGF1 receptor signaling, and cystic vs. solid organoid architecture is associated with LGR5 + stemness. Treatment-induced organoid morphology reflects organoid viability, drug mechanism of action, and is biologically interpretable. Inhibition of MEK leads to cystic reorganization of organoids and increases expression ofLGR5, while inhibition of mTOR induces IGF1 receptor signaling. In conclusion, we identify shared axes of variation for colorectal cancer organoid morphology, their underlying biological mechanisms, and pharmacological interventions with the ability to move organoids along them.

The core of grammar-based test suite construction algorithms is a procedure to derive a set of specific phrases, which are then converted into sentences that can be fed into the system under test. This process includes several degrees of freedom and different implementations choose different but ultimately fixed solutions. We show that these fixed choices inherently bias the generated test suite. We quantify these biases and evaluate the effect they have on coverage over the system under test for which the test suite is constructed. We show that the effect of these biases remains prevalent in large real world grammars and systems, even when the test suites grow very large.

We describe the first approach to automatically repair bugs in context-free grammars: given a grammar that fails some tests in a given test suite, we iteratively and gradually transform the grammar until it passes all tests. Our core idea is to build on spectrum-based fault localization to identify promising repair sites (i.e., specific positions in rules), and to apply grammar patches at these sites whenever they satisfy explicitly formulated pre-conditions necessary to potentially improve the grammar. We have implemented this approach in the gfixr system, and successfully used it to fix grammars students submitted as homeworks in a compiler engineering course, and to map one Pascal dialect grammar against another dialect. gfixr can be configured to explore the repair space in different ways, and can also take advantage of counterexamples to enable restriction patches that make the grammar less permissive.

Statistik für Einsteiger*innen Die Autor*innen stellen hier grundlegende statistische Verfahren vor. Mit diesen Verfahren können bildungswissenschaftliche Fragestellungen über Zusammenhang, Unterschied oder Veränderung auf Basis von Stichprobendaten beantwortet werden. Die statistischen Grundideen, Kennwerte und Verfahrensweisen werden kleinschrittig hergeleitet, sodass ein tiefes Verständnis für ihre Bedeutung erlangt wird. Durch Übungsaufgaben wird das erlernte Wissen angewendet und gefestigt. Selbst wenn Ihnen Mathematik nicht zufliegt, haben Sie nach der Erarbeitung dieses Buches keinen Grund mehr, Statistik zu fürchten, sondern werden Statistik als ein nützliches Werkzeug für Studium und Forschung zu schätzen wissen.

Climate and weather data play an important role for e.g. identifying actions against climate change and optimizing industries. However, a correct understanding and handling of such data is often difficult for users without a meteorological background. Moreover, specialized software solutions and an infrastructure capable of handling large amounts of data are needed to process and analyze these data. The research project FAIR addresses this issue by simplifying the exchange of information and data between the German Meteorological Service (DWD) and stakeholders from industry and public. To fulfill this purpose, microservices for processing, caching, visualizing, and analyzing meteorological data in an efficient way are being developed. Processing comprises, for example, the selection of specific information from model data or the conversion of the result into formats commonly used by the user. The compilation of microservices makes it possible to support different types of applications and at the same time to make data from third parties available to the DWD. To demonstrate the utility of these microservices, three test scenarios are considered: 1) wind farm planning, 2) integration of meteorological data for individual traffic routing, and 3) planning of social events such as festivals. In this article, we present the general idea and the current state of the project. The focus is on the challenges that have been identified for the three test scenarios and our technical approaches to address them. Herein we present the developed architecture, the data flow, the FAIR portal and the handling of metadata.

MicroRNAs are promising biological markers for prenatal diagnosis. They regulate placental development and are present in maternal plasma. Maternal metabolic diseases are major risk factors for placental deterioration. We analysed the influence of a maternal insulin-dependent diabetes mellitus on microRNA expression in maternal plasma and in blastocysts employing an in vivo rabbit diabetic pregnancy model and an in vitro embryo culture in hyperglycaemic and hypoinsulinaemic medium. Maternal diabetes led to a marked downregulation of Dicer protein in embryoblast cells and Drosha protein in trophoblast cells. MiR-27b, miR-141 and miR-191 were decreased in trophoblast cells and in maternal plasma of diabetic rabbits. In vitro studies indicate, that maternal hyperglycaemia and hypoinsulinaemia partially contribute to the downregulation of trophoblastic microRNAs. As the altered microRNA expression was detectable in maternal plasma, too, the plasma microRNA signature could serve as an early biological marker for the prediction of trophoblast function during a diabetic pregnancy.

