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Nasolabial fold and fat infiltration (A) Upper cheek area. The nasolabial fold is indicated by a dotted line. Nasolabial fold severity was evaluated according to our photograph‐based grading criteria. (B) Fat infiltration into the dermal layer, observed by ultrasonography. The minimum depth of the fat from the skin surface was measured as the indicator of the degree of fat infiltration (fat infiltration index).
Source publication
Background
Facial morphology changes with aging, producing an aged appearance, but the mechanisms involved are not fully established. We recently showed that subcutaneous fat infiltrates into the dermal layer with aging, but it is not yet clear whether and how this drastic change of the dermal layer influences facial appearance.
Purpose
We aimed t...
Citations
... 6 This fat infiltration impairs the dermal layer, which is a critical contributor to the skin's physical properties due to its abundant extracellular matrix, consisting of collagen and elastic fibers. 7 We also clarified that this fat infiltration decreases the skin's elasticity 8 and induces sagging, ptosis of the face, which is one of the critical features of an aged face. However, the relationship between fat infiltration and wrinkle formation, another feature of aged appearance, has not been established. ...
... Since the properties of facial skin differ depending on the area, we first investigated whether fat infiltration occurs in the forehead area similarly to the cheek area, where we previously observed fat infiltration. 8 Although the thickness of subcutaneous fat at the forehead is drastically less than in the cheek area, ultrasonography confirmed the presence of infiltrated fat in middle-aged female forehead skin. Furthermore, the infiltrated fat was connected to the subcutaneous adipose layer and had the same intensity in ultrasonography as the subcutaneous adipose layer (Figure 1). ...
... 11 Indeed, we have shown that fat infiltration is related to a loss of dermal elasticity. 8 Further, fat infiltration occurs in a concave pattern that may directly cause impairment of the dermal physical properties, rather than simply expanding uniformly into the dermal layer. However, it remains possible that factors such as age-dependent changes in skin structure and elasticity may be a prerequisite for fat infiltration, and further study will be needed to clarify the mechanism of fat infiltration in detail. ...
Background
Wrinkles appear with aging, producing an aged impression, but the mechanism of wrinkle formation has not yet been fully elucidated. We recently reported that subcutaneous fat infiltrates into the dermal layer with aging and impairs skin elasticity, but the contribution of this process to wrinkle formation is still unclear.
Purpose
We aimed to clarify the contribution of dermal fat infiltration to wrinkle formation by analyzing the relationship between them in the forehead of female volunteers.
Methods
We measured the severity of fat infiltration in the forehead of 29 middle‐aged female volunteers by means of ultrasonography. Fixed wrinkles present when the eyes were closed and wrinkles transiently formed when the eyes were open were evaluated using a photograph‐based 6‐grade evaluation system for each type of wrinkle.
Results
Fat infiltration at the forehead area was observed similarly to that in the cheek area as we reported previously. We found that opening the eyes induced the formation of stable transient wrinkles, the grade of which was significantly related to fat infiltration severity. Furthermore, fat infiltration was also significantly related to the severity of fixed wrinkles. Moreover, the severity of transient wrinkles was significantly related to that of fixed wrinkles.
Conclusions
Our results suggest that fat infiltration into the dermal layer enhances transient wrinkle formation during facial expression by impairing the ability of the skin to resist deformation, thereby promoting fixed wrinkle formation. Therefore, fat infiltration is a critical cause of wrinkle formation.
Microneedles (MNs) have emerged as a promising solution for drug delivery and extraction of body fluids. Pain is an important physiological attribute to be examined when designing MNs. There is no known representation of pain with geometric features of a MN despite the focus on experimental work. This study focuses on optimizing MN designs with the aim of minimizing pain through means of machine learning, finite element analysis, and optimization tools. Three distinct approaches are proposed. The first approach involves training multiple regression models on data obtained through finite element analysis in COMSOL. The second approach uses COMSOL's built‐in nonlinear optimization solver. Finally, the third approach utilizes the LiveLink interface between COMSOL and MATLAB, combined with Bayesian optimization. Each approach presents unique strengths and challenges, with the third approach demonstrating significant promise due to its efficiency, practicality, and time‐saving.
