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256 results for “Aedes aegypti”
The midguts transcriptome of Aedes aegypti (Liverpool strain) females blood fed DENV2 NS1 versus those blood fed BSA
GEO Series GSE73967. Aedes aegypti. 6 samples. Type: Expression profiling by high throughput sequencing.
Differential gene expression analysis of cycle gene knockout Aedes aegypti mosquito
GEO Series GSE241953. Aedes aegypti. 48 samples. Type: Expression profiling by high throughput sequencing.
Multifaceted Functional Implications of an Endogenously Expressed tRNA Fragment in Vector Mosquito Aedes aegypti
GEO Series GSE101956. Aedes aegypti. 40 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Aedes aegypti circadian expression profiling
GEO Series GSE28010. Aedes aegypti. 12 samples. Type: Expression profiling by array.
Transcriptomic analysis of Aedes aegypti midgut epithelial cells upon heme exposure
GEO Series GSE141651. Aedes aegypti. 8 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomics of phagocytosis and melanization in Aedes aegypti.
GEO Series GSE4279. Aedes aegypti. 51 samples. Type: Expression profiling by array.
Transcriptomic analyses of Aedes aegypti cultured cells upon heme exposure
GEO Series GSE140752. Aedes aegypti. 33 samples. Type: Expression profiling by high throughput sequencing.
Effect of the noncoding RNA produced by ZIKA virus (ZIKV) on expression of Aedes aegypti genes
GEO Series GSE131827. Aedes aegypti. 9 samples. Type: Expression profiling by high throughput sequencing.
RNAseq analysis of blood-meal induced gene-expression changes in Aedes aegypti ovaries
GEO Series GSE152209. Aedes aegypti. 19 samples. Type: Expression profiling by high throughput sequencing.
Data from: Morbidity rate prediction of dengue hemorrhagic fever (DHF) using the support vector machine and the Aedes aegypti infection rate in similar climates and geographical areas
Background: In the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate parameters. However, climate factors can be unreliable and can lower the effectiveness of prediction when they are applied in locations where climate factors do not differ significantly, and thus, they cannot enhance the capability of the predictive model's learning algorithm. The purpose of this study was to improve a dengue surveillance system in areas with similar climate by exploiting the infection rate in the Aedes aegypti mosquito and using the support vector machine (SVM) technique for forecasting the dengue morbidity rate. Methods and Findings: We identified the study areas in three provinces (Nakhon Pathom, Ratchaburi, and Samut Sakhon) of central Thailand that were reported to have a high incidence of dengue outbreaks. Prior to being added to the model, the infection data of the dengue vector, Aedes aegypti, the climate parameters, and the population density were collected from various sources and standardized. This process ensured that the data were not overwhelmed by each other in terms of the distance measures and to enhance the model effectiveness. The proposed framework consisted of the following three major parts: 1) data integration, 2) model construction, and 3) model evaluation. We discovered that the Aedes aegypti female and larvae mosquito infection rates were significantly positively associated with the morbidity rate. Thus, the increasing infection rate of female mosquitoes and larvae led to a higher number of dengue cases, and the prediction performance increased when those predictors were integrated into a predictive model. The support vector machine (SVM), a machine learning technique, has been receiving attention in many research areas due to its remarkable generalization performance. In this research, we applied the SVM with the radial basis function (RBF) kernel, referred to as the SVM-R, to forecast the high morbidity rate and take precautions to prevent the development of pervasive dengue epidemics. The experimental results showed that the introduced parameters significantly increased the prediction accuracy to 88.37% when used on the test set data, and these parameters led to the highest performance compared to state-of-the-art forecasting models. Conclusions: The infection rates of the Aedes aegypti female mosq uitoes and larvae improved the morbidity rate forecasting efficiency better than the climate parameters used in classical frameworks. This approach is more reliable and practical for monitoring dengue outbreaks, particularly in locations with similar climates because it does not rely on only climate factors. In addition, we demonstrated that the SVM-R-based model has high generalization performance and obtained the highest prediction performance compared to classical models as measured by the accuracy, sensitivity, specificity, and mean absolute error (MAE).
