We present an image dataset of monothalamous soft-shelled Foraminifera (Monothalamea, [1]), an important component of benthic foraminiferal assemblage in sediment cores collected during two oceanographic expeditions that contributed to the MSM30-CORIBAR project (Ice dynamics and meltwater deposits: coring in the Kveithola trough, NW Barents Sea). 9 subsamples of sediment cores were collected during different years (2013-2016) in the Kveithola Trough, a glacially carved system in the NW Barents Sea. Cores were retrieved using a multi-corer (MUC) and a giant box-corer (GBC) and the subcores for foraminiferal analyses were obtained using Plexiglas tubes inserted manually into the cores. These subcores were sliced at 0.5 cm intervals down to 2 cm sediment depth and then every 1 cm down to 10 cm. Two staining methods, Cell Tracker Green (CTG) and Rose Bengal (RB), were used to distinguish between living and dead individuals. Then, the fixed sediment samples were sieved through 63 and 150 μm mesh screens and preserved in 10 % borax-buffered formalin. Six species and 37 undescribed morphotypes were recognized and included in this image dataset. Relatively few species of soft-shelled, monothalamous foraminifera have been described compared to a much larger number of undescribed morphotypes recognised from across the marine realm. Few researchers study with their taxonomy because of the time and difficulties that morphological identification involves. In addition, because "soft", delicate monothalamids rarely fossilize, they are generally overlooked by micropaleontologists. However, they are abundant and diverse and represent an important faunal component of marine as well as freshwater ecosystems. Further information about these frequently overlooked protists will help to address important knowledge gaps and enhance our ability to manage and conserve the planet's resources responsibly. In particular, our image dataset highlights the importance of monothalamous soft-shelled foraminifera in this peculiar Arctic environment and contributes to the first species/morphotype checklist for the area. We hope it will serve to fill gaps in knowledge regarding the ecology and biodiversity of benthic foraminifera, helping users to identify monothalamids species and morphotypes in Arctic waters and beyond. This data article is associated with the research papers: "Benthic foraminiferal assemblages and environmental drivers along the Kveithola Trough (NW Barents Sea)" by [2].
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562152 | PMC |
http://dx.doi.org/10.1016/j.dib.2023.109603 | DOI Listing |
Biomed Phys Eng Express
January 2025
Chiba University Center for Frontier Medical Engineering, 1-33 Yayoi-cho, Inage-ku, Chiba, Chiba, 263-8522, JAPAN.
Traumatic injury remains a leading cause of death worldwide, with traumatic bleeding being one of its most critical and fatal consequences. The use of whole-body computed tomography (WBCT) in trauma management has rapidly expanded. However, interpreting WBCT images within the limited time available before treatment is particularly challenging for acute care physicians.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Science and Engineering, School of Computer Science, University of Hull, Hull, United Kingdom.
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. The technique leverages a feature extraction method called Derivative Level Thresholding to pinpoint suspicious regions within an image.
View Article and Find Full Text PDFCell Rep
January 2025
Department of Psychology, University of Oregon, Eugene, OR, USA.
More than a century of research shows that spaced learning improves long-term memory. However, there remains debate concerning why that is. A major limitation to resolving theoretical debates is the lack of evidence for how neural representations change as a function of spacing.
View Article and Find Full Text PDFJ Eur Acad Dermatol Venereol
January 2025
Pathology Department, IHP Group, Nantes, France.
Background: There is a need to improve risk stratification of primary cutaneous melanomas to better guide adjuvant therapy. Taking into account that haematoxylin and eosin (HE)-stained tumour tissue contains a huge amount of clinically unexploited morphological informations, we developed a weakly-supervised deep-learning approach, SmartProg-MEL, to predict survival outcomes in stages I to III melanoma patients from HE-stained whole slide image (WSI).
Methods: We designed a deep neural network that extracts morphological features from WSI to predict 5-y overall survival (OS), and assign a survival risk score to each patient.
Intensive Care Med
January 2025
Medical Intensive Care Unit, AP-HP, Saint-Louis Hospital, Paris-Cité University, INSERM UMR1342 Institut de Recherche Saint-Louis, Paris, France.
Purpose: Invasive pulmonary aspergillosis (IPA) is a life-threatening opportunistic infection in immunocompromised patients. The diagnosis is often made late, with mortality reaching 90% when mechanical ventilation is needed. We sought to develop and validate a risk prediction model for the diagnosis of IPA.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!