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BACKGROUND: The wettability of target crop surfaces affects pesticide wetting and deposition. The structure and properties of the leaf surface of litchi leaves undergo severe changes after infestation by Aceria litchii (Keifer). The objective of this study was to systematically investigate the surface texture and wettability of litchi leaves infested. RESULTS: Firstly, the investigation focused on the surface structure and physicochemical properties of litchi leaves infested with Aceria litchii. Subsequently, different levels of Contact Angle (CA) were measured individually on the infested litchi leaves. Lastly, Surface Free Energy (SFE) and its polar and dispersive components were calculated using the Owens‐Wendt‐Rabel‐Kaelble (OWRK) method. The outcomes revealed distinctive 3D surface structures of the erineum at various stages of mycorrhizal growth. At stage NO. 1, the height of the fungus displayed a peaked appearance, with the skewness value indicating a surface characterized by more crests. In contrast, at stages NO. 2 and NO. 3, the surface appeared relatively flat. Furthermore, post‐infestation of litchi leaves, the CA of droplets on the abaxial surface of diseased leaves exhibited an increase, while the SFE value on the abaxial surface of leaves decreased significantly, in contrast to the abaxial surface of healthy leaves. CONCLUSION: The infestation behavior of Aceria litchii changed the surface structure and chemistry of litchi leaves, which directly affected the CA value of foliar liquids and the SFE value of leaves, changing the surface wettability of litchi leaves from hydrophobic to superhydrophobic. This study provides useful information for improving the wetting and deposition behavior of liquid droplets on the surface of infested leaves. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Plant height is regarded as a key indicator that is crucial for assessing the crop growth status and predicting yield. In this study, an advanced method based on solid-state LiDAR technology is proposed, which is specifically designed to accurately capture the phenotypic characteristics of plant height during the maize growth cycle. By segmenting the scanned point cloud of maize, detailed point cloud data of a single maize plant were successfully extracted, from which stem information was accurately measured to obtain accurate plant height information. In this study, we will concentrate on the analysis of individual maize plants. Leveraging the advantages of solid-state LiDAR technology in precisely capturing phenotypic information, the data processing approach for individual maize plants, as compared to an entire maize community, will better restore the maize's original growth patterns. This will enable the acquisition of more accurate maize plant height information and more clearly demonstrate the potential of solid-state LiDAR in capturing detailed phenotypic information. To enhance the universality of the research findings, this study meticulously selected key growth stages of maize for data validation and comparison, encompassing the tasseling, silking, and maturity phases. At these crucial stages, 20 maize plants at the tasseling stage, 40 at the flowering stage, and 40 at the maturity stage were randomly selected, totaling 100 samples for analysis. Each sample not only included actual measurement values but also included plant height information extracted using point cloud technology. The observation period was set from 20 June to 20 September 2021. This period encompasses the three key growth stages of maize described above, and each growth stage included one round of data collection, with three rounds of data collection each, each spaced about a week apart, for a total of nine data collections. To ensure the accuracy and reliability of the data, all collections were performed at noon when the natural wind speed was controlled within the range of 0 to 1.5 m/s and the weather was clear. The findings demonstrate that the root mean square error (RMSE) of the maize plant height data, procured through LiDAR technology, stands at 1.27 cm, the mean absolute percentage error (MAPE) hovers around 0.77%, and the peak R2 value attained is 0.99. These metrics collectively attest to the method's ongoing high efficiency and precision in capturing the plant height information. In the comparative study of different stem growth stages, especially at the maturity stage, the MAPE of the plant height was reduced to 0.57%, which is a significant improvement compared to the performance at the nodulation and sprouting stage. These results effectively demonstrate that the maize phenotypic information extraction method based on solid-state LiDAR technology is not only highly accurate and effective but is also effective on individual plants, which provides a reliable reference for applying the technique to a wider range of plant populations and extending it to the whole farmland. [ABSTRACT FROM AUTHOR]

