The Dynamics of an Avoidance Behavior by Ixodid Ticks to Liquid Water

Life stages of different tick species avoid walking on a wet surface surrounding a dry patch by systematically returning to the dry each time they contact the wet surface beyond the border with the tip of a first leg tarsus. Sequential analysis of the border behaviors shows that repetitive contact with the water increases the probability of walks astride the border. Ticks accept this unilateral contact with the water for longer intervals and eventually walk on to the wet surface after a combination of a short patch walk followed by a border walk which is longer than the foregoing ones. Staying time on a small circular patch is shorter than on a large one, arising probably from faster adaptation of peripheral receptors following a higher frequency of border contacts. However, an equal number of border reactions on patches of different sizes and shapes suggests that a counter in the CNS may also influence dry patch departure.     

Particle size dependent feeding by the rotifer Brachionus plicatilis

Size selective feeding by Brachionus plicatilis was investigated with algae and bacteria (0.3–3.5 µm) and mono-disperse latex beads (0.3–3.0 µm) in short term feeding experiments. B. plicatilis demonstrated maximum clearance rate of particles with diameter 2µm, but particles with diameter down to 0.3 µm were also ingested. The clearance rate of bacteria was 15–55% of that obtained for optimal sized particles (2 µm), and was related to particle size. The relative reduction in retention of particles with diameter < 2 µm was more pronounced for latex beads than for natural food particles, suggesting other mechanisms than size to be important for the particle retention by the rotifer. This is emphasized by the fact that the clearance rates were much lower for latex beads than for natural food particles of comparable size. Efficient retention of bacteria was observed for rotifers in poor physiological condition, i.e. rotifers with low maximum clearance rate. This may reflect a strategy to optimize energy utilization by reducing locomotion costs and increasing energy intake.The results indicate that B. plicatilis has a low to medium ability to feed on bacteria. In natural ecosystems, its importance as a bacterial grazer is of limited importance. At high population densities, such as in live feed cultures, the rotifer may, however, efficiently remove bacteria from the culture.     

Filter mesh size and food particle uptake by Daphnia

Food size selection of four Daphnia, species (D. magna, D. hyalina, D. galeata, D. pulicaria) was investigated using spherical plastic beads as artificial food and with small bacteria. The size of the particles ranged from 0.1 to 35 m with special emphasis to the particle diameters between 0.1 and 1 m. In one set of experiments a mixture of differently sized particles was offered as food suspension and the selectivity of filtering was determined by comparing the size spectrum of the particles found in the gut contents with the spectrum in the food suspension. In a second series of experiments suspensions of uniformly sized particles were offered to single animals and their feeding activity was observed directly. In both types of experiments the mesh sizes of the filtering apparatus of the respective animals studied were measured after the experiments by, scanning electron microscopy. The mean sizes of the filter meshes were about 0.4–0.7 m. In all experiments the size of the particles found in the gut or those which caused high feeding activities were larger than the smallest mesh sizes of the filters. As a consequence simple mechanical sieving provides a sufficient explanation for the mechanism of particle retention of the filtering process in Daphnia. D. magna was found to feed with high efficiency on suspended freshwater bacteria, the residual species investigated showed low filtering efficiencies when bacteria were offered as food.The present study was supported by Deutscher Akademischer Austauschdients     

Macroporous poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) resins—Versatile immobilization supports for biocatalysts

