Distinction of subtype-specific antibodies against European porcine influenza viruses by indirect ELISA based on recombinant hemagglutinin protein fragment-1

BACKGROUND: Serological investigations of swine influenza virus infections and epidemiological conclusions thereof are challenging due to the complex and regionally variable pattern of co-circulating viral subtypes and lineages and varying vaccination regimes. Detection of subtype-specific antibodies currently depends on hemagglutination inhibition (HI) assays which are difficult to standardize and unsuitable for large scale investigations. METHODS: The nucleocapsid protein (NP) and HA1 fragments of the hemagglutinin protein (HA) of five different lineages (H1N1av, H1N1pdm, H1pdmN2, H1N2, H3N2) of swine influenza viruses were bacterially expressed and used as diagnostic antigens in indirect ELISA. RESULTS: Proteins were co-translationally mono-biotinylated and refolded in vitro into an antigenically authentic conformation. Western blotting and indirect ELISA revealed highly subtype-specific antigenic characteristics of the recombinant HA1 proteins although some cross reactivity especially among antigens of the H1 subtype were evident. Discrimination of antibodies directed against four swine influenza virus subtypes co-circulating in Germany was feasible using the indirect ELISA format. CONCLUSIONS: Bacterially expressed recombinant NP and HA1 swine influenza virus proteins served as antigens in indirect ELISAs and provided an alternative to commercial blocking NP ELISA and HI assays concerning generic (NP-specific) and HA subtype-specific sero-diagnostics, respectively, on a herd basis

Rapid detection and subtyping of European swine influenza viruses in porcine clinical samples by haemagglutinin- and neuraminidase-specific tetra- and triplex real-time RT-PCRs

BACKGROUND: A diversifying pool of mammalian‐adapted influenza A viruses (IAV) with largely unknown zoonotic potential is maintained in domestic swine populations worldwide. The most recent human influenza pandemic in 2009 was caused by a virus with genes originating from IAV isolated from swine. Swine influenza viruses (SIV) are widespread in European domestic pig populations and evolve dynamically. Knowledge regarding occurrence, spread and evolution of potentially zoonotic SIV in Europe is poorly understood. OBJECTIVES: Efficient SIV surveillance programmes depend on sensitive and specific diagnostic methods which allow for cost‐effective large‐scale analysis. METHODS: New SIV haemagglutinin (HA) and neuraminidase (NA) subtype‐ and lineage‐specific multiplex real‐time RT‐PCRs (RT‐qPCR) have been developed and validated with reference virus isolates and clinical samples. RESULTS: A diagnostic algorithm is proposed for the combined detection in clinical samples and subtyping of SIV strains currently circulating in Europe that is based on a generic, M‐gene‐specific influenza A virus RT‐qPCR. In a second step, positive samples are examined by tetraplex HA‐ and triplex NA‐specific RT‐qPCRs to differentiate the porcine subtypes H1, H3, N1 and N2. Within the HA subtype H1, lineages “av” (European avian‐derived), “hu” (European human‐derived) and “pdm” (human pandemic A/H1N1, 2009) are distinguished by RT‐qPCRs, and within the NA subtype N1, lineage “pdm” is differentiated. An RT‐PCR amplicon Sanger sequencing method of small fragments of the HA and NA genes is also proposed to safeguard against failure of multiplex RT‐qPCR subtyping. CONCLUSIONS: These new multiplex RT‐qPCR assays provide adequate tools for sustained SIV monitoring programmes in Europe

Uncovering cis Regulatory Codes Using Synthetic Promoter Shuffling

Revealing the spectrum of combinatorial regulation of transcription at individual promoters is essential for understanding the complex structure of biological networks. However, the computations represented by the integration of various molecular signals at complex promoters are difficult to decipher in the absence of simple cis regulatory codes. Here we synthetically shuffle the regulatory architecture — operator sequences binding activators and repressors — of a canonical bacterial promoter. The resulting library of complex promoters allows for rapid exploration of promoter encoded logic regulation. Among all possible logic functions, NOR and ANDN promoter encoded logics predominate. A simple transcriptional cis regulatory code determines both logics, establishing a straightforward map between promoter structure and logic phenotype. The regulatory code is determined solely by the type of transcriptional regulation combinations: two repressors generate a NOR: NOT (a OR b) whereas a repressor and an activator generate an ANDN: a AND NOT b. Three-input versions of both logics, having an additional repressor as an input, are also present in the library. The resulting complex promoters cover a wide dynamic range of transcriptional strengths. Synthetic promoter shuffling represents a fast and efficient method for exploring the spectrum of complex regulatory functions that can be encoded by complex promoters. From an engineering point of view, synthetic promoter shuffling enables the experimental testing of the functional properties of complex promoters that cannot necessarily be inferred ab initio from the known properties of the individual genetic components. Synthetic promoter shuffling may provide a useful experimental tool for studying naturally occurring promoter shuffling

