Model Features of a Cardiac lontophoretic Drug Delivery Implant

Pharmaceutical Research -     

优化枳椇子的提取工艺

目的　确定枳椇子干浸膏的最佳提取工艺?椒ā∫愿山嗟寐屎透山嘀凶芑仆课副?,对索式提取器提取的方法、渗滤法和浸渍法进行筛选。结果　渗滤法出膏率和干浸膏中黄酮含量最高,索式提取次之,浸渍法出膏率和干浸膏中黄酮含量最低。结论　渗滤法提取干浸膏简单易行,成本低廉,适合批量生产。     

Films of Carbon Nanomaterials for Transparent Conductors

The demand for transparent conductors is expected to grow rapidly as electronic devices, such as touch screens, displays, solid state lighting and photovoltaics become ubiquitous in our lives. Doped metal oxides, especially indium tin oxide, are the commonly used materials for transparent conductors. As there are some drawbacks to this class of materials, exploration of alternative materials has been conducted. There is an interest in films of carbon nanomaterials such as, carbon nanotubes and graphene as they exhibit outstanding properties. This article reviews the synthesis and assembly of these films and their post-treatment. These processes determine the film performance and understanding of this platform will be useful for future work to improve the film performance.     

Electrically and Thermally Conducting Nanocomposites for Electronic Applications

Nanocomposites made up of polymer matrices and carbon nanotubes are a class of advanced materials with great application potential in electronics packaging. Nanocomposites with carbon nanotubes as fillers have been designed with the aim of exploiting the high thermal, electrical and mechanical properties characteristic of carbon nanotubes. Heat dissipation in electronic devices requires interface materials with high thermal conductivity. Here, current developments and challenges in the application of nanotubes as fillers in polymer matrices are explored. The blending together of nanotubes and polymers result in what are known as nanocomposites. Among the most pressing current issues related to nanocomposite fabrication are (i) dispersion of carbon nanotubes in the polymer host, (ii) carbon nanotube-polymer interaction and the nature of the interface, and (iii) alignment of carbon nanotubes in a polymer matrix. These issues are believed to be directly related to the electrical and thermal performance of nanocomposites. The recent progress in the fabrication of nanocomposites with carbon nanotubes as fillers and their potential application in electronics packaging as thermal interface materials is also reported.     

Determining Adsorption Parameters of Potentially Contaminant-Releasing Materials Using Batch Tests with Differing Liquid-Solid Ratios

Adsorption parameters such as the distribution coefficient are required to predict the release behavior of contaminants using advection-dispersion models. However, for potentially contaminant-releasing materials (PCMs) such as dredged sludge and coal ash, these parameters cannot be obtained by conventional adsorption tests. This study developed a method to determine adsorption parameters for PCMs from a set of batch tests conducted in parallel as a function of the liquid-solid ratio (LS-parallel test). This LS-parallel test was performed on sandy soil derived from marine sediment using liquid-solid ratios from 1 to 300 L/kg. The water-contact time was also changed from 10 min to 28 d to elucidate the kinetics or equilibrium of contaminants released from the sample. Adsorption parameters were successfully obtained if the substance was under adsorption control. A column percolation test was performed to confirm the effectiveness of the obtained parameters. Good agreements were observed for SO₄²⁻ and B, but discrepancies remained for other substances such as F⁻ and As suggesting that improvements are necessary in both the LS-parallel test procedure and the advection-dispersion model.     

Indirect influence in social networks as an induced percolation phenomenon

Percolation theory has been widely used to study phase transitions in network systems. It has also successfully explained various macroscopic spreading phenomena across different fields. Yet, the theoretical frameworks have been focusing on direct interactions among nodes, while recent empirical observations have shown that indirect interactions are common in many network systems like social and ecological networks, among others. By investigating the detailed mechanism of both direct and indirect influence on scientific collaboration networks, here we show that indirect influence can play the dominant role in behavioral influence. To address the lack of theoretical understanding of such indirect influence on the macroscopic behavior of the system, we propose a percolation mechanism of indirect interactions called induced percolation. Surprisingly, our model exhibits a unique anisotropy property. Specifically, directed networks show first-order abrupt transitions as opposed to the second-order continuous transition in the same network structure but with undirected links. A mix of directed and undirected links leads to rich hybrid phase transitions. Furthermore, a unique feature of the nonmonotonic pattern is observed in network connectivities near the critical point. We also present an analytical framework to characterize the proposed induced percolation, paving the way to further understanding network dynamics with indirect interactions.

