The timing and sequence of events underlying the origin and early evolution of vertebrates remains poorly understood. The palaeontological evidence should shed light on these issues, but difficulties in interpretation of the non-biomineralized fossil record make this problematic. Here we present an experimental analysis of decay of vertebrate characters based on the extant jawless vertebrates (Lampetra and Myxine). This provides a framework for the interpretation of the anatomy of soft-bodied fossil vertebrates and putative cyclostomes, and a context for reading the fossil record of non-biomineralized vertebrate characters. Decay results in transformation and non-random loss of characters. In both lamprey and hagfish, different types of cartilage decay at different rates, resulting in taphonomic bias towards loss of 'soft' cartilages containing vertebrate-specific Col2α1 extracellular matrix proteins; phylogenetically informative soft-tissue characters decay before more plesiomorphic characters. As such, synapomorphic decay bias, previously recognized in early chordates, is more pervasive, and needs to be taken into account when interpreting the anatomy of any non-biomineralized fossil vertebrate, such as Haikouichthys, Mayomyzon and Hardistiella.
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http://dx.doi.org/10.1098/rspb.2010.1641 | DOI Listing |
BMC Med Res Methodol
January 2025
Prehospital Center Region Zealand, Ringstedgade 61, 14th Floor, Naestved, 4700, Denmark.
Background: Effective interventions to reduce drowning incidents require accurate and reliable data for scientific analysis. However, the lack of high-quality evidence and the variability in drowning terminology, definitions, and outcomes present significant challenges in assessing studies to inform drowning guidelines. Many drowning reports use inappropriate classifications for drowning incidents, which significantly contributes to the underreporting of drowning.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Department of Information Technology, Vardhaman College of Engineering, Shamshabad, Hyderabad, India.
Background: Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora, which may not always be accessible. To overcome these challenges, deep learning (DL) methods have emerged.
View Article and Find Full Text PDFAnn Med
December 2025
Endoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, China.
Background: Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and establish a predictive model for diagnosis of venous thrombosis clinical by routine blood tests and endoscopic characteristics.
Methods: Patients from Gansu Provincial Hospital from October 2019 to December 2023 were enrolled.
BMJ Open
January 2025
Department of Medical Oncology, Section Translational Medical Ethics, National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Objectives: Patient-reported financial effects of a tumour disease in a universal healthcare setting are a multidimensional phenomenon. Actual and anticipated objective financial burden caused by direct medical and non-medical costs as well as indirect costs such as loss of income can lead to subjective financial distress. To better understand subjective financial distress, the presented study explores self-reported determinants for subjective financial distress in German patients with cancer, aiming to inform a new German-language patient-reported outcome measure for determining the financial effects of a tumour disease.
View Article and Find Full Text PDFDatabase (Oxford)
January 2025
Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON CA K1A 0C6, Canada.
It is well-known that the use of vocabulary in phenotype treatments is often inconsistent. An earlier survey of biologists who create or use phenotypic characters revealed that this lack of standardization leads to ambiguities, frustrating both the consumers and producers of phenotypic data. Such ambiguities are challenging for biologists, and more so for Artificial Intelligence, to resolve.
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