Worm burdens in outbred and inbred laboratory rats with morphometric data on Syphacia muris (Yamaguti, 1935) Yamaguti, 1941 (Nematoda, Oxyuroidea)

Syphacia muris worm burdens were evaluated in the rat Rattus norvegicus of the strains Wistar (outbred), Low/M and AM/2/Torr (inbred), maintained conventionally in institutional animal houses in Brazil. Morphometrics and illustration data for S. muris recovered from Brazilian laboratory rats are provided for the first time since its proposition in 1935.

New host and locality records for Tetrameres (Gynaecophila) spirospiculum Pinto & Vicente, 1995 (Nematoda: Tetrameridae), with new morphological data

We report the finding of Tetrameres spirospiculum Pinto & Vicente, 1995 from Theristicus melanopis melanopis (Threskiornithidae) from Patagonia, Argentina. These constitute new host and locality records. We propose the assignation of this species to the subgenus T. (Gynaecophila) Gubanov, 1950, based on the presence of labia and the absence of cuticular flanges at the anterior end. Some new morphological data are provided, such as the arrangement of cuticular spines and the presence of a pair of somatic papillae at beginning of posterior third of body length. T. (G.) spirospiculum may probably be regarded as specific to birds of the genus Theristicus.

Is real GDP stationary? Evidence from a panel unit root test with cross-sectional dependence and historical data

We use historical data that cover more than one century on real GDP for industrial countries and employ the Pesaran panel unit root test that allows for cross-sectional dependence to test for a unit root on real GDP. We find strong evidence against the unit root null. Our results are robust to the chosen group of countries and the sample period. Key words: real GDP stationarity, cross-sectional dependence, CIPS test. JEL Classification: C23, E32

An examination of male and female odds ratios by BMI, cigarette smoking, and alcohol consumption for cancers of the oral cavity, pharynx, and larynx in pooled data from 15 case-control studies.

BACKGROUND: Greater tobacco smoking and alcohol consumption and lower body mass index (BMI) increase odds ratios (OR) for oral cavity, oropharyngeal, hypopharyngeal, and laryngeal cancers; however, there are no comprehensive sex-specific comparisons of ORs for these factors. METHODS: We analyzed 2,441 oral cavity (925 women and 1,516 men), 2,297 oropharynx (564 women and 1,733 men), 508 hypopharynx (96 women and 412 men), and 1,740 larynx (237 women and 1,503 men) cases from the INHANCE consortium of 15 head and neck cancer case-control studies. Controls numbered from 7,604 to 13,829 subjects, depending on analysis. Analyses fitted linear-exponential excess ORs models. RESULTS: ORs were increased in underweight (<18.5 BMI) relative to normal weight (18.5-24.9) and reduced in overweight and obese categories (>/=25 BMI) for all sites and were homogeneous by sex. ORs by smoking and drinking in women compared with men were significantly greater for oropharyngeal cancer (p < 0.01 for both factors), suggestive for hypopharyngeal cancer (p = 0.05 and p = 0.06, respectively), but homogeneous for oral cavity (p = 0.56 and p = 0.64) and laryngeal (p = 0.18 and p = 0.72) cancers. CONCLUSIONS: The extent that OR modifications of smoking and drinking by sex for oropharyngeal and, possibly, hypopharyngeal cancers represent true associations, or derive from unmeasured confounders or unobserved sex-related disease subtypes (e.g., human papillomavirus-positive oropharyngeal cancer) remains to be clarified.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Health and Social Care: Comparative Data for Northern Ireland and other Countries - May 2004 (PDF 121 KB)

Health and Social Care: Comparative Data for Northern Ireland and other Countries - May 2004

Testing kin selection with sex allocation data in eusocial hymenoptera

Sex allocation data in eusocial Hymenoptera (ants, bees and wasps) provide an excellent opportunity to assess the effectiveness of kin selection, because queens and workers differ in their relatedness to females and males. The first studies on sex allocation in eusocial Hymenoptera compared population sex investment ratios across species. Female-biased investment in monogyne (= with single-queen colonies) populations of ants suggested that workers manipulate sex allocation according to their higher relatedness to females than males (relatedness asymmetry). However, several factors may confound these comparisons across species. First, variation in relatedness asymmetry is typically associated with major changes in breeding system and life history that may also affect sex allocation. Secondly, the relative cost of females and males is difficult to estimate across sexually dimorphic taxa, such as ants. Thirdly, each species in the comparison may not represent an independent data point, because of phylogenetic relationships among species. Recently, stronger evidence that workers control sex allocation has been provided by intraspecific studies of sex ratio variation across colonies. In several species of eusocial Hymenoptera, colonies with high relatedness asymmetry produced mostly females, in contrast to colonies with low relatedness asymmetry which produced mostly males. Additional signs of worker control were found by investigating proximate mechanisms of sex ratio manipulation in ants and wasps. However, worker control is not always effective, and further manipulative experiments will be needed to disentangle the multiple evolutionary factors and processes affecting sex allocation in eusocial Hymenoptera.

Evaluación de la eficacia y seguridad del tratamiento con tetratiomolibdato de amonio en la enfermedad de Wilson con afectación neurológica

El tractament actual de la malaltia de Wilson amb afectació neurològica és controvertit. Els fàrmacs actuals s’associen a risc de deteriorament neurològic (50% amb penicilamina i 26% amb trientine). El nou medicament tetratiomolibdat s’està estudiant perquè sembla tenir menor freqüència d’empitjorament neurològic. S’associa a efectes secundaris lleus i generalment reversibles. A la nostra sèrie de cinc pacients vàrem observar una milloria significativa dels símptomes després del tractament amb tetratiomolibdat. No es va detectar cap empitjorament neurològic. En dos casos va haver també una millora radiològica. Un pacient va presentar lleu anèmia, leucopènia i elevació de les transaminases reversible.

Ecological Data of Travassosnema travassosi travassosi (Dracunculoidea: Guyanemidae) from the Humour of the Eyes of Acestrorhynchus lacustris from Tibagi River, Paraná, Brazil

Data obtained between 1990 and 1995 provide, for the first time, ecological information of the parasitic nematode Travassosnema travassosi travassosi Costa, Moreira & Oliveira, 1991 from Acestrorhynchus lacustris (Characiformes: Acestrorhynchidae) collected in the Tibagi River, Sertanópolis, Paraná, Brazil. These nematode occurred with low prevalences (7.7% to 28.6%) and intensities (1 to 3) during almost the whole year. The observation of mature females throughout the year indicate that liberation of larvae can occur during all the year around. This is the first report on the occurrence of T. travassosi travassosi inside the eyes. These nematodes were mostly located in humour of the eyes (87% of cases), being less frequently detected in tissues behind the eyes (13% of cases).

Carcinomes canalaires in situ: données anatomo-pathologiques actuelles [Ductal carcinoma in situ: current anatomo-pathologic data]

Ductal carcinoma in situ (DCIS), accounting for 15-25% of all breast cancers, is frequently diagnosed by mammographic examination. This heterogeneous disease requires a rigorous local treatment based, in about two-third of cases, on conservative surgery and radiotherapy. DCIS are currently classified on the basis of nuclear grade. Most lesions, and especially high nuclear grade DCIS, are limited to one quadrant. Micropapillary DCIS are likely to be of larger size/extent and thus a conservative approach is often difficult. A careful pathological examination of an oriented excisional biopsy is a pre-requisite for optimal therapy.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.