Fabrication of multifunctional materials based on chitosan/gelatin incorporating curcumin-clove oil emulsion for meat freshness monitoring and shelf-life extension.

A new multifunctional film with active and intelligent effects was developed by incorporating curcumin-clove oil emulsion into natural materials. The basic properties, functional characteristics, and pH/NH3-sensitivity of films were investigated, and then these films were applied to extend shelf-life and monitor freshness of meat. Curcumin solution and emulsion illustrated significant color variations at different pH values. The incorporation of emulsion improved the UV-vis barrier and water resistance properties of films, which blocked most of UV-light and its water contact angle reached 100.03°. Meanwhile, the films had stronger mechanical strength and higher thermal stability, with elongation at break reaching 79.18 % and the maximum degradation temperature rising to 316 °C. Moreover, emulsion made films have a slow-release effect on clove oil, which not only enhanced the antioxidant property but also significantly improved their antibacterial activity. Additionally, the multifunctional films presented a significant color response to acidic/alkaline environments over a short time interval and could be easily identified by naked eyes. Finally, the films effectively extended the shelf-life of fresh meat by 3 days at 4 °C and visually monitored freshness through color changes in real-time. This knowledge provides insights and ideas for the development of novel food packaging with both active and intelligent functions.

Screening of genes related to breast cancer prognosis based on the DO-UniBIC method.

BACKGROUND: Early screening is the most effective way to control breast cancer. Due to the lack of accurate biomarkers, early diagnosis of breast cancer is still very difficult. Therefore, it is necessary to discover new candidate genes of breast cancer and improve the early diagnosis and prognosis. METHODS: A DO-UniBIC gene screening method was proposed. First, Disease Ontology (DO) analysis was used to screen out breast cancer related genes from differentially expressed genes, and then the UniBIC algorithm was used to find all gene clusters with the same changing trend based on the longest common subsequence. In addition, an eight-gene prognostic model was constructed to assess the prognostic risk of breast cancer patients. RESULTS: The prognostic analysis of the candidate genomes based on multivariate Cox proportional regression model revealed eight genes that were significantly related to prognosis. The eight genes were ACSL1, CD24, EMP1, JPH3, CAMK4, JUN, S100B and TP53AIP1. Among them, ACSL1 was a new potential breast cancer related gene screened by the DO-UniBIC method. CONCLUSIONS: More comprehensive cancer-related genes can be screened based on the DO-UniBIC method, which can be used as the candidate gene set for prognostic analysis.