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With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if a new wind tunnel is designed, the experimental data may be insufficient to build a controlling model. This article reports research on the following two models: (1) for a 0.6 m continuous transonic wind tunnel supported by a large amount of historical data, the false nearest neighbor (FNN) algorithm was adopted to calculate the order of the input variables, and the nonlinear auto-regressive model with the exogenous inputs–backpropagation network (NARX-BP) was proposed to build its Mach number prediction model; (2) for a new 2.4 m continuous transonic wind tunnel with only a small amount of experimental data, the method of model migration, the input and output slope/bias correction–particle swarm optimization (IOSBC-PSO) algorithm, was developed to convert the old model of the 0.6 m wind tunnel into the new model of the 2.4 m wind tunnel, so that the new Mach number prediction could be conducted. Through simulation experiments, it was found that by introducing the NARX-BP algorithm to build the Mach number prediction model, the root-mean-square error (RMSE) of the model decreased by 44.93–77.90%, and the maximum deviation (MD) decreased by 64.05–85.32% compared to the BP model. The performance of the IOSBC-PSO migration model was also better than that of the non-migration model, as evidenced by the 82.06% decrease of the RMSE value and the 78.25% decrease of the MD value. The experiments showed the effectiveness of the proposed strategy.

Productive Lytic Replication in LECs, but not in BECs

Kaposi sarcoma is the most common cancer in human immunodeficiency virus–positive individuals and is caused by Kaposi sarcoma–associated herpesvirus (KSHV). It is believed that a small number of latently infected Kaposi sarcoma tumor cells undergo spontaneous lytic reactivation to produce viral progeny for infection of new cells. Here, we use matched donor-derived human dermal blood and lymphatic endothelial cells (BEC and LEC, respectively) to show that KSHV-infected BECs progressively lose viral genome as they proliferate. In sharp contrast, KSHV-infected LECs predominantly entered lytic replication, underwent cell lysis, and released new virus. Continuous lytic cell lysis and de novo infection allowed LEC culture to remain infected for a prolonged time. Because of the strong propensity of LECs toward lytic replication, LECs maintained virus as a population, despite the death of individual host cells from lytic lysis. The master regulator of lymphatic development, Prox1, bound the promoter of the RTA gene to upregulate its expression and physically interacted with RTA protein to coregulate lytic genes. Thus, LECs may serve as a proficient viral reservoir that provides viral progeny for continuous de novo infection of tumor origin cells, and potentially BECs and mesenchymal stem cells, which give rise to Kaposi sarcoma tumors. Our study reveals drastically different host cell behaviors between BEC and LEC and defines the underlying mechanisms of the lymphatic cell environment supporting persistent infection in Kaposi sarcoma tumors.Significance:This study defines the mechanism by which Kaposi's sarcoma could be maintained by virus constantly produced by lymphatic cells in HIV-positive individuals.

Considering the mismatch of complex process models under the influence of external environment changes and uncertain disturbance, the optimization results are not the real optimal values, and the process operating performance deviates from the optimal operation, a real-time optimization compensation method based on a two-level multi-block is proposed. Firstly, the interval plant-wide hierarchical optimization (IPHO) method is used to perform the uncertain optimization for the hydrometallurgical plant-wide process. The hierarchical optimization method is adopted, which simplifies the optimization model and realizes the hierarchical compensation operation when the process is running at the non-optimal grade. Furthermore, the interval number-based uncertain optimization method is utilized to solve the uncertain optimization problem in the presence of uncertain disturbance variables under the upper procedure-layer. Secondly, the data compensation method based on just-in-time learning (JITL) is constructed, which realizes the real-time compensation operation of the production index set-points obtained by the optimization of the procedure-layer. Thirdly, to realize the optimization compensation of the lower process layer, the real-time optimization compensation method based on self-optimization control (SOC) is proposed to compensate the manipulated variables set-points of each sub-block. Therefore, within a certain disturbance range, the operation compensation of the non-optimal operation process can be realized by performing the above-mentioned hierarchical compensation decision in real-time. Finally, an industrial simulation experiment of the hydrometallurgical production process is carried out. Compared with the traditional operation optimization and compensation methods, the proposed method can realize the self-optimization adjustment of the non-optimal operation process faster and more effectively, which can minimize the economic loss of the plant-wide production process.

