Blank experimental study on the determination of nitrogen and oxygen isotopes by chemical conversion method

Recent advances in non-plasmonic surface-enhanced Raman spectroscopy nanostructures for biomedical applications

Surface-enhanced Raman spectroscopy (SERS) is an emerging powerful vibrational technique offering unprecedented opportunities in biomedical science for the sensitive detection of biomarkers and the imaging and tracking of biological samples. Conventional SERS detection is based on the use of plasmonic substrates (e.g., Au and Ag nanostructures), which exhibit very high enhancement factors (EF = 1010 -1011 ) but suffers from serious limitations, including light-induced local heating effect due to ohmic loss and expensive price. These drawbacks may limit detection accuracy and large-scaled practical applications. In this review, we focus on alternative approaches based on plasmon-free SERS detection on low-cost nanostructures, such as carbons, oxides, chalcogenides, polymers, silicons, and so forth. The mechanism of non-plasmonic SERS detection has been attributed to interfacial charge transfer between the substrate and the adsorbed molecules, with no photothermal side-effects but usually less EF compared with plasmonic nanostructures. The strategies to improve Raman signal detection, through the tailoring of substrate composition, structure, and surface chemistry, is reviewed and discussed. The biomedical applications, for example, SERS cell characterization, biosensing, and bioimaging are also presented, highlighting the importance of substrate surface functionalization to achieve sensitive, accurate analysis, and excellent biocompatibility. This article is categorized under: Diagnostic Tools > Diagnostic Nanodevices Diagnostic Tools > Biosensing Diagnostic Tools > In Vivo Nanodiagnostics and Imaging.

Identification of nitrate sources in the Jing River using dual stable isotopes, Northwest China

Nitrate (NO₃^-) contamination has become a dominant international problem in the aquatic environment, so identifying the sources and transformations of NO₃^- is the basis for improving water quality. Since the Jing River is the largest tributary of the Wei River, to understand its water quality, this study collected surface water samples from the Shaanxi section of the Jing River during the dry season. The potential sources of NO₃^- were analyzed by hydrochemical and bi-isotopic methods, and the SIAR model was used to estimate the proportional contribution of each source. Results indicated that NO₃^--N was the main form of inorganic nitrogen in this area, and the average total nitrogen content was 10.23 mg·L^-1, which showed that nitrogen pollution was highly serious; the transformation process of nitrogen in this study area was mainly nitrification; The results of Bayesian model showed that manure and sewage contributed to the most NO₃^- (64.39%) in the dry season, followed by soil nitrogen, which was 26.35%. These results help to adopt better nitrogen management measures to meet the national environmental quality standards for surface water.