Does the physical disector method provide an accurate estimation of sensory neuron number in rat dorsal root ganglia?

The physical disector is a method of choice for estimating unbiased neuron numbers; nevertheless, calibration is needed to evaluate each counting method. The validity of this method can be assessed by comparing the estimated cell number with the true number determined by a direct counting method in serial sections. We reconstructed a 1/5 of rat lumbar dorsal root ganglia taken from two experimental conditions. From each ganglion, images of 200 adjacent semi-thin sections were used to reconstruct a volumetric dataset (stack of voxels). On these stacks the number of sensory neurons was estimated and counted respectively by physical disector and direct counting methods. Also, using the coordinates of nuclei from the direct counting, we simulate, by a Matlab program, disector pairs separated by increasing distances in a ganglion model. The comparison between the results of these approaches clearly demonstrates that the physical disector method provides a valid and reliable estimate of the number of sensory neurons only when the distance between the consecutive disector pairs is 60 microm or smaller. In these conditions the size of error between the results of physical disector and direct counting does not exceed 6%. In contrast when the distance between two pairs is larger than 60 microm (70-200 microm) the size of error increases rapidly to 27%. We conclude that the physical dissector method provides a reliable estimate of the number of rat sensory neurons only when the separating distance between the consecutive dissector pairs is no larger than 60 microm.

Tumor-host interactions Part 1: Stromal signatures of breast and prostate cancer Part 2: GLG1 and the control of the secretory pathway in tumor cells

Tumor-host interaction is a key determinant during cancer progression, from primary tumor growth to metastatic dissemination. At each step, tumor cells have to adapt to and subvert different types of microenvironment, leading to major phenotypic and genotypic alterations that affect both tumor and surrounding stromal compartments. Understanding the molecular mechanisms that govern tumor-host interplay may be essential for better comprehension of tumorigenesis in an effort to improve current anti-cancer therapies. The present work is composed of two projects that address tumor-host interactions from two different perspectives, the first focusing on the characterization of tumor-associated stroma and the second on membrane trafficking in tumor cells. Part 1. To selectively address stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to analyze the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Comparison showed that invasive breast and prostate cancer elicit distinct, tumor-specific stromal responses, with a limited panel of shared induced and/or repressed genes. Both breast and prostate tumor-specific deregulated stromal gene sets displayed statistically significant survival-predictive ability for their respective tumor type. By contrast, a stromal gene signature common to both tumor types did not display prognostic value, although expression of two individual genes within this common signature was found to be associated with patient survival. Part 2. GLG1 is known as an E-selectin ligand and an intracellular FGF receptor, depending on cell type and context. Immunohistochemical and immunofluorescence analyses showed that GLG1 is primarily localized in the Golgi of human tumor cells, a central location in the biosynthetic/secretory pathways. GLG1 has been shown to interact with and to recruit the ARF GEF BIGI to the Golgi membrane. Depletion of GLG1 or BIGI markedly reduced ARF3 membrane localization and activation, and altered the Golgi structure. Interestingly, these perturbations did not impair constitutive secretion in general, but rather seemed to impair secretion of a specific subset of proteins that includes MMP-9. Thus, GLG1 coordinates ARF3 activation by recruiting BIGI to the Golgi membrane, thereby affecting secretion of specific molecules. - Les interactions tumeur-hôte constituent un élément essentiel à la progression tumorale, de la croissance de la tumeur primaire à la dissémination des métastases. A chaque étape, les cellules tumorales doivent s'adapter à différents types de microenvironnement et les détourner à leur propre avantage, donnant lieu à des altérations phénotypiques et génotypiques majeures qui affectent aussi bien la tumeur elle-même que le compartiment stromal environnant. L'étude des mécanismes moléculaires qui régissent les interactions tumeur-hôte constitue une étape essentielle pour une meilleure compréhension du processus de tumorigenèse dans le but d'améliorer les thérapies anti cancer existantes. Le travail présenté ici est composé de deux projets qui abordent la problématique des interactions tumeur-hôte selon différentes perspectives, le premier se concentrant sur la caractérisation du stroma tumoral et le second sur le trafic intracellulaire des cellules tumorales. Partie 1. Pour examiner les changements d'expression des gènes dans le stroma en réponse à la progression du cancer, des puces à ADN Affymetrix ont été utilisées afin d'analyser les transcriptomes des cellules stromales issues de carcinomes invasifs du sein et de la prostate et collectées par microdissection au laser. L'analyse comparative a montré que les cancers invasifs du sein et de la prostate provoquent des réponses stromales spécifiques à chaque type de tumeur, et présentent peu de gènes induits ou réprimés de façon similaire. L'ensemble des gènes dérégulés dans le stroma associé au cancer du sein, ou à celui de la prostate, présente une valeur pronostique pour les patients atteints d'un cancer du sein, respectivement de la prostate. En revanche, la signature stromale commune aux deux types de cancer n'a aucune valeur prédictive, malgré le fait que l'expression de deux gènes présents dans cette liste soit liée à la survie des patients. Partie 2. GLG1 est connu comme un ligand des sélectines E ainsi que comme récepteur intracellulaire pour des facteurs de croissances FGFs selon le type de cellule dans lequel il est exprimé. Des analyses immunohistochimiques et d'immunofluorescence ont montré que dans les cellules tumorales, GLG1 est principalement localisé au niveau de l'appareil de Golgi, une place centrale dans la voie biosynthétique et sécrétoire. Nous avons montré que GLG1 interagit avec la protéine BIGI et participe à son recrutement à la membrane du Golgi. L'absence de GLG1 ou de BIGI réduit drastiquement le pool d'ARF3 associé aux membranes ainsi que la quantité d'ARF3 activés, et modifie la structure de l'appareil de Golgi. Il est particulièrement intéressant de constater que ces perturbations n'ont pas d'effet sur la sécrétion constitutive en général, mais semblent plutôt affecter la sécrétion spécifique d'un sous-groupe défini de protéines comprenant MMP-9. GLG1 coordonne donc l'activation de ARF3 en recrutant BIGI à la membrane du Golgi, agissant par ce moyen sur la sécrétion de molécules spécifiques.

