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Biomedical subjects

M S Kung

Publications and source records attributed to M S Kung.

2 recordsLinked to original sources

Effect of long-term and short-term diabetes on the parathyroid hormone sensitive rat renal adenylate cyclase: correlation with vitamin D metabolism.

In short-term experiments, male Wistar rats were made diabetic for 10 days with a single injection of streptozotocin (65 mg/kg body weight). One group of diabetic rats was treated with insulin for 3 days prior to sacrifice. In long-term experiments, vitamin D replete or vitamin D depleted rats were made diabetic for 6 weeks. Criteria for diabetes were loss of weight, glycosuria (Tes-Tape), and hyperglycemia. In long-term diabetic rats the activity of renal mitochondrial 25-hydroxyvitamin D3 (25-(OH)D3) 1 alpha-hydroxylase was significantly decreased and that of 25-(OH)D3 24-hydroxylase increased. However, the parathyroid hormone (PTH) sensitive renal adenylate cyclase activity of diabetic rats was not different from that of the nondiabetic rats in either the vitamin D replete group or the vitamin D depleted group. On the other hand, the PTH-sensitive renal adenylate cyclase activity was significantly higher in short-term diabetic rats than in control and insulin-treated rats. These differences were observed at doses of 10(-8) to 10(-5) M of PTH. This study has demonstrated for the first time that there are differences in the PTH-sensitive adenylate cyclase response between long-term and short-term diabetic rats. The hypersensitivity to PTH of the renal adenylate cyclase observed in short-term diabetic rats probably represents a response to insulin deficiency during the early development of diabetes mellitus in the rats.

Adenylyl Cyclases↗

Statistical prediction of drug stability based on nonlinear parameter estimation.

The classical approach in Arrhenius prediction of drug stability uses two sequential steps of linear regression involving (a) a function of drug content versus time to obtain the rate constants (k) at several elevated temperatures and (b) the relationship of logarithm of mean k versus reciprocal temperature to predict the room temperature rate constant and hence the shelf-life of the drug. Uncertainties in drug content determinations are often neglected in the second regression. The classical approach also provides a wide and unsymmetrical 95% confidence interval for the predicted shelf-life. We have developed equations which allow for direct statistical prediction of shelf-life using observed values of drug content, time, and temperature. Nonlinear regression analysis was employed to provide parameter estimates of drug shelf-life and the energy of activation. The developed approach was shown to provide good estimates of shelf-life with meaningful statistics of reactions over a wide range of stability and energetics, with various kinetic orders, with different levels of noise in the data, and with different types of data structure. Comparison between the nonlinear approach and the classical approach showed that the nonlinear approach provided better mean estimates of shelf-life with much smaller and more symmetrical 95% confidence intervals than the classical approach. The method appears sufficiently robust and wide-ranging as to be potentially applicable for the prediction of the drug stability of pharmaceutical products.

Chemistry, Pharmaceutical↗