Degradation of temporal contrast from post-pedestal interference with a chirped pulse in an optical parametric amplifier

Pre-pedestal generation is observed in a 0.35-PW laser front end coming from a post-pedestal via instantaneous gain and pump depletion in an optical parametric amplifier during chirped-pulse amplification. Generalized simulations show how this effect arises from gain nonlinearity and applies to all optical parametric chirped-pulse-amplification systems with a post-pedestal. An experiment minimizing the effect of B-integral is used to isolate and study the newly observed conversion of a continuous post-pedestal into a continuous pre-pedestal. Matching numerical simulations confirm experimental results and additionally reveal how third-order dispersion largely controls the slope of the generated pre-pedestal.

Global forecasts in reservoir computers

A reservoir computer is a machine learning model that can be used to predict the future state(s) of time-dependent processes, e.g., dynamical systems. In practice, data in the form of an input-signal are fed into the reservoir. The trained reservoir is then used to predict the future state of this signal. We develop a new method for not only predicting the future dynamics of the input-signal but also the future dynamics starting at an arbitrary initial condition of a system. The systems we consider are the Lorenz, Rossler, and Thomas systems restricted to their attractors. This method, which creates a global forecast, still uses only a single input-signal to train the reservoir but breaks the signal into many smaller windowed signals. We examine how well this windowed method is able to forecast the dynamics of a system starting at an arbitrary point on a system's attractor and compare this to the standard method without windows. We find that the standard method has almost no ability to forecast anything but the original input-signal while the windowed method can capture the dynamics starting at most points on an attractor with significant accuracy.

Final amplifier of an ultra-intense all-OPCPA system with 13-J output signal energy and 41% pump-to-signal conversion efficiency

Optical parametric chirped-pulse amplification (OPCPA) using high-energy Nd:glass lasers has the potential to produce ultra-intense pulses (>1023 W/cm2). We report on the performance of the final high-efficiency amplifier in an OPCPA system based on large-aperture (63 × 63-mm2) partially deuterated potassium dihydrogen phosphate (DKDP) crystals. The seed beam (180-nm bandwidth, 110 mJ) was provided by the preceding OPCPA stages. A maximum pump-to-signal conversion efficiency of 41% and signal energy up to 13 J were achieved with a 52-mm-long DKDP crystal due to the flattop super-Gaussian pump beam profile and flat-in-time pulse shape.

Achieving 100 GW idler pulses from an existing petawatt optical parametric chirped pulse amplifier

Optical parametric chirped-pulse-amplification produces two broadband pulses, a signal and an idler, that can both provide peak powers >100 GW. In most cases the signal is used, but compressing the longer-wavelength idler opens up opportunities for experiments where the driving laser wavelength is a key parameter. This paper will describe several subsystems that were added to a petawatt class, Multi-Terawatt optical parametric amplifier line (MTW-OPAL) at the Laboratory for Laser Energetics to address two long-standing issues introduced by the use of the idler, angular dispersion, and spectral phase reversal. To the best of our knowledge, this is the first time that compensation of angular dispersion and phase reversal has been achieved in a single system and results in a 100 GW, 120-fs duration, pulse at 1170 nm.

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

Short-term risk prediction after major lower limb amputation: PERCEIVE study

BACKGROUND

The accuracy with which healthcare professionals (HCPs) and risk prediction tools predict outcomes after major lower limb amputation (MLLA) is uncertain. The aim of this study was to evaluate the accuracy of predicting short-term (30 days after MLLA) mortality, morbidity, and revisional surgery.

METHODS

The PERCEIVE (PrEdiction of Risk and Communication of outcomE following major lower limb amputation: a collaboratIVE) study was launched on 1 October 2020. It was an international multicentre study, including adults undergoing MLLA for complications of peripheral arterial disease and/or diabetes. Preoperative predictions of 30-day mortality, morbidity, and MLLA revision by surgeons and anaesthetists were recorded. Probabilities from relevant risk prediction tools were calculated. Evaluation of accuracy included measures of discrimination, calibration, and overall performance.

