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The isolation and subsequent molecular analysis of extracellular vesicles (EVs) derived from patient samples is a widely used strategy to understand vesicle biology and to facilitate biomarker discovery. Expressed prostatic secretions in urine are a tumor proximal fluid that has received significant attention as a source of potential prostate cancer (PCa) biomarkers for use in liquid biopsy protocols. Standard EV isolation methods like differential ultracentrifugation (dUC) co-isolate protein contaminants that mask lower-abundance proteins in typical mass spectrometry (MS) protocols. Further complicating the analysis of expressed prostatic secretions, uromodulin, also known as Tamm-Horsfall protein (THP), is present at high concentrations in urine. THP can form polymers that entrap EVs during purification, reducing yield. Disruption of THP polymer networks with dithiothreitol (DTT) can release trapped EVs, but smaller THP fibres co-isolate with EVs during subsequent ultracentrifugation. To resolve these challenges, we describe here a dUC method that incorporates THP polymer reduction and alkaline washing to improve EV isolation and deplete both THP and other common protein contaminants. When applied to human expressed prostatic secretions in urine, we achieved relative enrichment of known prostate and prostate cancer-associated EV-resident proteins. Our approach provides a promising strategy for global proteomic analyses of urinary EVs.

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.

BackgroundAs an excellent nondestructive testing technology, cold neutron radiography is widely employed to image materials of interest in many basic and application research fields. One of key components of such device is the neutron sensitive scintillation screen. Normally, these screens are made up of scintillation or phosphor powder mixed with/without neutron sensing isotopes, such as 6LiF:ZnS(Ag) and Gd2O2S:Tb. Uniform scintillation screens are very difficult to make a trade-off between spatial resolution and neutron detection efficiency. Recently a new type of micro-structural scintillation screens has been proposed, which is expected to have higher spatial resolution while maintaining higher neutron detection efficiency. Following this idea, a scintillation screen has been proposed, developed, and studied by our group.PurposeThis study aims to develop a new type of scintillation screens based on a glass capillary array filled with scintillation powders to achieve high spatial resolution and neutron detection efficiency.MethodsFirst of all, a neutron sensing scintillation screen was made by filling very fine grinded Gd2O2S:Tb phosphor powder into glass capillary arrays. Three main steps, i.e. the phosphor powder grinding, the particle size screening, and the vacuum suction filtration process, were taken making such screens. Then, photographs of Gd2O2S:Tb phosphor before and after grinding were taken with a scanning electron microscope (SEM) to examine the filling efficiency of scintillation powder in the glass capillary arrays. Finally, experimental test of spatial resolution of such scintillation screens was carried out by using an optical system to read out the scintillation light emitted by the screen, and a Siemens Star neutron test target to characterize the screens' spatial resolution with cold neutrons.ResultsX-ray luminescence spectra show that the grinding process reduces the light yield of the phosphor. The filling efficiency of scintillation powder in the glass capillary arrays is up to 70%. The cold neutron imaging system with developed scintillation screen achieves spatial resolution of about 300 μm@CTF=3% by experimental test.ConclusionsAlthough the new neutron sensing scintillation screen is still under-developing and there are still some problems to be overcome, cold neutron imaging scintillation screen based on glass capillary array filled with Gd2O2S:Tb phosphor, proposed in this study, can be used to achieve high spatial resolution and neutron detection efficiency with advantages of low cost and simple fabrication process.

In view of the current prosperity of China’s fresh market transactions, fresh e-commerce enterprises in the end of the construction of the logistics network of the pain point problem, this study of fresh e-commerce in the “last mile” distribution of site planning issues. This paper focuses on a fresh food ecommerce enterprise’s end distribution network and explores the key influencing factors in fresh food product distribution from three dimensions: timeliness, economy and service quality. And then establishes a mathematical model for selecting community stores for end distribution of fresh food e-commerce enterprises with the objectives of minimizing input costs and maximizing customer satisfaction. The model takes into account the costs of building and operating community stores and the transportation costs of distribution. In the model introduces three types of penalty costs due to site selection variability and transforms the model from a dual-objective to a single-objective model. The study takes the example of store location selection in 35 neighborhoods in region B by enterprise A and designs an immune optimization algorithm to solve the model. Based on the results of the algorithm, we verify the rationality and validity of the model, and obtain the optimal solution that ensures customer satisfaction and minimizes all costs.

