Dynamics of driven three-dimensional thin films: from hdrophilic to superhydrophobic substrates

We study the forced displacement of a thin film of fluid in contact with vertical and inclined substrates of different wetting properties, that range from hydrophilic to hydrophobic, using the lattice-Boltzmann method. We study the stability and pattern formation of the contact line in the hydrophilic and superhydrophobic regimes, which correspond to wedge-shaped and nose-shaped fronts, respectively. We find that contact lines are considerably more stable for hydrophilic substrates and small inclination angles. The qualitative behavior of the front in the linear regime remains independent of the wetting properties of the substrate as a single dispersion relation describes the stability of both wedges and noses. Nonlinear patterns show a clear dependence on wetting properties and substrate inclination angle. The effect is quantified in terms of the pattern growth rate, which vanishes for the sawtooth pattern and is finite for the finger pattern. Sawtooth shaped patterns are observed for hydrophilic substrates and low inclination angles, while finger-shaped patterns arise for hydrophobic substrates and large inclination angles. Finger dynamics show a transient in which neighboring fingers interact, followed by a steady state where each finger grows independently.

Comparative genomic analysis of the odorant-binding protein family in 12 Drosophila genomes: purifying selection and birth-and-death evolution

Background: Chemoreception is a widespread mechanism that is involved in critical biologic processes, including individual and social behavior. The insect peripheral olfactory system comprises three major multigene families: the olfactory receptor (Or), the gustatory receptor (Gr), and the odorant-binding protein (OBP) families. Members of the latter family establish the first contact with the odorants, and thus constitute the first step in the chemosensory transduction pathway.Results: Comparative analysis of the OBP family in 12 Drosophila genomes allowed the identification of 595 genes that encode putative functional and nonfunctional members in extant species, with 43 gene gains and 28 gene losses (15 deletions and 13 pseudogenization events). The evolution of this family shows tandem gene duplication events, progressive divergence in DNA and amino acid sequence, and prevalence of pseudogenization events in external branches of the phylogenetic tree. We observed that the OBP arrangement in clusters is maintained across the Drosophila species and that purifying selection governs the evolution of the family; nevertheless, OBP genes differ in their functional constraints levels. Finally, we detect that the OBP repertoire evolves more rapidly in the specialist lineages of the Drosophila melanogaster group (D. sechellia and D. erecta) than in their closest generalists.Conclusion: Overall, the evolution of the OBP multigene family is consistent with the birth-and-death model. We also found that members of this family exhibit different functional constraints, which is indicative of some functional divergence, and that they might be involved in some of the specialization processes that occurred through the diversification of the Drosophila genus.

An adaptive multiscale method for density-driven instabilities

Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Evaluating the Effectiveness of Red Light Running Camera Enforcement in Cedar Rapids and Developing Guidelines for Selection and Use of Red Light Running Countermeasures Final Report, November 2011

Red light running (RLR) is a problem in the US that has resulted in 165,000 injuries and 907 fatalities annually. In Iowa, RLR-related crashes make up 24.5 percent of all crashes and account for 31.7 percent of fatal and major injury crashes at signalized intersections. RLR crashes are a safety concern due to the increased likelihood of injury compared to other types of crashes. One tool used to combat red light running is automated enforcement in the form of RLR cameras. Automated enforcement, while effective, is often controversial. Cedar Rapids, Iowa installed RLR and speeding cameras at seven intersections across the city. The intersections were chosen based on crash rates and whether cameras could feasibly be placed at the intersection approaches. The cameras were placed starting in February 2010 with the last one becoming operational in December 2010. An analysis of the effect of the cameras on safety at these intersections was determined prudent in helping to justify the installation and effectiveness of the cameras. The objective of this research was to assess the safety effectiveness of the RLR program that has been implemented in Cedar Rapids. This was accomplished by analyzing data to determine changes in the following metrics:  Reductions in red light violation rates based on overall changes, time of day changes, and changes by lane  Effectiveness of the cameras over time  Time in which those running the red light enter the intersection  Changes in the average headway between vehicles entering the intersection

Inference of chromosomal inversion dynamics from Pool-Seq data in natural and laboratory populations of Drosophila melanogaster.

