Frequency of human toxocariasis in a rural population from Cajamarca, Peru determined by DOT-ELISA test

The aim of this study was to estimate the frequency of human toxocariasis in Cauday district, Cajamarca, Peru, using a dot-ELISA test. From June to October 2005, a total of 256 adult subjects were studied. Blood samples were collected for serology by a dot-ELISA test and for hematological examination. Parasitological examination was also carried out in stool samples to check cross-reactions in the dot-ELISA. The frequency observed was 44.92%, with a significant higher proportion of positivity in male subjects. From subjects with positive serology, 45.6% had respiratory symptoms, 40.44% abdominal pain, 32.35% hepatic symptoms, 14.7% cutaneous signs, 13.23% ocular manifestations, 43.38% eosinophilia, and all of these were statistically associated to serology. Among the population evaluated, 90.23% (231/256) were parasitized. From subjects with positive serology, 92.17% had at least one intestinal parasite and the most frequent were: Blastocystis hominis (68.38%), Giardia lamblia (28.68%), Hymenolepis nana (20.0%), Ascaris lumbricoides (15.65%), Entamoeba histolytica/E. dispar (13.24%), Cyclospora cayetanensis (4.41%), Cryptosporidium sp. (1.47%), Enterobius vermicularis (0.87%), Strongyloides stercoralis (0.87%), Taenia sp. (0.87%), and Trichuris trichiura (0.87%). The rate of false positives in the dot-ELISA test was improved by serum absorption each with A. suum antigens, with a decrease of cross-reactions. In conclusion, human toxocariasis is highly frequent in this population and some risk factors like dog/cat ownership, presence of pets within house, and previous history of geophagia were observed in the present study.

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.