99 research outputs found
Lentiviral vectors can be used for full-length dystrophin gene therapy
Duchenne Muscular Dystrophy (DMD) is caused by a lack of dystrophin expression in patient muscle fibres. Current DMD gene therapy strategies rely on the expression of internally deleted forms of dystrophin, missing important functional domains. Viral gene transfer of full-length dystrophin could restore wild-type functionality, although this approach is restricted by the limited capacity of recombinant viral vectors. Lentiviral vectors can package larger transgenes than adeno-associated viruses, yet lentiviral vectors remain largely unexplored for full-length dystrophin delivery. In our work, we have demonstrated that lentiviral vectors can package and deliver inserts of a similar size to dystrophin. We report a novel approach for delivering large transgenes in lentiviruses, in which we demonstrate proof-of-concept for a 'template-switching' lentiviral vector that harnesses recombination events during reverse-transcription. During this work, we discovered that a standard, unmodified lentiviral vector was efficient in delivering full-length dystrophin to target cells, within a total genomic load of more than 15,000 base pairs. We have demonstrated gene therapy with this vector by restoring dystrophin expression in DMD myoblasts, where dystrophin was expressed at the sarcolemma of myotubes after myogenic differentiation. Ultimately, our work demonstrates proof-of-concept that lentiviruses can be used for permanent full-length dystrophin gene therapy, which presents a significant advancement in developing an effective treatment for DMD
Syntactic Markovian Bisimulation for Chemical Reaction Networks
In chemical reaction networks (CRNs) with stochastic semantics based on
continuous-time Markov chains (CTMCs), the typically large populations of
species cause combinatorially large state spaces. This makes the analysis very
difficult in practice and represents the major bottleneck for the applicability
of minimization techniques based, for instance, on lumpability. In this paper
we present syntactic Markovian bisimulation (SMB), a notion of bisimulation
developed in the Larsen-Skou style of probabilistic bisimulation, defined over
the structure of a CRN rather than over its underlying CTMC. SMB identifies a
lumpable partition of the CTMC state space a priori, in the sense that it is an
equivalence relation over species implying that two CTMC states are lumpable
when they are invariant with respect to the total population of species within
the same equivalence class. We develop an efficient partition-refinement
algorithm which computes the largest SMB of a CRN in polynomial time in the
number of species and reactions. We also provide an algorithm for obtaining a
quotient network from an SMB that induces the lumped CTMC directly, thus
avoiding the generation of the state space of the original CRN altogether. In
practice, we show that SMB allows significant reductions in a number of models
from the literature. Finally, we study SMB with respect to the deterministic
semantics of CRNs based on ordinary differential equations (ODEs), where each
equation gives the time-course evolution of the concentration of a species. SMB
implies forward CRN bisimulation, a recently developed behavioral notion of
equivalence for the ODE semantics, in an analogous sense: it yields a smaller
ODE system that keeps track of the sums of the solutions for equivalent
species.Comment: Extended version (with proofs), of the corresponding paper published
at KimFest 2017 (http://kimfest.cs.aau.dk/
On deducing causality in metabolic networks
Β© 2008 Bodei et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution Licens
Standard operating procedure for curation and clinical interpretation of variants in cancer
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC\u27s clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants
RKappa: Statistical sampling suite for Kappa models
We present RKappa, a framework for the development and analysis of rule-based
models within a mature, statistically empowered R environment. The
infrastructure allows model editing, modification, parameter sampling,
simulation, statistical analysis and visualisation without leaving the R
environment. We demonstrate its effectiveness through its application to Global
Sensitivity Analysis, exploring it in "parallel" and "concurrent"
implementations.
The pipeline was designed for high performance computing platforms and aims
to facilitate analysis of the behaviour of large-scale systems with limited
knowledge of exact mechanisms and respectively sparse availability of parameter
values, and is illustrated here with two biological examples.
The package is available on github: https://github.com/lptolik/R4KappaComment: Hybrid Systems and Biology 2014, Vienn
Critical Review of Theoretical Models for Anomalous Effects (Cold Fusion) in Deuterated Metals
We briefly summarize the reported anomalous effects in deuterated metals at
ambient temperature, commonly known as "Cold Fusion" (CF), with an emphasis on
important experiments as well as the theoretical basis for the opposition to
interpreting them as cold fusion. Then we critically examine more than 25
theoretical models for CF, including unusual nuclear and exotic chemical
hypotheses. We conclude that they do not explain the data.Comment: 51 pages, 4 Figure
Security Limitations of Classical-Client Delegated Quantum Computing
Secure delegated quantum computing allows a computationally weak client to
outsource an arbitrary quantum computation to an untrusted quantum server in a
privacy-preserving manner. One of the promising candidates to achieve classical
delegation of quantum computation is classical-client remote state preparation
(), where a client remotely prepares a quantum state using a
classical channel. However, the privacy loss incurred by employing
as a sub-module is unclear.
In this work, we investigate this question using the Constructive
Cryptography framework by Maurer and Renner (ICS'11). We first identify the
goal of as the construction of ideal RSP resources from classical
channels and then reveal the security limitations of using . First,
we uncover a fundamental relationship between constructing ideal RSP resources
(from classical channels) and the task of cloning quantum states. Any
classically constructed ideal RSP resource must leak to the server the full
classical description (possibly in an encoded form) of the generated quantum
state, even if we target computational security only. As a consequence, we find
that the realization of common RSP resources, without weakening their
guarantees drastically, is impossible due to the no-cloning theorem. Second,
the above result does not rule out that a specific protocol can
replace the quantum channel at least in some contexts, such as the Universal
Blind Quantum Computing (UBQC) protocol of Broadbent et al. (FOCS '09).
However, we show that the resulting UBQC protocol cannot maintain its proven
composable security as soon as is used as a subroutine. Third, we
show that replacing the quantum channel of the above UBQC protocol by the
protocol QFactory of Cojocaru et al. (Asiacrypt '19), preserves the
weaker, game-based, security of UBQC.Comment: 40 pages, 12 figure
Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems
Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. Β© 2014 Hogg et al
Cellular senescence in naevi and immortalisation in melanoma: a role for p16?
Cellular senescence, the irreversible proliferative arrest seen in somatic cells after a limited number of divisions, is considered a crucial barrier to cancer, but direct evidence for this in vivo was lacking until recently. The best-known form of human cell senescence is attributed to telomere shortening and a DNA-damage response through p53 and p21. There is also a more rapid form of senescence, dependent on the p16-retinoblastoma pathway. p16 (CDKN2A) is a known melanoma susceptibility gene. Here, we use retrovirally mediated gene transfer to confirm that the normal form of senescence in cultured human melanocytes involves p16, since disruption of the p16/retinoblastoma pathway is required as well as telomerase activation for immortalisation. Expression (immunostaining) patterns of senescence mediators and markers in melanocytic lesions provide strong evidence that cell senescence occurs in benign melanocytic naevi (moles) in vivo and does not involve p53 or p21 upregulation, although p16 is widely expressed. In comparison, dysplastic naevi and early (radial growth-phase, RGP) melanomas show less p16 and some p53 and p21 immunostaining. All RGP melanomas expressed p21, suggesting areas of p53-mediated senescence, while most areas of advanced (vertical growth-phase) melanomas lacked both p16 and p21, implying escape from both forms of senescence (immortalisation). Moreover, nuclear p16 but not p21 expression can be induced in human melanocytes by oncogenic BRAF, as found in around 80% of naevi. We conclude that cell senescence can form a barrier to melanoma development. This also provides a potential explanation of why p16 is a melanoma suppressor gene
Diffusion tensor imaging of frontal lobe white matter tracts in schizophrenia
We acquired diffusion tensor and structural MRI images on 103 patients with schizophrenia and 41 age-matched normal controls. The vector data was used to trace tracts from a region of interest in the anterior limb of the internal capsule to the prefrontal cortex. Patients with schizophrenia had tract paths that were significantly shorter in length from the center of internal capsule to prefrontal white matter. These tracts, the anterior thalamic radiations, are important in frontal-striatal-thalamic pathways. These results are consistent with findings of smaller size of the anterior limb of the internal capsule in patients with schizophrenia, diffusion tensor anisotropy decreases in frontal white matter in schizophrenia and hypothesized disruption of the frontal-striatal-thalamic pathway system
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