RESULTS

Some 537 patients were included. HCPs had acceptable discrimination in predicting mortality (931 predictions; C-statistic 0.758) and MLLA revision (565 predictions; C-statistic 0.756), but were poor at predicting morbidity (980 predictions; C-statistic 0.616). They overpredicted the risk of all outcomes. All except three risk prediction tools had worse discrimination than HCPs for predicting mortality (C-statistics 0.789, 0.774, and 0.773); two of these significantly overestimated the risk compared with HCPs. SORT version 2 (the only tool incorporating HCP predictions) demonstrated better calibration and overall performance (Brier score 0.082) than HCPs. Tools predicting morbidity and MLLA revision had poor discrimination (C-statistics 0.520 and 0.679).

CONCLUSION

Clinicians predicted mortality and MLLA revision well, but predicted morbidity poorly. They overestimated the risk of mortality, morbidity, and MLLA revision. Most short-term risk prediction tools had poorer discrimination or calibration than HCPs. The best method of predicting mortality was a statistical tool that incorporated HCP estimation.

Analysis of pump-to-signal noise transfer in two-stage ultra-broadband optical parametric chirped-pulse amplification

In optical parametric chirped-pulse amplification (OPCPA), pump temporal intensity modulation is transferred to the chirped-signal spectrum via instantaneous parametric gain and results in contrast degradation of the recompressed signal. We investigate, for the first time to our knowledge, the pump-to-signal noise transfer in a two-stage ultra-broadband OPCPA pumped by a single laser and show the dependence of pump-induced signal noise, characterized both before and after pulse compression, on the difference in pump-seed delay in the two stages. We demonstrate an up-to-15-dB reduction of the pump-induced contrast degradation via pump-seed delay optimization. Experiments and simulations show that, even when parametric amplifiers are operated in saturation, the pump-seed delay can be used to minimize the pump-induced contrast degradation that is attributed largely to the noises from the unsaturated edges of the pulse and that of the beam.

Looking down: a model for visual route following in flying insects

Insect visual navigation is often assumed to depend on panoramic views of the horizon, and how these change as the animal moves. However, it is known that honey bees can visually navigate in flat, open meadows where visual information at the horizon is minimal, or would remain relatively constant across a wide range of positions. In this paper we hypothesise that these animals can navigate using view memories of the ground. We find that in natural scenes, low resolution views from an aerial perspective of ostensibly self-similar terrain (e.g. within a field of grass) provide surprisingly robust descriptors of precise spatial locations. We propose a new visual route following approach that makes use of transverse oscillations to centre a flight path along a sequence of learned views of the ground. We deploy this model on an autonomous quadcopter and demonstrate that it provides robust performance in the real world on journeys of up to 30 m. The success of our method is contingent on a robust view matching process which can evaluate the familiarity of a view with a degree of translational invariance. We show that a previously developed wavelet based bandpass orientated filter approach fits these requirements well, exhibiting double the catchment area of standard approaches. Using a realistic simulation package, we evaluate the robustness of our approach to variations in heading direction and aircraft height between inbound and outbound journeys. We also demonstrate that our approach can operate using a vision system with a biologically relevant visual acuity and viewing direction.

Using Integrative Modeling Platform to compute, validate, and archive a model of a protein complex structure

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).

Simulation of grating compressor misalignment tolerances and mitigation strategies for chirped-pulse-amplification systems of varying bandwidths and beam sizes

The effects of pulse compressor grating misalignment on pulse duration and focusability are simulated for chirped-pulse-amplification systems of varying bandwidths, beam sizes, groove densities, and incident angles. Tilt-alignment tolerances are specified based on a 2 drop in focused intensity, illustrating how tolerances scale with bandwidth and compressor beam size, which scales with energy when transformed via known grating damage thresholds. Grating-alignment tolerance scaling with grating groove density and incident/diffracted angles is investigated and applied to compressor design. A correlation between grating tip and in-plane rotation error sensitivity is defined and used to compensate residual out-of-plane angular dispersion, even for ultra-broadband pulses. Simulation of dispersion compensation methods after grating misalignment is shown to mitigate pulse lengthening, limited by temporal contrast degradation and higher-order effects for ultrabroad bandwidths.

