Evaluation of iron transport from ferrous glycinate liposomes using Caco-2 cell model

Background: Iron fortification of foods is currently a strategy employed to fight iron deficiency in countries. Liposomes were assumed to be a potential carrier of iron supplements.Objective: The objective of this study was to investigate the iron transport from ferrous glycinate liposomes, and to estimate the effects of liposomal carriers, phytic acid, zinc and particle size on iron transport using Caco-2 cell models.Methods: Caco-2 cells were cultured and seeded in DMEM medium. Minimum essential medium was added to the basolateral side. Iron liposome suspensions were added to the apical side of the transwell.Results: The iron transport from ferrous glycinate liposomes was significantly higher than that from ferrous glycinate. In the presence of phytic acid or zinc ion, iron transport from ferrous glycinate liposomes and ferrous glycinate was evidently inhibited, and iron transport decreased with increasing phytic acid concentration. Iron transport was decreased with increase of particle size increasing of ferrous glycinate liposome.Conclusion: Liposomes could behave as more than a simple carrier, and iron transport from liposomes could be implemented via a mechanism different from the regulated non-heme iron pathway.Keywords: Ferrous glycinate liposomes, iron transport, phytic acid, particle siz

Essays on decision making under variable information

This thesis is composed of three chapters that invoke axiomatic approaches to study models of decision making under objective and variable information. In Chapter 1, we propose a model of choice from choice architectures that refer to environments where alternatives are presented with objective and observable choice-relevant information. We identify choice architectures by directed graphs on sets of alternatives where directed edges represent choice-relevant information about the alternatives. In this domain, a choice function hence singles out a vertex from each given directed graph, whereas a choice correspondence assigns to every directed graph a set of vertices. A choice function and choice correspondence are respectively characterised by a choice procedure that separates the role of information processing from that of preferences. Notably, both choice procedures suggest the same machinery of information processing that is hinged on properties of directed graphs, hence being objective and predictable. We then explore its implications on the formation mechanism of consideration sets and the sources of the stochasticity of choice. Later in the chapter, we also study the applications in terms of demand shaping and revealing equilibrium, respectively. Chapter 2 considers decision making under uncertainty with objective and variable information structures. We take as primitive a family of information-dependent preferences over subjective acts indexed by partitions of the state space. Each partition corresponds to an information structure. We characterise a utility representation that comprises an affine utility index over simple lotteries, a unique capacity over the state space, and for each partition, a probability measure on the $\sigma$-algebra generated by the partition. We find that such a representation is equivalent to the Choquet expected utility representation with specific machinery of non-additive belief formation. We then connect the utility representation to the definition of comparative uncertainty aversion to explore the characteristic conditions related to the translatability of uncertainty attitude among variable information structures. In Chapter 3, we explicitly incorporate framing of information into decision making under uncertainty. As in Chapter 2, we also study a family of partition-indexed preferences over subjective acts, where we interpret each partition as a frame of information. Under a modest set of axioms, we characterise a general utility representation, which we call frame-adaptive expected utility. Having the general utility representation, we focus on two parameterised forms of frame-adaptive expected utility featuring attitude towards informativeness and degree of salience, respectively. We then apply the frame-adaptive models to the definition of comparative uncertainty aversion and that of definitive uncertainty-aversion to study the translatability of uncertainty attitude among variable frames of information. We also conduct a comparative analysis and find that the decision maker's reaction to information frames plays a role in modifying the degree of uncertainty attitude revealed from choices. Later in the chapter, we relate frame-adaptivity to ambiguity-aversion and argue that the latter can be viewed as a manifestation of the decision-maker performing frame-adaptive reasoning

On the shock wave boundary layer interaction in slightly-rarefied gas

The shock wave and boundary layer interaction (SWBLI) plays an important role in the design of hypersonic vehicles. However, discrepancies between the numerical results of high-temperature gas dynamics and experiment data have not been fully addressed. It is believed that the rarefaction effects are important in SWBLI, but the systematic analysis of the temperature-jump boundary conditions and the role of translational/rotational/vibrational heat conductivities are lacking. In this paper, we derive the three-temperature Navier-Stokes-Fourier (NSF) equations from the gas kinetic theory, with special attention paid to the components of heat conductivity. With proper temperature-jump boundary conditions, we simulate the SWBLI in the double cone experiment. Our numerical results show that, when the three heat conductivities are properly recovered, the NSF equations can capture the position and peak value of the surface heat flux, in both low- and high-enthalpy inflow conditions. Moreover, the separation bubble induced by the separated shock and the reattachment point induced by impact between transmitted shock and boundary layer are found to agree with the experimental measurement

Fish oil alleviated high-fat diet–induced non-alcoholic fatty liver disease via regulating hepatic lipids metabolism and metaflammation: a transcriptomic study

Table S1. The nutrient composition, energy ratio and fatty acid profiles of experimental diets. Table S2. Primers used in this study. Figure S3. The weekly body weight change of experiment animals. Table S4. Differentially expressed genes between WD group and CON group. Table S5. Differentially expressed genes between FOH group and WD group. Table S6. Upregulated DEGs (FOH vs. WD) implicated in the enrichedgene ontology processes. Table S7. Downregulated DEGs (FOH vs. WD) implicated in the enrichedgene ontology processes. (ZIP 236 kb

PointVotes: A Deep Learing Point Cloud Model for Tire Bubble Defect Detection

In order to eliminate the hidden dangers caused by tire bubble defects, considering that the two-dimensional technology is sensitive to light, the 3D point cloud technology is used to obtain the tire surface morphology. This paper proposes a 3D point cloud network model named PointVotes, a point based target detection method. The designed structural framework includes: the fusion sampling layer, the voting layer and the proposal refinement layer. By observing the spatial characteristics of the detected target, a new point sampling method named C-farthest point sampling (C-FPS) is proposed. Combining with the fusion sampling strategy, the FPS and the C-FPS are sampled in a certain proportion. It solves the problem that the proposal box cannot be generated due to less available prospect information when generating suggestions for small targets. The network model uses Set Abstraction layers in multiple PointNet++ to extract features, arranges and combines features of different scales, forms high-dimensional features of points and votes, judges whether there are bubble defects through classification, and then generates proposals and regression to the prediction frame. Experiment results show that the mean average precision of the model can reach 82.8 % with a detection time of 0.12 s

Improved Duncan-Chang model for reconstituted hydrate-bearing clayey silt from the South China Sea

The experimental testing and analysis of strength and deformation characteristics of hydrate reservoirs is an integral part of natural gas hydrate exploitation. However, studies so far have failed to deeply explore samples from the South China Sea. Especially, there is a lack of a simple and applicable method to estimate their mechanical behaviors. Thus, based on test data, an improved Duncan-Chang model is established in this paper to characterize the strength and deformation of reconstituted samples with various hydrate saturation and stress states from this area. This model can accurately describe the strain-hardening characteristics, and failure strength is estimated by the improved Drucker-Prager criterion with high fitting accuracy. The initial elastic modulus and failure ratio are given by the proposed empirical models, which are obtained from experimental data and fitting methods. Generally, this model has several advantages including simple structure, favorable performances, and a limited number of model parameters. Therefore, it could be widely used in strength and deformation analysis. This study can support the prevention and control of geological risks during natural gas hydrate exploitation in the South China Sea.Cited as: Dong, L., Wu, N., Zhang, Y., Liao, H., Hu, G. Li, Y. Improved Duncan-Chang model for reconstituted hydrate-bearing clayey silt from the South China Sea. Advances in Geo-Energy Research, 2023, 8(2): 136-140. https://doi.org/10.46690/ager.2023.05.0