Natural stone deposits in an assemblage of subhorizontal intrusions - The Kuru granite batholith

Short communication, no abstrac

Fluorescent Discrimination between Traces of Chemical Warfare Agents and Their Mimics

An array of fluorogenic probes is able to discriminate between nerve agents, sarin, soman, tabun, VX and their mimics, in water or organic solvent, by qualitative fluorescence patterns and quantitative multivariate analysis, thus making the system suitable for the inthe- field detection of traces of chemical warfare agents as well as to differentiate between the real nerve agents and other related compounds.Ministerio de Economía y Competitividad, Spain (Project CTQ2012- 31611), Junta de Castilla y León, Consejería de Educación y Cultura y Fondo Social Europeo (Project BU246A12-1), the European Commission, Seventh Framework Programme (Project SNIFFER FP7-SEC-2012-312411) and the Swedish Ministry of Defence (no. A403913

4 organisationer och 825 chefer : En studie om chefslösa organisationer

This Bachelor’s thesis is about bossless organizations. We have observed that the hierarchical structure that the majority of organizations is structured by today is a remnant of a time long gone, and can be an obstacle for independent thinking and responsibility inside organizations. We want to question the accepted perception that an organization is best structured in a hierarchic form. The purpose of the thesis is to provide an understanding of how a bossless organization works and to give a concrete explanation of the consequences of this kind of organizational structure. The thesis is of a qualitative nature and is designed with an inductive approach at an organizational level. We conducted a case study on a bossless company and supplemented this with secondary sources from three other bossless organizations. It concludes that the bossless approach can work and that there are a number of advantages to benefit from it. It is based on the intrinsic motivation of the employees and the willingness and ability to be a co-producer of corporate success. Another important conclusion we made is that the function of a boss never disappears, even though the position is removed. The study has shown that the bossless approach seems to be applied to the most types of businesses.Denna uppsats behandlar fenomenet chefslösa organisationer. Vi ser att den hierarkiska struktur som förr krävdes, idag inte fyller sitt syfte och att chefsskap förhindrar självständigt tänkade och ansvarstagande. Vi vill ifrågasätta den vedertagna uppfattningen om att en organisation bör struktureras enligt en hierarkisk modell. Uppsatsen syftar till att ge en förståelse för hur en chefslös organisation fungerar och ge en konkret bild av följderna av att strukturera sig på detta vis. Vi söker även svara på hur överförbar arbetssättet är på organisationer i allmänhet. Studien är av kvalitativ natur och är utförd med en induktiv ansats på en organisatorisk nivå.Vi har genomfört en fallstudie på ett chefslöst företag och kompletterat detta med sekundärkällor från tre andra chefslösa organisationer. Slutsatsen är att det chefslösa arbetssättet kan fungera och att det finns en rad fördelar att dra av det. Det grundar sig på den inre motivation hos de anställda samt viljan och förmågan att vara en medproducent av företags framgång. En annan viktig slutsats är att chefsfunktionen och koordineringsfunktionen aldrig försvinner, trots att positionen i sig plockas bort

Cross-talks via mTORC2 can explain enhanced activation in response to insulin in diabetic patients

The molecular mechanisms of insulin resistance in Type 2 diabetes have been extensively studied in primary human adipocytes, and mathematical modelling has clarified the central role of attenuation of mammalian target of rapamycin (mTOR) complex 1 (mTORC1) activity in the diabetic state. Attenuation of mTORC1 in diabetes quells insulin-signalling network-wide, except for the mTOR in complex 2 (mTORC2)-catalysed phosphorylation of protein kinase B (PKB) at Ser(473) (PKB-S473P), which is increased. This unique increase could potentially be explained by feedback and interbranch cross-talk signals. To examine if such mechanisms operate in adipocytes, we herein analysed data from an unbiased phosphoproteomic screen in 3T3-L1 adipocytes. Using a mathematical modelling approach, we showed that a negative signal from mTORC1-p70 S6 kinase (S6K) to rictor-mTORC2 in combination with a positive signal from PKB to SIN1-mTORC2 are compatible with the experimental data. This combined cross-branch signalling predicted an increased PKB-S473P in response to attenuation of mTORC1 - a distinguishing feature of the insulin resistant state in human adipocytes. This aspect of insulin signalling was then verified for our comprehensive model of insulin signalling in human adipocytes. Introduction of the cross-branch signals was compatible with all data for insulin signalling in human adipocytes, and the resulting model can explain all data network-wide, including the increased PKB-S473P in the diabetic state. Our approach was to first identify potential mechanisms in data from a phosphoproteomic screen in a cell line, and then verify such mechanisms in primary human cells, which demonstrates how an unbiased approach can support a direct knowledge-based study.Funding Agencies|Swedish Research Council [K2014-55X-12157-18-5]; Linkoping Initiative in Life Science Technologies; CENIIT [15.09]</p

A comprehensive mechanistic model of adipocyte signaling with layers of confidence

Abstract Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70–90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes

LASSIM-A network inference toolbox for genome-wide mechanistic modeling

Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naive Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.Funding Agencies|Swedish research council [VR 2015-03807, VR2016-07108]; center for Industrial Information Technology; Free State of Thuringia; European Regional Development Fund; Deutsche Forschungsgemeinschaft CRC/Transregio</p

Fluorescent Discrimination between Traces of Chemical Warfare Agents and Their Mimics

An array of fluorogenic probes is able to discriminate between nerve agents, sarin, soman, tabun, VX and their mimics, in water or organic solvent, by qualitative fluorescence patterns and quantitative multivariate analysis, thus making the system suitable for the in-the-field detection of traces of chemical warfare agents as well as to differentiate between the real nerve agents and other related compounds