Stem water storage and diurnal patterns of water use in tropical forest canopy trees

Stem water storage capacity and diurnal patterns of water use were studied in five canopy trees of a seasonal tropical forest in Panama. Sap flow was measured simultaneously at the top and at the base of each tree using constant energy input thermal probes inserted in the sapwood. The daily stem storage capacity was calculated by comparing the diurnal patterns of basal and crown sap flow. The amount of water withdrawn from storage and subsequently replaced daily ranged from 4 kg d^–1 in a 0·20-m-diameter individual of Cecropia longipes to 54 kg d^–1 in a 1·02-m-diameter individual of Anacardium excelsum, representing 9–15% of the total daily water loss, respectively. Ficus insipida, Luehea seemannii and Spondias mombin had intermediate diurnal water storage capacities. Trees with greater storage capacity maintained maximum rates of transpiration for a substantially longer fraction of the day than trees with smaller water storage capacity. All five trees conformed to a common linear relationship between diurnal storage capacity and basal sapwood area, suggesting that this relationship was species-independent and size-specific for trees at the study site. According to this relationship there was an increment of 10 kg of diurnal water storage capacity for every 0·1 m² increase in basal sapwood area. The diurnal withdrawal of water from, and refill of, internal stores was a dynamic process, tightly coupled to fluctuations in environmental conditions. The variations in basal and crown sap flow were more synchronized after 1100 h when internal reserves were mostly depleted. Stem water storage may partially compensate for increases in axial hydraulic resistance with tree size and thus play an important role in regulating the water status of leaves exposed to the large diurnal variations in evaporative demand that occur in the upper canopy of seasonal lowland tropical forests.     

Detecting network communities: an application to phylogenetic analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis.     

Dynamic viral populations in hypersaline systems as revealed by metagenomic assembly

Viruses of the Bacteria and Archaea play important roles in microbial evolution and ecology, and yet viral dynamics in natural systems remain poorly understood. Here, we created de novo assemblies from 6.4 Gbp of metagenomic sequence from eight community viral concentrate samples, collected from 12 h to 3 years apart from hypersaline Lake Tyrrell (LT), Victoria, Australia. Through extensive manual assembly curation, we reconstructed 7 complete and 28 partial novel genomes of viruses and virus-like entities (VLEs, which could be viruses or plasmids). We tracked these 35 populations across the eight samples and found that they are generally stable on the timescale of days and transient on the timescale of years, with some exceptions. Cross-detection of the 35 LT populations in three previously described haloviral metagenomes was limited to a few genes, and most previously sequenced haloviruses were not detected in our samples, though 3 were detected upon reducing our detection threshold from 90% to 75% nucleotide identity. Similar results were obtained when we applied our methods to haloviral metagenomic data previously reported from San Diego, CA: 10 contigs that we assembled from that system exhibited a variety of detection patterns on a timescale of weeks to 1 month but were generally not detected in LT. Our results suggest that most haloviral populations have a limited or, possibly, a temporally variable global distribution. This study provides high-resolution insight into viral biogeography and dynamics and it places "snapshot" viral metagenomes, collected at a single time and location, in context.     

The Psychedelic State Induced by Ayahuasca Modulates the Activity and Connectivity of the Default Mode Network

The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.     

Purification of a lectin from Eugenia uniflora L. seeds and its potential antibacterial activity

Aims: The aim of this work was to analyse the antimicrobial properties of a purified lectin from Eugenia uniflora L. seeds. Methods and Results: The E. uniflora lectin (EuniSL) was isolated from the seed extract and purified by ion‐exchange chromatography in DEAE‐Sephadex with a purification factor of 11·68. The purified lectin showed a single band on denaturing electrophoresis, with a molecular mass of 67 kDa. EuniSL agglutinated rabbit and human erythrocytes with a higher specificity for rabbit erythrocytes. The haemagglutination was not inhibited by the tested carbohydrates but glycoproteins exerted a strong inhibitory action. The lectin proved to be thermo resistant with the highest stability at pH 6·5 and divalent ions did not affect its activity. EuniSL demonstrated a remarkable nonselective antibacterial activity. EuniSL strongly inhibited the growth of Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella sp. with a minimum inhibitory concentration (MIC) of 1·5 μg ml^?1, and moderately inhibited the growth of Bacillus subtilis, Streptococcus sp. and Escherichia coli with a MIC of 16·5 μg ml^?1. Conclusions: EuniSL was found to be effective against bacteria. Significance and Impact of the Study: The strong antibacterial activity of the studied lectin indicates a high potential for clinical microbiology and therapeutic applications.     

Zero‐modified Poisson model: Bayesian approach,influence diagnostics,and an application to a Brazilian leptospirosis notification data

In this paper, a Bayesian method for inference is developed for the zero‐modified Poisson (ZMP) regression model. This model is very flexible for analyzing count data without requiring any information about inflation or deflation of zeros in the sample. A general class of prior densities based on an information matrix is considered for the model parameters. A sensitivity study to detect influential cases that can change the results is performed based on the Kullback–Leibler divergence. Simulation studies are presented in order to illustrate the performance of the developed methodology. Two real datasets on leptospirosis notification in Bahia State (Brazil) are analyzed using the proposed methodology for the ZMP model.