Association of UGT1A6 gene polymorphism with clinical outcome in pediatric epileptic patients on sodium valproate monotherapy

Pediatric epilepsy comprises chronic neurological disorders characterized by recurrent seizures. Sodium valproate is one of the common antiseizure medications used for treatment. Glucuronide conjugation is the major metabolic pathway of sodium valproate, carried out by the enzyme uridine 5'-diphosphate (UDP) glucuronosyl transferase (UGT) whose gene polymorphisms may alter the clinical outcome. The objective of this study was to assess the association between UGT1A6 genetic polymorphism and clinical outcome in terms of efficacy and tolerability in pediatric epileptic patients on sodium valproate monotherapy. Pediatric epileptic patients (n=65) aged 2-18 years receiving sodium valproate monotherapy for the past one month were included. Genetic polymorphism patterns of UGT1A6 (T19G, A541G, A552C) were evaluated by PCR-RFLP. Clinical outcome was seizure control during the 6 months observation period. Tolerability was measured by estimating the hepatic, renal, and other lab parameters. Out of 65 patients, TT (40%), TG (57%), and GG (3%) patterns were observed in UGT1A6 (T19G) gene, AA (51%), AG (40%), and GG (9%) in (A541G) gene, and AA (43%), AC (43%), and CC (14%) in (A552C) gene. No statistical difference in clinical outcome was found for different UGT1A6 genetic polymorphism patterns. We concluded that different patterns of UGT1A6 genetic polymorphism were not associated with the clinical outcome of sodium valproate in terms of efficacy and tolerability. Sodium valproate was well-tolerated among pediatric patients with epilepsy and can be used as an effective antiseizure medication.

Mapping infected cell phenotype

Quantitative modeling of the phenotypic changes in the host cell during the bacterial infection makes it possible to explore an empirical relation between the infection stages and the quantifiable host-cell phenotype. A statistically reliable model of this relation can facilitate therapeutic defense against threats due to natural and genetically engineered bacterium. In the preliminary experiment, we have collected several thousand cell images over a period of 72 h of infection with a 2-h sampling frequency that covers various stages of infection by Francisella tularenesis (Ft). Segmentation of macrophages in images was accomplished using a fully automatic, parallel region growing technique. Over two thousand feature descriptors for the host cell were calculated. Multidimensional scaling, followed by hierarchical clustering, was used to group the cells. Preliminary results show that the host-cell phenotype, as defined by the set of measureable features, groups into different classes that can be mapped to the stages of infection.

Estimating contrast transfer function and associated parameters by constrained non-linear optimization

The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.