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  • Tiger Mosquito Larvae Exhibit Consistent Individual Personality (November 2025)

    Tiger Mosquito Larvae Exhibit Consistent Individual Personality (November 2025)
    2025/11/17
    Briefing Document: Personality Traits in the Tiger Mosquito, Aedes albopictusSource: Cordeschi, G., Mastrantonio, V., De Nicola, C. et al. Insect vectors have personality: first evidence with the tiger mosquito Aedes albopictus. Sci Rep 15, 39943 (2025). https://doi.org/10.1038/s41598-025-23665-wDate: Received - 16 June 2025 | Accepted - 08 October 2025 | Published - 14 November 2025Executive SummaryThis document synthesizes findings from a foundational study providing the first evidence of animal personality in a mosquito species, the tiger mosquito Aedes albopictus. Researchers investigated personality traits in the larval stage, a critical phase in the mosquito life cycle. The study demonstrates that individual mosquito larvae exhibit consistent, repeatable differences in behavior across time, specifically in the traits of activity, exploration, and boldness.Key findings indicate that these traits are not only stable within individuals but are also significantly correlated, forming a "behavioral syndrome" where more active larvae are also bolder and more exploratory. These individual behavioral variations were observed independent of sex. The discovery of personality in mosquito larvae challenges the traditional view of insects as having purely stereotyped behaviors and introduces a new dimension of intra-specific diversity.The implications of these findings are substantial, impacting both basic mosquito biology and applied public health strategies. Larval personality may influence population dynamics through differential resource acquisition and survival rates. Furthermore, these traits could persist through metamorphosis ("carry-over effects"), affecting adult mosquito characteristics such as dispersal and disease transmission potential. Critically, the study suggests that the effectiveness of current larval control methods—both chemical and biological—may be influenced by the personality composition of a mosquito population. This research lays the groundwork for incorporating behavioral ecology into vector control strategies and the management of mosquito-borne diseases. -------------------------------------------------------------------------------- 1. Introduction: The Concept of Animal Personality in InsectsAnimal personality is defined as consistent, inter-individual variation in behavioral traits that is stable across time and different contexts. For the past two decades, this has been a central topic in behavioral ecology, primarily focusing on vertebrates. Key personality traits include boldness (risk-taking), exploration, activity, aggressiveness, and sociability. These traits are often correlated, forming what are known as behavioral syndromes.A growing body of research demonstrates that personality significantly influences ecological and evolutionary processes by affecting:Population demography and persistenceLocal adaptationDispersal dynamicsSpecies interactionsWhile initial research concentrated on vertebrates, an increasing number of studies have documented personality in invertebrates, including insects. This has challenged the conventional view that insects exhibit purely stereotyped behaviors. It is now evident that personality shapes insect population ecology and evolution. For instance:In the field cricket Gryllus integer, populations exposed to higher predation exhibit reduced boldness.In the firebug Pyrrhocoris apterus, bolder and more exploratory individuals are more likely to disperse and host parasites.Despite this progress, the existence and implications of personality traits in mosquito species remained an unexplored area of research until this study.2. Study Context: The Tiger Mosquito (Aedes albopictus)Mosquitoes (Diptera: Culicidae) comprise approximately 3,500 species and are globally significant vectors for major diseases affecting humans and animals, including malaria, dengue, yellow fever, and chikungunya. The larval stage is a critical part of their life cycle, as it is when they accumulate the necessary food reserves for metamorphosis. Conditions experienced during this stage can have lasting "carry-over effects" on adult traits and, consequently, on their potential to transmit pathogens.The subject of this study, the tiger mosquito Aedes albopictus, is an invasive species native to Asia that has spread to every continent except Antarctica. Its rapid expansion and capacity to vector several arboviruses make it a major global threat to public health.The primary objective of this research was to address the gap in mosquito biology by investigating the presence of personality traits in Ae. albopictus larvae. Specifically, the study aimed to:Characterize the larval personality traits of activity, exploration, and boldness.Assess whether these traits are consistent and repeatable over time.Determine if these traits are correlated, indicating a behavioral syndrome.3. MethodologyThe study was conducted under controlled laboratory conditions using 41 Ae. albopictus...