Modeling Biological Complexes Using Integrative Modeling Platform

Integrative structure modeling provides 3D models of macromolecular systems that are based on information from multiple types of experiments, physical principles, statistical inferences, and prior structural models. Here, we provide a hands-on realistic example of integrative structure modeling of the quaternary structure of the actin, tropomyosin, and gelsolin protein assembly based on electron microscopy, solution X-ray scattering, and chemical crosslinking data for the complex as well as excluded volume, sequence connectivity, and rigid atomic X-ray structures of the individual subunits. We follow the general four-stage process for integrative modeling, including gathering the input information, converting the input information into a representation of the system and a scoring function, sampling alternative model configurations guided by the scoring function, and analyzing the results. The computational aspects of this approach are implemented in our open-source Integrative Modeling Platform (IMP), a comprehensive and extensible software package for integrative modeling ( https://integrativemodeling.org ). In particular, we rely on the Python Modeling Interface (PMI) module of IMP that provides facile mixing and matching of macromolecular representations, restraints based on different types of information, sampling algorithms, and analysis including validations of the input data and output models. Finally, we also outline how to deposit an integrative structure and corresponding experimental data into PDB-Dev, the nascent worldwide Protein Data Bank (wwPDB) resource for archiving and disseminating integrative structures ( https://pdb-dev.wwpdb.org ). The example application provides a starting point for a user interested in using IMP for integrative modeling of other biomolecular systems.

SAXS Merge: an automated statistical method to merge SAXS profiles using Gaussian processes

Small-angle X-ray scattering (SAXS) is an experimental technique that allows structural information on biomolecules in solution to be gathered. High-quality SAXS profiles have typically been obtained by manual merging of scattering profiles from different concentrations and exposure times. This procedure is very subjective and results vary from user to user. Up to now, no robust automatic procedure has been published to perform this step, preventing the application of SAXS to high-throughput projects. Here, SAXS Merge, a fully automated statistical method for merging SAXS profiles using Gaussian processes, is presented. This method requires only the buffer-subtracted SAXS profiles in a specific order. At the heart of its formulation is non-linear interpolation using Gaussian processes, which provides a statement of the problem that accounts for correlation in the data.

Comparative Modeling of Drug Target Proteins☆

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state-of-the-art by a number of specific examples.

Optimized atomic statistical potentials: assessment of protein interfaces and loops

MOTIVATION

Statistical potentials have been widely used for modeling whole proteins and their parts (e.g. sidechains and loops) as well as interactions between proteins, nucleic acids and small molecules. Here, we formulate the statistical potentials entirely within a statistical framework, avoiding questionable statistical mechanical assumptions and approximations, including a definition of the reference state.

RESULTS

We derive a general Bayesian framework for inferring statistically optimized atomic potentials (SOAP) in which the reference state is replaced with data-driven 'recovery' functions. Moreover, we restrain the relative orientation between two covalent bonds instead of a simple distance between two atoms, in an effort to capture orientation-dependent interactions such as hydrogen bonds. To demonstrate this general approach, we computed statistical potentials for protein-protein docking (SOAP-PP) and loop modeling (SOAP-Loop). For docking, a near-native model is within the top 10 scoring models in 40% of the PatchDock benchmark cases, compared with 23 and 27% for the state-of-the-art ZDOCK and FireDock scoring functions, respectively. Similarly, for modeling 12-residue loops in the PLOP benchmark, the average main-chain root mean square deviation of the best scored conformations by SOAP-Loop is 1.5 Å, close to the average root mean square deviation of the best sampled conformations (1.2 Å) and significantly better than that selected by Rosetta (2.1 Å), DFIRE (2.3 Å), DOPE (2.5 Å) and PLOP scoring functions (3.0 Å). Our Bayesian framework may also result in more accurate statistical potentials for additional modeling applications, thus affording better leverage of the experimentally determined protein structures.