Sequencing of pools of individuals (Pool-Seq) represents a reliable and cost-effective approach for estimating genome-wide SNP and transposable element insertion frequencies. However, Pool-Seq does not provide direct information on haplotypes so that, for example, obtaining inversion frequencies has not been possible until now. Here, we have developed a new set of diagnostic marker SNPs for seven cosmopolitan inversions in Drosophila melanogaster that can be used to infer inversion frequencies from Pool-Seq data. We applied our novel marker set to Pool-Seq data from an experimental evolution study and from North American and Australian latitudinal clines. In the experimental evolution data, we find evidence that positive selection has driven the frequencies of In(3R)C and In(3R)Mo to increase over time. In the clinal data, we confirm the existence of frequency clines for In(2L)t, In(3L)P and In(3R)Payne in both North America and Australia and detect a previously unknown latitudinal cline for In(3R)Mo in North America. The inversion markers developed here provide a versatile and robust tool for characterizing inversion frequencies and their dynamics in Pool-Seq data from diverse D. melanogaster populations.

Low Water Stream Crossing: Design and Construction Recommendations; A Selection and Design Guide, February 2003

Most Iowa counties maintain low volume roads with at least one bridge or culvert that is structurally deficient or obsolete. In some counties the percentage of deficient drainage structures may be as high as 62%. Replacement with structures of similar size would require large capital expenditures that many counties cannot afford. Low water stream crossings (LWSCs) may be an acceptable lowcost alternative in some cases.

Automatic selection of tidal volume, respiratory frequency and minute ventilation in intubated ICU patients as start up procedure for closed-loop controlled ventilation.

OBJECTIVE: Before a patient can be connected to a mechanical ventilator, the controls of the apparatus need to be set up appropriately. Today, this is done by the intensive care professional. With the advent of closed loop controlled mechanical ventilation, methods will be needed to select appropriate start up settings automatically. The objective of our study was to test such a computerized method which could eventually be used as a start-up procedure (first 5-10 minutes of ventilation) for closed-loop controlled ventilation. DESIGN: Prospective Study. SETTINGS: ICU's in two adult and one children's hospital. PATIENTS: 25 critically ill adult patients (age > or = 15 y) and 17 critically ill children selected at random were studied. INTERVENTIONS: To stimulate 'initial connection', the patients were disconnected from their ventilator and transiently connected to a modified Hamilton AMADEUS ventilator for maximally one minute. During that time they were ventilated with a fixed and standardized breath pattern (Test Breaths) based on pressure controlled synchronized intermittent mandatory ventilation (PCSIMV). MEASUREMENTS AND MAIN RESULTS: Measurements of airway flow, airway pressure and instantaneous CO2 concentration using a mainstream CO2 analyzer were made at the mouth during application of the Test-Breaths. Test-Breaths were analyzed in terms of tidal volume, expiratory time constant and series dead space. Using this data an initial ventilation pattern consisting of respiratory frequency and tidal volume was calculated. This ventilation pattern was compared to the one measured prior to the onset of the study using a two-tailed paired t-test. Additionally, it was compared to a conventional method for setting up ventilators. The computer-proposed ventilation pattern did not differ significantly from the actual pattern (p > 0.05), while the conventional method did. However the scatter was large and in 6 cases deviations in the minute ventilation of more than 50% were observed. CONCLUSIONS: The analysis of standardized Test Breaths allows automatic determination of an initial ventilation pattern for intubated ICU patients. While this pattern does not seem to be superior to the one chosen by the conventional method, it is derived fully automatically and without need for manual patient data entry such as weight or height. This makes the method potentially useful as a start up procedure for closed-loop controlled ventilation.

The Effect of Inoculum Size on Selection of In Vitro Resistance to Vancomycin, Daptomycin, and Linezolid in Methicillin-Resistant Staphylococcus aureus.

