Viscosity of aqueous and cyanate ester suspensions containing alumina nanoparticles

Concentrated aqueous alumina nanoparticle suspensions with additions of saccharides such as fructose, glucose, sucrose, and others were studied by rheometry and low temperature differential scanning calorimetry. The shear thinning behavior of the suspensions was used to develop a model based on fractal-type agglomeration which describes the viscosity decrease seen with the addition of these saccharides. The characteristics of particle flocculation were found to depend on the saccharide concentration and type. The developed model is in qualitative agreement with the observed melting behavior and earlier bound water hypothesis as illustrated by sub-zero DSC experiments. The effect of alumina nanoparticles on the viscosity and curing behavior of a bisphenol E cyanate ester monomer (BECy) suspension was investigated by rheometry as well. The viscosity was found to increase with solids content and was fit well by the Mooney equation. The viscosity reduction achieved at high particle loadings by the addition of benzoic acid was also investigated. NMR experiments indicate that benzoic acid interacts with the alumina particle surface

Memory effects in biochemical networks as the natural counterpart of extrinsic noise

We show that in the generic situation where a biological network, e.g. a protein interaction network, is in fact a subnetwork embedded in a larger "bulk" network, the presence of the bulk causes not just extrinsic noise but also memory effects. This means that the dynamics of the subnetwork will depend not only on its present state, but also its past. We use projection techniques to get explicit expressions for the memory functions that encode such memory effects, for generic protein interaction networks involving binary and unary reactions such as complex formation and phosphorylation, respectively. Remarkably, in the limit of low intrinsic copy-number noise such expressions can be obtained even for nonlinear dependences on the past. We illustrate the method with examples from a protein interaction network around epidermal growth factor receptor (EGFR), which is relevant to cancer signalling. These examples demonstrate that inclusion of memory terms is not only important conceptually but also leads to substantially higher quantitative accuracy in the predicted subnetwork dynamics

Genomic clustering and co-regulation of transcriptional networks in the pathogenic fungus Fusarium graminearum.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: Genes for the production of a broad range of fungal secondary metabolites are frequently colinear. The prevalence of such gene clusters was systematically examined across the genome of the cereal pathogen Fusarium graminearum. The topological structure of transcriptional networks was also examined to investigate control mechanisms for mycotoxin biosynthesis and other processes. RESULTS: The genes associated with transcriptional processes were identified, and the genomic location of transcription-associated proteins (TAPs) analyzed in conjunction with the locations of genes exhibiting similar expression patterns. Highly conserved TAPs reside in regions of chromosomes with very low or no recombination, contrasting with putative regulator genes. Co-expression group profiles were used to define positionally clustered genes and a number of members of these clusters encode proteins participating in secondary metabolism. Gene expression profiles suggest there is an abundance of condition-specific transcriptional regulation. Analysis of the promoter regions of co-expressed genes showed enrichment for conserved DNA-sequence motifs. Potential global transcription factors recognising these motifs contain distinct sets of DNA-binding domains (DBDs) from those present in local regulators. CONCLUSIONS: Proteins associated with basal transcriptional functions are encoded by genes enriched in regions of the genome with low recombination. Systematic searches revealed dispersed and compact clusters of co-expressed genes, often containing a transcription factor, and typically containing genes involved in biosynthetic pathways. Transcriptional networks exhibit a layered structure in which the position in the hierarchy of a regulator is closely linked to the DBD structural class

The de Morton Mobility Index (DEMMI) provides a valid method for measuring and monitoring the mobility of patients making the transition from hospital to the community: an observational study

QuestionIsthe de Morton Mobility Index (DEMMI) valid for measuring the mobility of patients making the transition from hospital to the community?DesignObservational cohort study.Participants696 consecutive patients admitted to 11 Transition Care Programs for multidisciplinary care in Victoria and Tasmania during a 6-month period. The DEMMI and Modified Barthel Index were administered within 5 working days of admission and discharge from the Transition Care Program.Outcome measuresThe DEMMI and Modified Barthel Index.ResultsNeither the DEMMI nor the Modified Barthel Index had a floor or ceiling effect. Similar evidence of convergent, discriminant and known-groups validity were obtained for each instrument. The DEMMI was significantly more responsive to change than the Modified Barthel Index using criterion- and distribution-based methods. The minimum clinically important difference estimates represented similar proportions of the scale width for the DEMMI and Modified Barthel Index and were similar using criterion- and distribution-based estimates. Rasch analysis identified the DEMMI as essentially unidimensional in a Transition Care Program cohort and therefore can be applied to obtain interval level measurement. Rasch analysis demonstrated that the DEMMI was administered similarly by physiotherapists and allied health assistants under the direction of a physiotherapist.ConclusionThe DEMMI and Modified Barthel Index are both valid measures of activity limitation for Transition Care Program patients. The DEMMI has a broader scale width, provides interval level measurement, and is significantly more responsive to change than the Modified Barthel Index for measuring the mobility of Transition Care Program patient