Crosslinked macroporous hydrophilic poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate)s [abbreviated poly(GMA-co-EGDMA)] with identical chemical structure (60% of glycidyl methacrylate) but with varied average pore sizes (from 30 to 560 nm), specific surface areas (from 13.2 to 106.0 m²/g), specific volumes (from 0.755 to 1.191 cm³/g) and particle sizes (less than 100–650 μm) were synthesized via suspension polymerization. The influence of the resin properties on the loading of Candida antarctica lipase B (Cal-B) during immobilization and on the hydrolytic (hydrolysis of para-nitrophenyl acetate) and synthetic (ring-opening polymerization of -caprolactone) activity of the immobilized Cal-B were studied. Immobilization of Cal-B was performed at different temperatures and pH values. Cal-B immobilized at 30 °C and pH 6.8 was leading to increased activities. By decreasing the resin diameter: (i) the amount of Cal-B adsorbed onto the resin decreases, (ii) the conversion of para-nitrophenyl acetate increases (hydrolytic activity) and (iii) the conversion of -caprolactone and the molecular weight of the synthesized poly--caprolactone increases (synthetic activity). Varying the porosity parameters results in different hydrolytic and synthetic activities. Pore sizes of all synthesized resins (from 30 to 560 nm) are big enough to overcome diffusion limitations. Therefore increasing the pore size of the resins resulted in a large increase in the hydrolytic and synthetic activity. Increasing the specific surface area resulted in an increase of activities, as the result of alleviated substrate approach to the immobilized enzyme zones. The obtained results were compared to results from dried Cal-B powder and Novozyme 435. Resin with particle size less than 100 μm and pore size 48 nm had much higher hydrolytic activity than both dried Cal-B powder and Novozyme 435. Nearly similar trends were observed for the synthetic activity.Via the DMSO leaching technique we could show that about 80% of Cal-B was covalently attached to the macroporous resin.     

Experimental limitations in microdosimetry measurements using the variance technique

Summary Microdosimetry measurements give information about the energy imparted to a volume of given size. With the most frequent method only data for object sizes above 0.2 µm are obtainable. Although restricted to the dose mean values, the variance technique can, however, be applied to object sizes an order of magnitude less. In this report some limiting parameters for this technique are discussed and results down to about 20 nm in a⁶⁰co-ray beam are reported. The resulting data exceed earlier reported values at object sizes below 0.1 µm, but are in good agreement for larger object sizes.     

Laser light scattering determination of size and dispersity of synaptosomes and synaptic vesicles isolated from squid (Loligo pealei) optic lobes

Quasi-elastic laser light scattering has been used to investigate the size and dispersity of synaptosomes and synaptic vesicles isolated from optic lobes of the squid Loligo pealei. Synaptosomal fractions were highly polydisperse ( ) and the mean diameter ( ) ranged from 0.5–2.0 m. Size distribution histograms yielded two major components — smaller particles ( ) and a larger group of particles ( ). The heterogeneity of the synaptosomal particles detected in solution is in agreement with published data obtained using electron microscopy. Purified synaptic vesicle fractions also yielded complex particle size distribution data. A component with a mean diameter in the range 150–250 nm was detected, though a smaller particle ( ) dominated the scattering signal. This smaller particle closely resembles in size the electron lucent vesicles seen in the majority of squid optic lobe nerve terminals when examined by electron microscopy. Osmotically-induced shirnkage and swelling of the synptosomes was detected. Depolarization by veratridine (1.0×10^–4 M) did not result in a detectable change in the size of synaptosomal particles.     

Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans

The identification of quantitative trait loci (QTLs) of small effect size that underlie complex traits poses a particular challenge for geneticists due to the large sample sizes and large numbers of genetic markers required for genomewide association scans. An efficient solution for screening purposes is to combine single nucleotide polymorphism (SNP) microarrays and DNA pooling (SNP-MaP), an approach that has been shown to be valid, reliable and accurate in deriving relative allele frequency estimates from pooled DNA for groups such as cases and controls for 10K SNP microarrays. However, in order to conduct a genomewide association study many more SNP markers are needed. To this end, we assessed the validity and reliability of the SNP-MaP method using Affymetrix GeneChip^® Mapping 100K Array set. Interpretable results emerged for 95% of the SNPs (nearly 110000 SNPs). We found that SNP-MaP allele frequency estimates correlated 0.939 with allele frequencies for 97605 SNPs that were genotyped individually in an independent population; the correlation was 0.971 for 26 SNPs that were genotyped individually for the 1028 individuals used to construct the DNA pools. We conclude that extending the SNP-MaP method to the Affymetrix GeneChip^® Mapping 100K Array set provides a useful screen of >100000 SNP markers for QTL association scans.     

