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"Tucker, James"
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Costume and fashion : a concise history
From the momentous invention of the needle some 40,000 years ago to the development of blue denim, this classic guide covers the landmarks of costume history, the forms and materials used through the ages, as well as the ways in which clothes have been used to protect, to express identity, and to attract or influence others. For the fifth edition, Amy de la Haye, former Curator of Twentieth-Century Dress at the Victoria and Albert Museum, has revised the final chapter and included a new section addressing the fashion industry in the twenty-first century. She discusses the expansion of the Asian luxury market, the rise of \"fast fashion,\" stylists, and celebrity endorsements, and the influence of the Internet.
Book
Ultrarapid detection of SARS-CoV-2 RNA using a reverse transcription–free exponential amplification reaction, RTF-EXPAR
A rapid isothermal method for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, is reported. The procedure uses an unprecedented reverse transcription–free (RTF) approach for converting genomic RNA into DNA. This involves the formation of an RNA/DNA heteroduplex whose selective cleavage generates a short DNA trigger strand, which is then rapidly amplified using the exponential amplification reaction (EXPAR). Deploying the RNA-to-DNA conversion and amplification stages of the RTF-EXPAR assay in a single step results in the detection, via a fluorescence read-out, of single figure copy numbers per microliter of SARS-CoV-2 RNA in under 10 min. In direct threeway comparison studies, the assay has been found to be faster than both RT-qPCR and reverse transcription loop-mediated isothermal amplification (RT-LAMP), while being just as sensitive. The assay protocol involves the use of standard laboratory equipment and is readily adaptable for the detection of other RNA-based pathogens.
Journal Article
Verteporfin selectively kills hypoxic glioma cells through iron-binding and increased production of reactive oxygen species
Gliomas are highly malignant brain tumours characterised by extensive areas of poor perfusion which subsequently leads to hypoxia and reduced survival. Therapies that address the hypoxic microenvironment are likely to significantly improve patient outcomes. Verteporfin, a benzoporphyrin-like drug, has been suggested to target the Yes-associated protein (YAP). Increased YAP expression and transcriptional activity has been proposed in other tumour types to promote malignant cell survival and thus YAP-inhibitor, verteporfin, may be predicted to impact glioma cell growth and viability. Due to the extensive hypoxic nature of gliomas, we investigated the effect of hypoxia on YAP expression and found that YAP transcription is increased under these conditions. Treatment of both primary and immortalised glioblastoma cell lines with verteporfin resulted in a significant decrease in viability but strikingly only under hypoxic conditions (1% O
2
). We discovered that cell death occurs through a YAP-independent mechanism, predominately involving binding of free iron and likely through redox cycling, contributes to production of reactive oxygen species. This results in disruption of normal cellular processes and death in cells already under oxidative stress – such as those in hypoxia. We suggest that through repurposing verteporfin, it represents a novel means of treating highly therapy-resistant, hypoxic cells in glioma.
Journal Article
The Drone Revolution of Shark Science: A Review
Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.
Journal Article
Genome-Wide Association Study of Waterlogging Tolerance in Barley (Hordeum vulgare L.) Under Controlled Field Conditions
Waterlogging is one of the main abiotic stresses severely reducing barley grain yield. Barley breeding programs focusing on waterlogging tolerance require an understanding of genetic loci and alleles in the current germplasm. In this study, 247 worldwide spring barley genotypes grown under controlled field conditions were genotyped with 35,926 SNPs with minor allele frequency (MAF) > 0.05. Significant phenotypic variation in each trait, including biomass, spikes per plant, grains per plant, kernel weight per plant, plant height and chlorophyll content, was observed. A genome-wide association study (GWAS) based on linkage disequilibrium (LD) for waterlogging tolerance was conducted. Population structure analysis divided the population into three subgroups. A mixed linkage model using both population structure and kinship matrix (Q+K) was performed. We identified 17 genomic regions containing 51 significant waterlogging-tolerance-associated markers for waterlogging tolerance response, accounting for 5.8–11.5% of the phenotypic variation, with a majority of them localized on chromosomes 1H, 2H, 4H, and 5H. Six novel QTL were identified and eight potential candidate genes mediating responses to abiotic stresses were located at QTL associated with waterlogging tolerance. To our awareness, this is the first GWAS for waterlogging tolerance in a worldwide barley collection under controlled field conditions. The marker-trait associations could be used in the marker-assisted selection of waterlogging tolerance and will facilitate barley breeding.
