Development and Field Validation of an Environmental DNA (eDNA) Assay for Invasive Clams of the Genus Corbicula

Early detection is imperative for successful control or eradication of invasive species, but many organisms are difficult to detect at the low abundances characteristic of recently introduced populations. Environmental DNA (eDNA) has emerged as a promising invasive species surveillance tool for freshwaters, owing to its high sensitivity to detect aquatic species even when scarce. We report here a new eDNA assay for the globally invasive Asian clam Corbicula fluminea (Müller, 1774), with field validation in large lakes of western North America. We identified a candidate primer pair for the Cytochrome c oxidase subunit 1 (COI) gene for C. fluminea. We tested it for specificity via qPCR assay against genomic DNA of the target species C. fluminea, and synthetic DNA gBlocks for other non-target species within and outside of the genus Corbicula. Our best identified primer amplifies a 208-bp fragment for C. fluminea and several closely related species within the genus, but was specific for these non-native Asian clams relative to native mollusks of western North America. We further evaluated this assay in application to eDNA water samples for the detection of C. fluminea from four lakes in California and Nevada, United States, where the species is known to occur (including Lake Tahoe) relative to seven lakes where it has never been observed. Our assay successfully detected C. fluminea in all four lakes with historic records for this species, and did not detect C. fluminea from the seven lakes without known populations. Further, the distribution of eDNA detections within Lake Tahoe generally matched the known, restricted distribution of C. fluminea in this large lake. We conclude from this successful field validation that our eDNA assay for C. fluminea will be useful for researchers and managers seeking to detect new introductions and potentially monitor population trends of this major freshwater invader and other closely related members of its genus

Oligonucleotides Targeting DNA Repeats Downregulate Huntingtin Gene Expression in Huntington's Patient-Derived Neural Model System

Huntington's disease (HD) is one of the most common, dominantly inherited neurodegenerative disorders. It affects the striatum, cerebral cortex, and other subcortical structures leading to involuntary movement abnormalities, emotional disturbances, and cognitive impairments. HD is caused by a CAG•CTG trinucleotide-repeat expansion in exon 1 of the huntingtin (HTT) gene leading to the formation of mutant HTT (mtHTT) protein aggregates. Besides the toxicity of the mutated protein, there is also evidence that mtHTT transcripts contribute to the disease. Thus, the reduction of both mutated mRNA and protein would be most beneficial as a treatment. Previously, we designed a novel anti-gene oligonucleotide (AGO)-based strategy directly targeting the HTT trinucleotide-repeats in DNA and reported downregulation of mRNA and protein in HD patient fibroblasts. In this study, we differentiate HD patient-derived induced pluripotent stem cells to investigate the efficacy of the AGO, a DNA/Locked Nucleic Acid mixmer with phosphorothioate backbone, to modulate HTT transcription during neural in vitro development. For the first time, we demonstrate downregulation of HTT mRNA following both naked and magnetofected delivery into neural stem cells (NSCs) and show that neither emergence of neural rosette structures nor self-renewal of NSCs is compromised. Furthermore, the inhibition potency of both HTT mRNA and protein without off-target effects is confirmed in neurons. These results further validate an anti-gene approach for the treatment of HD

Au nanoparticle-functionalised WO3 nanoneedles and their application in high sensitivity gas sensor devices

A new method of synthesising nanoparticle-functionalised nanostructured materials via Aerosol Assisted Chemical Vapour Deposition (AACVD) has been developed. Co-deposition of Au nanoparticles with WO3 nanoneedles has been used to deposit a sensing layer directly onto gas sensor substrates providing devices with a six-fold increase in response to low concentrations of a test analyte (ethanol)

Synthesis and Cathodoluminescence of Undoped and Cr^3^+-Doped Sodium Titanate Nanotubes and Nanoribbons

We report on the synthesis of Cr^3^+-doped sodium titanate nanotubes and nanoribbons by a hydrothermal method. The presence of dopant ions in these nanostructures was confirmed by high angle annular dark field scanning transmission electron microscopy in combination with electron energy loss spectroscopy measurements. Luminescence properties of undoped and Cr^3^+-doped sodium titanate nanotubes and nanoribbons were investigated by cathodoluminescence in the scanning electron microscope. A broad visible band in the range 1.7−2.7 eV is observed in these nanostructures. Such emission is similar to that observed in bulk anatase TiO_2 and titanate powders, and is related to TiO_6 octahedra, which is a common feature to all the samples investigated. Near-infrared emission, sometimes attributed to Ti^3^+ interstitials, is observed in bulk powders but is absent in the titanate nanotubes and nanoribbons. Incorporation of Cr^3^+ between the titanate layers of the nanostructures is revealed by the characteristic intraionic emission line at 1.791 eV. Sodium titanate nanoribbons appear to be an effective host for optically active Cr^3^+ ions, as compared with nanotubes or bulk powder

Higher education students’ achievement emotions and their antecedents in e-learning amid COVID-19 pandemic: A multi-country survey

