An extraction method for sampling small insect from vegetation

An optimized affordable DNA-extraction method from Salmonella enterica Enteritidis for PCR experiments

In diagnostic and research bacteriology settings with budget and staff restrictions, fast and cost-effective genome extraction methods are desirable. If not inactivated properly, cellular and/or environmental DNA nucleases will degrade genomic material during the extraction stage, and therefore might give rise to incorrect results in PCR experiments. When crude cell extracts, proteinase K–treat...

An Efficient Method For DNA Extraction From Paraffin Wax Embedded Tissues For PCR Amplification Of Human And Viral DNA

  Background and Objective: Formalin-fixed paraffin-embedded tissues are a valuable source of DNA for molecular studies. We designed and optimized an efficient procedure for DNA extraction from formalin-fixed paraffin embedded tissues. Materials and Methods: Seventy three blocks of cervical paraffin-embedded tissues were investigated. DNA was extracted using 45 minutes boiling in alkaline sol...

Insect Food Habits and Vegetation

I-41: Chorionic Villus Sampling (CVS): An Invasive Method for Prenatal Diagnosis

Background: Chorionic villus sampling(CVS) has a major role in prenatal diagnosis . It is an invasive diagnostic method in completion of primary prenatal screenings. This article is a report of our 8 years experience of CVS in Mashhad. Materials and Methods: We have done 1511 cases of invasive diagnostic procedure including 723 CVS which were included in our study and also 788 cases of amniocen...

AN ADAPTIVE IMPORTANCE SAMPLING-BASED ALGORITHM USING THE FIRST-ORDER METHOD FOR STRUCTURAL RELIABILITY

Monte Carlo simulation (MCS) is a useful tool for computation of probability of failure in reliability analysis. However, the large number of samples, often required for acceptable accuracy, makes it time-consuming. Importance sampling is a method on the basis of MCS which has been proposed to reduce the computational time of MCS. In this paper, a new adaptive importance sampling-based algorith...