Sexual recombination in Phytophthora cinnamomi in vitro and aggressiveness of single-oospore progeny to Eucalyptus

Fifty single oospore progeny were established from an in vitro mating of A1 and A2 mating type isolates of Phytophthora cinnamomi from South Africa. Forty-nine progeny were identified as F-1 hybrids using seven random amplified polymorphic DNA (RAPD) primers, and one was a selfed isolate of the A1 mating type parent. Among the hybrid progeny, 24 and 25 were A1 and A2 mating type, respectively. Aggressiveness of progeny and parental isolates was assessed on 1-year-old seedlings of Eucalyptus smithii. The mean aggressiveness of hybrid oosporic isolates, expressed as lesion length, was significantly (P = 0.0001) lower than that of the parental isolates. No significant difference in aggressiveness of A1 and A2 mating type F-1 hybrid isolates was observed. This is the first report demonstrating sexual recombination in vitro in P. cinnamomi.

Radon Distribution and Prevalence of Lung Cancer in Several Areas of West Georgia

ჩატარებულია რადონის განაწილების რაოდენობრივი შეფასება დასავლეთ საქართველოს ცალკეულ რაიონებში. მიღებული მონაცემები მოწმობს, რომ 100-ზე მეტი წყლის სინჯში აღინიშნება რადონის მაღალი შემცველობა. ამ უბნებთანაა დაკავშირებული ბინებში რადონის დაგროვების მაღალი მაჩვენებლები.ჩვენს მიერ ჩატარებული კვლევა კიდევ ერთხელ ადასტურებს კორელაციურ კავშირს რადონის კონცენტრაციასა და ფილტვის კიბოს გავრცელებას შორის.

Genetic diversity and genetic exchange in Trypanosoma cruzi: dual drug-resistant "progeny" from episomal transformants

Extensive characterisation of Trypanosoma cruzi by isoenzyme phenotypes has separated the species into three principal zymodeme groups, Z1, Z2 and Z3, and into many individual zymodemes. There is marked diversity within Z2. A strong correlation has been demonstrated between the strain clusters determined by isoenzymes and those obtained using random amplified polymorphic DNA (RAPD) profiles. Polymorphisms in ribosomal RNA genes, in mini-exon genes, and microsatellite fingerprinting indicate the presence of at least two principal T. cruzi genetic lineages. Lineage 1 appears to correspond with Z2 and lineage 2 with Z1. Z1 (lineage 2) is associated with Didelphis. Z2 (lineage 1) may be associated with a primate host. Departures from Hardy-Weinberg equilibrium and linkage disequilibrium indicate that propagation of T. cruzi is predominantly clonal. Nevertheless, two studies show putative homozygotes and heterozygotes circulating sympatrically: the allozyme frequencies for phosphoglucomutase, and hybrid RAPD profiles suggest that genetic exchange may be a current phenomenon in some T. cruzi transmission cycles. We were able to isolate dual drug-resistant T. cruzi biological clones following copassage of putative parents carrying single episomal drug-resistant markers. A multiplex PCR confirmed that dual drug-resistant clones carried both episomal plasmids. Preliminary karyotype analysis suggests that recombination may not be confined to the extranuclear genome.

Inbreeding effects on progeny sex ratio and gender variation in the gynodioecious Silene vulgaris (Caryophyllaceae).

In gynodioecious species, sex expression is generally determined through cytoplasmic male sterility genes interacting with nuclear restorers of the male function. With dominant restorers, there may be an excess of females in the progeny of self-fertilized compared with cross-fertilized hermaphrodites. Moreover, the effect of inbreeding on late stages of the life cycle remains poorly explored. Here, we used hermaphrodites of the gynodioecious Silene vulgaris originating from three populations located in different valleys in the Alps to investigate the effects of two generations of self- and cross-fertilization on sex ratio and gender variation. We detected an increase in females in the progeny of selfed compared with outcrossed hermaphrodites and inbreeding depression for female and male fertility. Male fertility correlated positively with sex ratio differences between outbred and inbred progeny, suggesting that dominant restorers are likely to influence male fertility qualitatively and quantitatively in S. vulgaris. We argue that the excess of females in the progeny of selfed compared with outcrossed hermaphrodites and inbreeding depression for gamete production may contribute to the maintenance of females in gynodioecious populations of S. vulgaris because purging of the genetic load is less likely to occur.