OBJECTIVES: The inoculum effect (IE) is an increase in the minimum inhibitory concentration (MIC) at high bacterial densities. The effect of three inoculum sizes on the selection of resistance to vancomycin, daptomycin, and linezolid was investigated in methicillin-resistant Staphylococcus aureus (MRSA). METHODS: Low (10(4) CFU/ml), medium (10(6) CFU/ml), and high (10(8) CFU/ml) inocula of MRSA were exposed to twofold increasing concentrations of either drug during 15 days of cycling. MICs for low (MICL), medium (MICM), and high (MICH) inocula were determined daily. Conventional MICs were measured at days 1, 5, 10, and 15. Experiments were performed in triplicate. RESULTS: At the beginning of the experiment a small IE was observed for vancomycin (MICL=1 μg/ml, MICM=1-2 μg/ml, and MICH=2 μg/ml) and a significant IE for daptomycin (MICL=0.25 μg/ml, MICM=0.25-0.5 μg/ml, and MICH=2 μg/ml). Linezolid exhibited no IE at low and medium inocula (MICL=1 μg/ml and MICM=1-2 μg/ml), but with the high inoculum, concentrations up to 2,048 μg/ml did not fully inhibit visual growth. During cycling, increase of MIC was observed for all antibiotics. At day 15, MICL, MICM, and MICH of vancomycin were 2-4, 4-8, and 4-16 μg/ml and of daptomycin were 0.5-2, 8-128, and 64-256 μg/ml, respectively. MICL and MICM of linezolid were 1 and 2-4 μg/ml, respectively. Conventional MICs showed vancomycin and daptomycin selection of resistance since day 5 depending on the inocula. No selection of linezolid resistance was observed. CONCLUSIONS: Our results showed the importance of the inoculum size in the development of resistance. Measures aimed at lowering the inoculum at the site of infection should be used whenever possible in parallel to antimicrobial therapy.

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10(-12)). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the 'intermediate phenotype' nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host-pathogen interaction. DOI:http://dx.doi.org/10.7554/eLife.01123.001.

Autoreactive T cells bypass negative selection and respond to self-antigen stimulation during infection.

Central and peripheral tolerance prevent autoimmunity by deleting the most aggressive CD8(+) T cells but they spare cells that react weakly to tissue-restricted antigen (TRA). To reveal the functional characteristics of these spared cells, we generated a transgenic mouse expressing the TCR of a TRA-specific T cell that had escaped negative selection. Interestingly, the isolated TCR matches the affinity/avidity threshold for negatively selecting T cells, and when developing transgenic cells are exposed to their TRA in the thymus, only a fraction of them are eliminated but significant numbers enter the periphery. In contrast to high avidity cells, low avidity T cells persist in the antigen-positive periphery with no signs of anergy, unresponsiveness, or prior activation. Upon activation during an infection they cause autoimmunity and form memory cells. Unexpectedly, peptide ligands that are weaker in stimulating the transgenic T cells than the thymic threshold ligand also induce profound activation in the periphery. Thus, the peripheral T cell activation threshold during an infection is below that of negative selection for TRA. These results demonstrate the existence of a level of self-reactivity to TRA to which the thymus confers no protection and illustrate that organ damage can occur without genetic predisposition to autoimmunity.

Fine-Tuning Translation Kinetics Selection as the Driving Force of Codon Usage Bias in the Hepatitis A Virus Capsid

