Premise: Resolving relationships within order Commelinales has posed quite a challenge, as reflected in its unstable infra-familial classification. Thus, we investigated (1) relationships across families and genera of Commelinales; (2) phylogenetic placement of never-before sequenced genera; (3) how well off-target plastid data integrate with other plastid-based data sets; and (4) how the novel inferences coincide with the infra-familial classification.
Methods: We generated two large data sets (nuclear and plastome) by means of target sequence capture using the Angiosperms353 probe set, with additional sequences mined from publicly available transcriptomes and full plastomes. A third extended-plastid data set was considered, including all species with sequences in public repositories. Species trees were inferred under a multispecies coalescent framework from individual gene trees and also using maximum likelihood analyses from concatenated and partitioned data.
Results: The nuclear, plastome, and extended-plastid data sets include 52, 53, and 58 genera, respectively, and up to 290 species of Commelinales, representing the most comprehensive molecular sampling for the order to date, which includes seven never-before sequenced genera.
Conclusions: We inferred robust phylogenies supporting the monophyly of Commelinales and its five constituent families, and we recovered the clades Pontederiaceae-Haemodoraceae and Hanguanaceae-Commelinaceae, as previously reported. The placement of Philydraceae remains contentious. Relationships within the two largest families, Commelinaceae and Haemodoraceae, are resolved. Based on the latter results, we confirm the subfamilial classification of Haemodoraceae and propose a new classification for Commelinaceae, which includes the synonymization of Tapheocarpa in Commelina.
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http://dx.doi.org/10.1002/ajb2.1698 | DOI Listing |
ACS Nano
January 2025
Graduate School for Integrative Sciences and Engineering Programme, National University of Singapore, Singapore119077, Singapore.
Machine-learned potentials (MLPs) have transformed the field of molecular simulations by scaling "quantum-accurate" potentials to linear time complexity. While they provide more accurate reproduction of physical properties as compared to empirical force fields, it is still computationally costly to generate their training data sets from ab initio calculations. Despite the emergence of foundational or general MLPs for organic molecules and dense materials, it is unexplored if one general MLP can be effectively developed for a wide variety of nanoporous metal-organic frameworks (MOFs) with different chemical moieties and geometric properties.
View Article and Find Full Text PDFCommun Med (Lond)
January 2025
Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Leibniz ScienceCampus Primate Cognition and German Center for Child and Adolescent Health (DZKJ), Göttingen, Germany.
Background: To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments in early infancy. GMA has been increasingly augmented through machine learning approaches intending to scale-up its application, circumvent costs in the training of human assessors and further standardize classification of spontaneous motor patterns. Available deep learning tools, all of which are based on single sensor modalities, are however still considerably inferior to that of well-trained human assessors.
View Article and Find Full Text PDFSci Data
January 2025
Section of Intensive Plant Food Systems, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.
Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015-2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits.
View Article and Find Full Text PDFSci Data
January 2025
State Key Laboratory of Mariculture Breeding, Key Laboratory of Marine Biotechnology of Fujian Province, Institute of Oceanology, College of Marine Sciences, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Anisarchus medius (Reinhardt, 1837) is a widely distributed Arctic fish, serving as an indicator of climate change impacts on coastal Arctic ecosystems. This study presents a chromosome-level genome assembly for A. medius using PacBio sequencing and Hi-C technology.
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January 2025
Department of Radiology, China-Japan Friendship Hospital, Beijing, China.
The sharing of multimodal magnetic resonance imaging (MRI) data is of utmost importance in the field, as it enables a deeper understanding of facial nerve-related pathologies. However, there is a significant lack of multi-modal neuroimaging databases specifically focused on these conditions, which hampers our comprehensive knowledge of the neural foundations of facial paralysis. To address this critical gap and propel advancements in this area, we have released the Multimodal Neuroimaging Dataset of Meige Syndrome, Facial Paralysis, and Healthy Controls (MND-MFHC).
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