An assessment of how bio-E10 will impact the vehicle-related ozone contamination in China

Bio-E10 is short for the biofuel made up of 90% gasoline in volume and 10% bio-ethanol, which is the ethanol made from commercially-grown crops such as corn and wheat by the sugar fermentation process. In China, bio-E10 will be supplied nationwide from 2020 as an alternative to conventional gasoline, aiming at ensuring greater energy security and lowering the greenhouse gas emissions. In order to assess the impacts of the upcoming bio-E10 application on the ozone forming potential (OFP) of the emissions from in-use vehicles, this paper examined the carbonyls and volatile organic compounds (VOCs) in the evaporative and tailpipe emissions of three China-4 certified in-use vehicles fueled with a market-available gasoline and two match-blend bio-E10s, and calculated their OFPs using the Maximum Incremental Reactivity (MIR) method. The results revealed that for the evaporative emissions, the use of bio-E10s increased the carbonyl and VOC emissions released within the diurnal-loss stage by 8.5–17.6% and 11.1–78.6% respectively, but decreased the carbonyl and VOC emissions in the hot-soak stage by 47.4%–61.5% and 4.8%–20.6% respectively. Regarding the tailpipe emissions, in comparison to the gasoline baseline, burning bio-E10s increased the carbonyls by 15%–46% while reducing the VOCs by 37%–56% over the New European Driving Cycle (NEDC). Reductions in the tailpipe OFPs up to 47.3% were seen with the application of the bio-E10s, however, there were no clear conclusions with respect to the evaporative OFPs, which varied from −15% to ＋25% compared to the gasoline baseline. Based on the test results and census data, the application of bio-E10 in China is shown to help remove part of ozone contamination from the in-use vehicle sector

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

2:1 Multiplexing Function in a Simple Molecular System

1-[(Anthracen-9-yl)methylene] thiosemicarbazide shows weak fluorescence due to a photo-induced electron transfer (PET) process from the thiosemicarbazide moiety to the excited anthracene. The anthracene emission can be recovered via protonation of the amine as the protonated aminomethylene as an electron-withdrawing group that suppresses the PET process. Similarly, chelation between the ligand and the metal ions can also suppress the PET process and results in a fluorescence enhancement (CHEF). When solvents are introduced as the third control, a molecular 2:1 multiplexer is constructed to report selectively the inputs. Therefore, a molecular 2:1 multiplexer is realized in a simple molecular system

Molecular decoding using luminescence from an entangled porous framework

Chemosensors detect a single target molecule from among several molecules, but cannot differentiate targets from one another. In this study, we report a molecular decoding strategy in which a single host domain accommodates a class of molecules and distinguishes between them with a corresponding readout. We synthesized the decoding host by embedding naphthalenediimide into the scaffold of an entangled porous framework that exhibited structural dynamics due to the dislocation of two chemically non-interconnected frameworks. An intense turn-on emission was observed on incorporation of a class of aromatic compounds, and the resulting luminescent colour was dependent on the chemical substituent of the aromatic guest. This unprecedented chemoresponsive, multicolour luminescence originates from an enhanced naphthalenediimide–aromatic guest interaction because of the induced-fit structural transformation of the entangled framework. We demonstrate that the cooperative structural transition in mesoscopic crystal domains results in a nonlinear sensor response to the guest concentration

Improving the ability of ED physicians to identify subclinical/electrographic seizures on EEG after a brief training module

Background: Approximately 5% of emergency department (ED) patients with altered mental status (AMS) have non-convulsive seizures (NCS). Patients with NCS should be diagnosed with EEG as soon as possible to initiate antiepileptic treatment. Since ED physicians encounter such patients first in the ED, they should be familiar with general EEG principles as well as the EEG patterns of NCS/NCSE. We evaluated the utility of a brief training module in enhancing the ED physicians’ ability to identify seizures on EEG. Methods: This was a randomized controlled trial conducted in three academic institutions. A slide presentation was developed describing the basic principles of EEG including EEG recording techniques, followed by characteristics of normal and abnormal patterns, the goal of which was to familiarize the participants with EEG seizure patterns. We enrolled board-certified emergency medicine physicians into the trial. Subjects were randomized to control or intervention groups. Participants allocated to the intervention group received a self-learning training module and were asked to take a quiz of EEG snapshots after reviewing the presentation, while the control group took the quiz without the training. Results: A total of 30 emergency physicians were enrolled (10 per site, with 15 controls and 15 interventions). Participants were 52% male with median years of practice of 9.5 years (3, 14). The percentage of correct answers in the intervention group (65%, 63% and 75%) was significantly different (p = 0.002) from that of control group (50%, 45% and 60%). Conclusions: A brief self-learning training module improved the ability of emergency physicians in identifying EEG seizure patterns