COMPARING GC×GC-TOFMS-BASED METABOLOMIC PROFILING AND WOOD ANATOMY FOR FORENSIC IDENTIFICATION OF FIVE MELIACEAE (MAHOGANY) SPECIES

Illegal logging and associated trade have increased worldwide. Such environmental crimes represent a major threat to forest ecosystems and society, causing distortions in market prices, economic instability, ecological deterioration, and poverty. To prevent illegal imports of forest products, there is a need to develop wood identification methods for identifying tree species regulated by the Convention on International Trade in Species of Wild Fauna andFlora in Trade (CITES) and other look-alike species. In this exploratory study, we applied metabolomic profiling of five species (Swietenia mahagoni, Swietenia macrophylla, Cedrela odorata, Khaya ivorensis, and Toona ciliata) using two-dimensional gas chromatog- raphy combined with time-of-flight mass spectrometry (GC3GC-TOFMS). We also performed qualitative, quantitative (based on the measurement of vessel area, tangential vessel lumina diameter,vessel element length, ray height, and ray width), and machine-vision aided (XyloTron) wood anatomy on a subsample of wood specimens to explore thepotential and limits of each approach. Fifty dried xylaria wood specimens were ground, extracted with methanol, and subsequently analyzed by GC3GC-TOFMS. In this study, the four genera could easily be identified using qualitative wood anatomy and chemical profiling. At the spe- cies level, Swietenia macrophylla and Swietenia mahagoni specimens were found to share many major metabolites and could only be differentiated after feature selection guided by cluster resolution (FS-CR) and visualization using Principal Component Analysis (PCA). Expectedly, specimens from the two Swiete- nia spp. could not be distinguished based on qualitative wood anatomy. However, significant differences in quantitative anatomical features were obtained for these two species. Excluding T. ciliata that was not included in the reference database of end grain images at the time of testing (2021), the XyloTron could successfully identify the majority of the specimens to the right genus and 50% of the specimens to the right species. The machine-vision tool was particularly successful at identifying Cedrela odorata samples, where all samples were correctly identified. Despite the limited number of specimens available for thisstudy, our preliminary results indicate that GC3GC-TOFMS-based metabolomic profiles could be used as comple- mentary method to differentiate CITES-regulated wood specimens at the genus and species levels.

A novel ML-driven test case selection approach for enhancing the performance of grammatical evolution

Computational cost in metaheuristics such as Evolutionary Algorithm (EAs) is often a major concern, particularly with their ability to scale. In data-based training, traditional EAs typically use a significant portion, if not all, of the dataset for model training and fitness evaluation in each generation. This makes EA suffer from high computational costs incurred during the fitness evaluation of the population, particularly when working with large datasets. To mitigate this issue, we propose a Machine Learning (ML)-driven Distance-based Selection (DBS) algorithm that reduces the fitness evaluation time by optimizing test cases. We test our algorithm by applying it to 24 benchmark problems from Symbolic Regression (SR) and digital circuit domains and then using Grammatical Evolution (GE) to train models using the reduced dataset. We use GE to test DBS on SR and produce a system flexible enough to test it on digital circuit problems further. The quality of the solutions is tested and compared against state-of-the-art and conventional training methods to measure the coverage of training data selected using DBS, i.e., how well the subset matches the statistical properties of the entire dataset. Moreover, the effect of optimized training data on run time and the effective size of the evolved solutions is analyzed. Experimental and statistical evaluations of the results show our method empowered GE to yield superior or comparable solutions to the baseline (using the full datasets) with smaller sizes and demonstrates computational efficiency in terms of speed

Using globally threatened pelagic birds to identify priority sites for marine conservation in the South Atlantic Ocean

The Convention on Biological Diversity aspires to designate 10% of the global oceans as Marine Protected Areas (MPAs), but so far, few MPAs protect pelagic species in the high seas. Transparent scientific approaches are needed to ensure that these encompass areas with high biodiversity value. Here we used the distribution of all globally threatened seabirds breeding in a centrally located archipelago (Tristan da Cunha) to provide guidance on where MPAs could be established in the South Atlantic Ocean. We combined year-round tracking data from six species, and used the systematic conservation-planning tool, 'Zonation', to delineate areas that would protect the largest proportion of each population. The areas used most intensively varied among species and seasons. Combining the sites used by all six species suggested that the most important areas of the South Atlantic are located south of South Africa, around the central South Atlantic between 30 degrees S and 55 degrees S, and near South America. We estimated that the longline fishing effort in these intensively used areas is around 11 million hooks on average each year, highlighting the need for improved monitoring of seabird bycatch rates and the enforcement of compliance with bird bycatch mitigation requirements by fisheries. There was no overlap between the identified areas and any of the existing MPAs in the South Atlantic. The conservation of these highly mobile, pelagic species cannot be achieved by single countries, but requires a multi-national approach at an ocean-basin scale, such as an agreement for the conservation of biodiversity beyond national jurisdiction under the United Nation Convention on the Law of the Sea