The Light Curve of the Weakly-Accreting T Tauri Binary KH 15D from 2005-10: Insights into the Nature of its Protoplanetary Disk

Photometry of the unique pre-main sequence binary system KH 15D is presented, spanning the years 2005-2010. This system has exhibited photometric variations and eclipses over the last 50 years caused by a precessing circumbinary disk. Advancement of the occulting edge across the binary orbit has continued and the photospheres of both stars are now completely obscured at all times. The system is now visible only by scattered light, and yet it continues to show a periodic variation on the orbital cycle with an amplitude exceeding two magnitudes. This variation, which depends only on the binary phase, has likely been present in the data since at least 1995. It can, by itself, account for shoulders on the light curve prior to ingress and following egress, obviating the need for components of extant models such as a scattering halo around star A or forward scattering from a fuzzy disk edge. A plausible source for the variable scattering component is reflected light from the far side of a warped occulting disk. We have detected color changes in V-I of several tenths of a magnitude to both the blue and red that occur during times of minima. These may indicate the presence of a third source of light (faint star) within the system, or a change in the reflectance properties of the disk as the portion being illuminated varies with the orbital motion of the stars. The data support a picture of the circumbinary disk as a geometrically thin, optically thick layer of perhaps mm or cm-sized particles that has been sculpted by the binary stars and possibly other components into a decidedly nonplanar configuration. A simple (infinitely sharp) knife-edge model does a good job of accounting for all of the recent (2005-2010) occultation data.Comment: To appear in The Astronomical Journa

Utilization of care among drug resistant epilepsy patients with symptoms of anxiety and depression

AbstractPurposeEpilepsy patients have a significantly higher rate of anxiety and depression than the general population, and psychiatric disease is particularly prevalent among drug resistant epilepsy patients. Symptoms of anxiety and depression might serve as a barrier to appropriate epilepsy care.The aim of this study was to determine if drug resistant epilepsy patients with symptoms of anxiety and/or depression receive different epilepsy management than controls.MethodWe identified 83 patients with drug resistant focal epilepsy seen at the Penn Epilepsy Center. Upon enrollment, all patients completed 3 self-report scales and a neuropsychiatric inventory and were grouped into those with symptoms of anxiety and/or depression and controls. Each patient's medical records were retrospectively reviewed for 1–2 years, and objective measures of outpatient and inpatient epilepsy management were assessed.ResultsAt baseline, 53% (n=43) of patients screened positive for symptoms of anxiety and/or depression. The remaining 47% (n=38) served as controls. Patients with anxiety and/or depression symptoms had more missed outpatient visits per year compared to controls (median 0.84 vs. 0.48, p=0.02). Patients with symptoms of both anxiety and depression were more likely to undergo an inpatient admission or procedure (56% vs. 24%, p=0.02).ConclusionFor most measures of epilepsy management, symptoms of anxiety and/or depression do not alter epilepsy care; however, drug resistant epilepsy patients with anxiety and/or depression symptoms may be more likely to miss outpatient appointments, and those with the highest burden of psychiatric symptoms may be admitted more frequently for inpatient services compared to controls

Rapid-Motion-Track: Markerless Tracking of Fast Human Motion with Deeper Learning

Objective The coordination of human movement directly reflects function of the central nervous system. Small deficits in movement are often the first sign of an underlying neurological problem. The objective of this research is to develop a new end-to-end, deep learning-based system, Rapid-Motion-Track (RMT) that can track the fastest human movement accurately when webcams or laptop cameras are used. Materials and Methods We applied RMT to finger tapping, a well-validated test of motor control that is one of the most challenging human motions to track with computer vision due to the small keypoints of digits and the high velocities that are generated. We recorded 160 finger tapping assessments simultaneously with a standard 2D laptop camera (30 frames/sec) and a high-speed wearable sensor-based 3D motion tracking system (250 frames/sec). RMT and a range of DLC models were applied to the video data with tapping frequencies up to 8Hz to extract movement features. Results The movement features (e.g. speed, rhythm, variance) identified with the new RMT system exhibited very high concurrent validity with the gold-standard measurements (97.3\% of RMT measures were within +/-0.5Hz of the Optotrak measures), and outperformed DLC and other advanced computer vision tools (around 88.2\% of DLC measures were within +/-0.5Hz of the Optotrak measures). RMT also accurately tracked a range of other rapid human movements such as foot tapping, head turning and sit-to -stand movements. Conclusion: With the ubiquity of video technology in smart devices, the RMT method holds potential to transform access and accuracy of human movement assessment