Percolation theory (1) is one of the most prominent frameworks within statistical physics. Initially developed (2, 3) to explain the chemical formation of large macromolecules, it has been recently used to study various dynamical processes in complex networks (4–9). Examples include the use of bond percolation (9, 10) to study the wide spread of rumors over online social media and outbreaks of infectious diseases on structured populations. Site percolation (4, 5, 11) has been employed to study the cascading failures of infrastructure networks (6, 12–16) and the resilience of protein–protein interaction networks (17). Likewise, bootstrap percolation (18), k-core (19–21), and linear threshold percolation (7, 22–24) have enabled the study of the spreading of behaviors over social networks. Finally, the so-called explosive percolation (25) has allowed a better characterization of systems’ structural transitions when they are growing or can adapt, whereas core percolation (26, 27) has contributed significantly to insights into nondeterministic polynomial problems. Common to all these percolation models is that they have successfully described various important dynamical phenomena by considering different direct interactions (8, 9, 28) among network nodes; in particular, they have captured the behavior of network systems as given by phase transitions (4, 8, 9, 28, 29).Our study is motivated by recent evidence that there are many systems in which indirect interactions play a major role in their spreading dynamics (30–35). Such underlying indirect interactions have important implications not only on the dynamics of the system but also on the evolution and the emergence of network structures. For example, Christakis and Fowler (30, 31) found that for the spreading of many social behaviors, such as drug (36) and alcohol addictions (37) and obesity (30), an individual can span their influence to their friends around three degrees of separation (friend of a friend’s friend). This phenomenon is also widely known as “three degrees of influence” in social science. In ecological networks, Guimarães et al. (32, 33) discovered in 2017 that indirect effects contribute strongly to the trait coevolution among reciprocal species, which can alter environmental selection and promote the evolution of species.Despite the ubiquity of indirect influence in various real-world systems, few studies have examined the exact mechanisms by which the indirect influences occur, or the relative strengths between direct and indirect influences. Here, based on empirical analyses of scientific collaboration networks, we reveal that indirect influence occurs through next-nearest neighbors and can be the dominant mechanism through which research interests change; on the contrary, evidence of direct (nearest) influence is relatively weak.However, on the theoretical front, up to now there has been no percolation-based theoretical model to describe the underlying mechanism of indirect influence or its distinctions with existing percolation models in terms of the macroscopic behaviors. For either regular networks or complex networks, various percolation models like bond, site, bootstrap, k-core, linear threshold and core, etc., are always based on direct interactions (8, 9, 28) among nodes. In essence, all of these models only take into account the existence and the strength of directly connected nodes, regardless of any indirect influences of other nodes. Hence, they are not suitable for describing the indirect mechanism. Here, we propose a percolation framework called induced percolation to theoretically study the impact of such an indirect mechanism on the whole system.Our results show that indirect interactions lead to a unique macroscopic behavior characterized by anisotropy and phase transitions and different spreading outcomes compared to the direct influence mechanisms. Specifically, we study the most general scenario in which links can have directions and report that varying the links’ directionality could change the order of the phase transition. This is in sharp contrast to previous percolation models, for which the nature of the phase transitions is not affected by the directionality of links. Such rich phase transition behavior is further illustrated in our simulations on empirical networks. To the best of our knowledge, the phenomenon of directionality-related order of the phase transitions only exists in some special cases of core percolation (27), whereas it is shown to be a generic feature in our indirect interaction model.     

