Environment versus dispersal in the assembly of western Amazonian palm communities

Aim It is a central issue in ecology and biogeography to understand what governs community assembly and the maintenance of biodiversity in tropical rain forest ecosystems. A key question is the relative importance of environmental species sorting (niche assembly) and dispersal limitation (dispersal assembly), which we investigate using a large dataset from diverse palm communities. Location Lowland rain forest, western Amazon River Basin, Peru. Methods We inventoried palm communities, registering all palm individuals and recording environmental conditions in 149 transects of 5 m × 500 m. We used ordination, Mantel tests and indicator species analysis (ISA) to assess compositional patterns, species responses to geographical location and environmental factors. Mantel tests were used to assess the relative importance of geographical distance (as a proxy for dispersal limitation) and environmental differences as possible drivers of dissimilarity in palm species composition. We repeated the Mantel tests for subsets of species that differ in traits of likely importance for habitat specialization and dispersal (height and range size). Results We found a strong relationship between compositional dissimilarity and environmental distance and a weaker but also significant relationship between compositional dissimilarity and geographical distance. Consistent with expectations, relationships with environmental and geographical distance were stronger for understorey species than for canopy species. Geographical distance had a higher correlation with compositional dissimilarity for small‐ranged species compared with large‐ranged species, whereas the opposite was true for environmental distance. The main environmental correlates were inundation and soil nutrient levels. Main conclusions The assembly of palm communities in the western Amazon appears to be driven primarily by species sorting according to hydrology and soil, but with dispersal limitation also playing an important role. The importance of environmental characteristics and geographical distance varies depending on plant height and geographical range size in agreement with functional predictions, increasing our confidence in the inferred assembly mechanisms.     

Identifying essential genes in bacterial metabolic networks with machine learning methods

Background  

Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective.     

Characterization of newly established colorectal cancer cell lines: correlation between cytogenetic abnormalities and allelic deletions associated with multistep tumorigenesis

We have established a series of 20 colorectal cancer cell lines and performed cytogenetic and RFLP analyses to show that the recurrent genetic abnormalities of chromosomes 1, 5, 17 and 18 associated with multistep tumorigenesis in colorectal cancer, and frequently detected as recurrent abnormalities in primary tumours, are also retained in long-term established cell lines. Earlier studies by us and other investigators showed that allelic losses of chromosomes 1 and 17 in primary colorectal cancers predicted poorer survival for the patients (P = 0.03). We utilized the cell lines to identify specific chromosomal sites or gene(s) on chromosomes 1 and 17 which confer more aggressive phenotype. Cytogenetic deletions of chromosome 1p were detected in 14 out of the 20 (70%) cell lines, whereas allelic deletions for 1p using polymorphic markers were detected in 13 out of 18 (72%) informative cell lines for at least one polymorphic marker. We have performed Northern blotting, immunohistochemical staining (p53 mRNA, protein) and RFLP analysis using several probes including p53 and nm23. RFLP analysis using a total of seven polymorphic markers located on 17p and 17q arms showed allelic losses aroundthe p53 locus in 16 out of the 20 cell lines (80%), four of which were losses of thep53 locus itself. In addition, seven cell lines (out of nine informative cases) also showed losses of thenm23 gene, four with concurrent losses of thep53 locus, while the remaining three were homozygous. In addition, five out of seven cell lines withnm23 deletions were derived from hepatic metastatic tumours, and one cell line was obtained from recurrent tumour. A comparison between allelic deletions of 1p and functional loss ofnm23 gene revealed a close association between these two events in cell lines derived from hepatic metastasis. Following immunohistochemical staining, nine out of the twenty cell lines showed high levels (25–80%) of mutant p53, four showed intermediate levels (>20%), and seven had undetectable levels of the protein. Of these seven, four showed complete absence of mRNA. Of the remaining three cell lines one showed aberrant mRNA due to germline rearrangement of thep53 gene, whereas in two cell lines normal levels of mRNA were present. Nineteen of the 20 cell lines had normal germline configurations for thep53 gene, while one showed a rearrangement. These data suggest that functional loss ofp53 andnm23 genes accomplished by a variety of mechanisms may be associated with poor prognosis and survival. In addition, concurrent deletions of chromosome regions 17p, 17q and 1p were closely associated with high-stage hepatic metastatic disease. These cell lines with well-characterized genetic alterations and known clinical history provide an invaluable source of material for various biological and clinical studies relating to multistep colorectal tumorigenesis.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

Toll-like receptor 4 deficiency: Smaller infarcts,but nogain in function

Backgound  

It has been reported that Toll-like receptor 4 (TLR4) deficiency reduces infarct size after myocardial ischemia/reperfusion (MI/R). However, measurement of MI/R injury was limited and did not include cardiac function. In a chronic closed-chest model we assessed whether cardiac function is preserved in TLR4-deficient mice (C3H/HeJ) following MI/R, and whether myocardial and systemic cytokine expression differed compared to wild type (WT).     

Effect of feeding boxes on the behavior of stereotyping amur tigers (Panthera tigris altaica) in the Zurich Zoo,Zurich, Switzerland

The stereotyped pacing shown by the two Amur tigers in the Zurich Zoo was hypothesized as being caused by permanently frustrated appetitive foraging behavior. Several electrically controlled feeding boxes were installed and access to each box was possible only twice a day for 15 min at semi‐random times. The boxes had to be opened actively by the tigers. Two trials were carried out: one with solitary confinement, and one with paired confinement. During box feeding, the female's stereotyped pacing was significantly reduced from 16% (solitary confinement, conventional feeding) and 7% (paired confinement, conventional feeding) to 1% (solitary confinement) and less than 0.01% (paired confinement) of the daily observed time. The female's sleeping increased significantly in both solitary and paired confinement. The male only showed a significant reduction in stereotyped pacing behavior when kept with the female (conventional feeding: 10%; box feeding: <0.01% of the daily observed time). On days with a box‐feeding regime in paired confinement, the male spent 25% (83 min) of the observed time with active behavior at the feeding boxes. The results support the hypothesis that permanently frustrated appetitive foraging behavior causes stereotyped pacing in adult tigers. Zoo Biol 21:573–584, 2002. © 2002 Wiley‐Liss, Inc.