AVAILABILITY AND IMPLEMENTATION

SOAP-PP and SOAP-Loop are available as part of MODELLER (http://salilab.org/modeller).

Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies

A set of software tools for building and distributing models of macromolecular assemblies uses an integrative structure modeling approach, which casts the building of models as a computational optimization problem where information is encoded into a scoring function used to evaluate candidate models.

MultiFit: a web server for fitting multiple protein structures into their electron microscopy density map

Advances in electron microscopy (EM) allow for structure determination of large biological assemblies at increasingly higher resolutions. A key step in this process is fitting multiple component structures into an EM-derived density map of their assembly. Here, we describe a web server for this task. The server takes as input a set of protein structures in the PDB format and an EM density map in the MRC format. The output is an ensemble of models ranked by their quality of fit to the density map. The models can be viewed online or downloaded from the website. The service is available at; http://salilab.org/multifit/ and http://bioinfo3d.cs.tau.ac.il/.

UCSF Chimera, MODELLER, and IMP: an integrated modeling system

Structural modeling of macromolecular complexes greatly benefits from interactive visualization capabilities. Here we present the integration of several modeling tools into UCSF Chimera. These include comparative modeling by MODELLER, simultaneous fitting of multiple components into electron microscopy density maps by IMP MultiFit, computing of small-angle X-ray scattering profiles and fitting of the corresponding experimental profile by IMP FoXS, and assessment of amino acid sidechain conformations based on rotamer probabilities and local interactions by Chimera.

Elemental and non-elemental olfactory learning in Drosophila

Brain complexity varies across many orders of magnitude between animals, and it is often assumed that complexity underpins cognition. It is thus important to explore the cognitive capacity of widely used model organisms such as Drosophila. We systematically investigated the fly's ability to learn discriminations involving compound olfactory stimuli associated with shock. Flies could distinguish binary mixtures (AB+ CD-), including overlapping mixtures (AB+ BC-). They could learn positive patterning (AB+A- B-) but could not learn negative patterning (A+ B+ AB-) or solve a biconditional discrimination task (AB+ CD+ AC- BD-). Learning about the elements of a compound (AB+) was not affected by prior conditioning of one of the elements (A+ AB+): flies do not exhibit blocking in this task. We compare these results with the predictions from simulation of several well-known theoretical models of learning, and find none are fully consistent with the overall pattern of observed behaviour.

Integrative structure modeling of macromolecular assemblies from proteomics data

Proteomics techniques have been used to generate comprehensive lists of protein interactions in a number of species. However, relatively little is known about how these interactions result in functional multiprotein complexes. This gap can be bridged by combining data from proteomics experiments with data from established structure determination techniques. Correspondingly, integrative computational methods are being developed to provide descriptions of protein complexes at varying levels of accuracy and resolution, ranging from complex compositions to detailed atomic structures.

Comparative protein structure modeling using MODELLER

Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Comparative protein structure modeling using Modeller

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Protein structure fitting and refinement guided by cryo-EM density

For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.

Protein structure modeling with MODELLER

Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. This chapter presents an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of similar protocols (correction of protcols) has resulted in models of useful accuracy for domains in more than half of all known protein sequences.

Processing of first-order motion in marmoset visual cortex is influenced by second-order motion

We measured the responses of single neurons in marmoset visual cortex (V1, V2, and the third visual complex) to moving first-order stimuli and to combined first- and second-order stimuli in order to determine whether first-order motion processing was influenced by second-order motion. Beat stimuli were made by summing two gratings of similar spatial frequency, one of which was static and the other was moving. The beat is the product of a moving sinusoidal carrier (first-order motion) and a moving low-frequency contrast envelope (second-order motion). We compared responses to moving first-order gratings alone with responses to beat patterns with first-order and second-order motion in the same direction as each other, or in opposite directions to each other in order to distinguish first-order and second-order direction-selective responses. In the majority (72%, 67/93) of cells (V1 73%, 45/62; V2 70%, 16/23; third visual complex 75%, 6/8), responses to first-order motion were significantly influenced by the addition of a second-order signal. The second-order envelope was more influential when moving in the opposite direction to the first-order stimulus, reducing first-order direction sensitivity in V1, V2, and the third visual complex. We interpret these results as showing that first-order motion processing through early visual cortex is not separate from second-order motion processing; suggesting that both motion signals are processed by the same system.