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    11 分
  • Predicting Dengue Risk with Machine Learning and Microclimate Data (October 2025)

    Predicting Dengue Risk with Machine Learning and Microclimate Data (October 2025)
    2025/10/24
    Briefing: Fine-Scale Predictive Modeling for Dengue Risk in MalaysiaSource: Dom, N.C., Abdullah, N.A.M.H., Dapari, R. et al. Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables. Sci Rep 15, 37017 (2025). https://doi.org/10.1038/s41598-025-17191-yDate: Received - 01 February 2025 | Accepted - 21 August 2025 | Published - 23 October 2025Executive SummaryThis briefing document synthesizes the findings of a study on the use of machine learning (ML) for fine-scale prediction of Aedes mosquito abundance and dengue risk in Kuala Selangor, Malaysia. Faced with a doubling of dengue cases in 2023, the study addresses the limitations of coarse, regional forecasting models by incorporating daily microclimatic data (temperature, relative humidity, rainfall) to improve predictive accuracy at the neighborhood level.Key Takeaways:Variable Model Performance: No single machine learning algorithm—Artificial Neural Network (ANN), Random Forest (RF), or Support Vector Machine (SVM)—was universally superior. Performance was highly dependent on the specific mosquito species (Ae. aegypti vs. Ae. albopictus), the risk indicator being predicted (Aedes Index vs. Dengue Positive Trap Index), and the combination of microclimatic inputs. For instance, ANN excelled at predicting the Ae. aegypti Aedes Index, while SVM was most effective for predicting the Ae. albopictus Dengue Positive Trap Index.Impact of Predictor Complexity: Models incorporating multiple microclimatic variables (dual or triple combinations) generally yielded lower error metrics than single-variable models. However, increasing model complexity did not always improve accuracy and, in some cases, led to overfitting and higher prediction errors, particularly for ANN models. This highlights a critical trade-off between model complexity and predictive power.Moderate and Time-Lagged Climatic Influence: While statistically significant, the correlations between microclimatic variables and mosquito indices were weak to moderate (correlation coefficients ranged from -0.30 to 0.32). This indicates that microclimate alone is insufficient to fully explain mosquito population dynamics and that other unmodeled factors, such as breeding site density, vegetation, and human activity, play a crucial role. The analysis also revealed significant time lags of up to 91 days, suggesting cumulative or delayed environmental effects on mosquito life cycles.Species-Specific Ecological Responses: The study identified distinct ecological sensitivities between the primary dengue vectors. Aedes albopictus demonstrated a quicker response to rainfall for dengue risk (a lag of -28 days) compared to Aedes aegypti (-63 days), which aligns with its known preference for more transient breeding habitats.Conclusion: The research validates the potential of fine-scale, microclimate-driven ML models as a valuable tool for creating proactive and targeted dengue control strategies. However, it underscores that effective implementation requires careful model selection tailored to specific species and local conditions. Future predictive systems would benefit from integrating a broader range of ecological and anthropogenic data to enhance accuracy and operational value. -------------------------------------------------------------------------------- 1. Background and RationaleDengue fever remains a significant and escalating public health threat in Malaysia. The Ministry of Health reported over 123,000 cases in 2023, a twofold increase from 2021, with the state of Selangor bearing the highest burden. This trend suggests that existing vector control strategies, public awareness campaigns, and regulatory enforcement face significant limitations, particularly in densely populated urban areas.The proliferation of Aedes mosquitoes, the primary vectors for dengue, is heavily influenced by environmental conditions, especially microclimatic variables like temperature, humidity, and rainfall. Previous predictive models have often relied on coarse-resolution data from regional weather stations or satellites. This approach fails to capture the localized microclimatic variations critical to mosquito breeding at the neighborhood or household level, thereby limiting the models' utility for guiding timely and targeted interventions.This study aimed to bridge this gap by developing and evaluating fine-scale predictive models for Aedes mosquito abundance and dengue risk indicators in Kuala Selangor, a known dengue hotspot. The core objective was to leverage machine learning algorithms to analyze daily, localized microclimatic data, thereby improving forecasting accuracy for more effective, data-driven vector control.2. Methodological FrameworkThe study was conducted over 26 weeks, from February 6 to August 6, 2023, in urban and suburban districts of Kuala Selangor, a region with a tropical climate conducive to mosquito breeding...