Dynamically typed languages languages are very well suited for rapid prototyping, agile programming methodologies and rapidly evolving software. However, programmers can still benefit from the ability to detect type errors in their code early, in particular if this does not impose restrictions on their programming style.In this paper we describe a new type checking system that identifies potential type errors in such languages through a flow-sensitive static analysis. It computes for every expression the variable’s present (from the values that it has last been assigned) and future (with which it is used in the further program execution) types, respectively. Using this information, the mechanism inserts type checks at strategic points in the original program. We prove that these checks are inserted as early as possible and preempt type errors earlier than existing type systems. We further show that these checks do not change the semantics of programs that do not raise type errors.Preemptive type checking can be added to existing languages without the need to modify the existing runtime environment. Instead, it can be invoked at a very late stage, after the compilation to bytecode and initialisation of the program. We demonstrate an implementation of this for the Python language, and its effectiveness on a number of standard benchmarks.

Im bewusstseinsphilosophischen Fundament von identitats-, sozial- und kulturpolitischen Positionierungen spielen anerkennungstheoretische Uberlegungen seit der Mitte des 20. Jahrhunderts eine bedeutende Rolle. Die wichtigsten Ansatze borgen Kerngedanken aus der Hochphase des deutschen Idealismus und berufen sich haufig auf die Herr / Knecht-Dialektik aus Georg Wilhelm Friedrich Hegels ›Phanomenologie des Geistes‹ (1807).

We report on our experience in using various grammar-based test suite generation methods to test 61 single-pass compilers that undergraduate students submitted for the practical project of a computer architecture course. We show that (1) all test suites constructed systematically following different grammar coverage criteria fall far behind the instructor's test suite in achieved code coverage, in the number of triggered semantic errors, and in detected failures and crashes; (2) a medium-sized positive random test suite triggers more crashes than the instructor's test suite, but achieves lower code coverage and triggers fewer non-crashing errors; and (3) a combination of the systematic and random test suites performs as well or better than the instructor's test suite in all aspects and identifies errors or crashes in every single submission. We then develop a light-weight extension of the basic grammar-based testing framework to capture contextual constraints, by encoding scoping and typing information as ``semantic mark-up tokens'' in the grammar rules. These mark-up tokens are interpreted by a small generic core engine when the tests are rendered, and tests with a syntactic structure that cannot be completed into a valid program by choosing appropriate identifiers are discarded. % We formalize individual error models by overwriting individual mark-up tokens, and generate tests that are guaranteed to break specific contextual properties of the language. We show that a fully automatically generated random test suite with 15 error models achieves roughly the same coverage as the instructor's test suite, and outperforms it in the number of triggered semantic errors and detected failures and crashes. Moreover, all failing tests indicate real errors, and we have detected errors even in the instructor's reference implementation.

We describe gtutr, an interactive feedback system designed to assist students in developing context-free grammars and corresponding ANTLR parsers. It intelligently controls students' access to a large test suite for the target language. After each submission, gtutr analyzes any failing tests and uses the Needleman-Wunsch sequence alignment algorithm over the tests' rule traces to identify and eliminate similar failing tests. This reduces the redundancy in the feedback given to the students and prevents them from being overloaded. gtutr uses simple gamification to encourage independent problem solving by students: it gives as little information as possible, and students need to prompt the system for further details such as failing tests similar to or different from already seen tests, or even for hints about rules that are the most likely to contain faults. It tracks the students' information requests and uses this to attenuate marks following an instructor-set penalty schema. The system also visualizes test outcomes over multiple submissions, helping students to keep track of the effects of their changes as their grammar development progresses.

Katharina Doderlein untersucht in ihrer Heidelberger Dissertation anhand von funf Prosatexten die Diskrepanz zwischen Recht und Rechtsgefuhl. Historische und systematische Bedeutungspotenziale von Recht, Gefuhl und Rechtsgefuhl sind in der juristischen Praxis und zumal in fiktiven Welten kontextabhangig und auf komplizierte Weise miteinander verschrankt. Doderlein setzt diesem Befund ein kenntnisreiches Theoriekapitel entgegen, in dem sie die Bedeutungsbreite der drei Begriffe in einschlagigen Disziplinen diskutiert.

