We investigated higher-order relationships in the cycads, an ancient group of seed-bearing plants, by examining a large portion of the chloroplast genome from seven species chosen to exemplify our current understanding of taxonomic diversity in the order. The regions considered span approximately 13.5 kb of unaligned data per taxon, and comprise a diverse range of coding sequences, introns and intergenic spacers dispersed throughout the plastid genome. Our results provide substantial support for most of the inferred backbone of cycad phylogeny, and weak evidence that the sister-group of the cycads among living seed plants is Ginkgo biloba. Cycas (representing Cycadaceae) is the sister-group of the remaining cycads; Dioon is part of the next most basal split. Two of the three commonly recognized families of cycads (Zamiaceae and Stangeriaceae) are not monophyletic; Stangeria is embedded within Zamiaceae, close to Zamia and Ceratozamia, and not closely allied to the other genus of Stangeriaceae, Bowenia. In contrast to the other seed plants, cycad chloroplast genomes share two features with Ginkgo: a reduced rate of evolution and an elevated transition:transversion ratio. We demonstrate that the latter aspect of their molecular evolution is unlikely to have affected inference of cycad relationships in the context of seed-plant wide analyses.
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Cereb Cortex
January 2025
Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei, Chongqing 400715, China.
Prior work highlighted that procrastination and impulsivity shared a common neuroanatomical basis in the dorsolateral prefrontal cortex, implying a tight relationship between these traits. However, theorists hold that procrastination is motivated by avoiding aversiveness, while impulsivity is driven by approaching immediate pleasure. Hence, exploring the common and distinct neural basis underlying procrastination and impulsivity through functional neuroimaging becomes imperative.
View Article and Find Full Text PDFMach Learn Appl
June 2024
McGill University Department of Biostatistics, 805 rue Sherbrooke O, Montréal, H3A 0B9, Quebec, Canada.
In the context of survival analysis, data-driven neural network-based methods have been developed to model complex covariate effects. While these methods may provide better predictive performance than regression-based approaches, not all can model time-varying interactions and complex baseline hazards. To address this, we propose Case-Base Neural Networks (CBNNs) as a new approach that combines the case-base sampling framework with flexible neural network architectures.
View Article and Find Full Text PDFNeuroimage
January 2025
Academy of Wellness and Human Development, Hong Kong Baptist University, Hong Kong, China.
The ability to infer a speaker's utterance within a particular context for the intended meaning is central to communication. Yet, little is known about the underlying neurocomputational mechanisms of pragmatic inference, let alone relevant differences among individuals. Here, using a reference game combined with model-based functional magnetic resonance imaging (fMRI), we showed that an individual-level pragmatic inference model was a better predictor of listeners' performance than a population-level model.
View Article and Find Full Text PDFJ Pharm Sci
January 2025
Department of Chemical Engineering, Indian Institute of Technology Delhi. Electronic address:
Stability of complex biotherapeutics like monoclonal antibodies is paramount for their safe and efficacious use. Excipients are inactive ingredients that are added to the purified product so as to offer it a stable environment. Trehalose dihydrate is a non-reducing sugar that is commonly used as a stabilizing agent in biotherapeutic formulations under liquid and frozen states.
View Article and Find Full Text PDFUltrasonics
January 2025
School of Biological Science and Medical Engineering, Beihang University, Beijing, China. Electronic address:
Transcranial focused ultrasound (tFUS) has been gaining increased attention as a non-invasive modality for treating brain diseases. However, accurately focusing on brain structures remains a challenge as the ultrasound is severely distorted by the presence of the skull. In this article, we propose a promising distortion correction method based on spherical wave expansions.
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