Predicting fine‐scale distributions of peripheral aquatic species in headwater streams

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.     

Exploring the protein–protein interaction landscape in plants

Protein–protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.     

稻-鸭农作系统对稻田生物种群的影响

通过田间试验,研究了稻-鸭农作系统对稻田有关生物种群的影响.结果表明：稻鸭共育对稻田相关昆虫、杂草、病原菌等有害生物的发生和危害及天敌数量具有较大影响.与不养鸭相比,稻鸭共育后12 d和42 d, 水稻基部害虫飞虱及叶蝉的数量平均减少64.8%和78.5%;稻鸭共育后15 d和45 d,稻田杂草平均减少67.7%和98.1%;水稻分蘖高峰期和齐穗期的纹枯病病情指数分别降低了40.4%和62.0%.稻鸭共育还增加了稻田害虫天敌蜘蛛的数量,抑制了水稻害虫的危害.     

CeLINC,a fluorescence-based protein–protein interaction assay in Caenorhabditis elegans

Interactions among proteins are fundamental for life and determining whether two particular proteins physically interact can be essential for fully understanding a protein’s function. We present Caenorhabditis elegans light-induced coclustering (CeLINC), an optical binary protein–protein interaction assay to determine whether two proteins interact in vivo. Based on CRY2/CIB1 light-dependent oligomerization, CeLINC can rapidly and unambiguously identify protein–protein interactions between pairs of fluorescently tagged proteins. A fluorescently tagged bait protein is captured using a nanobody directed against the fluorescent protein (GFP or mCherry) and brought into artificial clusters within the cell. Colocalization of a fluorescently tagged prey protein in the cluster indicates a protein interaction. We tested the system with an array of positive and negative reference protein pairs. Assay performance was extremely robust with no false positives detected in the negative reference pairs. We then used the system to test for interactions among apical and basolateral polarity regulators. We confirmed interactions seen between PAR-6, PKC-3, and PAR-3, but observed no physical interactions among the basolateral Scribble module proteins LET-413, DLG-1, and LGL-1. We have generated a plasmid toolkit that allows use of custom promoters or CRY2 variants to promote flexibility of the system. The CeLINC assay is a powerful and rapid technique that can be widely applied in C. elegans due to the universal plasmids that can be used with existing fluorescently tagged strains without need for additional cloning or genetic modification of the genome.     

Primordia Vita. Deconvolution from Modern Sequences.

Evolution of the triplet code is reconstructed on the basis of consensus temporal order of appearance of amino acids. Several important predictions are confirmed by computational sequence analyses. The earliest amino acids, alanine and glycine, have been encoded by GCC and GGC codons, as today. They were succeeded, respectively, by A- and G-series of amino acids, encoded by pyrimidine-central and purine-central codons. The length of the earliest proteins is estimated to be 6–7 residues. The earliest mRNAs were short G+C-rich molecules. These short sequences could have formed hairpins. This is confirmed by analysis of modern prokaryotic mRNA sequences. Predominant size of detected ancient hairpins also corresponds to 6–7 amino acids, as above. Vestiges of last common ancestor can be found in extant proteins in form of entirely conserved short sequences of size six to nine residues present in all or almost all sequenced prokaryotic proteomes (omnipresent motifs). The functions of the topmost conserved octamers are not involved in the basic elementary syntheses. This suggests an initial abiotic supply of amino acids, bases and sugars. Presented at: National Workshop on Astrobiology: Search for Life in the Solar System, Capri, Italy, 26 to 28 October, 2005.     

The compliance score as a regressor in randomized trials

The compliance score in randomized trials is a measure of the effect of randomization on treatment received. It is in principle a group-level pretreatment variable and so can be used where individual-level measures of treatment received can produce misleading inferences. The interpretation of models with the compliance score as a regressor of interest depends on the link function. Using the identity link can lead to valid inference about the effects of treatment received even in the presence of nonrandom noncompliance; such inference is more problematic for nonlinear links. We illustrate these points with data from two randomized trials.     

Evaluating the use of macroscale variables as proxies for local aquatic variables and to model stream fish distributions

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Molecular dynamics simulation of helium–argon gas mixture under various wall conditions

As computational capabilities increase, molecular dynamics (MD) simulations become important tools of simulating reality. These simulations are especially useful for compressible gas mixture problems. In this study, binary diffusion of helium and argon was examined using a hard-sphere MD simulation method. For the sake of computational speed, low spacing ratios were chosen. Binary mass diffusion of gases in two equally sized halves of a box was simulated for identical initial kinetic energies and number densities. It has been noted that a purely mass diffusion mechanism of different gases is not physically possible. The resultant gas mixtures of several diffusion simulations were used as initial conditions for combined heat transfer – Couette flow, and heating and cooling experiments. The results showed the interesting behaviour of the mixture, which was subjected to various wall conditions. Energy of heavier molecules is found to be more sensitive to the wall velocities and less sensitive to the wall temperatures than lighter molecules. Diffusion, heat transfer, viscosity and heat capacity coefficients are deduced as well.     

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.     

Pattern-based clustering of daily weigh-in trajectories using dynamic time warping

“Smart”-scales are a new tool for frequent monitoring of weight change as well as weigh-in behavior. These scales give researchers the opportunity to discover patterns in the frequency that individuals weigh themselves over time, and how these patterns are associated with overall weight loss. Our motivating data come from an 18-month behavioral weight loss study of 55 adults classified as overweight or obese who were instructed to weigh themselves daily. Adherence to daily weigh-in routines produces a binary times series for each subject, indicating whether a participant weighed in on a given day. To characterize weigh-in by time-invariant patterns rather than overall adherence, we propose using hierarchical clustering with dynamic time warping (DTW). We perform an extensive simulation study to evaluate the performance of DTW compared to Euclidean and Jaccard distances to recover underlying patterns in adherence time series. In addition, we compare cluster performance using cluster validation indices (CVIs) under the single, average, complete, and Ward linkages and evaluate how internal and external CVIs compare for clustering binary time series. We apply conclusions from the simulation to cluster our real data and summarize observed weigh-in patterns. Our analysis finds that the adherence trajectory pattern is significantly associated with weight loss.