赞坦稳定可可黄乳液:α-曼戈斯的特征,分子相互作用,物理化学稳定性和生物可访问性
Naymul Karim1, Ke Zhang1, Mohammad Rezaul Islam Shishir1
1School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
Food chemistry
|January 30, 2026
概括
稳定了可可黄乳液与香丹 (XG) 有效封装α-曼戈斯 (αM),提高其稳定性和控制其释放. 这种配方对在胃肠道中输送疏水生物活性物有前途.
科学领域:
- 食品科学与技术 食品科学与技术
- 制药科学 制药科学
- 材料科学 材料科学 材料科学
背景情况:
- 阿尔法-曼戈斯 (αM) 是一种难以溶解的香,具有潜在的健康益处.
- 提高像αM这样的疏水生物活性物质的稳定性和受控的输送对于它们的治疗应用至关重要.
- 传统配方往往与这种化合物的可溶性和稳定性不佳作斗争.
研究的目的:
- 开发和特征可可黄乳液稳定由香甘 (XG) 用于封装αM.
- 评估XG度对乳液性质,稳定性和αM递送的影响.
- 为了评估这些乳液在模拟胃肠道消化过程中的性能.
主要方法:
- 在不同XG度 (0-0.5%) 的可可黄乳液中封装αM.
- 乳液性质的表征:滴滴大小,多分散度指数,泽塔电位和粘度.
- 评估21天内的物理,化学和微生物稳定性.
- 使用FTIR和XRD进行结构分析.
- 微镜技术 (CLSM,FESEM) 用于滴滴形态学.
- 模拟胃肠道消化研究,以评估生物可访问性和抗氧化剂保留.
主要成果:
- 实现了高封装效率 (77-85%) 和亚微米滴滴大小 (440-540 nm).
- 增加XG度提高了粘度,剪切稀释行为和热/离心稳定性.
- 乳液在21天内表现出极好的稳定性,没有降解.
- 结构分析证实了半晶体矩阵内的αM封装成功.
- 模拟消化显示了XG依赖的控制滴滴行为,αM生物可访问性和抗氧化剂保留.
结论:
- 克桑稳定可可黄乳液是有效提高αM的稳定性.
- 这些乳液提供了受控释放和改善了疏水生物活性的生物可访问性.
- 该配方为胃肠道中疏水化合物提供了一个有前途的输送系统.
相关概念视频
Nuclear Stability
23.2K
Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
To hold positively charged protons together...
To hold positively charged protons together...
23.2K
RNA Stability
35.7K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.7K
Stability
418
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
418
Stability of structures
523
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
523
Pole and System Stability
965
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
965
Multimachine Stability
579
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
579


