Protective Effect of Red Light-Emitting Diode against UV-B Radiation-Induced Skin Damage in SKH:HR-2 Hairless Mice.

In this in vivo study on hairless mice, we examined the effects of light-emitting diode (LED) treatment applied prior to ultraviolet B (UVB) irradiation. We found that pre-treating with LED improved skin morphological and histopathological conditions compared to those only exposed to UVB irradiation. In our study, histological evaluation of collagen and elastic fibers after LED treatment prior to UVB irradiation showed that this pretreatment significantly enhanced the quality of fibers, which were otherwise poor in density and irregularly arranged due to UV exposure alone. This suggests that LED treatment promotes collagen and elastin production, leading to improved skin properties. Additionally, we observed an increase in Claudin-1 expression and a reduction in nuclear factor-erythroid 2-related factor 2 (Nrf-2) and heme-oxygenase 1 (HO-1) expression within the LED-treated skin tissues, suggesting that LED therapy may modulate key skin barrier proteins and oxidative stress markers. These results demonstrate that pretreatment with LED light can enhance the skin's resistance to UVB-induced damage by modulating gene regulation associated with skin protection. Further investigations are needed to explore the broader biological effects of LED therapy on other tissues such as blood vessels. This study underscores the potential of LED therapy as a non-invasive approach to enhance skin repair and counteract the effects of photoaging caused by UV exposure.

Investigating the Nutritional and Functional Properties of Protaetia brevitarsis Larvae and Isolated Soy Protein Mixtures as Alternative Protein Sources.

The growing demand for sustainable and alternative protein sources has spurred interest in insect-based and plant-based proteins. Protaetia brevitarsis (PB) larvae and isolated soy protein (ISP) are notable in this regard, offering potential health benefits and nutritional enhancements. We assessed the feasibility of PB larvae and ISP mixtures as alternative food ingredients. Methods included the optimized purification and freeze-drying of PB larvae, extraction and refinement of legume proteins, physicochemical and antioxidant capacity evaluations, DPPH radical scavenging activity measurement, total phenolic and flavonoids content quantification, general component analysis, amino acid profiling using HPLC, fatty acid profiling through gas chromatography, and mineral content analysis using inductively coupled plasma spectrometry. The study found that certain PB:ISP ratios, particularly a 7:3 ratio, significantly improved the blend's antioxidant capacity, as evidenced by DPPH scavenging activity. This ratio also impacted the nutritional profile by altering the mixture's general components, with a notable increase in moisture, crude protein, and fiber and a decrease in crude fat and ash. Amino acid analysis revealed a balanced presence of essential and non-essential amino acids. The fatty acid profile was rich in unsaturated fatty acids, especially in certain ratios. Mineral analysis showed a complex interplay between PB larvae and ISP, with some minerals decreasing and others increasing in the blend. PB larvae and ISP mixtures have significant potential as alternative protein sources, offering a diversified nutritional profile and enhanced antioxidant properties. The 7:3 ratio of PB larvae to ISP has been shown to be particularly effective, suggesting that this ratio may offer an optimal balance for enhancing the overall nutritional quality of the mixture. This study sets the stage for future research to further explore and optimize the potential of these mixtures for human consumption while considering the challenges of consumer acceptance and long-term safety.

A powerful statistical method for identifying differentially methylated markers in complex diseases.

DNA methylation is an important epigenetic modification that regulates transcriptional expression and plays an important role in complex diseases, such as cancer. Genome-wide methylation patterns have unique features and hence require the development of new analytic approaches. One important feature is that methylation levels in disease tissues often differ from those in normal tissues with respect to both average and variability. In this paper, we propose a new score test to identify methylation markers of disease. This approach simultaneously utilizes information from the first and second moments of methylation distribution to improve statistical efficiency. Because the proposed score test is derived from a generalized regression model, it can be used for analyzing both categorical and continuous disease phenotypes, and for adjusting for covariates. We evaluate the performance of the proposed method and compare it to other tests including the most commonlyused t-test through simulations. The simulation results show that the validity of the proposed method is robust to departures from the normal assumption of methylation levels and can be substantially more powerful than the t-test in the presence of heterogeneity of methylation variability between disease and normal tissues. We demonstrate our approach by analyzing the methylation dataset of an ovarian cancer study and identify novel methylation loci not identified by the t-test.