The precision detection of dense small targets in orchards is critical for the visual perception of agricultural picking robots. At present, the visual detection algorithms for plums still have a poor recognition effect due to the characteristics of small plum shapes and dense growth. Thus, this paper proposed a lightweight model based on the improved You Only Look Once version 4 (YOLOv4) to detect dense plums in orchards. First, we employed a data augmentation method based on category balance to alleviate the imbalance in the number of plums of different maturity levels and insufficient data quantity. Second, we abandoned Center and Scale Prediction Darknet53 (CSPDarknet53) and chose a lighter MobilenetV3 on selecting backbone feature extraction networks. In the feature fusion stage, we used depthwise separable convolution (DSC) instead of standard convolution to achieve the purpose of reducing model parameters. To solve the insufficient feature extraction problem of dense targets, this model achieved fine-grained detection by introducing a 152 × 152 feature layer. The Focal loss and complete intersection over union (CIOU) loss were joined to balance the contribution of hard-to-classify and easy-to-classify samples to the total loss. Then, the improved model was trained through transfer learning at different stages. Finally, several groups of detection experiments were designed to evaluate the performance of the improved model. The results showed that the improved YOLOv4 model had the best mean average precision (mAP) performance than YOLOv4, YOLOv4-tiny, and MobileNet-Single Shot Multibox Detector (MobileNet-SSD). Compared with some results from the YOLOv4 model, the model size of the improved model is compressed by 77.85%, the parameters are only 17.92% of the original model parameters, and the detection speed is accelerated by 112%. In addition, the influence of the automatic data balance algorithm on the accuracy of the model and the detection effect of the improved model under different illumination angles, different intensity levels, and different types of occlusions were discussed in this paper. It is indicated that the improved detection model has strong robustness and high accuracy under the real natural environment, which can provide data reference for the subsequent orchard yield estimation and engineering applications of robot picking work. [ABSTRACT FROM AUTHOR]

Background: Unmanned Aerial Vehicles (UAVs) applied to agricultural plant protection is widely used, and the field of operation is expanding due to their high efficiency and pesticide application reduction. However, the work on pesticide drift lags behind the development of the UAV spraying device. Methods: We compared the spray drift potential at four liquid pressures of 2, 3, 4, and 5 bar ejected from the hydraulic nozzles mounted on a UAV test platform exposed to different wind speeds of 2, 4, and 6 m/s produced by a wind tunnel. The combination of the wind tunnel and the UAV test platform was used to obtain strict test conditions. The droplet size distribution under spray drift pressures was measured by a laser diffraction instrument. Results: Increasing the pressure leads to smaller droplet volume diameters and produced fine droplets of less than 100 µm. The deposition in the drift area was elevated at most of the sampling locations by setting higher pressure and faster wind speed. The deposition ratios were all higher than the flow ratios under three wind speeds after the adjustment of pressures. For most samples within a short drift distance (2–8 m), the drift with the rotor motor off was more than an order of magnitude higher than that with the rotor motor on at a pressure of 3 bar. Conclusions: In this study, the wind speed and liquid pressure all had a significant effect on the UAV spray drift, and the rotor wind significantly inhibited a large number of droplets from drifting further. [ABSTRACT FROM AUTHOR]

