Post-acquisition Data Processing Research Articles

Integrated post-acquisition data processing strategy for rapid steroid sulfate characterization in Toad gall-bladder

LC–MS serves as a workhorse for chemical profile characterization of Chinese medicinal materials (CMMs) attributing to the ability of measuring fruitful MS/MS spectral information. However, it is laborious to extract the information belonging to the compounds-of-interest from the massive data matrixes even employing those well-defined post-acquisition data processing strategies. Here, efforts were devoted to propose an integrated strategy allowing rapid chemical homologs-focused data filtering through integrating the fit-for-purpose existing strategies, such as molecular weight imprinting (MWI), diagnostic fragment ion filtering (DFIF), neutral loss filtering (NLF), and isotope pattern filtering (IPF). Homologs-focused chemical characterization of a precious CMM namely Toad gall-bladder (Chinese name: Chandan) that is rich of diverse effective steroid sulfates, particularly bufogenin sulfates, bile acid sulfates and bilichol sulfates, was employed as a proof-of-concept. Recombinant human SULT2A1-catalyzed in vitro metabolism was undertaken to generate eight bufogenin sulfates to facilitate summarizing MS/MS spectral behaviors. After in-house data library construction and MS1 and MS2 spectral acquisition, data filtering was conducted as follows: 1) MWI and IPF was utilized in combination to capture deprotonated molecular ions and the 34S isotopic ions for the sulfates of those reported steroids; 2) m/z 79.9568 (SO3−·) and 96.9596 (HSO4−) were applied to DFIF; and 3) SO3 (79.9568 Da) served as the feature to achieve NLF. Those captured MS/MS information subsequently participated in tentatively structural annotation through applying those empirical mass fragmentation rules. As a result, 71 compounds including 7 bufogenin sulfates, 17 bile acid sulfates, 13 bilichol sulfates and a C-23 steroid sulfate were detected from Toad gall-bladder and thereof, 39 ones received plausible identities assignment. Above all, the steroid sulfates in Toad gall-bladder were profiled in depth, and more importantly, the proposed strategy should be a meaningful option for, but not limited to, submetabolome characterization in CMMs.

Exploration of plant metabolomics variation and absorption characteristics of water-extracted Rheum tanguticum and ethanol-extracted Rheum tanguticum by UHPLC-Q-TOF-MS/MS.

The herb Rheum tanguticum (RT), a member of the Polygonaceae family, is listed in the Chinese Pharmacopoeia and has been widely used to treat cardiovascular and gastrointestinal disease. The research aimed to identify the different substances from two kinds of RT extraction methods and the in vivo biotransformation of RT components. In this study, by using ultrahigh-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS), we have investigated the metabolomic variation and the in vivo metabolism of RT. A post-acquisition data processing software, PeakView, was applied to an accurate qualitative analysis of the chemical components in RT. Through plant metabolomics analysis, 24 related, differentially expressed metabolites of RT water extract and alcohol extract were obtained. Combined with novel identification strategies and systematic in vivo metabolism analysis, a total of 101 compounds were discovered or tentatively identified in rat serum (including 15 prototype compounds and 86 metabolites). In this study, a combination of extraction methods, liquid chromatography-mass spectrometry (LC-MS) technology, and in vivo animal metabolism studies have been established for the screening, identification, and research of chemical active components of natural medicines. LC-MS analysis combined with plant metabolomics was used to study the differential metabolites between different extraction methods of RT. Based on UHPLC-Q-TOF-MS/MS technology, the composition and metabolism of rat plasma before and after RT administration were analysed in vivo, and 15 prototype components and 86 metabolites were detected.