Mechanisms of seed harvest by heteromyid rodents: soil texture effects on harvest rate and seed size selection

Summary Several lines of evidence show that soil texture plays an important role in the distribution of desert-dwelling heteromyid rodents. This is not surprising, since texture influences the energetic cost of digging burrows and of scratching at the soil surface to harvest buried seeds. Texture also may influence the efficiency with which seeds can be separated from the soil particles with which they are mixed. To explore mechanisms of particle separation by foraging heteromyids we measured seed harvest rates and size selection in the laboratory for a variety of seed sizes and soil textures. Harvest rate declined with increasing soil coarseness, and the preference for seeds of intermediate size that was apparent in fine soil disappeared when seeds were mixed with soil slightly coarser than the preferred seed size. In addition, there was evidence that particle separation efficiency is sensitive to the relative sizes of seeds and soil. A discontinity in the function relating harvest rate to soil texture occurred at finer soil textures for small seeds than for large seeds, suggesting that harvest techniques change once soil particle diameter equals or exceeds that of seeds. These results are consistent with the hypothesis that heteromyids use a combination of gravity-and rake-sorting mechanisms for particle separation.     

Visualizing flock house virus infection in Drosophila cells with correlated fluorescence and electron microscopy

Virus assembly occurs in a complex environment and is dependent upon viral and cellular components being properly correlated in time and space. The simplicity of the flock house virus (FHV) capsid and the extensive structural, biochemical and genetic characterization of the virus make it an excellent system for studying in vivo virus assembly. The tetracysteine motif (CCPGCC), that induces fluorescence in bound biarsenical compounds (FlAsH and ReAsH), was genetically inserted in the coat protein, to visualize this gene product during virus infection. The small size of this modification when compared to those made by traditional fluorescent proteins minimizes disruption of the coat proteins numerous functions. ReAsH not only fluoresces when bound to the tetracysteine motif but also allows correlated electron microscopy (EM) of the same cell following photoconversion and osmium staining. These studies demonstrated that the coat protein was concentrated in discrete patches in the cell. High pressure freezing (HPF) followed by freeze substitution (FS) of infected cells showed that these patches were formed by virus particles in crystalline arrays. EM tomography (EMT) of the HPF/FS prepared samples showed that these arrays were proximal to highly modified mitochondria previously established to be the site of RNA replication. Two features of the mitochondrial modification are 60 nm spherules that line the outer membrane and the large chamber created by the convolution induced in the entire organelle.     

Reproducible Clusters from Microarray Research: Whither?

Motivation

In cluster analysis, the validity of specific solutions, algorithms, and procedures present significant challenges because there is no null hypothesis to test and no 'right answer'. It has been noted that a replicable classification is not necessarily a useful one, but a useful one that characterizes some aspect of the population must be replicable. By replicable we mean reproducible across multiple samplings from the same population. Methodologists have suggested that the validity of clustering methods should be based on classifications that yield reproducible findings beyond chance levels. We used this approach to determine the performance of commonly used clustering algorithms and the degree of replicability achieved using several microarray datasets.

Methods

We considered four commonly used iterative partitioning algorithms (Self Organizing Maps (SOM), K-means, Clutsering LARge Applications (CLARA), and Fuzzy C-means) and evaluated their performances on 37 microarray datasets, with sample sizes ranging from 12 to 172. We assessed reproducibility of the clustering algorithm by measuring the strength of relationship between clustering outputs of subsamples of 37 datasets. Cluster stability was quantified using Cramer's v ² from a kXk table. Cramer's v ² is equivalent to the squared canonical correlation coefficient between two sets of nominal variables. Potential scores range from 0 to 1, with 1 denoting perfect reproducibility.

Results

All four clustering routines show increased stability with larger sample sizes. K-means and SOM showed a gradual increase in stability with increasing sample size. CLARA and Fuzzy C-means, however, yielded low stability scores until sample sizes approached 30 and then gradually increased thereafter. Average stability never exceeded 0.55 for the four clustering routines, even at a sample size of 50. These findings suggest several plausible scenarios: (1) microarray datasets lack natural clustering structure thereby producing low stability scores on all four methods; (2) the algorithms studied do not produce reliable results and/or (3) sample sizes typically used in microarray research may be too small to support derivation of reliable clustering results. Further research should be directed towards evaluating stability performances of more clustering algorithms on more datasets specially having larger sample sizes with larger numbers of clusters considered.

     

Detecting neural assemblies in calcium imaging data

Background

Activity in populations of neurons often takes the form of assemblies, where specific groups of neurons tend to activate at the same time. However, in calcium imaging data, reliably identifying these assemblies is a challenging problem, and the relative performance of different assembly-detection algorithms is unknown.

