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Rapid clonal expansion of antigen specific T cells is a fundamental feature of adaptive immune responses. It enables the outgrowth of an individual T cell into thousands of clonal descendants that diversify into short-lived effectors and long-lived memory cells. Clonal expansion is thought to be programmed upon priming of a single naïve T cell and then executed by homogenously fast divisions of all of its descendants. However, the actual speed of cell divisions in such an emerging ‘T cell family’ has never been measured with single-cell resolution. Here, we utilize continuous live-cell imagingin vitroto track the division speed and genealogical connections of all descendants derived from a single naïve CD8+T cell throughout up to ten divisions of activation-induced proliferation. This comprehensive mapping of T cell family trees identifies a short burst phase, in which division speed is homogenously fast and maintained independent of external cytokine availability or continued T cell receptor stimulation. Thereafter, however, division speed diversifies and model-based computational analysis using a novel Bayesian inference framework for tree-structured data reveals a segregation into heritably fast and slow dividing branches. This diversification of division speed is preceded already during the burst phase by variable expression of the interleukin-2 receptor alpha chain. Later it is accompanied by selective expression of memory marker CD62L in slower dividing branches. Taken together, these data demonstrate that T cell clonal expansion is structured into subsequent burst and diversification phases the latter of which coincides with specification of memory vs. effector fate.SignificanceRapid clonal expansion of antigen-specific T cells is a fundamental feature of adaptive immune responses. Here, we utilize continuous live-cell imagingin vitroto track the division speed and genealogical connections of all descendants derived from a single naïve CD8+T cell throughout up to ten divisions of activation-induced proliferation. Bayesian inference of tree-structured data reveals that clonal expansion is divided into a homogenously fast burst phase encompassing two to three divisions and a subsequent diversification phase during which T cells segregate into quickly dividing effector T cells and more slowly cycling memory precursors. Our work highlights cell cycle speed as a major heritable property that is regulated in parallel to key lineage decisions of activated T cells.

Background: Chrysanthemum; also commonly known as mums or chrysanths, is one of the most important ornamental crops worldwide. Introducing desirable traits into this valuable plant by the conventional breeding has so far been faced with some restrictions due to the limited gene pool and cross-incompatibility. Therefore, breeders have decided to exploit Agrobacterium-mediated transformation methods in order to satisfy the growing market demands. However, more efficient in vitro regeneration protocols are required for this approach.Objectives: The objective of this research was to develop an efficient protocol for an in vitro plant regeneration by the examining the effects of various combinations and concentrations of the plant growth regulators (PGRs) and different explants types.Materials and Methods: The leaf and petiole explants of the Chrysanthemum morifolium cv. ‘Resomee Splendid’ were collected from the in vitro grown plantlets. Murashige and Skooge (MS) medium was supplemented with different concentrations and combinations of benzylaminopurine (BAP), 1-naphthaleneacetic acid (NAA) and thidiazuron (TDZ). Thereafter, the effects of these hormonal treatments were investigated on shoot initiation percentage, the average number of shoots per explants, callogenesis, and the type of organogenesis in regard to both types of the explants.Results: Shoots were directly formed from leaf explants on the media that only contained BAP without callus formation. Amongst the other hormonal treatments, a combination of 4.5 mg.L-1 BAP plus 1 mg.L-1 NAA resulted in the direct organogenesis from the leaf explants, which was superior to the other combinations and concentrations. In regard to the petiole explants, direct shoot formation occurred in all the media except for the ones which were fortified with TDZ. In this case, considering the shoot initiation percentage and the mean shoot number per explants, the best results were achieved in the medium supplemented with 1.5 mg.L-1 BAP and 1 mg.L-1 NAA. Results showed that interaction of either BAP or TDZ with NAA was necessary for the callus induction.Conclusions: Significant differences in shoot initiation percentage and the average number of shoots per explants were observed both in leaves and petioles grown on different media. Moreover, the callogenesis rates, as well as organogenesis types, showed some differences among the studied explants when compared on the same media.

This thesis aims to establish robust, reliable and feasible mesoscopic approximative methods that can be used in the formalism of systems biology to learn about the underlying mechanisms of stochastic biochemical processes. One of the main contributions of this work is proposing a model reduction, based on the topological structure of the reaction network, that enables mesoscopic modelling of large-scale biological processes. In addition, a simulation platform was developed as a part of this thesis which enables efficient simulation and comprehensive comparisons across a broad range of modelling approaches. Ziel dieser Dissertation ist es, zugleich robuste, zuverlässige und realisierbare mesoskopische Näherungsverfahren zu schaffen. Diese können auf biochemische Systeme angewendet werden, um mehr über ihre stochastische Natur zu lernen. Einer der Hauptbeiträge dieser Arbeit ist die Ausarbeitung einer Modell-Reduktion, die auf der topologischen Struktur des Reaktionsnetzwerks basiert. Sie ermöglicht eine mesoskopische Modellierung von umfangreichen biologischen Prozessen. Des Weiteren wurde eine Simulations-Plattform als Teil dieser Arbeit entwickelt, die numerisch-effiziente Rechnungen gewährleistet und umfassende Vergleiche zwischen verschiedenen Modellierungsansätzen ermöglicht.

