Cerebral hemodynamics on MR perfusion images before and after bypass surgery in patients with giant intracranial aneurysms

Preoperative assessment of the anatomy and dynamics of cerebral circulation for patients with giant intracranial aneurysm can improve both outcome prediction and therapeutic approach. The aim of our study was to use perfusion MR imaging to evaluate cerebral hemodynamics in such patients before and after extraintracranial high-flow bypass surgery. METHODS: Five patients with a giant aneurysm of the intracranial internal carotid artery underwent MR studies before, 1 week after, and 1 month after high-flow bypass surgery. We performed MR and digital subtraction angiography, and conventional and functional MR sequences (diffusion and perfusion). Surgery consisted of middle cerebral artery (MCA)-internal carotid artery bypass with saphenous vein grafts (n = 4) or MCA-external carotid artery bypass (n = 1). RESULTS: In four patients, MR perfusion study showed impaired hemodynamics in the vascular territory supplied by the MCA of the aneurysm side, characterized by significantly reduced mean cerebral blood flow (CBF), whereas mean transit time (MTT) and regional cerebral blood volume (rCBV) were either preserved, reduced, or increased. After surgery, angiography showed good canalization of the bypass graft. MR perfusion data obtained after surgery showed improved cerebral hemodynamics in all cases, with a return of CBF index (CBFi), MTT, and rCBV to nearly normal values. CONCLUSION: Increased MTT with increased or preserved rCBV can be interpreted as a compensatory vasodilatory response to reduced perfusion pressure, presumably from compression and disturbed flow in the giant aneurysmal sac. When maximal vasodilation has occurred, however, the brain can no longer compensate for diminished perfusion by vasodilation, and rCBV and CBFi diminish. Bypass surgery improves hemodynamics, increasing perfusion pressure and, thus, CBFi. Perfusion MR imaging can be used to evaluate cerebral hemodynamics in patients with intracranial giant aneurysm.BACKGROUND AND PURPOSE: Preoperative assessment of the anatomy and dynamics of cerebral circulation for patients with giant intracranial aneurysm can improve both outcome prediction and therapeutic approach. The aim of our study was to use perfusion MR imaging to evaluate cerebral hemodynamics in such patients before and after extraintracranial high-flow bypass surgery. METHODS: Five patients with a giant aneurysm of the intracranial internal carotid artery underwent MR studies before, 1 week after, and 1 month after high-flow bypass surgery. We performed MR and digital subtraction angiography, and conventional and functional MR sequences (diffusion and perfusion). Surgery consisted of middle cerebral artery (MCA)-internal carotid artery bypass with saphenous vein grafts (n = 4) or MCA-external carotid artery bypass (n = 1). RESULTS: In four patients, MR perfusion study showed impaired hemodynamics in the vascular territory supplied by the MCA of the aneurysm side, characterized by significantly reduced mean cerebral blood flow (CBF), whereas mean transit time (MTT) and regional cerebral blood volume (rCBV) were either preserved, reduced, or increased. After surgery, angiography showed good canalization of the bypass graft. MR perfusion data obtained after surgery showed improved cerebral hemodynamics in all cases, with a return of CBF index (CBFi), MTT, and rCBV to nearly normal values. CONCLUSION: Increased MTT with increased or preserved rCBV can be interpreted as a compensatory vasodilatory response to reduced perfusion pressure, presumably from compression and disturbed flow in the giant aneurysmal sac. When maximal vasodilation has occurred, however, the brain can no longer compensate for diminished perfusion by vasodilation, and rCBV and CBFi diminish. Bypass surgery improves hemodynamics, increasing perfusion pressure and, thus, CBFi. Perfusion MR imaging can be used to evaluate cerebral hemodynamics in patients with intracranial giant aneurysm

The rna-binding ubiquitin ligase mex3a affects glioblastoma tumorigenesis by inducing ubiquitylation and degradation of rig-i

Glioblastoma multiforme (GB) is the most malignant primary brain tumor in humans, with an overall survival of approximatively 15 months. The molecular heterogeneity of GB, as well as its rapid progression, invasiveness and the occurrence of drug-resistant cancer stem cells, limits the efficacy of the current treatments. In order to develop an innovative therapeutic strategy, it is mandatory to identify and characterize new molecular players responsible for the GB malignant phenotype. In this study, the RNA-binding ubiquitin ligase MEX3A was selected from a gene expression analysis performed on publicly available datasets, to assess its biological and still-unknown activity in GB tumorigenesis. We find that MEX3A is strongly up-regulated in GB specimens, and this correlates with very low protein levels of RIG-I, a tumor suppressor involved in differentiation, apoptosis and innate immune response. We demonstrate that MEX3A binds RIG-I and induces its ubiquitylation and proteasome-dependent degradation. Further, the genetic depletion of MEX3A leads to an increase of RIG-I protein levels and results in the suppression of GB cell growth. Our findings unveil a novel molecular mechanism involved in GB tumorigenesis and suggest MEX3A and RIG-I as promising therapeutic targets in GB

