146 research outputs found

    A Deep Insight into the Sialome of Rhodnius neglectus, a vector of chagas disease

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    Background Triatomines are hematophagous insects that act as vectors of Chagas disease. Rhodnius neglectus is one of these kissing bugs found, contributing to the transmission of this American trypanosomiasis. The saliva of hematophagous arthropods contains bioactive molecules responsible for counteracting host haemostatic, inflammatory, and immuneresponses. Methods/Principal Findings Next generation sequencing and mass spectrometry-based protein identification were performed to investigate the content of triatomine R. neglectus saliva.We deposited 4,230 coding DNA sequences (CDS) in GenBank. A set of 636 CDS of proteins of putative secretory nature was extracted from the assembled reads, 73 of them confirmed by proteomic analysis. The sialome of R. neglectus was characterized and serine protease transcripts detected. The presence of ubiquitous protein families was revealed, including lipocalins, serine protease inhibitors, and antigen-5. Metalloproteases, disintegrins, and odorant binding protein families were less abundant. Conclusions/Significance The data presented improve our understanding of hematophagous arthropod sialomes, and aid in understanding hematophagy and the complex interplay among vectors and their vertebrate hosts

    Método automático de clasificación de color en dientes humanos usando aprendizaje de máquina

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    Trabajo de InvestigaciónActualmente el proceso de identificación del color de los dientes para la fabricación de prótesis dentales es realizado manualmente por un experto que, utilizando un método de identificación visual, determina el color de las piezas dentales en la boca del paciente, usando guías de color como la VITA®. A pesar de que el método visual es el más utilizado para la identificación del color de dientes, este se ve afectado por distintas variables tales como: el cansancio del experto, la luminosidad en el ambiente, salud visual del especialista, entre otras que influyen en la identificación del color en los dientes. Los errores en la clasificación del color de los dientes pueden generar pérdidas de tiempo lo que implicaría en consecuencia sobrecostos que afectarían directamente al fabricante y la satisfacción final del cliente.1. Planteamiento del problema 2. Pregunta de investigación 3. Objetivos 4. Estado del arte 5. Marco de referencia 6. Alcances y limitaciones 7. Metodología 8. Diseño metodológico 9. Discusión y resultados 10. Conclusiones 11. Trabajos futuros 12. Bibliografía 13. ANEXOSPregradoIngeniero de Sistema

    Modeling Disease Vector Occurrence when Detection Is Imperfect: Infestation of Amazonian Palm Trees by Triatomine Bugs at Three Spatial Scales

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    Blood-sucking bugs of the genus Rhodnius are major vectors of Chagas disease. Control and surveillance of Chagas disease transmission critically depend on ascertaining whether households and nearby ecotopes (such as palm trees) are infested by these vectors. However, no bug detection technique works perfectly. Because more sensitive methods are more costly, vector searches face a trade-off between technical prowess and sample size. We compromise by using relatively inexpensive sampling techniques that can be applied multiple times to a large number of palms. With these replicated results, we estimate the probability of failing to detect bugs in a palm that is actually infested. We incorporate this information into our analyses to derive an unbiased estimate of palm infestation, and find it to be about 50% – twice the observed proportion of infested palms. We are then able to model the effects of regional, landscape, and local environmental variables on palm infestation. Individual palm attributes contribute overwhelmingly more than landscape or regional covariates to explaining infestation, suggesting that palm tree management can help mitigate risk locally. Our results illustrate how explicitly accounting for vector, pathogen, or host detection failures can substantially improve epidemiological parameter estimation when perfect detection techniques are unavailable
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