Zinc status and peripheral nerve function in guinea pigs

Guinea pigs fed a diet low in zinc develop clinical signs of apparent neurological origin. The signs include abnormal posture and locomotion as well as hypersensitivity to touch. In this study, electrophysiological and biochemical measurements were made on sciatic nerves from zinc-deficient and repleted animals as well as on controls fed either ad libitum or restricted to maintain weight comparable to those consuming the deficient diet. Both in vivo and in vitro measurements showed decreased motor nerve conduction velocity (NCV) in nerves of deficient animals. A longitudinal study showed excellent correlation of NCV and severity of clinical signs. Nerves from zinc-deficient guinea pigs had decreased Na,K-ATPase activity, but the number of sodium channels, as determined by saxitoxin binding, was not affected. It was concluded that the clinical signs of neuropathy in zinc deficiency are associated with impaired NCV and decreased Na,K-ATPase activity of peripheral nerves. The zinc-deficient guinea pig provides a useful model to study the biochemical defect in a peripheral neuropathy.     

Procedures for comparing samples with multiple endpoints

Five procedures are considered for the comparison of two or more multivariate samples. These procedures include a newly proposed nonparametric rank-sum test and a generalized least squares test. Also considered are the following tests: ordinary least squares, Hotelling's T2, and a Bonferroni per-experiment error-rate approach. Applications are envisaged in which each variable represents a qualitatively different measure of response to treatment. The null hypothesis of no treatment difference is tested with power directed towards alternatives in which at least one treatment is uniformly better than the others. In all simulations the nonparametric procedure provided relatively good power and accurate control over the size of the test, and is recommended for general use. Alternatively, the generalized least squares procedure may also be useful with normally distributed data in moderate or large samples. A convenient expression for this procedure is obtained and its asymptotic relative efficiency with respect to the ordinary least squares test is evaluated.