The outbreak of the COVID-19 pandemic has had a wide range of negative consequences for higher education students. We explored the generalizability of the control-value theory of achievement emotions for e-learning, focusing on their antecedents. We involved 17019 higher education students from 13 countries, who completed an online survey during the first wave of the pandemic. A structural equation model revealed that proximal antecedents (e-learning self-efficacy, computer self-efficacy) mediated the relation between environmental antecedents (cognitive and motivational quality of the task) and positive and negative achievement emotions, with some exceptions. The model was invariant across country, area of study, and gender. The rates of achievement emotions varied according to these same factors. Beyond their theoretical relevance, these findings could be the basis for policy recommendations to support stakeholders in coping with the challenges of e-learning and the current and future sequelae of the pandemic.info:eu-repo/semantics/publishedVersio

Exceptional Preferences Mining

Exceptional Preferences Mining (EPM) is a crossover between two subfields of datamining: local pattern mining and preference learning. EPM can be seen as a local pattern mining task that finds subsets of observations where the preference relations between subsets of the labels significantly deviate from the norm; a variant of Subgroup Discovery, with rankings as the (complex) target concept. We employ three quality measures that highlight subgroups featuring exceptional preferences, where the focus of what constitutes 'exceptional' varies with the quality measure: the first gauges exceptional overall ranking behavior, the second indicates whether a particular label stands out from the rest, and the third highlights subgroups featuring unusual pairwise label ranking behavior. As proof of concept, we explore five datasets. The results confirm that the new task EPM can deliver interesting knowledge. The results also illustrate how the visualization of the preferences in a Preference Matrix can aid in interpreting exceptional preference subgroups

Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 degrees C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naive Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 mu g/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures.Ines Mendes and Ricardo Franco-Duarte are recipients of a fellowship from the Portuguese Science Foundation, FCT (SFRH/BD/74798/2010, SFRH/BD/48591/2008, respectively) and Joao Drumonde-Neves is recipient of a fellowship from the Azores government (M3.1.2/F/006/2008 (DRCT)). Financial support was obtained from FEDER funds through the program COMPETE and by national funds through FCT by the projects FCOMP-01-0124-008775 (PTDC/AGR-ALI/103392/2008) and PTDC/AGR-ALI/121062/2010. Lan Umek and Blaz Zupan acknowledge financial support from Slovene Research Agency (P2-0209). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Attainment of Brown Adipocyte Features in White Adipocytes of Hormone-Sensitive Lipase Null Mice

BACKGROUND: Hormone-sensitive lipase (HSL) is expressed predominantly in adipose tissue, where it plays an important role in catecholamine-stimulated hydrolysis of stored tri- and diglycerides, thus mobilizing fatty acids. HSL exhibits broad substrate specificity and besides acylglycerides it hydrolyzes cholesteryl esters, retinyl esters and lipoidal esters. Despite its role in fatty acid mobilization, HSL null mice have been shown to be resistant to diet-induced obesity. METHODOLOGY/PRINCIPAL FINDINGS: Following a high-fat diet (HFD) regimen, energy expenditure, measured using indirect calorimetry, was increased in HSL null mice. White adipose tissue of HSL null mice was characterized by reduced mass and reduced protein expression of PPARgamma, a key transcription factor in adipogenesis, and stearoyl-CoA desaturase 1, the expression of which is known to be positively correlated to the differentiation state of the adipocyte. The protein expression of uncoupling protein-1 (UCP-1), the highly specific marker of brown adipocytes, was increased 7-fold in white adipose tissue of HSL null mice compared to wildtype littermates. Transmission electron microscopy revealed an increase in the size of mitochondria of white adipocytes of HSL null mice. The mRNA expression of pRb and RIP140 was decreased in isolated white adipocytes, while the expression of UCP-1 and CPT1 was increased in HSL null mice compared to wildtype littermates. Basal oxygen consumption was increased almost 3-fold in white adipose tissue of HSL null mice and was accompanied by increased uncoupling activity. CONCLUSIONS: These data suggest that HSL is involved in the determination of white versus brown adipocytes during adipocyte differentiation The exact mechanism(s) underlying this novel role of HSL remains to be elucidated, but it seems clear that HSL is required to sustain normal expression levels of pRb and RIP140, which both promote differentiation into the white, rather than the brown, adipocyte lineage

Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries

The outbreak of the COVID-19 pandemic has dramatically shaped higher education and seen the distinct rise of e-learning as a compulsory element of the modern educational landscape. Accordingly, this study highlights the factors which have influenced how students perceive their academic performance during this emergency changeover to e-learning. The empirical analysis is performed on a sample of 10,092 higher education students from 10 countries across 4 continents during the pandemic’s first wave through an online survey. A structural equation model revealed the quality of e-learning was mainly derived from service quality, the teacher’s active role in the process of online education, and the overall system quality, while the students’ digital competencies and online interactions with their colleagues and teachers were considered to be slightly less important factors. The impact of e-learning quality on the students’ performance was strongly mediated by their satisfaction with e-learning. In general, the model gave quite consistent results across countries, gender, study fields, and levels of study. The findings provide a basis for policy recommendations to support decision-makers incorporate e-learning issues in the current and any new similar circumstances.info:eu-repo/semantics/publishedVersio