Variations in water use by a mature mangrove of Avicennia germinans, French Guiana

In the tropical intertidal zones, little is known on water uptake by mangroves. Transpiration rates are generally measured at leaf level, but few studies exist on water use at tree or stand levels. The objective of this study was to measure sap flow in trees of different sizes to appreciate the range of variation in water use that may exist in a site dominated by 80% mature Avicennia germinans. The results showed that from the dry to the wet season the mean water use increased from 3.2 to 5.3 dm3 d−1 in small trees (DBH ∼ 13 cm), from 11.5 to 30.8 dm3 d−1 in medium trees (∼24 cm) and from 40.8 to 64.1 dm3 d−1 in large ones (∼45 cm). Sapwood remained active up to a depth of 8 cm with radial variations within the stem. Weak correlations were obtained with VPD and net radiation. This study confirmed that transpiration was larger under low levels of salinity. Water use at stand level (∼1900 living stems ha−1) was estimated to be in the range of 5.8 to 11.8 m3 ha−1 d−1 according to the season

Pcl-PRC2 is needed to generate high levels of H3-K27 trimethylation at Polycomb target genes

PRC2 is thought to be the histone methyltransferase (HMTase) responsible for H3-K27 trimethylation at Polycomb target genes. Here we report the biochemical purification and characterization of a distinct form of Drosophila PRC2 that contains the Polycomb group protein polycomblike (Pcl). Like PRC2, Pcl-PRC2 is an H3-K27-specific HMTase that mono-, di- and trimethylates H3-K27 in nucleosomes in vitro. Analysis of Drosophila mutants that lack Pcl unexpectedly reveals that Pcl-PRC2 is required to generate high levels of H3-K27 trimethylation at Polycomb target genes but is dispensable for the genome-wide H3-K27 mono- and dimethylation that is generated by PRC2. In Pcl mutants, Polycomb target genes become derepressed even though H3-K27 trimethylation at these genes is only reduced and not abolished, and even though targeting of the Polycomb protein complexes PhoRC and PRC1 to Polycomb response elements is not affected. Pcl-PRC2 is thus the HMTase that generates the high levels of H3-K27 trimethylation in Polycomb target genes that are needed to maintain a Polycomb-repressed chromatin state

From protein sequences to 3D-structures and beyond: the example of the UniProt Knowledgebase

With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website (http://www.uniprot.org/). It also evokes precautions that are necessary for successful predictions and extrapolations

Degradation of haloaromatic compounds

An ever increasing number of halogenated organic compounds has been produced by industry in the last few decades. These compounds are employed as biocides, for synthetic polymers, as solvents, and as synthetic intermediates. Production figures are often incomplete, and total production has frequently to be extrapolated from estimates for individual countries. Compounds of this type as a rule are highly persistent against biodegradation and belong, as "recalcitrant" chemicals, to the class of so-called xenobiotics. This term is used to characterise chemical substances which have no or limited structural analogy to natural compounds for which degradation pathways have evolved over billions of years. Xenobiotics frequently have some common features. e.g. high octanol/water partitioning coefficients and low water solubility which makes for a high accumulation ratio in the biosphere (bioaccumulation potential). Recalcitrant compounds therefore are found accumulated in mammals, especially in fat tissue, animal milk supplies and also in human milk. Highly sophisticated analytical techniques have been developed for the detection of organochlorines at the trace and ultratrace level

Nanoscale measurements of the mechanical properties of lipid bilayers

Lipid bilayers form the basis of the membranes that serve as a barrier between a cell and its physiological environment. Their physical properties make them ideally suited for this role: they are extremely soft with respect to bending but essentially incompressible under lateral tension, and they are quite permeable to water but essentially impermeable to ions which allows the rapid establishment of the osmotic gradients. The function of membrane proteins, which are vital for tasks ranging from signal transduction to energy conversion, depends on their interactions with the lipid environment. Because of the complexity of natural membranes, model systems consisting of simpler lipid mixtures have become indispensable tools in the study of membrane biophysics. The objective of the work reported here is to develop a deeper understanding of the underlying physics of lipid bilayers through nanoscale measurements of the mechanical properties of mixed lipid systems including cholesterol, a key ingredient of cell membranes. Atomic force microscopy (AFM) has been used extensively to measure the topographical and elastic properties of supported lipid bilayers displaying complex phase behaviour and containing mixtures of important PC, PE lipids and cholesterol. Phase transformations have been investigated varying the membrane temperature, and the effects of cholesterol in controlling membrane fluidity, phase, and energetics have been studied. Elastic modulus measurements were correlated with phase behaviour observations. To aid in the nanoscale probing of lipid bilayers, AFM probes with a high aspect ratio and tip radii of $sim$4~nm were fabricated and characterised. These probes were used to investigate the phase boundary in binary and ternary lipid systems, leading to the discovery of a raised region at the boundary which has implications for the localisation of reconstituted proteins as well as the role of natural domains or lipid rafts. The electrical properties of the probes were examined to assess their potential application for combined structural and electrical measurements in liquid. A novel technique was developed to aid in the study of the physical properties of lipid bilayers. Membrane budding was induced above microfabricated substrates through osmotic pressure. Modification of the adhesion energy of the bilayer through biotin-avidin linking was successful in modulating budding behaviour of liquid disordered bilayers. The free energy of the system was modelled to allow quantitative information to be extracted from the data.This thesis is not currently available in OR

Performance metrics for tensorial learning: prediction of Li4Ti5O12 nuclear magnetic resonance observables at experimental accuracy

Machine learning (ML) surrogate modeling is a powerful approach to reduce the computational cost of first-principles calculations. While well established for the prediction of scalar observables like energetics or band gaps, performance metrics for the learning of tensor-based observables have not yet been formalized. Here we use the electric field tensor (EFG) underlying nuclear magnetic resonance (NMR) spectroscopy to demonstrate and quantify the superiority of a tensorial learning that fully encodes the corresponding symmetries over a separate scalar learning of individual tensor-derived observables. To this end we establish an extensive EFG data set representative of real experimental applications and develop performance metrics for model evaluation which directly focus on the targeted NMR observables. Our results relate the inferiority of symmetry-agnostic scalar learning especially to its inability to capture the orientation of the EFG tensor. Tensorial learning instead achieves results within experimental precision at a high learning rate