Results

To test the performance of several recently proposed assembly-detection algorithms, we first generated large surrogate datasets of calcium imaging data with predefined assembly structures and characterised the ability of the algorithms to recover known assemblies. The algorithms we tested are based on independent component analysis (ICA), principal component analysis (Promax), similarity analysis (CORE), singular value decomposition (SVD), graph theory (SGC), and frequent item set mining (FIM-X). When applied to the simulated data and tested against parameters such as array size, number of assemblies, assembly size and overlap, and signal strength, the SGC and ICA algorithms and a modified form of the Promax algorithm performed well, while PCA-Promax and FIM-X did less well, for instance, showing a strong dependence on the size of the neural array. Notably, we identified additional analyses that can improve their importance. Next, we applied the same algorithms to a dataset of activity in the zebrafish optic tectum evoked by simple visual stimuli, and found that the SGC algorithm recovered assemblies closest to the averaged responses.

Conclusions

Our findings suggest that the neural assemblies recovered from calcium imaging data can vary considerably with the choice of algorithm, but that some algorithms reliably perform better than others. This suggests that previous results using these algorithms may need to be reevaluated in this light.

     

A Multiresolution Approach to Discrete Tomography Using DART

In discrete tomography, a scanned object is assumed to consist of only a few different materials. This prior knowledge can be effectively exploited by a specialized discrete reconstruction algorithm such as the Discrete Algebraic Reconstruction Technique (DART), which is capable of providing more accurate reconstructions from limited data compared to conventional reconstruction algorithms. However, like most iterative reconstruction algorithms, DART suffers from long computation times. To increase the computational efficiency as well as the reconstruction quality of DART, a multiresolution version of DART (MDART) is proposed, in which the reconstruction starts on a coarse grid with big pixel (voxel) size. The resulting reconstruction is then resampled on a finer grid and used as an initial point for a subsequent DART reconstruction. This process continues until the target pixel size is reached. Experiments show that MDART can provide a significant speed-up, reduce missing wedge artefacts and improve feature reconstruction in the object compared with DART within the same time, making its use with large datasets more feasible.     

Hydrothermal synthesis, characterization, and KOH activation of carbon spheres from glucose

Carbon spheres (CSs) with controllable sizes and rich in oxygen-containing groups were fabricated using a simple hydrothermal treatment of glucose. The effects of the hydrothermal parameters, including the concentration of glucose, reaction temperature, duration, and the second hydrothermal treatment were investigated. The obtained CSs were then activated using KOH for the eventual preparation of porous carbon spheres. A scanning electron microscope was used to characterize the morphology and size of the CSs. Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy were used to analyze the functional surface groups. N₂ adsorption–desorption isotherms were used to analyze the porous structure of the CS. The results revealed that the morphologies and size distribution of the CSs can be controlled by adjusting the experimental parameters. A hydrothermal temperature between 180 and 190 °C over 4–5 h was suitable for CS formation. Under these conditions, the size of the CS increased with the concentration of glucose. Mono-dispersed CSs with good morphologies and large numbers of oxygen-containing functional groups (primarily –OH and CO) can be obtained using a 0.3 mol/L glucose solution that is hydrothermally treated at 190 °C for 4 h. The resulting CSs sizes were about 350 nm in diameter. After a second hydrothermal treatment, the sizes of CSs grew nearly 250 nm without damage to its morphology or broadening of their size distribution. Porous CSs with perfectly spherical shapes and fully developed structures (S_BET = 1282.8 m²/g, V_micro = 0.44 cm³/g) could then be obtained via KOH activation.     

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence–absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size ( n  < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.     

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications

Background

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly.

Methods

In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets.

Results

The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task.

