Multi-planet extrasolar systems - detection and dynamics

20 years after the discovery of the first planets outside our solar system, the current exoplanetary population includes more than 700 confirmed planets around main sequence stars. Approximately 50% belong to multiple-planet systems in very diverse dynamical configurations, from two-planet hierarchical systems to multiple resonances that could only have been attained as the consequence of a smooth large-scale orbital migration. The first part of this paper reviews the main detection techniques employed for the detection and orbital characterization of multiple-planet systems, from the (now) classical radial velocity (RV) method to the use of transit time variations (TTV) for the identification of additional planetary bodies orbiting the same star. In the second part we discuss the dynamical evolution of multi-planet systems due to their mutual gravitational interactions. We analyze possible modes of motion for hierarchical, secular or resonant configurations, and what stability criteria can be defined in each case. In some cases, the dynamics can be well approximated by simple analytical expressions for the Hamiltonian function, while other configurations can only be studied with semi-analytical or numerical tools. In particular, we show how mean-motion resonances can generate complex structures in the phase space where different libration islands and circulation domains are separated by chaotic layers. In all cases we use real exoplanetary systems as working examples.

Molecular detection of in-vivo microbial contamination of metallic orthodontic brackets by checkerboard DNA-DNA hybridization

Introduction: Knowing the microbiota that colonizes orthodontic appliances is important for planning strategies and implementing specific preventive measures during treatment. The purpose of this clinical trial was to evaluate in vivo the contamination of metallic orthodontic brackets with 40 DNA probes for different bacterial species by using the checkerboard DNA-DNA hybridization (CDDH) technique. Methods: Eighteen patients, 11 to 29 years of age having fixed orthodontic treatment, were enrolled in the study. Each subject had 2 new metallic brackets bonded to different premolars in a randomized manner. After 30 days, the brackets were removed and processed for analysis by CDDH. Data on bacterial contamination were analyzed descriptively and with the Kruskal-Wallis and Dunn post tests (alpha = 0.05). Forty microbial species (cariogenic microorganisms, bacteria of the purple, yellow, green, orange complexes, "red complex + Treponema socranskii," and the cluster of Actinomyces) were assessed. Results: Most bacterial species were present in all subjects, except for Streptococcus constellatus, Campylobacter rectus, Tannerella forsythia, T socranskii, and Lactobacillus acidophillus (94.4%), Propionibacterium acnes I and Eubacterium nodatum (88.9%), and Treponema denticola (77.8%). Among the cariogenic microorganisms, Streptococcus mutans and Streptococcus sobrinus were found in larger numbers than L acidophillus and Lactobacillus casei (P < 0.001). The periodontal pathogens of the orange complex were detected in larger numbers than those of the "red complex + T socranskii" (P < 0.0001). Among the bacteria not associated with specific pathologies, Veillonella parvula (purple complex) was the most frequently detected strain (P < 0.0001). The numbers of yellow and green complex bacteria and the cluster of Actinomyces were similar (P > 0.05). Conclusions: Metallic brackets in use for 1 month were multi-colonized by several bacterial species, including cariogenic microorganisms and periodontal pathogens, reinforcing the need for meticulous oral hygiene and additional preventive measures to maintain oral health in orthodontic patients. (Am J Orthod Dentofacial Orthop 2012;141:24-9)

Electrochemical detection of carbamate pesticides in fruit and vegetables with a biosensor based on acetylcholinesterase immobilised on a composite of polyaniline-carbon nanotubes

A sensitive electrochemical acetylcholinesterase (AChE) biosensor was successfully developed on polyaniline (PANI) and multi-walled carbon nanotubes (MWCNTs) core-shell modified glassy carbon electrode (GC), and used to detect carbamate pesticides in fruit and vegetables (apple, broccoli and cabbage). The pesticide biosensors were applied in the detection of carbaryl and methomyl pesticides in food samples using chronoamperometry (CA). The GC/MWCNT/PANI/AChE biosensor exhibited detection limits of 1.4 and 0.95 mu mol L-1, respectively, for carbaryl and methomyl. These detection limits were below the allowable concentrations set by Brazilian regulation standards for the samples in which these pesticides were analysed. Reproducibility and repeatability values of 2.6% and 3.2%, respectively, were obtained in the conventional procedure. The proposed biosensor was successfully applied in the determination of carbamate pesticides in cabbage, broccoli and apple samples without any spiking procedure. The obtained results were in full agreement with those from the HPLC procedure. (C) 2012 Elsevier Ltd. All rights reserved.

Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Multi-molecular markers and metals as tracers of organic matter inputs and contamination status from an Environmental Protection Area in the SW Atlantic (Laranjeiras Bay, Brazil)

The sources and concentrations of aliphatic hydrocarbons (AHs) and polycyclic aromatic hydrocarbons (PAHs), faecal and biogenic sterols, and trace metals at 10 sampling sites located in Laranjeiras Bay, a large Environmental Protection Area in the southern Atlantic region of Brazil, were determined to assess the sources of organic matter and the contamination status of estuarine sediments. Organic compounds were determined by GC-FID and GC-MS, and ICP-OES was used to evaluate trace metals. The total AHs concentration ranged from 0.28 to 8.19 mu g g(-1), and n-C-29 and n-C-31 alkanes were predominant, indicating significant inputs from higher terrestrial plants. Unresolved complex mixtures (UCM) were not detected at any site, suggesting that the study area was not significantly contaminated by fossil fuels. The total PAH concentration varied from 3.85 to 89.2 ng g(-1). The ratio between selected PAH isomers showed that combustion of biomass, coal, and petroleum is the rnain source of PAHs in the study area. The concentrations of the faecal sterols coprostanol and epicoprostanol were below the detection limits, suggesting that sewage was not a significant contributor to sedimentary organic matter. The concentrations of the trace metals (As, Cr, Cu, Ni, Pb and Zn) were low, except near sites located at the mouths of rivers that discharge into the study area and near urbanised regions (Paranagua city and the adjoining harbour). In general, the concentrations of PAHs were below the threshold effect concentrations (TEL) levels. Although the As, Cr and Ni concentrations were above the TEL levels, the study area can be considered as preserved from human activities.

Effects of Continuous Erythropoietin Receptor Activator in Sepsis-Induced Acute Kidney Injury and Multi-Organ Dysfunction

Background: Despite advances in supportive care, sepsis-related mortality remains high, especially in patients with acute kidney injury (AKI). Erythropoietin can protect organs against ischemia and sepsis. This effect has been linked to activation of intracellular survival pathways, although the mechanism remains unclear. Continuous erythropoietin receptor activator (CERA) is an erythropoietin with a unique pharmacologic profile and long half-life. We hypothesized that pretreatment with CERA would be renoprotective in the cecal ligation and puncture (CLP) model of sepsis-induced AKI. Methods: Rats were randomized into three groups: control; CLP; and CLP+CERA (5 mu g/kg body weight, i.p. administered 24 h before CLP). At 24 hours after CLP, we measured creatinine clearance, biochemical variables, and hemodynamic parameters. In kidney tissue, we performed immunoblotting-to quantify expression of the Na-K-2Cl cotransporter (NKCC2), aquaporin 2 (AQP2), Toll-like receptor 4 (TLR4), erythropoietin receptor (EpoR), and nuclear factor kappa B (NF-kappa B)-and immunohistochemical staining for CD68 (macrophage infiltration). Plasma interleukin (IL)-2, IL-1 beta, IL-6, IL-10, interferon gamma, and tumor necrosis factor alpha were measured by multiplex detection. Results: Pretreatment with CERA preserved creatinine clearance and tubular function, as well as the expression of NKCC2 and AQP2. In addition, CERA maintained plasma lactate at normal levels, as well as preserving plasma levels of transaminases and lactate dehydrogenase. Renal expression of TLR4 and NF-kappa B was lower in CLP+CERA rats than in CLP rats (p<0.05 and p<0.01, respectively), as were CD68-positive cell counts (p<0.01), whereas renal EpoR expression was higher (p<0.05). Plasma levels of all measured cytokines were lower in CLP+CERA rats than in CLP rats. Conclusion: CERA protects against sepsis-induced AKI. This protective effect is, in part, attributable to suppression of the inflammatory response.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.