3,610 research outputs found

    High affinity binding of amyloid β-peptide to calmodulin: Structural and functional implications.

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    Amyloid β-peptides (Aβ) are a major hallmark of Alzheimer's disease (AD) and their neurotoxicity develop with cytosolic calcium dysregulation. On the other hand, calmodulin (CaM), a protein which plays a major multifunctional role in neuronal calcium signaling, has been shown to be involved in the regulation of non-amyloidogenic processing of amyloid β precursor protein (APP). Using fluorescent 6-bromoacetyl-2-dimethylaminonaphthalene derivatives of CaM, Badan-CaM, and human amyloid β(1-42) HiLyte™-Fluor555, we show in this work that Aβ binds with high affinity to CaM through the neurotoxic Aβ25-35 domain. In addition, the affinity of Aβ for calcium-saturated CaM conformation is approximately 20-fold higher than for CaM conformation in the absence of calcium (apo-CaM). Moreover, the value of Kd of 0.98 ± 0.11 nM obtained for Aβ1-42 dissociation from CaM saturated by calcium point out that CaM is one of the cellular targets with highest affinity for neurotoxic Aβ peptides. A major functional consequence of Aβ-CaM interaction is that it slowdowns Aβ fibrillation. The novel and high affinity interaction between calmodulin and Aβ shown in this work opens a yet-unexplored gateway to further understand the neurotoxic effect of Aβ in different neural cells and also to address the potential of calmodulin and calmodulin-derived peptides as therapeutic agents in AD

    A first step to accelerating fingerprint matching based on deformable minutiae clustering

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    Fingerprint recognition is one of the most used biometric methods for authentication. The identification of a query fingerprint requires matching its minutiae against every minutiae of all the fingerprints of the database. The state-of-the-art matching algorithms are costly, from a computational point of view, and inefficient on large datasets. In this work, we include faster methods to accelerating DMC (the most accurate fingerprint matching algorithm based only on minutiae). In particular, we translate into C++ the functions of the algorithm which represent the most costly tasks of the code; we create a library with the new code and we link the library to the original C# code using a CLR Class Library project by means of a C++/CLI Wrapper. Our solution re-implements critical functions, e.g., the bit population count including a fast C++ PopCount library and the use of the squared Euclidean distance for calculating the minutiae neighborhood. The experimental results show a significant reduction of the execution time in the optimized functions of the matching algorithm. Finally, a novel approach to improve the matching algorithm, considering cache memory blocking and parallel data processing, is presented as future work.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Circuit dissection of the role of somatostatin in itch and pain

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    Stimuli that elicit itch are detected by sensory neurons that innervate the skin. This information is processed by the spinal cord; however, the way in which this occurs is still poorly understood. Here we investigated the neuronal pathways for itch neurotransmission, particularly the contribution of the neuropeptide somatostatin. We find that in the periphery, somatostatin is exclusively expressed in Nppb+ neurons, and we demonstrate that Nppb+somatostatin+ cells function as pruriceptors. Employing chemogenetics, pharmacology and cell-specific ablation methods, we demonstrate that somatostatin potentiates itch by inhibiting inhibitory dynorphin neurons, which results in disinhibition of GRPR+ neurons. Furthermore, elimination of somatostatin from primary afferents and/or from spinal interneurons demonstrates differential involvement of the peptide released from these sources in itch and pain. Our results define the neural circuit underlying somatostatin-induced itch and characterize a contrasting antinociceptive role for the peptide

    Automata for true concurrency properties

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    We present an automata-theoretic framework for the model checking of true concurrency properties. These are specified in a fixpoint logic, corresponding to history-preserving bisimilarity, capable of describing events in computations and their dependencies. The models of the logic are event structures or any formalism which can be given a causal semantics, like Petri nets. Given a formula and an event structure satisfying suitable regularity conditions we show how to construct a parity tree automaton whose language is non-empty if and only if the event structure satisfies the formula. The automaton, due to the nature of event structure models, is usually infinite. We discuss how it can be quotiented to an equivalent finite automaton, where emptiness can be checked effectively. In order to show the applicability of the approach, we discuss how it instantiates to finite safe Petri nets. As a proof of concept we provide a model checking tool implementing the technique

    A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies

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    Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials

    Small RNA Profile in Moso Bamboo Root and Leaf Obtained by High Definition Adapters

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    Moso bamboo (Phyllostachy heterocycla cv. pubescens L.) is an economically important fast-growing tree. In order to gain better understanding of gene expression regulation in this important species we used next generation sequencing to profile small RNAs in leaf and roots of young seedlings. Since standard kits to produce cDNA of small RNAs are biased for certain small RNAs, we used High Definition adapters that reduce ligation bias. We identified and experimentally validated five new microRNAs and a few other small non-coding RNAs that were not microRNAs. The biological implication of microRNA expression levels and targets of microRNAs are discussed

    Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia.

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    The role of Hedgehog signaling in normal and malignant T-cell development is controversial. Recently, Hedgehog pathway mutations have been described in T-ALL, but whether mutational activation of Hedgehog signaling drives T-cell transformation is unknown, hindering the rationale for therapeutic intervention. Here, we show that Hedgehog pathway mutations predict chemotherapy resistance in human T-ALL, and drive oncogenic transformation in a zebrafish model of the disease. We found Hedgehog pathway mutations in 16% of 109 childhood T-ALL cases, most commonly affecting its negative regulator PTCH1. Hedgehog mutations were associated with resistance to induction chemotherapy (P = 0.009). Transduction of wild-type PTCH1 into PTCH1-mutant T-ALL cells induced apoptosis (P = 0.005), a phenotype that was reversed by downstream Hedgehog pathway activation (P = 0.007). Transduction of most mutant PTCH1, SUFU, and GLI alleles into mammalian cells induced aberrant regulation of Hedgehog signaling, indicating that these mutations are pathogenic. Using a CRISPR/Cas9 system for lineage-restricted gene disruption in transgenic zebrafish, we found that ptch1 mutations accelerated the onset of notch1-induced T-ALL (P = 0.0001), and pharmacologic Hedgehog pathway inhibition had therapeutic activity. Thus, Hedgehog-activating mutations are driver oncogenic alterations in high-risk T-ALL, providing a molecular rationale for targeted therapy in this disease

    Silicon CMOS photonics platform for enabling high-speed DQPSK transceivers

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    In this work we review the results obtained under the framework of FP7-HELIOS project for integrated DQPSK transceivers in silicon photonics. A differential DQPSK receiver with balanced zero biased Germanium photodiodes has been demonstrated at 10Gbit/s with an error floor around 10(-15). Furthermore, DPSK modulation up to 10Gbit/s with a bit error rate below 10(-9) is also demonstrated using a silicon push-pull operated dual-drive Mach-Zehnder modulator (MZM) based on carrier depletion. The results indicate the potential of the silicon CMOS photonics platform for boosting next-generation optical networks based on advanced modulation formats
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