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Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition. The approach presented here is based on the analysis of brightness distribution patterns present in rectangular segments (here called “characteristic vectors“) from the ultrasound digital images. In a first step we identified and eliminated the skin and subcutaneous tissue (fat and muscle) in lung ultrasound frames, and the “characteristic vectors”were analyzed using standard neural networks using artificial intelligence methods. We analyzed 60 lung ultrasound frames corresponding to 21 children under age 5 years (15 children with confirmed pneumonia by clinical examination and X-rays, and 6 children with no pulmonary disease) from a hospital based population in Lima, Peru. Lung ultrasound images were obtained using an Ultrasonix ultrasound device. A total of 1450 positive (pneumonia) and 1605 negative (normal lung) vectors were analyzed with standard neural networks, and used to create an algorithm to differentiate lung infiltrates from healthy lung. A neural network was trained using the algorithm and it was able to correctly identify pneumonia infiltrates, with 90.9% sensitivity and 100% specificity. This approach may be used to develop operator-independent computer algorithms for pneumonia diagnosis using ultrasound in young children. [ABSTRACT FROM AUTHOR]

The adult Taenia solium, the pork tapeworm, usually lives as a single worm in the small intestine of humans, its only known definitive host. Mechanisms of genetic variation in T. solium are poorly understood. Using three microsatellite markers previously reported [], this study explored the genetic variability of T. solium from cysts recovered from experimentally infected pigs. It then explored the genetic epidemiology and transmission in naturally infected pigs and adult tapeworms recovered from human carriers from an endemic rural community in Peru. In an initial study on experimental infection, two groups of three piglets were each infected with proglottids from one of two genetically different tapeworms for each of the microsatellites. After 7 weeks, pigs were slaughtered and necropsy performed. Thirty-six (92.3%) out of 39 cysts originated from one tapeworm, and 27 (100%) out of 27 cysts from the other had exactly the same genotype as the parental tapeworm. This suggests that the microsatellite markers may be a useful tool for studying the transmission of T. solium. In the second study, we analyzed the genetic variation of T. solium in cysts recovered from eight naturally infected pigs, and from adult tapeworms recovered from four human carriers; they showed genetic variability. Four pigs had cysts with only one genotype, and four pigs had cysts with two different genotypes, suggesting that multiple infections of genetically distinct parental tapeworms are possible. Six pigs harbored cysts with a genotype corresponding to one of the identified tapeworms from the human carriers. In the dendrogram, cysts appeared to cluster within the corresponding pigs as well as with the geographical origin, but this association was not statistically significant. We conclude that genotyping of microsatellite size polymorphisms is a potentially important tool to trace the spread of infection and pinpoint sources of infection as pigs spread cysts with a shared parental genotype. [ABSTRACT FROM AUTHOR]

Background: Infections with Taenia solium are the most common cause of adult acquired seizures worldwide, and are the leading cause of epilepsy in developing countries. A better understanding of the genetic diversity of T. solium will improve parasite diagnostics and transmission pathways in endemic areas thereby facilitating the design of future control measures and interventions. Microsatellite markers are useful genome features, which enable strain typing and identification in complex pathogen genomes. Here we describe microsatellite identification and characterization in T. solium, providing information that will assist in global efforts to control this important pathogen. Methods: For genome sequencing, T. solium cysts and proglottids were collected from Huancayo and Puno in Peru, respectively. Using next generation sequencing (NGS) and de novo assembly, we assembled two draft genomes and one hybrid genome. Microsatellite sequences were identified and 36 of them were selected for further analysis. Twenty T. solium isolates were collected from Tumbes in the northern region, and twenty from Puno in the southern region of Peru. The size-polymorphism of the selected microsatellites was determined with multi-capillary electrophoresis. We analyzed the association between microsatellite polymorphism and the geographic origin of the samples. Results: The predicted size of the hybrid (proglottid genome combined with cyst genome) T. solium genome was 111 MB with a GC content of 42.54%. A total of 7,979 contigs (>1,000 nt) were obtained. We identified 9,129 microsatellites in the Puno-proglottid genome and 9,936 in the Huancayo-cyst genome, with 5 or more repeats, ranging from mono- to hexa-nucleotide. Seven microsatellites were polymorphic and 29 were monomorphic within the analyzed isolates. T. solium tapeworms were classified into two genetic groups that correlated with the North/South geographic origin of the parasites. Conclusions/Significance: The availability of draft genomes for T. solium represents a significant step towards the understanding the biology of the parasite. We report here a set of T. solium polymorphic microsatellite markers that appear promising for genetic epidemiology studies. [ABSTRACT FROM AUTHOR]