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Camila N Ortiz Department of Basic Sciences, Ponce Health Sciences University, Ponce Research Institute, Ponce, Puerto Rico, USA

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Annelyn Torres-Reverón DHR Health Institute for Research and Development, Edinburg, Texas, USA

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Caroline B Appleyard Department of Basic Sciences, Ponce Health Sciences University, Ponce Research Institute, Ponce, Puerto Rico, USA
Department of Internal Medicine, Ponce Health Sciences University, Ponce, Puerto Rico, USA

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using a metabolomics-based approach to provide a better understanding of the pathophysiology and potentially mine this information for early diagnosis of endometriosis ( Dutta et al. 2012 , Ghazi et al. 2016 , Dutta et al. 2018 , Li et al

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Emmanuel Amabebe Academic Unit of Reproductive and Developmental Medicine, Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK

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Steven Reynolds Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK

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Dilly O C Anumba Academic Unit of Reproductive and Developmental Medicine, Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK

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spectroscopy . Metabolomics 12 67. ( https://doi.org/10.1007/s11306-016-0985-x ) 27065760 Ansari A Lee H You YA Jung Y Park S Kim SM Hwang GS Kim YJ 2020 Identification of potential biomarkers in the cervicovaginal fluid by metabolic

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Steven Reynolds Imaging Sciences, Department of Immunity, Infection and Cardiovascular Disease, University of Sheffield, Royal Hallamshire Hospital, Sheffield, UK

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Sarah J Calvert Department of Oncology and Metabolism, University of Sheffield, The Jessop Wing, Tree Root Walk, Sheffield, UK

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Stephen J Walters School of Health Related Research, University of Sheffield, Regent Court, Sheffield, UK

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Martyn N Paley Imaging Sciences, Department of Immunity, Infection and Cardiovascular Disease, University of Sheffield, Royal Hallamshire Hospital, Sheffield, UK

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Allan A Pacey Department of Oncology and Metabolism, University of Sheffield, The Jessop Wing, Tree Root Walk, Sheffield, UK

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to monitor temporal changes in sperm metabolomes as a result of, for example, capacitation. Furthermore, metabolomics could be used in clinical analysis, where once a metabolomic assessment had been made, the same sperm could be used in assisted

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Noof Abdulrahman Alrabiah School of Agriculture and Food Science, University College Dublin, Ireland
Biological Sciences Department, College of Science, King Faisal University, Al Ahsa, Saudi Arabia

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Constantine A Simintiras School of Animal Sciences, Agricultural Center, Louisiana State University, Baton Rouge, Louisiana, USA

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Alexander C O Evans School of Agriculture and Food Science, University College Dublin, Ireland

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Patrick Lonergan School of Agriculture and Food Science, University College Dublin, Ireland

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Trudee Fair School of Agriculture and Food Science, University College Dublin, Ireland

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biochemical profile of bovine FF with a particular emphasis on the usefulness of the FF metabolomic profile as a non-invasive predictor of bovine oocyte developmental potential ( Fair 2014 ). The fatty acid and amino acid profiles of bovine FF were reported to

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Kirsten S Wilson MRC Centre for Reproductive Health, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

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Desheng Li Key Laboratory of SFGA on Conservation Biology of Rare Animals in The Giant Panda National Park, China Conservation and Research Centre for the Giant Panda (CCRCGP), DuJiangYan City, Sichuan Province, China

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Iain Valentine Zoocraft Ltd., Scotland, UK

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Alan McNeilly MRC Centre for Reproductive Health, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

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Simon Girling RZSS Edinburgh Zoo, Edinburgh, UK

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Rengui Li Key Laboratory of SFGA on Conservation Biology of Rare Animals in The Giant Panda National Park, China Conservation and Research Centre for the Giant Panda (CCRCGP), DuJiangYan City, Sichuan Province, China

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Yingmin Zhou Key Laboratory of SFGA on Conservation Biology of Rare Animals in The Giant Panda National Park, China Conservation and Research Centre for the Giant Panda (CCRCGP), DuJiangYan City, Sichuan Province, China

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Lynn Vanhaecke Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium

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W Colin Duncan MRC Centre for Reproductive Health, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

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Jella Wauters Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
Leibniz Institute for Zoo and Wildlife Research, Department Reproduction Biology, Berlin, Germany

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Graphical abstract

Abstract

Giant pandas are mono-estrus seasonal breeders, with the breeding season typically occurring in the spring. Successful fertilization is followed by an embryonic diapause, of variable length, with birth in the late summer/autumn. There is a need for additional understanding of giant panda reproductive physiology, and the development of enhanced biomarkers for impending proestrus and peak fertility. We aimed to determine the utility of non-invasive androgen measurements in the detection of both proestrus and estrus. Urine from 20 cycles (−40 days to +10 days from peak estrus) from 5 female giant pandas was analyzed for estrogen, progestogens and androgens (via testosterone and DHEA assays), and hormone concentrations were corrected against urinary specific gravity. Across proestrus, estrogens increased while progestogens and androgens decreased – at the point of entry into proestrus, androgens (as detected by the testosterone assay) decreased prior to progestogens and gave 4 days advanced warning of proestrus. At the time of peak estrus, androgens (as detected by the DHEA assay) were significantly increased at the time of the decrease in estrogen metabolites from the peak, acting as an alternative confirmatory indicator of the fertile window. This novel finding allows for enlargement of the preparative window for captive breeding and facilitates panda management within breeding programmes. Androgens allow an enhanced monitoring of giant panda estrus, not only advancing the warning of impending proestrus, but also prospectively identifying peak fertility.

