Different responses of taxonomic and functional trait structure of benthic macroinvertebrate assemblages to eutrophication in a large Chinese freshwater lake.

Functional trait measures have the potential to represent local habitat conditions and are considered promising tools for biomonitoring and bioassessment programs. Macroinvertebrates are an ecologically significant group in freshwater ecosystems and possess a range of functional traits which are employed to assess ecological quality. Nevertheless, the relationships between macroinvertebrate functional structure and anthropogenic disturbances remain poorly understood. In this study, we conducted a comparison of how functional trait-based and taxonomy-based composition of macroinvertebrate assemblages responded to eutrophication in Lake Taihu, a typical large eutrophic freshwater lake in China. Specifically, we examined both the taxonomy-based and trait-based compositions of benthic macroinvertebrates varied along the eutrophication gradient. Eutrophication was associated with remarkable decreases in the abundance of gastropod taxa and increases in Oligochaeta and Chironomidae. Ten categories belonging to six traits were significantly different among three site groups. The eutrophic and transition sites showed higher abundance of Size2, burrowers, and integument-respiration organisms than macrophytic sites, whereas abundance of Size1, conical-shaped, sprawlers, scrapers, and lung-respiration were higher in macrophytic sites. Both taxonomic (36.8%) and functional compositions (39.8%) of macroinvertebrate assemblages were influenced by the same variables: CODMn and transparency. Our study showed that macroinvertebrate trait-based approaches can be considered a useful supplement to traditional taxonomic approach for biomonitoring programs in freshwater lakes.

Biomarker Discovery for Hepatocellular Carcinoma in Patients with Liver Cirrhosis Using Untargeted Metabolomics and Lipidomics Studies.

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is the third leading cause of mortality globally. Patients with HCC have a poor prognosis due to the fact that the emergence of symptoms typically occurs at a late stage of the disease. In addition, conventional biomarkers perform suboptimally when identifying HCC in its early stages, heightening the need for the identification of new and more effective biomarkers. Using metabolomics and lipidomics approaches, this study aims to identify serum biomarkers for identification of HCC in patients with liver cirrhosis (LC). Serum samples from 20 HCC cases and 20 patients with LC were analyzed using ultra-high-performance liquid chromatography-Q Exactive mass spectrometry (UHPLC-Q-Exactive-MS). Metabolites and lipids that are significantly altered between HCC cases and patients with LC were identified. These include organic acids, amino acids, TCA cycle intermediates, fatty acids, bile acids, glycerophospholipids, sphingolipids, and glycerolipids. The most significant variability was observed in the concentrations of bile acids, fatty acids, and glycerophospholipids. In the context of HCC cases, there was a notable increase in the levels of phosphatidylethanolamine and triglycerides, but the levels of fatty acids and phosphatidylcholine exhibited a substantial decrease. In addition, it was observed that all of the identified metabolites exhibited a superior area under the receiver operating characteristic (ROC) curve in comparison to alpha-fetoprotein (AFP). The pathway analysis of these metabolites revealed fatty acid, lipid, and energy metabolism as the most impacted pathways. Putative biomarkers identified in this study will be validated in future studies via targeted quantification.