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    13 分
  • Medfly Gut Microbiota and Insecticide Resistance (September 2025)

    Medfly Gut Microbiota and Insecticide Resistance (September 2025)
    2025/10/01
    Gut Microbiota and Insecticide Resistance in the Mediterranean Fruit Fly (Ceratitis capitata)Source: Charaabi, K., Hamdene, H., Djobbi, W. et al. Assessing gut microbiota diversity and functional potential in resistant and susceptible strains of the mediterranean fruit fly. Sci Rep 15, 33456 (2025). https://doi.org/10.1038/s41598-025-01534-wDates: Received - 06 November 2024 | Accepted - 06 May 2025 | Published - 29 September 2025Executive SummaryThis briefing document synthesizes findings from a study investigating the link between gut microbiota and insecticide resistance in the Mediterranean fruit fly (Ceratitis capitata), a destructive agricultural pest. The research reveals a strong correlation between resistance to common insecticides (malathion, dimethoate, and spinosad) and significant alterations in the composition and functional potential of the fly's gut bacterial community.Resistant strains of the medfly, developed over 36 generations of insecticide exposure, exhibit significantly lower microbial diversity compared to their susceptible counterparts. This reduction in diversity is accompanied by a profound shift in the gut's bacterial landscape. Specifically, the phylum Bacillota and the genera Enterococcus and Klebsiella are substantially enriched in resistant flies. Conversely, the dominant phylum Pseudomonadota and the genera Serratia and Buttiauxella are sharply reduced.Functional analysis predicts that the gut microbiota of resistant flies possess enhanced metabolic capabilities for xenobiotic biodegradation. These enriched pathways are associated with the breakdown of various toxic environmental chemicals, suggesting a direct or indirect role in insecticide detoxification. The findings indicate that symbiont-mediated resistance is likely a key mechanism in the medfly, driven by the synergistic effect of multiple bacterial species rather than a single microbe. This research opens new avenues for pest management strategies that could target the gut microbiome to mitigate insecticide resistance.Background and Research ObjectivesThe Mediterranean fruit fly (Ceratitis capitata), or medfly, is a highly polyphagous pest that infests over 300 plant species, causing billions of dollars in annual economic losses worldwide. These losses stem from reduced agricultural production, costly control measures, and restricted market access. While methods like the Sterile Insect Technique (SIT) are used, the predominant control practice remains the application of chemical insecticides.The widespread and excessive use of insecticides has led to the development of significant resistance in medfly populations, undermining control efforts. While resistance is often linked to genetic traits in the insect, such as increased enzyme activity, recent evidence from other species suggests that symbiotic gut microorganisms can play a crucial role. These bacteria may contribute to resistance by directly metabolizing toxic substances or by modulating the host's detoxification gene expression.Despite extensive research on the medfly's gut microbiota in relation to its fitness and SIT applications, the connection to insecticide resistance has remained largely unexplored. This study aimed to address this gap by investigating the potential association between the medfly gut microbiota and insecticide resistance. The primary objectives were to:Characterize and compare the gut microbiota community structure between insecticide-susceptible (IS) and insecticide-resistant (IR) strains of the medfly.Identify specific bacterial taxa that correlate with resistance phenotypes.Predict the functional differences between the microbiomes of susceptible and resistant strains.Experimental Design and MethodologyTo achieve its objectives, the study employed a controlled laboratory selection process and advanced sequencing techniques.Strain Development: Three insecticide-resistant (IR) strains were developed from a susceptible parent strain (IS) originally from Egypt (Egypt II). For 36 successive generations, populations were exposed to increasing concentrations of one of three insecticides: malathion (ML-SEL strain), dimethoate (Dm-SEL strain), or spinosad (Sp-SEL strain). The selection pressure was calibrated to achieve 50-70% mortality in each generation.Resistance Confirmation: Toxicological bioassays were conducted on the 36th generation of each IR strain and the IS strain. The lethal concentration required to kill 50% of the population (LC50) was calculated to quantify the level of resistance. The results confirmed a significant increase in tolerance in the selected strains. | Strain | Insecticide | LC50 (ppm) | Resistance Ratio (RR) vs. IS Strain | IS | Malathion | 18.8 | - | ML-SEL (G36) | Malathion | 1872.2 | 99.23-fold | IS | Dimethoate | 0.85 | - | Dm-SEL (G36) | Dimethoate | 215.79 | 252.68-fold | IS | Spinosad | 0.55 | - | Sp-SEL (G36) | Spinosad | 133.79 | 241.49-foldMicrobiota Analysis: Gut tissues were dissected from adult...
