Antibiotic resistance and molecular typing among cockle (Anadara granosa) strains of Vibrio parahaemolyticus by polymerase chain reaction (PCR)-based analysis

Genomic DNA of Vibrio parahaemolyticus were characterized by antibiotic resistance, enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) and random amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR) analysis. These isolates originated from 3 distantly locations of Selangor, Negeri Sembilan and Melaka (East coastal areas), Malaysia. A total of 44 (n = 44) of tentatively V. parahaemolyticus were also examined for the presence of toxR, tdh and trh gene. Of 44 isolates, 37 were positive towards toxR gene; while, none were positive to tdh and trh gene. Antibiotic resistance analysis showed the V. parahaemolyticus isolates were highly resistant to bacitracin (92 %, 34/37) and penicillin (89 %, 33/37) followed by resistance towards ampicillin (68 %, 25/37), cefuroxime (38 %, 14/37), amikacin (6 %, 2/37) and ceftazidime (14 %, 5/37). None of the V. parahaemolyticus isolates were resistant towards chloramphenicol, ciprofloxacin, ceftriaxone, enrofloxacin, norfloxacin, streptomycin and vancomycin. Antibiogram patterns exhibited, 9 patterns and phenotypically less heterogenous when compared to PCR-based techniques using ERIC- and RAPD-PCR. The results of the ERIC- and RAPD-PCR were analyzed using GelCompare software. ERIC-PCR with primers ERIC1R and ERIC2 discriminated the V. parahaemolyticus isolates into 6 clusters and 21 single isolates at a similarity level of 80 %. While, RAPD-PCR with primer Gen8 discriminated the V. parahaemolyticus isolates into 11 clusters and 10 single isolates and Gen9 into 8 clusters and 16 single isolates at the same similarity level examined. Results in the presence study demonstrated combination of phenotypically and genotypically methods show a wide heterogeneity among cockle isolates of V. parahaemolyticus.     

On the estimation of average treatment effects with right-censored time to event outcome and competing risks

We are interested in the estimation of average treatment effects based on right-censored data of an observational study. We focus on causal inference of differences between t-year absolute event risks in a situation with competing risks. We derive doubly robust estimation equations and implement estimators for the nuisance parameters based on working regression models for the outcome, censoring, and treatment distribution conditional on auxiliary baseline covariates. We use the functional delta method to show that these estimators are regular asymptotically linear estimators and estimate their variances based on estimates of their influence functions. In empirical studies, we assess the robustness of the estimators and the coverage of confidence intervals. The methods are further illustrated using data from a Danish registry study.