Exploring the compatibility between hydrothermal depolymerization of alkaline lignin from sugarcane bagasse and metabolization of the aromatics by bacteria.

Although hydrothermal treatments for biomass fractionation have been vastly studied, their effect on the depolymerization of isolated lignins in terms of yield, composition, and compatibility of the produced lignin bio-oils with bioconversion is still poorly investigated. In this study, we evaluated the hydrothermal depolymerization of an ß-O-4'-rich lignin extracted from sugarcane bagasse by alkaline fractionation, investigating the influence of temperature (200-350 °C), time (30-90 min), and solid-liquid ratio (1:10-1:50 m.v-1) on yield of bio-oils (up to 31 wt%) rich in monomers (light bio-oils). Principal Components Analysis showed that the defunctionalization of the aromatic monomers was more pronounced in the most severe reaction conditions and that the abundance of more hydrophobic monomers increased in more diluted reactions. While the high-molecular-weight (heavy) bio-oil generated at 350 °C, 90 min, and 1:50 m.v-1 failed to support bacterial growth, the corresponding light bio-oil rich in aromatic monomers promoted the growth of bacteria from 9 distinct species. The isolates Pseudomonas sp. LIM05 and Burkholderia sp. LIM09 showed the best growth performance and tolerance to lignin-derived aromatics, being the most promising for the future development of biological upgrading strategies tailored for this lignin stream.

Insights into immune responses in oral cancer through proteomic analysis of saliva and salivary extracellular vesicles.

The development and progression of oral cavity squamous cell carcinoma (OSCC) involves complex cellular mechanisms that contribute to the low five-year survival rate of approximately 20% among diagnosed patients. However, the biological processes essential to tumor progression are not completely understood. Therefore, detecting alterations in the salivary proteome may assist in elucidating the cellular mechanisms modulated in OSCC and improve the clinical prognosis of the disease. The proteome of whole saliva and salivary extracellular vesicles (EVs) from patients with OSCC and healthy individuals were analyzed by LC-MS/MS and label-free protein quantification. Proteome data analysis was performed using statistical, machine learning and feature selection methods with additional functional annotation. Biological processes related to immune responses, peptidase inhibitor activity, iron coordination and protease binding were overrepresented in the group of differentially expressed proteins. Proteins related to the inflammatory system, transport of metals and cellular growth and proliferation were identified in the proteome of salivary EVs. The proteomics data were robust and could classify OSCC with 90% accuracy. The saliva proteome analysis revealed that immune processes are related to the presence of OSCC and indicate that proteomics data can contribute to determining OSCC prognosis.