1,673 research outputs found
Molecular Mechanisms of Assembly and Long-term Maintenance of Neuronal Architecture: A Dissertation
Nervous system function is closely tied to its structure, which ensures proper connectivity and neural activity. Neuronal architecture is assembled by a series of morphogenetic events, including the coordinated migrations of neurons and axons during development. Subsequently, the neuronal architecture established earlier must persist in the face of further growth, maturation of the nervous system, and the mechanical stress of body movements. In this work, we have shed light on the molecular mechanisms governing both the initial assembly of the nervous system and the long-term maintenance of neural circuits. In particular, we identified heparan sulfate proteoglycans (HSPGs) as regulators of neuronal migrations. Our discovery and analysis of viable mutations in the two subunits of the heparan sulfate co-polymerase reveals the importance of the coordinated and dynamic action of HSPGs in neuronal and axon guidance during development. Furthermore, we uncovered that the HSPG LON-2/glypican functions as a modulator of UNC-6/netrin signaling through interactions with the UNC-40/DCC receptor. During larval and adult life, molecules such as the protein SAX-7, homologous to mammalian L1CAM, function to protect the integrity of nervous system architecture. Indeed, loss of sax-7 leads to progressive disorganization of neuronal architecture. Through a forward genetic screen, we identified LON-1 as a novel maintenance molecule that functions post-embryonically with SAX-7 to maintain the architecture of the nervous system. Together, our work highlights the importance of extracellular interactions to modulate signaling events during the initial development of the nervous system, and to subsequently maintain neuronal architecture for the long-term
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Housing markets and independence in old age: expanding the opportunities
This report highlights the benefits of specialised private retirement accommodation and recommends a
number of simple policy changes at no cost to the public purse to help increase its supply and address
the challenges of housing an ageing population
Alien Registration- Riendeau, Lida R. (Brunswick, Cumberland County)
https://digitalmaine.com/alien_docs/31918/thumbnail.jp
ENIGMA: Efficient Learning-based Inference Guiding Machine
ENIGMA is a learning-based method for guiding given clause selection in
saturation-based theorem provers. Clauses from many proof searches are
classified as positive and negative based on their participation in the proofs.
An efficient classification model is trained on this data, using fast
feature-based characterization of the clauses . The learned model is then
tightly linked with the core prover and used as a basis of a new parameterized
evaluation heuristic that provides fast ranking of all generated clauses. The
approach is evaluated on the E prover and the CASC 2016 AIM benchmark, showing
a large increase of E's performance.Comment: Submitted to LPAR 201
An implementation of Deflate in Coq
The widely-used compression format "Deflate" is defined in RFC 1951 and is
based on prefix-free codings and backreferences. There are unclear points about
the way these codings are specified, and several sources for confusion in the
standard. We tried to fix this problem by giving a rigorous mathematical
specification, which we formalized in Coq. We produced a verified
implementation in Coq which achieves competitive performance on inputs of
several megabytes. In this paper we present the several parts of our
implementation: a fully verified implementation of canonical prefix-free
codings, which can be used in other compression formats as well, and an elegant
formalism for specifying sophisticated formats, which we used to implement both
a compression and decompression algorithm in Coq which we formally prove
inverse to each other -- the first time this has been achieved to our
knowledge. The compatibility to other Deflate implementations can be shown
empirically. We furthermore discuss some of the difficulties, specifically
regarding memory and runtime requirements, and our approaches to overcome them
The Art of Clinical Supervision: Pastoral Counseling (New York and Mahwah, NJ: Paulist Press, 1987)
Reviewed by Peter Yuichi Clark
Predicting direct protein interactions from affinity purification mass spectrometry data
