Dual mutations in the whitefly nicotinic acetylcholine receptor ß1 subunit confer target-site resistance to multiple neonicotinoid insecticides.

Neonicotinoid insecticides, which target insect nicotinic acetylcholine receptors (nAChRs), have been widely and intensively used to control the whitefly, Bemisia tabaci, a highly damaging, globally distributed, crop pest. This has inevitably led to the emergence of populations with resistance to neonicotinoids. However, to date, there have been no reports of target-site resistance involving mutation of B. tabaci nAChR genes. Here we characterize the nAChR subunit gene family of B. tabaci and identify dual mutations (A58T&R79E) in one of these genes (BTß1) that confer resistance to multiple neonicotinoids. Transgenic D. melanogaster, where the native nAChR Dß1 was replaced with BTß1A58T&R79E, were significantly more resistant to neonicotinoids than flies where Dß1 were replaced with the wildtype BTß1 sequence, demonstrating the causal role of the mutations in resistance. The two mutations identified in this study replace two amino acids that are highly conserved in >200 insect species. Three-dimensional modelling suggests a molecular mechanism for this resistance, whereby A58T forms a hydrogen bond with the R79E side chain, which positions its negatively-charged carboxylate group to electrostatically repulse a neonicotinoid at the orthosteric site. Together these findings describe the first case of target-site resistance to neonicotinoids in B. tabaci and provide insight into the molecular determinants of neonicotinoid binding and selectivity.

Spectroscopic measurement of the two-dimensional flame temperature based on a perovskite single photodetector.

Existing non-contact flame temperature measuring methods depend on complex, bulky and expensive optical instruments, which make it difficult for portable applications and high-density distributed networking monitoring. Here, we demonstrate a flame temperature imaging method based on a perovskite single photodetector. High-quality perovskite film epitaxy grows on the SiO2/Si substrate to fabricate the photodetector. Duo to the Si/MAPbBr3 heterojunction, the light detection wavelength is extended from 400 nm to 900 nm. Then, a perovskite single photodetector spectrometer has been developed using the deep-learning method for spectroscopic measurement of flame temperature. In the temperature test experiment, the spectral line of doping element K+ has been selected to measure the flame temperature. The photoresponsivity function of the wavelength was learned based on a commercial standard blackbody source. The spectral line of element K+ has been reconstructed using the photocurrents matrix by the regression solving photoresponsivity function. As a validation experiment, the "NUC" pattern is realized by scanning the perovskite single-pixel photodetector. Finally, the flame temperature of adulterated element K+ has been imaged with the error of 5%. It provides a way to develop high precision, portable, low-cost flame temperature imaging technology.

Perovskite single-detector visible-light spectrometer.

We demonstrate a perovskite single-phototransistor visible-light spectrometer based on a deep-learning method. The size of the spectrometer is set to the scale of the phototransistor. A photoresponsivity matrix for the deep-learning system is learned from the characteristic parameters of the visible-light wavelength, gate voltage, and power densities of a commercial standard blackbody source. Unknown spectra are reconstructed using the corresponding photocurrent vectors. As a confirmatory experiment, a 532-nm laser and multipeak broadband spectrum are successfully reconstructed using our perovskite single-phototransistor spectrometer. The resolution is improved to 1 nm by increasing the number of sampling points from 80 to 400. In addition, a way to further improve the resolution is provided by increasing the number of sampling points, characteristic parameters, and training datasets. Furthermore, artificial intelligence technology may open pathways for on-chip visible-light spectroscopy.

Over-expression of UDP-glycosyltransferase UGT353G2 confers resistance to neonicotinoids in whitefly (Bemisia tabaci).

The whitefly, Bemisia tabaci, comes up high metabolic resistance to most neonicotinoids in long-term evolution, which is the key problem of pest control. UGT glycosyltransferase, as a secondary detoxification enzyme, plays an indispensable role in detoxification metabolism. In this study, UGT inhibitors, 5-nitrouracil and sulfinpyrazone, dramatically augmented the toxic damage of neonicotinoids to B. tabaci. A UGT named UGT353G2 was identified in whitefly, which was notably up-regulated in resistant strain (3.92 folds), and could be induced by most neonicotinoids. Additionally, the using of RNA interference (RNAi) suppresses UGT353G2 substantially increased sensitivity to neonicotinoids in resistant strain. Our results support that UGT353G2 may be involved in the neonicotinoids resistance of whitefly. These findings will help further verify the functional role of UGTs in neonicotinoid resistance.

Novel_miR-1517 mediates CYP6CM1 to regulate imidacloprid resistance in Bemisia tabaci (Hemiptera: Gennadius).

