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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]

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]

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]

Epigenetic modifications have been shown to be important for immune cell differentiation by regulating gene transcription. However, the role and mechanism of histone methylation in the development and differentiation of iNKT cells in rheumatoid arthritis (RA) mice have yet to be deciphered. The DBA/1 mouse RA model was established by using a modified GPI mixed peptide. We demonstrated that total peripheral blood, thymus, and spleen iNKT cells in RA mice decreased significantly, while iNKT1 in the thymus and spleen was increased significantly. PLZF protein and PLZF mRNA levels were significantly decreased in thymus DP T cells, while T-bet protein and mRNA were significantly increased in thymus iNKT cells. We found a marked accumulation in H3K27me3 around the promoter regions of the signature gene Zbtb16 in RA mice thymus DP T cells, and an accumulation of H3K4me3 around the promoters of the Tbx21 gene in iNKT cells. The expression levels of UTX in the thymus of RA mice were significantly reduced. The changes in the above indicators were particularly significant in the progressive phase of inflammation (11 days after modeling) and the peak phase of inflammation (14 days after modeling) in RA mice. Developmental and differentiation defects of iNKT cells in RA mice were associated with abnormal methylation levels (H3K27me3 and H3K4me3) in the promoters of key genes Zbtb16 (encoding PLZF) and Tbx21 (encoding T-bet). Decreased UTX of thymus histone demethylase levels resulted in the accumulation of H3K27me3 modification. [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]

During the aerial spraying of pesticides by plant protection UAVs (unmanned aerial vehicles), droplets are deposited below the aircraft under the influence of rotor airflow. The existence of a downwash airflow can improve the deposition of spray on target crops. However, during operation, variations in flight altitude and the gradual decrease in the payload of pesticide solution in the tank leads to changes in the flow field below the UAV which affects droplets distribution. In order to study this, the downwash airflow speed and droplet distributions below a UAV under different flight altitudes (1.5–3 m) and payloads (0-10 kg) were measured and analysed. The results indicated that the changes in operational parameters normally found during operation can change distribution of downwash airflow in all directions but particularly vertical and this can affect the distribution of spray below the UAV. Through correlation analysis, it was shown that the vertical component of airflow (downwash) had a significant positive correlation with spray deposition and penetration (P < 0.05, B = 0.082, B = 0.029), and a negative correlation with droplet deposition uniformity (coefficient of variation) and drift (P < 0.05, B = −3.818, B = −0.042). Thus, it can be seen that downwash is conducive to spray deposition and penetration, which can improve the droplet distribution uniformity and reduce drift. Thus, the influence mechanism of UAV airflow on droplet distribution was explored and shown to strongly influence have the quality of spraying by plant protection UAVs. • Wireless wind speed sensors used to test the downwash airflow UAV. • Reduction in payload affects the downwash airflow of UAV. • Downwash airflow of UAV in turn affects spray distribution. • Vertical downwash airflow has a significant correlation with droplet distribution. [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]

• A single boll weight prediction model for cotton was established. • Using FCN to extract cotton bolls from images can improve the accuracy of prediction. • The model can make large-scale predictions of cotton single boll weight. Single boll weight is the main factor of cotton yield and a key index used to evaluate the quality of cotton. Predicting the single boll weight in a large area is important for variety selection and yield improvement. A model was established to predict the single boll weight by using the multitemporal high-resolution visible light remote sensing data obtained from UAV. Specifically, remote sensing data were collected for 29 fields in the Changji, Shihezi and Shawan areas in northern Xinjiang during the blooming period and boll opening stage. Five circular areas with a radius of 1 m were selected from each field as the ground investigation area for collection of the cotton boll samples. Fully convolutional networks (FCN) was used to recognize and extract bolls at the boll opening stage in the remote sensing images as a dependent variable of the model. Correlation analysis was carried out by combining VDVI (Visible-band difference vegetation index) at the flowering and boll setting stages, VDVI at boll opening stages, VDVI at boll opening areas (Extracted by FCN) and RGB mean values, then use the least squares linear regression and BP neural networks to model the upper, middle, lower cotton layers and average single boll weight in investigation area. Subsequently, K-fold cross-validation was performed to evaluate the results. The results showed that the results of the least squares linear regression (R2 = 0.8162) and BP neural networks (R2 = 0.8170) were nearly equivalent. The percentage of boll opening in the area and VDVI at the flowering and boll setting stages were highly correlated with upper single boll weight. This study proposes a method to realize the large scale prediction of single boll weight, which provided a new idea for cotton yield prediction and breeding screening. [ABSTRACT FROM AUTHOR]

In recent times, Wireless Sensor Network (WSN) technology is widely applied in various agricultural applications. However, when a WSN becomes large and complex, it is difficult to maintain and adjust the whole WSN or multiple WSNs manually. Therefore, we propose an UAV-based scheme for automatic delivery and recovery of WSN nodes in the field. This scheme includes a combination of specially designed UAV, node platforms together with a GNSS-RTK (Global Navigation Satellite System, Real – Time Kinematic) system. A prototype system was built to test the UAV-based scheme. The results and analyses of indoor and outdoor experiments demonstrated the feasibility and efficacy of the scheme. [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]