MeHg production in eutrophic lakes: Focusing on the roles of algal organic matter and iron-sulfur-phosphorus dynamics.

The mechanisms by which eutrophication affects methylmercury (MeHg) production have not been comprehensively summarized, which hinders accurately predicting the MeHg risk in eutrophic lakes. In this review, we first discussed the effects of eutrophication on biogeochemical cycle of mercury (Hg). Special attentions were paid to the roles of algal organic matter (AOM) and iron (Fe)-sulfur (S)-phosphorus (P) dynamics in MeHg production. Finally, the suggestions for risk control of MeHg in eutrophic lakes were proposed. AOM can affect in situ Hg methylation by stimulating the abundance and activities of Hg methylating microorganisms and regulating Hg bioavailability, which are dependent on bacteria-strain and algae species, the molecular weight and composition of AOM as well as environmental conditions (e.g., light). Fe-S-P dynamics under eutrophication including sulfate reduction, FeS formation and P release could also play crucial but complicated roles in MeHg production, in which AOM may participate through influencing the dissolution and aggregation processes, structural order and surface properties of HgS nanoparticles (HgSNP). Future studies should pay more attention to the dynamics of AOM in responses to the changing environmental conditions (e.g., light penetration and redox fluctuations) and how such variations will subsequently affect MeHg production. The effects of Fe-S-P dynamics on MeHg production under eutrophication also deserve further investigations, especially the interactions between AOM and HgSNP. Remediation strategies with lower disturbance, greater stability and less cost like the technology of interfacial O2 nanobubbles are urgent to be explored. This review will deepen our understanding of the mechanisms of MeHg production in eutrophic lakes and provide theoretical guidance for its risk control.

Graphene Oxide-Based Highly Sensitive Assay of Circulating MicroRNAs for Early Prediction of the Response to Neoadjuvant Chemotherapy in Breast Cancer.

The response to neoadjuvant chemotherapy (NAC) is highly correlated with survival in breast cancer (BC) patients. The early prediction of the response to NAC could facilitate treatment adjustments on a patient-by-patient basis, which would improve patient outcomes and survival. Conventional techniques used for detecting circulating microRNAs (miRNAs), which act as biomarkers for the early prediction of NAC efficacy in BC patients, are associated with limitations such as low sensitivity and specificity. We designed a highly sensitive graphene oxide (GO)-based qRT-PCR method for detecting miRNAs associated with the chemotherapeutic response in BC patients. The results showed that miRNA levels at both the baseline and end of the first NAC cycle could help distinguish NAC responders from NAC nonresponders; BC patients with lower plasma miRNA levels were more likely to achieve pathological complete remission. Thus, GO-based qRT-PCR could facilitate early prediction of NAC efficacy in BC patients.

Graphene oxide-based qRT-PCR assay enables the sensitive and specific detection of miRNAs for the screening of ovarian cancer.

Circulating microRNAs (miRNAs) have the potential to become reliable and noninvasive biomarkers for ovarian cancer (OC) diagnosis; however, the conventional miRNAs detection techniques exhibit enduring limitations of low sensitivity and specificity. Graphene oxide (GO), a novel nanomaterial, is at the forefront of material design for extensive biomedical applications. Owing to the excellent water affinity and single-stranded DNA (ssDNA) adsorption characteristics of GO, we designed and developed a GO-based qRT-PCR assay for the detection of miRNAs associated with OC. In the GO-based qRT-PCR system, GO could significantly improve the sensitivity and specificity of the qRT-PCR assay by noncovalently interacting with primers and ssDNA and reducing the occurrence of non-specific amplification. Moreover, the detection of miRNAs associated with OC confirmed that GO-based qRT-PCR assay could differentiate benign ovarian tumors from OC (sensitivity, 0.91; specificity, 1.00). Collectively, these findings provide robust evidence that GO-based qRT-PCR assay can be effectively used as a promising method to detect miRNAs for the screening of OC patients.