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Traditional cancer therapy methods, especially those directed against specific intracellular targets or signaling pathways, are not powerful enough to overcome tumor heterogeneity and therapeutic resistance. Oncolytic peptides that can induce membrane lysis-mediated cancer cell death and subsequent anticancer immune responses, has provided a new paradigm for cancer therapy. However, the clinical application of oncolytic peptides is always limited by some factors such as unsatisfactory bio-distribution, poor stability, and off-target toxicity. To overcome these limitations, oncolytic polymers stand out as prospective therapeutic materials owing to their high stability, chemical versatility, and scalable production capacity, which has the potential to drive a revolution in cancer treatment. This review provides an overview of the mechanism and structure-activity relationship of oncolytic peptides. Then the oncolytic peptides-mediated combination therapy and the nano-delivery strategies for oncolytic peptides are summarized. Emphatically, the current research progress of oncolytic polymers has been highlighted. Lastly, the challenges and prospects in the development of oncolytic polymers are discussed.

Background and aims: Preeclampsia (PE) is the leading cause of maternal and fetal morbidity and mortality worldwide. Apoptosis of trophoblast cells induced by oxidative stress is a principal reason of placental injury in PE. 6-Gingerol, an antioxidant from ginger, plays an important role in many disease models, but its effect on obstetric diseases has not been elucidated. In this study, we investigated the protective effect of 6-gingerol against placental injury.Methods:In vitro hypoxia/reoxygenation (H/R) model of HTR8/Svneo cells and preeclamptic mice model were established to simulate PE. The effects of 6-Gingerol on PE were evaluated by morphological detection, biochemical analysis, and Western blot.Results: We found that H/R treatment induced cell apoptosis, increased the production of reactive oxygen species, malondialdehyde and lactate dehydrogenase, and decreased superoxide dismutase in trophoblast. In addition, the polarization of mitochondrial membrane potential and the cellular calcium flux were also destroyed under H/R condition, which also activated BCL2-interacting protein 3 (BNIP3) and provoked excessive mitophagy. Importantly, 6-Gingerol reversed these corrosive effects. Furthermore, the placenta damage in PE-like mouse caused by the cell apoptosis, oxidative stress and mitophagy was mitigated by 6-Gingerol.Conclusion: These findings suggest that 6-Gingerol exerts a protective effect against placental injury in PE by reducing oxidative stress and inhibiting excessive mitophagy caused by mitochondrial dysfunction.

Considering that the centralized optimization control strategy is difficult to adapt to the access of large-scale electric vehicles, a distributed collaborative control strategy based on consensus algorithm is proposed in this paper to control the operation of multiple charging stations. In order to reduce the computational cost, a charging station aggregation model is established to reduce the optimization variables of large-scale electric vehicle access. According to the dispatching instructions issued by the distribution network, this method takes the economic operation of charging stations as the goal, satisfies the global and local constraints, and realizes the power allocation among charging stations. The case analysis proves the accuracy, effectiveness and robustness of the method, and the adaptability to large-scale electric vehicle access.

Under the background of the reform of energy development strategy and low oil prices, the sustainable development of oilfields faces multiple challenges of new energy squeeze, energy conservation and emission reduction, and low-cost development. Since oilfield development is a fairly complex process, only a more accurate prediction of oilfield output can better plan oilfield exploitation, reduce production investment, improve productivity, and promote the sustained and steady development of the oilfield economy. Based on summarizing the common oilfield production forecasting models: Weng’s model, decreasing yield model, time series method, machine learning method, etc., this paper analyzes and compares its similarities and differences, and proposes that the method based on the combined forecasting model is the development trend of oilfield production forecasting under the idea of low-carbon development in the future.