A model of antennal wall-following and escape in the cockroach

Cockroaches exploit tactile cues from their antennae to avoid predators. During escape running the same sensors are used to follow walls. We hypothesise that selection of these mutually exclusive behaviours can be explained without representation of the stimulus or an explicit switching mechanism. A neural model is presented that embodies this hypothesis. The model incorporates behavioural and neurophysiological data and is embedded in a mobile robot in order to test the response to stimuli in the real world. The system is shown to account for data on escape direction and high-speed wall-following in the cockroach, including the counter-intuitive observation that faster running cockroaches maintain a closer distance to the wall. The wall-following behaviour is extended to include discrimination of tactile escape cues according to behavioural context. We conclude by highlighting questions arising from the robot experiments that suggest interesting hypotheses to test in the cockroach.

Detection of HCV and HIV-1 antibody negative infections in Scottish and Northern Ireland blood donations by nucleic acid amplification testing

BACKGROUND AND OBJECTIVES

To reduce the risk of transfusion-transmissible viruses entering the blood supply, the nucleic acid amplification testing (NAT) was implemented to screen Scottish and Northern Irish blood donations in minipools. After 5 years of NAT for hepatitis C virus (HCV) and 2 years for human immunodeficiency virus-1 (HIV-1), the yield of serologically negative, nucleic acid positive 'window donations' and cost-benefit of NAT is under review.

MATERIALS AND METHODS

When the Scottish National Blood Transfusion Service (SNBTS) implemented NAT in 1999, a fully automated 'black box' system was not available. Therefore, an 'in-house' assimilated NAT assay was developed, validated and implemented. The system is flexible and allows testing for additional viral markers to be introduced with relative ease.

RESULTS

The HCV and HIV NAT assays have 95% detection levels of 7.25 IU/ml and 39.8 IU/ml, respectively, as determined by probit analysis. One HCV (1 in 1.9 million) and one HIV (1 in 0.77 million) window donation have been detected in 5 and 2 years, respectively, of NAT.

CONCLUSION

The SNBTS NAT assays are robust and have performed consistently over the last 5 years. The design of the in-house system allowed HIV NAT to be added in 2003 at a relatively small additional cost per sample, although for both assays, the royalty fee far exceeds the cost of the test itself. Clearly NAT has a benefit in improving the safety of the blood supply although the risks of transfusion-transmitted viral infections, as reported in the Serious Hazards of Transfusion (SHOT) report, are extremely low. Also, in UK the yield of HCV antibody negative, NAT positive donations is far lower than predicted although the early detection of an HIV window period donation and the increase of HIV in the blood donor and general populations may provide a stronger case for HIV NAT. SUMMARY SENTENCE: The yield of HCV and HIV NAT in UK is significantly less than that anticipated from statistical models.

MODBASE, a database of annotated comparative protein structure models, and associated resources

MODBASE (http://salilab.org/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on the MODELLER package for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE uses the MySQL relational database management system for flexible querying and CHIMERA for viewing the sequences and structures (http://www.cgl.ucsf.edu/chimera/). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different data sets. The largest data set contains 1,26,629 models for domains in 659,495 out of 1,182,126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only models based on alignments with significant similarity scores and models assessed to have the correct fold despite insignificant alignments are included. Another model data set supports target selection and structure-based annotation by the New York Structural Genomics Research Consortium; e.g. the 53 new structures produced by the consortium allowed us to characterize structurally 24,113 sequences. MODBASE also contains binding site predictions for small ligands and a set of predicted interactions between pairs of modeled sequences from the same genome. Our other resources associated with MODBASE include a comprehensive database of multiple protein structure alignments (DBALI, http://salilab.org/dbali) as well as web servers for automated comparative modeling with MODPIPE (MODWEB, http://salilab. org/modweb), modeling of loops in protein structures (MODLOOP, http://salilab.org/modloop) and predicting functional consequences of single nucleotide polymorphisms (SNPWEB, http://salilab. org/snpweb).