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    13 分
  • Mosquito Diversity and Vector Distribution in Kerala, India (Aug 2025)

    Mosquito Diversity and Vector Distribution in Kerala, India (Aug 2025)
    2025/08/23
    Mosquito Diversity and Public Health Risk in Kerala, India: A Synthesis of a Multi-District SurveySource: Mathiarasan, L., Natarajan, R., Aswin, A. et al. Diversity and spatiotemporal distribution of mosquitoes (Diptera: Culicidae) with emphasis on disease vectors across agroecological areas of Kerala, India. Sci Rep 15, 30603 (2025). https://doi.org/10.1038/s41598-025-16357-yDate: Received - 29 May 2025 | Accepted - 14 August 2025 | Published - 20 August 2025Executive SummaryThis document synthesizes the findings of an extensive entomological survey conducted across five agroecological districts of Kerala, India. The research reveals a remarkably diverse mosquito fauna, identifying 108 species, including 14 known disease vectors, which underscores the region's complex public health challenges. The study highlights the overwhelming predominance of Stegomyia albopicta (54.82% of all collected specimens), a highly adaptable vector for dengue and chikungunya, posing a significant and ongoing threat.Key findings indicate that artificial, human-made habitats—such as discarded tires, plastic containers, and latex collection cups—are the primary breeding grounds, supporting greater species diversity than natural habitats and pointing to critical deficiencies in solid waste management. The Wayanad district was identified as a major biodiversity hotspot for mosquitoes, attributed to its unique ecological niches. The investigation also yielded significant scientific discoveries, including the description of a new species, Heizmannia rajagopalani, and the first regional records of several other species. The co-existence of multiple vectors for arboviruses, malaria, and filariasis creates a complex risk profile that necessitates comprehensive surveillance and targeted, ecologically-informed control strategies.1. Overview of the Entomological SurveyThe study was designed to conduct a comprehensive assessment of mosquito biodiversity, spatiotemporal distribution, and habitat preferences across diverse ecological settings in Kerala, India, a state known for its unique agro-geographical features and history of mosquito-borne disease (MBD) outbreaks.Objective: To evaluate mosquito species composition, spatial and temporal distribution, and ecological and habitat preferences to inform public health risk assessment and vector control strategies.Scope and Duration: The survey was conducted from February 2016 to September 2017 in five districts selected for their varied ecotypes: Wayanad (forested, high altitude) Ernakulam (coastal, plantation) Pathanamthitta (Western Ghats, plantation) Idukki (mountainous, tea cultivation) Thiruvananthapuram (capital, urban/rural/coastal) Methodology: The research employed a dual sampling approach, collecting both immature (larvae, pupae) and adult mosquitoes. Immature specimens were collected from 777 habitats, while 4,021 adult mosquitoes were collected from 422 sites. Species were identified using standard morphological and taxonomic keys.Total Collection: A total of 12,535 mosquito specimens were collected and identified.2. Species Composition and AbundanceThe survey revealed a rich and diverse mosquito fauna, highlighting a complex ecosystem of both nuisance species and medically important vectors.Overall DiversityA total of 108 mosquito species belonging to 28 genera were identified. The genus Culex exhibited the highest species richness (25.0%), followed by Anopheles (12.9%) and Stegomyia (10.2%).Dominant SpeciesThe vast majority of collected specimens were dominated by a few highly prevalent species: | Species | Percentage of Total Collection | Known Significance | Stegomyia albopicta | 54.82% | Primary vector for dengue, chikungunya, Zika | Culex quinquefasciatus | 6.92% | Vector for lymphatic filariasis | Hulecoeteomyia chrysolineata | 6.33% | Noted for diverse breeding patterns | Armigeres subalbatus | 5.03% | Nuisance mosquito, prefers polluted waterIdentified Disease VectorsThe study identified 14 known disease vector species, creating a multifaceted public health risk. The co-existence of primary and secondary vectors for various diseases complicates transmission dynamics.Arboviruses (Dengue, Chikungunya, Zika, Japanese Encephalitis): St. albopicta, St. aegypti, Fredwardsius vittatus, Cx. tritaeniorhynchus, Cx. bitaeniorhynchus, Cx. gelidus, Cx. vishnui, Cx. pseudovishnui.Malaria: Anopheles stephensi, An. culicifacies (primary vectors), and An. varuna (secondary vector).Filariasis: Cx. quinquefasciatus, Mansonia uniformis, An. barbirostris.While St. albopicta was abundant, other primary vectors were found in extremely low numbers, such as St. aegypti(1.43%), An. stephensi (0.06%), and An. culicifacies (0.01%). However, the study emphasizes that even low-density vector populations can sustain pathogen transmission cycles and cause outbreaks under favorable conditions.3. Spatiotemporal Distribution and Biodiversity HotspotsThe distribution of mosquito species ...