Role of FGF and Wnt pathways in endoderm patterning and pancreas organogenesis

Summary Between gastrulation and gut tube formation, the endoderm becomes regionally specified along the anterior-posterior axis. An early sign of patterning is the expression of organ-specific genes in restricted endoderm domains. We studied the role of the fibroblast growth factor (FGF) and Wnt pathways in the establishment of the antero-posterior (A-P) axis domains. Here we report the first evidence that graded FGF4-mediated signaling establishes gut tube domains along the A-P axis in vivo from gastrulation to somitogenesis. At gastrulation, FGF4 may act cooperatively with Wnts, since both of them affect the gut tube patterning by promoting posterior and inhibiting anterior endoderm cell fate. The activity of the Wnt pathway is however time restricted, since. it does not affect patterning at somitogenesis. Our experiments point to a global mechanism that coordinates the A-P patterning of all three primary germ layers. Soon after regionalization of the gut tube, morphogenetic evidences of organogenesis appear. We focused our attention on one of these organs, the pancreas. We report a comprehensive investigation of the activity and the role of the Wnt pathway in pancreas organogenesis. We have used two mouse reporter lines to monitor canonical Wnt-pathway activity during development and after birth and demonstrate activity in early pancreatic bud, endocrine cells and in the mesenchyme. We have specifically deleted the ß-catenin .gene, a key component of the Wnt pathway, in the epithelium of the pancreas and duodenum using Pdxl -Cre mice. In agreement with Wnt pathway activity in pancreatic endocrine cells, we find a reduction in endocrine islet numbers. Our study reveals that ß-catenin deletion also affects cells in which Wnt pathway activity is not detected. Indeed, ß-catenin mutant cells have a competitive disadvantage during development that also' affects the exocrine compartment. Moreover, the conditional KO mice develop acute edematous pancreatitis perinatally due to the disruption of the epithelial structure of acini. These effects are likely to be due to the function of ß-catenin at the membrane. Résumé Entre la gastrulation et la formation du tube digestif, l'endoderme est progressivement régionalisé le long de l'axe antéropostérieur (A-P). Un des premiers signes de cette régionalisation est l'expression de gènes spécifiques à certains organes dans une région restreinte. Nous avons étudié l'implication des voies de signalisation FGF et Wnt dans l'établissement de la régionalisation A-P. Nous rapportons les premières preuves que FGF4 établit la ségrégation des domaines de l'endoderme le long de l'axe A-P in vivo de la gastrulation à la somitogenèse. Cette activité peut être menée en collaboration avec les Wnts, puisque ceux-ci influencent aussi l'endoderme en inhibant le destin antérieur et en induisant le destin postérieur des cellules. Cette activité des Wnts est perdue à la somitogenèse. Nos expériences démontrent une régionalisation coordonnée des trois feuillets germinaux le long de l'axe A-P. Peu après la régionalisation, les premiers signes morphologiques de l'organogenèse apparaissent. Nous nous sommes intéressés au rôle des Wnts dans un des dérivés de l'endoderme : le pancréas. Nous avons utilisés deux lignés de souris rapportrices de l'activité de la voie canonique des Wnts, qui montrent une activité dans le bourgeon précoce du pancréas avant la différentiation, puis plus tard dans les cellules endocrines et le mésenchyme. Nous avons utilisé la souris transgénique Pdxl -Cre pour inactiver spécifiquement le gène de la ß-caténine, un intermédiaire de la voie des Wnts, dans la région pancréatique. En accord avec l'activité de la voie de signalisation Wnt, la perte de la ßcaténine conduit à une réduction du nombre de cellules endocrines. De plus certaines cellules qui ne montrent aucune activité de la voie Wnt sont aussi affectées. En effet, les cellules ayant perdu la ß-caténine ont un désavantage compétitif face aux cellules sauvages dans un environnement mosaïque. Cette compétition résulte en l'absence de cellules déplétées en ßcaténine chez l'adulte. De plus, vers la naissance, les animaux déficients pour la ß-caténine développent une pancréatite aiguë due à la destruction de l'architecture des acini. Ceci est probablement aux fonctions d'adhésion de la ß-caténine à la membrane.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Cardiac raptor deletion impairs adaptive hypertrophy, alters metabolic gene expression and causes heart failure in mice

