Ultraviolet B (UVB) irradiation causes adverse effects on the skin. Corn silk contains flavonoids and other bioactive compounds and antioxidants, which may prevent skin photoaging through antioxidant and anti-inflammatory effects. We aimed to investigate the potential photoprotective effects of dietary corn silk on UVB-induced skin damage in mice and the mechanisms behind these effects on human skin cells. Oral administration of corn silk water extract (CS) (2 or 4 g/kg/day) for 19 weeks decreased epidermal thickness, wrinkle formation, and positive staining for PCNA, Ki67, and 8-OHdG, and increased collagen staining in UVB-irradiated SKH-1 hairless mice compared with controls. The pro-inflammatory NF-κB target genes (IL-1β, iNOS, and COX-2) and MMP-9 expressions were lower in the CS groups, and TGF-β/Smad signaling increased. Low skin lipid peroxidation and blood DNA oxidation levels and high blood glutathione were detected. Antioxidant transcription factor Nrf2-related catalase and SOD1 proteins and glutaredoxin mRNA levels increased. The results of CS extract treatment and UVB irradiation in HaCaT cells showed the same results in Nrf2 and NF-κB target genes. An LC-MS/MS analysis showed that the CS extract contained potential antioxidants, which might have contributed to its anti-photoaging effects in tissues and cells. CS extract may reduce UVB-induced skin damage through antioxidant and anti-inflammatory mechanisms.

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With the ever growing amount of digital information and multimedia on the World Wide Web and the current trend towards personalizing technology, users find themselves wanting a more intuitive way of finding related information, and not just any information but relevant information that is personal to them. One way to personalize and filter the information is by extracting the mood affectation, allowing the user to search based on current mood. The artificial intelligence field has done extensive research and continues to discover and improve current mood extraction techniques for each distinct medium. This paper will explore how to link and integrate the mood extraction of several distinct mediumsaudio, image, and text-by utilizing a common emotion model that is customizable to the user. This project will allow the user to provide an input medium and find a matching output of a different medium based on default settings or user customization.