Fabrication of multifunctional facial masks from phenolic acid grafted chitosan/collagen peptides via aqueous electrospinning.

Facial masks have become ubiquitous in our daily life to endow skin enough moisture and activated nutrition through mask nonwovens infused with skincare ingredients. However, the active nutrients in wet masks are prone to deterioration and deactivation. Herein, a novel multifunctional nanofiber dry mask was successfully prepared using aqueous-electrospun phenolic acid grafted chitosan/collagen peptides. When used, the functional nanofibers in the mask dissolve through spraying moisture, activating active ingredients in response to water and providing in-situ free radical scavenging, moisturizing and antibacterial effects to the skin. In this work, a series of gallic acid (GA), caffeic acid (CA), and protocatechuic acid (PA) have been studied to be grafted with chitosan to improve water solubility of chitosan (CS). Also, through aqueous electrospinning of phenolic acid-grafted chitosan/collagen peptides, a one-step green multifunctional nanofiber mask was obtained. The results showed that the mask had a 12.14 % moisturizing rate and a 94.09 % activity for removing free radicals from the skin after encountering moisture. Considering its high efficiency, controllable function release, and easy processability, the nanofiber multifunctional mask may provide a competitive alternative to facial masks and promote potential value-added applications of bio-based macro-molecules.

Respiratory immune status and microbiome in recovered COVID-19 patients revealed by metatranscriptomic analyses.

Coronavirus disease 2019 (COVID-19) is currently a severe threat to global public health, and the immune response to COVID-19 infection has been widely investigated. However, the immune status and microecological changes in the respiratory systems of patients with COVID-19 after recovery have rarely been considered. We selected 72 patients with severe COVID-19 infection, 57 recovered from COVID-19 infection, and 65 with non-COVID-19 pneumonia, for metatranscriptomic sequencing and bioinformatics analysis. Accordingly, the differentially expressed genes between the infected and other groups were enriched in the chemokine signaling pathway, NOD-like receptor signaling pathway, phagosome, TNF signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, and C-type lectin receptor signaling pathway. We speculate that IL17RD, CD74, and TNFSF15 may serve as disease biomarkers in COVID-19. Additionally, principal coordinate analysis revealed significant differences between groups. In particular, frequent co-infections with the genera Streptococcus, Veillonella, Gemella, and Neisseria, among others, were found in COVID-19 patients. Moreover, the random forest prediction model with differential genes showed a mean area under the curve (AUC) of 0.77, and KCNK12, IL17RD, LOC100507412, PTPRT, MYO15A, MPDZ, FLRT2, SPEG, SERPINB3, and KNDC1 were identified as the most important genes distinguishing the infected group from the recovered group. Agrobacterium tumefaciens, Klebsiella michiganensis, Acinetobacter pittii, Bacillus sp. FJAT.14266, Brevundimonas naejangsanensis, Pseudopropionibacterium propionicum, Priestia megaterium, Dialister pneumosintes, Veillonella rodentium, and Pseudomonas protegens were selected as candidate microbial markers for monitoring the recovery of COVID patients. These results will facilitate the diagnosis, treatment, and prognosis of COVID patients recovering from severe illness.