Net regional ecosystem CO2 exchange from airborne and ground-based eddy covariance, land-use maps and weather observations

Measurements of regional net ecosystem exchange (NEE) were made over a period of 21 days in summer 2002 in the South‐Central part of the Netherlands and extrapolated to an area of 13 000 km² using a combination of flux measurements made by a Sky Arrow ERA research aircraft, half‐hourly eddy covariance data from four towers, half‐hourly weather data recorded by three weather stations and detailed information on regional land use. The combination of this type of information allowed to estimate the net contribution of the terrestrial ecosystems to the overall regional carbon flux and to map dynamically the temporal and spatial variability of the fluxes. A regional carbon budget was calculated for the study period and the contributions of the different land uses to the overall regional flux, were assessed. Ecosystems were, overall, a small source of carbon to the atmosphere equivalent to to 0.23±0.025 g C m⁻² day⁻¹. When considered separately, arable and grasslands were a source of, respectively, 0.68±0.022 and 1.28±0.026 g C m⁻² day⁻¹. Evergreen and deciduous forests were instead a sink of −1.42±0.015 g C m⁻² day⁻¹. During the study period, forests offset approximately 3.5% of anthropogenic carbon emission estimates obtained from inventory data. Lacking of a robust validation, NEE values obtained with this method were compared with independent state of art estimates of the regional carbon balance that were obtained by applying a semi‐empirical model of NEE driven by MODIS satellite fAPAR data. The comparison showed an acceptable matching for the carbon balance of forest that was a sink in both cases, while a much larger difference for arable and grassland was found. Those ecosystems were a sink for satellite‐based estimates while they were a source for the combined aircraft and tower estimates. Possible causes of such differences are discussed and partly addressed. The importance of new methods for determining carbon balance at the regional scale, is outlined.     

v-SNAREs control exocytosis of vesicles from priming to fusion

SNARE proteins (soluble NSF-attachment protein receptors) are thought to be central components of the exocytotic mechanism in neurosecretory cells, but their precise function remained unclear. Here, we show that each of the vesicle-associated SNARE proteins (v-SNARE) of a chromaffin granule, synaptobrevin II or cellubrevin, is sufficient to support Ca(2+)-dependent exocytosis and to establish a pool of primed, readily releasable vesicles. In the absence of both proteins, secretion is abolished, without affecting biogenesis or docking of granules indicating that v-SNAREs are absolutely required for granule exocytosis. We find that synaptobrevin II and cellubrevin differentially control the pool of readily releasable vesicles and show that the v-SNARE's amino terminus regulates the vesicle's primed state. We demonstrate that dynamics of fusion pore dilation are regulated by v-SNAREs, indicating their action throughout exocytosis from priming to fusion of vesicles.     

Functional groups based on leaf physiology: are they spatially and temporally robust?

The functional grouping concept, which suggests that complexity in ecosystem function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species regulate exchange of carbon and water with the atmosphere as indicated by both instantaneous gas exchange measurements and integrated measures of function (%N, δ¹³C, δ¹⁵N, C:N ratio) in fire-maintained Florida scrub, which was considered the natural state for scrub habitat. Using cluster analysis, five distinct physiologically based functional groups were identified in the fire-maintained scrub and were determined to be distinct clusters and not just arbitrary divisions in a continuous distribution by the non-parametric multivariate analysis of similarities (ANOSIM; R=0.649, P=0.005). These functional groups were tested for robustness spatially, temporally, and with management regime using ANOSIM. The physiological functional groups remained distinct clusters in this broader array of sites (R=0.794, P=0.001) and were not altered by plot differences, primarily, water table depth (R=−0.115, P=0.893) or by the three different management regimes: prescribed burn, mechanically treated and burned, and fire-suppressed (R=0.018, P=0.349). The physiological groupings also remained robust between the two climatically different years, with 1999 being a much wetter year than 2000 (R=−0.027, P=0.725). Easy-to-measure morphological characteristics, if they indicate the same functional groups, would be more practical for scaling and modeling ecosystem processes than detailed gas exchange measurements; therefore, we tested a variety of morphological characteristics as functional indicators. A combination of non-parametric multivariate techniques were used to compare the ability of life form, leaf thickness (LT), and specific leaf area (SLA) classifications to identify the physiologically based functional groups. Life form classifications (ANOSIM; R=0.629, P=0.001) were able to depict the physiological groupings more adequately than either SLA (ANOSIM; R=0.426, P=0.001) or LT (ANOSIM; R=0.344, P=0.001). The ability of life forms to depict the physiological groupings was improved by separating the parasitic Ximenia americana from the shrub category (ANOSIM; R=0.794, P=0.001). Therefore, a life form classification including parasites was determined to be a good indicator of the physiological processes of scrub species and would be a useful method of grouping species for scaling physiological processes to the ecosystem level.     

