Peregrine: A Pattern-Aware Graph Mining System

Graph mining workloads aim to extract structural properties of a graph by exploring its subgraph structures. General purpose graph mining systems provide a generic runtime to explore subgraph structures of interest with the help of user-defined functions that guide the overall exploration process. However, the state-of-the-art graph mining systems remain largely oblivious to the shape (or pattern) of the subgraphs that they mine. This causes them to: (a) explore unnecessary subgraphs; (b) perform expensive computations on the explored subgraphs; and, (c) hold intermediate partial subgraphs in memory; all of which affect their overall performance. Furthermore, their programming models are often tied to their underlying exploration strategies, which makes it difficult for domain users to express complex mining tasks. In this paper, we develop Peregrine, a pattern-aware graph mining system that directly explores the subgraphs of interest while avoiding exploration of unnecessary subgraphs, and simultaneously bypassing expensive computations throughout the mining process. We design a pattern-based programming model that treats "graph patterns" as first class constructs and enables Peregrine to extract the semantics of patterns, which it uses to guide its exploration. Our evaluation shows that Peregrine outperforms state-of-the-art distributed and single machine graph mining systems, and scales to complex mining tasks on larger graphs, while retaining simplicity and expressivity with its "pattern-first" programming approach.Comment: This is the full version of the paper appearing in the European Conference on Computer Systems (EuroSys), 202

Cellular biophysical dynamics and ion channel activities detected by AFM-based nanorobotic manipulator in insulinoma β-cells

Distinct biochemical, electrochemical and electromechanical coupling processes of pancreatic β-cells may well underlie different response patterns of insulin release from glucose and capsaicin stimulation. Intracellular Ca2+ levels increased rapidly and dose-dependently upon glucose stimulation, accompanied with about threefold rapid increases in cellular stiffness. Subsequently, cellular stiffness diminished rapidly and settled at a value about twofold of the baseline. Capsaicin caused a similar transient increase in intracellular Ca2+ changes. However, cellular stiffness increased gradually to about twofold until leveling off. The current study characterizes for the first time the biophysical properties underlying glucose-induced biphasic responses of insulin secretion, distinctive from the slow and single-phased stiffness response to capsaicin despite similar changes in intracellular Ca2+ levels. The integrated AFM nanorobotics and optical investigation enables the fine dissection of mechano-property from ion channel activities in response to specific and non-specific agonist stimulation, providing novel biomechanical markers for the insulin secretion process. From the Clinical Editor: This study characterizes the biophysical properties underlying glucose-induced biphasic responses of insulin secretion. Integrated AFM nanorobotics and optical investigations provided novel biomechanical markers for the insulin secretion process. © 2013 Elsevier Inc.Link_to_subscribed_fulltex

Data underlying the publication: Cytotoxic activities against MCF-7 and MDA-MB-231, antioxidant and α-glucosidase inhibitory activities of Trachelospermum jasminoides extracts in vitro

cytotoxic activities against MCF-7 and MDA-MB-231 and the antioxidant and α-glucosidase inhibitory activities of the extracts of Trachelospermum jasminoides in vitr