Effects of restricted methionine and energy intake on egg weight and shell quality

Selostus: Metioniinin ja energian saannin rajoittamisen vaikutukset kananmunan painoon ja laatuun

The effect of free or restricted acidified milk feeding of Finnish Ayrshire bull calves on the subsequent fattening and slaughter performance

Selostus: Vapaan ja rajoitetun maitojuoton vaikutukset ayrshiresonnien kasvuun koko kasvatuskauden aikana ja teurastuloksiin

The Structure and Function of αI Domains in Collagen Receptor and Leukocyte Integrins

Integrins are heterodimeric, signaling transmembrane adhesion receptors that connect the intracellular actin microfilaments to the extracellular matrix composed of collagens and other matrix molecules. Bidirectional signaling is mediated via drastic conformational changes in integrins. These changes also occur in the integrin αI domains, which are responsible for ligand binding by collagen receptor and leukocyte specific integrins. Like intact integrins, soluble αI domains exist in the closed, low affinity form and in the open, high affinity form, and so it is possible to use isolated αI domains to study the factors and mechanisms involved in integrin activation/deactivation. Integrins are found in all mammalian tissues and cells, where they play crucial roles in growth, migration, defense mechanisms and apoptosis. Integrins are involved in many human diseases, such as inflammatory, cardiovascular and metastatic diseases, and so plenty of effort has been invested into developing integrin specific drugs. Humans have 24 different integrins, four of which are collagen receptor (α1β1, α2β1, α10β1, α11β1) and five leukocyte specific integrins (αLβ2, αMβ2, αXβ2, αDβ2, αEβ7). These two integrin groups are quite unselective having both primary and secondary ligands. This work presents the first systematic studies performed on these integrin groups to find out how integrin activation affects ligand binding and selectivity. These kinds of studies are important not only for understanding the partially overlapping functions of integrins, but also for drug development. In general, our results indicated that selectivity in ligand recognition is greatly reduced upon integrin activation. Interestingly, in some cases the ligand binding properties of integrins have been shown to be cell type specific. The reason for this is not known, but our observations suggest that cell types with a higher integrin activation state have lower ligand selectivity, and vice versa. Furthermore, we solved the three-dimensional structure for the activated form of the collagen receptor α1I domain. This structure revealed a novel intermediate conformation not previously seen with any other integrin αI domain. This is the first 3D structure for an activated collagen receptor αI domain without ligand. Based on the differences between the open and closed conformation of the αI domain we set structural criteria for a search for effective collagen receptor drugs. By docking a large number of molecules into the closed conformation of the α2I domain we discovered two polyketides, which best fulfilled the set structural criteria, and by cell adhesion studies we showed them to be specific inhibitors of the collagen receptor integrins.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.