Glucose uptake in mammalian cells measured by ICP-MS

We developed a sensitive, ratiometric method to measure simultaneously 13C-labeled glucose and rubidium in biological samples using ICP-MS. The method uses probe-assisted ultra-sonication with water to extract 13C-[6C]-labeled-D-glucose and other polar analytes from mammalian tissues. It extracts >80% of the reference value for Rb and >95 % of 13C in a CRM spiked with 13C-[6C]-labeled-D-glucose in the micro-molar range. Using optimized instrument conditions, the method achieves a stable 13C/12C signal without spectral interferences. The 13C/12C signal is independent of sample composition and depends linearly on the concentration of 13C-[6C]-labeled-D-glucose in spiked samples. Overall, the method achieves a limit of detection of 10 uM for 6-C-labeled 13C glucose in biological tissues. This detection capability for carbon in biological matrices by ICP-MS opens a wider range of applications for ICP-MS in biomedical research. As proof-of-principle, we combined 13C detection with the multi-channel capability of ICP-MS to measure glucose and rubidium uptake in the same contracting skeletal muscles. Multi-isotope detection is needed to study many biological processes, including coupled membrane transport. These results demonstrate a capability for carbon detection by ICP-MS that can significantly advance studies of complex biological processes that require multi-isotope detection.

Selective quantification of nanoplastics in environmental matrices by asymmetric flow field – flow fractionation with total organic carbon detection

Nanoplastics are of rapidly emerging concern as ubiquitous environmental pollutants. However, fate and transport assessments are currently hindered by a need for new analytical methods that can selectively quantify nanoplastics...

The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder – IV. Neutral carbon detection in the SPIRE FTS spectra

ABSTRACT The SPIRE Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF), developed within the Herschel Spectral and Photometric Imaging Receiver (SPIRE) FTS instrument team, is an automated spectral feature fitting routine that attempts to find significant features in SPIRE FTS spectra. The 3P1–3P0 and 3P2–3P1 neutral carbon fine structure lines are common features in carbon-rich far-infrared astrophysical sources. These features can be difficult to detect using an automated feature detection routine due to their typically low amplitude and line blending. In this paper, we describe and validate the FF subroutine designed to detect the neutral carbon emission observed in SPIRE spectral data.

Fouling prediction method using TOC and EEM analysis

Many studies on membrane fouling have been made and reported, and it has been revealed, based on liquid chromatography organic carbon detection (LC-OCD), that biopolymer is the main foulant in the drinking water treatment process, in which the raw water is taken from a river or a dam. However, measurement by LC-OCD is time-consuming and costly. Therefore, continuous measurement of biopolymer concentration by LC-OCD is not feasible. For this reason, we have not been able to monitor biopolymer continuously and control membrane fouling. The purpose of this study is to find a new fouling index (FR) to control membrane fouling without measuring the biopolymer concentration. Then, we tried to find a correlation between biopolymer and other water components by a multiple regression analysis. As the result, we have suggested the new fouling index (FR) which consists of the sum of the fluorescence intensity within the Region III domain measured by excitation emission matrix (EEM) fluorescence spectroscopy and the concentration of dissolved organic carbon measured by the total organic carbon (TOC) measurement. TOC and EEM are measured easily and continuously. Thus, we can control membrane fouling by monitoring the FR continuously.