Distinct large-scale turbulent-laminar states in transitional pipe flow

When fluid flows through a channel, pipe, or duct, there are two basic forms of motion: smooth laminar motion and complex turbulent motion. The discontinuous transition between these states is a fundamental problem that has been studied for more than 100 yr. What has received far less attention is the large-scale nature of the turbulent flows near transition once they are established. We have carried out extensive numerical computations in pipes of variable lengths up to 125 diameters to investigate the nature of transitional turbulence in pipe flow. We show the existence of three fundamentally different turbulent states separated by two distinct Reynolds numbers. Below Re ₁ ≃ 2,300, turbulence takes the form of familiar equilibrium (or longtime transient) puffs that are spatially localized and keep their size independent of pipe length. At Re ₁ the flow makes a striking transition to a spatio-temporally intermittent flow that fills the pipe. Irregular alternation of turbulent and laminar regions is inherent and does not result from random disturbances. The fraction of turbulence increases with Re until Re ₂ ≃ 2,600 where there is a continuous transition to a state of uniform turbulence along the pipe. We relate these observations to directed percolation and argue that Re ₁ marks the onset of infinite-lifetime turbulence.     

裂缝性气藏气井的分形渗流产能方程

在裂缝性气藏中, 常规模型难以准确描述裂缝发育的非均质性。如何更准确的评价单井的产能, 是现场开 发生产中面临的紧迫问题。在分形渗流研究基础上, 引入裂缝发育参数, 用于表征井控范围内裂缝的分布与连通情况, 建立了分形渗流稳态产能方程, 明确了裂缝对产能计算结果的影响, 并用塔里木油田克深区块实际井例进行了验证。相 对于常规模型, 分形渗流产能方程使预测产量与实测产量误差由20. 9%下降为3. 53%, 预测结果与现场实测更加吻合。     

生脉饮治疗慢性心衰大鼠不同提取工艺的比较

目的:比较不同提取工艺的生脉饮对慢性心衰大鼠的治疗效果。方法:雄性Wistar大鼠按1.5mg.kg-1体重剂量腹腔注射阿霉素,每周2次,共7周进行造模;正常组注射相同体积的生理盐水。将造模的Wistar大鼠随机分成四组:模型组、阳性药物组、渗漉药物组、水煎药物组。连续灌胃给药4周,观察不同提取工艺制成的生脉饮对大鼠行为体征、血流动力学指标以及做心脏病理切片观察其组织学变化;检测血清中丙二醛(malondialdehyde,MDA)、乳酸脱氢酶(lactate dehydrogenase,LDH)、肌酸激酶(creatine kinase,CK)、脑钠肽(brain natriuretic peptide,BNP)、超氧化物歧化酶(superoxide dismutase,SOD)的含量。结果:与渗漉药物组相比,水煎药物组大鼠精神萎靡不振,活动量、进食量减少。水煎药物组大鼠心肌组织受损程度比渗漉药物组大。两种提取物均能降低慢性心衰大鼠血清中MDA,LDH,CK活性,升高SOD水平;渗漉提取物能极显著地降低慢性心衰大鼠血清BNP水平,水煎液则不能。渗漉药物组和水煎药物组大鼠收缩压(systolic pres-sure,SP)、舒张压(diastolic pressure,DP)、动脉血压(arterial pressure,AP)、左心室压力最大下降速率(-dp/dt-max)较模型组极显著上升。结论:治疗慢性心衰大鼠,渗漉提取工艺的效果比水煎工艺好。     

The Impact of Dose and Solubility of Additives on the Release from HPMC Matrix Tablets—Identifying Critical Conditions

Purpose  The dissolution of HPMC matrix tablets containing different amounts of highly soluble (mannitol) or poorly soluble (dicalcium phosphate, DCP) was studied to deduce the parameters critical to release robustness. Methods  The release of HPMC and additives was studied using a modified USP II method at two paddle stirring rates, 50 and 125 rpm, at HPMC content varying from 15% to 100%. Results  At HPMC contents between 30% and 35% a critical point was identified and found crucial to the release from the HPMC/mannitol tablets. Below this point the matrix rapidly disintegrated in a non robust manner. At higher HPMC contents the mannitol release became increasingly diffusion controlled with maintained matrix integrity. The release robustness was lower for HPMC/DCP than HPMC/mannitol tablets at high HPMC contents, however, lacking critical points. The critical point was interpreted as the percolation threshold for HPMC and differences explained in terms of water transport into the matrix. Conclusion  The release robustness was lower for formulations with additives of low solubility having an erosion controlled release than for additives with higher solubility and a diffusion controlled release. However, for additives creating a steep osmotic pressure gradient, an HPMC content above the percolation threshold becomes vital for maintaining the release robustness.