The COVID-19 outbreak in early 2020 not only had a significant impact on China at the macro level, but also triggered changes in public psychology and irrational behavior at the individual level, one of the typical features of which was the panic buying behavior exhibited by residents during the outbreak. Based on Perceived Risk theory, emotion infection theory and information processing theory, this paper investigates the influence of herd mentality on panic buying behavior and the mediating role of Perceived Risk and information overload, and validates the model by collecting data from 326 residents through a questionnaire. The results show that herding mentality, Perceived Risk, and information overload all have positive effects on panic buying; Perceived Risk and information overload partially mediate the effect between herding mentality and panic buying, and information overload carries more mediating effects. These results suggest that higher levels of herding, Perceived Risk, and information overload can intensify individuals’ panic buying and cause further irrational buying behavior. In response to the findings, this paper also proposes countermeasures to deal with panic buying from three aspects: individuals, media, and government.

In recent years, the drone swarm has experienced remarkable growth, finding applications across diverse domains such as agricultural surveying, disaster rescue and logistics delivery. However, the rapid expansion of drone swarm usage underscores the necessity for innovative approaches in the field. Traditional algorithms face challenges in adapting to complex tasks, environmental modeling and computational complexity, highlighting the need for more advanced solutions like multi-agent deep reinforcement learning to enhance efficiency and robustness in drone swarm. Our proposed approach tackles this challenge by embracing temporal and spatial. In terms of the temporal, the proposed approach builds upon historical data, it enhances the predictive capabilities regarding future behaviors. In the spatial, the proposed approach leverage graph theory to model the swarm's features, while attention mechanisms strengthen the relationships between individual drones. The proposed approach addresses the unique characteristics of drone swarms by incorporating temporal dependencies, spatial structures and attention mechanisms. Extensive experiments validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Simple Summary: Model-based decision-making guides organism behavior by representing the relationships between states. Previous studies have shown that the mammalian hippocampus (Hp) plays a key role in model-based learning. However, the hippocampal neural mechanisms of birds for model-based learning are largely unknown. We trained pigeons to perform a two-step task. Using a combination of neural analysis and computational modeling, we show that the pigeons use model-based inferences to learn multi-step tasks, and multiple LFP frequency bands collaboratively contribute to model-based learning. Specifically, the high-frequency (12–100 Hz) oscillations represent model-based valuations, while the low-frequency (1–12 Hz) neural similarity is influenced by the relationship between temporal context states. These findings expand the understanding of the hippocampus' role in avian model-based learning. Model-based decision-making guides organism behavior by the representation of the relationships between different states. Previous studies have shown that the mammalian hippocampus (Hp) plays a key role in learning the structure of relationships among experiences. However, the hippocampal neural mechanisms of birds for model-based learning have rarely been reported. Here, we trained six pigeons to perform a two-step task and explore whether their Hp contributes to model-based learning. Behavioral performance and hippocampal multi-channel local field potentials (LFPs) were recorded during the task. We estimated the subjective values using a reinforcement learning model dynamically fitted to the pigeon's choice of behavior. The results show that the model-based learner can capture the behavioral choices of pigeons well throughout the learning process. Neural analysis indicated that high-frequency (12–100 Hz) power in Hp represented the temporal context states. Moreover, dynamic correlation and decoding results provided further support for the high-frequency dependence of model-based valuations. In addition, we observed a significant increase in hippocampal neural similarity at the low-frequency band (1–12 Hz) for common temporal context states after learning. Overall, our findings suggest that pigeons use model-based inferences to learn multi-step tasks, and multiple LFP frequency bands collaboratively contribute to model-based learning. Specifically, the high-frequency (12–100 Hz) oscillations represent model-based valuations, while the low-frequency (1–12 Hz) neural similarity is influenced by the relationship between temporal context states. These results contribute to our understanding of the neural mechanisms underlying model-based learning and broaden the scope of hippocampal contributions to avian behavior. [ABSTRACT FROM AUTHOR]