BACKGROUND: Agricultural pests and diseases affect grain yield and quality. In addition to the use of chemical agents, the biological control of diseases and insect pests has attracted more and more attention due to an urgent need for environmental protection. However, traditional operational methods do not integrate well with biological control technology. With the advantages of simple operation, low operating cost, high operating efficiency and wide application range, use of multirotor unmanned aerial vehicles (UAVs) in biological control is of great significance. RESULTS: An intelligent delivery system comprising an insect natural enemy (Trichogramma) capsule based on an M45 electric multirotor UAV was built to release Trichogramma ostriniae in corn fields under full autonomous mode. During operation, the M45 UAV can fly accurately in accordance with operational requirements; average deviation between the actual and planned routes was 0.24 m, the average flight speed was 9.18 m s−1 and the average altitude was 5.08 m. The effective coverage rate of natural enemies was 99.33% and the coverage redundancy was 36.75%. After delivery, an investigation into the field control effect showed an average control effect of 83.70%, which can result in effective pest control. CONCLUSION: A natural enemy carrier intelligent delivery system based on an M45 electric multirotor UAV was found to have good flight performance. In addition, natural enemies were evenly distributed, giving even coverage of the target fields. The system had a good control effect. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Whether different injection modes of α-galactosylceramide (α-GalCer) affect the activation of different subsets of invariant natural killer T (iNKT) cells in different tissues and organs of mice is unclear. This study included healthy control, subcutaneous injection, and intraperitoneal injection groups (n=10 in each group). The subcutaneous and intraperitoneal injection groups were injected with α-Galcer (0.1 mg/kg weight), and then the changes in thymus, spleen, and liver iNKT cell frequencies and subsets were observed. The intraperitoneal injection of α-GalCer could increase the frequency of splenic iNKT cells, but the subcutaneous injection did not affect the frequency. Neither injection had any effect on the frequency of iNKT cells in the thymus and liver. The subcutaneous injection of α-GalCer increased the rate of iNKT2 subsets in the thymus but did not affect the rate of iNKT1 subsets. However, the intraperitoneal injection of α-GalCer did not affect thymus iNKT1 and iNKT2 subsets. Interestingly, the subcutaneous injection of α-GalCer significantly increased the proportion of iNKT1 in the spleen and liver but did not significantly change the proportion of iNKT2. The intraperitoneal injection of α-GalCer significantly increased the rate of iNKT2 in spleen and liver but decreased the rate of iNKT1. Subsets of iNKT1 or iNKT2 cells in the spleen and liver were selectively activated by the subcutaneous or intraperitoneal injection of α-GalCer. It provides a valuable means for treating tumors and certain autoimmune diseases. Further exploration of the activation mechanism may provide new ideas about the development of related vaccines. [ABSTRACT FROM AUTHOR]

Wind field is one of the important factors affecting the distribution characteristics of aerial spraying droplet deposition. In order to reveal the impact mechanism of droplet deposition distribution by the wind field below agricultural unmanned helicopter rotor, in this study, the wind field distribution below uniaxial single-rotor electric unmanned helicopter rotor was measured by using a wireless wind speed sensor network measurement system for unmanned helicopter. The effects of wind field in three directions (X, Y, Z) below the rotor on droplet deposition distribution were analyzed with the condition of aerial spraying droplet deposition in rice canopy, and the regression model was established via variance and regression analyses of experiment results. The results showed that, the wind field in Y direction had a significant effect on droplet deposition in effective spray area, the wind field in Z direction had an extremely significant effect on droplet deposition in effective spray area, and the corresponding significance (sig.) values were 0.011 and 0.000. Furthermore, the wind field in Z direction had a significant effect on the penetrability and uniformity of droplet deposition in effective spray area, the corresponding sig. values were 0.025 and 0.011 respectively. The wind speed in Y direction at the edge of effective spray area had a significant effect on droplet drift, the sig. value was 0.021. In addition, the correlation coefficient R of the regression model was 0.869 between droplet deposition in effective spray area and the wind speed in Y and Z directions, and 0.915 between the uniformity of droplet deposition in effective spray area and the maximum wind speed in Z direction. The result revealed the influencing mechanism of the wind field below the rotor of uniaxial single-rotor electric unmanned helicopter on the distribution of aerial spraying droplet deposition. The results can provide guidance for the actual production application of aerial spraying to reduce liquid drift and improve the utilization rate of pesticide. [ABSTRACT FROM AUTHOR]

Modern technologies and information tools can be used to maximize agricultural aviation productivity allowing for precision application of agrochemical products. This paper reviews and summarizes the state-of-the-art in precision agricultural aviation technology highlighting remote sensing, aerial spraying and ground verification technologies. Further, the authors forecast the future of precision agricultural aviation technology with key development directions in precision agricultural aviation technologies, such as real-time image processing, variable-rate spraying, multi-sensor data fusion and RTK differential positioning, and other supporting technologies for UAV-based aerial spraying. This review is expected to provide references for peers by summarizing the history and achievements, and encourage further development of precision agricultural aviation technologies. [ABSTRACT FROM AUTHOR]