Conclusions

No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

     

The influence of prey hardness on Daphnia's selectivity for large prey

Two comparable methods were used to study the feeding of four species of Daphnia on large spherical particles which differed in size and hardness. The first method used gut analysis to estimate the selectivities of daphnids feeding in a broad size range of a single particle type, including polystyrene beads (4–60 µm diameter) in the laboratory and Eudorina colonies (10–90 µm) in the field. In the second method, Daphnia of different sizes fed in a mixture of 6.5 µm Chlamydomonas and one of eight test particles. Smaller daphnids were less effective in feeding on large test particles. Nonlinear regression was therefore used to estimate the Daphnia body size at which the clearance rate on a test particle was reduced to 50% of that for Chlamydomonas. The results of both methods show that prey size and hardness are both very important in determining daphnid feeding selectivity. For a given particle size, soft algae (naked and gelatinous flagellates) are more readily ingested than hard algae (diatoms and dinoflagellates), and hard algae are more readily ingested than polystyrene beads. Daphnia can feed effectively on algae that are 2–5 times larger than the largest ingestible bead.     

Numerical treatment of two-center overlap integrals

Among the two-center integrals occurring in the molecular context, the two-center overlap integrals are numerous and difficult to evaluate to a level of high accuracy. The analytical and numerical difficulties arise mainly from the presence of the spherical Bessel integrals in the analytic expressions of these molecular integrals. Different approaches have been used to develop efficient algorithms for the numerical evaluation of the molecular integrals under consideration. These approaches are based on quadrature rules, Levin’s u transform, or the epsilon-algorithm of Wynn. In the present work, we use the nonlinear transformation of Sidi. This transformation is shown to be highly efficient in improving the convergence of highly oscillatory integrals, and it has been applied to molecular multicenter integrals, namely three-center attraction, hybrid, two-, three-, and four-center two-electron Coulomb and exchange integrals over B functions and over Slater-type functions. It is also been shown that when evaluating these molecular multicenter integrals the transformation is more efficient compared with the methods cited above. It is now proven that the integrand occurring in the analytic expression of the two-center overlap integrals satisfies all the conditions required to apply the transformation. A highly accurate algorithm based on this transformation is now developed. Special cases are presented and discussed for a better optimization of the algorithm. The numerical results section illustrates clearly the high efficiency of our algorithm.     

Numerical approximations of the mean absorption cross-section of a variety of randomly oriented microalgal shapes

The size, shape, and absorption coefficient of a microalgal cell determines, to a first order approximation, the rate at which light is absorbed by the cell. The rate of absorption determines the maximum amount of energy available for photosynthesis, and can be used to calculate the attenuation of light through the water column, including the effect of packaging pigments within discrete particles. In this paper, numerical approximations are made of the mean absorption cross-section of randomly oriented cells, . The shapes investigated are spheroids, rectangular prisms with a square base, cylinders, cones and double cones with aspect ratios of 0.25, 0.5, 1, 2, and 4. The results of the numerical simulations are fitted to a modified sigmoid curve, and take advantage of three analytical solutions. The results are presented in a non-dimensionalised format and are independent of size. A simple approximation using a rectangular hyperbolic curve is also given, and an approach for obtaining the upper and lower bounds of for more complex shapes is outlined.     

Bacterial adhesion to different termite flagellates: Ultrastructural and functional evidence for distinct molecular attachment modes

Summary The attachment modes of rodlike ectobiotic bacteria to the surface of two different termite flagellates were studied.Devescovina glabra was covered by laterally attached bacteria. Treatment with chemicals that disturb hydrophobic interactions and solubilize proteins removed the ectobionts. Freeze-fracture and freeze-etching electron microscopy revealed rows of intramembrane particles that occurred exclusively along the attachment sites. The adhering Gram-negative bacteria possessed an S-layer (surface layer) composed of globular protein particles. The S-layer could be removed by protein-solubilizing chemicals, e.g., urea, as shown by ultrathin-section electron microscopy. Therefore, it seems plausible that the attachment was mediated by hydrophobic interactions between the flagellate's plasma membrane and the S-layer of the bacteria. The bacteria of the second flagellate,Joenia annectens, adhered by their tips. The attachment was extremely strong. Chemicals disturbing ionic or hydrophobic bindings or solubilizing proteins did not detach the ectobionts. Globular intramembrane protein particles were preferentially found in a ringlike array at the external fracture face of the flagellate's contact sites.Abbreviations DIC differential interference contrast - EGTA ethylene glycol-bis(-aminoethyl ether) N,N,N,N-tetraacetic acid - TEM transmission electron microscope - Tween 20 polyoxyethylenesorbitan