The aryl hydrocarbon receptor (AhR) has been extensively characterized as an environmental sensor with major roles in xenobiotic-induced toxicity. Evidence is accumulating that these functions serve as adaptive mechanisms overlapping its physiological roles. We previously described a critical role of constitutive AhR activation for the correct progress of mammalian oocyte maturation but the signaling pathway through which AhR controls maturation remains unclear. The aim of this study was to investigate whether the AhR interacts with the epidermal growth factor receptor (EGFR) and p42/44 extracellular regulated kinases (ERK1/2), both key factors in the signaling network that finely regulates the oocyte maturation. As experimental model we used bovine cumulus-oocyte complexes (COCs) during in vitro maturation (IVM). Blocking ERK1/2 signaling in COCs during IVM with the specific EGFR inhibitor AG1478 or the mitogen-activated protein kinase kinase (MEK) inhibitor PD98059 downregulated the expression of the AhR-target gene Cyp1a1. Inhibition of AhR activity was associated with a reduction in the oocytes’ ability to progress in meiosis resumption. In contrast, exposure to the AhR antagonist resveratrol reduced both CYP1A1 expression and the oocytes’ maturation competence, without affecting ERK1/2 signaling. These findings strongly indicate the EGFR/ERKs signaling network as an upstream regulator of the AhR activation in COCs, offering a new understanding of the finely tuned physiological mechanism leading to oocyte maturation. This information may provide fresh opportunities for improving oocyte in vitro maturation, and therefore boosting the efficiency of assisted reproduction techniques in mammals.

The Peroxiredoxin 1 (PRDX1) gene maps to chromosome arm 1p and is hemizygously deleted and epigenetically silenced in isocitrate dehydrogenase 1 or 2 (IDH)-mutant and 1p/19q-codeleted oligodendroglial tumors. In contrast, IDH-wildtype astrocytic gliomas including glioblastomas mostly lack epigenetic silencing and express PRDX1 protein. In our study, we investigated how PRDX1 contributes to the infiltrative growth of IDH-wildtype gliomas. Focusing on p38α-dependent pathways, we analyzed clinical data from 133 patients of the NOA-04 trial cohort to look for differences in the gene expression profiles of gliomas with wildtype or mutant IDH. Biochemical interaction studies as well as in vitro and ex vivo migration studies were used to establish a biological role of PRDX1 in maintaining pathway activity. Whole-brain high-resolution ultramicroscopy and survival analyses of pre-clinical mouse models for IDH-wildtype gliomas were then used for in vivo confirmation. Based on clinical data, we found that the absence of PRDX1 is associated with changes in the expression of MET/HGF signaling components. PRDX1 forms a heterodimer with p38α mitogen-activated protein kinase 14 (MAPK14), stabilizing phospho-p38α in glioma cells. This process amplifies hepatocyte growth factor (HGF)-mediated signaling and stimulates actin cytoskeleton dynamics that promote glioma cell migration. Whole-brain high-resolution ultramicroscopy confirms these findings, indicating that PRDX1 promotes glioma brain invasion in vivo. Finally, reduced expression of PRDX1 increased survival in mouse glioma models. Thus, our preclinical findings suggest that PRDX1 expression levels may serve as a molecular marker for patients who could benefit from targeted inhibition of MET/HGF signaling.

Fault localisation, i.e. the identification of program locations that cause errors, takes significant effort and cost. We describe a fast model-based fault localisation algorithm that, given a test suite, uses symbolic execution methods to fully automatically identify a small subset of program locations where genuine program repairs exist. Our algorithm iterates over failing test cases and collects locations where an assignment change can repair exhibited faulty behaviour. Our main contribution is an improved search through the test suite, reducing the effort for the symbolic execution of the models and leading to speed-ups of more than two orders of magnitude over the previously published implementation by Griesmayer et al. We implemented our algorithm for C programs, using the KLEE symbolic execution engine, and demonstrate its effectiveness on the Siemens TCAS variants. Its performance is in line with recent alternative model-based fault localisation techniques, but narrows the location set further without rejecting any genuine repair locations where faults can be fixed by changing a single assignment. We also show how our tool can be used in an educational context to improve self-guided learning and accelerate assessment. We apply our algorithm to a large selection of actual student coursework submissions, providing precise localisation within a sub-second response time. We show this using small test suites, already provided in the coursework management system, and on expanded test suites, demonstrating the scalability of our approach. We also show compliance with test suites does not reliably grade a class of “almost-correct” submissions, which our tool highlights, as being close to the correct answer. Finally, we show an extension to our tool that extends our fast localisation results to a selection of student submissions that contain two faults.