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    14 分
  • AI and Electric Fields for Automated Insect Monitoring (Aug 2025)

    AI and Electric Fields for Automated Insect Monitoring (Aug 2025)
    2025/08/16
    Briefing: Automated Insect Monitoring via AI and Electrical Field SensorsSource: Odgaard, F.B., Kjærbo, P.V., Poorjam, A.H. et al. Automated insect detection and biomass monitoring via AI and electrical field sensor technology. Sci Rep 15, 29858 (2025). https://doi.org/10.1038/s41598-025-15613-5Date: Received - 11 April 2025 | Accepted - 08 August 2025 | Published - 14 August 2025Executive SummaryThis document outlines a novel, automated insect monitoring system that uses electrical field sensors and artificial intelligence to provide a non-invasive, continuous alternative to traditional methods. The system addresses the critical need for improved insect monitoring in the face of global declines, aiming to overcome the labor-intensive, lethal, and temporally limited nature of conventional techniques like Malaise traps.The core technology detects atmospheric electrical field modulations caused by flying insects. A differential sensor design suppresses environmental noise, while a cloud-based AI pipeline processes the signals. This pipeline employs a Convolutional Neural Network (CNN) for insect detection, a probabilistic algorithm for Wing-Beat Frequency (WBF) analysis, and a lookup-based algorithm for biomass estimation.A field validation study conducted in a Danish nature reserve compared the system against standard Townes Malaise traps. The results demonstrated a moderate to strong positive correlation between sensor and trap data for insect counts (Spearman’s ρ up to 0.725). However, the correlation for biomass was weaker and not consistently significant. A major discrepancy in magnitude was observed, with sensors recording approximately three times more insect counts and 26 times more biomass than the traps. This is attributed to fundamental methodological differences (passive sensing vs. single capture) and significant uncertainty within the system's current biomass estimation algorithm.Notably, the sensor system exhibited higher measurement consistency between its own units (sensor-sensor correlation for biomass ρ = 0.867) than paired Malaise traps (Malaise-Malaise correlation for biomass ρ = 0.641), although this difference was not statistically significant (P = 0.057). The study concludes that while the technology shows significant promise for scalable, non-lethal insect monitoring, the biomass algorithm requires substantial refinement and calibration before it can be used for absolute estimation.1. The Challenge in Conventional Insect MonitoringInsects, comprising over half of all described species, are vital for ecosystem stability through functions like pollination, nutrient cycling, and pest control. Alarming reports of declines in insect abundance, biomass, and species richness underscore the urgent need for effective monitoring to support conservation and safeguard ecosystem services.However, conventional monitoring techniques present significant challenges:• Labor-Intensive: Methods such as pan, pit, light, and Malaise traps require substantial manual effort for insect collection, sorting, counting, and weighing.• Invasive and Lethal: These trap-based approaches remove insects from the local population, posing a potential threat to fragile species and raising ethical concerns. The validation study for this new system highlighted this impact, with 55,443 insects killed in just two Malaise traps during the sampling period.• Limited Granularity: Traditional methods typically provide data at coarse temporal intervals (e.g., daily or weekly), limiting insights into finer-scale activity patterns.Automation and non-invasive technologies are critical for overcoming these limitations, enabling continuous data collection across large areas without disrupting local ecosystems.2. A Novel Automated Monitoring SystemThe presented system offers a comprehensive, automated solution for non-invasive insect monitoring, from data acquisition in the field to data analysis in the cloud.2.1. Operating Principle and Sensor DesignThe system's core innovation is its ability to passively detect flying insects by exploiting natural electrical effects.• Detection Mechanism: As insects fly, they acquire a positive electrical charge through air friction (triboelectric effect) and disrupt the ambient atmospheric electric field. These combined effects create unique electrical signatures that the sensor detects.• Differential Probe Design: To function in noisy outdoor environments, the sensor employs two identical electrostatic probes spaced 28 cm apart. This differential measurement approach effectively mitigates distant, common-mode noise sources like atmospheric disturbances and radio signals.• Detection Volume: The design creates a detection volume sensitive to nearby insects. However, it also creates a "blind plane" of zero sensitivity on the symmetry plane directly between the two probes. The sensor's sensitivity is size-dependent, meaning larger insects are detectable at greater distances than ...
