Morphometric analysis of the spinal cord of the Sus scrofa (large white and landrace crossbreed).
Omowumi Femi-AkinlosotuFunmilayo Eniola OlopadeOluwaseun Ahmed MustaphaAdejoke AdekanmbiJames Olukayode OlopadePublished in: Anatomia, histologia, embryologia (2022)
The incidence of spinal cord (SC) injury in developed and undeveloped countries is alarming. The pig (Sus scrofa) has been recommended as a suitable research model for translational studies because of its morphophysiological similarities of organ systems with humans. There is a dearth of information on the SC anatomy of the large white and landrace crossbreed (LW-LC) pigs. We therefore aim to describe the gross morphology and morphometry of its SC. Twelve juvenile LW-LC pigs (six males and six females) were used. The skin and epaxial muscles were dissected to expose the vertebral column. The SC was carefully harvested by laminectomy, and 13 gross SC morphometric parameters were evaluated. Thirty-three spinal nerves were seen emanating from either side of the SC by means of dorsal and ventral spinal roots. The overall average of SC length and weight was 36.23 ± 1.01 cm and 16.60 ± 0.58 g, respectively. However, the mean SC length and weight were higher in females compared with males, with SC weight being statistically significant. A positive relationship between SC length and weight was significant for males (p = 0.0435) but not for females (p = 0.42). Likewise, the strength of the relationship between SC length and weight was significant in males (r = 0.82) but not significant in females (r = 0.41). Baseline data for the morphometric features of the spinal cord in the LW-LC pigs were generated, which will contribute to the knowledge of this species anatomy and useful information on regional anaesthesia that should further strengthen the drive in adopting the pig as a suitable research model for biomedical research.
Keyphrases
- spinal cord
- body mass index
- neuropathic pain
- physical activity
- weight loss
- spinal cord injury
- weight gain
- healthcare
- mass spectrometry
- body weight
- machine learning
- high resolution
- simultaneous determination
- deep learning
- liquid chromatography
- bone mineral density
- social media
- body composition
- big data
- artificial intelligence