Morphological study of the antennal sensilla in Gerromorpha (Insecta: Hemiptera: Heteroptera)

The external morphology and distribution of the antennal sensilla of 21 species from five families of semiaquatic bugs (Gerromorpha) were examined using scanning electron microscopy. Nine main types were distinguished based on their morphological structure: sensilla trichoidea, sensilla chaetica, sensilla leaflike, sensilla campaniformia, sensilla coeloconica, sensilla ampullacea, sensilla basiconica, sensilla placoidea and sensilla bell-mouthed. The specific morphological structure of one type of sensilla (bell-mouthed sensilla) was observed only in Aquarius paludum. Several subtypes of sensilla are described, differentiated by number, location and type of sensillum characteristic for each examined taxon. The present study provides new data about the morphology and distribution of the antennal sensilla in Gerromorpha

A Single Gene Target of an ETS-Family Transcription Factor Determines Neuronal CO2-Chemosensitivity

Many animals possess neurons specialized for the detection of carbon dioxide (CO2), which acts as a cue to elicit behavioral responses and is also an internally generated product of respiration that regulates animal physiology. In many organisms how such neurons detect CO2 is poorly understood. We report here a mechanism that endows C. elegans neurons with the ability to detect CO2. The ETS-5 transcription factor is necessary for the specification of CO2-sensing BAG neurons. Expression of a single ETS-5 target gene, gcy-9, which encodes a receptor-type guanylate cyclase, is sufficient to bypass a requirement for ets-5 in CO2-detection and transforms neurons into CO2-sensing neurons. Because ETS-5 and GCY-9 are members of gene families that are conserved between nematodes and vertebrates, a similar mechanism might act in the specification of CO2-sensing neurons in other phyla

Evaluation of Spatially Targeted Strategies to Control Non-Domiciliated Triatoma dimidiata Vector of Chagas Disease

Chagas disease is one of the most important parasitic diseases in Latin America. Since the 1980's, many national and international initiatives have contributed to eliminate vectors developing inside human domiciles. Today's challenge is to control vectors that are non-adapted to the human domicile, but still able to transmit the parasite through regular short stay in the houses. Here, we assess the potential of different control strategies applied in specific spatial patterns using a mathematical model that reproduces the dynamic of dispersion of such ‘non-domiciliated’ vectors within a village of the Yucatan Peninsula, Mexico. We show that no single strategy applied in the periphery of the village, where the insects are more abundant, provides satisfying protection to the whole village. However, combining the use of insect screens in houses at the periphery of the village (to simultaneously fight insects dispersing from the garden and the forest), and the cleaning of the peri-domicile areas of the centre of the village (where sylvatic insects are absent), would provide a cost-effective control. This type of spatially mixed strategy offers a promising way to reduce the cost associated with the repeated interventions required to control non-domiciliated vectors that permanently attempt to infest houses

Characterization of the Dispersal of Non-Domiciliated Triatoma dimidiata through the Selection of Spatially Explicit Models

Chagas disease is one of the most important neglected diseases in Latin America. Although insecticides have been successfully sprayed to control domiciliated vector populations, this strategy has proven to be ineffective in areas where non-domiciliated vectors immigrating from peridomestic or sylvatic ecotopes can (re-)infest houses. The development of strategies for the control of non-domiciliated vectors has thus been identified by the World Health Organization as a major challenge. Such development primarily requires a description of the spatio-temporal dynamics of infestation by these vectors, and a good understanding of their dispersal. We combined for the first time extensive spatio-temporal data sets describing house infestation dynamics by Triatoma dimidiata inside one village, and spatially explicit population dynamics models. The models fitted and predicted remarkably the observed infestation dynamics. They thus provided both key insights into the dispersal of T. dimidiata in this area, and a suitable mathematical background to evaluate the efficacy of various control strategies. Interestingly, the observed and modelled patterns of infestation suggest that interventions could focus on the periphery of the village, where there is the highest risk of transmission. Such spatial optimization may allow for reducing the cost of control, compensating for repeated interventions necessary for non-domiciliated vectors