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    19 分
  • Successive Feeding Impacts Wolbachia's Dengue Virus Inhibition in Aedes aegypti (July 2025)

    Successive Feeding Impacts Wolbachia's Dengue Virus Inhibition in Aedes aegypti (July 2025)
    2025/07/29
    Impact of Mosquito Feeding Behavior on Wolbachia-Based Dengue ControlDate: Received - 17 February 2025 | Accepted - 18 July 2025 | Published - 29 July 2025Source: Johnson, R.M., Breban, M.I., Nolan, B.L. et al. Implications of successive blood feeding on Wolbachia-mediated dengue virus inhibition in Aedes aegypti mosquitoes. Nat Commun 16, 6971 (2025). https://doi.org/10.1038/s41467-025-62352-2Executive SummaryThis document synthesizes findings from a study on the interplay between mosquito feeding behavior and the effectiveness of Wolbachia bacteria in inhibiting the dengue virus (DENV-2). The central conclusion is that successive blood feeding by Aedes aegypti mosquitoes, a natural behavior often overlooked in laboratory settings, enhances the relative efficacy of the wAlbB Wolbachia strain. While frequent feeding accelerates virus dissemination in both Wolbachia-infected and uninfected (wildtype, WT) mosquitoes, the effect is significantly more pronounced in the WT population.This leads to a critical insight: traditional single-feed laboratory experiments likely underestimate the real-world impact of Wolbachia-based control strategies. The modeling of epidemiologically relevant factors shows that the protective advantage of wAlbB over WT is magnified under conditions that mimic natural feeding patterns. These findings provide robust support for the ongoing deployment of Wolbachia-transinfected mosquitoes for dengue transmission control, suggesting their functional inhibition of DENV-2 may be even stronger than previously demonstrated.--------------------------------------------------------------------------------Introduction and Study ContextThe release of Aedes aegypti mosquitoes transinfected with the Wolbachia pipientis bacterium is a promising novel strategy to combat the significant public health threat of dengue virus (DENV). Wolbachia inhibits virus transmission, but the mechanisms are not fully understood, and the effectiveness can be incomplete.A critical factor often unaccounted for in laboratory assessments is the natural feeding behavior of Ae. aegypti, which frequently take multiple blood meals. Previous work has shown that this "successive feeding" can accelerate virus dissemination from the mosquito's midgut, thereby shortening the extrinsic incubation period (EIP)—the time required for a mosquito to become infectious.This study investigated the hypothesis that successive blood feeding decreases the effectiveness of Wolbachia by facilitating more efficient DENV-2 dissemination in mosquitoes carrying the wMelM and wAlbB strains.Key FindingsI. Successive Feeding Accelerates DENV-2 DisseminationThe study compared mosquitoes given a single infectious blood meal (single-fed, SF) to those given an additional non-infectious blood meal four days later (double-fed, DF).• Increased Dissemination: At 7 days post-infection, a second blood meal significantly increased the rate of DENV-2 dissemination in both wildtype (WT) and wAlbB-infected mosquitoes.• Higher Viral Titers: Correspondingly, double-fed WT and wAlbBmosquitoes exhibited higher DENV-2 genome equivalents (viral load) in their bodies compared to their single-fed counterparts.• Temporal Shift: Time course experiments confirmed that successive feeding leads to earlier dissemination, effectively shortening the EIP in both WT and wAlbB mosquitoes. For example, at day 5 post-infection, dissemination in the double-fed WT group was significantly higher than in the single-fed group. A similar, though less pronounced, acceleration was observed in wAlbB mosquitoes at days 6 and 7.II. Wolbachia Strain Performance and DensityThe study reaffirmed the virus-inhibiting properties of Wolbachia and explored the role of bacterial density.• Strong Virus Inhibition: Consistent with previous research, both Wolbachiastrains strongly inhibited DENV-2. Mosquitoes with wMelM showed stronger inhibition (fewer infections and disseminations) than those with wAlbB. Due to the extremely low infection rates in wMelM mosquitoes, many subsequent analyses focused on the wAlbB strain.• Wolbachia Density: While a second blood meal slightly increased wAlbBdensity, there was no significant correlation between Wolbachia levels and DENV-2 levels in individual mosquitoes. Instead, higher DENV-2 titers were strongly associated with whether the infection had disseminated, suggesting that midgut escape allows for increased viral replication in other tissues.III. Modeling the Extrinsic Incubation Period (EIP)By modeling the time course data, the study quantified the impact of successive feeding on the EIP, defined as the time until 50% of mosquitoes develop a disseminated infection (EIP50).• EIP50 Reduction in wAlbB Mosquitoes: Successive feeding significantly shortened the time to 50% dissemination in wAlbB mosquitoes.wAlbB Mosquito Group | Estimated EIP50 (Days Post-Infection) | 95% Credible IntervalSingle-Fed (SF) | 8.38 days | 7.72–9.01 daysDouble-Fed (DF) | ...
