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41 results for “Culex mosquitoes”
Climate adaptation and genetic differentiation in the mosquito species Culex tarsalis
<p>The increasing prevalence of vector-borne diseases around the world highlights the pressing need for an in-depth exploration of the genetic and environmental factors that shape the adaptability and widespread distribution of mosquito populations. This research focuses on <em>Culex tarsalis</em>, a principal vector for various viral diseases including West Nile Virus (WNV). Through the development of a new reference genome and the examination of Restriction-Site Associated DNA sequencing (RAD-seq) data from over 300 individuals and 28 locations, we demonstrate that variables such as temperature, evaporation rates, and the density of vegetation significantly impact the genetic makeup of <em>Cx. tarsalis</em> populations. Among the alleles most strongly associated with environmental factors is a nonsynonymous mutation in a key gene related to circadian rhythms. These results offer new insights into the mechanisms of spread and adaptation in a key North American vector species, which is poised to become a growing health threat to both humans and animals in the face of ongoing climate change.</p>
Figure 2 in Culex quinquefasciatus predominance during integrated mosquito surveillance in an urban area of the Brazilian Amazon
Figure 2. Nasci Aspirator (A) and a plastic pot (B) with a screen (C) adapted for electric vacuuming. Open pot (D) and pot with a lid (E) in the nozzle of the aspirator.
Figure 1 in Culex quinquefasciatus predominance during integrated mosquito surveillance in an urban area of the Brazilian Amazon
Figure 1. Map of the study area, Porto Velho city in Rondônia State, Brazil, demonstrating the location of each residence of collect (represented by a black circle).
Fig. 3 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 3. Time of mosquito biting activity on infected or uninfected frogs. Mosquitoes that fed on infected frogs are represented by the solid line, and those that fed on uninfected frogs are represented by the dashed line. The top figure represents the time for each mosquito to land in trials where mosquitoes were allowed to feed to repletion (i.e., uninterrupted trials). A significantly higher proportion of mosquitoes that fed on infected frogs began to land later in the trial, compared to mosquitoes feeding on uninfected frogs. The bottom figure represents the time for each mosquito to land in trials where mosquitoes were allow to land but were removed before feeding (i.e., interrupted trials). A significant difference in the time for mosquitoes to land on infected or uninfected frogs was not observed in interrupted trials.
Fig. 4 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 4. Time between mosquito bites on infected and uninfected frogs. Mosquitoes that were allowed to feed are represented by a solid line. Mosquitoes that were aspirated off the frog after landing are represented by the dashed line. A significantly longer amount of time passed between the bite of one mosquito and the bite of the following mosquito during trials in which mosquitoes were allowed to feed on a frog, compared to trials where mosquitoes were removed before feeding.
Fig. 1 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 1. Number of mosquitoes that chose wild-caught frogs paired by different levels of infection. Each panel represents a pairing by infection level in green frogs. Each trial was repeated three times, and separate trials are shown by different shapes. Higher numbers of mosquitoes chose to land on wild-caught frogs with high infections of H. clamatae when paired with frogs with moderate infections or without infection. Infection level had a weakly significant effect on the number of mosquitoes that chose to land on a frog. UI = uninfected.
Fig. 2 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 2. Number of mosquitoes that chose laboratory-raised frogs that were uninfected or experimentally infected. Each panel represents a pairing of infected or uninfected green frogs. Each pairing was repeated four times and each trial is represented by a different shape. Infection level did not have a significant effect on the number of mosquitoes choosing to land on a frog.
Fig. 3. Maximum likelihood tree for Culex species showing the 5 clades representing 5 subgroups. Clade I in Mosquito identification and haemosporidian parasites detection in the enclosure of the African penguins (Spheniscus demersus) at the SANBI zoological garden
Fig. 3. Maximum likelihood tree for Culex species showing the 5 clades representing 5 subgroups. Clade I is the Trifilatus Subgroup (Mattingly and Rageau, 1958) for Cx. torrentium; Clade II and III are the Pipiens Complex; Clade IV the Theileri Subgroup (Sirivanakarn, 1976) for Cx. theileri; and Clade V is the Tarsalis (Edwards, 1932) for Cx. declaratory and Apicinus Subgroups (Edwards, 1932) for Cx. mollis. Lutzia sp. used as outgroups. Sequences from this study are indicated by asterisks (*).