Data from: Engineered action at a distance: blood-meal-inducible paralysis in Aedes aegypti
Background: Population suppression through mass-release of Aedes aegypti males carrying dominant-lethal transgenes has been demonstrated in the field. Where population dynamics show negative density-dependence, suppression can be enhanced if lethality occurs after the density-dependent (i.e. larval) stage. Existing molecular tools have limited current examples of such Genetic Pest Management (GPM) systems to achieving this through engineering 'cell-autonomous effectors' i.e. where the expressed deleterious protein is restricted to the cells in which it is expressed – usually under the control of the regulatory elements (e.g. promoter regions) used to build the system. This limits the flexibility of these technologies as regulatory regions with useful spatial, temporal or sex-specific expression patterns may only be employed if the cells they direct expression in are simultaneously sensitive to existing effectors, and also precludes the targeting of extracellular regions such as cell-surface receptors. Expanding the toolset to 'non-cell autonomous' effectors would significantly reduce these limitations. Methodology/Principal Findings: We sought to engineer female-specific, late-acting lethality through employing the Ae. aegypti VitellogeninA1 promoter to drive blood-meal-inducible, fat-body specific expression of tTAV. Initial attempts using pro-apoptotic effectors gave no evident phenotype, potentially due to the lower sensitivity of terminally-differentiated fat-body cells to programmed-death signals. Subsequently, we dissociated the temporal and spatial expression of this system by engineering a novel synthetic effector (Scorpion neurotoxin – TetO-gp67.AaHIT) designed to be secreted out of the tissue in which it was expressed (fat-body) and then affect cells elsewhere (neuro-muscular junctions). This resulted in a striking, temporary-paralysis phenotype after blood-feeding. Conclusions/Significance: These results are significant in demonstrating for the first time an engineered 'action at a distance' phenotype in a non-model pest insect. The potential to dissociate temporal and spatial expression patterns of useful endogenous regulatory elements will extend to a variety of other pest insects and effectors.
Data from: Deltamethrin resistance in Aedes aegypti results in treatment failure in Merida, Mexico
The operational impact of deltamethrin resistance on the efficacy of indoor insecticide applications to control Aedes aegypti was evaluated in Merida, Mexico. A randomized controlled trial quantified the efficacy of indoor residual spraying (IRS) against adult Ae. aegypti in houses treated with either deltamethrin (to which local Ae. aegypti expressed a high degree of resistance) or bendiocarb (to which local Ae. aegypti were fully susceptible) as compared to untreated control houses. All adult Ae. aegypti infestation indices during 3 months post-spraying were significantly lower in houses treated with bendiocarb compared to untreated houses (odds ratio <0.75; incidence rate ratio < 0.65) whereas no statistically significant difference was detected between the untreated and the deltamethrin-treated houses. On average, bendiocarb spraying reduced Ae. aegypti abundance by 60% during a 3-month period. Results demonstrate that vector control efficacy can be significantly compromised when the insecticide resistance status of Ae. aegypti populations is not taken into consideration.
Transcriptome of the hindgut of Aedes aegypti wild type females fed on sucrose ad libitum
GEO Series GSE301574. Aedes aegypti. 3 samples. Type: Expression profiling by high throughput sequencing.
Global transcriptome analysis of Aedes aegypti mosquitoes in response to Zika virus infection
GEO Series GSE102939. Aedes aegypti. 18 samples. Type: Expression profiling by high throughput sequencing.
Data from: Morbidity rate prediction of dengue hemorrhagic fever (DHF) using the support vector machine and the Aedes aegypti infection rate in similar climates and geographical areas
Open the record for dataset details and reuse information.
Data from: Deltamethrin resistance in Aedes aegypti results in treatment failure in Merida, Mexico
Open the record for dataset details and reuse information.
Data from: Engineered action at a distance: blood-meal-inducible paralysis in Aedes aegypti
Open the record for dataset details and reuse information.
Transcriptomic analysis of gnotobiotic Aedes aegypti mosquitoes
GEO Series GSE173472. Aedes aegypti. 48 samples. Type: Expression profiling by high throughput sequencing.
Aedes aegypti NeSt1 interacts with human CD47 to enhance Zika virus infectivity
GEO Series GSE239840. Homo sapiens. 64 samples. Type: Expression profiling by high throughput sequencing.
The effect of permethrin resistance on Aedes aegypti transcriptome following ingestion of Zika virus infected blood
GEO Series GSE118858. Aedes aegypti. 24 samples. Type: Expression profiling by high throughput sequencing.
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