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    14 分
  • AI for Culex Mosquito Identification using Wing Patterns (July 2025)

    AI for Culex Mosquito Identification using Wing Patterns (July 2025)
    2025/07/01
    Detailed Briefing Document: Application of Wing Interference Patterns (WIPs) and Deep Learning (DL) for Culex spp. ClassificationApplication of wings interferential patterns (WIPs) and deep learning (DL) to classify some Culex. spp (Culicidae) of medical or veterinary importanceArnaud Cannet, Camille Simon Chane, Aymeric Histace, Mohammad Akhoundi, Olivier Romain, Pierre Jacob, Darian Sereno, Marc Souchaud, Philippe Bousses & Denis Sereno Scientific Reports volume 15, Article number: 21548 (2025)Source: https://doi.org/10.1038/s41598-025-08667-yReceived - 28 November 2024 | Accepted - 23 June 2025 | Published - 01 July 2025This briefing document reviews a study that successfully demonstrates the utility of combining Wing Interference Patterns (WIPs) with deep learning (DL) models for the accurate identification of Culex mosquito species. Culex mosquitoes are significant vectors for numerous arboviruses and parasites of medical and veterinary importance, including West Nile virus, Japanese encephalitis, Saint Louis encephalitis, and lymphatic filariasis. Traditional morphological identification methods are labor-intensive, prone to errors due to cryptic species or damaged samples, and often yield variable accuracy (e.g., ~64% average species-level accuracy in external assessments).The research team developed a method leveraging the unique, stable interference patterns visible on transparent insect wing membranes (WIPs) as species-specific morphological markers. By integrating these WIPs with Convolutional Neural Networks (CNNs), the study achieved over 95% genus-level accuracy for Culex and up to 100% species-level accuracy for certain species. While challenges remain with underrepresented species in the dataset, this approach presents a scalable, cost-effective, and robust alternative or complement to traditional identification methods, with significant potential for enhancing vector surveillance and global health initiatives.Key Themes and Important Ideas/Facts1. The Challenge of Mosquito Identification and its ImportanceGlobal Health Threat: Arthropod-transmitted pathogens, including viruses, bacteria, and parasites, are "among the most destructive infectious agents globally."Vector Role of Culex: The Culex genus, comprising over 783 recognized species and 55 subspecies, "are recognized vectors of significant diseases, such as West Nile virus fever, Japanese encephalitis, Saint Louis encephalitis, or lymphatic filariasis."Difficulty of Traditional Methods: "Traditional morphological identification is labor-intensive and relies on diagnostic features and determination keys." This method is "often challenged by cryptic species, overlapping morphological traits, and damaged specimens."Need for Innovation: These limitations "emphasize the need for innovative identification methods to enhance entomological surveys."2. Wing Interference Patterns (WIPs) as Species-Specific MarkersNature of WIPs: WIPs are "visible color patterns caused by thin-film interference" on the thin, transparent wing membranes of insects, particularly smaller species. They become visible when wings are "illuminated in a dark, light-absorbing setting."Species-Specific Consistency: "These Wing Interference Patterns (WIPs) show substantial variation between different species, while remaining relatively consistent within a species or between sexes."Stability of WIPs: Unlike conventional iridescence, the "microstructure of insect wings functions as a dioptric system that stabilizes the interference pattern, making WIPs largely insensitive to viewing angle."Potential as Morphological Markers: Due to their "species-specific consistency and interspecific variability, WIPs hold strong potential as morphological markers for insect classification, offering a promising alternative or complement to traditional taxonomic traits."3. Integration of WIPs with Deep Learning (DL) for ClassificationPrevious Successes: WIPs and DL have previously "successfully demonstrated their utility in identifying Anopheles, Aedes, sandflies, and tsetse flies." This study extends the approach to Culex.Methodology: The study applied "WIPs, generated by thin-film interference on wing membranes, in combination with convolutional neural networks (CNNs) for species classification."CNN Advantages: Deep Convolutional Neural Networks (CNNs) are "most effective for image classification" and "automatically selects the optimal features during the learning process, making it particularly suitable for WIP classification tasks."Dataset: The study used a refined dataset of "553 images representing WIPs from 7 species" for training, with a larger database including "572 images of 12 species across 5 subgenera" for general classification and 4,944 images of non-Culex Diptera as negative controls.4. Classification Performance and ResultsHigh Genus-Level Accuracy: The CNN achieved "genus-level classification accuracy exceeding 95.00%."Variable Species-Level Accuracy: "At the species ...
