Following the excited state relaxation dynamics of indole and 5-hydroxyindole using time-resolved photoelectron spectroscopy

Time-resolved photoelectron spectroscopy was used to obtain new information about the dynamics of electronic relaxation in gas-phase indole and 5-hydroxyindole following UV excitation with femtosecond laser pulses centred at 249 nm and 273 nm. Our analysis of the data was supported by ab initio calculations at the coupled cluster and complete-active-space self-consistent-field levels. The optically bright 1La and 1Lb electronic states of 1\u3c0\u3c0* character and spectroscopically dark and dissociative 1\u3c0\u3c3* states were all found to play a role in the overall relaxation process. In both molecules we conclude that the initially excited 1La state decays non-adiabatically on a sub 100 fs timescale via two competing pathways, populating either the subsequently long-lived 1Lb state or the 1\u3c0\u3c3* state localised along the N-H coordinate, which exhibits a lifetime on the order of 1 ps. In the case of 5-hydroxyindole, we conclude that the 1\u3c0\u3c3* state localised along the O-H coordinate plays little or no role in the relaxation dynamics at the two excitation wavelengths studied.Peer reviewed: YesNRC publication: Ye

Phytophthora Root Rot Resistance in Soybean E00003

Phytophthora root rot (PRR) is a devastating disease in soybean [Glycine max (L.) Merr.] production. Michigan elite soybean E00003 is resistant to Phytophthora sojae and has been used as a resistance source in breeding. Genetic control of PRR resistance in this source is unknown. To facilitate marker-assisted selection (MAS), the PRR resistance loci in E00003 and their map locations need to be determined. In this study, a genetic mapping approach was used to identify major PRR -resistant loci in E00003. The mapping population consists of 240 F4–derived lines developed by crossing E00003 with the P. sojae susceptible line PI 567543C. In 2009 and 2010, the mapping population was evaluated in the greenhouse for PRR resistance against P. sojae races 1, 4, and 7, using modified rice (Oryza sativa L.) grain inoculation method. The population was genotyped with seven simple sequence repeat (SSR) and three single nucleotide polymorphism (SNP) markers derived from bulk segregant analysis. The heritability of resistance in the population ranged from 83 to 94%. A major locus, contributing 50 to 76% of the phenotypic variation, was mapped within a 3 cM interval in the Rps1 region. The interval was further saturated with more BARCSOY SSRs and SNPs with TaqMan assays. Two SSRs and three SNPs within the Rps1k gene were highly associated with PRR resistance in the mapping population. The major resistance gene in E00003 is either allelic or tightly linked to Rps1k.The molecular markers located in the Rps1k gene can be used to improve MAS for PRR resistance

A Simplified Approach to Operational InSAR Monitoring of Volcano Deformation in Low- and Middle-Income Countries: Case Study of Rabaul Caldera, Papua New Guinea

The primary goal of operational volcano monitoring is the timely identification of volcanic unrest. This provides critical information to decision makers tasked with mitigating the societal impacts of volcanic eruptions. Volcano deformation is recognized as a key indicator of unrest at many active volcanoes and can be used to provide insight into the depth and geometry of the magma source. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique that has detected deformation at many volcanoes globally, but most often with hindsight. To date, the use of InSAR for operational volcano monitoring has been limited to a few cases and only in high income countries. Yet a vast number of active volcanoes are located in low- and middle-income countries (LMICs), where resources for operational monitoring are constrained. In these countries, InSAR could provide deformation monitoring at many active volcanoes, including those that have no existing ground monitoring infrastructure. Several barriers combine to make uptake of InSAR into operational volcano monitoring difficult in most countries, but particularly in resource-constrained environments. To overcome some of these limiting factors, we propose a simplified processing chain to better incorporate InSAR and Global Navigation Satellite Systems (GNSS) data into the decision-making process at volcano observatories. To combine the InSAR and GNSS data we use a joint modelling procedure that infers volume changes of a spherical source beneath the volcano. The benefits of our approach for operational use include that the algorithm is computationally lightweight and can be run quickly on a standard desktop or laptop PC. This enables a volcano observatory to interpret geodetic data in a timely fashion, and use the information as part of frequent reporting procedures. To demonstrate our approach we combine ALOS-PALSAR InSAR data and continuous GNSS data from the Rabaul Caldera, Papua New Guinea between 2007 and 2011. Joint inversion of the two datasets indicates volume loss of ~1 × 107 m3 (deflation) occurring between February 2008 and November 2009, followed by volume gain of ~2.5 × 106 m3 (inflation) until February 2011 in a magma body situated ~1.5 km beneath the caldera

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to provide robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. The tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation

Tissue Compartment Analysis for Biomarker Discovery by Gene Expression Profiling

BACKGROUND:Although high throughput technologies for gene profiling are reliable tools, sample/tissue heterogeneity limits their outcomes when applied to identify molecular markers. Indeed, inter-sample differences in cell composition contribute to scatter the data, preventing detection of small but relevant changes in gene expression level. To date, attempts to circumvent this difficulty were based on isolation of the different cell structures constituting biological samples. As an alternate approach, we developed a tissue compartment analysis (TCA) method to assess the cell composition of tissue samples, and applied it to standardize data and to identify biomarkers. METHODOLOGY/PRINCIPAL FINDINGS:TCA is based on the comparison of mRNA expression levels of specific markers of the different constitutive structures in pure isolated structures, on the one hand, and in the whole sample on the other. TCA method was here developed with human kidney samples, as an example of highly heterogeneous organ. It was validated by comparison of the data with those obtained by histo-morphometry. TCA demonstrated the extreme variety of composition of kidney samples, with abundance of specific structures varying from 5 to 95% of the whole sample. TCA permitted to accurately standardize gene expression level amongst >100 kidney biopsies, and to identify otherwise imperceptible molecular disease markers. CONCLUSIONS/SIGNIFICANCE:Because TCA does not require specific preparation of sample, it can be applied to all existing tissue or cDNA libraries or to published data sets, inasmuch specific operational compartments markers are available. In human, where the small size of tissue samples collected in clinical practice accounts for high structural diversity, TCA is well suited for the identification of molecular markers of diseases, and the follow up of identified markers in single patients for diagnosis/prognosis and evaluation of therapy efficiency. In laboratory animals, TCA will interestingly be applied to central nervous system where tissue heterogeneity is a limiting factor