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Development of an ovine efferent mammary lymphatic cannulation model with minimal tissue damage

Overview of attention for article published in BMC Veterinary Research, December 2016
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Title
Development of an ovine efferent mammary lymphatic cannulation model with minimal tissue damage
Published in
BMC Veterinary Research, December 2016
DOI 10.1186/s12917-016-0908-0
Pubmed ID
Authors

Hung-Hsun Yen, Elizabeth Washington, Wayne Kimpton, Evan Hallein, Joanne Allen, Silk Yu Lin, Stuart Barber

Abstract

Two mammary lymphatic cannulation models in sheep have been described with minimal use in the past 50 years. The purpose of this study was to investigate a new surgical technique to allow long term monitoring of mammary lymph flow and composition from the mammary glands, with rapid ewe recovery and minimal complications post-surgery. We developed a modified methodology for cannulating the efferent mammary lymphatic from the mammary lymph node with minimum tissue damage. Compared to the previous models, our method required only a small incision on the aponeurosis of the external abdominal oblique muscles and thus reduced the difficulties in suturing the aponeurosis. It allowed for lymph collection and assessment for at least one week post-surgery with concurrent milk collection. This method allows for good ewe recovery post-surgery and in vivo sampling of efferent mammary lymph from the mammary lymph nodes in real-time and comparison with milk parameters.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 2 18%
Professor 1 9%
Other 1 9%
Lecturer 1 9%
Student > Bachelor 1 9%
Other 2 18%
Unknown 3 27%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 4 36%
Immunology and Microbiology 1 9%
Medicine and Dentistry 1 9%
Design 1 9%
Unknown 4 36%