Cancer-Specific Perturbations to Arginine Metabolism Blunt Replication and Performance of Oncolytic Myxoma Virus

Oncolytic virotherapy (OV) is a class of immunotherapy for treatment of malignancy. Using viruses that exhibit natural coincidental tropisms for cancer, or others that have been engineered to the same effect, intentional infection of lesions leads to two therapeutically beneficial effects: (1) direct destruction of the infected tumor through virally-mediated cell lysis, and (2) recruitment of an otherwise blunted or absent anti-cancer immune response to affect both local and disseminated disease. A surfeit of cancer-specific changes are accumulated during progression from first genetic insult to clinical detection, presenting a dramatically altered underlying biology of cell and tissue. The viruses employed within OV have been characterized over decades, however, all largely within the context of normal and otherwise-healthy host cells bearing infections. As such, these disparities between cancerous tissues and their normal counterparts may pose barriers to viral infection not encountered or compensated for. Dysregulations within cellular metabolism are a hallmark of cancer, and the replication of all viruses – oncolytic or not – is contingent on access to host metabolites. Despite this, no research has been conducted evaluating how metabolic changes within tumors may lead to resistance to OV infection. One such dysregulated metabolic pathway is synthesis and consumption of L-arginine (Arg), a semi-essential amino acid whose bioavailability is required for the in vitro replication of several oncolytic viruses. Cancer types such as hepatocellular carcinoma, sarcoma, and melanoma often clinically present as functionally auxotrophic for this amino acid due to epigenetic silencing of argininosuccinate synthetase 1 (ASS1), an enzyme responsible for the conversion of citrulline and aspartate into the Arg precursor argininosuccinate (AS). Additionally, the recruitment of Arginase-1 (ARG1) positive myeloid derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs) further insult Arg availability within the TME. Here, we show that the in vitro replication of oncolytic myxoma virus (MYXV) is dependent on the presence of bioavailable Arg, with insight towards several stages within the viral life cycle. We demonstrate that the presence of MDSCs negatively reduces viral burden within infected tumors in a B16F10 model of murine melanoma, with their depletion capable of reducing initial required MYXV dose to elicit a therapeutic response, and these effects possibly attributable to an expression of ARG1 as evidenced within cocultures ex vivo. Secondly, we determine the role of ASS1 in mediating tumoral capacity for viral replication in vitro and in vivo using CRISPR/Cas9 generated ASS1KO cell lines. Here, we find tumors formed from functionally ASS1KO B16F10 melanoma cells display multi-log reductions in MYXV replication during oncolytic virotherapy (OV) as well as significantly poorer therapeutic responses. Lastly, we demonstrate that reconstitution of Arg biosynthesis through ASS1-armed MYXV constructs at least partially rescues these effects. Collectively, these studies demonstrate an Arg-dependent replication of MYXV that may be affected by cancer-specific changes within Arg metabolism and consumption. This work is the first to characterize a metabolic barrier to achieving optimal viral replication within tumors, and indicates that consideration towards tumoral metabolism may improve replication and therapeutic efficacy of OV agents

A Numerical Approach to Space-Time Finite Elements for the Wave Equation

We study a space-time finite element approach for the nonhomogeneous wave equation using a continuous time Galerkin method. We present fully implicit examples in 1+1, 2+1, and 3+1 dimensions using linear quadrilateral, hexahedral, and tesseractic elements. Krylov solvers with additive Schwarz preconditioning are used for solving the linear system. We introduce a time decomposition strategy in preconditioning which significantly improves performance when compared with unpreconditioned cases.Comment: 9 pages, 5 figures, 5 table

Microstructure Characterization of TRIP Steel CMnAlSi

Finely grained multiphase microstructures ofTRIP- aided steel CMnAlSi were characterized by opticalmicroscopy, scanning microscopy and atomic force microscopyobservation

Abstract robust coarse spaces for systems of PDEs via generalized eigenproblems in the overlaps

Coarse spaces are instrumental in obtaining scalability for domain decomposition methods for partial differential equations (PDEs). However, it is known that most popular choices of coarse spaces perform rather weakly in the presence of heterogeneities in the PDE coefficients, especially for systems of PDEs. Here, we introduce in a variational setting a new coarse space that is robust even when there are such heterogeneities. We achieve this by solving local generalized eigenvalue problems in the overlaps of subdomains that isolate the terms responsible for slow convergence. We prove a general theoretical result that rigorously establishes the robustness of the new coarse space and give some numerical examples on two and three dimensional heterogeneous PDEs and systems of PDEs that confirm this property

Restricted Additive Schwarz Preconditioners with Harmonic Overlap for Symmetric Positive Definite Linear Systems

A restricted additive Schwarz (RAS) preconditioning technique was introduced recently for solving general nonsymmetric sparse linear systems. In this paper, we provide one-level and two-level extensions of RAS for symmetric positive definite problems using the so-called harmonic overlaps (RASHO). Both RAS and RASHO outperform their counterparts of the classical additive Schwarz variants (AS). The design of RASHO is based on a much deeper understanding of the behavior of Schwarz-type methods in overlapping subregions and in the construction of the overlap. In RASHO, the overlap is obtained by extending the nonoverlapping subdomains only in the directions that do not cut the boundaries of other subdomains, and all functions are made harmonic in the overlapping regions. As a result, the subdomain problems in RASHO are smaller than those of AS, and the communication cost is also smaller when implemented on distributed memory computers, since the right-hand sides of discrete harmonic systems are always zero and therefore do not need to be communicated. We also show numerically that RASHO-preconditioned CG takes fewer iterations than the corresponding AS-preconditioned CG. A nearly optimal theory is included for the convergence of RASHO-preconditioned CG for solving elliptic problems discretized with a finite element method

Utreexo: A dynamic hash-based accumulator optimized for the Bitcoin UTXO set

In the Bitcoin consensus network, all nodes come to agreement on the set of Unspent Transaction Outputs (The “UTXO” set). The size of this shared state is a scalability constraint for the network, as the size of the set expands as more users join the system, increasing resource requirements of all nodes. Decoupling the network’s state size from the storage requirements of individual machines would reduce hardware requirements of validating nodes. We introduce a hash based accumulator to locally represent the UTXO set, which is logarithmic in the size of the full set. Nodes attach and propagate inclusion proofs to the inputs of transactions, which along with the accumulator state, give all the information needed to validate a transaction. While the size of the inclusion proofs results in an increase in network traffic, these proofs can be discarded after verification, and aggregation methods can reduce their size to a manageable level of overhead. In our simulations of downloading Bitcoin’s blockchain up to early 2019 with 500MB of RAM allocated for caching, the proofs only add approximately 25% to the amount otherwise downloaded