Bemisia tabaci (Hemiptera: Gennadius) is a notorious pest that is capable of feeding on >600 kinds of agricultural crops. Imidacloprid is critical in managing pest with sucking mouthparts, such as B. tabaci. However, the field population of B. tabaci has evolved resistance because of insecticide overuse. The overexpression of the detoxification enzyme cytochrome P450 monooxygenase is considered the main mechanism of imidacloprid resistance, but the mechanism underlying gene regulation remains unclear. MicroRNAs are a type of endogenous small molecule compounds that is fundamental in regulating gene expression at the post-transcriptional level. Whether miRNAs are related to the imidacloprid resistance of B. tabaci remains unknown. To gain deep insight into imidacloprid resistance, we conducted on miRNAs expression profiling of two B. tabaci Mediterranean (MED) strains with 19-fold resistance through deep sequencing of small RNAs. A total of 8 known and 1591 novel miRNAs were identified. In addition, 16 miRNAs showed significant difference in expression levels between the two strains, as verified by quantitative reverse transcription PCR. Among these, novel_miR-376, 1517, and 1136 significantly expressed at low levels in resistant samples, decreasing by 36.9%, 60.2%, and 15.6%, respectively. Moreover, modulating novel_miR-1517 expression by feeding with 1517 inhibitor and 1517 mimic significantly affected B. tabaci imidacloprid susceptibility by regulating CYP6CM1 expression. In this article, miRNAs related to imidacloprid resistance of B. tabaci were systematically screened and identified, providing important information for the miRNA-based technological innovation for this pest management.

Manganese-Catalyzed Redox-Neutral Thiolation of Alkyl Halides with Thioformates.

Transition metal-catalyzed C-S cross-coupling has emerged as an important strategy to furnish thioethers; however, the dominant utilization of noble metal catalysts as well as the construction of challenging C(sp3 )-S bonds by transition metal-catalysis remain highly problematic. Earth-abundant manganese has gathered increasing interest as an attractive catalyst for new reaction development; nevertheless, C(sp3 )-S cross-coupling reaction by manganese catalysis has not been reported. Herein, we disclose a highly efficient manganese-catalyzed redox-neutral thiolation of a broad range of alkyl halides with thioformates as practical sulfuration agents. Strategically, employing easily synthesized thioformates as thiyl radical precursors allows access to various aryl and alkyl thioethers in good to excellent yields. Notably, this redox-neutral method avoids the utilization of strong bases, external ligands, forcing reaction conditions, and stoichiometric manganese, thus presenting apparent advantages, such as broad substrate scope, excellent functional group compatibility, and mild reaction conditions. Finally, the utilities of this method are also illustrated by downstream transformations and late-stage thiolation of structurally complex natural products and pharmaceuticals.

Research on the Dynamic Model of Fireball Thermal Dose Based on the Effective Band Integral Method.

In the brief combustion process of an explosive fireball, the fireball can release considerable radiant energy. Aiming at the problem that the Stephen-Boltzmann formula calculates the fireball surface radiant energy (full band), it does not match the working bands of most infrared thermal imagers. So, in this paper, we obtain dynamic parameters such as the temperature, diameter, and height of the fireball from the infrared thermal image of the thermobaric explosive fireball, achieve on-site atmospheric transmittance by the temperature calibration target, and integrate within the effective wavelength band of the infrared thermal imager, and a precise dynamic model of the fireball's thermal radiation dose was finally established. According to the fireball test data of the infrared thermal imaging camera in the 2-5 µm band, the heat dose of the fireball at different distances is calculated, which is about 1/2.5 of the calculation result of the Stephen-Boltzmann full-band integral formula. The calculations in this paper are more accurate than measurements from existing static models and provide a better assessment of the thermal damage performance of various types of munitions.

Flame Imaging Technology Based on 64-Pixel Area Array Sensor.

High-resolution flame temperature images are essential indicators for evaluating combustion conditions. Tunable diode laser absorption spectroscopy (TDLAS) is an effective combustion diagnostic method. In actual engineering, due to the limitation of line-of-sight (LOS) measurement, TDLAS technology has the problems of small data volume and low dimensionality in measuring combustion fields, which seriously limits the development of TDLAS in combustion diagnosis. This article demonstrates a TDLAS imaging method based on a 64-pixel area array sensor to reconstruct the two-dimensional temperature field of the flame. This paper verifies the robustness of the Algebraic Reconstruction Technique (ART) algorithm through numerical simulation and studies the effects of temperature, concentration, and pressure on the second harmonic intensity based on the HITRAN database. The two-dimensional temperature field of the flame was reconstructed, and reconstruction accuracy was verified using thermocouples. The maximum relative error was 3.71%. The TDLAS detection system based on a 64-pixel area array sensor provides a way to develop high-precision, high-complexity flame temperature measurement technology.

Knockdown of the Nicotinic Acetylcholine Receptor ß1 Subunit Decreases the Susceptibility to Five Neonicotinoid Insecticides in Whitefly (Bemisia tabaci).