Automation of images registration and stitching is one of the most important key technologies to the wide use of the low-altitude remote sensing by Micro-UAVs (unmanned aerial vehicles) in rice growing. In order to overcome the limitations, i.e. the thresholds need to be artificially determined for the traditional Harris corner detection algorithm, this paper proposed a self-adaptive algorithm for Harris corner detection, which was used in image registration and stitching of the rice low-altitude remote sensing. The algorithm was improved based on the traditional Harris corner detection algorithm by using a self-adaptive threshold determination method, which calculated from the standard deviation of image pixel gray-scale value. And then the characteristics of image were described by corners, and the images were registered by using the Euclidean distance among descriptors. In order to verify the effectiveness of the algorithm and optimize the relevant parameters, a verification test was conducted based on low-altitude remote sensing images, which were gained by a multispectral camera mounted on a multi-rotor unmanned helicopter during rice tillering stage. Four indices, the repetition rate (a measure of the stability of corner detection), the recognition rate (a measure of corner recognizable description operator), the registration rate (a measure of the accuracy of image registration and stitching) and running time of algorithm (a measure of computing speed of the algorithm), were proposed to evaluate the results of registration and stitching. Sixty images were randomly divided into 3 groups for verification test. Test results showed that the average registration rate reached 98.95%, and also the average repetition rate reached 96%, which indicated that the proposed algorithm had high accuracy. The repetition rate and the difference in image registration rates among the groups were not significant (at 0.05 significance level), which indicated that the proposed algorithm was stable and reliable. And the recognition rate among the groups was significant, and it indicated that the proposed algorithm had higher distinguishability to the remote sensing images, which was conducive to the precision of the automation of images registration and stitching. Threshold value of the proposed algorithm, which is the standard deviation of the image pixel gray values after standardization, here is set to 1 and 2 for optimization test. Test results showed that the registration rate was not significant, namely there was no significant difference (at 0.05 significance level) when the threshold value was equal to 1 or 2. However, comparing the average running time of the proposed algorithm, it showed that the running time when the threshold value was 1, is 2.5 times that when the threshold value was 2. Based on comprehensive consideration of the registration rate, the running time and the efficiency, the threshold value of 2 can be set as the optimum parameter of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The aerial spraying of pesticides by plant protection unmanned aerial vehicles (UAV) is a process in which the spray droplet deposition on target sites occurs under the influence of the downwash wind field. The downwash wind field is the most important factor affecting droplet deposition distribution characteristics in an aerial spray. To understand the mechanism of the downwash wind field, spray tests were conducted at different flight heights by using a DJI UAV, and the downwash wind field in the three-dimensional direction (X-directional wind, Y-crosswind, and Z-vertical wind) was measured by using a wind speed measurement system for UAV. Combined with the droplet deposition of aerial spray, the distribution characteristics of the downwash wind field and the influence of the downwash wind field on droplet deposition were studied. The results showed that it had obvious differences in the distribution of the downwash wind field for UAV at different flight heights. As the flight height increases, the downwash wind field in X-direction and Z-direction showed a strong to weak trend, while the downwash wind field in Y-direction showed an opposite trend. In addition, it was found that the downwash wind field in Y-direction and Z-direction both have a significant influence on droplet deposition. With the increase of flight height, the change of the downwash wind field led to a gradual decrease in droplet deposition in the effective spray area, and droplets deposited more uniformly. For the DJI T16 plant protection UAV in this test, the optimal flight height was 2.0 m, and the downwash wind field had a better improvement effect on droplet deposition. Therefore, in order to make full use of the downwash wind field of UAV, the appropriate flight height should be selected to improve droplet deposition of liquid pesticide and achieve a better control effect for crop disease and pests when UAV is used for aerial spray operations in the field. This study revealed the influence mechanism of the downwash wind field on droplet deposition of aerial spray, and proposed appropriate operation parameters from the perspective of practical operation. It was expected to provide data support for improving the operation quality of aerial spraying and the formulation of field operation specifications. [ABSTRACT FROM AUTHOR]

