2020
DOI: 10.1007/s00441-020-03310-w
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Improvement in identification of pro-estrous mice by using a novel method of detecting vaginal mucous cells

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Cited by 8 publications
(4 citation statements)
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“…Several attempts have been made to develop rapid, objective methods, particularly for use in mice. These include using non-stained smear material ( 27 , 40 ), modifications to staining methods ( 41 ) and application of deep learning technology for classification of smears ( 42 ). Alternatives to vaginal cytology have been proposed based on gross examination of the vaginal opening ( 43 ), changes in skin temperature due to activation of brown adipose tissue ( 44 ) and variations in vaginal wall impedence ( 45 ).…”
Section: Introductionmentioning
confidence: 99%
“…Several attempts have been made to develop rapid, objective methods, particularly for use in mice. These include using non-stained smear material ( 27 , 40 ), modifications to staining methods ( 41 ) and application of deep learning technology for classification of smears ( 42 ). Alternatives to vaginal cytology have been proposed based on gross examination of the vaginal opening ( 43 ), changes in skin temperature due to activation of brown adipose tissue ( 44 ) and variations in vaginal wall impedence ( 45 ).…”
Section: Introductionmentioning
confidence: 99%
“…östrus fazı öncesi dönemden elde edilen smear örneklerinde, vajen epitelinin yüzeyini kaplayan mukus hücrelerine odaklanarak, bu hücrelerin PAS ve Alcian blue ile boyandığını göstermişlerdir. Optimum çiftleşme zamanı için Alcian blue ve PAS ile boyalı preparatların, Giemsa boyasına göre daha doğru sonuçlar verdiğini iddia etmişlerdir (21). Spontan ovulasyonla elde edilen oositleri değerlendiren bir çalışmada, Toluidin mavisi kullanarak, smearde geniş kornifiye epitelin gözlendiği aşamada denekleri sakrifiye edip tuba uterinanın ampulla bölgesinden oosit elde ettiklerini belirtmişlerdir (13) (Şekil 3).…”
Section: öStrus Döngüsünde çEvresel Etkenlerunclassified
“…Estrus smears are unambiguous, whereas smears at other times are variable in cell composition (Raimondi et al, 2022). Stages other than estrus are traditionally defined by subtle, nuanced features of cytology that require a trained eye regardless of whether qualitative (Cora et al 2015;OECD, 2008;Sugiyama et al, 2021) or semi-quantitative (Hubscher et al, 2005;Paccola et al, 2013) criteria are used. Recently, machine learning tools have been developed to assist in staging cytology smears and, interestingly, these tools most readily detect the estrus stage (Sano et al, 2020;Wolcott et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…Stages other than estrus are traditionally defined by subtle, nuanced features of cytology that require a trained eye regardless of whether qualitative (Cora et al. 2015; OECD, 2008; Sugiyama et al., 2021) or semi‐quantitative (Hubscher et al., 2005; Paccola et al., 2013) criteria are used.…”
Section: Introductionmentioning
confidence: 99%