Characterization of iron compounds in tumour tissue from temporal lobe epilepsy patients using low temperature magnetic methods

Excess iron accumulation in the brain has been shown to be related to a variety of neurodegenerative diseases. However, identification and characterization of iron compounds in human tissue is difficult because concentrations are very low. For the first time, a combination of low temperature magnetic methods was used to characterize iron compounds in tumour tissue from patients with mesial temporal lobe epilepsy (MTLE). Induced magnetization as a function of temperature was measured between 2 and 140 K after cooling in zero-field and after cooling in a 50 mT field. These curves reveal an average blocking temperature for ferritin of 10 K and an anomaly due to magnetite at 48 K. Hysteresis measurements at 5 K show a high coercivity phase that is unsaturated at 7 T, which is typical for ferritin. Magnetite concentration was determined from the saturation remanent magnetization at 77 K. Hysteresis measurements at various temperatures were used to examine the magnetic blocking of magnetite and ferritin. Our results demonstrate that low temperature magnetic measurements provide a useful and sensitive tool for the characterisation of magnetic iron compounds in human tissue.Published online: March 2005     

Estimating the cumulative risk of a false-positive test in a repeated screening program

The goal of screening tests for a chronic disease such as cancer is early detection and treatment with a consequent reduction in mortality from the disease. Screening tests, however, might produce false positive and false-negative results. With an increasing number of screening tests, it is clear that the risk of a false-positive screen, a finding with potentially significant emotional, financial, and health costs, also increases. Elmore et al. (1998, New England Journal of Medicine 338, 1089-1096), Christiansen et al. (2000, Journal of the National Cancer Institute 92, 1657-1666), and Gelfand and Wang (2000, Statistics in Medicine 19, 1865-1879) investigated this problem under the somewhat unrealistic assumption that the choice of making the decision to drop out at the kth screen does not depend upon the results of the earlier k - 1 screens. In this article we obtain sufficient and necessary conditions for their assumption to hold and use one of them to provide a method for testing the validity of the assumption. A new model which does not depend on their assumption is introduced. The maximum likelihood estimator of the cumulative risk of receiving a false-positive screen under the new model is derived and its asymptotic normality is proved. The extension of the new model by incorporating covariate information is also considered. We apply our testing method and the new model to data from the breast cancer screening trial of the Health Insurance Plan of Greater New York.     

Inhibition of poly (ADP-ribose) polymerase and caspase-3, but not caspase-1, prevents apoptosis and improves spatial memory of rats with twice-repeated cerebral ischemia

The effect of inhibition of PARP [(poly (ADP-ribose) polymerase], caspase-3 and caspase-1 on twice-repeated ischemia-induced apoptosis and memory impairment were examined. The twice repeated ischemia was induced by four-vessel occlusion method in which a 10 min ischemic episode was repeated once after 60 min. The spatial memory was assessed using 8-arm radial maze. The results of this study showed that the repeated ischemia impaired memory and induced apoptosis in hippocampus CA1 field after 7 days. Moreover, 3-aminobezamide (10 mg/kg i.v.), a PARP inhibitor, and Ac-DEVD-CHO (8.4 microg/5 microL i.c.v., bilaterally), a caspase-3 inhibitor, decreased apoptosis by 45% and 58% respectively. Both drugs reduced the error choices, but 3-aminobezamide additionally increased the correct choices and improved the memory when either drug was injected immediately after the ischemic insult. The results also showed that inhibition of interleukin-1beta-converting enzyme, ICE (caspase-1) by Z-ASP-DCB-CH2 (100 microg/kg i.c.v., bilaterally) neither decreased apoptosis (13% reduction) nor improved memory of the ischemic rats. These results suggest that direct inhibition of PARP and caspase-3, but not of caspase-1, prevents apoptosis and improves spatial memory impaired by repeated ischemia.     

