Intermediate wheatgrass (IWG) is a perennial grass that produces nutritious grain while offering substantial ecosystem services. Commercial varieties of this crop are mostly synthetic panmictic populations that are developed by intermating a few selected individuals. As development and generation advancement of these synthetic populations is a multiyear process, earlier synthetic generations are tested by the breeders and subsequent generations are released to the growers. A comparison of generations within IWG synthetic cultivars is currently lacking. In this study, we used simulation models and genomic prediction to analyze population differences and trends of genetic variance in 4 synthetic generations of MN-Clearwater, a commercial cultivar released by the University of Minnesota. Little to no differences were observed among the 4 generations for population genetic, genetic kinship, and genome-wide marker relationships measured via linkage disequilibrium. A reduction in genetic variance was observed when 7 parents were used to generate synthetic populations while using 20 led to the best possible outcome in determining population variance. Genomic prediction of plant height, free threshing ability, seed mass, and grain yield among the 4 synthetic generations showed a few significant differences among the generations, yet the differences in values were negligible. Based on these observations, we make 2 major conclusions: (1) the earlier and latter synthetic generations of IWG are mostly similar to each other with minimal differences and (2) using 20 genotypes to create synthetic populations is recommended to sustain ample genetic variance and trait expression among all synthetic generations.
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http://dx.doi.org/10.1093/g3journal/jkae154 | DOI Listing |
ACS Nano
January 2025
Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore.
Transition-metal dichalcogenides (TMDs), such as molybdenum disulfide (MoS), have emerged as a generation of nonprecious catalysts for the hydrogen evolution reaction (HER), largely due to their theoretical hydrogen adsorption energy close to that of platinum. However, efforts to activate the basal planes of TMDs have primarily centered around strategies such as introducing numerous atomic vacancies, creating vacancy-heteroatom complexes, or applying significant strain, especially for acidic media. These approaches, while potentially effective, present substantial challenges in practical large-scale deployment.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
SynVaccine Ltd, Ramat Hachayal, 3 Golda Meir Street, Science Park, Nes Ziona 7403648, Israel.
Many viruses of the Flaviviridae family, including the Zika virus (ZIKV), are human pathogens of significant public health concerns. Despite extensive research, there are currently no approved vaccines available for ZIKV and specifically no live-attenuated Zika vaccine. In this current study, we suggest a novel computational algorithm for generating live-attenuated vaccines via the introduction of silent mutation into regions that undergo selection for strong or weak local RNA folding or into regions that exhibit medium levels of sequence conservation.
View Article and Find Full Text PDFInt J Lang Commun Disord
January 2025
Division of Communication Sciences and Disorders, University of Cape Town, Rondebosch, South Africa.
Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.
Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.
Methods & Procedures: A mixed methods research design was selected.
Acta Otolaryngol
January 2025
Department of Otorhinolaryngology, Institute of Science Tokyo, Tokyo, Japan.
Background: Recent advances in artificial intelligence have facilitated the automatic diagnosis of middle ear diseases using endoscopic tympanic membrane imaging.
Aim: We aimed to develop an automated diagnostic system for middle ear diseases by applying deep learning techniques to tympanic membrane images obtained during routine clinical practice.
Material And Methods: To augment the training dataset, we explored the use of generative adversarial networks (GANs) to produce high-quality synthetic tympanic images that were subsequently added to the training data.
Sensors (Basel)
January 2025
Department of Computer Science, Al-Baha University, Al-Baha 65779, Saudi Arabia.
Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
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