Context: version control repositories contain a wealth of implicit information that can be used to answer many questions about a projects development process. However, this information is not directly accessible in the repositories and must be extracted and visualized.Objective: the main objective of this work is to develop a flexible and generic interactive visualization engine called ConceptCloud that supports exploratory search in version control repositories.Method: ConceptCloud is a flexible, interactive browser for SVN and Git repositories. Its main novelty is the combination of an intuitive tag cloud visualization with an underlying concept lattice that provides a formal structure for navigation. ConceptCloud supports concurrent navigation in multiple linked but individually customizable tag clouds, which allows for multi-faceted repository browsing, and scriptable construction of unique visualizations.Results: we describe the mathematical foundations and implementation of our approach and use ConceptCloud to quickly gain insight into the team structure and development process of three projects. We perform a user study to determine the usability of ConceptCloud. We show that untrained participants are able to answer historical questions about a software project better using ConceptCloud than using a linear list of commits.Conclusion: ConceptCloud can be used to answer many difficult questions such as What has happened in this project while I was away? and Which developers collaborate?. Tag clouds generated from our approach provide a visualization in which version control data can be aggregated and explored interactively.

RNA-binding proteins (RBPs) play essential roles in RNA biology, responding to cellular and environmental stimuli to regulate gene expression. Important advances have helped to determine the (near) complete repertoires of cellular RBPs. However, identification of RBPs associated with specific transcripts remains a challenge. Here, we describe “specific ribonucleoprotein (RNP) capture,” a versatile method for the determination of the proteins bound to specific transcripts in vitro and in cellular systems. Specific RNP capture uses UV irradiation to covalently stabilize protein–RNA interactions taking place at “zero distance.” Proteins bound to the target RNA are captured by hybridization with antisense locked nucleic acid (LNA)/DNA oligonucleotides covalently coupled to a magnetic resin. After stringent washing, interacting proteins are identified by quantitative mass spectrometry. Applied to in vitro extracts, specific RNP capture identifies the RBPs bound to a reporter mRNA containing the Sex-lethal (Sxl) binding motifs, revealing that the Sxl homolog sister of Sex lethal (Ssx) displays similar binding preferences. This method also revealed the repertoire of RBPs binding to 18S or 28S rRNAs in HeLa cells, including previously unknown rRNA-binding proteins.

Acquiring an overview of an unfamiliar discipline and exploring relevant papers and journals is often a laborious task for researchers. In this paper we show how exploratory search can be supported on a large collection of academic papers to allow users to answer complex scientometric questions which traditional retrieval approaches do not support optimally. We use our ConceptCloud browser, which makes use of a combination of concept lattices and tag clouds, to visually present academic publication data (specifically, the ACM Digital Library) in a browsable format that facilitates exploratory search. We augment this dataset with semantic categories, obtained through automatic keyphrase extraction from papers’ titles and abstracts, in order to provide the user with uniform keyphrases of the underlying data collection. We use the citations and references of papers to provide additional mechanisms for exploring relevant research by presenting aggregated reference and citation data not only for a single paper but also across topics, authors and journals, which is novel in our approach. We conduct a user study to evaluate our approach in which we asked 34 participants, from different academic backgrounds with varying degrees of research experience, to answer a variety of scientometric questions using our ConceptCloud browser. Participants were able to answer complex scientometric questions using our ConceptCloud browser with a mean correctness of 73%, with the user’s prior research experience having no statistically significant effect on the results.

We describe and evaluate the first spectrum-based fault localization method aimed at finding faulty rules in a context-free grammar. It takes as input a test suite and a modified parser for the grammar that can collect grammar spectra, i.e., the sets of rules used in attempts to parse the individual test cases, and returns as output a ranked list of suspicious rules. We show how grammar spectra can be collected for both LL and LR parsers, and how the ANTLR and CUP parser generators can be modified and used to automate the collection of the grammar spectra. We evaluate our method over grammars with seeded faults as well as real world grammars and student grammars submitted in compiler engineering courses that contain real faults. The results show that our method ranks the seeded faults within the top five rules in more than half of the cases and can pinpoint them in 10%–40% of the cases. On average, it ranks the faults at around 25% of all rules, and better than 15% for a very large test suite. It also allowed us to identify deviations and faults in the real world and student grammars.

Grammar-based test case generation has focused almost exclusively on generating syntactically correct programs (i.e., positive tests) from a context-free reference grammar but a positive test suite cannot detect when the unit under test accepts words outside the language (i.e., false positives). Here, we investigate the converse problem and describe two mutation-based approaches for generating programs with guaranteed syntax errors (i.e., negative tests). % Word mutation systematically modifies positive tests by deleting, inserting, substituting, and transposing tokens in such a way that at least one impossible token pair emerges. % Rule mutation applies such operations to the symbols of the right-hand sides of productions in such a way that each derivation that uses the mutated rule yields a word outside the language.