Lay summary

Giant pandas have one chance at pregnancy per year. The 2-day fertile window timing varies by year and panda. This is monitored by measuring the level of estrogens in the urine, which increase, indicating an upcoming fertile period. After 1–2 weeks of increase, estrogens peak and fall, marking the optimal fertile time. We tested other hormones to see if we can predict the fertile window in advance, and the specific fertile time with more accuracy. In 20 breeding seasons from 5 females, we found androgens, usually thought of as male hormones, had an important role. Testosterone gives 4 days advanced warning of estrogens increasing. DHEA identified peak estrogen and the fertile time before needing to see a confirmed decrease in estrogen itself. Therefore, androgens help improve monitoring of the giant panda breeding season, giving early warning of fertility, key in facilitating captive breeding and giant panda conservation.

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Rolando Pasquariello Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA
Colorado State University, Fort Collins, Colorado, USA

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Mingxiang Zhang Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA

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Jason R Herrick Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA
Omaha’s Henry Doorly Zoo and Aquarium, Omaha, Nebraska, USA

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Alison F Ermisch Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA

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John Becker Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA

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William B Schoolcraft Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA

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Jennifer P Barfield Colorado State University, Fort Collins, Colorado, USA

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Ye Yuan Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA

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Rebecca L Krisher Colorado Center for Reproductive Medicine, Lone Tree, Colorado, USA
Omaha’s Henry Doorly Zoo and Aquarium, Omaha, Nebraska, USA

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RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data . Analytical Chemistry 86 6812 – 6817 . ( https://doi.org/10.1021/ac501530d ) Broeckling CD Ganna A Layer M Brown K Sutton B Ingelsson

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S M O’Mahony Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
APC Microbiome Ireland, University College Cork, Cork, Ireland

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P Comizzoli Smithsonian’s National Zoo and Conservation Biology Institute, Washington, District of Columbia, USA

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animals. The integration of technologies to identify microbes and analyze their functions (including metagenomics, meta-transcriptomics, metabolomics, and mass spectrometry) will advance our understanding of the complex relationships between reproductive

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Hiroshi Kobayashi Department of Obstetrics and Gynecology, Nara Medical University, Kashihara, Japan
Department of Gynecology, Ms.Clinic MayOne, Kashihara, Japan

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Hiroshi Shigetomi Department of Obstetrics and Gynecology, Nara Medical University, Kashihara, Japan
Aska Ladies Clinic, Nara, Japan

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Shogo Imanaka Department of Obstetrics and Gynecology, Nara Medical University, Kashihara, Japan
Department of Gynecology, Ms.Clinic MayOne, Kashihara, Japan

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to controls. Metabolomics analysis revealed that citrate, alpha-ketoglutarate (α-KG), and succinate were elevated in endometriosis ( Jana et al. 2013 ) whereas malate was decreased ( Atkins et al. 2019 ). The cause for the elevated citrate, α

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Darren J X Chow Robinson Research Institute, School of Biomedicine, The University of Adelaide, Adelaide, Australia
Australian Research Council Centre of Excellence for Nanoscale Biophotonics, The University of Adelaide, Adelaide, Australia
Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, Australia

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Philip Wijesinghe SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, United Kingdom

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Kishan Dholakia Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, Australia
SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, United Kingdom
School of Biological Sciences, The University of Adelaide, Adelaide, Australia
Department of Physics, College of Science, Yonsei University, Seoul, South Korea

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Kylie R Dunning Robinson Research Institute, School of Biomedicine, The University of Adelaide, Adelaide, Australia
Australian Research Council Centre of Excellence for Nanoscale Biophotonics, The University of Adelaide, Adelaide, Australia
Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, Australia

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have a role in analysing data from non-invasive metabolomic and secretory profiles from the embryo during culture. Consequently, this may lead to improved culture media formulations and regimens. Studies using AI to predict embryo developmental

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Mary Ann Ottinger Department of Biology and Biochemistry, University of Houston, Houston, Texas, USA

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Shailaja Mani Department of Molecular & Cellular Biology and Neuroscience, Baylor College of Medicine, Houston, Texas, USA

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Sonja Krüger Ezemvelo KwaZulu-Natal Wildlife, Scientific Services, Queen Elizabeth Park, 1 Peter Brown Drive, Pietermaritzburg, South Africa
Centre for Functional Biodiversity, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa

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Brent Coverdale Ezemvelo KwaZulu-Natal Wildlife, Scientific Services, Queen Elizabeth Park, 1 Peter Brown Drive, Pietermaritzburg, South Africa

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Sandi Willows-Munro Centre for Functional Biodiversity, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa

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Leigh Combrink School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA

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domesticated birds encompass a wide array of species, including those grown for agricultural food production and pets. The domestic chicken has been extensively studied, including genomics, metabolomics, characterization of bacterial populations, effects of

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