<p>Abstract</p> <p>Background</p> <p>Affinity purification followed by mass spectrometry identification (AP-MS) is an increasingly popular approach to observe protein-protein interactions (PPI) <it>in vivo</it>. One drawback of AP-MS, however, is that it is prone to detecting indirect interactions mixed with direct physical interactions. Therefore, the ability to distinguish direct interactions from indirect ones is of much interest.</p> <p>Results</p> <p>We first propose a simple probabilistic model for the interactions captured by AP-MS experiments, under which the problem of separating direct interactions from indirect ones is formulated. Then, given idealized quantitative AP-MS data, we study the problem of identifying the most likely set of direct interactions that produced the observed data. We address this challenging graph theoretical problem by first characterizing signatures that can identify weakly connected nodes as well as dense regions of the network. The rest of the direct PPI network is then inferred using a genetic algorithm.</p> <p>Our algorithm shows good performance on both simulated and biological networks with very high sensitivity and specificity. Then the algorithm is used to predict direct interactions from a set of AP-MS PPI data from yeast, and its performance is measured against a high-quality interaction dataset.</p> <p>Conclusions</p> <p>As the sensitivity of AP-MS pipeline improves, the fraction of indirect interactions detected will also increase, thereby making the ability to distinguish them even more desirable. Despite the simplicity of our model for indirect interactions, our method provides a good performance on the test networks.</p
A formalized general theory of syntax with bindings
We present the formalization of a theory of syntax with bindings that has been developed and refined over the last decade to support several large formalization efforts. Terms are defined for an arbitrary number of constructors of varying numbers of inputs, quotiented to alpha-equivalence and sorted according to a binding signature. The theory includes a rich collection of properties of the standard operators on terms, such as substitution and freshness. It also includes induction and recursion principles and support for semantic interpretation, all tailored for smooth interaction with the bindings and the standard operators
Effect of Wood Particle Size on Fungal Growth in a Model Biomechanical Pulping Process
The pretreatment of aspen wood chips with white-rot fungus has been evaluated as a way of making biomechanical pulp. Our study addressed (1) whether wood particle size (chip size) affects the growth pattern of the attacking organism, and (2) whether the difference in particle size between chips and coarse pulp is related to the availability of wood polymers to the fungus. We qualitatively evaluated the growth of Phanerochaete chrysosporium BKM-F-1767 on aspen wood using standard industrial 6- and 19-mm chips and coarse refiner mechanical pulp. Scanning electron microscopy revealed a slight increase in the number of hyphae in the 19-mm chips compared to that in the 6-mm chips, but no major morphological differences in cellulose or lignin loss. Dense aerial hyphal growth occurred around the chips, but not around the coarse pulp. The fungus appeared to attack the coarse pulp from both outside and within the fiber wall. Hyphae within both the middle lamella and the cell lumina attacked the cell walls. The fungus eroded the chip cell walls and their constituents primarily from the wood cell lumen outward. After only 3 weeks of fungal treatment, both chips and coarse pulp showed marked localized cell-wall thinning and fragmentation as well as generalized swelling and relaxing of the normally rigid cell-wall structure. We conclude that particle size has only a minor effect on fungal growth on wood under conditions such as those likely to be used in a commercial biopulping process
Neuronal post-developmentally acting SAX-7S/L1CAM can function as cleaved fragments to maintain neuronal architecture in C. elegans [preprint]
Whereas remarkable advances have uncovered mechanisms that drive nervous system assembly, the processes responsible for the lifelong maintenance of nervous system architecture remain poorly understood. Subsequent to its establishment during embryogenesis, neuronal architecture is maintained throughout life in the face of the animal’s growth, maturation processes, the addition of new neurons, body movements, and aging. The C. elegans protein SAX-7, homologous to the vertebrate L1 protein family, is required for maintaining the organization of neuronal ganglia and fascicles after their successful initial embryonic development. To dissect the function of sax-7 in neuronal maintenance, we generated a null allele and sax-7S-isoform-specific alleles. We find that the null sax-7(qv30) is, in some contexts, more severe than previously described mutant alleles, and that the loss of sax-7S largely phenocopies the null, consistent with sax-7S being the key isoform in neuronal maintenance. Using a sfGFP::SAX-7S knock-in, we observe sax-7S to be predominantly expressed across the nervous system, from embryogenesis to adulthood. Yet, its role in maintaining neuronal organization is ensured by post-developmentally acting SAX-7S, as larval transgenic sax-7S(+) expression alone is sufficient to profoundly rescue the null mutants’ neuronal maintenance defects. Moreover, the majority of the protein SAX-7 appears to be cleaved, and we show that these cleaved SAX-7S fragments together, not individually, can fully support neuronal maintenance. These findings contribute to our understanding of the role of the conserved protein SAX-7/L1CAM in long-term neuronal maintenance, and may help decipher processes that go awry in some neurodegenerative conditions
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