Background: Mammalian target of rapamycin (mTOR), a central regulator of cell growth, is found in two structurally and functionally distinct multiprotein complexes called mTOR complex (mTORC)1 and mTORC2. The specific roles of each of these branches of mTOR signaling have not been dissected in the adult heart. In the present study, we aimed to bring new insights into the function of cardiac mTORC1-mediated signaling in physiological as well as pathological situations.Methods: We generated mice homozygous for loxP-flanked raptor and positive for the tamoxifen-inducible Cre recombinase (MerCreMer) under control of the α- myosin heavy chain promoter. The raptor gene encodes an essential component of mTORC1. Gene ablation was induced at the age of 10-12 weeks, and two weeks later the raptor cardiac-knockout (raptor-cKO) mice started voluntary cagewheel exercise or were subjected to transverse aortic constriction (TAC) to induce pressure overload.Results: In sedentary raptor-cKO mice, ejection fractions gradually decreased, resulting in significantly reduced values at 38 days (P < 0.001). Raptor-cKO mice started to die during the fifth week after the last tamoxifen injection. At that time, the mortality rate was 36% in sedentary (n = 11) and 64% in exercising (n = 14) mice. TAC-induced pressure overload resulted in severe cardiac dysfunction already at earlier timepoints. Thus, at 7-9 days after surgery, ejection fraction and fractional shortening values were 22.3% vs 43.5% and 10.2% vs 21.5% in raptor-cKO vs wild-type mice, respectively. This was accompanied by significant reductions of ventricular wall and septal thickness as well as an increase in left ventricular internal diameter. Moreover, ventricular weight to tibial length ratios were increased in wild-type, but not in the raptor-cKO TAC mice. Together, this shows that raptor-cKO mice rapidly developed dilated cardiomyopathy without going through a phase of adaptive hypertrophy. Expression of ANP and β-MHC was induced in all raptor-cKO mice irrespective of the cardiac load conditions. Consistent with reduced mTORC1 activity, phosphorylation of ribosomal S6 kinase and 4E-BP1 was blunted, indicating reduced protein synthesis. Moreover, expression of multiple genes involved in the regulation of energy metabolism was altered, and followed by a shift from fatty acid to glucose oxidation.Conclusion: Our study suggests that mTORC1 coordinates protein and energy metabolic pathways in the heart. Moreover, we demonstrate that raptor is essential for the cardiac adaptation to increased workload and importantly, also for normal physiological cardiac function.

