Cotton leafroll dwarf virus (CLRDV), a threat to the cotton industry, was first reported in the United States (US) as an emergent pathogen in 2017. Phylogenetic analysis supports the hypothesis that US CLRDV strains are genetically distinct from strains in South America and elsewhere, which is not consistent with the hypothesis that the virus is newly introduced into the country. Using database mining, we evaluated the timeline and geographic distribution of CLRDV in the country. We uncovered evidence that shows CLRDV had been in the US for over a decade before its official first report. CLRDV sequences were detected in datasets derived from Mississippi in 2006, Louisiana in 2015, and California in 2018. Additionally, through field surveys of upland cotton in 2023, we confirmed that CLRDV is present in California, which had no prior reports of the virus. Viral sequences from these old and new datasets exhibited high nucleotide identities (>98%) with recently characterized US isolates, and phylogenetic analyses with their homologs placed these sequences within a US-specific clade, further supporting the earlier presence of CLRDV in the country. Moreover, potential new hosts, including another fiber crop, flax, were determined through data mining. Retrospective analysis suggests CLRDV has been present in the US since at least 2006 (Mississippi). Our findings challenge the current understanding of the arrival and spread of CLRDV in the US, highlight the power of data mining for virus discovery, and underscore the need for further investigation into CLRDV's impact on US cotton.
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http://dx.doi.org/10.1094/PDIS-06-24-1265-SC | DOI Listing |
Anal Methods
January 2025
Program in Chemical and Biochemical Process Engineering, School of Chemistry, Federal University of Rio de Janeiro, Cidade Universitária, Rio de Janeiro, CEP 21941-909, Brazil.
Low-carbon fuels, emitting less carbon than fossil fuels, are proposed to help in the transition to a sustainable, decarbonized transport sector. The new biofuels being studied and developed in this context include hydrotreated vegetable oils (HVO). Its chemical composition, which is the same as fossil diesel (primarily composed of linear chain hydrocarbons C12-C24), makes HVO (more homogeneous mixtures of paraffinic hydrocarbons C10-C20, containing no sulfur or aromatics) a fuel with slightly lower density than fossil diesel due to these characteristics.
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January 2025
This study aimed to develop an advanced ensemble approach for automated classification of mental health disorders in social media posts. The research question was: can an ensemble of fine-tuned transformer models (XLNet, RoBERTa, and ELECTRA) with Bayesian hyperparameter optimization improve the accuracy of mental health disorder classification in social media text. Three transformer models (XLNet, RoBERTa, and ELECTRA) were fine-tuned on a dataset of social media posts labelled with 15 distinct mental health disorders.
View Article and Find Full Text PDFHeliyon
July 2024
School of Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.
Road traffic accidents pose a significant global health concern, with an alarming 1.19 million fatalities reported in 2021. Traditionally, strategies to address this challenge have relied on expert input and subjective evaluations.
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December 2024
Eijkman Research Center for Molecular Biology, National Research and Innovation Agency (BRIN), Bogor, Indonesia.
Nephrotic syndrome, a multifaceted medical condition characterized by significant proteinuria, has recently prompted a reorientation of research efforts toward B-cell-mediated mechanisms. This shift underscores the pivotal role played by B-cells in its pathogenesis. The aim of this study was to explore potential therapeutic pathways, with specific attention given to compounds found in , including withanolides, such as physalins, which constitute one of the five distinct withanolide subgroups identified in .
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biochemistry, Microbiology &Biotechnology, University of Limpopo, Private BagX1106, Sovenga, Limpopo, 0727, South Africa.
Egg quality is affected by lot of factors. Study was conducted to compare performance of data mining algorithms; Classification and regression tree (CART), Chi-square automatic interaction detection (CHAID), Exhaustive chi-square automatic interaction detection (Ex-CHAID) and Multivariate adaptive regression spline (MARS) in prediction of Potchefstroom Koekoek's eggshell thickness from egg quality traits. 350 eggs were collected at 31st to 39th week to examine the egg quality traits.
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