Journal Article
GPTransformer: A Transformer-Based Deep Learning Method for Predicting Fusarium Related Traits in Barley
Fusarium head blight (FHB) incited by Fusarium graminearum Schwabe is a devastating disease of barley and other cereal crops worldwide. Fusarium head blight is associated with trichothecene mycotoxins such as deoxynivalenol (DON), which contaminates grains, making them unfit for malting or animal feed industries. While genetically resistant cultivars offer the best economic and environmentally responsible means to mitigate disease, parent lines with adequate resistance are limited in barley. Resistance breeding based upon quantitative genetic gains has been slow to date, due to intensive labor requirements of disease nurseries. The production of a high-throughput genome-wide molecular marker assembly for barley permits use in development of genomic prediction models for traits of economic importance to this crop. A diverse panel consisting of 400 two-row spring barley lines was assembled to focus on Canadian barley breeding programs. The panel was evaluated for FHB and DON content in three environments and over 2 years. Moreover, it was genotyped using an Illumina Infinium High-Throughput Screening (HTS) iSelect custom beadchip array of single nucleotide polymorphic molecular markers (50 K SNP), where over 23 K molecular markers were polymorphic. Genomic prediction has been demonstrated to successfully reduce FHB and DON content in cereals using various statistical models. Herein, we have studied an alternative method based on machine learning and compare it with a statistical approach. The bi-allelic SNPs represented pairs of alleles and were encoded in two ways: as categorical (–1, 0, 1) or using Hardy-Weinberg probability frequencies. This was followed by selecting essential genomic markers for phenotype prediction. Subsequently, a Transformer-based deep learning algorithm was applied to predict FHB and DON. Apart from the Transformer method, a Residual Fully Connected Neural Network (RFCNN) was also applied. Pearson correlation coefficients were calculated to compare true vs. predicted outputs. Models which included all markers generally showed marginal improvement in prediction. Hardy-Weinberg encoding generally improved correlation for FHB (6.9%) and DON (9.6%) for the Transformer network. This study suggests the potential of the Transformer based method as an alternative to the popular BLUP model for genomic prediction of complex traits such as FHB or DON, having performed equally or better than existing machine learning and statistical methods.
Journal Article
Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine
To improve power production and structural reliability of wind turbines, there is a pressing need to understand how turbines interact with the atmospheric boundary layer. However, experimental techniques capable of quantifying or even qualitatively visualizing the large-scale turbulent flow structures around full-scale turbines do not exist today. Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine in a sampling area of ~\\n36 × 36 m
2
. The spatial and temporal resolutions of the measurements are sufficiently high to quantify the evolution of blade-generated coherent motions, such as the tip and trailing sheet vortices, identify their instability mechanisms and correlate them with turbine operation, control and performance. Our experiment provides an unprecedented
in situ
characterization of flow structures around utility-scale turbines, and yields significant insights into the Reynolds number similarity issues presented in wind energy applications.
Models of turbulent flows are often simulated in the laboratory, in sampling areas with dimensions <1 m. Here, the authors exploit a natural snowstorm to quantify turbulent flows, exploring the complex dynamics of the atmospheric boundary layer around a 2.5-MW utility-scale wind turbine.
Journal Article
Genome-Wide Analysis of Gene Expression Provides New Insights into Waterlogging Responses in Barley (Hordeum vulgare L.)
Waterlogging is a major abiotic stress causing oxygen depletion and carbon dioxide accumulation in the rhizosphere. Barley is more susceptible to waterlogging stress than other cereals. To gain a better understanding, the genome-wide gene expression responses in roots of waterlogged barley seedlings of Yerong and Deder2 were analyzed by RNA-Sequencing. A total of 6736, 5482, and 4538 differentially expressed genes (DEGs) were identified in waterlogged roots of Yerong at 72 h and Deder2 at 72 and 120 h, respectively, compared with the non-waterlogged control. Gene Ontology (GO) enrichment analyses showed that the most significant changes in GO terms, resulted from these DEGs observed under waterlogging stress, were related to primary and secondary metabolism, regulation, and oxygen carrier activity. In addition, more than 297 transcription factors, including members of MYB, AP2/EREBP, NAC, WRKY, bHLH, bZIP, and G2-like families, were identified as waterlogging responsive. Tentative important contributors to waterlogging tolerance in Deder2 might be the highest up-regulated DEGs: Trichome birefringence, α/β-Hydrolases, Xylanase inhibitor, MATE efflux, serine carboxypeptidase, and SAUR-like auxin-responsive protein. The study provides insights into the molecular mechanisms underlying the response to waterlogging in barley, which will be of benefit for future studies of molecular responses to waterlogging and will greatly assist barley genetic research and breeding.
Journal Article
Increased shark bite survivability revealed by two centuries of Australian records
The perceived and real threat of shark bites have significant direct health and indirect economic impacts. Here we assess the changing odds of surviving an unprovoked shark bite using 200 years of Australian records. Bite survivability rates for bull (
Carcharhinus leucas
), tiger (
Galeocerdo cuvier
) and white (
Carcharodon carcharias
) sharks were assessed relative to environmental and anthropogenic factors. Survivability of unprovoked bull, tiger and white shark bites were 62, 75 and 53% respectively. Bull shark survivability increased over time between 1807 and 2018. Survivability decreased for both tiger and white sharks when the person was doing an in water activity, such as swimming or diving. Not unsurprisingly, a watercraft for protection/floatation increased survivability to 92% from 30%, and 88% from 45%, for tiger and white sharks respectively. We speculate that survival may be related to time between injury and treatment, indicating the importance of rapid and appropriate medical care. Understanding the predictors of unprovoked bites, as well as survivability (year and water activity), may be useful for developing strategies that reduce the number of serious or fatal human-shark interactions without impacting sharks and other marine wildlife.
Journal Article