Unleashing the power of chlorogenic acid: exploring its potential in nutrition delivery and the food industry.

In the contemporary era, heightened emphasis on health and safety has emerged as a paramount concern among individuals with food. The concepts of "natural" and "green" have progressively asserted dominance in the food consumption market. Consequently, through continuous exploration and development, an escalating array of natural bioactive ingredients is finding application in both nutrition delivery and the broader food industry. Chlorogenic acid (CGA), a polyphenolic compound widely distributed in various plants in nature, has garnered significant attention. Abundant research underscores CGA's robust biological activity, showcasing notable preventive and therapeutic efficacy across diverse diseases. This article commences with a comprehensive overview, summarizing the dietary sources and primary biological activities of CGA. These encompass antioxidant, anti-inflammatory, antibacterial, anti-cancer, and neuroprotective activities. Next, a comprehensive overview of the current research on nutrient delivery systems incorporating CGA is provided. This exploration encompasses nanoparticle, liposome, hydrogel, and emulsion delivery systems. Additionally, the article explores the latest applications of CGA in the food industry. Serving as a cutting-edge theoretical foundation, this paper contributes to the design and development of CGA in the realms of nutrition delivery and the food industry. Finally, the article presents informed speculations and considerations for the future development of CGA.

Sarcopenia is associated with hypomethylation of TWEAK and increased plasma levels of TWEAK and its downstream inflammatory factor TNF-α in older adults: A case-control study.

BACKGROUND: Sarcopenia is a harmful condition common among older adults for which no treatment is available. Tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) and its receptor fibroblast growth factor inducible 14 (FN14) are known to play important roles in the pathogenesis of sarcopenia. This study investigated alterations in methylation in TWEAK and Fn14 to identify potential targets for the managing sarcopenia. MATERIALS AND METHODS: Through an epidemiological investigation, we detected methylation of CpG islands (CpGs) in TWEAK and Fn14 in community-dwelling older adult of Xinjiang by bisulfite sequencing. Significant CpGs associated with sarcopenia were selected for detection in 152 older individuals by pyrosequencing. Associations between CpG methylation, plasma inflammatory marker levels, and sarcopenia were analyzed. RESULTS: Of 38 CpGs in TWEAK and 30 CpGs in Fn14 detected in 60 individuals, 6 CpGs showed lower methylation in sarcopenia patients compared with control individuals. In 152 older adults, covariance analysis with adjustment for age, gender, triglyceride level, obesity, diabetes, and hypertension showed that the methylation levels of 6 CpGs (CpG8, CpG12, CpG13, CpG20 and CpG21of TWEAK, and CpG24 of Fn14) were significantly lower in sarcopenia patients than in control individuals. With adjustment for additional confounding factors, covariate variance analysis showed that plasma TWEAK, TNF-α and IL-10 levels in the sarcopenia group were significant higher than those in the control group (P = 0.007, P < 0.001, P = 0.003). Multivariate logistic regression analysis showed that CpG8, CpG13, CpG21, and total methylation of TWEAK (OR = 0.767, 95 % CI = 0.622-0.947; OR = 0.740, 95 % CI = 0.583-0.941; OR = 0.734, 95 % CI = 0.561-0.958; OR = 0.883, 95 % CI = 0.795-0.980) as well as CpG22 and total methylation of Fn14 were significantly associated with sarcopenia (OR = 826, 95 % CI = 0.704-0.968; OR = 0.918, 95 % CI = 0.852-0.989). From partial correlation analysis, plasma TWEAK was correlated with plasma TNF-α (r = 0.172, P = 0.042). CONCLUSION: Sarcopenia is associated with hypomethylation of TWEAK and increased plasma levels of TWEAK and its downstream inflammatory factor TNF-α in a community-dwelling population of older adults in Xinjiang.

A novel method for prediction of dynamic smiling expressions after orthodontic treatment: a case report.

Smile esthetics has become increasingly important for orthodontic patients, thus prediction of post-treatment smile is necessary for a perfect treatment plan. In this study, with a combination of three-dimensional craniofacial data from the cone beam computed tomography and color-encoded structured light system, a novel method for smile prediction was proposed based on facial expression transfer, in which dynamic facial expression was interpreted as a matrix of facial depth changes. Data extracted from the pre-treatment smile expression record were applied to the post-treatment static model to realize expression transfer. Therefore smile esthetics of the patient after treatment could be evaluated in pre-treatment planning procedure. The positive and negative mean values of error for prediction accuracy were 0.9 and - 1.1 mm respectively, with the standard deviation of ± 1.5 mm, which is clinically acceptable. Further studies would be conducted to reduce the prediction error from both the static and dynamic sides as well as to explore automatically combined prediction from the two sides.