Patient derived organoids resemble the biology of tissues and tumors, enablingex vivomodeling of human diseases from primary patient samples. Organoids can be used as models for drug discovery and are being explored to guide clinical decision making. Patient derived organoids can have heterogeneous morphologies with unclear biological causes and relationship to treatment response. Here, we used high-throughput, image-based profiling to quantify phenotypes of over 5 million individual colorectal cancer organoids after treatment with more than 500 small molecules. Integration of data using a joint multi-omics modelling framework identified organoid size and cystic vs. solid organoid architecture as axes of morphological variation across organoids. Mechanistically, we found that organoid size was linked to IGF1 receptor signaling, while a cystic organoid architecture was associated with an LGR5+ stemness program. Treatment-induced organoid morphology reflected organoid viability, drug mechanism of action, and was biologically interpretable using joint modelling. Inhibition of MEK led to cystic reorganization of organoids and increased expression of LGR5, while inhibition of mTOR induced IGF1 receptor signaling. In conclusion, we identified shared axes of variation for colorectal cancer organoid morphology, their underlying biological mechanisms, and pharmacological interventions with the ability to move organoids along them. Image-based profiling of patient derived organoids coupled with multi-omics integration facilitates drug discovery by linking drug responses with underlying biological mechanisms.

Whether post-transcriptional regulation of gene expression controls differentiation of stem cells for tissue renewal remains unknown. Quiescent stem cells exhibit a low level of protein synthesis1, which is key to maintaining the pool of fully functional stem cells, not only in the brain but also in the bone marrow and hair follicles2–6. Neurons also maintain a subset of messenger RNAs in a translationally silent state, which react ‘on demand’ to intracellular and extracellular signals. This uncoupling of general availability of mRNA from translation into protein facilitates immediate responses to environmental changes and avoids excess production of proteins, which is the most energy-consuming process within the cell. However, when post-transcriptional regulation is acquired and how protein synthesis changes along the different steps of maturation are not known. Here we show that protein synthesis undergoes highly dynamic changes when stem cells differentiate to neurons in vivo. Examination of individual transcripts using RiboTag mouse models reveals that whereas stem cells translate abundant transcripts with little discrimination, translation becomes increasingly regulated with the onset of differentiation. The generation of neurogenic progeny involves translational repression of a subset of mRNAs, including mRNAs that encode the stem cell identity factors SOX2 and PAX6, and components of the translation machinery, which are enriched in a pyrimidine-rich motif. The decrease of mTORC1 activity as stem cells exit the cell cycle selectively blocks translation of these transcripts. Our results reveal a control mechanism by which the cell cycle is coupled to post-transcriptional repression of key stem cell identity factors, thereby promoting exit from stemness. Sequencing of total and ribosome-associated mRNAs enables identification of specific mRNAs that are differentially translationally regulated along the neuronal stem cell lineage, independently of their availability.

With no antiviral drugs or widely available vaccines, Dengue virus (DENV) constitutes a public health concern. DENV replicates at ER-derived cytoplasmic structures that include substructures called convoluted membranes (CMs); however, the purpose of these membrane alterations remains unclear. We determine that DENV nonstructural protein (NS)4B, a promising drug target with unknown function, associates with mitochondrial proteins and alters mitochondria morphology to promote infection. During infection, NS4B induces elongation of mitochondria, which physically contact CMs. This restructuring compromises the integrity of mitochondria-associated membranes, sites of ER-mitochondria interface critical for innate immune signaling. The spatio-temporal parameters of CM biogenesis and mitochondria elongation are linked to loss of activation of the fission factor Dynamin-Related Protein-1. Mitochondria elongation promotes DENV replication and alleviates RIG-I-dependent activation of interferon responses. As Zika virus infection induces similar mitochondria elongation, this perturbation may protect DENV and related viruses from innate immunity and create a favorable replicative environment.

The mammalian target of rapamycin complex 1 (mTORC1) is known to be a central cellular nutrient sensor and master regulator of protein metabolism; therefore, it is indispensable for normal embryonic development. We showed previously in a diabetic pregnancy that embryonic mTORC1 phosphorylation is increased in case of maternal hyperglycaemia and hypoinsulinaemia. Further, the preimplantation embryo is exposed to increased L-leucine levels during a diabetic pregnancy. To understand how mTOR signalling is regulated in preimplantation embryos, we examined consequences of L-leucine and glucose stimulation on mTORC1 signalling and downstream targets inin vitrocultured preimplantation rabbit blastocysts andin vivo. High levels of L-leucine and glucose lead to higher phosphorylation of mTORC1 and its downstream target ribosomal S6 kinase 1 (S6K1) in these embryos. Further, L-leucine supplementation resulted in higher embryonic expression of genes involved in cell cycle (cyclin D1;CCND1), translation initiation (eukaryotic translation initiation factor 4E;EIF4E), amino acid transport (large neutral amino acid transporter 2; Lat2: geneSLC7A8) and proliferation (proliferating cell nuclear antigen;PCNA) in a mTORC1-dependent manner. Phosphorylation of S6K1 and expression patterns ofCCND1andEIF4Ewere increased in embryos from diabetic rabbits, while the expression of proliferation markerPCNAwas decreased. In these embryos, protein synthesis was increased and autophagic activity was decreased. We conclude that mammalian preimplantation embryos sense changes in nutrient supply via mTORC1 signalling. Therefore, mTORC1 may be a decisive mediator of metabolic programming in a diabetic pregnancy.

