Taeniasis due to Taenia solium is a disease with important public health consequences, since the larval stage is not exclusive to the animal intermediate, the pig, but also infects humans, causing neurocysticercosis. Early diagnosis and treatment of T. solium tapeworm carriers is important to prevent human cysticercosis. Current diagnosis based on microscopic observation of eggs lacks both sensitivity and specificity. In the present study, a nested-PCR assay targeting the Tso31 gene was developed for the specific diagnosis of taeniasis due to T. solium. Initial specificity and sensitivity testing was performed using stored known T. solium-positive and -negative samples. The assay was further analyzed under field conditions by conducting a case-control study of pretreatment stool samples collected from a population in an area of endemicity. Using the archived samples, the assay showed 97% (31/32) sensitivity and 100% (123/123) specificity. Under field conditions, the assay had 100% sensitivity and specificity using microscopy/enzyme-linked immunosorbent assay coproantigen testing as the gold standards. The Tso31 nested PCR described here might be a useful tool for the early diagnosis and prevention of taeniasis/cysticercosis.
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.
iHuman sapovirus has been shown to be one of the most important etiologies in pediatric patients with acute diarrhea. However, very limited data are available about the causative roles and epidemiology of sapovirus in community settings. A nested matched case-control study within a birth cohort study of acute diarrhea in a peri-urban community in Peru from 2007 to 2010 was conducted to investigate the attributable fraction (AF) and genetic diversity of sapovirus. By quantitative reverse transcription-realtime PCR (qPCR) sapovirus was detected in 12.4% (37/299) of diarrheal and 5.7% (17/300) of nondiarrheal stools (P ؍ 0.004). The sapovirus AF (7.1%) was higher in the second year (13.2%) than in the first year (1.4%) of life of children. Ten known genotypes and one novel cluster (n ؍ 5) within four genogroups (GI, GII, GIV, and GV) were identified by phylogenetic analysis of a partial VP1 gene. Further sequence analysis of the full VP1 gene revealed a possible novel genotype, tentatively named GII.8. Notably, symptomatic reinfections with different genotypes within the same (n ؍ 3) or different (n ؍ 5) genogroups were observed in eight children. Sapovirus exhibited a high attributable burden for acute gastroenteritis, especially in the second year of life, of children in a Peruvian community. Further large-scale studies are needed to understand better the global burden, genetic diversity, and repeated infections of sapovirus. Acute diarrhea is one of the most important causes of morbidity and mortality in pediatric populations, especially in developing countries. Rotavirus, norovirus, and other viruses are common causative etiological agents, and rotavirus accounts for about 440,000 child deaths annually (1), while norovirus is a leading cause of epidemic and sporadic acute diarrhea (2). Currently a rotavirus vaccination program has been implemented in 80 countries as a part of national immunization programs (http://sites.path.org /rotavirusvaccine/rotavirus-vaccines/#global-intro). It successfully reduced the number of hospitalizations and deaths due to acute gastroenteritis (3, 4) and is cost-effective (5). Norovirus has now replaced rotavirus as the leading cause of medically attended acute diarrhea in pediatric populations (6, 7), and sapovirus, belonging to a separate genus of the Caliciviridae family, has been reported as the second most commonly detected virus after norovirus in children with acute diarrhea where rotavirus vaccination was implemented (8, 9). In addition, reports on sapovirus outbreaks across all age groups have increased in South Asia, Europe, and North America recently (10)(11)(12)(13)(14).The genome of sapovirus consists of a positive-sense, singlestranded RNA with two open reading frames (ORFs) (12). ORF1 encodes the nonstructural proteins and a major capsid protein, VP1, and ORF2 encodes a protein whose function is still unknown (12). Like for norovirus, multiple genetic clusters of human sapovirus have been reported, including four genogroups (GI, GII, GIV, and GV) with 17 gen...
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