Mutations in STIL, Encoding a Pericentriolar and Centrosomal Protein, Cause Primary Microcephaly

Primary microcephaly (MCPH) is an autosomal-recessive congenital disorder characterized by smaller-than-normal brain size and mental retardation. MCPH is genetically heterogeneous with six known loci: MCPH1-MCPH6. We report mapping of a novel locus, MCPH7, to chromosome 1p32.3-p33 between markers D1S2797 and D1S417, corresponding to a physical distance of 8.39 Mb. Heterogeneity analysis of 24 families previously excluded from linkage to the six known MCPH loci suggested linkage of five families (20.83%) to the MCPH7 locus. In addition, four families were excluded from linkage to the MCPH7 locus as well as all of the six previously known loci, whereas the remaining 15 families could not be conclusively excluded or included. The combined maximum two-point LOD score for the linked families was 5.96 at marker D1S386 at theta = 0.0. The combined multipoint LOD score was 6.97 between markers D1S2797 and D1S417. Previously, mutations in four genes, MCPH1, CDK5RAP2, ASPM, and CENPJ, that code for centrosomal proteins have been shown to cause this disorder. Three different homozygous mutations in STIL, which codes for a pericentriolar and centrosomal protein, were identified in patients from three of the five families linked to the MCPH7 locus; all are predicted to truncate the STIL protein. Further, another recently ascertained family was homozygous for the same mutation as one of the original families. There was no evidence for a common haplotype. These results suggest that the centrosome and its associated structures are important in the control of neurogenesis in the developing human brain.

Phenotypic plasticity and longevity in plants and animals: cause and effect?

Immobile plants and immobile modular animals outlive unitary animals. This paper discusses competing but not necessarily mutually exclusive theories to explain this extreme longevity, especially from the perspective of phenotypic plasticity. Stem cell immortality, vascular autonomy, and epicormic branching are some important features of the phenotypic plasticity of plants that contribute to their longevity. Monocarpy versus polycarpy can also influence the kind of senescent processes experienced by plants. How density-dependent phenomena affecting the establishment of juveniles in these immobile organisms can influence the evolution of senescence, and consequently longevity, is reviewed and discussed. Whether climate change scenarios will favour long-lived or short-lived organisms, with their attendant levels of plasticity, is also presented.

A Durable PEFC with Carbon-Supported Pt-TiO2 Cathode: A Cause and Effect Study

Durability is central to the commercialization of polymer electrolyte fuel cells (PEFCs). The incorporation of TiO2 with platinum (Pt) ameliorates both the stability and catalytic activity of cathodes in relation to pristine Pt cathodes currently being used in PEFCs. PEFC cathodes comprising carbon-supported Pt-TiO2 (Pt-TiO2/C) exhibit higher durability in relation to Pt/C cathodes as evidenced by cell polarization, impedance, and cyclic voltammetry data. The degradation in performance of the Pt-TiO2/C cathodes is 10% after 5000 test cycles as against 28% for Pt/C cathodes. These data are in conformity with the electrochemical surface area and impedance values. Pt-TiO2/C cathodes can withstand even 10,000 test cycles with nominal effect on their performance. X-ray diffraction, transmission electron microscope, and cross-sectional field-emission-scanning electron microscope studies on the catalytic electrodes reflect that incorporating TiO2 with Pt helps in mitigating the aggregation of Pt particles and protects the Nafion membrane against peroxide radicals formed during the cathodic reduction of oxygen. (C) 2010 The Electrochemical Society. [DOI: 10.1149/1.3421970] All rights reserved.

