Efficiency of the CATIE and BACS neuropsychological batteries in assessing cognitive effects of antipsychotic treatments in schizophrenia

Efficient and reliable assessments of cognitive treatment effects are essential for the comparative evaluation of procognitive effects of pharmacologic therapies. Yet, no studies have addressed the sensitivity and efficiency with which neurocognitive batteries evaluate cognitive abilities before and after treatment. Participants were primarily first episode schizophrenia patients who completed baseline (n = 367) and 12-week (n = 219) assessments with the BACS (Brief Assessment of Cognition in Schizophrenia) and CATIE (Clinical Antipsychotic Trials of Intervention Effectiveness) neuropsychological batteries in a clinical trial comparing olanzapine, quetiapine, and risperidone. Exploratory factor analysis revealed that performance on both batteries was characterized by a single factor of generalized cognitive deficit for both baseline performance and cognitive change after treatment. Both batteries estimated similar levels of change following treatment, although the BACS battery required half the administration time. Because a unitary factor characterized baseline cognitive abilities in early psychosis as well as cognitive change after treatment with atypical antipsychotic medications, short batteries such as the BACS may efficiently provide sufficient assessment of procognitive treatment effects with antipsychotic medications. Assessment of cognitive effects of adjunctive therapies targeting specific cognitive domains or impairments may require more extensive testing of the domains targeted to maximize sensitivity for detecting specific predicted cognitive outcomes

Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)-encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non-conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements

Deterministic mathematical modelling for cancer chronotherapeutics: cell population dynamics and treatment optimisation

Chronotherapeutics has been designed and used for more than twenty years as an effective treatment against cancer by a few teams around the world, among whom one of the first is Francis Lévi's at Paul-Brousse hospital (Villejuif, France), in application of circadian clock physiology to determine best infusion times within the 24-hour span for anticancer drug delivery. Mathematical models have been called in the last ten years to give a rational basis to such optimised treatments, for use in the laboratory and ultimately in the clinic. While actual clinical applications of the theoretical optimisation principles found have remained elusive so far to improve chronotherapeutic treatments in use, mathematical models provide proofs of concepts and tracks to be explored experimentally, to progress from theory to bedside. Starting from a simple ordinary differential equation model that allowed setting and numerically solving a drug delivery optimisation problem with toxicity constraints, this modelling enterprise has been extended to represent the division cycle in proliferating cell populations with different molecular targets, to allow for the representation of anticancer drug combinations that are used in clinical oncology. The main point to be made precise in such a therapeutic optimisation problem is to establish, here in the frame of circadian chronobiology, physiologically based differences between healthy and cancer cell populations in their responses to drugs. To this aim, clear biological evidence at the molecular level is still lacking, so that, starting from indirect observations at the experimental and clinical levels and from theoretical considerations on the model, speculations have been made, that will be exposed in this review of cancer chronotherapeutics models with the corresponding optimisation problems and their numerical solutions, to represent these differences between the two cell populations, with regard to circadian clock control

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Sea-air CO2 fluxes in the Southern Ocean for the period 1990–2009

The Southern Ocean (44–75°S) plays a critical role in the global carbon cycle, yet remains one of the most poorly sampled ocean regions. Different approaches have been used to estimate sea–air CO2 fluxes in this region: synthesis of surface ocean observations, ocean biogeochemical models, and atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Southern Ocean sea–air CO2 fluxes between 1990–2009. Using all models and inversions (26), the integrated median annual sea–air CO2 flux of −0.42 ± 0.07 PgC yr−1 for the 44–75°S region, is consistent with the −0.27 ± 0.13 PgC yr−1 calculated using surface observations. The circumpolar region south of 58°S has a small net annual flux (model and inversion median: −0.04 ± 0.07 PgC yr−1 and observations: +0.04 ± 0.02 PgC yr−1), with most of the net annual flux located in the 44 to 58°S circumpolar band (model and inversion median: −0.36 ± 0.09 PgC yr−1 and observations: −0.35 ± 0.09 PgC yr−1). Seasonally, in the 44–58°S region, the median of 5 ocean biogeochemical models captures the observed sea–air CO2 flux seasonal cycle, while the median of 11 atmospheric inversions shows little seasonal change in the net flux. South of 58°S, neither atmospheric inversions nor ocean biogeochemical models reproduce the phase and amplitude of the observed seasonal sea–air CO2 flux, particularly in the AustralWinter. Importantly, no individual atmospheric inversion or ocean biogeochemical model is capable of reproducing both the observed annual mean uptake and the observed seasonal cycle. This raises concerns about projecting future changes in Southern Ocean CO2 fluxes. The median interannual variability from atmospheric inversions and ocean biogeochemical models is substantial in the Southern Ocean; up to 25% of the annual mean flux, with 25% of this interannual variability attributed to the region south of 58°S. Resolving long-term trends is difficult due to the large interannual variability and short time frame (1990–2009) of this study; this is particularly evident from the large spread in trends from inversions and ocean biogeochemical models. Nevertheless, in the period 1990–2009 ocean biogeochemical models do show increasing oceanic uptake consistent with the expected increase of −0.05 PgC yr−1 decade−1. In contrast, atmospheric inversions suggest little change in the strength of the CO2 sink broadly consistent with the results of Le Quéré et al. (2007)

Dynamic Microstructural Evolution of Graphite under Displacing Irradiation

Graphitic materials and graphite composites experience dimensional change when exposed to radiation-induced atomic displacements. This has major implications for current and future technological ranging from nuclear fission reactors to the processing of graphene-silicon hybrid devices. Dimensional change in nuclear graphites is a complex problem involving the filler, binder, porosity, cracks and atomic-level effects all interacting within the polygranular structure. An improved understanding of the atomistic mechanisms which drive dimensional change within individual graphitic crystals is required to feed into the multiscale modelling of this system. In this study, micromechanically exfoliated samples of highly oriented pyrolytic graphite have been ion irradiated and studied in situ using transmission electron microscopy (TEM) in order to gain insights into the response of single graphitic crystals to displacing radiation. Under continuous ion bombardment, a complex dynamic sequence of deformation evolves featuring several distinct stages from the inducement of strain, the creation of dislocations leading to dislocation arrays, the formation of kink band networks and localised doming of the sample. Observing these ion irradiation-induced processes using in situ TEM reveals previously unknown details of the sequence of microstructural developments and physics driving these phenomena. A mechanistic model consistent with the microstructural changes observed is presented

Geocode Matching and Privacy Preservation

Abstract. Geocoding is the process of matching addresses to geographic locations, such as latitudes and longitudes, or local census areas. In many applications, addresses are the key to geo-spatial data analysis and mining. Privacy and confidentiality are of paramount importance when data from, for example, cancer registries or crime databases is geocoded. Various approaches to privacy-preserving data matching, also called record linkage or entity resolution, have been developed in recent times. However, most of these approaches have not considered the specific privacy issues involved in geocode matching. This paper provides a brief introduction to privacy-preserving data and geocode matching, and using several real-world scenarios the issues involved in privacy and confidentiality for data and geocode matching are illustrated. The challenges of making privacy-preserving matching practical for real-world applications are highlighted, and potential directions for future research are discussed