In the field of pesticide spraying, droplet size is one of the most important factors affecting droplet deposition and drift. In order to study the effect of different droplet size parameters on droplet deposition distribution and drift of aerial spraying by using plant protection UAV, an aerial spraying test with the same spraying rate and different size droplets in rice canopy was carried out by using multi-rotor unmanned aerial vehicles (UAV) and four TEEJET nozzles with different orifice sizes (these droplets with a volume median diameter (VMD) of 95.21, 121.43, 147.28, and 185.09 μm, respectively), and the deposition distribution and penetration of droplets in the target area and the drift distribution of droplets in the non-target area were compared and analyzed. The results showed that the deposition distribution and penetration of droplets in the target area and the drift distribution of droplets in the non-target area were influenced by the droplet size. The droplet deposition rate in the upper and lower rice canopies were increased in the target area with the increase of droplet size. The penetration results of droplets also increased with the increase of droplet size, and that of droplets with a VMD of 185.09 μm was the best, reaching 38.13%. The average values of the cumulative drift rate of droplets in the rice canopy in the four tests were 73.87%, 50.26%, 35.91%, and 23.06%, respectively, and the cumulative drift rate and the drift distance of droplets decreased with the increase of droplet size, which indicated that the increase of droplet size can effectively reduce droplet drift. It demonstrated that the droplet size is one of the most important factors affecting droplet deposition and drift for pesticide spraying by plant protection UAV, and for the application of plant protection UAV with extra-low volume spraying, the use of droplets with VMD less than 160 μm should be avoided and a more than 10 m buffer zone should be considered downwind of the spraying field to avoid drug damage caused by pesticide drift. The results have fully revealed the effect of droplet size parameters on droplet deposition and drift of aerial spraying. Moreover, the influence of the wind field below the rotors on the distribution of droplet deposition was surmised and analyzed from the perspective of plant protection UAV. It is important for optimizing the droplet parameters of aerial spraying, increasing the spraying efficiency, and realizing precision agricultural aviation spray. [ABSTRACT FROM AUTHOR]

Abstract Background The therapeutic effect of adoptive infusion of specific thymus-derived invariant natural killer T (iNKT) cells in a mouse model of rheumatoid arthritis (RA) was observed, and the mechanism of cellular immunotherapy was preliminarily explored. Methods Thymus-derived iNKT cells were infused to RA model mice, with α-GalCer as a positive control. Then, ankle swelling was examined, as well as inflammatory cell infiltration to the joint tissue (hematoxylin-eosin [H&E] staining). Flow cytometry (FCM) was used to assess iNKT cell and helper T lymphocyte (Th) subsets. Serum cytokine levels were determined with cytometric bead array (CBA), with protein expression levels of related transcription factors assessed by Western blot. Results The joint swelling in RA model animals were significantly improved in the cell therapy and α-GalCer positive control groups (P < 0.05). In addition, iNKT frequencies in peripheral blood, the thymus and spleen were increased significantly (P < 0.05). Meanwhile, iNKT1 subset frequencies in the thymus and spleen were decreased, as well as splenic Th1 and Th17 cell subset rates, and serum TNF-α, IFN-γ and IL-6 levels. The rates of iNKT2 and Th2 subsets as well as IL-4 and IL-10 levels were increased (P < 0.05). Thymus GATA-3 and splenic PLZF protein levels were increased (P < 0.05). Conclusions Adoptive infusion of thymus-derived iNKT cells exerts therapeutic effects in RA mice by increasing iNKT frequency, altering the proportions of iNKT cell subsets, correcting Th cell subset imbalance and reducing the amounts of inflammatory cytokines. Graphical abstract Unlabelled Image Highlights • The iNKT1 involved in and iNKT2 suppression of inflammatory response in RA. • Adoptive infusion of iNKT can correct the immune imbalance caused by Th1 and Th17. • iNKT therapy promotes Th0 to Th2 differentiation via up-regulating GATA3 expression. [ABSTRACT FROM AUTHOR]

