Innervation of supraclavicular adipose tissue: A human cadaveric study.

Functional brown adipose tissue (BAT) was identified in adult humans only in 2007 with the use of fluorodeoxyglucose positron emission tomography imaging. Previous studies have demonstrated a negative correlation between obesity and BAT presence in humans. It is proposed that BAT possesses the capacity to increase metabolism and aid weight loss. In rodents it is well established that BAT is stimulated by the sympathetic nervous system with the interscapular BAT being innervated via branches of intercostal nerves. Whilst there is evidence to suggest that BAT possesses beta-3 adrenoceptors, no studies have identified the specific nerve branch that carries sympathetic innervation to BAT in humans. The aim of this study was to identify and trace the peripheral nerve or nerves that innervate human BAT in the supraclavicular region. The posterior triangle region of the neck of cadaveric specimens were dissected in order to identify any peripheral nerve branches piercing and/or terminating in supraclavicular BAT. A previously undescribed branch of the cervical plexus terminating in a supraclavicular adipose depot was identified in all specimens. This was typically an independent branch of the plexus, from the third cervical spinal nerve, but in one specimen was a branch of the supraclavicular nerve. Histological analysis revealed the supraclavicular adipose depot contained tyrosine hydroxylase immunoreactive structures, which likely represent sympathetic axons. This is the first study that identifies a nerve branch to supraclavicular BAT-like tissue. This finding opens new avenues for the investigation of neural regulation of fat metabolism in humans.

Prediction of Skeletal Medial-Lateral for transfemoral ischial containment sockets.

Accurate measurement of the pelvis is critical for well-fitting and comfortable ischial containment sockets. The "Skeletal Medial-Lateral (ML)" is intrusive and unreliable to measure in vivo. This study aimed to determine how accurately the Skeletal ML could be predicted and to identify which measurements were significant predictors. Computed tomography scans were randomly sampled from a cadaveric database (n = 200). Inclusion criteria were age > 20 yr; lower-limb alignment that replicated the anatomical position; and no evidence of osteological trauma, implants, or bony growths. Multivariate linear regression models were developed to predict the Skeletal ML based on a suite of independent variables, including sex, body mass, and distance between pelvic landmarks. The regression model explained 76% of the variance in the Skeletal ML (p < 0.001). Variables that contributed significantly to the prediction of the Skeletal ML (p < 0.05) included body mass, sex, inter-greater trochanter distance, pelvic depth, and age. Significant predictors of the Skeletal ML dimension characterize variation in subcutaneous adipose tissue thickness and pelvic morphology. The Skeletal ML could be predicted with relatively small errors (standard error of the estimate = 7 mm) that could be easily and reliably adjusted during socket fitting. Further research is needed to test the predictive tool in a real-world setting.

Prediction of the skeletal medio-lateral dimension using non-invasive anthropometric measurements for the provision of ischial containment sockets: a pilot study.

BACKGROUND: Great emphasis is placed on the skeletal medio-lateral to maintain the normal adduction of the remnant femur and to ensure coronal plane stability in an ischial containment socket. Given the invasiveness of the skeletal medio-lateral measurement, an alternative approach using prediction based on non-invasive measures would be welcomed. OBJECTIVES: Determine the accuracy with which the skeletal medio-lateral dimension could be predicted using sex, stature, anterior-posterior dimension and iliofemoral angle. STUDY DESIGN: Cross-sectional. METHOD: Anthropometric measurements on 77 persons were recorded and used as input data into a standard multiple regression. RESULTS: The regression model explained 59% of the variance in skeletal medio-lateral (r(2) = 0.59) that was statistically significant (F(4,72) = 25.37, p = 0.000). Only sex contributed significantly to the prediction of skeletal medio-lateral (ß = 0.67, t = 6.15, p = 0.00). The degree of error associated with the regression model (sum of squared errors = 0.009) indicated that the actual skeletal medio-lateral could be predicted within ±18 mm in 95% of the cases. CONCLUSION: The regression model is not sufficiently accurate to predict skeletal medio-lateral for clinical purposes. Accuracy of the prediction could be improved with more accurate input data from computed tomography scans and use of other independent variables that explain the unique variance not already described by the participants' sex. Clinical relevance This pilot study demonstrates potential for the skeletal medio-lateral to be predicted using non-invasive anthropometric measurements. Given this proof of concept, future investigators should use more accurate input data from computed tomography scans and identify alternative independent variables that explain the variance in the skeletal medio-lateral not attributable to sex.