Unraveling the pathogenesis of ARX polyalanine tract variants using a clinical and molecular interfacing approach

The Aristaless-related homeobox (ARX) gene is implicated in intellectual disability with the most frequent pathogenic mutations leading to expansions of the first two polyalanine tracts. Here, we describe analysis of the ARX gene outlining the approaches in the Australian and Portuguese setting, using an integrated clinical and molecular strategy. We report variants in the ARX gene detected in 19 patients belonging to 17 families. Seven pathogenic variants, being expansion mutations in both polyalanine tract 1 and tract 2, were identifyed, including a novel mutation in polyalanine tract 1 that expands the first tract to 20 alanines. This precise number of alanines is sufficient to cause pathogenicity when expanded in polyalanine tract 2. Five cases presented a probably non-pathogenic variant, including the novel HGVS: c.441_455del, classified as unlikely disease causing, consistent with reports that suggest that in frame deletions in polyalanine stretches of ARX rarely cause intellectual disability. In addition, we identified five cases with a variant of unclear pathogenic significance. Owing to the inconsistent ARX variants description, publications were reviewed and ARX variant classifications were standardized and detailed unambiguously according to recommendations of the Human Genome Variation Society. In the absence of a pathognomonic clinical feature, we propose that molecular analysis of the ARX gene should be included in routine diagnostic practice in individuals with either nonsyndromic or syndromic intellectual disability. A definitive diagnosis of ARX-related disorders is crucial for an adequate clinical follow-up and accurate genetic counseling of at-risk family members.Unit for Multidisciplinary Research in Biomedicine, UMIB, ICBAS-UP, Porto, Portugal was funded by FEDER funds of the Operational Program for Competitiveness Factors – COMPETE through FCT – Foundation for Science and Technology under the project: Fcomp-01-0124-FEDER-015896. The Neurogenetics research program in the Department of Paediatrics, University of Adelaide, Australia was funded by the Australian National Health and Medical Research Council (Grant No. 1063025). C. S. is supported Australian Research Council (Future Fellowship FT120100086

Comprehensive characterization of mainstream marijuana and tobacco smoke

Abstract: Recent increases in marijuana use and legalization without adequate knowledge of the risks necessitate the characterization of the billions of nanoparticles contained in each puff of smoke. Tobacco smoke offers a benchmark given that it has been extensively studied. Tobacco and marijuana smoke particles are quantitatively similar in volatility, shape, density and number concentration, albeit with differences in size, total mass and chemical composition. Particles from marijuana smoke are on average 29% larger in mobility diameter than particles from tobacco smoke and contain 3.4× more total mass. New measurements of semi-volatile fractions determine over 97% of the mass and volume of the particles from either smoke source are comprised of semi-volatile compounds. For tobacco and marijuana smoke, respectively, 4350 and 2575 different compounds are detected, of which, 670 and 536 (231 in common) are tentatively identified, and of these, 173 and 110 different compounds (69 in common) are known to cause negative health effects through carcinogenic, mutagenic, teratogenic, or other toxic mechanisms. This study demonstrates striking similarities between marijuana and tobacco smoke in terms of their physical and chemical properties

Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of s√=7TeV proton-proton collisions

Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Search for New Physics with Jets and Missing Transverse Momentum in pp collisions at sqrt(s) = 7 TeV

A search for new physics is presented based on an event signature of at least three jets accompanied by large missing transverse momentum, using a data sample corresponding to an integrated luminosity of 36 inverse picobarns collected in proton--proton collisions at sqrt(s)=7 TeV with the CMS detector at the LHC. No excess of events is observed above the expected standard model backgrounds, which are all estimated from the data. Exclusion limits are presented for the constrained minimal supersymmetric extension of the standard model. Cross section limits are also presented using simplified models with new particles decaying to an undetected particle and one or two jets