Abstract
High-resolution (1″ × 2″) Atacama Large Millimeter Array CO(2−1) observations of the ram pressure stripped galaxy NGC 4402 in the Virgo cluster show some of the clearest evidence yet for the ...impacts of ram pressure on the molecular interstellar medium (ISM) of a galaxy. The eastern side of the galaxy at
r
∼ 4.5 kpc, upon which ram pressure is incident, has a large (width ∼1 kpc, height ∼1 kpc above the disk midplane) extraplanar plume of molecular gas and dust. Molecular gas in the plume region shows distinct noncircular motions in the direction of the ram pressure; the kinematic offset of up to 60 km s
−1
is consistent with acceleration by ram pressure. We also detect a small amount of gas in clouds below the plume that are spatially and kinematically distinct from the surrounding medium, and appear to be decoupled from the stripped ISM. We propose that diffuse molecular gas is directly stripped but giant molecular cloud (GMC) density gas is not directly stripped, and so decouples from lower density stripped gas. However, GMCs become effectively stripped on short timescales. We also find morphological and kinematic signatures of ram pressure compression of molecular gas in a region of intense star formation on the leading side at
r
∼ 3.5 kpc. We propose that the compressed and stripped zones represent different evolutionary stages of the ram pressure interaction, and that feedback from star formation in the compressed zone facilitates the effective stripping of GMCs by making the gas cycle rapidly to a lower density diffuse state.
•This ESO-ESMO ABC 5 Clinical Practice Guideline provides key recommendations for managing advanced breast cancer patients.•It provides updates on managing patients with all breast cancer subtypes, ...LABC, follow-up, palliative and supportive care.•Updated diagnostic and treatment algorithms are also provided.•All recommendations were compiled by a multidisciplinary group of international experts.•Recommendations are based on available clinical evidence and the collective expert opinion of the authors.
This paper considers a class of strategic scenarios in which two networks of agents have opposing objectives with regard to the optimization of a common objective function. In the resulting zero-sum ...game, individual agents collaborate with neighbors in their respective network and have only partial knowledge of the state of the agents in the other network. For the case when the interaction topology of each network is undirected, we synthesize a distributed saddle-point strategy and establish its convergence to the Nash equilibrium for the class of strictly concave–convex and locally Lipschitz objective functions. We also show that this dynamics does not converge in general if the topologies are directed. This justifies the introduction, in the directed case, of a generalization of this distributed dynamics which we show converges to the Nash equilibrium for the class of strictly concave–convex differentiable functions with globally Lipschitz gradients. The technical approach combines tools from algebraic graph theory, nonsmooth analysis, set-valued dynamical systems, and game theory.
The phosphoinositide 3 (PI3)-kinase/Akt signaling pathway has always been a focus of interest in breast cancer due to its role in cell growth, cell proliferation, cell migration and deregulated ...apoptosis. Its activation has been linked to endocrine resistance and worse prognosis in certain subgroups of breast cancer. In addition, deregulation of the PI3K/Akt pathway including PIK3CA activating mutation is frequently present in breast cancer. Multiple efforts have been carried out to target this pathway, initially with pan-PI3K inhibitors with some hint of activity but hampered by their limiting side-effects. A recent large randomized trial in patients with endocrine-resistant PIK3CA-mutant hormone receptor (HR)-positive tumors led to the approval of the first PI3K inhibitor, alpelisib, in combination with fulvestrant. The specificity of alpelisib against the p110α catalytic isoform provided additional efficacy and a better toxicity profile. In this review, we summarize the main research with PI3K inhibitors in breast cancer and we provide some insight of potential future combinations of this treatment in breast cancer patients.
This paper studies a deployment problem for a group of robots where individual agents operate with outdated information about each other’s locations. Our objective is to understand to what extent ...outdated information is still useful and at which point it becomes essential to obtain new, up-to-date information. We propose a self-triggered coordination algorithm based on spatial partitioning techniques with uncertain information. We analyze its correctness in synchronous and asynchronous scenarios, and establish the same convergence guarantees that a synchronous algorithm with perfect information at all times would achieve. The technical approach combines computational geometry, set-valued stability analysis, and event-based systems.
This technical note studies robotic sensor networks performing static coverage optimization with area constraints. Given a density function describing the probability of events happening and a ...performance function measuring the cost to service a location, the objective is to position sensors in the environment so as to minimize the expected servicing cost. Moreover, because of load balancing considerations, the area of the region assigned to each robot is constrained to be a pre-specified amount. We characterize the optimal configurations as center generalized Voronoi configurations. The generalized Voronoi partition depends on a set of weights, one per robot, assigned to the network. We design a Jacobi iterative algorithm to find the weight assignment whose corresponding generalized Voronoi partition satisfies the area constraints. This algorithm is distributed over the generalized Delaunay graph. We also design the ¿move-to-center-and-compute-weight¿ strategy to steer the robotic network towards the set of center generalized Voronoi configurations while monotonically optimizing coverage.
Two decades ago, the recognition of protein misfolding and aggregate accumulation as defining features of neurodegenerative disease set the stage for a thorough examination of how protein quality ...control is maintained in neurons and in other non-neuronal cells in the central nervous system (CNS). Autophagy, a pathway of cellular self-digestion, has emerged as especially important for CNS proteostasis, and autophagy dysregulation has been documented as a defining feature of neurodegeneration in Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Transcription factor EB (TFEB) is one of the main transcriptional regulators of autophagy, as it promotes the expression of genes required for autophagosome formation, lysosome biogenesis, and lysosome function, and it is highly expressed in CNS. Over the last 7 years, TFEB has received considerable attention and TFEB dysfunction has been implicated in the pathogenesis of numerous neurodegenerative disorders. In this review, we delineate the current understanding of how TFEB dysregulation is involved in neurodegeneration, highlighting work done on AD, PD, HD, X-linked spinal & bulbar muscular atrophy, and amyotrophic lateral sclerosis. Because TFEB is a central node in defining autophagy activation status, efforts at understanding the basis for TFEB dysfunction are yielding insights into how TFEB might be targeted for therapeutic application, which may represent an exciting opportunity for the development of a treatment modality with broad application to neurodegeneration.
This paper considers robotic sensor networks performing spatially-distributed estimation tasks. A robotic sensor network is deployed in an environment of interest, and takes successive point ...measurements of a dynamic physical process modeled as a spatio-temporal random field. Taking a Bayesian perspective on the Kriging interpolation technique from geostatistics, we design the distributed Kriged Kalman filter for predictive inference of the random field and of its gradient. The proposed algorithm makes use of a novel distributed strategy to compute weighted least squares estimates when measurements are spatially correlated. This strategy results from the combination of the Jacobi overrelaxation method with dynamic average consensus algorithms. As an application of the proposed algorithm, we design a gradient ascent cooperative strategy and analyze its convergence properties in the absence of measurement errors via stochastic Lyapunov functions. We illustrate our results in simulation.