"Particle Informatics": Advancing Our Understanding of Particle Properties through Digital Design

We introduce a combination of existing and novel approaches to the assessment and prediction of particle properties intrinsic to the formulation and manufacture of pharmaceuticals. Naturally following on from established solid form informatics methods, we return to the drug lamotrigine, re-evaluating its context in the Cambridge Structural Database (CSD). We then apply predictive digital design tools built around the CSD-System suite of software, including Synthonic Engineering methods that focus on intermolecular interaction energies, to analyze and understand important particle properties and their effects on several key stages of pharmaceutical manufacturing. We present a new, robust workflow that brings these approaches together to build on the knowledge gained from each step and explain how this knowledge can be combined to provide resolutions at decision points encountered during formulation design and manufacturing processes

A Very Large Number of GABAergic Neurons Are Activated in the Tuberal Hypothalamus during Paradoxical (REM) Sleep Hypersomnia

We recently discovered, using Fos immunostaining, that the tuberal and mammillary hypothalamus contain a massive population of neurons specifically activated during paradoxical sleep (PS) hypersomnia. We further showed that some of the activated neurons of the tuberal hypothalamus express the melanin concentrating hormone (MCH) neuropeptide and that icv injection of MCH induces a strong increase in PS quantity. However, the chemical nature of the majority of the neurons activated during PS had not been characterized. To determine whether these neurons are GABAergic, we combined in situ hybridization of GAD67 mRNA with immunohistochemical detection of Fos in control, PS deprived and PS hypersomniac rats. We found that 74% of the very large population of Fos-labeled neurons located in the tuberal hypothalamus after PS hypersomnia were GAD-positive. We further demonstrated combining MCH immunohistochemistry and GAD67 in situ hybridization that 85% of the MCH neurons were also GAD-positive. Finally, based on the number of Fos-ir/GAD+, Fos-ir/MCH+, and GAD+/MCH+ double-labeled neurons counted from three sets of double-staining, we uncovered that around 80% of the large number of the Fos-ir/GAD+ neurons located in the tuberal hypothalamus after PS hypersomnia do not contain MCH. Based on these and previous results, we propose that the non-MCH Fos/GABAergic neuronal population could be involved in PS induction and maintenance while the Fos/MCH/GABAergic neurons could be involved in the homeostatic regulation of PS. Further investigations will be needed to corroborate this original hypothesis

Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. Author Summary Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc

Chromatic Illumination Discrimination Ability Reveals that Human Colour Constancy Is Optimised for Blue Daylight Illuminations

The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow) and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K), all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed

Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance, and Comparison to Density Functional Theory

Crystal lattice energy is a key property affecting the ease of processing pharmaceutical materials during manufacturing, as well as product performance. We present an extensive comparison of 324 force-field protocols for calculating the lattice energies of single component, organic molecular crystals (further restricted to Z′ less than or equal to one), corresponding to a wide variety of force-fields (DREIDING, Universal, CVFF, PCFF, COMPASS, COMPASSII), optimization routines, and other variations, which could be implemented as part of an automated workflow using the industry standard Materials Studio software. All calculations were validated using a large new dataset (SUB-BIG), which we make publicly available. This dataset comprises public domain sublimation data, from which estimated experimental lattice energies were derived, linked to 235 molecular crystals. Analysis of pharmaceutical relevance was performed according to two distinct methods based upon (A) public and (B) proprietary data. These identified overlapping subsets of SUB-BIG comprising (A) 172 and (B) 63 crystals, of putative pharmaceutical relevance, respectively. We recommend a protocol based on the COMPASSII force field for lattice energy calculations of general organic or pharmaceutically relevant molecular crystals. This protocol was the most highly ranked prior to subsetting and was either the top ranking or amongst the top 15 protocols (top 5%) following subsetting of the dataset according to putative pharmaceutical relevance. Further analysis identified scenarios where the lattice energies calculated using the recommended force-field protocol should either be disregarded (values greater than or equal to zero and/or the messages generated by the automated workflow indicate extraneous atoms were added to the unit cell) or treated cautiously (values less than or equal to −249 kJ/mol), as they are likely to be inaccurate. Application of the recommended force-field protocol, coupled with these heuristic filtering criteria, achieved an root mean-squared error (RMSE) around 17 kJ/mol (mean absolute deviation (MAD) around 11 kJ/mol, Spearman’s rank correlation coefficient of 0.88) across all 226 SUB-BIG structures retained after removing calculation failures and applying the filtering criteria. Across these 226 structures, the estimated experimental lattice energies ranged from −60 to −269 kJ/mol, with a standard deviation around 29 kJ/mol. The performance of the recommended protocol on pharmaceutically relevant crystals could be somewhat reduced, with an RMSE around 20 kJ/mol (MAD around 13 kJ/mol, Spearman’s rank correlation coefficient of 0.76) obtained on 62 structures retained following filtering according to pharmaceutical relevance method B, for which the distribution of experimental values was similar. For a diverse set of 17 SUB-BIG entries, deemed pharmaceutically relevant according to method B, this recommended force-field protocol was compared to dispersion corrected density functional theory (DFT) calculations (PBE + TS). These calculations suggest that the recommended force-field protocol (RMSE around 15 kJ/mol) outperforms PBE + TS (RMSE around 37 kJ/mol), although it may not outperform more sophisticated DFT protocols and future studies should investigate this. Finally, further work is required to compare our recommended protocol to other lattice energy calculation protocols reported in the literature, as comparisons based upon previously reported smaller datasets indicated this protocol was outperformed by a number of other methods. The SUB-BIG dataset provides a basis for these future studies and could support protocol refinement

The Neurocognitive Architecture of Individual Differences in Math Anxiety in Typical Children

Math Anxiety (MA) is characterized by a negative emotional response when facing math-related situations. MA is distinct from general anxiety and can emerge during primary education. Prior studies typically comprise adults and comparisons between high- versus low-MA, where neuroimaging work has focused on differences in network activation between groups when completing numerical tasks. The present study used voxel-based morphometry (VBM) to identify the structural brain correlates of MA in a sample of 79 healthy children aged 7–12 years. Given that MA is thought to develop in later primary education, the study focused on the level of MA, rather than categorically defining its presence. Using a battery of cognitive- and numerical-function tasks, we identified that increased MA was associated with reduced attention, working memory and math achievement. VBM highlighted that increased MA was associated with reduced grey matter in the left anterior intraparietal sulcus. This region was also associated with attention, suggesting that baseline differences in morphology may underpin attentional differences. Future studies should clarify whether poorer attentional capacity due to reduced grey matter density results in the later emergence of MA. Further, our data highlight the role of working memory in propagating reduced math achievement in children with higher MA

Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia

© 2007 Reeves et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue

Boundary vector cells in entorhinal cortex fire when a rat is in locations at a specific distance from walls of an environment. This firing may originate from memory of the barrier location combined with path integration, or the firing may depend upon the apparent visual input image stream. The modeling work presented here investigates the role of optic flow, the apparent change of patterns of light on the retina, as input for boundary vector cell firing. Analytical spherical flow is used by a template model to segment walls from the ground, to estimate self-motion and the distance and allocentric direction of walls, and to detect drop-offs. Distance estimates of walls in an empty circular or rectangular box have a mean error of less than or equal to two centimeters. Integrating these estimates into a visually driven boundary vector cell model leads to the firing patterns characteristic for boundary vector cells. This suggests that optic flow can influence the firing of boundary vector cells