Abstract Background Type 3 fibroids are a special subtype of intramural fibroids that are likely to affect the pregnancy outcomes of assisted reproductive techniques. Hysteroscopic resection is a treatment for type 3 fibroids, but there has few study of its efficacy to date. In this study we evaluated the effect of hysteroscopic resection of type 3 fibroids on the pregnancy outcomes in infertile women. Methods This retrospective case–control study was conducted from January 1, 2014 to June 30, 2021. Patients who underwent IVF-ICSI in our unit were divided into a type 3 fibroid group and a hysteroscopic myomectomy group. The inclusion criteria for the type 3 fibroid group and the hysteroscopic myomectomy group were as follows: 1) age ≤ 40 years; 2) fibroid diameter or total fibroid diameter > 2.0 cm. The following exclusion criteria were used: 1) oocyte donor treatment cycles and 2) presence of chromosomal abnormalities; 3) history of other uterine surgery; 4) presence of intracavitary lesions, including submucosal fibroids; 5) single fibroid > 5.0 cm; 6) cervical fibroids; 7) unclear ultrasound description of fibroids; 8) preimplantation genetic testing was performed and 9) congenital or acquired uterine malformations. The control group in our study was selected from patients who were treated with IVF only because of fallopian tube factors. According to the age of the type 3 fibroid group and hysteroscopic myomectomy group, random sampling was carried out in the patients between 25 and 47 years of age to determine a control group. The outcomes measured included the average transfer times to live birth, cumulative clinical pregnancy rate, and cumulative live birth rate. Results A total of 302 cycles were enrolled in our study, including 125 cycles with type 3 fibroids, 122 cycles with hysteroscopic myomectomy, and 139 cycles of control patients. The average transfer times to live birth were significantly higher in the type 3 fibroid group than in the other two groups. The frequency of cumulative live births in the type 3 fibroid group was significantly lower than that in the control group. Compared with the control group, the hysteroscopic myomectomy patients had no statistically significant differences in the cumulative clinical pregnancy rate and cumulative live birth rate. Conclusions Type 3 fibroids significantly reduced the cumulative live birth rate of IVF patients. Ultrasound-guided hysteroscopic myomectomy can be used as a treatment for type 3 fibroids and could improve the pregnancy outcomes in infertile women.

Background: Diminished ovarian reserve is one of the most important causes of female infertility. In the etiology study of DOR, besides age, it is known that chromosomal abnormality, radiotherapy, chemotherapy and ovarian surgery can result in DOR. For young women without obvious risk factors, gene mutation should be considered as a possible cause. However, the specific molecular mechanism of DOR has not been fully elucidated.Methods: In order to explore the pathogenic variants related to DOR, twenty young women under 35 years old affected by DOR without definite factors damaging ovarian reserve were recruited as the research subjects, and five women with normal ovarian reserve were recruited as the control group. Whole exome sequencing was applied as the genomics research tool.Results: As a result, we obtained a set of mutated genes that may be related to DOR, where the missense variant on GPR84 was selected for further study. It is found that GPR84Y370H variant promotes the expression of proinflammatory cytokines (TNF-α, IL12B, IL-1β) and chemokines (CCL2, CCL5), as well as the activation of NF-κB signaling pathway.Conclusion: In conclusion, GPR84Y370H variant was identified though analysis for WES results of 20 DOR patients. The deleterious variant of GPR84 could be the potential molecular mechanism of non-age-related pathological DOR through its role in promoting inflammation. The findings of this study can be used as a preliminary research basis for the development of early molecular diagnosis and treatment target selection of DOR.

Abstract Backgroup Frozen-thawed embryo transfer is rising worldwide. One adverse effect of programmed frozen embryo transfer (FET) reported in some studies is an increased risk of adverse obstetric and perinatal outcomes. Meanwhile, body mass index (BMI) also has adverse effect on obstetric and perinatal outcomes. In this study, we investigated that the influence of different endometrial preparation protocols on obstetric and perinatal outcomes and the role of BMI in it. Method This retrospective cohort study included 2333 singleton deliveries after frozen-thaw embryo transfer at our centre between 2014 and 2021, including 550 cycles with programmed FET, 1783 cycles with true natural cycle FET (tNC-FET). In further analysis according to BMI grouped by Asian criterion, group A (18.5 kg/m2 ≤ BMI 0.05). The programmed FET cycles were associated to a higher risk of pregnancy-induced hypertension (PIH) compared with the tNC-FET cycles (7.3% vs 4.4%, crude OR 1.71[1.16–2.54]; adjusted OR 1.845[1.03–3.30]). After dividing the patients into three groups according to the BMI, The programmed FET cycles were associated to a higher risk of PIH in group C (14.4% vs 6.2%, crude OR 2.55 [1.42–4.55]; adjusted OR 4.71 [1.77–12.55]) compared with the tNC-FET cycles. But there was no statistically significant difference in group A and group B. Programmed FET group compared with the tNC-FET group, the risk of PIH increase as the body mass index increase. Conclusion This study showed a tendency toward increasing risk of PIH in programmed FET cycle compared with the tNC-FET cycle, and the risk of PIH increases as BMI increases. Increased risk of preterm birth and low birth weight is linked to increased risk of PIH.