Muscle moment-arms: a key element in muscle-force estimation.

A clear and rigorous definition of muscle moment-arms in the context of musculoskeletal systems modelling is presented, using classical mechanics and screw theory. The definition provides an alternative to the tendon excursion method, which can lead to incorrect moment-arms if used inappropriately due to its dependency on the choice of joint coordinates. The definition of moment-arms, and the presented construction method, apply to musculoskeletal models in which the bones are modelled as rigid bodies, the joints are modelled as ideal mechanical joints and the muscles are modelled as massless, frictionless cables wrapping over the bony protrusions, approximated using geometric surfaces. In this context, the definition is independent of any coordinate choice. It is then used to solve a muscle-force estimation problem for a simple 2D conceptual model and compared with an incorrect application of the tendon excursion method. The relative errors between the two solutions vary between 0% and 100%.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Sense of coherence and job characteristics in predicting burnout in a South African sample

Orientation: Research that considers the effects of individual characteristics and job characteristics jointly in burnout is necessary, especially when one considers the possibility of curvilinear relationships between job characteristics and burnout. Research purpose: This study examines the contribution of sense of coherence (SOC) and job characteristics to predicting burnout by considering direct and moderating effects. Motivation for this study: Understanding the relationships of individual and job characteristics with burnout is necessary for preventing burnout. It also informs the design of interventions. Research design, approach and method: The participants were 632 working adults (57% female) in South Africa. The measures included the Job Content Questionnaire, the Sense of Coherence Questionnaire and the Maslach Burnout Inventory. The authors analysed the data using hierarchical multiple regression with the enter method. Main findings: Job characteristics and SOC show the expected direct effects on burnout. SOC has a direct negative effect on burnout. Job demands and supervisor social support show nonlinear relationships with burnout. SOC moderates the effect of demands on burnout and has a protective function so that the demands-burnout relationship differs for those with high and low SOC. Practical/managerial implications: The types of effects, the shape of the stressor-strain relationship and the different contributions of individual and job characteristics have implications for designing interventions. Contribution/value add: SOC functions differently when combined with demands, control and support. These different effects suggest that it is not merely the presence or absence of a job characteristic that is important for well-being outcomes but how people respond to its presence or absence.

Gender and socioeconomic disparities in BMI trajectories in the Seychelles using birth cohorts generated from serial population-based surveys.

ABSTRACT: BACKGROUND: The relationship between body mass index (BMI) and socioeconomic status (SES) tends to change over time and across populations. In this study, we examined, separately in men and women, whether the association between BMI and SES changed over successive birth cohorts in the Seychelles (Indian Ocean, African region). METHODS: We used data from all participants in three surveys conducted in 1989, 1994 and 2004 in independent random samples of the population aged 25-64 years in the Seychelles (N= 3'403). We used linear regression to model mean BMI according to age, cohort, SES and smoking status, allowing for a quadratic term for age to account for a curvilinear relation between BMI and age and interactions between SES and age and between SES and cohorts to test whether the relation between SES and BMI changed across subsequent cohorts. All analyses were performed separately in men and women. RESULTS: BMI increased with age in all birth cohorts. BMI was lower in men of low SES than high SES but was higher in women of low SES than high SES. In all SES categories, BMI increased over successive cohorts (1.24 kg/m2 in men and 1.51 kg/m2 for a 10-year increase in birth cohorts, p <0.001). The difference in BMI between men or women of high vs. low SES did not change significantly across successive cohorts (the interaction between SES and year of birth of cohort was statistically not significant). Smoking was associated with lower BMI in men and women (respectively -1.55 kg/m2 and 2.46 kg/m2, p <0.001). CONCLUSIONS: Although large differences exist between men and women, social patterning of BMI did not change significantly over successive cohorts in this population of a middle-income country in the African region.

Stage-specific integration of maternal and embryonic peroxisome proliferator-activated receptor delta signaling is critical to pregnancy success.