Hepatitis A virus (HAV), the prototype of genus Hepatovirus, has several unique biological characteristics that distinguish it from other members of the Picornaviridae family. Among these, the need for an intact eIF4G factor for the initiation of translation results in an inability to shut down host protein synthesis by a mechanism similar to that of other picornaviruses. Consequently, HAV must inefficiently compete for the cellular translational machinery and this may explain its poor growth in cell culture. In this context of virus/cell competition, HAV has strategically adopted a naturally highly deoptimized codon usage with respect to that of its cellular host. With the aim to optimize its codon usage the virus was adapted to propagate in cells with impaired protein synthesis, in order to make tRNA pools more available for the virus. A significant loss of fitness was the immediate response to the adaptation process that was, however, later on recovered and more associated to a re-deoptimization rather than to an optimization of the codon usage specifically in the capsid coding region. These results exclude translation selection and instead suggest fine-tuning translation kinetics selection as the underlying mechanism of the codon usage bias in this specific genome region. Additionally, the results provide clear evidence of the Red Queen dynamics of evolution since the virus has very much evolved to re-adapt its codon usage to the environmental cellular changing conditions in order to recover the original fitness.

Plants respond to pathogen infection by enhancing the antifungal gene expression of root-associated bacteria.

Plant health and fitness widely depend on interactions with soil microorganisms. Some bacteria such as pseudomonads can inhibit pathogens by producing antibiotics, and controlling these bacteria could help improve plant fitness. In the present study, we tested whether plants induce changes in the antifungal activity of root-associated bacteria as a response to root pathogens. We grew barley plants in a split-root system with one side of the root system challenged by the pathogen Pythium ultimum and the other side inoculated with the biocontrol strain Pseudomonas fluorescens CHA0. We used reporter genes to follow the expression of ribosomal RNA indicative of the metabolic state and of the gene phlA, required for production of 2,4-diacetylphloroglucinol, a key component of antifungal activity. Infection increased the expression of the antifungal gene phlA. No contact with the pathogen was required, indicating that barley influenced gene expression by the bacteria in a systemic way. This effect relied on increased exudation of diffusible molecules increasing phlA expression, suggesting that communication with rhizosphere bacteria is part of the pathogen response of plants. Tripartite interactions among plants, pathogens, and bacteria appear as a novel determinant of plant response to root pathogens.

Mean first-passage time of continuous non-Markovian processes driven by colored noise

An equation for mean first-passage times of non-Markovian processes driven by colored noise is derived through an appropriate backward integro-differential equation. The equation is solved in a Bourret-like approximation. In a weak-noise bistable situation, non-Markovian effects are taken into account by an effective diffusion coefficient. In this situation, our results compare satisfactorily with other approaches and experimental data.

Mutations in penicillin-binding protein (PBP) genes and in non-PBP genes during selection of penicillin-resistant Streptococcus gordonii.

Penicillin resistance in Streptococcus spp. involves multiple mutations in both penicillin-binding proteins (PBPs) and non-PBP genes. Here, we studied the development of penicillin resistance in the oral commensal Streptococcus gordonii. Cyclic exposure of bacteria to twofold-increasing penicillin concentrations selected for a progressive 250- to 500-fold MIC increase (from 0.008 to between 2 and 4 microg/ml). The major MIC increase (> or = 35-fold) was related to non-PBP mutations, whereas PBP mutations accounted only for a 4- to 8-fold additional increase. PBP mutations occurred in class B PBPs 2X and 2B, which carry a transpeptidase domain, but not in class A PBP 1A, 1B, or 2A, which carry an additional transglycosylase domain. Therefore, we tested whether inactivation of class A PBPs affected resistance development in spite of the absence of mutations. Deletion of PBP 1A or 2A profoundly slowed down resistance development but only moderately affected resistance in already highly resistant mutants (MIC = 2 to 4 microg/ml). Thus, class A PBPs might facilitate early development of resistance by stabilizing penicillin-altered peptidoglycan via transglycosylation, whereas they might be less indispensable in highly resistant mutants which have reestablished a penicillin-insensitive cell wall-building machinery. The contribution of PBP and non-PBP mutations alone could be individualized in DNA transformation. Both PBP and non-PBP mutations conferred some level of intrinsic resistance, but combining the mutations synergized them to ensure high-level resistance (> or = 2 microg/ml). The results underline the complexity of penicillin resistance development and suggest that inhibition of transglycosylase might be an as yet underestimated way to interfere with early resistance development.