The sweet potato whitefly, Bemisia tabaci, (Gennadius) (Hemiptera:Aleyrodidae) is a global pest of crops. Neonicotinoids are efficient insecticides used for control of this pest. Insecticidal targets of neonicotinoids are insect nicotinic acetylcholine receptors (nAChRs). Here, we characterized and cloned the full length of the nAChR ß1 subunit (BTß1) in B. tabaci and confirmed the consistency of BTß1 in B. tabaci MEAM1 and MED. Expression levels of BTß1 in different developmental stages and body parts of adults were investigated and compared in B. tabaci MED. dsRNA was prepared to knock down BTß1 in adult B. tabaci and significantly decreases the susceptibility to five neonicotinoid insecticides, including imidacloprid, clothianidin, thiacloprid, nitenpyram, and dinotefuran. This study indicated BTß1 as a notable site influencing the susceptibility of B. tabaci to neonicotinoids.

Flame Edge Detection Method Based on a Convolutional Neural Network.

In this study, an improved flame edge detector based on convolutional neural network (CNN) was proposed. The proposed method can generate edge graphs and extract edge graphs relatively effectively. Our network architecture was based on VGG16 primarily, the last two max-pooling operators and all full connection layers of the VGG16 network were deleted, and the rest was taken as the basic network. The images output by the five convolution layers were upsampled to the size of the input images and finally fused to the edge image. Error calculation and back propagation of the fusion image and label image are carried out to form a weakly supervised model. Using the open datasets BSDS500 to train the network, the ODS F-measure can reach 0.810. Various experiments were carried out on different flame and fire images, including butane-air flame, oxygen-ethanol flame, energetic material flame, and oxygen-acetylene premixed jet flame, and the infrared thermogram was also verified by our method. The results demonstrate the effectiveness and robustness of the proposed algorithm.

Current susceptibilities of brown planthopper Nilaparvata lugens to triflumezopyrim and other frequently used insecticides in China.

The brown planthopper is a notorious rice pest in many areas of Asia. The evolution of insecticide resistance in Nilaparvata lugens has become a serious problem in the effective control of this pest in the paddy field. In this article, the current susceptibility of N. lugens field populations to novel mesoionic insecticide triflumezopyrim and major classes of chemical insecticides was determined and compared. The monitoring results indicated that field populations of N. lugens had developed low resistance to triflumezopyrim (resistance ratio, RR: 1.3-7.3-fold) during 2015-2018 in China, and the median lethal concentration values varied from 0.05 to 0.29 mg/L. Additionally, during 2017 to 2018, field populations of N. lugens showed high resistance levels to thiamethoxam (RR: 456.1-1025.6-fold), imidacloprid (RR: 2195.3-6899.0-fold) and buprofezin (RR: 1241.5-4521.7-fold), moderate to high resistance levels to dinotefuran (RR: 97.6-320.1-fold), clothianidin (RR: 69.4-230.1-fold) and isoprocarb (RR: 44.1-108.0-fold), and low to moderate levels of resistance to chlorpyrifos (RR: 12.0-29.7-fold) and nitenpyram (RR: 6.9-24.1-fold). In contrast, N. lugens just showed low resistance to sulfoxaflor (RR: 3.3-8.5-fold) and etofenprox (RR: 5.0-9.1-fold) in the field. Additionally, the P450 gene CYP6ER1 was found to be significantly overexpressed in all five field populations of N. lugens collected in 2018 when compared with a laboratory susceptible strain. Our findings will provide useful information to delay the evolution of insecticide resistance in N. lugens.

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To understand the adaptation mechanism of Machilus pauhoi seedlings to environmental changes, leaf functional traits of M. pauhoi seedlings from nine provenances, as well as relationships between leaf traits and environmental factors were analyzed. The results showed that leaf functional traits of M. pauhoi seedlings from different provenances showed significant intraspecific variations, with the coefficient of variation ranging from 8.8% to 28.2%. Specific leaf area, leaf relative water content, leaf tissue density and leaf thickness differed significantly among seedlings from different provenances, implying high leaf morphological plasticity. Moreover, leaf tissue density was positively correlated to leaf dry matter content and leaf relative water content, but negatively correlated to specific leaf area and leaf thickness. Specific leaf area showed significantly negative correlations with leaf dry matter content and leaf area. The covariation among those traits examined here indicated that M. pauhoi seedlings could adjust and balance the combination of leaf traits in response to environmental changes. Longitude, latitude, >10 ℃ annual accumulated temperature and mean annual temperature contributed largely to the variation of leaf functional traits of M. pauhoi seedlings. Leaf thickness decreased with the increase of longitude, while leaf dry matter content and leaf relative water content increased with the increase of longitude. Leaf tissue density was positively correlated with longitude and mean annual temperature, suggesting that longitude rather than mean annual temperature had greater effects on it. Leaf area was positively correlated with >10 ℃ annual accumulated temperature and longitude, indicating that annual accumulated temperature rather than longitude had greater effects on the variation of leaf area.