Wearable Sensors Outperform Behavioral Coding as Valid Marker of Childhood Anxiety and Depression

There is a significant need to develop objective measures for identifying children under the age of 8 who have anxiety and depression. If left untreated, early internalizing symptoms can lead to adolescent and adult internalizing disorders as well as comorbidity which can yield significant health problems later in life including increased risk for suicide. To this end, we propose the use of an instrumented fear induction task for identifying children with internalizing disorders, and demonstrate its efficacy in a sample of 63 children between the ages of 3 and 7. In so doing, we extract objective measures that capture the full six degree-of-freedom movement of a child using data from a belt-worn inertial measurement unit (IMU) and relate them to behavioral fear codes, parent-reported child symptoms and clinician-rated child internalizing diagnoses. We find that IMU motion data, but not behavioral codes, are associated with parent-reported child symptoms and clinician-reported child internalizing diagnosis in this sample. These results demonstrate that IMU motion data are sensitive to behaviors indicative of child psychopathology. Moreover, the proposed IMU-based approach has increased feasibility of collection and processing compared to behavioral codes, and therefore should be explored further in future studies

Predicting novel candidate human obesity genes and their site of action by systematic functional screening in Drosophila.

Funder: NIHR [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation TrustFunder: NHS National Institute for Health Research Clinical Research NetworkFunder: Royal Society Darwin Trust Research ProfessorshipFunder: NIHR Senior Investigator AwardFunder: Health Data Research UKFunder: Higher Education Funding Council for England CatalystFunder: NIHR Cambridge Biomedical Research CentreFunder: Bernard Wolfe Health Neuroscience EndowmentFunder: The Botnar FondationThe discovery of human obesity-associated genes can reveal new mechanisms to target for weight loss therapy. Genetic studies of obese individuals and the analysis of rare genetic variants can identify novel obesity-associated genes. However, establishing a functional relationship between these candidate genes and adiposity remains a significant challenge. We uncovered a large number of rare homozygous gene variants by exome sequencing of severely obese children, including those from consanguineous families. By assessing the function of these genes in vivo in Drosophila, we identified 4 genes, not previously linked to human obesity, that regulate adiposity (itpr, dachsous, calpA, and sdk). Dachsous is a transmembrane protein upstream of the Hippo signalling pathway. We found that 3 further members of the Hippo pathway, fat, four-jointed, and hippo, also regulate adiposity and that they act in neurons, rather than in adipose tissue (fat body). Screening Hippo pathway genes in larger human cohorts revealed rare variants in TAOK2 associated with human obesity. Knockdown of Drosophila tao increased adiposity in vivo demonstrating the strength of our approach in predicting novel human obesity genes and signalling pathways and their site of action

DART: Denoising Algorithm based on Relevance network Topology improves molecular pathway activity inference

Abstract Background Inferring molecular pathway activity is an important step towards reducing the complexity of genomic data, understanding the heterogeneity in clinical outcome, and obtaining molecular correlates of cancer imaging traits. Increasingly, approaches towards pathway activity inference combine molecular profiles (e.g gene or protein expression) with independent and highly curated structural interaction data (e.g protein interaction networks) or more generally with prior knowledge pathway databases. However, it is unclear how best to use the pathway knowledge information in the context of molecular profiles of any given study. Results We present an algorithm called DART (Denoising Algorithm based on Relevance network Topology) which filters out noise before estimating pathway activity. Using simulated and real multidimensional cancer genomic data and by comparing DART to other algorithms which do not assess the relevance of the prior pathway information, we here demonstrate that substantial improvement in pathway activity predictions can be made if prior pathway information is denoised before predictions are made. We also show that genes encoding hubs in expression correlation networks represent more reliable markers of pathway activity. Using the Netpath resource of signalling pathways in the context of breast cancer gene expression data we further demonstrate that DART leads to more robust inferences about pathway activity correlations. Finally, we show that DART identifies a hypothesized association between oestrogen signalling and mammographic density in ER+ breast cancer. Conclusions Evaluating the consistency of prior information of pathway databases in molecular tumour profiles may substantially improve the subsequent inference of pathway activity in clinical tumour specimens. This de-noising strategy should be incorporated in approaches which attempt to infer pathway activity from prior pathway models. </jats:sec