Therapeutic Potential of a Novel Vitamin D3 Oxime Analogue, VD1-6, with CYP24A1 Enzyme Inhibitory Activity and Negligible Vitamin D Receptor Binding

Abstract: The regulation of vitamin D3 actions in humans occurs mainly through the Cytochrome P450 24-hydroxylase (CYP24A1) enzyme activity. CYP24A1 hydroxylates both 25-hydroxycholecalciferol (25(OH)D3) and 1,25-dihydroxycholecalciferol (1,25(OH)2D3), which is the first step of vitamin D catabolism. An abnormal status of the upregulation of CYP24A1 occurs in many diseases, including chronic kidney disease (CKD). CYP24A1 upregulation in CKD and diminished activation of vitamin D3 contribute to secondary hyperparathyroidism (SHPT), progressive bone deterioration, and soft tissue and cardiovascular calcification. Previous studies have indicated that CYP24A1 inhibition may be an effective strategy to increase endogenous vitamin D activity and decrease SHPT. This study has designed and synthesized a novel C-24 O-methyloxime analogue of vitamin D3 (VD1-6) to have specific CYP24A1 inhibitory properties. VD1-6 did not bind to the vitamin D receptor (VDR) in concentrations up to 10-7 M, assessed by a VDR binding assay. The absence of VDR binding by VD1-6 was confirmed in human embryonic kidney HEK293T cultures through the lack of CYP24A1 induction. However, in silico docking experiments demonstrated that VD1-6 was predicted to have superior binding to CYP24A1, when compared to that of 1,25(OH)2D3. The inhibition of CYP24A1 by VD1-6 was also evident by the synergistic potentiation of 1,25(OH)2D3-mediated transcription and reduced 1,25(OH)2D3 catabolism over 24 h. A further indication of CYP24A1 inhibition by VD1-6 was the reduced accumulation of the 24,25(OH)D3, the first metabolite of 25(OH)D catabolism by CYP24A1. Our findings suggest the potent CYP24A1 inhibitory properties of VD1-6 and its potential for testing as an alternative therapeutic candidate for treating SHPT.Ali K. Alshabrawy, Yingjie Cui, Cyan Sylvester, Dongqing Yang, Emilio S. Petito, Kate R. Barratt, Rebecca K. Sawyer, Jessica K. Heatlie, Ruhi Polara, Matthew J. Sykes, Gerald J. Atkins, Shane M. Hickey, Michael D. Wiese, Andrea M. Stringer, Zhaopeng Liu, and Paul H. Anderso

Brain computer interface analysis using wavelet transforms and auto regressive coefficients

The idea of an EEG based BCI is to assist the people unable to communicate their thoughts due to neuromuscular disorders and hence affected by motor disabilities. The BCI helps them acting as an interface between the human mind and the computer. In this paper an offline analysis of the EEG data recorded from the C3 and C4 electrodes pertaining to motor activities was done. The data obtained was preprocessed with techniques like wavelet transform and linear predictive coding was applied to it to determine the auto regressive coefficients which are treated as feature vectors to train an artificial neural network for appropriate classification. The trained net was then subjected to testing of data from 140 random trials that were taken and the accuracy was determined. The efficiency of this approach was found to be 71.5%

Hard Equality Constrained Integer Knapsacks

We consider the following integer feasibility problem: "Given positive integer numbers a 0 ; a 1 ; : : : ; an ; with gcd(a 1 ; : : : ; an ) = 1 and a = (a 1 ; : : : ; an ), does there exist a vector x 2 Z 0 satisfying ax = a 0 ?" Some instances of this type have been found to be extremely hard to solve by standard methods such as branch-and-bound, even if the number of variables is as small as ten. We observe that not only the sizes of the numbers a 0 ; a 1 ; : : : ; an ; but also their structure, have a large impact on the difficulty of the instances. This particular structure enables us to derive a strong lower bound on the Frobenius number for these instances. Moreover, we demonstrate that the same structural characteristics that make the instances so difficult to solve by branch-and-bound make the solution of a certain reformulation of the problem almost trivial. We accompany our results by a small computational study