Microalgae-mediated bioremediation: current trends and opportunities-a review.

Environmental pollution poses a critical global challenge, and traditional wastewater treatment methods often prove inadequate in addressing the complexity and scale of this issue. On the other hand, microalgae exhibit diverse metabolic capabilities that enable them to remediate a wide range of pollutants, including heavy metals, organic contaminants, and excess nutrients. By leveraging the unique metabolic pathways of microalgae, innovative strategies can be developed to effectively remediate polluted environments. Therefore, this review paper highlights the potential of microalgae-mediated bioremediation as a sustainable and cost-effective alternative to conventional methods. It also highlights the advantages of utilizing microalgae and algae-bacteria co-cultures for large-scale bioremediation applications, demonstrating impressive biomass production rates and enhanced pollutant removal efficiency. The promising potential of microalgae-mediated bioremediation is emphasized, presenting a viable and innovative alternative to traditional treatment methods in addressing the global challenge of environmental pollution. This review identifies the opportunities and challenges for microalgae-based technology and proposed suggestions for future studies to tackle challenges. The findings of this review advance our understanding of the potential of microalgae-based technology wastewater treatment.

Correlation of Increased Soluble Tumor Necrosis Factor Receptor 1 with Mortality and Dependence on Treatment in Non-Small-Cell Lung Cancer Patients: A Longitudinal Cohort Study.

BACKGROUND: Tumor necrosis factor (TNF) is a multipotent cytokine involved in inflammation and anti-tumor activity. TNF-α exerts its function upon binding to TNF-receptor 1 (TNF-R1) and TNF-receptor 2 (TNF-R2). This study investigates the relationship of soluble (s) TNF-R1 levels in non-small-cell lung cancer (NSCLC) patients with treatment and overall survival. METHODS: In total, 134 NSCLC patients treated at the Medical Faculty of Martin Luther University Halle-Wittenberg between 2017 and 2019 were included in this study. Serum levels of sTNF-R1 were measured via ELISA at baseline and during and after treatment. A linear mixed-effects model was used to assess sTNF-R1 changes over time. Linear regression was applied to investigate the association between clinical characteristics and changes in sTNF-R1. Cox regression models were used to estimate associations with overall mortality. RESULTS: The estimated average sTNFR-1 at baseline was 2091.71 pg/mL, with a change of 6.19 pg/mL per day. Cox models revealed that the individual change in sTNF-R1 was more strongly associated with mortality than its baseline value, especially after adjusting for covariates. CONCLUSIONS: This study provides evidence that the individual change in sTNF-R1 levels during and after treatment were associated with the risk of mortality, suggesting the use of the sTNF-R1 trajectory as a prognostic marker.