Quantitative measurements in 3-dimensional datasets of mouse lymph nodes resolve organ-wide functional dependencies

Deep tissue imaging has become state of the art in biology, but now the problem is to quantify spatial information in a global, organ-wide context. Although access to the raw data is no longer a limitation, the computational tools to extract biologically useful information out of these large data sets is still catching up. In many cases, to understand the mechanism behind a biological process, where molecules or cells interact with each other, it is mandatory to know their mutual positions. We illustrate this principle here with the immune system. Although the general functions of lymph nodes as immune sentinels are well described, many cellular and molecular details governing the interactions of lymphocytes and dendritic cells remain unclear to date and prevent an in-depth mechanistic understanding of the immune system. We imaged ex vivo lymph nodes isolated from both wild-type and transgenic mice lacking key factors for dendritic cell positioning and used software written in MATLAB to determine the spatial distances between the dendritic cells and the internal high endothelial vascular network. This allowed us to quantify the spatial localization of the dendritic cells in the lymph node, which is a critical parameter determining the effectiveness of an adaptive immune response.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Computational Techniques for Spatial Logistic Regression with Large Datasets

In epidemiological work, outcomes are frequently non-normal, sample sizes may be large, and effects are often small. To relate health outcomes to geographic risk factors, fast and powerful methods for fitting spatial models, particularly for non-normal data, are required. We focus on binary outcomes, with the risk surface a smooth function of space. We compare penalized likelihood models, including the penalized quasi-likelihood (PQL) approach, and Bayesian models based on fit, speed, and ease of implementation. A Bayesian model using a spectral basis representation of the spatial surface provides the best tradeoff of sensitivity and specificity in simulations, detecting real spatial features while limiting overfitting and being more efficient computationally than other Bayesian approaches. One of the contributions of this work is further development of this underused representation. The spectral basis model outperforms the penalized likelihood methods, which are prone to overfitting, but is slower to fit and not as easily implemented. Conclusions based on a real dataset of cancer cases in Taiwan are similar albeit less conclusive with respect to comparing the approaches. The success of the spectral basis with binary data and similar results with count data suggest that it may be generally useful in spatial models and more complicated hierarchical models.

Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection

Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining 'molecular Banff' signatures. Recently, the description of pathogenesis-based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high-quality transcript panels is thus critical to define high-performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up-regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the 'in silico' approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.

RNetCDF – A Package for Reading and Writing NetCDF Datasets

This paper describes the RNetCDF package (version 1.6), an interface for reading and writing files in Unidata NetCDF format, and gives an introduction to the NetCDF file format. NetCDF is a machine independent binary file format which allows storage of different types of array based data, along with short metadata descriptions. The package presented here allows access to the most important functions of the NetCDF C-interface for reading, writing, and modifying NetCDF datasets. In this paper, we present a short overview on the NetCDF file format and show usage examples of the package.

A systematized workflow for assessing land resources using readily available spatial datasets

Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Optimally Combining Censored and Uncensored Datasets

Economists and other social scientists often face situations where they have access to two datasets that they can use but one set of data suffers from censoring or truncation. If the censored sample is much bigger than the uncensored sample, it is common for researchers to use the censored sample alone and attempt to deal with the problem of partial observation in some manner. Alternatively, they simply use only the uncensored sample and ignore the censored one so as to avoid biases. It is rarely the case that researchers use both datasets together, mainly because they lack guidance about how to combine them. In this paper, we develop a tractable semiparametric framework for combining the censored and uncensored datasets so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. When the censored sample, which we refer to as the master sample, is much bigger than the uncensored sample (which we call the refreshment sample), the latter can be thought of as providing identification where it is otherwise absent. In contrast, when the refreshment sample is large and could typically be used alone, our methodology can be interpreted as using information from the censored sample to increase effciency. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. We also demonstrate how refreshment samples for this application can be created by matching cohort information across census datasets.

Ocean temperature measured by elephant seal-CTDs in the Southern Ocean with links to datasets

The potential effects of ocean warming on marine predators are largely unknown, though the impact on the distribution of prey in vertical space may have far reaching impacts on diving predators such as southern elephant seals. We used data from satellite-tracked southern elephant seals from Marion Island to investigate the relationship between their dive characteristics (dive depths, dive durations and time-at-depth index values) and environmental variables (temperature at depth, depth of maximum temperature below 100 m, frontal zone and bathymetry) as well as other demographic and behavioural variables (migration stage, age-class, track day and vertical diel strategy). While other variables, such as bathymetry and vertical diel strategy also influenced dive depth, our results consistently indicated a significant influence of temperature at depth on dive depths. This relationship was positive for all groups of animals, indicating that seals dived to deeper depths when foraging in warmer waters. Female seals adjusted their dive depths proportionally more than males in warmer water. Dive durations were also influenced by temperature at depth, though to a lesser extent. Results from time-at-depth indices showed that both male and female seals spent less time at targeted dive depths in warmer water, and were presumably less successful foragers when diving in warmer water. Continued warming of the Southern Ocean may result in the distribution of prey for southern elephant seals shifting either poleward and/or to increasing depths. Marion Island elephant seals are expected to adapt their ranging and diving behaviour accordingly, though such changes may result in greater physiological costs associated with foraging.

