Highly recurrent BRAF p.V595E mutation in canine papillary oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common oral epithelial malignancy in dogs. It exhibits locally aggressive biological behaviour with the potential to metastasize, and a reported 1-year survival rate of 0% when left untreated. Expression studies suggest that aberrant MAPK signalling plays a key role in canine OSCC tumorigenesis, which is consistent with BRAF and HRAS MAPK-activating mutations reported in some tumours. Several morphological subtypes of canine OSCC have been described, with papillary, conventional, and basaloid as the most common patterns. We hypothesized that mutational differences may underlie these phenotypic variations. In this study, targeted Sanger sequencing and restriction fragment length polymorphism assays demonstrate that up to 85.7% of canine papillary OSCC (n = 14) harbour a BRAF p.V595E mutation. Assessment of neoplastic epithelial cell proliferation using Ki67 immunolabelling (n = 10) confirmed a relatively high proliferation activity, consistent with their known aggressive clinical behaviour. These findings underscore a consistent genetic feature of canine papillary OSCC and provide a basis for the development of novel diagnostic and targeted therapeutic approaches that can improve the quality of veterinary care.     

Drivers of recent forest cover change in southern South America are linked to climate and CO2

Landscape Ecology - Widespread changes in forest structure and distribution have been documented in northern Patagonia over the past century. We employed LPJ-GUESS, a dynamic global...     

养猪生产中后代性别的预选——发展现状和应用前景

动物精子的性别可通过流式精子分选仪和DNA标识进行鉴定,而利用鉴定性别的精子(即性控精子)并借助人工授精技术或其它授精技术产生的后代,在过去5年中估计已多达30000个(其中大多数是母牛)。有关文献资料证明,能有效地区分X精子和Y精子的唯一标记物是精子染色体中的DNA。众所周知,目前世界各地采用的方法是Beltsville精子分选技术,该技术根据X精子群和Y精子群中DNA相对含量上的差异,用荧光染液(Hoechst33342染液)标记精子,随后利用流式细胞仪分选经荧光标记的精子,从而达到分离精子的目的。目前,X精子或Y精子正常的生产速度是每小时1500万个,该项技术已在家畜、实验动物和动物园动物中应用,如果将该技术应用在人上,在预选后代性别比例上可达90%～95%的成功率。因动物品种不同,性控精子在动物体内的授精部位也不相同。常规的人工授精技术、宫内授精技术、输卵管内授精技术、用于胚胎移植的体外受精(in-vitro fertilization,IVF)技术或子宫角深部授精技术均能有效地使动物怀孕,至于利用哪种技术进行性控精子的精则取决于动物品种。尽管所有动物都能获得高纯度的分选精子,但是在实际生产中利用低剂量精子还难以让母猪怀孕。子宫角深部授精技术每次授精0.5～1.00亿个性控精子已能产生可喜的效果:利用特制的输精管,输入常规人工授精所需精子量的五十分之一的性控精子,足以使动物怀孕。性控精子通过常规的授精技术能够被猪成功利用前,还需重新设计输精管,同时输精的次数和每次授精时精子数量也需作进一步的研究。分选精子的低温保存技术已被牛人工授精普遍采用。尽管已能利用冷冻的性别分选精子生产小猪,但是性别分选精子经冷冻和解冻处理后在常规生产中的应用还未达到最理想的效果。本文将讨论猪精子性别分选的最新研究成果及其发展趋势,并重点探讨将性别分选技术应用于养猪生产中必须对其进行必要的技术开发。     

Land-use history has a stronger impact on soil microbial community composition than aboveground vegetation and soil properties

The response of soil microbial communities following changes in land-use is governed by multiple factors. The objectives of this study were to investigate (i) whether soil microbial communities track the changes in aboveground vegetation during succession; and (ii) whether microbial communities return to their native state over time. Two successional gradients with different vegetation were studied at the W. K. Kellogg Biological Station, Michigan. The first gradient comprised a conventionally tilled cropland (CT), mid-succession forest (SF) abandoned from cultivation prior to 1951, and native deciduous forest (DF). The second gradient comprised the CT cropland, early-succession grassland (ES) restored in 1989, and long-term mowed grassland (MG). With succession, the total microbial PLFAs and soil microbial biomass C consistently increased in both gradients. While bacterial rRNA gene diversity remained unchanged, the abundance and composition of many bacterial phyla changed significantly. Moreover, microbial communities in the relatively pristine DF and MG soils were very similar despite major differences in soil properties and vegetation. After >50 years of succession, and despite different vegetation, microbial communities in SF were more similar to those in mature DF than in CT. In contrast, even after 17 years of succession, microbial communities in ES were more similar to CT than endpoint MG despite very different vegetation between CT and ES. This result suggested a lasting impact of cultivation history on the soil microbial community. With conversion of deciduous to conifer forest (CF), there was a significant change in multiple soil properties that correlated with changes in microbial biomass, rRNA gene diversity and community composition. In conclusion, history of land-use was a stronger determinant of the composition of microbial communities than vegetation and soil properties. Further, microbial communities in disturbed soils apparently return to their native state with time.     