Convergence of Quantum Annealing with Real-Time Schrodinger Dynamics

Convergence conditions for quantum annealing are derived for optimization problems represented by the Ising model of a general form. Quantum fluctuations are introduced as a transverse field and/or transverse ferromagnetic interactions, and the time evolution follows the real-time Schrodinger equation. It is shown that the system stays arbitrarily close to the instantaneous ground state, finally reaching the target optimal state, if the strength of quantum fluctuations decreases sufficiently slowly, in particular inversely proportionally to the power of time in the asymptotic region. This is the same condition as the other implementations of quantum annealing, quantum Monte Carlo and Green's function Monte Carlo simulations, in spite of the essential difference in the type of dynamics. The method of analysis is an application of the adiabatic theorem in conjunction with an estimate of a lower bound of the energy gap based on the recently proposed idea of Somma et. al. for the analysis of classical simulated annealing using a classical-quantum correspondence.Comment: 6 pages, minor correction

A multi-physics modelling tool for Reverse Electrodialysis

In this work, a multi-physics modelling approach has been developed for the RED process

Self-reported adherence supports patient preference for the single tablet regimen (STR) in the current cART era

Objective: To analyze self-reported adherence to antiretroviral regimens containing ritonavir-boosted protease inhibitors, non-nucleoside reverse transcriptase inhibitors (NNRTI), raltegravir, and maraviroc. Methods: Overall, 372 consecutive subjects attending a reference center for HIV treatment in Florence, Italy, were enrolled in the study, from December 2010 to January 2012 (mean age 48 years). A self-report questionnaire was filled in. Patients were defined as “non-adherent” if reporting one of the following criteria:<90% of pills taken in the last month, ≥1 missed dose in the last week, spontaneous treatment interruptions reported, or refill problems in the last 3 months. Gender, age, CD4, HIV-RNA, years of therapy, and type of antiretroviral regimen were analyzed with respect to adherence. Results: At the time of the questionnaire, 89.8% of patients had <50 copies/mL HIV-RNA and 14.2% were on their first combined antiretroviral therapy. 57% of patients were prescribed a regimen containing ritonavir boosted protease inhibitors (boosted PI), 41.7% NNRTI, 17.2% raltegravir, and 4.8% maraviroc; 49.5% of the subjects were on bis-in-die regimens, while 50.5% were on once-daily regimens, with 23.1% of these on the single tablet regimen (STR): tenofovir/emtricitabine/efavirenz. The non-adherence proportion was lower in NNRTI than in boosted-PI treatments (19.4% vs 30.2%), and even lower in STR patients (17.4%). In multivariable logistic regression, patients with the NNRTI regimen (OR: 0.56, 95% CI: 0.34–0.94) and the STR (OR: 0.45, 95% CI: 0.22–0.92) reported lower non-adherence. Efavirenz regimens were also associated with lower non-adherence (OR: 0.42, 95% CI: 0.21–0.83), while atazanavir/ritonavir regimens were associated with higher non-adherence. No other relation to specific antiretroviral drugs was found. A higher CD4 count, lower HIV-RNA, and older age were also found to be associated with lower non-adherence, while a longer time on combined antiretroviral therapy was related to higher non-adherence. Conclusion: In conclusion, older age, higher CD4 cell counts, lower HIV-RNA viral loads, and the use of STR are all related to lower non-adherence. In particular, the use of STR maintains an advantage in improving adherence with respect to other cARTs, even with the availability of new, well-tolerated antiretroviral drugs and drug classes in recent years

Iterative Approximate Consensus in the presence of Byzantine Link Failures

This paper explores the problem of reaching approximate consensus in synchronous point-to-point networks, where each directed link of the underlying communication graph represents a communication channel between a pair of nodes. We adopt the transient Byzantine link failure model [15, 16], where an omniscient adversary controls a subset of the directed communication links, but the nodes are assumed to be fault-free. Recent work has addressed the problem of reaching approximate consen- sus in incomplete graphs with Byzantine nodes using a restricted class of iterative algorithms that maintain only a small amount of memory across iterations [22, 21, 23, 12]. However, to the best of our knowledge, we are the first to consider approximate consensus in the presence of Byzan- tine links. We extend our past work that provided exact characterization of graphs in which the iterative approximate consensus problem in the presence of Byzantine node failures is solvable [22, 21]. In particular, we prove a tight necessary and sufficient condition on the underlying com- munication graph for the existence of iterative approximate consensus algorithms under transient Byzantine link model. The condition answers (part of) the open problem stated in [16].Comment: arXiv admin note: text overlap with arXiv:1202.609