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    16 分
  • Battle of the Mosquitoes: Genetic War on Malaria (June 2025)

    Battle of the Mosquitoes: Genetic War on Malaria (June 2025)
    2025/06/27
    Detailed Briefing Document: The Battle of the Mosquitoes - A New Approach to Malaria ControlSource: Adepoju, P. Battle of the mosquitoes. Nat Med 31, 1722–1726 (2025). https://doi.org/10.1038/s41591-025-03753-0Dates: Published - 11 June 2025 | Issue Date - June 2025I. Executive SummaryThis briefing document summarizes the key themes and facts from the provided source, "Battle of the Mosquitoes," detailing the innovative approach of using genetically modified mosquitoes to combat malaria, particularly in urban environments. The core of this strategy, pioneered by Oxitec, involves releasing male Anopheles stephensi mosquitoes engineered with a self-limiting gene, leading to a decline in malaria-carrying female mosquito populations. Djibouti is at the forefront of this experiment, driven by a dramatic resurgence of malaria cases linked to the invasive A. stephensi species, which thrives in cities and evades traditional control methods. The document highlights the painstaking scientific process, the urgent need for new solutions in the face of evolving malaria threats, the critical importance of community engagement to address skepticism about genetic modification, and the challenges of scaling up this technology across Africa amidst funding and regulatory hurdles.II. Main Themes and Key IdeasA. The Emergence of Anopheles stephensi as a "Game Changer" in Malaria TransmissionShift in Malaria Epidemiology: For decades, malaria in Africa was predominantly a rural disease, but the arrival and rapid spread of Anopheles stephensi have fundamentally altered this landscape.Urban Adaptation: Unlike A. gambiae, the traditional African malaria vector, A. stephensi "loves city life" and "thrives in urban environments, breeding in water storage tanks, wells and even discarded containers."Ineffectiveness of Traditional Tools: "Traditional malaria control tools — such as bed nets and insecticides — have proven largely ineffective" against A. stephensi because it "bites outdoors and during the day" and exhibits "resistance to multiple insecticides."Geographic Spread: Since its detection in Djibouti in 2012, A. stephensi has been reported in numerous other African and Middle Eastern countries, including Eritrea, Ethiopia, Ghana, Kenya, Nigeria, Somalia, Sudan, and Yemen (Fig. 2).Urgent Threat: The "2024 World Malaria Report warns that without urgent intervention, A. stephensi could derail malaria elimination efforts, particularly in Africa."B. Djibouti's Pioneering Role and the Severity of its Malaria CrisisDramatic Resurgence: Djibouti experienced a catastrophic increase in malaria cases, from "27 in 2012 to over 73,000 in 2020," directly linked to the arrival of A. stephensi.Personal Impact on Leadership: Colonel Abdoulilah Ahmed Abdi, the health advisor to the president of Djibouti, himself contracted malaria, emphasizing the severity: "I had been working for years to protect people from malaria, and yet I found myself in a hospital bed, fighting it... It was one of the worst experiences of my life."Urgency for Innovation: Abdi stresses, "Anopheles stephensi is a game changer. If we don’t act fast, it won’t just be Djibouti — it will be cities across Africa, battling a version of malaria we never thought possible." He notes, "We need something complementary to the existing tools — something sustainable and innovative."High Stakes: The resurgence has "threatened both lives and economic growth, with the government citing lost tourism and investment as direct consequences."C. Oxitec's Genetically Modified Mosquito TechnologyMechanism of Action: Oxitec's modified Anopheles stephensi mosquitoes are "bred with a self-limiting gene that ensures that only male offspring survive when they mate with wild females."Targeted Approach: "The modified males don’t bite and don’t spread malaria, but when released into the wild, they seek out female mosquitoes — the ones responsible for disease transmission. Their female offspring don’t survive, causing a gradual decline in the malaria-carrying population."Self-Limiting Nature: A key feature is that the mosquitoes are "self-limiting — meaning that once releases stop, they disappear. 'The moment you stop releasing our friendly males, they vanish from the environment,' Morrison said." This is intended to address regulatory and community concerns about unintended long-term consequences.Painstaking Production Process: Creating these mosquitoes is a "painstaking, manual process."Microinjection: Scientists "use microscopic glass needles to inject a tiny genetic construct into individual mosquito eggs — one by one." This requires extreme precision, with technicians stating, "If you’re too rough, the eggs explode," and "You have about a 30-minute window before they mature too much to inject." The best injectors manage about "1,000 eggs a day."Quality Control: Each mosquito is "carefully examined," looking for a "tiny fluorescent marker inside the mosquitoes’ bodies ...
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