Domestic radon exposure and risk of childhood cancer: a prospective census-based cohort study

BACKGROUND: In contrast with established evidence linking high doses of ionizing radiation with childhood cancer, research on low-dose ionizing radiation and childhood cancer has produced inconsistent results. OBJECTIVE: We investigated the association between domestic radon exposure and childhood cancers, particularly leukemia and central nervous system (CNS) tumors. METHODS: We conducted a nationwide census-based cohort study including all children < 16 years of age living in Switzerland on 5 December 2000, the date of the 2000 census. Follow-up lasted until the date of diagnosis, death, emigration, a child's 16th birthday, or 31 December 2008. Domestic radon levels were estimated for each individual home address using a model developed and validated based on approximately 45,000 measurements taken throughout Switzerland. Data were analyzed with Cox proportional hazard models adjusted for child age, child sex, birth order, parents' socioeconomic status, environmental gamma radiation, and period effects. RESULTS: In total, 997 childhood cancer cases were included in the study. Compared with children exposed to a radon concentration below the median (< 77.7 Bq/m3), adjusted hazard ratios for children with exposure ≥ the 90th percentile (≥ 139.9 Bq/m3) were 0.93 (95% CI: 0.74, 1.16) for all cancers, 0.95 (95% CI: 0.63, 1.43) for all leukemias, 0.90 (95% CI: 0.56, 1.43) for acute lymphoblastic leukemia, and 1.05 (95% CI: 0.68, 1.61) for CNS tumors. CONCLUSIONS: We did not find evidence that domestic radon exposure is associated with childhood cancer, despite relatively high radon levels in Switzerland.

Progeny Trial Estimates of Genetic Parameters for Growth and Quality Traits in Scots Pine

Summary

Mixed mating in androdioecious Mercurialis annua inferred using progeny arrays and diploid-acting microsatellite loci in a hexaploid background.

Background and Aims The frequency at which males can be maintained with hermaphrodites in androdioecious populations is predicted to depend on the selfing rate, because self-fertilization by hermaphrodites reduces prospective siring opportunities for males. In particular, high selfing rates by hermaphrodites are expected to exclude males from a population. Here, the first estimates are provided of the mating system from two wild hexaploid populations of the androdioecious European wind-pollinated plant M. annua with contrasting male frequencies.Methods Four diploid microsatellite loci were used to genotype 19-20 progeny arrays from two populations of M. annua, one with males and one without. Mating-system parameters were estimated using the program MLTR.Key Results Both populations had similar, intermediate outcrossing rates (t(m) = 0.64 and 0.52 for the population with and without males, respectively). The population without males showed a lower level of correlated paternity and biparental inbreeding and higher allelic richness and gene diversity than the population with males.Conclusions The results demonstrate the utility of new diploid microsatellite loci for mating system analysis in a hexaploid plant. It would appear that androdioecious M. annua has a mixed-mating system in the wild, an uncommon finding for wind-pollinated species. This study sets a foundation for future research to assess the relative importance of the sexual system, plant-density variation and stochastic processes for the regulation of male frequencies in M. annua over space and time.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Influence of pre partum and post partum plane of nutrition on the performance of crossbred suckler cows and their progeny

Selostus: Sisäruokintakauden energiamäärien vaikutus risteytysemolehmien tuotantoon

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.

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.

Effects of winter feeding strategies with alternative feeds on the performance of mature suckler cows and their progeny

Selostus: Tasaruokinnan ja vaihtoehtoisten rehujen soveltuvuus emolehmien talvikauden ruokintaan

Effect of strenuous maternal exercise before and during pregnancy on rat progeny renal function

The effects of strenuous exercise before and during pregnancy on the renal function and morphological alterations of the progeny were determined in a study on female Wistar rats. This research was done based on a previous study carried out in our laboratory, which showed morphological alterations in rats submitted to this kind of exercise. As the form is related to the function, the physiological relevance of submitting a pregnant female to a high-intensity exercise training regimen could be explained by the fact that morphological alterations can influence kidney function. The animals were assigned to one of two groups: control animals that did not exercise during pregnancy and trained animals that swam for 120 min 5 days a week for 8 weeks before pregnancy and daily for 60 min over a period of 8 weeks starting on the second day of pregnancy. Seven rats of each group were analyzed for morphological alterations and for renal function. The progeny of the rats used for morphological evaluation were born by cesarean section and the progeny of the animals used to evaluate renal function were born normally. The progeny were two months old when renal function was evaluated. Fertility and morbidity were the same for both groups. Strenuous maternal exercise had no significant influence on glomerular filtration rate (GFR) but renal plasma flow was lower in the progeny of the trained group (mean ± SD, 16.65 ± 3.77 ml min-1 kg-1) compared to the progeny of the control group (33.42 ± 2.56 ml min-1 kg-1). Antidiuretic and antinatriuretic effects on the progeny of the trained group were observed, since urine flow as percentage of GFR and the fraction of urinary sodium excretion were lower in this group (1.38 ± 0.10 and 0.60 ± 0.04%, respectively) compared to the progeny of the control group (2.36 ± 0.11 and 1.55 ± 0.20%, respectively). Moreover, in this exercise program, fetuses from trained animals were small-sized (2.45 ± 0.19 vs 4.66 ± 2.45 g for control animals) and showed lower differentiation compared to fetuses from the control group. These effects were probably caused by caloric restriction, hypoxia and reduction of umbilical cord length.