The wind field produced by the rotor-wing UAV has a significant impact on the distribution of rice pollen, which directly influences hybrid rice breeding. This research aimed to explore the distribution law of rice pollen in the wind field of small UAV. Aviation Beidou Positioning System UB351 positions all sampling nodes for precise corresponding coordinates and spacing information, and draws UVA's flying trajectories, thus providing accurate data for tests. Wireless sensor network measurement system was used to study the three-direction wind field produced by the rotor-wing UAV under various experimental factors and acquires wind field width and wind speed, and the data were compared with the area ratio and width of pollen distribution. Test of univariate normality was conducted through Shapiro-Wilk test and Kolmogorov-Smimov test. In order to figure out the appropriate flight speed for UAV's pollination under pollen distribution law, it is also necessary to perform analysis of variances on regression model. The comparison of wind speed in longitudinal (X) and lateral (Y) direction show that as the major force of the horizontal wind field produced by the rotor-wing UAV, the wind from Y-direction forms the widest wind field. Moreover, flight speed mainly influences wind field width. To be specific, the width of horizontal wind field decreases as flight speed increases. Meanwhile, UAV flight speed also exerts significant impact on vertical wind field. Both the pollen distribution width of more than 5 pollen grains and the area ratio reached the maximum when the UAV flight was at 4.53 m/s, which was the most favorable speed to pollination. In addition, pollen quantity is closely associated with both horizontal and vertical wind field. With comparison of the pollen quantity of sampling nodes, it was found that the wind field produced by the rotor-wing UAV exerted asymmetrical impact on pollen distribution. Q-Q plot of SPSS verifies that pollen distribution is against normal distribution. The establishment of a multiple linear regression model of pollen distribution and wind speed in three directions indicates that pollen distribution quantity only shares positive linear relation with the wind field in X-direction. These findings provide a theoretical guidance for rice pollination by using agricultural UAVs. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) applications at low-volume using fine and very fine size droplets have been adopted in several commercial spray scenarios allowing water-saving and high-efficiency operation in delivery of pesticides. However, spray drift associated with UAV applications, especially for fine droplets generated from spinning disk nozzles, has not been fully understood, raising environmental and regulatory concerns. The objectives of this study were to compare the drift potential of three different volume median diameter (VMD, or Dv 0.5) of 100, 150 and 200 μm from a commercial quadcopter equipped with centrifugal nozzles exposed to different wind speeds under field conditions. Prior to field test, the droplet size of the centrifugal nozzle was measured by a laser-diffraction particle-size analyzer. The results showed that the relationship between rotation speed and Dv 0.5 agrees with the negative power function. Field tests found that the deposition at 12 m downwind direction decreased by an order of magnitude compared with the average deposition within the in-swath zone. The deposition of almost all the treatments at 50 m downwind is lower than the detection limits of 0.0002 μL/cm2. Based on the results from this study, the drift distance of this specific very popular UAV model is much less than that of manned aerial applicators. Based on the predicted equation (R2 = 0.83), the detected drift amount increased with increasing wind speed and decreasing Dv 0.5. This work provides basic information to quantify the effect of wind speeds and droplet sizes on UAV spray drift potential which supports on-going regulatory guideline development for spray buffer zone and drift risk assessment protocols. Unlabelled Image • When the rotation speed of the centrifugal nozzle increased from 2000 rpm to 17,000 rpm, the droplet size category changed from Extremely Coarse to Fine. • The deposition at 12 m downwind generally decreases by an order of magnitude compared with the in-swath zone. • A downwind prediction equation for the UAV sprayer was formulated to predict the expected magnitude of the deposited drift. • Based on the test results, the drift distance of the tested UAV model is much less than that of manned aerial applicators. [ABSTRACT FROM AUTHOR]

