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LINDA A. SCHULER
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G. L. FLICKINGER
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J. F. STRAUSS III
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SUMMARY

The lipid composition of immature rat ovaries was examined after induction of ovulation with pregnant mare serum gonadotrophin and human chorionic gonadotrophin and subsequent (7–8 days later) stimulation with 10 μg LH. Two hours after the administration of LH, there was a decrease of approximately 50% in the concentration of cholesteryl esters in the ovary. The percentages (by weight) of sterol esters containing stearate, linoleate, eicosatrienoate and arachidonate were reduced by LH treatment, whereas the percentage of the C24:4 acid increased. No changes were observed in either the concentrations or fatty acid composition of phospholipids and triglycerides. These observations suggest that the metabolism of cholesteryl esters is acutely affected by LH and that sterol esters bearing long-chain polyunsaturated fatty acids are preferentially mobilized. Liberation of these unsaturated fatty acyl moieties may have significant effects on metabolism in the ovarian cell.

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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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