This study aims the third generation biobutanol production in P2 medium supplemented D. salina biomass mixotrophically cultivated with marble waste (MW). The wastes derived from the marble industry contain approximately 90% of carbon-rich compounds. Microalgal growth in mixotrophic conditions was optimized in the 0.4-2 g/L of MW concentration range. The highest microalgal concentration was obtained as 0.481 g/L in the presence of 1 g/L MW. Furthermore, some important parameters for the production of biobutanol, such as microalgal cultivation conditions, initial mixotrophic microalgal biomass loading (50-300 g/L), and fermentation time (24-96 h) were optimized. The highest biobutanol, total ABE, biobutanol yield and productivity were determined as 11.88 g/L, 13.89 g/L, 0.331 g/g and 0.165 g/L/h at the end of 72 h in P2 medium including 60 g/L glucose and 200 g/L microalgal biomass cultivated in 1 g/L MW, respectively. The results show that D. salina is a suitable raw material for supporting Clostridium beijerinckii DSMZ 6422 cells on biobutanol production. To the best of our knowledge, this is the first study on the use of MW which is a promising feedstock on the mixotrophic cultivation of D. salina for biobutanol production.

The present study aims to evaluate the use of cranberry bush fruit pomace (CBFP) (Viburnum opulus L.), which has recently become popular raw material, as a substrate in the presence of a reducing agent to increase biobutanol production by Clostridium beijerinckii DSMZ 6422. For this purpose, some factors were optimized, including the pretreatment, initial concentration of CBFP (5–20%), different types of reducing agents (ascorbic acid, L-cysteine, sodium dithionite and sodium sulfite), different concentrations of sodium dithionite (2.5–15 mM), inoculum concentration (5%, 10%, and 20%), and fermentation time (24–96 h). The maximum biobutanol, total ABE, biobutanol yield, and biobutanol productivity were 9.45 g/L, 12.08 g/L, 0.21 g/g, and 0.13 g/L/h in the medium containing enzymatically hydrolyzed 10% CBFP, 10 mM sodium dithionite, and 20% inoculum at the end of 72 h, respectively. These findings demonstrate that CBFP can be considered as a sustainable, economical, and viable substrate on biobutanol production for the first time in the literature.

Background/Objectives: Vitamin B12 deficiency affects up to 40% of certain populations worldwide and has been associated with cardiometabolic risk. However, its relationship with detailed lipoprotein subfractions remains poorly defined. This study aimed to investigate the association between serum vitamin B12 levels and atherogenic lipid profiles using NMR-based lipoprotein subfraction analysis. Methods: In this retrospective cross-sectional study, data from 20,665 apparently healthy adults undergoing routine health screening were analyzed. Participants were categorized into quartiles based on serum vitamin B12 levels (Q1: ≤328 pg/mL; Q4: ≥540 pg/mL). Lipoprotein subfractions were quantified using Bruker NMR spectroscopy. The Atherogenic Index of Plasma was calculated as log₁₀(triglycerides/HDL-cholesterol). Statistical analyses included ANCOVA adjusted for age, with corrections for multiple comparisons. Results: Higher serum B12 levels were significantly associated with a more favorable lipid profile. Specifically, AIP values decreased progressively across B12 quartiles (Q1: −0.051 ± 0.273; Q4: −0.170 ± 0.294; p < 0.001, partial η² = 0.017). HDL-cholesterol increased (p < 0.001, partial η² = 0.008), while triglycerides and VLDL-TG subfractions (VLDL1-TG: p < 0.001; VLDL5-TG: p = 0.029) declined with higher B12 levels. Among LDL subfractions, small dense LDL (LDL5-TG) exhibited a consistent inverse association with B12 (p = 0.002, partial η² = 0.001). These associations were robust across all age strata, with no significant interaction between B12 levels and age. Conclusions: Serum vitamin B12 levels are inversely associated with atherogenic lipid parameters in a large cohort of asymptomatic individuals. Higher B12 status correlates with lower AIP, reduced triglyceride-rich lipoproteins, and diminished small dense LDL particles across all age groups. These findings suggest that B12 status may serve as a potential biomarker in cardiovascular risk assessment and highlight the need for prospective interventional studies.

Alzheimer’s disease (AD), a neurodegenerative, irreversible, and progressive brain disorder, is characterized by memory loss and cognitive dysfunction. In neurodegeneration, gut microbiota and their metabolites have an impact on behavior and brain function. This study aimed to identify fecal candidate discriminant metabolites in 5XFAD mice assosciated with AD as compared to an age-matched wild-type (WT) healthy mice groups at three different time points (3, 6, and 9 month) using Proton Nuclear Magnetic Resonance (¹H NMR) spectroscopy. A total of 18 male mice (n = 9 for 5XFAD mice and n = 9 for WT, with three animals per age group) were used to determine the fecal candidate discriminant metabolites. As a result of the study, it was identified a total of 67 metabolites in fecal samples. Among these, 19 metabolites were found significantly up-regulated or down-regulated in 5XFAD mice compared to WT mice during the disease progress. According to the volcano plot analysis (FC ≥ 1.2 and p-value ≤ 0.05), the potential candidate discriminant metabolites were fumarate and malate in 3-month-old 5XFAD mice, 3-methylxanthine, glucose, cholate, phenylacetate, and trimethylamine N-oxide (TMAO) in 6-month-old 5XFAD mice and cholate and succinate in 9-month-old 5XFAD mice. These findings highlight the potential of fecal metabolomics as a non-invasive exploratory approach for understanding AD disease mechanisms and progression. Furthermore, to the best of our knowledge, this pilot study is the first to utilize NMR spectroscopy to investigate age-stratified cross-sectional changes in fecal metabolites in 5xFAD mice, thereby advancing our understanding of disease progression and potentially informing future therapeutic strategies. Graphical Abstract The alternative text for this image may have been generated using AI.