With the rapid increase of electric vehicles (EVs), the uncoordinated charging of large-scale EVs will inevitably form a new peak of power consumption, which will put forward new requirements for the adjustment of EV charging behavior and the power supply capacity of the distribution network. However, upgrading the infrastructure of the distribution network is very expensive, so it is of great value to research on how to realize the optimal integration of EVs without infrastructure upgrading. In this paper, an intelligent grouping method is proposed considering the coupling relationship among EV travel information, battery status and other characteristics, and a charging/discharging priority model is established based on the contribution index of charging process. Finally, a smart real-time energy management strategy is formed in order to maximize the penetration level of EVs under current conditions. With the strategy proposed, the maximum penetration level of EVs is increased from 20% to 60% in the simulation. The strategy has good adaptability to the gradually growth of the base load, which can effectively delay infrastructure upgrading of the distribution network and reduce the overall operation cost of the station. It could furtherly provide a reference for the operation and upgrading of the parking lot charging station.

Continuous implicit representations can flexibly describe complex 3D geometry and offer excellent potential for 3D point cloud analysis. However, it remains challenging for existing point-based deep learning architectures to leverage the implicit representations due to the discrepancy in data structures between implicit fields and point clouds. In this work, we propose a new point cloud representation by integrating the 3D Cartesian coordinates with the intrinsic geometric information encapsulated in its implicit field. Specifically, we parameterize the continuous unsigned distance field around each point into a low-dimensional feature vector that captures the local geometry. Then we concatenate the 3D Cartesian coordinates of each point with its encoded implicit feature vector as the network input. The proposed method can be plugged into an existing network architecture as a module without trainable weights. We also introduce a novel local canonicalization approach to ensure the transformation-invariance of encoded implicit features. With its local mechanism, our implicit feature encoding module can be applied to not only point clouds of single objects but also those of complex real-world scenes. We have validated the effectiveness of our approach using five well-known point-based deep networks (i.e., PointNet, SuperPoint Graph, RandLA-Net, CurveNet, and Point Structuring Net) on object-level classification and scene-level semantic segmentation tasks. Extensive experiments on both synthetic and real-world datasets have demonstrated the effectiveness of the proposed point representation.

Large-scale distributed demand response is a hotspot in the development of power systems, which is of much significance in accelerating the consumption of new energy power generation and the process of clean energy substitution. However, the rigorous distributed algorithms utilized in current research studies are mostly very complicated for the large-scale demand response, requiring high quality of information systems. Considering the electrical features of power systems, a weak-consistency–oriented collaborative strategy is proposed for the practical implementation of the large-scale distributed demand response in this study. First, the basic conditions and objectives of demand response are explored from the view of system operators, and the challenges of large-scale demand response are discussed and furthermore modelled with a simplification based on the power system characteristics, including uncertainties and fluctuations. Then, a weakly consistent distributed strategy for demand response is proposed based on the Paxos distributed algorithm, where the information transmission is redesigned based on the electrical features to achieve better error tolerance. Using case studies with different information transmission error rates and other conditions, the proposed strategy is demonstrated to be an effective solution for the large-scale distributed demand response implementation, with a robust response capability under even remarkable transmission errors. By integrating the proposed strategy, the requirement for the large-scale distributed systems, especially the information systems, is highly eased, leading to the acceleration of the practical demand response implementation.

Large-scale fast charging of electric vehicles (EVs) probably causes voltage deviation problems in the distribution network. Installing energy storage systems (ESSs) in the fast-charging stations (FCSs) and formulating appropriate active power plans for ESSs is an effective way to reduce the local voltage deviation problem. Some deterministic centralized strategies used for ESSs at FCSs are proposed to solve the voltage deviation problem mentioned above. However, the randomness of the EV load is very large, which can probably reduce the effects of deterministic centralized strategies. A fast and reliable centralized strategy considering the randomness of the EV load for ESSs is a key requirement. Therefore, we propose in this paper a day-ahead scheduling strategy with the aim of maximizing the probability of the nodal voltage change being smaller than a preset limit at the observation node. In the proposed strategy, the uncertainty of EV load is taken into account and the probability of the voltage change of an observation node is quantified by a proposed analytic assessment model (AMM). Furthermore, a voltage change optimization model (VCOM) based on a novel control parameter β is proposed, where β can be used as a constraint to suppress the nodal voltage change at the observation node. Finally, the IEEE 33-bus test system is used to verify the effectiveness of the proposed day-ahead ESS strategy.

Load transfer is an important way of restoring a power supply after equipment failure or maintenance. However, current methods ignore cooperation between networks and users, and they also fail to take into account the vehicle-to-grid (V2G) potential of electric vehicles (EVs). In this paper, a load transfer scheme between transmission and distribution networks is proposed, considering the mobile energy storage capacities of electric vehicles. First, the mobility characteristic and the available discharge capacity of EVs are analyzed on the basis of the parking generation rate. Then, the breadth-first algorithm is used to search the load transfer paths within and between stations, and an edge matching method is proposed to realize the conversion between networks with different voltage levels. Lastly, the optimal combination weighting method was adopted to combine subjective and objective index weights and to evaluate power supply paths. The effectiveness of the proposed scheme is validated in a case composed of an IEEE 30-node network and an IEEE 57-node network, with four typical scenarios.

In recent years, the orderly charging of electric vehicles (EVs) in commercial parking has become a meaningful research topic due to the increasing number of EVs, especially for parking lots close to workplaces and serving fixed users. In this paper, a parking lot energy management system integrated with energy storage system (ESS) and photovoltaic (PV) system is established. The concept of energy price tag (EPT) is introduced to define the price of all energy storage devices, and the priority order between PV, ESS, EVs, and power grid is established. Taking the minimization of charging cost as the optimization objective, the charging plans of ESS, EVs, and buildings are optimized considering the constraints of EVs user demand and PV power. By comparing the simulation results of four cases, it is proven that this strategy can reduce the charging cost and improve the consumption rate of PV.

The scattering properties of nonspherical particles can be approximately computed by equivalent spherical theory. The scattering properties of ice particles were approximately computed by Rayleigh approximation because the sizes of the ice particles are smaller than the wavelength of millimeter wave radar. Based on the above assumption, the echo fluctuation of moving particles was analyzed by computing the total backscattering field of a cirrus cloud using the classical vector potential technique. The simulation results showed that echo fluctuation influences the accuracy of retrieving the physical parameters of a cloud. To suppress the echo fluctuation of moving ice particles, a video integrator of a millimeter wave cloud radar would be used. However, video integrators lose the rapidly changing information of ice particles and reduce radar range resolution; thus, we propose the pace-diversity technique of MIMO radar to reduce the echo fluctuation, which could be validated by theoretical computation and experimental measurements.

We carried out radar cross-section (RSC) measurements of ice particles in a microwave anechoic chamber at Nanjing University of Information Science and Technology. We used microwave similarity theory to enlarge the size of particle from the micrometer to millimeter scale and to reduce the testing frequency from 94 GHz to 10 GHz. The microwave similarity theory was validated using the method of moments for single metal sphere, single dielectric sphere, and spherical and non-spherical dielectric particle swarms. The differences between the retrieved and theoretical results at 94 GHz were 0.016117%, 0.0023029%, 0.027627%, and 0.0046053%, respectively. We proposed a device that can measure the RCS of ice particles in the chamber based on the S21 parameter obtained from vector network analyzer. On the basis of the measured S21 parameter of the calibration material (metal plates) and their corresponding theoretical RCS values, the RCS values of a spherical Teflon particle swarm and cuboid candle particle swarm was retrieved at 10 GHz. In this case, the differences between the retrieved and theoretical results were 12.72% and 24.49% for the Teflon particle swarm and cuboid candle swarm, respectively.

Background and aims: Preeclampsia (PE) is the leading cause of maternal and fetal morbidity and mortality worldwide. Apoptosis of trophoblast cells induced by oxidative stress is a principal reason of placental injury in PE. 6-Gingerol, an antioxidant from ginger, plays an important role in many disease models, but its effect on obstetric diseases has not been elucidated. In this study, we investigated the protective effect of 6-gingerol against placental injury. Methods: In vitro hypoxia/reoxygenation (H/R) model of HTR8/Svneo cells and preeclamptic mice model were established to simulate PE. The effects of 6- Gingerol on PE were evaluated by morphological detection, biochemical analysis, and Western blot. Results: We found that H/R treatment induced cell apoptosis, increased the production of reactive oxygen species, malondialdehyde and lactate dehydrogenase, and decreased superoxide dismutase in trophoblast. In addition, the polarization of mitochondrial membrane potential and the cellular calcium flux were also destroyed under H/R condition, which also activated BCL2-interacting protein 3 (BNIP3) and provoked excessive mitophagy. Importantly, 6-Gingerol reversed these corrosive effects. Furthermore, the placenta damage in PE-like mouse caused by the cell apoptosis, oxidative stress and mitophagy was mitigated by 6-Gingerol. Conclusion: These findings suggest that 6-Gingerol exerts a protective effect against placental injury in PE by reducing oxidative stress and inhibiting excessive mitophagy caused by mitochondrial dysfunction. [ABSTRACT FROM AUTHOR]

为探索食用葵花籽清选、分级、选种、定价的理论依据，完善建立葵花籽的离散元法分析模型，对食用葵花籽的主要尺寸及均齐性进行了分析。选择内蒙古自治区主栽的3个品种食用葵花籽（1013、SH361、SH363）为研究对象，使用统计学方法，以籽粒的三轴尺寸(长度、宽度、厚度)、平均径（算术平均径、几何平均径）、百粒重为指标，分析葵花籽三轴尺寸的统计分布特性、均齐性以及平均径与百粒重的关系，并按宽度对葵花籽进行了清选分级试验。结果表明：不同品种葵花籽的三轴尺寸均服从正态分布并存在线性相关，且总体上存在显著性差异；葵花籽的均齐性存在差异且其几何平均径、算术平均径与百粒重的变化趋势一致；1013品种选用圆孔筛10 mm和8 mm规格，SH361和SH363品种选用圆孔筛10 mm和8.5 mm规格时，分级效果满足要求。In order to explore the theoretical basis for cleaning, grading, selection, pricing of sunflower seeds, and improve the discrete component analysis model of sunflower seeds, the main dimensions and homogeneity of edible sunflower seeds were analyzed. The three typical edible sunflower seeds (1013, SH361, SH363) planted in Inner Mongolia Autonomous Region were used as research objects, and the statistical distribution characteristics of the three-axis sizes, homogeneity and relationship between average diameter and hundred-grain weight of the sunflower seeds were analyzed with the three-axis size(length, width and thickness), mean size(geometric mean diameter, arithmetic mean diameter) and hundred-grain weight as indexes. The width grading test of sunflower seeds was carried out. The results showed that the three-axis sizes of different varieties of sunflower seeds followed a normal distribution and were linearly correlated with significant differences in general. The homogeneity of sunflower seeds was different, and its geometric mean diameter, arithmetic mean diameter and hundred-grain weight had the same changing trend. When round hole sieves of 10 mm and 8 mm were used for 1013, and round hole sieves of 10 mm and 8.5 mm were used for SH361 and SH363, the grading effect could meet the requirement.