Anxiety-related bias in the classification of emotionally ambiguous facial expressions

High- and low-trait socially anxious individuals classified the emotional expressions of photographic quality continua of interpolated ("morphed") facial images that were derived from combining 6 basic prototype emotional expressions to various degrees, with the 2 adjacent emotions arranged in an emotion hexagon. When fear was 1 of the 2 component emotions, the high-trait group displayed enhanced sensitivity for fear. In a 2nd experiment where a mood manipulation was incorporated, again, the high-trait group exhibited enhanced sensitivity for fear. The low-trait group was sensitive for happiness in the control condition. The mood-manipulated group had increased sensitivity for anger expressions, and trait anxiety did not moderate these effects. Interpretations of the results related to the classification of fearful expressions are discussed.

Solution structure of the carboxyl-terminal cysteine-rich domain of the VHv1.1 polydnaviral gene product: comparison with other cystine knot structural folds

Polydnaviruses are an unusual group of insect viruses that have an obligate symbiotic association with certain parasitic wasps. These viruses are transmitted with the wasp egg during oviposition into lepidopteran insects, enabling the survival and development of the egg inside the host larvae. We report the three-dimensional structure of a novel polydnaviral cysteine-rich motif (cys-motif), identified as the carboxyl-terminal domain of a two cys-motif containing polydnaviral VHv1.1 gene product, abbreviated "C-term VHv1.1". This 65-residue domain was identified experimentally by limited proteolysis of the full-length protein and was subsequently cloned in a bacterial expression system for NMR studies. The C-term VHv1.1 3D structure was determined in solution by two-dimensional (1)H NMR spectroscopy. Calculation of the structure was based on a total of 300 upper distance restraints and 20 dihedral angle constraints, and resulted in an ensemble of 25 representative conformers with an average rmsd of 0.47 A from the mean structure for core backbone atoms. The protein core is made of a four beta-strand scaffold held together in a compact structure by three disulfide bonds, which form a cystine knot. The four beta-strands are arranged in an unusual configuration to form a triple-stranded beta-sheet and double-stranded beta-sheet. Comparison with other classes of cystine knots provides indication that C-term VHv1.1 represents a new and distinct cystine knot motif. This analysis provides a structural basis for interpretation of the genetic and amino acid sequence data classifying polydnavirus gene products as members of cysteine-rich protein families.

Can robots make good models of biological behaviour?

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models--the representation of a hypothesis about a target system--are distinguished from several other relationships also termed "modelling" in discussions of scientific explanation. Seven dimensions on which simulation models can differ are defined and distinctions between them discussed: 1.

RELEVANCE

whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments.

An exploratory study in a community National Health Service Trust to understand why enrolled nurses choose not to convert to first-level registration

AIM

The aim of this research study was to more fully understand at local level what it was that prevented enrolled nurses (ENs) coming forward for conversion to the first level of the United Kingdom Central Council for Nursing, Midwifery and Health Visiting (UKCC) nursing register.

BACKGROUND

An NHS Trust had first-level nursing shortages and looked to the 69 ENs nurses -- 12% of the nursing workforce -- to meet that shortfall via conversion to first-level UKCC nurse registration. Based on local surveys, their intention to convert was the same as national findings, in that high numbers said they wanted to convert. In addition, this NHS Trust provided support and fully funded conversion courses, yet they did not come forward.

METHODS

A qualitative approach based on focus groups with ENs was adopted to research this 'problem' within the local organizational context.

FINDINGS

ENs were unaware that fully funded course places were available, extremely fearful of the academic expectations of the conversion course and highly committed to family needs. Conclusions Nationally, policymakers advocated the retention of and/or the conversion of ENs, on the grounds that research participants did not perceive or believe that managers were supportive of this proposal.