Thickening-dewatering process is widely used for solid–liquid separation in mineral processing plants. Usually, the feed quantity of the thickener is an uncertain variable, so the underflow concentration of the thickener cannot be accurately predicted, which may result in improper operation and high security risk. This paper proposes a stochastic chance-constrained optimization framework for the thickening-dewatering process with the uncertain feed quantity. Firstly, a feed quantity predictive model is established by gray correlation analysis (GCA) and partial least squares (PLS) to reduce the uncertainty of the feed quantity. Then, the stochastic chance-constrained optimization model of the thickening-dewatering process is established to minimize the energy economic index (EEI). In order to solve the stochastic chance-constrained optimization model, the nonlinear time-of-use electricity price function in the objective is linearized, and then the stochastic chance-constrained optimization model is transformed into a deterministic model. The cases study illustrate that the optimization framework can reduce the EEI and the security risk of the thickening-dewatering process.

Background: Mutations in PIEZO1 (Piezo type mechanosensitive ion channel component 1) cause human lymphatic malformations. We have previously uncovered an ORAI1 (ORAI calcium release-activated calcium modulator 1)-mediated mechanotransduction pathway that triggers lymphatic sprouting through Notch downregulation in response to fluid flow. However, the identity of its upstream mechanosensor remains unknown. This study aimed to identify and characterize the molecular sensor that translates the flow-mediated external signal to the Orai1-regulated lymphatic expansion. Methods: Various mutant mouse models, cellular, biochemical, and molecular biology tools, and a mouse tail lymphedema model were employed to elucidate the role of Piezo1 in flow-induced lymphatic growth and regeneration. Results: Piezo1 was found to be abundantly expressed in lymphatic endothelial cells. Piezo1 knockdown in cultured lymphatic endothelial cells inhibited the laminar flow-induced calcium influx and abrogated the flow-mediated regulation of the Orai1 downstream genes, such as KLF2 (Krüppel-like factor 2), DTX1 (Deltex E3 ubiquitin ligase 1), DTX3L (Deltex E3 ubiquitin ligase 3L,) and NOTCH1 (Notch receptor 1), which are involved in lymphatic sprouting. Conversely, stimulation of Piezo1 activated the Orai1-regulated mechanotransduction in the absence of fluid flow. Piezo1-mediated mechanotransduction was significantly blocked by Orai1 inhibition, establishing the epistatic relationship between Piezo1 and Orai1. Lymphatic-specific conditional Piezo1 knockout largely phenocopied sprouting defects shown in Orai1- or Klf2- knockout lymphatics during embryo development. Postnatal deletion of Piezo1 induced lymphatic regression in adults. Ectopic Dtx3L expression rescued the lymphatic defects caused by Piezo1 knockout, affirming that the Piezo1 promotes lymphatic sprouting through Notch downregulation. Consistently, transgenic Piezo1 expression or pharmacological Piezo1 activation enhanced lymphatic sprouting. Finally, we assessed a potential therapeutic value of Piezo1 activation in lymphatic regeneration and found that a Piezo1 agonist, Yoda1, effectively suppressed postsurgical lymphedema development. Conclusions: Piezo1 is an upstream mechanosensor for the lymphatic mechanotransduction pathway and regulates lymphatic growth in response to external physical stimuli. Piezo1 activation presents a novel therapeutic opportunity for preventing postsurgical lymphedema. The Piezo1-regulated lymphangiogenesis mechanism offers a molecular basis for Piezo1-associated lymphatic malformation in humans.

In order to improve the stability of dough with soybean oil, this article explored the effect of soybean oil addition on the rheological characteristics of dough under high hydrostatic pressure. The results showed that, compared with the dough without soybean oil, the β-sheet, disulfide bonds content, and gauche-gauche-gauche in the dough increased by 4.23%, 0.85 μmol/g, and 4.16%, respectively when the dough was added with 6% soybean oil, which improved the degree of cross-linking polymerization of gluten protein and the stability of gluten network. Meanwhile, the dough had the highest elastic modulus and the lowest maximum creep compliance (6.85 × 10