Use of spectral radiance for correcting nitrogen deficiencies and estimating soil test variability in an established bermudagrass pasture

The use of variable rate technology has become increasingly popular for applying plant nutrient elements. The most widely used method for determining variable fertilizer rates is presently based on soil testing and yield mapping. Three field studies (Bumeyville 1995, Burneyville 1996, and Ardmore 1996) were initiated in established Midland bermudagrass [Cynodon dacrylon (L) Pers.] pastures to determine the relationship between spectral radiance at specific wavelengths with forage nitrogen (N) removal and biomass, and to determine field variability of soil test parameters. Variable N (applied to 1.5 × 2.4 m subplots within 2.4 × 45.7 m main plots), fixed N and check treatments were evaluated at each location. Spectral radiance readings were taken in the red (671±6 nm), green (570±6 nm), and near infrared (NIR) (780±6 nm) wavelengths. The normalized difference vegetation index (NDVI) was calculated as NIR‐red/NIR+red. Variable N rates were applied based on NDVI. The highest fixed variable N rate was set at 224, 336, and 672 kg N ha^‐1 for Burneyville, 1995, 1996, and Ardmore, 1996, respectively. At Bumeyville, soil samples were collected in all variable rate plots (1.5 × 2.4 m) and analyzed for various soil test characteristics. NDVI, red, green, and NIR spectral radiance readings were correlated with bermudagrass forage N removal and yield. Correlation of forage yield and N removal with red, NIR, and NDVI were best with maximum forage production, however, when forage production levels were low correlation decreased dramatically for the red wavelength compared with NIR and NDVI. Forage yield and forage N removal in variable rate treatments increased when compared to the check while being equal to the half‐fixed and fixed rates where higher N rates were applied. Also, variability about the mean in variable rate plots was significantly lower than half‐fixed and fixed rates which supports adjusting N rates based on indirect NDVI measurements. Variable N rate plots reduced fertilizer inputs by 60% and produced the same yield as fixed rate plots, while fixed and half‐fixed rates did not increase N content in the forage over that of the variable rate treatment. Soil sample data collected from small consecutive plots (<4 m²) was extremely variable indicating that intense sampling would be needed if variable fertilizer application were to be based on soil test results.     

Classification of Azolla spp., section Azolla

Summary Azolla accessions (section Azolla) from the germplasm collections of the International Rice Research Institute and Washington State University were fingerprinted and classified by enzyme electrophoresis and leaf trichome morphology. A. filiculoides was enzymatically distinctive and also reliably identified by its prominent one-celled trichomes. Neotropical accessions labelled as A. filiculoides proved to be members of other species. Two groups of isolates were designated A. rubra, but those from Japan were identified as A. filiculoides. The A. rubra of Australia-New Zealand was biochemically unique and possessed less protuberant trichomes than A. filiculoides. A. microphylla, A. mexicana, and A. caroliniana were phenetically similar, but a. microphylla was identifiable from the others in the banding patterns of certain enzymes. A. mexicana and A. caroliniana were closely related enzymatically. The two-celled leaf trichomes of these three species were similar in size and shape.     

Using unsupervised learning techniques to assess interactions among complex traits in soybeans

Soybean yield components and agronomic traits are connected through physiological pathways that impose tradeoffs through genetic and environmental constraints. Our primary aim is to assess the interdependence of soybean traits by using unsupervised machine learning techniques to divide phenotypic associations into environmental and genetic associations. This study was performed on large scale, jointly analyzing 14 quantitative traits in a large multi-parental population designed for genetic studies. We collected phenotypes from 2012 to 2015 from a soybean nested association panel with 40 families of approximately 140 individuals each. Pearson and Spearman correlations measured phenotypic associations. A multivariate mixed linear model provided genotypic and environmental correlations. To evaluate relationships among traits, the study used principal component and undirected graphical models from phenotypic, genotypic, and environmental correlation matrices. Results indicate that high phenotypic correlation occurs when traits display both genetic and environmental correlations. In genetic terms, length of reproductive period, node number, and canopy coverage play important roles in determining yield potential. Optimal grain yield production occurs when the growing environment favors faster canopy closure and extended reproductive length. Environmental associations found among yield components give insight into the nature of yield component compensation. The use of unsupervised learning methods provides a good framework for investigating interactions among various quantitative traits and defining target traits for breeding.     

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Context

Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.

Objectives

We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.

Methods

We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.

Results

Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.

Conclusions

This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.