Climate adaptation and genetic differentiation in the mosquito species <em>Culex tarsalis</em>
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Data from: Transinfection of Wolbachia wAlbB into Culex quinquefasciatus mosquitoes does not alter vector competence for Hawaiian avian malaria (Plasmodium relictum GRW4)
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Spatially explicit habitat selection: testing contagion and the ideal free distribution with culex mosquitoes
<p>Since its inception, attempts have been made to improve Ideal Free Distribution (IFD) Theory in order make it better fit real-world data. Spatial contagion is a newer ecological concept that suggests the perceived quality of a patch can be affected by the quality of its neighbor patches. Here, we present a series of experiments testing for potential contagion effects, examining how contagion can interact with the IFD, and determining whether spatial context affects assessment of habitat quality. First, we tested whether the presence of conspecific competitors negatively impacts oviposition habitat selection by female mosquitoes (<em>Culex restuans</em>). We then used a more complex spatial landscape to determine whether competition can create a spatial contagion effect. Finally, we examined whether the density of conspecifics can adjust the contagion effect of nutrient availability. We found that while females avoided patches containing conspecifics, there was no effect of competition/density on neighboring patches. Additionally, we found that resource availability was a significant predictor of where egg rafts were laid, but resource availability did not have a contagion effect. These results provide further support for the utility of the IFD, as individuals were able to accurately assess patch-level habitat quality.<br> </p>
Heterocypris incongruens maintains an egg bank in stormwater habitats and influences the development of larval mosquito, Culex restuans
<p>Dormant propagules can provide a rapid colonization source for temporary aquatic habitats and set the trajectory for community dynamics, yet the egg banks of stormwater management systems have received little attention. We asked which species hatched from the sediment of drainage ditches in Champaign County, IL, and found bdelloid rotifers and ostracods (<em>Heterocypris incongruens</em>) to be the most common taxa. These sites also are colonized by mosquitoes, and we established laboratory experiments to examine interspecific interactions between common co-occurring taxa. Culex restuans larvae were reared in the presence or absence of <em>H. incongruens</em> at two intra- and interspecific densities (20 or 40 total individuals) and their survivorship to adulthood, development time to adulthood, adult body size, and sex ratio were determined. Survival for Cx. restuans was significantly lower at high larval density than at low larval density in both treatments. Culex restuans larvae reared in the presence of H. incongruens had a shorter development time to adulthood and emerged as larger adults compared to those reared in the absence of <em>H. incongruens</em>. The sex ratios in the <em>H. incongruens</em> treatments were female-biased whereas those in the Culex-only treatments were male-biased. These differences may have epidemiological implications, as only female mosquitoes serve as disease vectors. Our results emphasize the importance of understanding interspecific interactions in influencing larval mosquito development traits.</p>
Spatially explicit habitat selection: testing contagion and the ideal free distribution with culex mosquitoes
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Heterocypris incongruens maintains an egg bank in stormwater habitats and influences the development of larval mosquito, Culex restuans
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A multiplex qPCR followed by high resolution melting analysis for the detection of blood-feeding sources in Culex sp. (Diptera: Culicidae) mosquitoes
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MosqVision-3K: A Balanced Multi-Source Dataset of 3,000 Annotated Images for Culex, Anopheles, and Aedes Mosquito Species Classification