Soybean oil bodies (SOBs), a natural source of pre-emulsified oil, have important potential applications in food industry. In this study, SOBs were extracted from raw soybean milk at pH 5.0, 7.0, 8.0, 9.0 and 11.0. The pH 5.0-, 7.0- and 8.0-SOB contained extrinsic proteins (mainly 7S, 11S and γ-conglycinin) and oleosins (24 kDa, 18 kDa and 16 kDa), and pH 9.0-, 11.0-SOB only had oleosins. Extrinsic protein contents decreased from 83.9% at pH 5.0-SOB to 58.2% at pH 8.0-SOB, zeta potentials increased gradually from -21.7 mV to -14.67 mV and particle sizes decreased from 924 nm to 359 nm with increasing extraction pHs. In stomach digestion, oleosins of pH 5.0-, 7.0-, 8.0-SOB were hydrolyzed more rapidly than extrinsic proteins. All 24 kDa oleosins were hydrolyzed during 5 min, and 18 kDa oleosins were completely hydrolyzed at 30 min for all SOBs. Oleosins were hydrolyzed and produced15 kDa pepsin-resistant peptides. In addition, some 7S and 11S of pH 5.0-, 7.0-, 8.0-SOB resisted pepsin hydrolysis. For all SOB emulsions, zeta potentials decreased and the droplets sizes increased significantly (P 0.05) with the extension of gastric digestive time. The oil droplets of all SOB emulsions aggregated, and the coalescence of oil droplets more easily occurred in pH 9.0- and 11.0-SOB emulsions. During the intestinal phase, zeta potentials and diameters of the droplets decreased gradually, and the droplets of SOB emulsions dispersed according to the CLSM. FFA release rates of pH 5.0-, 7.0-, 8.0-SOB emulsions increased rapidly and then increased slowly, however, the release tendency of pH 9.0-, 11.0-SOB emulsions were opposite. Total FFA releases of pH 5.0-, 7.0-, 8.0-, 9.0-, 11.0-SOB emulsions were respectively 52.5%, 70.5%, 59%, 48.8%, 43.3% at 180 min. Therefore, the digestive behaviors of SOB emulsions extracted at different pHs were different. This study will provide guidance for SOB products.

In a wind tunnel process, Mach number is the most important parameter. However, it is difficult to measure directly, especially in the multimode operation process, leading to difficulty in process monitoring. Thus, it is necessary to measure the Mach number indirectly by utilizing data-driven methods, and based on which, to monitor the operation status of the wind tunnel process. In this paper, therefore, a multimode wind tunnel flow field system monitoring strategy is proposed. Since the wind tunnel system is a strongly nonlinear system, the kernel partial least squares method, which can efficiently handle the nonlinear regression problem, is utilized. Firstly, the Mach number is predicted utilizing the kernel partial least squares method. Secondly, process monitoring statistics, i.e., the Hotelling T2 statistic and the square prediction error, the SPE statistic, and their control limits, are proposed to be applied to monitor the wind tunnel process on the basis of the prediction of the Mach number. Finally, the Mach number prediction and monitoring strategy are applied to a real process, where mode analysis and division is necessary. After mode division, the single-mode and multimode processes are modeled and predicted, respectively, and both the single-mode and multimode processes are monitored online. Satisfactory results were achieved compared with those of the partial least squares method.

Kaposi sarcoma is the most common cancer in human immunodeficiency virus–positive individuals and is caused by Kaposi sarcoma–associated herpesvirus (KSHV). It is believed that a small number of latently infected Kaposi sarcoma tumor cells undergo spontaneous lytic reactivation to produce viral progeny for infection of new cells. Here, we use matched donor-derived human dermal blood and lymphatic endothelial cells (BEC and LEC, respectively) to show that KSHV-infected BECs progressively lose viral genome as they proliferate. In sharp contrast, KSHV-infected LECs predominantly entered lytic replication, underwent cell lysis, and released new virus. Continuous lytic cell lysis and de novo infection allowed LEC culture to remain infected for a prolonged time. Because of the strong propensity of LECs toward lytic replication, LECs maintained virus as a population, despite the death of individual host cells from lytic lysis. The master regulator of lymphatic development, Prox1, bound the promoter of the RTA gene to upregulate its expression and physically interacted with RTA protein to coregulate lytic genes. Thus, LECs may serve as a proficient viral reservoir that provides viral progeny for continuous de novo infection of tumor origin cells, and potentially BECs and mesenchymal stem cells, which give rise to Kaposi sarcoma tumors. Our study reveals drastically different host cell behaviors between BEC and LEC and defines the underlying mechanisms of the lymphatic cell environment supporting persistent infection in Kaposi sarcoma tumors. Significance: This study defines the mechanism by which Kaposi's sarcoma could be maintained by virus constantly produced by lymphatic cells in HIV-positive individuals.