Successful pregnancy depends on well coordinated developmental events involving both maternal and embryonic components. Although a host of signaling pathways participate in implantation, decidualization, and placentation, whether there is a common molecular link that coordinates these processes remains unknown. By exploiting genetic, molecular, pharmacological, and physiological approaches, we show here that the nuclear transcription factor peroxisome proliferator-activated receptor (PPAR) delta plays a central role at various stages of pregnancy, whereas maternal PPARdelta is critical to implantation and decidualization, and embryonic PPARdelta is vital for placentation. Using trophoblast stem cells, we further elucidate that a reciprocal relationship between PPARdelta-AKT and leukemia inhibitory factor-STAT3 signaling pathways serves as a cell lineage sensor to direct trophoblast cell fates during placentation. This novel finding of stage-specific integration of maternal and embryonic PPARdelta signaling provides evidence that PPARdelta is a molecular link that coordinates implantation, decidualization, and placentation crucial to pregnancy success. This study is clinically relevant because deferral of on time implantation leads to spontaneous pregnancy loss, and defective trophoblast invasion is one cause of preeclampsia in humans.

The Schizosaccharomyces pombe cdc14 gene is required for septum formation and can also inhibit nuclear division.

A conditional heat-sensitive mutation in the cdc14 gene of the fission yeast Schizosaccharomyces pombe results in failure to form a septum. Cells become highly elongated and multinucleate as growth and nuclear division continue in the absence of cell division. This article describes the cloning of the cdc14 gene and the identification of its product, a protein of 240 amino acids, p28cdc14. A null allele of the cdc14 gene shows that the gene is essential for septum formation and completion of the cell-division cycle. Overexpression of the gene product, p28cdc14, causes cell-cycle arrest in late G2 before mitosis. Cells leaking past the block activate p34cdc2 kinase and show condensed chromosomes, but the normal rearrangements of the microtubules and microfilaments that are associated with the transition from interphase to mitosis do not occur. Overexpression of p28cdc14 in mutants, in which the timing of mitosis is altered, suggests that these effects may be mediated upstream of the mitotic inhibitor wee1. These data are consistent with the idea that p28cdc14 may play a role in both the initiation of mitosis and septum formation and, by doing so, be part of the mechanism that coordinates these two cell-cycle events.

Investigation of the hepatitis C virus replication complex.

The NS5A protein of HCV is an essential component of the viral RNA replication machinery and may also function in modulation of the host cell environment. The exact function of NS5A in these processes remains unknown. NS5A is a large hydrophilic phosphoprotein protein consisting of three domains. The amino-terminal domain, designated domain I, coordinates a single zinc atom that is required for virus replication. We have determined the X-ray crystallographic structure of the domain I region of NS5A, and the structure sheds some light on the previously reported RNA binding activity observed for NS5A and suggests that the protein functions as a dimer. Here we describe the bacterial expression, purification, crystallization, and structural determination of the amino-terminal domain I of NS5A. The methods described herein should be of use for the generation of domain I for biochemical studies as well as future crystallization studies as antiviral compounds directed against this region of NS5A become available.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

T cell recognition of hapten. Anatomy of T cell receptor binding of a H-2kd-associated photoreactive peptide derivative.

To elucidate the structural basis of T cell recognition of hapten-modified antigenic peptides, we studied the interaction of the T1 T cell antigen receptor (TCR) with its ligand, the H-2Kd-bound Plasmodium berghei circumsporozoite peptide 252-260 (SYIPSAEKI) containing photoreactive 4-azidobenzoic acid (ABA) on P. berghei circumsporozoite Lys259. The photoaffinity-labeled TCR residue(s) were mapped as Tyr48 and/or Tyr50 of complementary determining region 2beta (CDR2beta). Other TCR-ligand contacts were identified by mutational analysis. Molecular modeling, based on crystallographic coordinates of closely related TCR and major histocompatibility complex I molecules, indicated that ABA binds strongly and specifically in a cavity between CDR3alpha and CDR2beta. We conclude that TCR expressing selective Vbeta and CDR3alpha sequences form a binding domain between CDR3alpha and CDR2beta that can accommodate nonpeptidic moieties conjugated at the C-terminal portion of peptides binding to major histocompatibility complex (MHC) encoded proteins.