Computed microtomography visualization and quantification of mouse ischemic brain lesion by nonionic radio contrast agents.

AIM: To explore the possibility of brain imaging by microcomputed tomography (microCT) using x-ray contrasting methods to visualize mouse brain ischemic lesions after middle cerebral artery occlusion (MCAO). ----- METHODS: Isolated brains were immersed in ionic or nonionic radio contrast agent (RCA) for 5 days and subsequently scanned using microCT scanner. To verify whether ex-vivo microCT brain images can be used to characterize ischemic lesions, they were compared to Nissl stained serial histological sections of the same brains. To verify if brains immersed in RCA may be used afterwards for other methods, subsequent immunofluorescent labeling with anti-NeuN was performed. ----- RESULTS: Nonionic RCA showed better gray to white matter contrast in the brain, and therefore was selected for further studies. MicroCT measurement of ischemic lesion size and cerebral edema significantly correlated with the values determined by Nissl staining (ischemic lesion size: P=0.0005; cerebral edema: P=0.0002). Brain immersion in nonionic RCA did not affect subsequent immunofluorescent analysis and NeuN immunoreactivity. ----- CONCLUSION: MicroCT method was proven to be suitable for delineation of the ischemic lesion from the non-infarcted tissue, and quantification of lesion volume and cerebral edema

Polynomial Time Algorithms for Branching Markov Decision Processes and Probabilistic Min(Max) Polynomial Bellman Equations

We show that one can approximate the least fixed point solution for a multivariate system of monotone probabilistic max(min) polynomial equations, referred to as maxPPSs (and minPPSs, respectively), in time polynomial in both the encoding size of the system of equations and in log(1/epsilon), where epsilon > 0 is the desired additive error bound of the solution. (The model of computation is the standard Turing machine model.) We establish this result using a generalization of Newton's method which applies to maxPPSs and minPPSs, even though the underlying functions are only piecewise-differentiable. This generalizes our recent work which provided a P-time algorithm for purely probabilistic PPSs. These equations form the Bellman optimality equations for several important classes of infinite-state Markov Decision Processes (MDPs). Thus, as a corollary, we obtain the first polynomial time algorithms for computing to within arbitrary desired precision the optimal value vector for several classes of infinite-state MDPs which arise as extensions of classic, and heavily studied, purely stochastic processes. These include both the problem of maximizing and mininizing the termination (extinction) probability of multi-type branching MDPs, stochastic context-free MDPs, and 1-exit Recursive MDPs. Furthermore, we also show that we can compute in P-time an epsilon-optimal policy for both maximizing and minimizing branching, context-free, and 1-exit-Recursive MDPs, for any given desired epsilon > 0. This is despite the fact that actually computing optimal strategies is Sqrt-Sum-hard and PosSLP-hard in this setting. We also derive, as an easy consequence of these results, an FNP upper bound on the complexity of computing the value (within arbitrary desired precision) of branching simple stochastic games (BSSGs)

Analysis of Probabilistic Basic Parallel Processes

Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They are the simplest common model of concurrent programs that allows unbounded spawning of processes. In the probabilistic version of BPPs, every process generates other processes according to a probability distribution. We study the decidability and complexity of fundamental qualitative problems over probabilistic BPPs -- in particular reachability with probability 1 of different classes of target sets (e.g. upward-closed sets). Our results concern both the Markov-chain model, where processes are scheduled randomly, and the MDP model, where processes are picked by a scheduler.Comment: This is the technical report for a FoSSaCS'14 pape

Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS

Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time of a given VASS. In particular, we focus on the practically important case of obtaining polynomial bounds on termination time. Our main contributions are as follows: First, we present a polynomial-time algorithm for deciding whether a given VASS has a linear asymptotic complexity. We also show that if the complexity of a VASS is not linear, it is at least quadratic. Second, we classify VASS according to quantitative properties of their cycles. We show that certain singularities in these properties are the key reason for non-polynomial asymptotic complexity of VASS. In absence of singularities, we show that the asymptotic complexity is always polynomial and of the form $\Theta(n^k)$, for some integer $k\leq d$, where $d$ is the dimension of the VASS. We present a polynomial-time algorithm computing the optimal $k$. For general VASS, the same algorithm, which is based on a complete technique for the construction of ranking functions in VASS, produces a valid lower bound, i.e., a $k$ such that the termination complexity is $\Omega(n^k)$. Our results are based on new insights into the geometry of VASS dynamics, which hold the potential for further applicability to VASS analysis.Comment: arXiv admin note: text overlap with arXiv:1708.0925

Optimal Strategies in Infinite-state Stochastic Reachability Games

We consider perfect-information reachability stochastic games for 2 players on infinite graphs. We identify a subclass of such games, and prove two interesting properties of it: first, Player Max always has optimal strategies in games from this subclass, and second, these games are strongly determined. The subclass is defined by the property that the set of all values can only have one accumulation point -- 0. Our results nicely mirror recent results for finitely-branching games, where, on the contrary, Player Min always has optimal strategies. However, our proof methods are substantially different, because the roles of the players are not symmetric. We also do not restrict the branching of the games. Finally, we apply our results in the context of recently studied One-Counter stochastic games

Analyzing probabilistic pushdown automata

The paper gives a summary of the existing results about algorithmic analysis of probabilistic pushdown automata and their subclasses.V článku je podán přehled známých výsledků o pravděpodobnostních zásobníkových automatech a některých jejich podtřídách

Unbiased high-content screening reveals Aβ- and tau-independent synaptotoxic activities in human brain homogenates from Alzheimer\u27s patients and high-pathology controls

Alzheimer\u27s disease (AD) is tightly correlated with synapse loss in vulnerable brain regions. It is assumed that specific molecular entities such as Aβ and tau cause synapse loss in AD, yet unbiased screens for synaptotoxic activities have not been performed. Here, we performed size exclusion chromatography on soluble human brain homogenates from AD cases, high pathology non-demented controls, and low pathology age-matched controls using our novel high content primary cultured neuron-based screening assay. Both presynaptic and postsynaptic toxicities were elevated in homogenates from AD cases and high pathology non-demented controls to a similar extent, with more modest synaptotoxic activities in homogenates from low pathology normal controls. Surprisingly, synaptotoxic activities were found in size fractions peaking between the 17-44 kDa size standards that did not match well with Aβ and tau immunoreactive species in these homogenates. The fractions containing previously identified high molecular weight soluble amyloid beta aggregates/ oligomers were non-toxic in this assay. Furthermore, immunodepletion of Aβ and tau did not reduce synaptotoxic activity. This result contrasts with previous findings involving the same methods applied to 3xTg-AD mouse brain extracts. The nature of the synaptotoxic species has not been identified. Overall, our data indicates one or more potential Aβ and tau independent synaptotoxic activities in human AD brain homogenates. This result aligns well with the key role of synaptic loss in the early cognitive decline and may provide new insight into AD pathophysiology

Persistence of the Exotic Mirid \u3ci\u3eNesidiocoris tenuis\u3c/i\u3e (Hemiptera: Miridae) in South Texas

The Rio Grande Valley is one of the most productive agricultural areas in the U.S and is located in the southernmost part of Texas. In October 2013, we detected an exotic plant bug, Nesidiocoris tenuis Reuter (Hemiptera: Miridae: Bryocorinae) occurring in the region. Nesidiocoris tenuis has zoophytophagous habits; however, in the absence of insect prey, it feeds on its plant hosts. After its morphological and genetic identification, this study monitored the population of N. tenuis in its introduction phase in commercial fields and corroborated its establishment in research fields for three years. Populations of N. tenuis were high during the fall and low during winter. This study found that N. tenuis populations were higher in tomato fields as compared to adjacent pepper, okra, and squash fields, indicating its host preferences during the introduction phase. Recurrent population growth patterns suggest that N. tenuis was established in Rio Grande Valley with permanent populations in tomato fields. In addition, N. tenuis populations were affected by tomato cultivar selection and by plastic mulch color. The presence of N. tenuis could establish a new trophic insect relationship for vegetable production. However, it is unknown if the presence of N. tenuis may help to control pests of economic importance, such as whiteflies in cotton, or become a pest on sesame, an emerging crop