The operational variables of the flotation industrial process (FIP) are controlled by the operators and are usually not adjusted in time. This makes it difficult to control the technical indexes such as concentrate grade within acceptable ranges. To resolve this problem, a Bayesian network (BN)-based modeling and operational adjustment method is investigated. Considering the complexity of modeling, a modular BN modeling framework for plantwide FIP is proposed. First, the plantwide FIP is decomposed into several related submodules, and corresponding local BNs are established through structure learning and parameter learning. Then, on the basis of the process knowledge and associated variables, each local BN is fused into the global BN. In the application, a novel operational adjustment framework for plantwide FIP is proposed. First, a global operational adjustment is inferred by setting the index of concentrate grade. Then, according to the obtained operational adjustment of each submodule from local to global, the concentrate grade is further predicted. Once the predicted result meets a certain condition, the current operational adjustment will be implemented right away. Data experiments evaluate the performance of the proposed method in the decision-making of operational adjustment.

In this paper, a two-dimensional, two-layer quality regression model is established to monitor multi-phase, multi-mode batch processes. Firstly, aiming at the multi-phase problem and the multi-mode problem simultaneously, the relations among modes and phases are captured through the analysis between process variables and quality variables by establishing a two-dimensional, two-layer regression partial least squares (PLS) model. The two-dimensional regression traces the intra-batch and inter-batch characteristics, while the two-layer structure establishes the relationship between the target process and historical modes and phases. Consequently, online monitoring is carried out for multi-phase, multi-mode batch processes based on quality prediction. In addition, the online quality prediction and monitoring results based on the proposed method and those based on the traditional phase mean PLS method are compared to prove the effectiveness of the proposed method.

BackgroundThere are limited therapeutic options for patients with progressive disease (PD) on or after PD-1–blocking antibody therapy. Vidutolimod (CMP-001) is a first-in-class, immunostimulatory virus-like particle containing a CpG-A Toll-like receptor 9 (TLR9) agonist. This phase 1b study evaluated the safety and clinical activity of intratumoral vidutolimod with and without pembrolizumab in patients with refractory melanoma.MethodsThis two-part, open-label, multicenter, phase 1b study (NCT02680184) enrolled adults with histologically confirmed metastatic or unresectable cutaneous melanoma who had stable disease after ≥12 weeks or PD on anti−PD-1 treatment, measurable disease per RECIST v1.1, ECOG PS 0/1, and ≥1 lesion accessible for intratumoral injection. Part 1 evaluated vidutolimod + pembrolizumab and Part 2 evaluated vidutolimod monotherapy. Key objectives included assessment of safety and clinical activity, and exploratory analyses were performed on available tumor biopsies using immunohistochemistry and RNAseq.ResultsAt data cutoff (August 17, 2021), 159 patients had enrolled in Part 1 and 40 patients in Part 2. The median age was 64 years in Part 1 (range, 30-90) and 68 years in Part 2 (range, 30-89). Most patients had PD as their last response to prior anti–PD-1 therapy (Part 1, 93.1%; Part 2, 80.0%). Grade 3/4 treatment-related adverse events (TRAEs) occurred in 37.1% of patients treated with vidutolimod + pembrolizumab and in 22.5% of patients treated with vidutolimod monotherapy. No treatment-related deaths occurred. Based on the efficacy data presented in Table 1, vidutolimod polysorbate 20 (PS20) A was selected for further development as this formulation in combination with pembrolizumab had a best objective response rate (ORR; RECIST v1.1) of 23.5%, with a median duration of response (DOR) of 25.2 months. Vidutolimod monotherapy had an ORR of 20.0%, with a median DOR of 5.6 months. Exploratory translational analyses identified association of unique biomarkers with response among patients with T cell–inflamed versus non-T cell–inflamed tumors at baseline.Abstract 950 Table 1Safety and clinical activity of vidutolomod ± pembrolizumabConclusionsPromising clinical activity was observed with vidutolimod + pembrolizumab and vidutolimod monotherapy in patients with PD-1 blockade–refractory melanoma. A manageable safety profile was observed. The DOR with vidutolimod + pembrolizumab was substantially longer than with vidutolimod monotherapy. Clinical studies to confirm the efficacy of vidutolimod + PD-1 blockade in patients with previously untreated unresectable/metastatic melanoma (phase 2/3, NCT04695977) or PD-1 blockade–refractory melanoma (phase 2, NCT04698187) are ongoing.AcknowledgementsThis work was supported by Checkmate Pharmaceuticals. Medical writing assistance was provided by Steffen Biechele, PhD (ApotheCom, San Francisco, CA, USA), and funded by Checkmate Pharmaceuticals.Trial RegistrationNCT02680184Ethics ApprovalThis study was approved by the WCG-WIRB; WIRB approval tracking number: 20152597.

There are unfavorable conditions such as constantly changing working conditions and frequent disturbances that affect Mach number control in wind tunnel flow fields. As the proportional, integral and differential (PID) parameters need to be re-tuned for each working conditions of a wind tunnel, the operational costs of wind tunnels are very high. Therefore, to lower these costs, a genetic algorithm was utilized to tune the PID parameters to achieve Mach number control of a multi-mode wind tunnel flow field. In this paper, firstly, models for the multi-mode wind tunnel were established; secondly, a PID control system was designed based on the genetic algorithm and the control effects of the proposed PID control system were verified by simulations and were compared with the effects of a PSO tuning PID control system.

In wind tunnels, the Mach number needs to be precisely monitored and controlled. It is difficult to obtain the Mach number directly online, especially when the wind tunnel system is operating in multiple modes. To deal with this problem, a Mach number prediction algorithm based on the kernel partial least squares method is proposed for multi-mode wind tunnel systems. First, in order to reflect real-time changes, the time-slice partial least squares regression method is adopted. Then, in order to enable the model to represent information about the whole working mode divided by key process variables, the mean-value partial least squares model is established and is compared with the time-slice model. Then, considering that wind tunnel systems exhibit strong nonlinear characteristics, the kernel partial least squares method, which is suitable for nonlinear systems, is used to predict the Mach number. The results show that the mean-value model is better than the time-slice model, the models for single modes show better prediction abilities than those for multiple modes, and the kernel partial least square method is more suitable for wind tunnel systems than the partial least square method.

In the batch processes, the transitional phase can be regarded as a connection process between its two neighboring stable phases. Thus, the effect on the transitional phase from its former phase to its latter phase exists. In this paper, a new transitional phase modeling and monitoring strategy is proposed. It provides two candidate models with respect to the effect of its two neighboring phases respectively. As a result, two candidate models are established for the transitional phase monitoring. To solve the above problem, an index is developed in this paper. The index is built with the combination of all the statistics and their corresponding control limits. In addition, as a key tool, it helps to select the suitable candidate model for every sample during the transitional phase. The reliability of the proposed strategy is illustrated with both the real three-tank experimental system and the Tennessee Eastman Process.

The process of hydrometallurgical has the characteristics of many sub-processes with complicated reaction mechanism and long process flow. How to keep the hydrometallurgical process running in the state of optimal economic efficiency is the difficulty task. In this paper, a method based on industrial big data is proposed to compensate the production index of the hydrometallurgical process. Based on the current production index, the just-in-time learning (JITL) idea is used to establish the model that describes the relationship between the compensation value and the economic benefit increment. Then, the compensation value of the current production index is calculated, and the result is applied to the production process. The simulation and offline experiment results verify the effectiveness of the proposed method.

Batch processes require effective quality analysis and prediction techniques to ensure product quality. In this paper, quality prediction work has been carried out for multiphase batch processes with slow time-varying characteristics based on the slow feature analysis (SFA) algorithm. To analyze the slow time-varying characteristics along the batch direction, sliding windows are constructed in the batch direction covering different batches, and accordingly a series of models are established using the SFA algorithm to capture the slow feature of the varying relationship between the process variables and the quality. At last, the proposed strategy is applied to the quality analysis and prediction of a typical slow time-varying batch process, the start-up process of the injection molding process, and the prediction results are compared with those obtained by the strategy using partial least squares (PLS) to build the regression models. The results verify the effectiveness of the proposed method in the quality prediction of slow time-varying batch processes.

In the process of wind tunnel experiments, it is often necessary to change the working condition of the wind tunnel. For the system which only uses the traditional PID controller, if the PID parameters are not adjusted in time, the control effect may become worse. Therefore, in this paper, first, for the working conditions with only a small number of data, transfer models are established and applied. Then, on the basis of PID control system, fuzzy controller is added to improve the control system. In addition, in the process of finding the optimal parameters of migration, genetic algorithm is used to achieve global optimization.