A combination of genome-scale RNA interference screening and genetic interaction analysis using process-directed phenotypes is used to assign components to specific pathways and complexes for modulators of mitosis and cytokinesis in Drosophila S2 cells., Cell-based RNA interference (RNAi) is a powerful approach to screen for modulators of many cellular processes. However, resulting candidate gene lists from cell-based assays comprise diverse effectors, both direct and indirect, and further dissecting their functions can be challenging. Here we screened a genome-wide RNAi library for modulators of mitosis and cytokinesis in Drosophila S2 cells. The screen identified many previously known genes as well as modulators that have previously not been connected to cell cycle control. We then characterized ∼300 candidate modifiers further by genetic interaction analysis using double RNAi and a multiparametric, imaging-based assay. We found that analyzing cell cycle–relevant phenotypes increased the sensitivity for associating novel gene function. Genetic interaction maps based on mitotic index and nuclear size grouped candidates into known regulatory complexes of mitosis or cytokinesis, respectively, and predicted previously uncharacterized components of known processes. For example, we confirmed a role for the Drosophila CCR4 mRNA processing complex component l(2)NC136 during the mitotic exit. Our results show that the combination of genome-scale RNAi screening and genetic interaction analysis using process-directed phenotypes provides a powerful two-step approach to assigning components to specific pathways and complexes.

Control of gene expression at the post-transcriptional level is essential in all organisms, and RNA-binding proteins play critical roles from mRNA synthesis to decay. To fully understand this process, it is necessary to identify the complete set of RNA-binding proteins and the functional consequences of the protein-mRNA interactions. Here, we provide an overview of the proteins that bind to mRNAs and their functions in the pathogenic bloodstream form of Trypanosoma brucei. We describe the production of a small collection of open-reading frames encoding proteins potentially involved in mRNA metabolism. With this ORFeome collection, we used tethering to screen for proteins that play a role in post-transcriptional control. A yeast two-hybrid screen showed that several of the discovered repressors interact with components of the CAF1/NOT1 deadenylation complex. To identify the RNA-binding proteins, we obtained the mRNA-bound proteome. We identified 155 high-confidence candidates, including many not previously annotated as RNA-binding proteins. Twenty seven of these proteins affected reporter expression in the tethering screen. Our study provides novel insights into the potential trypanosome mRNPs composition, architecture and function.

ESBMC is a mature, permissively licensed open-source context-bounded model checker for the verification of single- and multi-threaded C programs. It can verify both predefined safety properties (e.g., bounds check, pointer safety, overflow) and user-defined program assertions automatically. ESBMC provides C++ and Python APIs to access internal data structures, allowing inspection and extension at any stage of the verification process. We discuss improvements over previous versions of ESBMC, including the description of new front- and back-ends, IEEE floating-point support, and an improved k-induction algorithm. A demonstration is available at https://www.youtube.com/watch?v=YcJjXHlN1v8.

SUMMARYThe contribution of posttranscriptional regulation of gene expression to neural stem cell differentiation during tissue homeostasis remains elusive. Here we show highly dynamic changes in protein synthesis along differentiation of stem cells to neurons in vivo. Examination of individual transcripts using RiboTag mouse models reveals that neural stem cells efficiently translate abundant transcripts, whereas translation becomes increasingly controlled with the onset of differentiation. Stem cell generation of early neuroblasts involves translational repression of a subset of mRNAs including the stem cell-identity factors Sox2 and Pax6 as well as translation machinery components. In silico motif analysis identifies a pyrimidine-rich motif (PRM) in this repressed subset. A drop in mTORC1 activity at the onset of differentiation selectively blocks translation of PRM-containing transcripts. Our data uncovers how a drop in mTORC1 allows robust simultaneous posttranscriptional repression of key stem cell identity-factors and translation-components and thereby stemness exit and migration.

