Suitable Reference Gene Selection for Different Strains and Developmental Stages of the Carmine Spider Mite, Tetranychus cinnabarinus, using Quantitative Real-Time PCR

Reference genes are used as internal controls in gene expression studies, but their expression levels vary according to tissue types and experimental treatments. Quantitative real-time PCR (qPCR) is the most sensitive technique for transcript quantification provided that gene transcription patterns are normalized to an evaluated reference gene. In this study, the suitability of eight commonly used genes (β?-actin, 5.8SrRNA, α?-TUB, GAPDH, RPL13a, RPS18, TBP, SDHA) were cloned and investigated to find the most stable candidates for normalizing real-time PCR data generated from the four different strains (abamectin-resistant, fenpropathrin-resistant, omethoate-resistant, and susceptible strains) and different developmental stages (eggs, protonymphs, nymphs, and adults) of carmine spider mite, Tetranychus cinnabarinus (Boisduval) (Acarina: Tetranychidae). The stability of gene expression was assessed using two different analysis programs, geNorm and NormFinder. Using these analyses, RPS18 and 5.8SrRNA had the most stable expression regardless of the four different strains, whereas RPS18 and α?-TUB were expressed most stably in different developmental stages

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (Part 4): α-Chloroacetamides

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 69 α-chloroacetamide herbicides for which either Ames, chromosomal aberration or micronucleus test results are publicly available. A set of structural space alerts were defined, each linked to a key metabolic transformation present in the α-chloroacetamide metabolic space. The structural space alerts were combined with covalent chemistry profiling to develop categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data individual groups of plant protection products as the basis for the development of the structural space alerts

Intergenerational family caregiving in welfare policy context

Definition Intergenerational family caregiving refers to exchanges up and down family lines aimed at nurturing the needs of others. Caregiving is more than a task; it involves emotional and relationship work

Two birds with one stone: dual grain-boundary and interface passivation enables >22% efficient inverted methylammonium-free perovskite solar cells

Advancing inverted (p–i–n) perovskite solar cells (PSCs) is key to further enhance the power conversion efficiency (PCE) and stability of flexible and perovskite-based tandem photovoltaics. Yet, the presence of defects at grain boundaries and in particular interfacial recombination at the perovskite/electron transporting layer interface induce severe non-radiative recombination losses, limiting the open-circuit voltage (VOC) and fill factor (FF) of PSCs in this architecture. In this work, we introduce a dual passivation strategy using the long chain alkylammonium salt phenethylammonium chloride (PEACl) both as an additive and for surface treatment to simultaneously passivate the grain boundaries and the perovskite/C60 interface. Using [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz) as a hole transporting layer and a methylammonium (MA)-free Cs0.18FA0.82PbI3 perovskite absorber with a bandgap of ∼1.57 eV, prolonged charge carrier lifetime and an on average 63 meV enhanced internal quasi-Fermi level splitting are achieved upon dual passivation compared to reference p–i–n PSCs. Thereby, we achieve one of the highest PCEs for p–i–n PSCs of 22.7% (stabilized at 22.3%) by advancing simultaneously the VOC and FF up to 1.162 V and 83.2%, respectively. Using a variety of experimental techniques, we attribute the positive effects to the formation of a heterogeneous 2D Ruddlesden–Popper (PEA)2(Cs1−xFAx)n−1Pbn(I1−yCly)3n+1 phase at the grain boundaries and surface of the perovskite films. At the same time, the activation energy for ion migration is significantly increased, resulting in enhanced stability of the PSCs under light, humidity, and thermal stress. The presented dual passivation strategy highlights the importance of defect management both in the grain boundaries and the surface of the perovskite absorber layer using a proper passivation material to achieve both highly efficient and stable inverted p–i–n PSCs

Making in silico predictive models for toxicology FAIR

In silico predictive models for toxicology include quantitative structure-activity relationship (QSAR) and physiologically based kinetic (PBK) approaches to predict physico-chemical and ADME properties, toxicological effects and internal exposure. Such models are used to fill data gaps as part of chemical risk assessment. There is a growing need to ensure in silico predictive models for toxicology are available for use and reproducible. This paper describes how the FAIR (Findable, Accessible, Interoperable, Reusable) principles, developed for data sharing, have been applied to in silico predictive models. In particular, this investigation has focussed on how the FAIR principles could be applied to improved regulatory acceptance of predictions from such models. Eighteen principles have been developed that cover all aspects of FAIR. It is intended that FAIRification of in silico predictive models for toxicology will increase their use and acceptance

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization

Background RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts. Results Using the Genevestigator database of normalized and well-annotated microarray experiments, we describe the expression stability characteristics of the transciptomes of several organisms. The results show that a) no genes are universally stable, b) most commonly used reference genes yield very high transcript abundances as compared to the entire transcriptome, and c) for each biological context a subset of stable genes exists that has smaller variance than commonly used reference genes or genes that were selected for their stability across all conditions. Conclusion We therefore propose the normalization of RT-qPCR data using reference genes that are specifically chosen for the conditions under study. RefGenes is a community tool developed for that purpose. Validation RT-qPCR experiments across several organisms showed that the candidates proposed by RefGenes generally outperformed commonly used reference genes. RefGenes is available within Genevestigator at http://www.genevestigator.com

Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1)

Magic-angle spinning solid-state NMR (MAS SSNMR) represents a fast developing experimental technique with great potential to provide structural and dynamics information for proteins not amenable to other methods. However, few automated analysis tools are currently available for MAS SSNMR. We present a methodology for automating protein resonance assignments of MAS SSNMR spectral data and its application to experimental peak lists of the β1 immunoglobulin binding domain of protein G (GB1) derived from a uniformly 13C- and 15N-labeled sample. This application to the 56 amino acid GB1 produced an overall 84.1% assignment of the N, CO, CA, and CB resonances with no errors using peak lists from NCACX 3D, CANcoCA 3D, and CANCOCX 4D experiments. This proof of concept demonstrates the tractability of this problem

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio