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Outputs (71)

Association of season and herd size with somatic cell count for cows in Irish,English, and Welsh dairy herds (2013)
Journal Article
Archer, S. C., Mc Coy, F., Wapenaar, W., & Green, M. J. (2013). Association of season and herd size with somatic cell count for cows in Irish,English, and Welsh dairy herds. Veterinary Journal, 196(3), https://doi.org/10.1016/j.tvjl.2012.12.004

The aims of this study were to describe associations of time of year, and herd size with cow somatic cell count (SCC) for Irish, English, and Welsh dairy herds. Random samples of 497 and 493 Irish herds, and two samples of 200 English and Welsh (UK)... Read More about Association of season and herd size with somatic cell count for cows in Irish,English, and Welsh dairy herds.

Reliability and identification of aortic valve prolapse in the horse (2013)
Journal Article
Hallowell, G. D., & Bowen, M. (2013). Reliability and identification of aortic valve prolapse in the horse. BMC Veterinary Research, 9, Article 9. https://doi.org/10.1186/1746-6148-9-9

Background The objectives were to determine and assess the reliability of criteria for identification of aortic valve prolapse (AVP) using echocardiography in the horse. Results Opinion of equine cardiologists indicated that a long-axis view of... Read More about Reliability and identification of aortic valve prolapse in the horse.

Maternal undernutrition does not alter Sertoli cell numbers or the expression of key developmental markers in the mid-gestation ovine fetal testis (2013)
Journal Article
Andrade, L. P., Rhind, S. M., Rae, M. T., Kyle, C. E., Jowett, J., & Lea, R. G. (2013). Maternal undernutrition does not alter Sertoli cell numbers or the expression of key developmental markers in the mid-gestation ovine fetal testis. Journal of Negative Results in BioMedicine, 12(2), https://doi.org/10.1186/1477-5751-12-2

Background The aim of this study was to determine the effects of maternal undernutrition on ovine fetal testis morphology and expression of relevant histological indicators. Maternal undernutrition, in sheep, has been reported, previously, to alte... Read More about Maternal undernutrition does not alter Sertoli cell numbers or the expression of key developmental markers in the mid-gestation ovine fetal testis.

Membranes, molecules and biophysics: enhancing monocyte derived dendritic cell (MDDC) immunogenicity for improved anti-cancer therapy (2013)
Journal Article
Rauch, C., Ibrahim, H., & Foster, N. (2013). Membranes, molecules and biophysics: enhancing monocyte derived dendritic cell (MDDC) immunogenicity for improved anti-cancer therapy. Journal of cancer therapeutics & research, 2, Article 20. https://doi.org/10.7243/2049-7962-2-20

Despite great medical advancement in the treatment of cancer, cancer remains a disease of global significance. Chemotherapeutics can be very expensive and drain medical resources at a national level and in some cases the cost of treatment is so great... Read More about Membranes, molecules and biophysics: enhancing monocyte derived dendritic cell (MDDC) immunogenicity for improved anti-cancer therapy.

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning (2013)
Journal Article
Swan, A. L., Hillier, K. L., Smith, J. R., Allaway, D., Liddell, S., Bacardit, J., & Mobasheri, A. (2013). Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning. BMC Musculoskeletal Disorders, 14, Article 349. https://doi.org/10.1186/1471-2474-14-349

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiog... Read More about Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning.