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http://dx.doi.org/10.18632/aging.202826 | DOI Listing |
PeerJ
January 2025
Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, United States of America.
Despite the recent surge of viral metagenomic studies, it remains a significant challenge to recover complete virus genomes from metagenomic data. The majority of viral contigs generated from de novo assembly programs are highly fragmented, presenting significant challenges to downstream analysis and inference. To address this issue, we have developed Virseqimprover, a computational pipeline that can extend assembled contigs to complete or nearly complete genomes while maintaining extension quality.
View Article and Find Full Text PDFBMJ Open
December 2024
Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.
Introduction: Infants born very preterm (VPT, <32 weeks' gestation) are at increased risk for neurodevelopmental impairments including motor, cognitive and behavioural delay. Parents of infants born VPT also have poorer mental health outcomes compared with parents of infants born at term.We have developed an intervention programme called TEDI-Prem (Telehealth for Early Developmental Intervention in babies born very preterm) based on previous research.
View Article and Find Full Text PDFBMJ Open
December 2024
Regional Rehabilitation Unit, Northwick Park Hospital, London, UK.
Objectives: To adapt and apply a model for evaluating the functional benefits and cost efficiency of specialist inpatient rehabilitation to the Australian context, comparing functional outcomes and savings in the cost of ongoing care after acquired brain injury.
Design: An observational cohort analysis of prospectively collected clinical data from admission to discharge, with follow-up to 3 years.
Setting: A newly established state-wide inpatient postacute rehabilitation unit in Victoria, Australia for patients with moderate to severe acquired brain injury.
J Am Soc Mass Spectrom
January 2025
Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8362, United States.
While gas chromatography mass spectrometry (GC-MS) has long been used to identify compounds in complex mixtures, this process is often subjective and time-consuming and leaves a large fraction of seemingly good-quality spectra unidentified. In this work, we describe a set of new mass spectral library-based methods to assist compound identification in complex mixtures. These methods employ mass spectral uniqueness and compound ubiquity of library entries alongside noise reduction and automated comparison of retention indices to library compounds.
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