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Behavioral and molecular responses of Aedes aegypti to ultrasound
김동인,Ilyasov Rustem,yunusbaev ural,Lee Sung-Hwa,권형욱 한국응용곤충학회 2021 Journal of Asia-Pacific Entomology Vol.24 No.1
Mosquito-borne infectious diseases cause mortality and global infectious disease burden worldwide. There are several electronic mosquito repellents (EMRs) based on ultrasound have been developed and commercialized to reduce human-mosquito contacts. However, the efficacy of EMRs against mosquitoes is still unclear. In this study, we present experimental evidence that ultrasound of different frequency and sound pressure differentially affects the host-seeking behavior of Aedes aegypti females. Behavioral tests were accompanied by molecular experiments to check whether mosquitoes respond to ultrasound and are there any changes in specific mRNA expression. Experiments in bioassays revealed that the ultrasound of 100 kHz frequency and 90–110 dB pressure signifi cantly disrupted CO₂-oriented olfactory behaviors and blocked indoor invasion. Furthermore, a long time (>24 h) exposure to 100 kHz frequency/90 dB pressure of ultrasound decreased attractive behaviors to human skin. At the molecular level, there was no change in expression of odorant receptor co-receptor (AaOrco) in ultrasound treated animals, while one of the CO 2 receptor genes, AaGr3, and putative hearing-related gene, AAEL009258, were down-regulated and up-regulated, respectively. Our study indicates that high frequency (100 kHz) and pressure (90–110 dB) of the ultrasound has repellent effects to olfactory–driven behaviors of mosquitoes.
Rustem A. Ilyasov,Myeong‑Lyeol Lee,Ural Yunusbaev,Alexey Nikolenko,Hyung‑Wook Kwon 한국유전학회 2020 Genes & Genomics Vol.42 No.9
Background Marker-assisted selection is well established in animal breeding method of selecting individuals with desirable traits in a breeding scheme based on DNA molecular marker patterns. Objective Genetic diversity and C-derived admixture into local purebred gene pool of A. m. mellifera colonies was assessed using polymorphism of nine microsatellite loci in order to provide further marker-assisted selection of desired honey bee colonies. Methods The genetic diversity and the level of C-derived introgression into A. m. mellifera colonies in the Shulgan-Tash Nature Reserve (Russia) was assessed based on nine microsatellite loci (ap243, 4a110, A24, A8, A43, A113, A88, Ap049, A28), which were analized using the fragment analysis of the PCR products in Applied Biosystems 3130 DNA Analyzer. Phylogenetic relationship of colonies was evaluated using Neighbor-Joining methods with Cavalli-Sforza and Edwards genetic distance using the PHYLIP 3.68. The model-based Bayesian clustering algorithm implemented in STRUCTURE 2.3.3 was employed to infer membership and introgression proportions (Q-value). Results In the Shulgan-Tash Nature Reserve colonies of A. m. mellifera subdivided into four groups by level of C-derived introgression. Only fve colonies of A. m. mellifera had C-derived introgression which varied from 0.5 to 2%. The genetic diversity in colonies of A. m. mellifera varied from 0.12 to 0.40. The Neighbor-Joining tree demonstrates the genetic relationship of A. m. mellifera colonies, which subdivided into three groups with diferent levels of C-derived introgression. Group 1 combined fve honey bee colonies Bort_1, Bort_2, Bort_3, Baisalyan_1, and Kush_7 with a fraction of introgression close to 0.000 and genetic diversity from 0.20 to 0.25. Conclusion The results showed the excellence of nine microsatellite loci genotyping in estimation of genetic diversity, distinguishing the two European evolutionary lineages M and C and estimating C-derived introgression. These genetic parameters can be applied further to perform the marker-assisted selection of purebred dark European honey bees.
Application of ICT-based Dual Infrared Sensors for efficient honey bee monitoring
Jae Deok Son,Sooho Lim,Gi-Youn Han,Dong-In Kim,Ural Yunusbaev,Rustem Ilasov,Hyung Wook Kwon 한국응용곤충학회 2019 한국응용곤충학회 학술대회논문집 Vol.2019 No.04
Honey bees are affected by a variety of factors, so they have to be thoroughly managed according to their lifestyle. The activity of the honey bee foragers represent an important parameter of the hive state. Here, the real-time and automatic monitoring system using dual infrared sensors was applied for counting the foraging activity of honey bees based on ICT. According to this study, this system is very accurate with a relative error of 3.98% / 4.43% compared to manual counting through video analysis. This system showed the scalability of the system through the internal and external temperature sensors connected through the main board and BLE module. Furthermore, the data measured through this system for one month were analyzed, the monthly average foraging activity and the number of lost foragers were measured (1.88% of outgoing bees), and at the same time, the foraging patterns according to the changes of temperature and time were analyzed. This study suggests that the development of apicultural, scientific and educational materials with more powerful real-time monitoring tools through expansion of a complex monitoring system and big data accumulation.
ICT 기반 이중 적외선 센서를 이용한 꿀벌 출입 자동 모니터링 시스템
손재덕(Jae Deok Son),임수호(Sooho Lim),김동인(Dong-In Kim),한기윤(Giyoun Han),Rustem Ilyasov,Ural Yunusbaev,권형욱(Hyung Wook Kwon) 한국양봉학회 2019 韓國養蜂學會誌 Vol.34 No.1
Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.