<p><strong>Comprehensive Mosquito Species Image Dataset for Machine Learning</strong><br><strong>Description:</strong><br>This dataset is a meticulously curated collection of high-quality images featuring three major mosquito species: <strong>Culex</strong>, <strong>Anopheles</strong>, and <strong>Aedes</strong>. These species are significant vectors for transmitting vector-borne diseases such as malaria, dengue, and Zika. The dataset has been compiled to support research and development in entomology, vector-borne disease control, and image recognition.<br>With <strong>3,000 images in total</strong>, the dataset is structured to ensure a balanced representation of the three species, each having <strong>1,000 images</strong>. Images were sourced from four reputable platforms, including <strong>MosquitoAlert.com</strong>, <strong>Mendeley Data</strong>, <strong>IEEE DataPort</strong>, and the <strong>Dryad Digital Repository</strong>. These sources ensure a comprehensive and diverse representation of mosquito appearances, including variations in morphology, lighting conditions, and orientations.</p> <h2>The dataset is organized into directories for each species, making it easy to integrate into machine learning workflows for tasks like species identification and classification. The collection also includes metadata and annotations to enhance usability.</h2> <p><strong>Key Features:</strong></p> <ul> <li><strong>Species Represented:</strong> <ul> <li><em>Culex</em></li> <li><em>Anopheles</em></li> <li><em>Aedes</em></li> </ul> </li> <li><strong>Total Images:</strong> 3,000 (1,000 images per species)</li> <li><strong>Image Sources:</strong> <ul> <li><strong>MosquitoAlert.com</strong> (1,234 images)</li> <li><strong>Mendeley Data</strong> (876 images)</li> <li><strong>IEEE DataPort</strong> (748 images)</li> <li><strong>Dryad Digital Repository</strong> (600 images)</li> </ul> </li> </ul> <h2>- <strong>Image Annotations:</strong> Metadata and species labels are included for enhanced usability.</h2> <p><strong>Applications:</strong><br>This dataset is ideal for a variety of applications, including:</p> <ul> <li>Training machine learning models for mosquito species identification.</li> <li>Developing computer vision algorithms for pest control and public health.</li> </ul> <h2>- Enhancing vector control strategies to mitigate disease spread.</h2> <p><strong>Data Structure:</strong><br>The dataset is organized as follows:</p> <pre><code>Mosquito_Dataset/ ├── Anopheles/ │ ├── img_001<span>.jpg</span> │ ├── img_002<span>.jpg</span> │ └── ... ├── Aedes/ │ ├── img_001<span>.jpg</span> │ ├── img_002<span>.jpg</span> │ └── ... └── Culex/ ├── img_001<span>.jpg</span> ├── img_002<span>.jpg</span> └── ... </code></pre> <h2> </h2> <h2><strong>Acknowledgments:</strong><br>We acknowledge the following data sources for their contributions:</h2> <blockquote> <ul> <li>MosquitoAlert.com</li> <li>Mendeley Data</li> <li>IEEE DataPort</li> <li> Dryad Digital Repository</li> </ul> </blockquote>
Figure 10 in Aberrations in the larval chaetotaxy of mosquitoes (Diptera: Culicidae) of Iran and a taxonomic note on the seta 1-C (preclypeal seta) of Culex in southwestern Asia
Figure 10. (a) Culex (Neoculex) territans, Qom Province, Iran (100×). (b) Culex (Culex) laticinctus, Chaharmahal and Bakhtiari Province, Iran (100×).
Figure 3 in Aberrations in the larval chaetotaxy of mosquitoes (Diptera: Culicidae) of Iran and a taxonomic note on the seta 1-C (preclypeal seta) of Culex in southwestern Asia
Figure 3. Anopheles (Anopheles) maculipennis, (a) Kurdistan Province, Iran, 19 July 2006 (200×). (b) Ardebil Province, Iran, 30 July 2005 (100×).
Figure 2 in Aberrations in the larval chaetotaxy of mosquitoes (Diptera: Culicidae) of Iran and a taxonomic note on the seta 1-C (preclypeal seta) of Culex in southwestern Asia
Figure 2. Anopheles (Anopheles) maculipennis, Kurdistan Province, Iran, (a) 9 September 2005 (200×). (b) 19 July 2006 (200×).
Figure 8 in Aberrations in the larval chaetotaxy of mosquitoes (Diptera: Culicidae) of Iran and a taxonomic note on the seta 1-C (preclypeal seta) of Culex in southwestern Asia
Figure 8. (a) Culex (Culex) sinaiticus, Pipiens Group, Hormozgan Province, Iran, seta 1-C is thicker than the branches of 5-C but does not appear to be thicker than the branches of 6-C (100×). (b) Culex (Culex) tritaeniorhynchus, Sitiens Group, Sistan and Baluchistan Province, Iran (100×).
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OpenNeuro
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