• α-GalCer activates iNKT10 cells of adipose tissue by subcutaneous injection. • iNKT10 cells promote M2 macrophage polarization in adipose tissue. • Activation of iNKT10 and M2 macrophages improves inflammation of adipose tissue. The role of iNKT cells was investigated in chronic adipose tissue inflammation in obese mice after administration of α-GalCer in different pathways. C57BL/6J mice were fed high-fat diet (HFD) for 12 weeks to establish the obese mouse model. The pathology of adipose tissue was observed by H&E staining. The rates of iNKT cells, macrophages and cell subsets in adipose tissue were detected by FCM. Cytokine levels in serum and adipose tissue lymphocyte-stimulated supernatants were assessed with the CBA kit. The expression levels of related transcription factor in adipose tissue were detected by Western blot. The proportions of iNKT cells, iNKT10 cells and M2 macrophages were decreased, while those of iNKT1 and M1 macrophages were increased in adipose tissue of HFD-fed mice. The expression levels of the related transcriptional proteins E4BP4 and Arg-1 were decreased while iNOS expression was increased in adipose tissue. Administration of α-GalCer by subcutaneous injection resulted in increased rates of iNKT10 cells and M2 macrophages, and decreased amounts of M1 macrophages in adipose tissue of HFD-fed mice. The expression of E4BP4 and Arg-1 were up-regulated, but iNOS was down-regulated. Meanwhile, infiltration of inflammatory cells into adipose tissue was further reduced. The imbalance between the proportions of iNKT1 and iNKT10 cells may be involved in the development of chronic inflammation in obese adipose tissue. Administration of α-GalCer by subcutaneous injection in HFD-fed mice activates adipose tissue iNKT10 cells, which promote M2 macrophage polarization and improve chronic inflammation in obese adipose tissue. [ABSTRACT FROM AUTHOR]

The existence of association between the subpopulation of iNKT cells with different functions and nonalcoholic fatty liver disease has not been confirmed. To investigative the role of iNKT cells in the pathogenesis of nonalcoholic fatty liver disease, we established a non-alcoholic fatty liver model by feeding C57BL/6J mice for 12 weeks with a high-fat diet and injecting α-GalCer through different routes to activate hepatic iNKT cells. The liver of the mice fed a high-fat diet (HFD) had severe hepatic steatosis appearance, elevated pro-inflammatory cytokines and reduced anti-inflammatory cytokines in the liver, and high serum levels of TC, LDL, HDL, and ALT. Our results showed that the percentage of iNKT cells in the liver of the HFD-fed mice was lower than that of the control mice. The expression levels of the related transcription factor of T-bet increased but that of GATA-3 decreased in the HFD-fed mice. The administration of α-GalCer by intraperitoneal injection resulted in increasing of hepatic iNKT and iNKT2 cells but decreasing of hepatic iNKT1 cells, and the expression of GATA-3 and anti-inflammatory cytokine (IL-4) was increased in the liver, and hepatic steatosis was ameliorated in the HFD-fed mice. The administration of α-GalCer by subcutaneous injection resulted in a decrease in hepatic iNKT and iNKT2 and an augmentation of hepatic iNKT1 cells. However, hepatic steatosis was not significantly improved. We concluded that the intraperitoneal injection with α-GalCer effectively improved hepatic steatosis, according to increasing the number of hepatic iNKT2 cells. The precise mechanism requires further exploration. Unlabelled Image • The number of hepatic iNKT cells is reduced in model mice of NAFLD. • α-GalCer activates hepatic iNKT1 cells by subcutaneous injection. • α-GalCer activates hepatic iNKT2 cells by intraperitoneal injection. • Activation of hepatic iNKT2 effectively improves hepatic steatosis. [ABSTRACT FROM AUTHOR]

Multi-rotor unmanned aerial vehicle (UAV) is a new chemical application tool for tall stalk tropical crop Areca catechu , which could improve deposit performance, reduce operator healthy risk, and increase spraying efficiency. In this work, a spraying experiment was carried out in two A. catechu fields with two leaf area index (LAI) values, and different operational parameters were set. Spray deposit quality, spray drift, and ground loss were studied and evaluated. The results showed that the larger the LAI of A. catechu , the lesser the coverage of the chemical deposition. The maximum coverage could reach 4.28% and the minimum 0.33%. At a flight speed of 1.5 m/s, sprayed droplets had the best penetration and worst ground loss. The overall deposition effect was poor when the flight altitudes were greater than 11.09 m and the flight speed was over 2.5 m/s. Comparing flight speed of 2.5 to 1.5 m/s, the overall distance of 90% of the total drift increased to double under the same operating parameters. This study presents reference data for UAV chemical application in A. catechu protection., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Ma, Chen, Yao, Yan, Zeng, Chen and Lan.)

