Substrate filling ratio affects nitrogen removal and antibiotic resistance risk in modular moving bed constructed wetland: Biofilm-mediated microbial community succession and resistome profiles reshaping.
Aug 2026· Environmental Research· pp.
125574
· 0 citations· 48 references
Medicine
Abstract
Constructed wetlands (CWs) are widely used for advanced treatment of wastewater treatment plant effluents and their nitrogen (N) removal performance is often inhibited by antibiotics. Biofilms on CW substrates play a fundamental role in pollutant biodegradation, microbial community stability and antibiotic resistance gene (ARG) dissemination. This study investigated the effects of substrate filling ratios (90% and 60%) in modular moving bed constructed wetlands (MMB-CWs) on operational performance, biofilm properties and antibiotic resistance risks. The MMB-CW with higher substrate filling ratio exhibited a better N removal efficiency of 83.7% and a significant reduction of nitrous oxide emission by 72.6%. The higher substrate filling ratio increased the protein/polysaccharide ratio of extracellular polymeric substances (EPS), potentially forming a hydrophobic barrier and structured a highly modular microbial network with pronounced niche differentiation. Genome-centric analysis revealed that core taxa carrying denitrification and anammox genes (narG, narH, nirS, nosZ, hzs, hdh) enriched by 1.5- to 12.6-fold in abundance in the MMB-CW with 90% substrate filling ratio. Notably, Desulfobacillus increased by 1.7-fold in abundance, which served as a keystone species driving denitrification, EPS construction, oxidative stress adaptation and energy production. The elevated abundances of enzymes catalyzing key electron- and energy-generating steps in the tricarboxylic acid cycle and denitrification enzymes drove a more complete denitrification process. The highly modular network restricted horizontal gene transfer of ARGs, mitigated the enrichment of pathogenic antibiotic-resistant bacteria (PARBs) and occurrence of high-risk ARGs in MMB-CW. The findings provide an optimization strategy for MMB-CW in view of treatment performance and ecological risk.
This study constructed a pH-responsive P-TN/SF@Fe-Cur composite coating that demonstrated significant anti-infective, anti-inflammatory, antioxidant, pro-angiogenic, and pro-osteogenic effects in rat subcutaneous infection and femoral defect models.
The results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.
Felicia T. Jiang, Dengwang Chen, Ziwei Wang et al.· bioRxiv· 1 citation
Protein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in binding affinity, rather than absolute values. DyAb is built on top of a pre-trained protein language model and achieves a Spearman rank correlation of up to 0.85 on binding affinity prediction across monoclonal antibodies targeting three different antigens (EGFR, IL-6, and an internal target), given as few as 100 training data. We employ DyAb in two design contexts: as a ranking model to score combinations of known mutations, and combined with a genetic algorithm to generate new sequences. Our method consistently generates antibody variants with high binding rates, including designs that improve on the binding affinity of the lead molecule by more than ten-fold. DyAb represents a powerful tool for optimizing antibody binding affinity in low data regimes common in early-stage drug development.
Joshua Yao-Yu Lin, Jennifer L. Hofmann, Andrew Leaver‐Fay et al.· mAbs· 1 citation
Due to its importance and wide adoption, wheat cultivation is promptly required to shift towards sustainable practices, reducing the dependency on chemical components. Among bio-based solutions aimed at securing the sustainability of wheat cultivation, biostimulants offer a versatile platform of eco-friendly tools assuring sustainability and profitability. Microalgae present a concrete example of a biostimulant source due to their richness in metabolites and high value products. Therefore, this study evaluated the biostimulant potential of eleven eco-extracts prepared from soil-isolated microalgae strains. Eco-extracts applied via soil drench at low dose (0.1 g/L) were investigated for their biostimulant effects on wheat growth, physiology, yield, and quality under controlled conditions. Results demonstrated significant ameliorations in treated plants as compared to the control, with no phytoinhibitory effects. Remarkable enhancements were notable in growth parameters such as shoot and root lengths (+40-70%), physiological traits such as total chlorophyll and stomatal conductance (+7-52%), yield components in the example of grain number per spike and thousand grain weight (+17-103%), and grain quality namely protein and polyphenol content (+2-fold to 4-fold). Similarly, phosphorus accumulation and uptake were significantly improved, while soil physicochemical status was ameliorated, indicating enhanced fertility. Multivariate analysis and composite index ranking marked Chlorella sp. GA18, Chlorella sp. GA65, Scenedesmus sp. GA69, and Chlorococcum sp. GA63 as eco-extracts with consistent performances across all plant traits. These findings highlighted the promising potential of integrating microalgae-based eco-friendly extracts in sustainable wheat cultivation.
Amer Chabili, Z. Hakkoum, F. Minaoui et al.· Plant Science· 1 citation
ProteinReasoner is developed, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture and suggests a general route towards reasoning across interdependent representations in other scientific domains.
Chaozhong Liu, Linlin Chao, Shaomin Ji et al.· bioRxiv· 1 citation
HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in two and three dimensions.
Christian Lagemann, Sajeda Mokbel, Miro Gondrum et al.· Nature· 1 citation