Uncertainty estimation strategies for quantitative non-targeted analysis.

Non-targeted analysis (NTA) methods are widely used for chemical discovery but seldom employed for quantitation due to a lack of robust methods to estimate chemical concentrations with confidence limits. Herein, we present and evaluate new statistical methods for quantitative NTA (qNTA) using high-resolution mass spectrometry (HRMS) data from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). Experimental intensities of ENTACT analytes were observed at multiple concentrations using a semi-automated NTA workflow. Chemical concentrations and corresponding confidence limits were first estimated using traditional calibration curves. Two qNTA estimation methods were then implemented using experimental response factor (RF) data (where RF = intensity/concentration). The bounded response factor method used a non-parametric bootstrap procedure to estimate select quantiles of training set RF distributions. Quantile estimates then were applied to test set HRMS intensities to inversely estimate concentrations with confidence limits. The ionization efficiency estimation method restricted the distribution of likely RFs for each analyte using ionization efficiency predictions. Given the intended future use for chemical risk characterization, predicted upper confidence limits (protective values) were compared to known chemical concentrations. Using traditional calibration curves, 95% of upper confidence limits were within ~tenfold of the true concentrations. The error increased to ~60-fold (ESI+) and ~120-fold (ESI-) for the ionization efficiency estimation method and to ~150-fold (ESI+) and ~130-fold (ESI-) for the bounded response factor method. This work demonstrates successful implementation of confidence limit estimation strategies to support qNTA studies and marks a crucial step towards translating NTA data in a risk-based context.

Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization.

Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose-response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and compliance monitoring efforts. Yet, targeted methods have struggled to keep pace with the demands for data regarding the vast, and growing, number of known chemicals. Many contemporary monitoring studies therefore utilize non-targeted analysis (NTA) methods to screen for known chemicals with limited risk information. Qualitative NTA data has enabled identification of previously unknown compounds and characterization of data-poor compounds in support of hazard identification and exposure assessment efforts. In spite of this, NTA data have seen limited use in risk-based decision making due to uncertainties surrounding their quantitative interpretation. Significant efforts have been made in recent years to bridge this quantitative gap. Based on these advancements, quantitative NTA data, when coupled with other high-throughput data streams and predictive models, are poised to directly support 21st-century risk-based decisions. This article highlights components of the chemical risk assessment process that are influenced by NTA data, surveys the existing literature for approaches to derive quantitative estimates of chemicals from NTA measurements, and presents a conceptual framework for incorporating NTA data into contemporary risk assessment frameworks.

Photoactivation and saturated emission in blended conjugated polymer nanoparticles.

Blended poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-benzo-{2,1',3}-thiadiazole)] (PFBT)/poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) conjugated polymer nanoparticles were prepared and characterized by conventional and single-particle fluorescence spectroscopy. The particles exhibit red emission and improved quantum efficiency resulting from highly efficient energy transfer from donor PFBT to acceptor MEH-PPV as well as suppression of MEH-PPV aggregation. Photobleaching results indicate better photostability in the blended sample compared to undoped MEH-PPV nanoparticles and photoactivation of donor emission, which could be useful for single-molecule localization-based super-resolution microscopy. Single blended nanoparticles exhibit bright fluorescence as well as saturation behavior at very low excitation intensities. These and other properties of the blended conjugated polymer nanoparticles could provide substantial improvements in resolution when employed in super-resolution microscopy.

Conjugated polymer nanoparticles incorporating antifade additives for improved brightness and photostability.

Conjugated polymer nanoparticles with incorporated antifade agents were prepared, and ensemble and single particle measurements showed that incorporation of antifade agents effectively improves the fluorescence quantum yield and photostability of the conjugated polymer nanoparticles, likely by a combination of triplet quenching and suppression of processes involved in photogeneration of hole polarons (cations), which act as fluorescence quenchers. The photostability of conjugated polymer nanoparticles and CdSe quantum dots was compared, at both the ensemble and single particle level. The results provide confirmation of the hypothesis that quenching by photogenerated hole polarons is a key factor limiting the fluorescence quantum yield and maximum emission rate in conjugated polymer nanoparticles. Additionally, the results indicate the involvement of oxygen in photogeneration of hole polarons. The results also provide insight into the origin of quenching processes that could limit the performance of conjugated polymer devices.