OBJECTIVES: To develop a novel in vitro skin glycation model as a screening tool for topical formulations with antiglycation properties and to further characterize, at the molecular level, the glycation stress-driven skin ageing mechanism.
METHODS: The glycation model was developed using human reconstituted full-thickness skin; the presence of N(ε) -(carboxymethyl) lysine (CML) was used as evidence of the degree of glycation. Topical application of emulsion containing a well-known antiglycation compound (aminoguanidine) was used to verify the sensitivity and robustness of the model. Cytokine immunoassay, quantitative real-time polymerase chain reaction and histological analysis were further implemented to characterize the molecular mechanisms of skin ageing in the skin glycation model.
RESULTS: Transcriptomic and cytokine profiling analyses in the skin glycation model demonstrated multiple biological changes, including extracellular matrix catabolism, skin barrier function impairment, oxidative stress and subsequently the inflammatory response. Darkness and yellowness of skin tone observed in the in vitro skin glycation model correlated well with the degree of glycation stress.
CONCLUSIONS: The newly developed skin glycation model in this study has provided a new technological dimension in screening antiglycation properties of topical pharmaceutical or cosmeceutical formulations. This study concomitantly provides insights into skin ageing mechanisms driven by glycation stress, which could be useful in formulating skin antiageing therapy in future studies.
METHODS: KP metabolites and cytokines in plasma samples of patients with dengue infection (dengue without warning signs [DWS-], dengue with warning signs [DWS+], or severe dengue) were analyzed. Cytokines (interferon gamma [IFN-ɣ], tumor necrosis factor, interleukin 6, CXCL10/interferon-inducile protein 10 [IP-10], interleukin 18 [IL-18], CCL2/monocyte chemoattractant protein-1 [MCP-1], and CCL4/macrophage inflammatory protein-1beta [MIP-1β] were assessed by a Human Luminex Screening Assay, while KP metabolites (tryptophan, kynurenine, anthranilic acid [AA], picolinic acid, and quinolinic acid) were assessed by ultra-high-performance liquid chromatography and Gas Chromatography Mass Spectrophotometry [GCMS] assays.
RESULTS: Patients with DWS+ had increased activation of the KP where kynurenine-tryptophan ratio, anthranilic acid, and picolinic acid were elevated. These patients also had higher levels of the cytokines IFN-ɣ, CXCL10, CCL4, and IL-18 than those with DWS-. Further receiver operating characteristic analysis identified 3 prognostic biomarker candidates, CXCL10, CCL2, and AA, which predicted patients with higher risks of developing DWS+ with an accuracy of 97%.
CONCLUSIONS: The data suggest a unique biochemical signature in patients with DWS+. CXCL10 and CCL2 together with AA are potential prognostic biomarkers that discern patients with higher risk of developing DWS+ at earlier stages of infection.
OBJECTIVE: This study aimed to evaluate the content, features, and quality of commercial dialysis diet apps for adult dialysis patients.
METHODS: This study consisted of a quantitative content analysis of commercial dialysis diet apps downloaded from Google Play and the Apple App Store available in the Asian marketplace, searched for using the following keywords in English: dialysis diet and diet for kidney disease. Free and paid apps available in English that provide nutrition information for adult dialysis patients were included. Apps that were not relevant to the dialysis diet, not meant for patient self-management, or redundant were excluded. Apps were evaluated for language medium (subscore=1), credibility (subscore=1), food database (subscore=1), valuable features (subscore=12), health-behavior theory constructs (subscore=60), and technical quality (subscore=25). The relationships among the variables of interest were determined by Pearson correlation. Stepwise multiple linear regression analysis was performed to identify the features that contribute to greater technical quality of dialysis diet apps. Statistical significance was defined as P