RNA-binding proteins (RBPs) exert a broad range of biological functions. To explore the scope of RBPs across eukaryotic evolution, we determined the in vivo RBP repertoire of the yeast Saccharomyces cerevisiae and identified 678 RBPs from yeast and additionally 729 RBPs from human hepatocytic HuH-7 cells. Combined analyses of these and recently published data sets define the core RBP repertoire conserved from yeast to man. Conserved RBPs harbour defined repetitive motifs within disordered regions, which display striking evolutionary expansion. Only 60% of yeast and 73% of the human RBPs have functions assigned to RNA biology or structural motifs known to convey RNA binding, and many intensively studied proteins surprisingly emerge as RBPs (termed ‘enigmRBPs'), including almost all glycolytic enzymes, pointing to emerging connections between gene regulation and metabolism. Analyses of the mitochondrial hydroxysteroid dehydrogenase (HSD17B10) uncover the RNA-binding specificity of an enigmRBP., RNA-binding proteins (RBPs) are implicated in many biological functions. Here the authors expand the human and yeast RNA interactome identifying new and conserved RBPs, several of which with no prior function assigned to RNA biology or structural motifs known to mediate RNA-binding, and suggesting new roles of RNA as modulators of protein function.

Distributed memory architectures such as Linux clusters have become increasingly common but remain difficult to program. We target this problem and present a novel technique to automatically generate data distribution plans, and subsequently MPI implementations in C++, from programs written in a functional core language. The main novelty of our approach is that we support distributed arrays, maps, and lists in the same framework, rather than just arrays. We formalize distributed data layouts as types, which are then used both to search (via type inference) for optimal data distribution plans and to generate the MPI implementations. We introduce the core language and explain our formalization of distributed data layouts. We describe how we search for data distribution plans using an adaptation of the Damas---Milner type inference algorithm, and how we generate MPI implementations in C++ from such plans.

Maternal metabolic diseases such as diabetes mellitus with diabetogenic hypoinsulinemia and hyperglycemia change periconceptional developmental conditions in utero. In preimplantation rabbit embryos, all major metabolic pathways are affected. Alterations in protein, lipid and glucose metabolism, adipokines, advanced glycation end products (AGEs) and reactive oxygen species (ROS) are described in this review. The embryonic metabolism is characterized by a high plasticity which enables survival of most preimplantation embryos under the non-physiological developmental conditions in diabetic mothers. Adiponectin, for example, compensates for the missing insulin-driven glucose supply and stimulates intracellular lipid accumulation in embryonic cells. AGEs and ROS are clear indicators of metabolic stress. The price paid for survival, however, needs to be taken into consideration. It is an increase in lipogenesis and proteinogenesis, leading to metabolic stress and with potentially negative long-term health effects.

The Peroxiredoxin 1 (PRDX1) gene maps to chromosome arm 1p and is hemizygously deleted and epigenetically silenced in isocitrate dehydrogenase 1 or 2 (IDH)-mutant and 1p/19q-codeleted oligodendroglial tumors. In contrast, IDH-wildtype astrocytic gliomas including glioblastomas mostly lack epigenetic silencing and express PRDX1 protein. In our study, we investigated how PRDX1 contributes to the infiltrative growth of IDH-wildtype gliomas. Focusing on p38α-dependent pathways, we analyzed clinical data from 133 patients of the NOA-04 trial cohort to look for differences in the gene expression profiles of gliomas with wildtype or mutant IDH. Biochemical interaction studies as well as in vitro and ex vivo migration studies were used to establish a biological role of PRDX1 in maintaining pathway activity. Whole-brain high-resolution ultramicroscopy and survival analyses of pre-clinical mouse models for IDH-wildtype gliomas were then used for in vivo confirmation. Based on clinical data, we found that the absence of PRDX1 is associated with changes in the expression of MET/HGF signaling components. PRDX1 forms a heterodimer with p38α mitogen-activated protein kinase 14 (MAPK14), stabilizing phospho-p38α in glioma cells. This process amplifies hepatocyte growth factor (HGF)-mediated signaling and stimulates actin cytoskeleton dynamics that promote glioma cell migration. Whole-brain high-resolution ultramicroscopy confirms these findings, indicating that PRDX1 promotes glioma brain invasion in vivo. Finally, reduced expression of PRDX1 increased survival in mouse glioma models. Thus, our preclinical findings suggest that PRDX1 expression levels may serve as a molecular marker for patients who could benefit from targeted inhibition of MET/HGF signaling.