Simple Summary: The hippocampus (Hp) is involved in various aspects of spatial cognition during navigation, reflected in multiple neural oscillations across different frequencies. Given the structure homology between the avian and mammalian Hp, does it exhibit similar cross-frequency interaction mechanisms? Unlike rodents, birds can navigate by walking and flying. So, does the avian Hp share the same information interaction under different locomotor modes? In this study, we employed rock pigeons with exceptional spatial navigation abilities and conducted two goal-directed navigational experiments: a ground maze task with a circuitous paradigm and an outdoor homing flight task. These experiments were designed to explore the interactions between different frequency bands in the avian Hp during walking and flying navigation. The study revealed that phase–amplitude coupling (PAC) existed in the avian Hp during the navigational active phases. Meanwhile, the sub-frequency bands modulated by theta oscillations are different in different modes of locomotion. These findings support evidence for cross-frequency interactions in the avian Hp during spatial navigation and contribute to explaining the role of coupling, at least partially, in the ongoing cognitive demands during the navigation process. Navigation is a complex task in which the hippocampus (Hp), which plays an important role, may be involved in interactions between different frequency bands. However, little is known whether this cross-frequency interaction exists in the Hp of birds during navigation. Therefore, we examined the electrophysiological characteristics of hippocampal cross-frequency interactions of domestic pigeons (Columba livia domestica) during navigation. Two goal-directed navigation tasks with different locomotor modes were designed, and the local field potentials (LFPs) were recorded for analysis. We found that the amplitudes of high-frequency oscillations in Hp were dynamically modulated by the phase of co-occurring theta-band oscillations both during ground-based maze and outdoor flight navigation. The high-frequency amplitude sub-frequency bands modulated by the hippocampal theta phase were different at different tasks, and this process was independent of the navigation path and goal. These results suggest that phase–amplitude coupling (PAC) in the avian Hp may be more associated with the ongoing cognitive demands of navigational processes. Our findings contribute to the understanding of potential mechanisms of hippocampal PAC on multi-frequency informational interactions in avian navigation and provide valuable insights into cross-species evolution. [ABSTRACT FROM AUTHOR]

Diabetic cardiomyopathy (DCM) is a chronic microvascular complication of diabetes that is generally defined as ventricular dysfunction occurring in patients with diabetes and unrelated to known causes. Several mechanisms have been proposed to contribute to the occurrence and persistence of DCM, in which oxidative stress and autophagy play a non‐negligible role. Diabetic cardiomyopathy is involved in a variety of physiological and pathological processes. The 5′ adenosine monophosphate‐activated protein kinase/nuclear factor‐erythroid 2‐related factor 2 (AMPK/Nrf2) are expressed in the heart, and studies have shown that asiaticoside (ASI) and activated AMPK/Nrf2 have a protective effect on the myocardium. However, the roles of ASI and AMPK/Nrf2 in DCM are unknown. The intraperitoneal injection of streptozotocin (STZ) and high‐fat feed were used to establish the DCM models in 100 C57/BL mice. Asiaticoside and inhibitors of AMPK/Nrf2 were used for intervention. Cardiac function, oxidative stress, and autophagy were measured in mice. DCM mice displayed increased levels of oxidative stress while autophagy levels declined. In addition, AMPK/Nrf2 was activated in DCM mice with ASI intervention. Further, we discovered that AMPK/Nrf2 inhibition blocked the protective effect of ASI by compound C and treatment with ML‐385. The present study demonstrates that ASI exerts a protective effect against DCM via the potential activation of the AMPK/Nrf2 pathway. Asiaticoside is a potential therapeutic target for DCM. [ABSTRACT FROM AUTHOR]