Modeling antitumor activity by using a non-linear mixed-effects model

The response of solid tumors to antitumor treatment generally declines markedly with treatment time. Sometimes, a tumor regrows (rebounds) before the end of the treatment period. Studies of the patterns of tumor response to treatment are important, because they may provide useful information for clinical decision-making. We have investigated patterns of tumor response in mouse xenograft tumors by using data from a study conducted at St. Jude Children's Research Hospital. We applied a biexponential non-linear mixed-effects model to an analysis of changes in tumor volume over a given period of treatment. The model gives a good fit to the data, even for small sample sizes. We addressed the relation between the baseline tumor volumes and the decay rates of the first and second stages of the tumor's response to treatment, and we applied sensitive analysis to determine the effect of using different imputed values for missing data. We also proposed a novel approach to a comparison of the antitumor effects of three different treatments, and we used the data from a St. Jude study to demonstrate the potential of this comparison approach in cancer clinical decision-making.     

Distinctive architecture of the chloroplast genome in the chlorophycean green alga Stigeoclonium helveticum

The chloroplast genome has experienced many architectural changes during the evolution of chlorophyte green algae, with the class Chlorophyceae displaying the lowest degree of ancestral traits. We have previously shown that the completely sequenced chloroplast DNAs (cpDNAs) of Chamydomonas reinhardtii (Chlamydomonadales) and Scenedesmus obliquus (Sphaeropleales) are highly scrambled in gene order relative to one another. Here, we report the complete cpDNA sequence of Stigeoclonium helveticum (Chaetophorales), a member of a third chlorophycean lineage. This genome, which encodes 97 genes and contains 21 introns (including four putatively trans-spliced group II introns inserted at novel sites), is remarkably rich in derived features and extremely rearranged relative to its chlorophycean counterparts. At 223,902 bp, Stigeoclonium cpDNA is the largest chloroplast genome sequenced thus far, and in contrast to those of Chlamydomonas and Scenedesmus, features no large inverted repeat. Interestingly, the pattern of gene distribution between the DNA strands and the bias in base composition along each strand suggest that the Stigeoclonium genome replicates bidirectionally from a single origin. Unlike most known trans-spliced group II introns, those of Stigeoclonium exhibit breaks in domains I and II. By placing our comparative genome analyses in a phylogenetic framework, we inferred an evolutionary scenario of the mutational events that led to changes in genome architecture in the Chlorophyceae.Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.Nucleotide sequence data reported are available in the GenBank database under the accession number DQ630521.     

Exploring interactions by second-stage community analyses

Many biological data sets, from field observations and manipulative experiments, involve crossed factor designs, analysed in a univariate context by higher-way analyses of variance which partition out ‘main’ and ‘interaction’ effects. Indeed, tests for significance of interactions among factors, such as differing Before-After responses at Control and Impact sites, are the basis of the widely used BACI strategy for detecting impacts in the environment. There are difficulties, however, in generalising simple univariate definitions of interaction, from classic linear models, to the robust, non-parametric multivariate methods that are commonly required in handling assemblage data. The size of an interaction term, and even its existence at all, depends crucially on the measurement scale, so it is fundamentally a parametric construct. Despite this, certain forms of interaction can be examined using non-parametric methods, namely those evidenced by changing assemblage patterns over many time periods, for replicate sites from different experimental conditions (types of ‘Beyond BACI’ design) - or changing multivariate structure over space, at many observed times. Second-stage MDS, which can be thought of as an MDS plot of the pairwise similarities between MDS plots (e.g. of assemblage time trajectories), can be used to illustrate such interactions, and they can be formally tested by second-stage ANOSIM permutation tests. Similarities between (first-stage) multivariate patterns are assessed by rank-based matrix correlations, preserving the fully non-parametric approach common in marine community studies. The method is exemplified using time-series data on corals from Thailand, macrobenthos from Tees Bay, UK, and macroalgae from a complex recolonisation experiment carried out in the Ligurian Sea, Italy. The latter data set is also used to demonstrate how the analysis copes straightforwardly with certain repeated-measures designs.