The accumulation of advanced glycation end products (AGEs) occurs in ageing and in many degenerative diseases as a final outcome of persistent oxidative stress on cells and organs. Environmental alterations taking place during early embryonic development can also lead to oxidative damage, reactive oxygen species (ROS) production, and AGE accumulation. Whether similar mechanisms act on somatic and embryonic stem cells (ESC) exposed to oxidative stress is not known; and therefore, the modelling of oxidative stress in vitro on human ESC has been the focus of this study. We compared changes in Nε-carboxymethyl-lysine (CML) advanced glycation end products and RAGE levels in hESC versus differentiated somatic cells exposed to H2O2 within the noncytotoxic range. Our data revealed that hESC accumulates CML and RAGE under oxidative stress conditions in different ways than somatic cells, being the accumulation of CML statistically significant only in somatic cells and, conversely, the RAGE increase exclusively appreciated in hESC. Then, following cardiac and neural differentiation, we observed a progressive removal of AGEs and at the same time an elevated activity of the 20S proteasome. We conclude that human ESCs constitute a unique model to study the consequence of an oxidative environment in the pluripotent cells of the embryo during the human preimplantation period.

Lazy sequentialization has proven to be one of the most effective techniques for concurrent program verification. The Lazy-CSeq sequentialization tool performs a “lazy” code-to-code translation from a concurrent program into an equivalent non-deterministic sequential program, i.e., it preserves the valuations of the program variables along its executions. The obtained program is then analyzed using sequential bounded model checking tools. However, the sizes of the individual states still pose problems for further scaling. We therefore use abstract interpretation to minimize the representation of the concurrent program’s (shared global and thread-local) state variables. More specifically, we run the Frama-C abstract interpretation tool over the programs constructed by Lazy-CSeq to compute overapproximating intervals for all (original) state variables and then exploit CBMC’s bitvector support to reduce the number of bits required to represent these in the sequentialized program. We have implemented this approach in the last release of Lazy-CSeq and demonstrate the effectiveness of this approach; in particular, we show that it leads to large performance gains for very hard verification problems.

Maternal metabolic diseases such as diabetes mellitus with diabetogenic hypoinsulinemia and hyperglycemia change periconceptional developmental conditions in utero. In preimplantation rabbit embryos, all major metabolic pathways are affected. Alterations in protein, lipid and glucose metabolism, adipokines, advanced glycation end products (AGEs) and reactive oxygen species (ROS) are described in this review. The embryonic metabolism is characterized by a high plasticity which enables survival of most preimplantation embryos under the non-physiological developmental conditions in diabetic mothers. Adiponectin, for example, compensates for the missing insulin-driven glucose supply and stimulates intracellular lipid accumulation in embryonic cells. AGEs and ROS are clear indicators of metabolic stress. The price paid for survival, however, needs to be taken into consideration. It is an increase in lipogenesis and proteinogenesis, leading to metabolic stress and with potentially negative long-term health effects.

DepthK is a software verification tool that employs a proof by induction algorithm that combines k-induction with invariant inference. In order to efficiently and effectively verify and falsify safety properties in C programs, DepthK infers program invariants using polyhedral constraints. Experimental results show that our approach can handle a wide variety of safety properties in several intricate verification tasks.

Di(2-ethylhexyl)phthalate (DEHP) is the most common plasticizer in plastic devices of everyday use. It is a ubiquitous environmental contaminant and primarily known to impair male gonadal development and fertility. Studies concerning the long-term effects of prenatal DEHP exposure on certain diseases [The Developmental Origins of Health and Disease paradigm (DOHaD) hypothesis] are scarce although it is proven that DEHP crosses the placenta. Rising environmental pollution during the last centuries coincides with an increasing prevalence of cardiovascular and metabolic diseases. We have investigated the effects of an early embryonic DEHP exposure at different developmental stages on cardiomyogenesis. We used an in-vitro model, the murine P19 embryonic carcinoma cell line (P19 ECC), mimicking early embryonic stages up to differentiated beating cardiomyocytes. P19 ECC were exposed to DEHP (5, 50, 100 µg ml–1) at the undifferentiated stage for 5 days and subsequently differentiated to beating cardiomyocytes. We analyzed the expression of metabolic (Pparg1, Fabp4 and Glut4), cardiac (Myh6, Gja1) and methylation (Dnmt1, Dnmt3a) marker genes by quantitative real-time PCR (qRT-PCR), beating rate and the differentiation velocity of the cells. The methylation status of Pparg1, Ppara and Glut4 was investigated by pyrosequencing. DEHP significantly altered the expression of all investigated genes. The beating rate and differentiation velocity were accelerated. Exposure to DEHP led to small but statistically significant increases in methylation of specific CpGs within Ppara and Pparg1, which otherwise were generally hypomethylated, but methylation of Glut4 was unaltered. Early DEHP exposure of P19 ECC alters the expression of genes associated with cellular metabolism and the functional features of cardiomyocytes. Copyright © 2014 John Wiley & Sons, Ltd.