KARIN KIRCHGATTER
Projetos de Pesquisa
Unidades Organizacionais
LIM/49 - Laboratório de Protozoologia, Hospital das Clínicas, Faculdade de Medicina - Líder
4 resultados
Resultados de Busca
Agora exibindo 1 - 4 de 4
- Evolutionary ecology, taxonomy, and systematics of avian malaria and related parasites(2020) FECCHIO, Alan; CHAGAS, Carolina R. F.; BELL, Jeffrey A.; KIRCHGATTER, KarinHaemosporidian parasites of the genera Plasmodium, Leucocytozoon, and Haemoproteus are one of the most prevalent and widely studied groups of parasites infecting birds. Plasmodium is the most well-known haemosporidian as the avian parasite Plasmodium relictum was the original transmission model for human malaria and was also responsible for catastrophic effects on native avifauna when introduced to Hawaii. The past two decades have seen a dramatic increase in research on avian haemosporidian parasites as a model system to understand evolutionary and ecological parasite-host relationships. Despite haemosporidians being one the best studied groups of avian parasites their specialization among avian hosts and variation in prevalence amongst regions and host taxa are not fully understood. In this review we focus on describing the current phylogenetic and morphological diversity of haemosporidian parasites, their specificity among avian and vector hosts, and identifying the determinants of haemosporidian prevalence among avian species. We also discuss how these parasites might spread across regions due to global climate change and the importance of avian migratory behavior in parasite dispersion and subsequent diversification.
- The genetic diversity of Plasmodium malariae and Plasmodium brasilianum from human, simian and mosquito hosts in Brazil(2012) GUIMARAES, L. O.; BAJAY, M. M.; WUNDERLICH, G.; BUENO, M. G.; ROEHE, F.; CATAO-DIAS, J. L.; NEVES, A.; MALAFRONTE, R. S.; CURADO, I.; KIRCHGATTER, K.Plasmodium malariae is a protozoan parasite that causes malaria in humans and is genetically indistinguishable from Plasmodium brasilianum, a parasite infecting New World monkeys in Central and South America. P. malariae has a wide and patchy global distribution in tropical and subtropical regions, being found in South America, Asia, and Africa. However, little is known regarding the genetics of these parasites and the similarity between them could be because until now there are only a very few genomic sequences available from simian Plasmodium species. This study presents the first molecular epidemiological data for P. malariae and P. brasilianum from Brazil obtained from different hosts and uses them to explore the genetic diversity in relation to geographical origin and hosts. By using microsatellite genotyping, we discovered that of the 14 human samples obtained from areas of the Atlantic forest, 5 different multilocus genotypes were recorded, while in a sample from an infected mosquito from the same region a different haplotype was found. We also analyzed the longitudinal change of circulating plasmodial genetic profile in two untreated non-symptomatic patients during a 12-months interval. The circulating genotypes in the two samples from the same patient presented nearly identical multilocus haplotypes (differing by a single locus). The more frequent haplotype persisted for almost 3 years in the human population. The allele Pm09-299 described previously as a genetic marker for South American P. malariae was not found in our samples. Of the 3 non-human primate samples from the Amazon Region, 3 different multilocus genotypes were recorded indicating a greater diversity among isolates of P. brasilianum compared to P. malariae and thus, P. malariae might in fact derive from P. brasilianum as has been proposed in recent studies. Taken together, our data show that based on the microsatellite data there is a relatively restricted polymorphism of P. malariae parasites as opposed to other geographic locations.
- Influence of polymorphisms in toll-like receptors (TLRs) on malaria susceptibility in low-endemic area of the Atlantic Forest, Sao Paulo, Brazil(2018) GUIMARAES, Lilian O.; FERNANDES, Francisco; MONTEIRO, Eliana F.; CURADO, Izilda; HOLCMAN, Marcia M.; WUNDERLICH, Gerhard; SANTOS, Sidney E.; SOLER, Julia M.; KIRCHGATTER, KarinIn low-endemic areas for malaria transmission, asymptomatic individuals play an important role as reservoirs for malarial infection. Understanding the dynamics of asymptomatic malaria is crucial for its efficient control in these regions. Genetic host factors such as Toll-like receptor CUR) polymorphisms may play a role in the maintenance or elimination of infection. In this study, the effect of TLR polymorphisms on the susceptibility to malaria was investigated among individuals living in the Atlantic Forest of Sao Paulo, Southern Brazil. A hundred and ninety-five Brazilian individuals were enrolled and actively followed up for malaria for three years. Twenty-four polymorphisms in five toll-like receptor (TLR) genes were genotyped by RFLP, direct sequencing or fragment analysis. The genotypes were analyzed for the risk of malaria. Ongoing Plasmodium vivax or P. malaria infection, was identified by the positive results in PCR tests and previous P. vtvax malaria, was assumed when antiplasmodial antibodies against PvMSP1(19) were detected by ELISA. An evaluation of genomic ancestry was conducted using biallelic ancestry informative markers and the results were used as correction in the statistical analysis. Nine SNPs and one microsatellite were found polymorphic and three variant alleles in TLR genes were associated to malaria susceptibility. The regression coefficient estimated for SNP TLR9.-1237.T/C indicated that the presence of at least one allele C increased, on average, 2.3 times the malaria odds, compared to individuals with no allele C in this SNP. However, for individuals with the same sex, age and household, the presence of at least one allele C in SNP TLR9.-1486.T/C reduced, on average, 1.9 times the malaria odds, compared to individuals with no allele C. Moreover, this allele C plus an S allele in TLR6.P249S in individuals with same sex, age and ancestry, reduced, on average, 4.4 times the malaria odds. Our findings indicate a significant association of TLR9.-1237.T/C gene polymorphism with malarial infection and contribute to a better knowledge of the role of TLRs in malaria susceptibility in an epidemiological setting different from other settings.
- Integrating artificial intelligence and wing geometric morphometry to automate mosquito classification(2024) LIMA, Vinicio Rodrigues de; MORAIS, Mauro Cesar Cafundo de; KIRCHGATTER, KarinMosquitoes (Diptera: Culicidae) comprise over 3500 global species, primarily in tropical regions, where the females act as disease vectors. Thus, identifying medically significant species is vital. In this context, Wing Geometric Morphometry (WGM) emerges as a precise and accessible method, excelling in species differentiation through mathematical approaches. Computational technologies and Artificial Intelligence (AI) promise to overcome WGM challenges, supporting mosquito identification. AI explores computers' thinking capacity, originating in the 1950s. Machine Learning (ML) arose in the 1980s as a subfield of AI, and deep Learning (DL) characterizes ML's subcategory, featuring hierarchical data processing layers. DL relies on data volume and layer adjustments. Over the past decade, AI demonstrated potential in mosquito identification. Various studies employed optical sensors, and Convolutional Neural Networks (CNNs) for mosquito identification, achieving average accuracy rates between 84 % and 93 %. Furthermore, larval Aedes identification reached accuracy rates of 92 % to 94 % using CNNs. DL models such as ResNet50 and VGG16 achieved up to 95 % accuracy in mosquito identification. Applying CNNs to georeference mosquito photos showed promising results. AI algorithms automated landmark detection in various insects' wings with repeatability rates exceeding 90 %. Companies have developed wing landmark detection algorithms, marking significant advancements in the field. In this review, we discuss how AI and WGM are being combined to identify mosquito species, offering benefits in monitoring and controlling mosquito populations.