Occurrence and molecular characterization of on rice in Central Punjab, Pakistan.

threatens global rice production, yet is understudied for many areas where it is cultivated. To better understand the prevalence and incidence of in central Punjab, Pakistan, we carried out field surveys of rice fields in the districts of Faisalabad and Chiniot. isolates were recovered from soil and root samples and identified on the basis of perineal patterns and rDNA ITS-based sequencing.

Genetic Variability among Different Populations of Root Knot Nematodes Based on Their Encumbrance Response to Isolates Using PCR-RFLP.

A great variable response was observed when PP-3 and PP-J encumbered with 116 populations of root knot nematode (RKN) at two different temperatures (25 ± 2°C and 30 ± 2°C) and concentrations (10 and 10 spores/ml). The PCR reaction amplified intergenic region between cytochrome oxidase subunit II gene (COII) and large subunit of rRNA gene (lrRNA) of the mitochondrial genome of different RKN species. The primer C2F3 and 1108 identified with the highest frequency (52.

Artificial neural network prediction of the patterns of deposition of polydisperse aerosols within human lungs.

For optimum therapeutic response from drug administered to the lungs, it is paramount that the aerosolised drug is able to deposit in the lower airways. The filtering characteristics of the respiratory tract, however, make this a particularly challenging task. Computational tools afford a cost-effective means of studying the problem, and here we report on the development of a rapid and reliable method for predicting the pattern of deposition of polydisperse aerosols within human lungs using artificial neural networks (ANNs).

Artificial neural network prediction of aerosol deposition in human lungs.

Purpose: To develop a rapid and reliable method for predicting the pattern of aerosol particle deposition within the human lungs, using artificial neural networks (ANNs).

Methods: Experimental data from the literature were used to train multi-layer perceptron (MLP) networks to allow for prediction of regional and total aerosol particle deposition patterns in human lungs. These data covered particle sizes in the range 0.