The destabilization of human GCAP1 by a proline to leucine mutation might cause cone-rod dystrophy

Guanylate cyclase activating protein-1 (GCAP1) is required for activation of retinal guanylate cyclase-1 (RetGC1), which is essential for recovery of photoreceptor cells to the dark state. In this paper, experimentally derived observations are reported that help in explaining why a proline→leucine mutation at position 50 of human GCAP1 results in cone–rod dystrophy in a family carrying this mutation. The primary amino acid sequence of wild-type GCAP1 was mutated using site-directed mutagenesis to give a leucine at position 50. In addition, serine replaced a glutamic acid residue at position 6 to promote N‐terminal myristoylation, yielding the construct GCAP1 E6S/P50L. The enzyme was over-expressed in Escherichia coli cells, isolated and purified before being used in assays with RetGC1, characterized by circular dichroism (CD) spectroscopy, and investigated for protease resistance and thermal stability. Assays of cyclic guanosine monophosphate (cGMP) synthesis from guanosine triphosphate by RetGC1 in the presence of E6S/P50L showed that E6S/P50L could activate RetGC1 and displayed similar calcium sensitivity to wild-type GCAP1. In addition, E6S/P50L and wild-type GCAP1 possess similar CD spectra. However, there was a marked increase in the susceptibility to protease degradation and also a reduction in the thermal stability of E6S/P50L as observed by both the cGMP assay and CD spectroscopy. It is therefore suggested that although GCAP1 E6S/P50L has a similar activity and calcium dependency profile to the wild-type GCAP1, its lower stability could reduce its cellular concentration, which would in turn alter [Ca2+] and result in death of cells.

Root cause diagnostics using temporal data mining

A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence.

Cause and Effect of Feedback: Multiphase Gas in Cluster Cores Heated by AGN Jets

Multiwavelength data indicate that the X-ray-emitting plasma in the cores of galaxy clusters is not cooling catastrophically. To a large extent, cooling is offset by heating due to active galactic nuclei (AGNs) via jets. The cool-core clusters, with cooler/denser plasmas, show multiphase gas and signs of some cooling in their cores. These observations suggest that the cool core is locally thermally unstable while maintaining global thermal equilibrium. Using high-resolution, three-dimensional simulations we study the formation of multiphase gas in cluster cores heated by collimated bipolar AGN jets. Our key conclusion is that spatially extended multiphase filaments form only when the instantaneous ratio of the thermal instability and free-fall timescales (t(TI)/t(ff)) falls below a critical threshold of approximate to 10. When this happens, dense cold gas decouples from the hot intracluster medium (ICM) phase and generates inhomogeneous and spatially extended Ha filaments. These cold gas clumps and filaments ``rain'' down onto the central regions of the core, forming a cold rotating torus and in part feeding the supermassive black hole. Consequently, the self-regulated feedback enhances AGN heating and the core returns to a higher entropy level with t(TI)/t(ff) > 10. Eventually, the core reaches quasi-stable global thermal equilibrium, and cold filaments condense out of the hot ICM whenever t(TI)/t(ff) less than or similar to 10. This occurs despite the fact that the energy from AGN jets is supplied to the core in a highly anisotropic fashion. The effective spatial redistribution of heat is enabled in part by the turbulent motions in the wake of freely falling cold filaments. Increased AGN activity can locally reverse the cold gas flow, launching cold filamentary gas away from the cluster center. Our criterion for the condensation of spatially extended cold gas is in agreement with observations and previous idealized simulations.

Mutations in Drosophila Myosin Rod Cause Defects in Myofibril Assembly

The roles of myosin during muscle contraction are well studied, but how different domains of this protein are involved in myofibril assembly in vivo is far less understood. The indirect flight muscles (IFMs) of Drosophila melanogaster provide a good model for understanding muscle development and function in vivo. We show that two missense mutations in the rod region of the myosin heavy-chain gene, Mhc, give rise to IFM defects and abnormal myofibrils. These defects likely result from thick filament abnormalities that manifest during early sarcomere development or later by hypercontraction. The thick filament defects are accompanied by marked reduction in accumulation of flightin, a myosin binding protein, and its phosphorylated forms, which are required to stabilise thick filaments. We investigated with purified rod fragments whether the mutations affect the coiled-coil structure, rod aggregate size or rod stability. No significant changes in these parameters were detected, except for rod thermodynamic stability in one mutation. Molecular dynamics simulations suggest that these mutations may produce localised rod instabilities. We conclude that the aberrant myofibrils are a result of thick filament defects, but that these in vivo effects cannot be detected in vitro using the biophysical techniques employed. The in vivo investigation of these mutant phenotypes in IFM development and function provides a useful platform for studying myosin rod and thick filament formation generically, with application to the aetiology of human myosin rod myopathies. (C) 2012 Elsevier Ltd. All rights reserved.