Convergence theorems for quantum annealing

We prove several theorems to give sufficient conditions for convergence of quantum annealing, which is a protocol to solve generic optimization problems by quantum dynamics. In particular the property of strong ergodicity is proved for the path-integral Monte Carlo implementation of quantum annealing for the transverse Ising model under a power decay of the transverse field. This result is to be compared with the much slower inverse-log decay of temperature in the conventional simulated annealing. Similar results are proved for the Green's function Monte Carlo approach. Optimization problems in continuous space of particle configurations are also discussed.Comment: 19 page

How Long It Takes for an Ordinary Node with an Ordinary ID to Output?

In the context of distributed synchronous computing, processors perform in rounds, and the time-complexity of a distributed algorithm is classically defined as the number of rounds before all computing nodes have output. Hence, this complexity measure captures the running time of the slowest node(s). In this paper, we are interested in the running time of the ordinary nodes, to be compared with the running time of the slowest nodes. The node-averaged time-complexity of a distributed algorithm on a given instance is defined as the average, taken over every node of the instance, of the number of rounds before that node output. We compare the node-averaged time-complexity with the classical one in the standard LOCAL model for distributed network computing. We show that there can be an exponential gap between the node-averaged time-complexity and the classical time-complexity, as witnessed by, e.g., leader election. Our first main result is a positive one, stating that, in fact, the two time-complexities behave the same for a large class of problems on very sparse graphs. In particular, we show that, for LCL problems on cycles, the node-averaged time complexity is of the same order of magnitude as the slowest node time-complexity. In addition, in the LOCAL model, the time-complexity is computed as a worst case over all possible identity assignments to the nodes of the network. In this paper, we also investigate the ID-averaged time-complexity, when the number of rounds is averaged over all possible identity assignments. Our second main result is that the ID-averaged time-complexity is essentially the same as the expected time-complexity of randomized algorithms (where the expectation is taken over all possible random bits used by the nodes, and the number of rounds is measured for the worst-case identity assignment). Finally, we study the node-averaged ID-averaged time-complexity.Comment: (Submitted) Journal versio

Pleiotropic Outcomes of Glyphosate Exposure: From Organ Damage to Effects on Inflammation, Cancer, Reproduction and Development.

Glyphosate is widely used worldwide as a potent herbicide. Due to its ubiquitous use, it is detectable in air, water and foodstuffs and can accumulate in human biological fluids and tissues representing a severe human health risk. In plants, glyphosate acts as an inhibitor of the shi-kimate pathway, which is absent in vertebrates. Due to this, international scientific authorities have long‐considered glyphosate as a compound that has no or weak toxicity in humans. Howev-er, increasing evidence has highlighted the toxicity of glyphosate and its formulations in animals and human cells and tissues. Thus, despite the extension of the authorization of the use of glypho-sate in Europe until 2022, several countries have begun to take precautionary measures to reduce its diffusion. Glyphosate has been detected in urine, blood and maternal milk and has been found to induce the generation of reactive oxygen species (ROS) and several cytotoxic and genotoxic effects in vitro and in animal models directly or indirectly through its metabolite, ami-nomethylphosphonic acid (AMPA). This review aims to summarize the more relevant findings on the biological effects and underlying molecular mechanisms of glyphosate, with a particular focus on glyphosateʹs potential to induce inflammation, DNA damage and alterations in gene expression profiles as well as adverse effects on reproduction and development

Negative Impurity Magnetic Susceptibility and Heat Capacity in a Kondo Model with Narrow Peaks in the Local Density of Electron States

Temperature dependencies of the impurity magnetic susceptibility, entropy, and heat capacity have been obtained by the method of numerical renormalization group and exact diagonalization for the Kondo model with peaks in the electron density of states near the Fermi energy (in particular, with logarithmic Van Hove singularities). It is shown that these quantities can be {\it negative}. A new effect has been predicted (which, in principle, can be observed experimentally), namely, the decrease in the magnetic susceptibility and heat capacity of a nonmagnetic sample upon the addition of magnetic impurities into it