Dive depth and dive duration data of subadult and adult, male and female southern elephant seals from Marion Island between 2004 and 2008 with links to datasets

Although numerous studies have addressed the migration and dive behaviour of southern elephant seals (Mirounga leonina), questions remain about their habitat use in the marine environment. We report on the vertical use of the water column in the species and the potential lifetime implications for southern elephant seals from Marion Island. Long-term mark-resight data were used to complement vertical habitat use for 35 known individuals tagged with satellite-relay data loggers, resulting in cumulative depth use extrapolated for each individual over its estimated lifespan. Seals spent on average 77.59% of their lives diving at sea, 7.06% at the sea surface, and 15.35% hauled out on land. Some segregation was observed in maximum dive depths and depth use between male and female animals-males evidently being physiologically more capable of exploiting increased depths. Females and males spent 86.98 and 80.89% of their lives at sea, respectively. While at sea, all animals spent more time between 300 and 400 m depth, than any other depth category. Males and females spent comparable percentages of their lifetimes below 100 m depth (males: 65.54%; females: 68.92%), though males spent 8.98% of their lives at depths in excess of 700 m, compared to females' 1.84% at such depths. Adult males often performed benthic dives in excess of 2,000 m, including the deepest known recorded dive of any air-breathing vertebrate (>2,133 m). Our results provide a close approximation of vertical habitat use by southern elephant seals, extrapolated over their lifespans, and we discuss some physiological and developmental implications of their variable depth use.

Dive depth and dive duration data of subadult and adult, male and female southern elephant seals from Marion Island between 2004 and 2008 with links to datasets

Sexual segregation in habitat use occurs in a number of animal species, including southern elephant seals, where differences in migration localities and dive behaviour between sexes have been recorded. Due to the extreme sexual size dimorphism exhibited by southern elephant seals, it is unclear whether observed differences in dive behaviour are due to increased physiological capacity of males, compared to females, or differences in activity budgets and foraging behaviour. Here we use a mixed-effects modelling approach to investigate the effects of sex, size, age and individual variation on a number of dive parameters measured on southern elephant seals from Marion Island. Although individual variation accounted for substantial portions of total model variance for many response variables, differences in maximum and targeted dive depths were always influenced by sex, and only partly by body length. Conversely, dive durations were always influenced by body length, while sex was not identified as a significant influence. These results support hypotheses that physiological capability associated with body size is a limiting factor on dive durations. However, differences in vertical depth use appear to be the result of differences in forage selection between sexes, rather than a by-product of the size dimorphism displayed by this species. This provides further support for resource partitioning and possible avoidance of inter-sexual competition in southern elephant seals.

At surface behaviour data of juvenile southern elephant seals from Marion Island between 2001 and 2006 with links to datasets

Marine mammals forage in dynamic environments characterized by variables that are continuously changing in relation to large-scale oceanographic processes. In the present study, behavioural states of satellite-tagged juvenile southern elephant seals (n = 16) from Marion Island were assessed for each reliable location, using variation in turning angle and speed in a state-space modelling framework. A mixed modelling approach was used to analyse the behavioural response of juvenile southern elephant seals to sea-surface temperature and proximity to frontal and bathymetric features. The findings emphasised the importance of frontal features as potentially rewarding areas for foraging juvenile southern elephant seals and provided further evidence of the importance of the area west of Marion Island for higher trophic-level predators. The importance of bathymetric features during the transit phase of juvenile southern elephant seal migrations indicates the use of these features as possible navigational cues.

Reference datasets and pollen record from sediment core YAK, Yakumo, SW Hokkaido

This study reconstructs middle and late Holocene vegetation and climate dynamics in the Oshima Peninsula, SW Hokkaido, using the published method of biome reconstruction and modern analogue technique applied to the Yakumo pollen record (42°17'03''N, 140°15'34''E) spanning the last 5500 years. Two previously published matrices assigning Japanese plant/pollen taxa to the major vegetation types (biomes) are tested using a newly compiled dataset of 78 surface pollen spectra from Hokkaido. With both matrices showing strengths and weaknesses in reconstructing cool mixed and temperate deciduous forests of Hokkaido, the results suggest the necessity to consider the whole list of identified terrestrial pollen taxa for generating robust vegetation reconstructions for northern Japan. Applied to the fossil pollen data, both biome-reconstruction approaches demonstrate consistently that oak-dominated cool mixed forest spread in the study region between 5.5 and 3.6 cal ka BP and was subsequently replaced by beech-dominated temperate deciduous forest. The pollen-based climate reconstruction suggests this change in the vegetation composition was caused by a shift from cooler and drier than present climate to warmer and wetter, similar to modern conditions about 3.6 cal ka BP. Comparing the pollen-based reconstruction results with the published marine records from the NW Pacific, the reconstructed vegetation and climate dynamics can be satisfactorily explained by the greater role played by the warm Tsushima Current in the Sea of Japan and in the Tsugaru Strait during the middle and late Holocene. An increase in sea surface temperatures west and south of the study site would favour air temperature rise and moisture uptake and cause an increase in precipitation and snow accumulation in the western part of Hokkaido during the late Holocene.