Effects of Metabolic Cage Housing on Rat Behavior and Performance in the Social Interaction Test

Although the metabolic cage is commonly used for housing nonhuman animals in the laboratory, it has been recognized as constituting a unique stressor. Such an environment would be expected to affect behavioral change in animals housed therein. However, few studies have specifically addressed the nature or magnitude of this change. The current study sought to characterize the behavioral time budget of rats in metabolic cage housing in comparison to that of individually housed animals in standard open-top cages. Rats in metabolic cages spent less time moving, manipulating enrichment, and carrying out rearing behaviors, and there was a corresponding shift toward inactivity. In an applied Social Interaction Test, behavioral scoring implied that metabolic cage housing had an anxiogenic effect. In conclusion, metabolic cage housing produces measurable effects on spontaneous and evoked behavior in rats in the laboratory. These behavioral changes may lead to a negative emotional state in these animals, which could have negative welfare consequences. Further research is needed to quantify the existence and magnitude of such an effect on rat well being.     

Electromyogram refinement using muscle synergy based regulation of uncertain information

Electromyogram signal (EMG) measurement frequently experiences uncertainty attributed to issues caused by technical constraints such as cross talk and maximum voluntary contraction. Due to these problems, individual EMGs exhibit uncertainty in representing their corresponding muscle activations. To regulate this uncertainty, we proposed an EMG refinement, which refines EMGs with regulating the contribution redundancy of the signals from EMGs to approximating torques through EMG-driven torque estimation (EDTE) using the muscular skeletal forward dynamic model. To regulate this redundancy, we must consider the synergistic contribution redundancy of muscles, including “unmeasured” muscles, to approximating torques, which primarily causes redundancy of EDTE. To suppress this redundancy, we used the concept of muscle synergy, which is a key concept of analyzing the neurophysiological regulation of contribution redundancy of muscles to exerting torques. Based on this concept, we designed a muscle-synergy-based EDTE as a framework for EMG refinement, which regulates the abovementioned uncertainty of individual EMGs in consideration of unmeasured muscles. In achieving the proposed EMG refinement, the most considerable point is to suppress a large change such as overestimation attributed to enhancement of the contribution of particular muscles to estimating torques. Therefore it is reasonable to refine EMGs by minimizing the change in EMGs. To evaluate this model, we used a Bland-Altman plot, which quantitatively evaluates the proportional bias of refined signals to EMGs. Through this evaluation, we showed that the proposed EDTE minimizes the bias while approximating torques. Therefore this minimization optimally regulates the uncertainty of EMGs and thereby leads to optimal EMG refinement.     

Refining near‐native protein–protein docking decoys by local resampling and energy minimization

How to refine a near‐native structure to make it closer to its native conformation is an unsolved problem in protein‐structure and protein–protein complex‐structure prediction. In this article, we first test several scoring functions for selecting locally resampled near‐native protein–protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance‐scaled Ideal‐gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein‐InteRaction Energy) for optimization and re‐ranking. Significant improvement of final top‐1 ranked structures over initial near‐native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 Å or more and only 7% increased by 0.5 Å or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

International survey on the use and welfare of zebrafish Danio rerio in research

A survey was conducted regarding zebrafish Danio rerio use for scientific research with a focus on: anaesthesia and euthanasia; housing and husbandry; breeding and production; refinement opportunities. A total of 98 survey responses were received from laboratories in 22 countries in Europe, North America, South America, Asia and Australia. There appears a clear and urgent need to identify the most humane methods of anaesthesia and euthanasia. Aversive responses to MS‐222 were widely observed raising concerns about the use of this anaesthetic for D. rerio. The use of anaesthesia in fin clipping for genetic identification is widely practised and there appears to be an opportunity to further develop less invasive methods and refine this process. Optimization (and potentially standardization) of feeding is an area for further investigation. Given that diet and body condition can have such profound effects on results of experiments, differences in practice could have significant scientific implications. Further research into transition between dark and light phases in the laboratory appears to represent an opportunity to establish best practice. Plants and gravel were not considered practical by many laboratories. The true value and benefits need to be established and communicated. Overproduction is a concern both from ethical and financial viewpoints. There is an opportunity to further reduce wastage of D. rerio. There are clear concerns and opportunities for the scientific community to work together to further improve the welfare of these important laboratory models.     

