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Pathogen-insect interaction candidate molecules for transmission-blocking control strategies of vector borne diseases

Overview of attention for article published in Salud Pública de México, December 2017
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Title
Pathogen-insect interaction candidate molecules for transmission-blocking control strategies of vector borne diseases
Published in
Salud Pública de México, December 2017
DOI 10.21149/8140
Pubmed ID
Authors

Federico Alonso Zumaya-Estrada, María Carmen Rodríguez, Mario Henry Rodríguez

Abstract

To analyze the current knowledge of pathogen-insect interactions amenable for the design of molecular-based control strategies of vector-borne diseases. We examined malaria, dengue, and Chagas disease pathogens and insect molecules that participate in interactions during their vectors infection. Pathogen molecules that participate in the insect intestine invasion and induced vector immune molecules are presented, and their inclusion in transmission blocking vaccines (TBV) and in genetically modify insect (GMI) vectors or symbiotic bacteria are discussed. Disruption of processes by blocking vector-pathogen interactions provides several candidates for molecular control strategies, but TBV and GMI efficacies are still limited and other secondary effects of GMI (improving transmission of other pathogens, affectation of other organisms) should be discarded.

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Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 19%
Researcher 8 14%
Student > Ph. D. Student 6 10%
Student > Bachelor 5 8%
Other 2 3%
Other 6 10%
Unknown 21 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 17%
Medicine and Dentistry 7 12%
Agricultural and Biological Sciences 7 12%
Nursing and Health Professions 4 7%
Immunology and Microbiology 3 5%
Other 6 10%
Unknown 22 37%