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Trace 17β-estradiol (E2) is persistent against advanced treatment when blended with higher concentrations of low-toxicity organics, thus wasting energy. A circulating-flow selective photoelectrocatalysis (CF-SPEC) system is established with a selective E2-TiO2-NR photoanode, accurately reducing 1 μg L-1 E2 to less than 0.1 ng L-1 along with eliminating estrogenic activity even when blended with natural organic matter (NOM) at a thousand times higher concentration. Such high efficiency is derived from the augmented selectivity and activity of E2-TiO2-NRs toward E2 during CF-SPEC. Under a flow, the difference in adsorption capacity between NOM and E2 is further amplified 5.6-fold. Furthermore, the higher initial •OH concentration and faster mass transfer jointly endow CF-SPEC with a stronger oxidation capacity. [https://www.selleckchem.com/products/Rapamycin.html Rapamycin solubility dmso] As a result, the removal of E2 increases by 58.7%, and the elimination of estrogenic activity increases 5.8-fold. In addition, deeper mineralization and less homo- and heterocoupling under CF-SPEC are observed, leading to more thorough estrogenic activity removal. Although additional energy is needed to maintain the flow, there is a 55% decrease in energy consumption due to the accurate removal capacity. This work suggests a combination of flow degradation and surface engineering that can be expanded for the selective removal of toxic trace pollutants in blended systems.The necessity of a simple measurement of platelet activation has been increasing in clinical medicine to regulate the proper dose of the antiplatelet drugs for patients having clinical outcomes in acute situations such as angina pectoris, stroke, or peripheral vascular disease or procedures involving angioplasty or coronary thrombolysis. We developed a self-signaling polydiacetylene (PDA) liposome microarray to detect activated platelets from whole blood samples in a single step. A specific antibody, 9F9 antibody, to platelet-bound fibrinogen was selected and conjugated to the PDA liposome microarray to quantify the fibrinogen-bound platelets. The developed PDA liposome-9F9 microarray generated an intense fluorescence signal when activated platelets in whole blood were introduced and also successfully distinguished the reduced platelet activation in the presence of Tirofiban, a model antiplatelet drug. The results of this single-step benchtop assay incorporates simple, sensitive, and rapid attributes that can detect the extent of platelet activation prior to needed clinical procedures.In this work, we report the design of novel fluorophores that bear three benzothiadiazole and benzoselenadiazole groups, respectively, for sensitive detection of trimethyl arsine vapor. In particular, the fluorophore with the benzoselenadiazole groups can form stronger chalcogen bonding with trimethyl arsine than the fluorophore with the benzothiadiazole groups, which in turn triggers much faster and more sensitive fluorescence responses. On the basis of this novel mechanism, fluorescence detection of trimethyl arsine vapor with rapid response (∼3 s), high sensitivity (the theoretical LOD is 0.44 ppb), and high selectivity is achieved on bundled nanofibers from the fluorophore with the benzoselenadiazole groups. Here, the new fluorescence sensor may find wide applications in health and environmental monitoring, arsenic distribution recognition in soil, and arsenic mines exploration.γ-Secretase (GS) is one of the most attractive molecular targets for the treatment of Alzheimer's disease (AD). Its key role in the final step of amyloid-β peptides generation and its relationship in the cascade of events for disease development have caught the attention of many pharmaceutical groups. Over the past years, different inhibitors and modulators have been evaluated as promising therapeutics against AD. However, despite the great chemical diversity of the reported compounds, a global classification and visual representation of the chemical space for GS inhibitors and modulators remain unavailable. In the present work, we carried out a two-dimensional (2D) chemical space analysis from different classes and subclasses of GS inhibitors and modulators based on their structural similarity. Along with the novel structural information available for GS complexes, our analysis opens the possibility to identify compounds with high molecular similarity, critical to finding new chemical structures through the optimization of existing compounds and relating them with a potential binding site.Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.e., hauling, decay overland, and downstream). We introduce the microbial Find, Inform, and Test (FIT) framework, which expands previous LUR approaches and develops novel spatial predictor models to characterize the transported contributions. We applied FIT to characterize the sources of BoBac, a ruminant Bacteroides MST marker, quantified in riverbed sediment samples from Kewaunee County, Wisconsin. A 1 standard deviation increase in contributions from land-applied manure hauled from animal feeding operations (AFOs) was associated with a 77% (p-value less then 0.05) increase in the relative abundance of ruminant Bacteroides (BoBac-copies-per-16S-rRNA-copies) in the sediment. This is the first work finding an association between the upstream land-applied manure and the offsite bovine-associated fecal markers. These findings have implications for the sediment as a reservoir for microbial pollution associated with AFOs (e.g., pathogens and antibiotic-resistant bacteria). This framework and application advance statistical analysis in MST and water quality modeling more broadly.Salt marsh sediments are known hotspots for nitrogen cycling, including the production and consumption of nitrous oxide (N2O), a potent greenhouse gas and ozone-depleting agent. Coastal eutrophication, particularly elevated nitrogen loading from the application of fertilizers, is accelerating nitrogen cycling processes in salt marsh sediments. Here, we examine the impact of long-term fertilization on nitrogen cycling processes with a focus on N2O dynamics in a New England salt marsh. By combining 15N-tracer experiments with numerical modeling, we found that both nitrification and denitrification contribute to net N2O production in fertilized sediments. Long-term fertilization increased the relative importance of nitrification to N2O production, likely a result of increased oxygen penetration from nutrient-induced increases in marsh elevation. Substrate utilization rates of key nitrogen cycling processes revealed links between functions and the corresponding microbial communities. Higher specific substrate utilization rates leading to N2O production from nitrification in fertilized sediments indicate a shift in the community composition of ammonia oxidizers, whereas the lack of change in specific substrate utilization of N2O production from denitrification under long-term fertilization suggests resilience of the denitrifying communities.