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Multilabeled trees or MUL-trees, for short, are trees whose leaves are labeled by elements of some nonempty finite set X such that more than one leaf may be labeled by the same element of X. This class of trees includes phylogenetic trees and tree shapes. MUL-trees arise naturally in, for example, biogeography and gene evolution studies and also in the area of phylogenetic network reconstruction. In this paper, we introduce novel metrics which may be used to compare MUL-trees, most of which generalize well-known metrics on phylogenetic trees and tree shapes. These metrics can be used, for example, to better understand the space of MUL-trees or to help visualize collections of MUL-trees. In addition, we describe some relationships between the MUL-tree metrics that we present and also give some novel diameter bounds for these metrics. We conclude by briefly discussing some open problems as well as pointing out how MUL-tree metrics may be used to define metrics on the space of phylogenetic networks.
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http://dx.doi.org/10.1109/TCBB.2010.122 | DOI Listing |
Protein Cell
August 2025
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China.
Cardiovascular disease (CVD) research is hindered by limited comprehensive analyses of plasma proteome across disease subtypes. Here, we systematically investigated the associations between plasma proteins and cardiovascular outcomes in 53,026 UK Biobank participants over a 14-year follow-up. Association analyses identified 3,089 significant associations involving 892 unique protein analytes across 13 CVD outcomes.
View Article and Find Full Text PDFMuscle Nerve
September 2025
Department of Neurology, Seoul Hospital, Ewha Womans University College of Medicine, Seoul, South Korea.
Introduction/aims: There is a lack of up-to-date information on the burden of motor neuron diseases (MNDs) in the United States (US). This study aimed to estimate trends in the prevalence, incidence, mortality, and disability-adjusted life years (DALYs) for MNDs in the US from 1990 to 2021.
Methods: We performed a secondary analysis of MNDs in the US using estimates of prevalence, incidence, and mortality obtained from analyses of the Global Burden of Disease 2021 dataset.
Neurotrauma Rep
August 2025
Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China.
Accurate differentiation between persistent vegetative state (PVS) and minimally conscious state and estimation of recovery likelihood in patients in PVS are crucial. This study analyzed electroencephalography (EEG) metrics to investigate their relationship with consciousness improvements in patients in PVS and developed a machine learning prediction model. We retrospectively evaluated 19 patients in PVS, categorizing them into two groups: those with improved consciousness ( = 7) and those without improvement ( = 12).
View Article and Find Full Text PDFFront Hum Neurosci
August 2025
Baptist Medical Center, Department of Behavioral Health, Jacksonville, FL, United States.
Introduction: This study investigates four subdomains of executive functioning-initiation, cognitive inhibition, mental shifting, and working memory-using task-based functional magnetic resonance imaging (fMRI) data and graph analysis.
Methods: We used healthy adults' functional magnetic resonance imaging (fMRI) data to construct brain connectomes and network graphs for each task and analyzed global and node-level graph metrics.
Results: The bilateral precuneus and right medial prefrontal cortex emerged as pivotal hubs and influencers, emphasizing their crucial regulatory role in all four subdomains of executive function.
Comput Struct Biotechnol J
August 2025
Institut de Recherche en Cancérologie de Montpellier (IRCM), Équipe Labellisée Ligue Contre le Cancer, INSERM U1194, Université de Montpellier, Institut régional du Cancer de Montpellier (ICM), Montpellier, France.
Digital twins (DTs) are emerging tools for simulating and optimizing therapeutic protocols in personalized nuclear medicine. In this paper, we present a modular pipeline for constructing patient-specific DTs aimed at assessing and improving dosimetry protocols in PRRT such as therapy. The pipeline integrates three components: (i) an anatomical DT, generated by registering patient CT scans with an anthropomorphic model; (ii) a functional DT, based on a physiologically-based pharmacokinetic (PBPK) model created in SimBiology; and (iii) a virtual clinical trial module using GATE to simulate particle transport, image simulation, and absorbed dose distribution.
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