Reactions to disturbances in the context of antipredatory behaviour in a solitary subterranean rodent

We investigated reactions of free-living silvery mole-rats (Heliophobius argenteocinereus) to anthropogenic disturbances. Mole-rats detected soil vibrations caused by man carefully walking at a distance of up to 6 m (proved by radio-telemetry). Occasionally, mole-rats encountered outside a nest retreated there after this type of disturbance. After having their burrows broken into, the mole-rats retreated into deep tunnels, separating themselves from the rest of the burrows by soil plugs. Trapping success of silvery mole-rats using live traps for subterranean rodents was low, which contrasts with data so far published on social bathyergids. Antipredatory function of examined behaviours is discussed.     

Enabling flexibility on a dual head placement machine by optimizing platform-tray-feeder picking operations

The typical circuit card assembly line includes one or more dual head placement machines (DHPMs), which are capable of highly accurate placement and promise the flexibility to assemble a broad variety of circuit card types, each in minimal time. Each DHPM stages components for picking from feeder racks and platform tray feeders (PTFs), which are well suited for components that are large or odd-shaped, contributing to DHPM flexibility. The purpose of this paper is to present a model that can optimize operations that pick from a PTF and/or a feeder rack with the goal of enabling the flexibility needed to assemble a variety of circuit card types efficiently. The primary objective of this paper is a model to optimize operations that pick from a PTF and/or a feeder rack; a secondary objective is computational testing to evaluate the solvability of the model within reasonable run times.     

Identification of a Kinase Profile that Predicts Chromosome Damage Induced by Small Molecule Kinase Inhibitors

Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113×290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity.