139 research outputs found

    移植神経細胞の突起伸長は老齢ラットよりも幼若ラットにおいて著明に増加することが蛍光信号の自動計測で示される

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    京都大学新制・課程博士博士(医科学)甲第24202号医科博第143号京都大学大学院医学研究科医科学専攻(主査)教授 井上 治久, 教授 髙橋 良輔, 教授 花川 隆学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA

    Automated measurement of fluorescence signals reveals a significant increase of the graft-derived neurite extension in neonates compared to aged rats

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    [Background] --Neural tissue grafting is an acceptable form of cell therapy for brain injury and diseases. However, methods that can evaluate the graft integration and measure axonal extensions in a 3D environment are limited in scale, inconvenient, and operator intensive. [Method] --We stained grafts with a fluorescent antibody and then quantified the amount of fluorescence through the entire brain. To achieve this, we created an automated computer program designed to sort out authentic staining from background noise without any user input, enabling the analysis of thousands of images. [Results] --Our program could compensate for variations in the background brightness between images in all animals. Using this program, we show that human induced pluripotent stem cell (iPSC)-derived dopaminergic (DA) progenitor cells integrate better into the striatum of neonates than older rats. [Conclusion] --Our program can quantify quickly and conveniently the integration of neural grafts in a 3D environment without depending on a blinded human operator. We expect this method to be a useful tool to assess the efficiency of graft-enhancing treatments for neurodegenerative diseases or other neural reconstruction attempts

    Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar

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    Recent studies have underlined the importance of climatic variables in determining tree height and biomass in tropical forests. Nonetheless, the effects of climate on tropical forest carbon stocks remain uncertain. In particular, the application of process-based dynamic global vegetation models has led to contrasting conclusions regarding the potential impact of climate change on tropical forest carbon storage. Using a correlative approach based on a bioclimatic envelope model and data from 1771 forest plots inventoried during the period 1996–2013 in Madagascar over a large climatic gradient, we show that temperature seasonality, annual precipitation and mean annual temperature are key variables in determining forest above-ground carbon density. Taking into account the explicative climate variables, we obtained an accurate (R2 = 70% and RMSE = 40 Mg ha−1) forest carbon map for Madagascar at 250 m resolution for the year 2010. This national map was more accurate than previously published global carbon maps (R2 ≤ 26% and RMSE ≥ 63 Mg ha−1). Combining our model with the climatic projections for Madagascar from 7 IPCC CMIP5 global climate models following the RCP 8.5, we forecast an average forest carbon stock loss of 17% (range: 7–24%) by the year 2080. For comparison, a spatially homogeneous deforestation of 0.5% per year on the same period would lead to a loss of 30% of the forest carbon stock. Synthesis. Our study shows that climate change is likely to induce a decrease in tropical forest carbon stocks. This loss could be due to a decrease in the average tree size and to shifts in tree species distribution, with the selection of small-statured species. In Madagascar, climate-induced carbon emissions might be, at least, of the same order of magnitude as emissions associated with anthropogenic deforestation

    Multi-scale digital soil mapping with deep learning

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    We compared different methods of multi-scale terrain feature construction and their relative effectiveness for digital soil mapping with a Deep Learning algorithm. The most common approach for multi-scale feature construction in DSM is to filter terrain attributes based on different neighborhood sizes, however results can be difficult to interpret because the approach is affected by outliers. Alternatively, one can derive the terrain attributes on decomposed elevation data, but the resulting maps can have artefacts rendering the approach undesirable. Here, we introduce ‘mixed scaling’ a new method that overcomes these issues and preserves the landscape features that are identifiable at different scales. The new method also extends the Gaussian pyramid by introducing additional intermediate scales. This minimizes the risk that the scales that are important for soil formation are not available in the model. In our extended implementation of the Gaussian pyramid, we tested four intermediate scales between any two consecutive octaves of the Gaussian pyramid and modelled the data with Deep Learning and Random Forests. We performed the experiments using three different datasets and show that mixed scaling with the extended Gaussian pyramid produced the best performing set of covariates and that modelling with Deep Learning produced the most accurate predictions, which on average were 4–7% more accurate compared to modelling with Random Forests

    Chapitre 2. Spatialiser les stocks de carbone

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    Introduction Dans les laboratoires d’analyse des sols à Madagascar, la mesure du carbone organique du sol (COS) sert à calculer la teneur en matière organique (MO), une information utile pour la gestion de la fertilité des sols. Outre son évaluation quantitative, diverses études sur le COS ont été menées sur (1) sa dynamique, en interaction avec les autres constituants du sol selon les pratiques et modes d’usage des terres ou (2) sur sa variabilité spatio-temporelle. Ces études ont été effect..

    New insights into the systematics of Malagasy mongoose-like carnivorans (Carnivora, Eupleridae, Galidiinae) based on mitochondrial and nuclear DNA sequences

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    The Malagasy carnivorans (Eupleridae) comprise seven genera and up to ten species, depending on the authority, and, within the past decades, two new taxa have been described. The family is divided into two subfamilies, the Galidiinae, mongoose-like animals, and the Euplerinae, with diverse body forms. To verify the taxonomic status of Galidiinae species, including recently described taxa, as well as some recognized subspecies, we studied intrageneric genetic variation and structure, using both mitochondrial and nuclear markers. Our results suggest the recognition of four species in the Galidiinae, rendering each genus monospecific. We propose to recognize three subspecies in Galidia elegans (G. e. dambrensis, G. e. elegans, and G. e. occidentalis), two subspecies in Mungotictis decemlineata (M. d. decemlineata and M. d. lineata), and two subspecies in Galidictis fasciata (G. f. fasciata and G. f. grandidieri, the latter was recently described as a distinct species). Our results indicate also that Salanoia durrelli should be treated as a junior synonym of Salanoia concolor. Low levels of intraspecific divergence revealed some geographical structure for the Galidiinae taxa, suggesting that environmental barriers have isolated certain populations in recent geological time. All taxa, whether at the species or subspecies level, need urgent conservation attention, particularly those with limited geographical distributions, as all are threatened by forest habitat degradation
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