Publications by authors named "Liimatainen K"

Fungus-farming ants cultivate multiple lineages of fungi for food, but, because fungal cultivar relationships are largely unresolved, the history of fungus-ant coevolution remains poorly known. We designed probes targeting >2000 gene regions to generate a dated evolutionary tree for 475 fungi and combined it with a similarly generated tree for 276 ants. We found that fungus-ant agriculture originated ~66 million years ago when the end-of-Cretaceous asteroid impact temporarily interrupted photosynthesis, causing global mass extinctions but favoring the proliferation of fungi.

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This article is the 13th contribution in the Fungal Diversity Notes series, wherein 125 taxa from four phyla, ten classes, 31 orders, 69 families, 92 genera and three genera are treated, demonstrating worldwide and geographic distribution. Fungal taxa described and illustrated in the present study include three new genera, 69 new species, one new combination, one reference specimen and 51 new records on new hosts and new geographical distributions. Three new genera, (), ( genus ) and () are introduced based on distinct phylogenetic lineages and unique morphologies.

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Background: Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology to aid cancer research.

Methods: Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the models with associated quantitative features and full resolution serial section patches, and implementing the virtual reality application.

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Novel species of fungi described in this study include those from various countries as follows: , on soil, on leaves of on leaves of on leaves of sp., on soil, (incl. gen.

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This paper is a contribution to the current knowledge of taxonomy, ecology and distribution of South American (Pers.) Gray. is among the most widely distributed and species-rich basidiomycete genera occurring with South American and species are found in many distinct habitats, including shrublands and forests.

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As currently delineated, sect. is a polyphyletic assembly within subg. , encompassing glutinous and pigmented taxa.

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The focus of this paper is the North American species of in subg. . Eighteen species, including twelve new ones, and two tentative (aff.

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Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to assess protein localizations, with increasing demand of automated high throughput analysis methods to supplement the technical advancements in high throughput imaging. Here, we study the applicability of deep neural network-based artificial intelligence in classification of protein localization in 13 cellular subcompartments.

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Novel species of fungi described in this study include those from various countries as follows: , from marine sediment sand. , (incl. gen.

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3D printing has emerged as a popular technology in various biomedical applications. Physical models of anatomical structures concretize the digital representations and can be used for teaching and analysis. In this study we combine 3D histology with 3D printing, creating realistic physical models of tissues with hotspots of interest.

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We studied the South American species of section based on morphological and molecular data. Members of this group can easily be identified in the field because the basidiomata are small and -like with a bulbous stipe and the universal veil in most species forms a distinct volva at the base of the stipe. The phylogenetic delimitation of the clade was mostly in concordance with the earlier, morphology-based grouping of the South American taxa except that was resolved outside of the clade.

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Mushroom-forming fungi (Agaricomycetes) have the greatest morphological diversity and complexity of any group of fungi. They have radiated into most niches and fulfil diverse roles in the ecosystem, including wood decomposers, pathogens or mycorrhizal mutualists. Despite the importance of mushroom-forming fungi, large-scale patterns of their evolutionary history are poorly known, in part due to the lack of a comprehensive and dated molecular phylogeny.

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Background: Cell counting from cell cultures is required in multiple biological and biomedical research applications. Especially, accurate brightfield-based cell counting methods are needed for cell growth analysis. With deep learning, cells can be detected with high accuracy, but manually annotated training data is required.

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In this study, eight species of are recognized from Europe: , aff. 1, , cf, , . cf.

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In this study, we document and describe the new Cortinarius section Austroamericani. Our results reveal high species diversity within this clade, with a total of 12 recognized species. Of these, only C.

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In this study, 49 species of Hydnum are recognized worldwide. Twenty-two of them are described here as new species. Epitypes are proposed for H.

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is the largest genus of ectomycorrhizal fungi worldwide. Recent molecular studies have shown high levels of morphological homoplasy within the genus. Importantly, DNA phylogenies can reveal characteristics that have been either over- or underemphasized in taxonomic studies.

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Article Synopsis
  • The study explores the use of deep learning algorithms to enhance the detection of metastases in breast cancer patients' lymph node tissue sections, aiming to improve diagnostic accuracy and efficiency compared to traditional pathologist evaluations.
  • Conducted as part of the CAMELYON16 challenge, participants developed algorithms using a dataset of whole-slide images, and performance was assessed against a test set while also evaluating a group of pathologists under time constraints.
  • Results showed a wide range of algorithm effectiveness, with the area under the receiver operating characteristic curve varying from 0.556 to 0.994, indicating potential for high diagnostic accuracy with automated methods.
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Seven species of Cortinarius, subgenus Telamonia, section Colymbadini and /Flavobasilis, are reported from conifer forests in the mountains of western North America. They typically produce basidiomes in the spring and summer. Only one species, C.

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Digital pathology has led to a demand for automated detection of regions of interest, such as cancerous tissue, from scanned whole slide images. With accurate methods using image analysis and machine learning, significant speed-up, and savings in costs through increased throughput in histological assessment could be achieved. This article describes a machine learning approach for detection of cancerous tissue from scanned whole slide images.

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Five species of Cortinarius subgenus Callistei, are recognized in Europe and North America. Cortinarius callisteus, C. infucatus, and C.

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Different distance-based threshold selection approaches were used to assess and compare use of the internal transcribed spacer (ITS) region to distinguish among 901 Cortinarius species represented by >3000 collections. Sources of error associated with genetic markers and selection approaches were explored and evaluated using MOTUs from genus and lineage based-alignments. Our study indicates that 1%-2% more species can be distinguished by using the full-length ITS barcode as compared to either the ITS1 or ITS2 regions alone.

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Cortinarius is a species-rich and morphologically challenging genus with a cosmopolitan distribution. Many names have not been used consistently and in some instances the same species has been described two or more times under separate names. This study focuses on subg.

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DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments.

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