Motivation Stochastic molecular processes are a leading cause of cell-to-cell variability. Their dynamics are often described by continuous-time discrete-state Markov chains and simulated using stochastic simulation algorithms. As these stochastic simulations are computationally demanding, ordinary differential equation models for the dynamics of the statistical moments have been developed. The number of state variables of these approximating models, however, grows at least quadratically with the number of biochemical species. This limits their application to small- and medium-sized processes. Results In this article, we present a scalable moment-closure approximation (sMA) for the simulation of statistical moments of large-scale stochastic processes. The sMA exploits the structure of the biochemical reaction network to reduce the covariance matrix. We prove that sMA yields approximating models whose number of state variables depends predominantly on local properties, i.e. the average node degree of the reaction network, instead of the overall network size. The resulting complexity reduction is assessed by studying a range of medium- and large-scale biochemical reaction networks. To evaluate the approximation accuracy and the improvement in computational efficiency, we study models for JAK2/STAT5 signalling and NFκB signalling. Our method is applicable to generic biochemical reaction networks and we provide an implementation, including an SBML interface, which renders the sMA easily accessible. Availability and implementation The sMA is implemented in the open-source MATLAB toolbox CERENA and is available from https://github.com/CERENADevelopers/CERENA. Supplementary information Supplementary data are available at Bioinformatics online.

The authors report femtosecond pump-probe measurements of electronic energy relaxation in conventional metallic and high-T/sub c/ oxide superconductors. In conventional metallic superconductors, the energy relaxation rate of electrons is used to determine the electron-phonon coupling constant lambda . The agreement between the lambda values measured and those obtained by other techniques is excellent, confirming the theoretical predictions of P.B. Allen (1987). A novel Cu overlayer technique was developed in order to measure certain metals which do not have a strong optical transition to states near the Fermi level at a laser energy, of 1.98 eV. The effect of different Cu overlayer thicknesses has been studied. In the new copper-oxide high-T/sub c/ superconducting materials, electronic energy relaxation is monitored by measuring changes epsilon /sub 2/. The observed changes in epsilon /sub 2/ are related to the dynamics of the Cu d to O p band charge transfer excitation occurring in the CuO/sub 2/ planes. By depleting a YBa/sub 2/Cu/sub 3/O/sub 7- delta / sample of oxygen, one can simultaneously vary the Fermi level and the T/sub c/ and make dramatic changes in the pump-probe signal. An estimate of lambda , in several high-T/sub c/ materials, is also made using Allen's theory to fit the relaxation behavior of epsilon /sub 2/.

Abstract 2558 Background: The increasing use in the clinic of genome-wide analyses has placed a greater burden on, and need for novel informatics tools. Ideally such tools should be capable of reducing the vast amount of information generated per patient into integrated, simplified, intuitive, and preferably, visual data that can be easily translated into diagnostic, prognostic and theranostic actionable information. With the overarching goal of clarity and user-friendliness in mind we have co-opted a genome-wide representational tool used widely in non-clinical discovery genomics and tailored it to achieve its intended clinical use, i.e. simple graphical representation of complex data enabling clinicians to quickly derive meaning from robust clinical laboratory modalities, such as next-generation sequencing technologies and next-gen microarrays. Materials & Methods: For a proof of concept rendition, we collected cytogenetics, array CGH, and gene expression data on a subset of well-characterized core binding factor positive leukemias. Leukemias containing CBFA2 [t(8;21)(q22;q22)] or CBFB [inv(16)(p13q22)] fusion proteins were included in the study. Gene expression profiling data sets were extracted from Stanford Microarray Database. The associated karyotypes were obtained from the linked PubMed papers and directly from the authors. aCGH data sets were extracted from the SKY/M-FISH and CGH database at NCBI. All datasets for each case of CBF+ leukemia represented in this study were unified into a Microsoft Access Database, which contained the numeric coordinates of all genes included, and their associated cytogenetic band position. Results: By subjecting the data to customized subroutines, it was possible to extract and display relevant subsets of data into a customizable visually intuitive display, which allowed naïve observers to quickly assimilate all the clinically relevant genetic information on a particular AML case. From such a representation, heat maps of subsets of genes, structural and numerical chromosome abnormalities, copy-number changes and subsets of relevant point mutations could be displayed, all in a single integrated genome anchored image. Discussion: Our graphic user interface displays positionally-anchored genome-wide data and could be customized to represent CNVs, miRNA expression and DNA methylation patterns, associated phenotypes, etc, in addition to those shown in this study. Furthermore, any of these parameters can be segmented into functionally related groups to display, for instance, regulators of transcription, cell lineage or differentiation, proliferation, apoptosis, DNA repair, expression of genes that govern response or sensitivity to chemotherapy or entire signaling pathways. Conclusion: Integrated graphical representation of relevant genome-wide data facilitates and harmonizes communication among physicians with different expertise and facilitates patient stratification into defined risk groups, which is critically important in enabling risk-adapted and/or targeted therapies. Disclosures: No relevant conflicts of interest to declare.