KEY RECOMMENDATIONS

Create managers who looked beyond the immediate 'problem' of nursing shortages and invested in ENs to retain them in the NHS workforce. Establish local policy and an implementation plan to address the needs of ENs in line with clinical governance and the local nurse retention strategy. Empower ENs who would secure solutions to the issues for themselves.

Demonstration of different patterns of musculoskeletal, soft tissue and visceral involvement in melioidosis using 99m Tc stannous colloid white cell scanning

Melioidosis is an infectious disease that can present with multiple foci of disease involvement. Assessment of disease extent can be difficult, especially in musculoskeletal, visceral and soft tissue infection. This study examined the usefulness of white cell scans in this condition. 99mTc stannous colloid white cell scanning was performed in 21 patients with culture-proven melioidosis. Scan results were compared with clinical assessment and correlated with other forms of imaging. White cell scans demonstrated all but one of the clinically apparent sites of musculoskeletal, visceral and other soft tissue infection. Unsuspected disseminated soft tissue lesions were seen in two patients, including femoral node uptake in both, and these patients subsequently presented with relapsing musculoskeletal disease. Unsuspected musculoskeletal disease was found in one patient. Clinically suspected musculoskeletal disease was accurately excluded by white cell scan in another patient. The results of white cell scanning were also examined in disease of other viscera. Renal and prostatic disease were visualized. Unsuspected parotid involvement was found in two patients. Only one of two spinal lesions was visualized. Pulmonary disease was not necessarily associated with abnormal uptake. White cell scanning is a quick and effective way of assessing the extent of musculoskeletal, visceral and soft tissue disease in melioidosis.

View from the boundary

Re-implementing biological mechanisms on robots not only has technological application but can provide a unique perspective on the nature of sensory processing in animals. To make a robot work, we need to understand the function as part of an embodied, behaving system. I argue that this perspective suggests that the terms "representation" and "information processing" can be misleading when we seek to understand how neurobiological mechanisms carry out perceptual processes. This argument is presented here with reference to a robot model of cricket behavior, which has demonstrated competence comparable to that of the insect, but utilizes surprisingly simple central processing. Instead it depends on sensory interfaces that are well matched to the task, and on the link between environment, action, and perception.

What does robotics offer animal behaviour?

There is a growing body of robot-based research that makes a serious claim to be a new methodology for biology. Robots can be used as models of specific animal systems to test hypotheses regarding the control of behaviour. At levels from learning algorithms to specific dendritic circuits, implementing a proposed controller in a robotic device tests it against real environments in a way that is difficult to simulate. This often provides insight into the true nature of the problem. It also enforces complete specifications and combines bodies of data. Current work can sometimes be criticized for drawing unjustified conclusions given the limited evaluation and inevitable inaccuracies of robot models. Nevertheless, this approach has led to novel hypotheses for animal behaviour and seems likely to provide fruitful results in the future. Copyright 2000 The Association for the Study of Animal Behaviour.

Enrolled nurse conversion: a review of the literature

AIM

The aim of this literature review was to examine the policies and professional literature from the last 50 years about the introduction, the role and subsequent plight of the enrolled nurse (also known as second level nurses), and the need to convert to the first level of the UKCC nursing register.

BACKGROUND

Nurse shortages within the NHS have been cyclical since its inception in 1948. The policy decision to cease the training of enrolled nurses within the frame of modernizing the education and training of the nursing workforce had two distinct implications for enrolled nurses. Firstly, they could choose to stay as enrolled nurses or convert to first level nursing. Nevertheless, enrolled nurses have cited the lack of funded conversion course places, and managerial support for non-conversion.

METHODS

A critical review of the national policies and professional literature concerned with the evaluation of enrolled nurses' contribution to the NHS.

FINDINGS

It was argued that national policy needs to be supported on the ground, whereby enrolled nurses are proactively supported to come forward for conversion and/or meaningful roles are created and sustained where enrolled nurses continue to make a valuable contribution to the NHS agenda. Finally, the paper challenges all NHS organizations to consider the profile and value of enrolled nurses and become proactive in their recruitment and retention of this nursing group.