Experience-dependent refinement of the inhibitory axons projecting to the medial superior olive

Neurons in the medial superior olive (MSO) analyze interaural time differences (ITDs) by comparing the arrival times of the two excitatory inputs from each ear using a coincidence detection mechanism. They also receive a prominent inhibitory, glycinergic projection from the ipsilateral medial nucleus of the trapezoid body (MNTB), which contributes to the fine-tuning of ITD analysis. Here, we investigated developmental changes of the axonal arborisation pattern of single Microruby-labeled MNTB neurons projecting to the MSO region. During the first 2 weeks after hearing onset, the axonal arborisation of MNTB neurons was significantly refined resulting in a narrowed projection area across the tonotopic axis of the MSO and a redistribution of the axonal endsegments to a mostly somatic location. Rearing the animals in omnidirectional noise prevented the structural changes of single MNTB projections. These results indicate that the functional elimination of inhibitory inputs on MSO neurons after hearing onset, as described previously, is paralleled by a structural, site-specific refinement of the inputs and is dependent on the normal acoustic experience of the animal.     

Differentiable, multi-dimensional, knowledge-based energy terms for torsion angle probabilities and propensities

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file.     

Discrimination of near-native structures in protein-protein docking by testing the stability of local minima

Fast Fourier transform (FFT) correlation methods of protein-protein docking, combined with the clustering of low energy conformations, can find a number of local minima on the energy surface. For most complexes, the locations of the near-native structures can be constrained to the 30 largest clusters, each surrounding a local minimum. However, no reliable further discrimination can be obtained by energy measures because the differences in the energy levels between the minima are comparable with the errors in the energy evaluation. In fact, no current scoring function accounts for the entropic contributions that relate to the width rather than the depth of the minima. Since structures at narrow minima loose more entropy, some of the nonnative states can be detected by determining whether or not a local minimum is surrounded by a broad region of attraction on the energy surface. The analysis is based on starting Monte Carlo Minimization (MCM) runs from random points around each minimum, and observing whether a certain fraction of trajectories converge to a small region within the cluster. The cluster is considered stable if such a strong attractor exists, has at least 10 convergent trajectories, is relatively close to the original cluster center, and contains a low energy structure. We studied the stability of clusters for enzyme-inhibitor and antibody-antigen complexes in the Protein Docking Benchmark. The analysis yields three main results. First, all clusters that are close to the native structure are stable. Second, restricting considerations to stable clusters eliminates around half of the false positives, that is, solutions that are low in energy but far from the native structure of the complex. Third, dividing the conformational space into clusters and determining the stability of each cluster, the combined approach is less dependent on a priori information than exploring the potential conformational space by Monte Carlo minimizations.     

OPUS-Rota: a fast and accurate method for side-chain modeling

In this paper, we introduce a fast and accurate side-chain modeling method, named OPUS-Rota. In a benchmark comparison with the methods SCWRL, NCN, LGA, SPRUCE, Rosetta, and SCAP, OPUS-Rota is shown to be much faster than all the methods except SCWRL, which is comparably fast. In terms of overall chi (1) and chi (1+2) accuracies, however, OPUS-Rota is 5.4 and 8.8 percentage points better, respectively, than SCWRL. Compared with NCN, which has the best accuracy in the literature, OPUS-Rota is 1.6 percentage points better for overall chi (1+2) but 0.3 percentage points weaker for overall chi (1). Hence, our algorithm is much more accurate than SCWRL with similar execution speed, and it has accuracy comparable to or better than the most accurate methods in the literature, but with a runtime that is one or two orders of magnitude shorter. In addition, OPUS-Rota consistently outperforms SCWRL on the Wallner and Elofsson homology-modeling benchmark set when the sequence identity is greater than 40%. We hope that OPUS-Rota will contribute to high-accuracy structure refinement, and the computer program is freely available for academic users.     

Paramagnetism-based versus classical constraints: An analysis of the solution structure of Ca Ln calbindin D9k

The relative importance of paramagnetism-based constraints (i.e. pseudocontact shifts, residual dipolar couplings and nuclear relaxation enhancements) with respect to classical constraints in solution structure determinations of paramagnetic metalloproteins has been addressed. The protein selected for the study is a calcium binding protein, calbindin D9k, in which one of the two calcium ions is substituted with cerium(III). From 1823 NOEs, 191 dihedral angles, 15 hydrogen bonds, 769 pseudocontact shifts, 64 orientational constraints, 26 longitudinal relaxation rates, plus 969 pseudocontact shifts from other lanthanides, a final family with backbone r.m.s.d. from the average of 0.25 A was obtained. Then, several families of structures were generated either by removing subsets of paramagnetism-based constraints or by removing increasing numbers of NOEs. The results show the relative importance of the various paramagnetism-based constraints and their good complementarity with the diamagnetic ones. Although a resolved structure cannot be obtained with paramagnetism-based constraints only, it is shown that a reasonably well resolved backbone fold can be safely obtained by retaining as few as 29 randomly chosen long-range NOEs using the standard version of the program PSEUDYANA.