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WQ Jiang
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AC Chang
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M Satoh
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Y Furuichi
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PP Tam
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RR Reddel
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We previously isolated a mammalian gene STC1 that encodes a glycoprotein related to stanniocalcin (STC), a fish hormone that plays a major role in calcium homeostasis. However, the mammalian STC1 gene is expressed in a variety of adult tissues in contrast to fish where STC is expressed only in one unique gland, the corpuscles of Stannius. This suggested that STC1 may have wider autocrine/paracrine functions in mammals. In the present study, using immunocytochemistry, we showed that STC1 protein is localized in the developing bone and muscle of the mouse fetus. During endochondral bone formation, STC1 is found principally in prechondrocytes and prehypertrophic chondrocytes. During intramembranous bone formation STC1 is present in the mesenchyme that is about to undergo ossification. STC1 is also found in the myocardiocytes of the developing heart and at all stages of differentiation from myoblasts to myotube formation in developing skeletal muscle. The specific localization of STC1 to chondrocytes and muscle cells suggests a role for this protein in chondrogenic and myogenic differentiation.

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L Strauss Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland

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A Junnila Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland

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A Wärri Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland

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M Manti Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden

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Y Jiang Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden

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E Löyttyniemi Department of Biostatistics, University of Turku, Turku, Finland

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E Stener-Victorin Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden

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M K Lagerquist Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden

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K Kukoricza Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland

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T Heinosalo Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland

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S Blom Aiforia Technologies Oyj, Pursimiehenkatu, Helsinki, Finland

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M Poutanen Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Turku Center for Disease Modeling, University of Turku, Turku, Finland
Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden

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The mouse estrous cycle is divided into four stages: proestrus (P), estrus (E), metestrus (M), and diestrus (D). The estrous cycle affects reproductive hormone levels in a wide variety of tissues. Therefore, to obtain reliable results from female mice, it is important to know the estrous cycle stage during sampling. The stage can be analyzed from a vaginal smear under a microscope. However, it is time-consuming, and the results vary between evaluators. Here, we present an accurate and reproducible method for staging the mouse estrous cycle in digital whole-slide images (WSIs) of vaginal smears. We developed a model using a deep convolutional neural network (CNN) in a cloud-based platform, Aiforia Create. The CNN was trained by supervised pixel-level multiclass semantic segmentation of image features from 171 hematoxylin-stained samples. The model was validated by comparing the results obtained by CNN with those of four independent researchers. The validation data included three separate studies comprising altogether 148 slides. The total agreement attested by the Fleiss kappa value between the validators and the CNN was excellent (0.75), and when D, E, and P were analyzed separately, the kappa values were 0.89, 0.79, and 0.74, respectively. The M stage is short and not well defined by the researchers. Thus, identification of the M stage by the CNN was challenging due to the lack of proper ground truth, and the kappa value was 0.26. We conclude that our model is reliable and effective for classifying the estrous cycle stages in female mice.

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