In aerial spraying of plant protection UAVs, the continuous reduction of pesticides is an objective process. Under the condition of constant flight state (speed and altitude), the change of pesticide loading will inevitably lead to the shift of lift force and rotor speed generated by UAV rotor rotation, which will change the distribution of the rotor flow field and affect the effect of aerial spraying operation of plant protection UAV. Therefore, the rotor speed of UAV is taken as the research object in this paper, and the adaptive refinement physical model based on the Lattice Boltzmann Method (LBM) is used to numerically simulate the rotor flow field of the quadrotor plant-protection UAV at different speeds. A high-speed particle image velocimeter (PIV) was used to obtain and verify the motion state of the droplets emitted from the fan nozzle in the rotor flow field at different speeds. The results show that, with the increase of rotor speed, the maximum velocity and vorticity of the wind field under the rotor increase gradually, the top wind speed can reach 13m/s, and the maximum vorticity can reach 589.64 s -1 . Moreover, the maximum velocity flow value is mainly concentrated within 1m below the rotor, and the maximum vorticity value is primarily concentrated within 0.5m. However, with the increase of time, the ultimate value of velocity and vorticity decreases due to the appearance of turbulence, and the distribution of velocity and vorticity are symmetrically distributed along the centre line of the fuselage, within the range of (-1m, 1m) in the X direction. It is consistent with the motion state of droplets under the action of the rotor downwash flow field obtained by PIV. The study results are expected to reveal and understand the change law of the rotor flow field of plant protection UAVs with the dynamic change of pesticide loading to provide a theoretical basis for the development of precise spraying operation mode of plant protection UAVs and improve the operation effect., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Chang, Chen, Wang, Xue and Lan.)

As a major global pest, fall armyworm (FAW), Spodoptera frugiperda , invaded China in 2019, which has seriously threatened the safety of China's food production and raised widespread concerns. As a new low-volume application technology, an unmanned aerial spray system (UASS) is playing an important role in the control of FAW in China. However, the studies on the effect of the water application volume on the efficacy of FAW using UASS have been limited. In this study, Kromekote® cards were used to sample the deposition. The method of using a sampling pole and sampling leaf for the determination of deposition. Four water application volumes (7.5, 15.0, 22.5, and 30.0 L/ha) were evaluated with regard to the corn FAW control efficacy. A blank control was used as a comparison. The control efficacy was assessed at 1, 3, 7, and 14 days after treatment (DAT). The tested results showed that sampling methods have a significant effect on deposition results. The number of spray deposits and coverage on the sampling pole were 35 and 40% higher than those on the sampling leaves, respectively. The deposition and control efficacy gradually increased as the water application volume increased. The control efficacy at 14 DAT under different water application volumes was in the range of 59.4-85.4%. These data suggest that UASS spraying can be used to achieve a satisfying control of FAW, but the control efficacy of the water application volume of 30.0 and 22.5 L/ha did not differ significantly. Considering work efficiency, a water application volume of 22.5 L/ha is recommended for field operation., Competing Interests: JWu and HW were employed by Corteva Agroscience Technology (Shanghai) Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Shan, Wu, Song, Chen, Wang, Wang, Wang and Lan.)

Rheumatoid arthritis (RA) is a complex chronic inflammatory autoimmune disease. The pathogenesis of the disease is related to invariant natural killer T (iNKT) cells. Patients with active RA present fewer iNKT cells, defective cell function, and excessive polarization of Th1. In this study, an RA animal model was established using a mixture of hGPI325-339 and hGPI469-483 peptides. The iNKT cells were obtained by in vivo induction and in vitro purification, followed by infusion into RA mice for adoptive immunotherapy. The in vivo imaging system (IVIS) tracking revealed that iNKT cells were mainly distributed in the spleen and liver. On day 12 after cell therapy, the disease progression slowed down significantly, the clinical symptoms were alleviated, the abundance of iNKT cells in the thymus increased, the proportion of iNKT1 in the thymus decreased, and the levels of TNF-α, IFN-γ, and IL-6 in the serum decreased. Adoptive immunotherapy of iNKT cells restored the balance of immune cells and corrected the excessive inflammation of the body.