The effect of biomass concentration on the formation of Aspergillus oryzae alpha-amylase during submerged cultivation with A. oryzae and recombinant A. nidulans strains has been investigated. It was found that the specific rate of alpha-amylase formation in chemostats decreased significantly with increasing biomass concentration in the range of approx. 2-12 g dry weight kg(-1). When using a recombinant A. nidulans strain in which the gene responsible for carbon catabolite repression of the A. oryzae alpha-amylase gene (creA) was deleted, no significant decrease in the specific rate of alpha-amylase formation was observed. On the basis of the experimental results, it is suggested that the low value of the specific alpha-amylase productivity observed at high biomass concentration is caused by slow mixing of the concentrated feed solution in the viscous fermentation medium.
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http://dx.doi.org/10.1007/s002530000456 | DOI Listing |
Environ Res
January 2025
School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, 230601, China.
The efficient degradation of SAs is a significant challenge for the treatment of wastewater. To address this, the FeS@BC was prepared by calcining a mixture of pyrite and biomass, and used to activate peroxydisulfate (PDS) to degrade sulfadiazine (SDZ). The effect of carbon sources (wheat straw, rice husk, and corn cob) on catalytic activity of FeS@BC were investigated by Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), total Fe dissolution and free radical quantification.
View Article and Find Full Text PDFEnviron Res
January 2025
Institute of Science and Technology, São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, 18087-180 Sorocaba, SP, Brazil. Electronic address:
This study provides comprehensive overview of the current level, sources and human exposure risk to hazardous polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs) in South American outdoor air. Research documents were obtainable for only 6 countries within the target period (2014 - 2024). For all contaminants, urban concentrations exceeded that of rural/remote locations.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona, 18-26, 08034, Barcelona, Spain.
The present study evaluates for the first time the seasonal performance of an innovative green groundwater treatment. The pilot plant combines microalgae-bacteria treatment and a cork-wood biofilter to reduce nitrates, pesticides, antibiotics (ABs), and antibiotic resistance genes (ARGs) from groundwater. Groundwater had nitrate concentrations ranging from 220 to 410 mg/L, while ABs (sulfonamides and fluoroquinolones) and pesticides (triazines) were detected at concentrations ranging from a few ng/L to 150 ng/L.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha, China. Electronic address:
Traditionally, abiotic factors such as pH, temperature, and initial Cr(VI) concentration have been undoubtedly recognized as the external driving forces that dramatically affect the microbial-mediated remediation of Cr(VI) pollutants. However, concentrating on whether and how the biological behaviors and metabolic activities drive the microbial-mediated Cr(VI) detoxification is a study-worthy but little-known issue. In this study, Leucobacter chromiireducens CD49 isolated from heavy-metal-contaminated soil was identified to tolerate 8000.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Energy & Environmental Engineering, Hebei University of Technology, Tianjin, 300401, China. Electronic address:
Photosynthetic bacteria (PSB) excel in wastewater treatment by removing pollutants and generating biomass but are challenging to optimize due to complex operational and environmental interactions. Neural Ordinary Differential Equations, Elastic Net, Stacking, and Categorical Boosting were applied as artificial intelligence methods to predict chemical oxygen demand (COD) removal efficiency, biomass productivity, biomass yield, and energy yield. Among these, the Stacking model demonstrated superior predictive performance across all targets.
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