The Mach number is one of the most important variables in the wind tunnel system, which needs to be controlled precisely. Although there are mechanical principals to present the relationship between the Mach number and other process variables, it is hard to obtain the Mach number online directly, especially when the wind tunnel system operations in multiple modes. Therefore, in this paper, a Mach number prediction algorithm based on PLS is proposed for the multi-mode wind tunnel system, as well as the analysis strategy. First, on the premise of considering the control accuracy of the Mach number as well as the process characteristics, certain modes are identified and modelled for the Mach number prediction. Second, to reflect the real-time changes of the Mach number, time-slice-based PLS regression method is adopted. And then to further enhance the prediction accuracy, the analysis of process variables influence variance is carried out, and the variables with stable regression parameter are selected in the predictive model to reconduct the prediction. The method has been adopted to the real wind tunnel system, and the outcome demonstrates the effectiveness of the method.

The steam turbine regulating system is an important link of a steam turbine generator unit. The operating effect of the steam turbine is determined by the quality of control of the regulating system. In this paper, a particle swarm algorithm and fuzzy PID control are combined according to the regulation principle and characteristics of a steam turbine digital electro-hydraulic regulation system (DEH). Respective advantages of two control methods are taken to control the parameters in a loop and regulate the control quality of the system in real time according to the operation deviation change of the DEH control system. Finally, the system is better controlled.

Invasive breast cancer is highly regulated by tumor-derived cytokines in tumor microenvironment. The development of drugs that specifically target cytokines are promising in breast cancer treatment. In this study, we reported that arctigenin, a bioactive compound from

Glaucoma surgeries, such as trabeculectomy, are performed to lower intraocular pressure to reduce risk of vision loss. These surgeries create a new passage in the eye that reroutes the aqueous humor outflow to the subconjunctival space, where the fluid is presumably absorbed by the conjunctival lymphatics. Here, we characterized the development and function of the ocular lymphatics using transgenic lymphatic reporter mice and rats. We found that the limbal and conjunctival lymphatic networks are progressively formed from a primary lymphatic vessel that grows from the nasal-side medial canthus region at birth. This primary lymphatic vessel immediately branches out, invades the limbus and conjunctiva, and bidirectionally encircles the cornea. As a result, the distribution of the ocular lymphatics is significantly polarized toward the nasal side, and the limbal lymphatics are directly connected to the conjunctival lymphatics. New lymphatic sprouts are produced mainly from the nasal-side limbal lymphatics, posing the nasal side of the eye as more responsive to fluid drainage and inflammatory stimuli. Consistent with this polarized distribution of the ocular lymphatics, a higher drainage efficiency was observed in the nasal side than the temporal side of the eye when injected with a fluorescent tracer. In contrast, blood vessels are evenly distributed at the anterior surface of the eyes. Also, we found that these distinct vascular distribution patterns were conserved in human eyes. Together, our study demonstrated that the ocular surface lymphatics are more densely present in the nasal side and uncovered the potential clinical benefits in selecting the nasal side as a glaucoma surgery site to improve fluid drainage.

Soybean oil body (SOB), rich in polyunsaturated fatty acids and biologically active substances, is used as a natural emulsifier in food processing. In addition, SOB is healthier than synthetic emulsifiers. However, the physical and chemical properties of the SOB emulsion directly affect its application in food processing. In order to study the effect of water bath extraction (WBAE) on SOBs, the effects of WBAE method on the composition of SOBs, the zeta potential, average particle size, oxidation stability, and viscosity characteristics of SOB emulsions were researched. It was found that both protein and moisture contents of SOB decreased with increasing WBAE temperature; however, lipid content increased. These results were attributed to the exogenous proteins gradually denatured and dissociated with extraction temperature from 60°C to 100°C. Increasing the extraction temperature, the average particle size of the SOB emulsions increased, the oxidative stability was improved, the Zeta potential and viscosity decreased, and the fluidity of emulsions was improved. The SOB extracted at 100°C has broad application prospects in food, and this research is meaningful for supplying fundamental information for selecting proper extraction temperature of SOBs., In order to study the effect of water bath extraction (WBE) on soybean oil bodies, the effects of WBE methods on the composition of soybean oil bodies and the zeta potential, average particle size, oxidation stability, and viscosity characteristics of soybean oil body emulsions were studied. The results show that the soybean oil body obtained by WBE has broad application prospects in food.