A Durable RuO2-Carbon-Supported Pt Catalyst for PEFCs: A Cause and Effect Study

As Polymer Electrolyte Fuel Cells (PEFCs) are nearing the acceptable performance level for automotive and stationary applications, the focus on the research is shifting more and more toward enhancing their durability that still remains a major concern in their commercial acceptability. Hydrous ruthenium oxide (RuO2) is a promising material for pseudocapacitors due to its high stability, high specific-capacitance and rapid faradaic-reaction. Incorporation of carbon-supported RuO2 (RuO2/C) to platinum (Pt) is found to ameliorate both stability and catalytic activity of fuel cell cathodes that exhibit higher performance and durability in relation to Pt/C cathodes as evidenced by cell polarization, impedance and cyclic voltammetry data. The degradation in performance of Pt-RuO2/C cathodes is found to be only similar to 8% after 10000 accelerated stress test (AST) cycles as against similar to 60% for Pt/C cathodes after 7000 AST cycles under similar conditions. These data are in conformity with the Electrochemical Surface Area and impedance results. Interestingly, Pt-RuO2/C cathodes can withstand more than 10000 AST cycles with only a nominal loss in their performance. Studies on catalytic electrodes with X-ray diffraction, transmission electron microscopy and cross-sectional field-emission scanning electron microscopy reflect that incorporation of RuO2 to Pt helps mitigating aggregation of Pt particles and improves its stability during long-term operation of PEFCs. (C) 2012 The Electrochemical Society. DOI: 10.1149/2.jes113440] All rights reserved.

Activation of TGF-beta Pathway by Areca Nut Constituents: A Possible Cause of Oral Submucous Fibrosis

Oral submucous fibrosis (OSF) is a chronic inflammatory disease characterized by the accumulation of excess collagen, and areca nut chewing has been proposed as an important etiological factor for disease manifestation. Activation of transforming growth factor-beta signaling has been postulated as the main causative event for increased collagen production in OSF. Oral epithelium plays important roles in OSF, and arecoline has been shown to induce TGF-beta in epithelial cells. In an attempt to understand the role of areca nut constituents in the manifestation of OSF, we studied the global gene expression profile in epithelial cells (HaCaT) following treatment with areca nut water extract or TGF-beta. Interestingly, 64% of the differentially regulated genes by areca nut water extract matches with the TGF-beta induced gene expression profile. Out of these, expression of 57% of genes was compromised in the presence of ALK5 (T beta RI) inhibitor and 7% were independently induced by areca nut, highlighting the importance of TGF-beta in areca nut actions. Areca nut water extract treatment induced p-SMAD2 and TGF-beta downstream targets in HaCaT cells but not in human gingival fibroblast cells (hGF), suggesting epithelial cells could be the source of TGF-beta in promoting OSF. Water extract of areca nut consists of polyphenols and alkaloids. Both polyphenol and alkaloid fractions of areca nut were able to induce TGF-beta signaling and its downstream targets. Also, SMAD-2 was phosphorylated following treatment of HaCaT cells by Catechin, Tannin and alkaloids namely Arecoline, Arecaidine and Guvacine. Moreover, both polyphenols and alkaloids induced TGF-beta 2 and THBS1 (activator of latent TGF-beta) in HaCaT cells suggesting areca nut mediated activation of p-SMAD2 involves up-regulation and activation of TGF-beta. These data suggest a major causative role for TGF-beta that is induced by areca nut in OSF progression.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.