Nontargeted screening of aldehydes and ketones by chemical isotope labeling combined with ultra-high performance liquid chromatography-high resolution mass spectrometry followed by hybrid filtering of features

Aldehydes and ketones are important carbonyl compounds that are widely present in foodstuffs, biological organisms and human living environment. However, it is still challenging to comprehensively detect and capture them using liquid chromatography – mass spectrometry. In this work, a chemical isotope labeling (CIL) coupled with ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC–HRMS) strategy was developed for the capture and detection of this class of compounds. 2,4-Dinitrophenylhydrazine (DNPH) and isotope-labeled DNPH (DNPH-d3) were utilized to selectively label the target analytes. To address the difficulties in processing UHPLC–HRMS data, a post-acquisition data processing method called MSFilter was proposed to facilitate the screening and identification aldehydes and ketones in complex matrices. The MSFilter consists of four independent filters, namely statistical characteristic-based filtering, mass defect filtering, CIL paired peaks filtering, and diagnostic fragmentation ion filtering. These filters can be used individually or in combination to eliminate unrelated interfering MS features and efficiently detect DNPH-labeled aldehydes and ketones. The results of a mixture containing 48 model compounds showed that although all individual filtering methods could significantly reduce more than 95% of the raw MS features with acceptable recall rates above 85%, but they had relatively high false positive ratios of over 90%. In comparison, the hybrid filtering method combining four filters is able to eliminate massive interfering features (> 99.5%) with a high recall rate of 81.25% and a much lower false positive ratio of 15.22%. By implementing the hybrid filtering method in MSFilter, a total of 154 features were identified as potential signals of CCs from the original 45,961 features of real tobacco samples, of which 70 were annotated. We believe that the proposed strategy is promising to analyze the potential CCs in complex samples by UHPLC–HRMS.

Integrated strategy facilitates rapid in-depth chemome characterization of traditional Chinese medicine prescriptions: Shengbai oral liquid as a case.

Chemome characterization is the prerequisite for either therapeutic mechanism clarification or quality control of traditional Chinese medicine prescriptions (TCMPs). Liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) currently serves as the most popular analytical tool; however, chemome characterization is still challenged by MS/MS spectral acquisition and post-acquisition data processing. Here, an integrated strategy was proposed for in-depth chemome clarification of Shengbai oral liquid (SBOL). Gas phase ion fractionation with staggered mass ranges was demonstrated to be the superior acquisition method regarding MS2 spectrum coverage in this study, and narrower mass range further advanced coverage. To facilitate information extraction, all ingredient materials were measured in parallel to form an in-house library, where each MS1 -MS2 item generated a square mass-to-charge ratio (m/z) frame to capture the tagged identity and each chemical family produced a pentagon frame for mass defect features to accomplish chemical analogs-targeted quasi-molecular ion extraction. Square m/z frame imprinting captured 355 identities, while mass defect frames extracted 275 compounds. Attributing to comprehensive MS2 spectrum acquisition and efficient data processing, 355 components were captured and tentatively identified, resulting in a clarified chemical composition for SBOL. Therefore, the proposed strategy should be meaningful for the chemome characterization of TCMPs.

Comparative identification of the metabolites of dehydrocorydaline from rat plasma, bile, urine and feces by both the targeted and untargeted liquid chromatography/mass spectrometry strategies

Severe interference from the endogenous substances is often encountered in characterizing the drug metabolites by liquid chromatography/mass spectrometry using data-dependent acquisition (DDA). To add a precursor ions list (PIL) by DDA or apply data-independent acquisition (DIA) coupled with post-acquisition data processing (such as mass defect filtering, MDF) may assist to target more metabolites from the complex biosamples. Dehydrocorynine (DHC) is a bioactive alkaloid compound rich in Corydalis yanhusuo . We integrated both PIL-DDA and DIA-MDF strategies to probe the metabolites of DHC simultaneously from the rat plasma, bile, urine, and feces. Chromatographic separation was performed on an HSS C18 SB column. The positive-mode collision-induced dissociation-MS 2 data of DHC metabolites were recorded by PIL-DDA on both the QTrap 4500 and Vion IM-QTOF mass spectrometers, and by HDMS E on Vion IM-QTOF. Efficient workflows to process the high-definition DDA (HDDDA) and HDMS E data were elaborated. Totally 40 metabolites (orally administrated at the dose of 100 mg/kg) were identified or tentatively characterized, involving 30 from bile, 16 from feces, 7 from plasma, and 18 from urine. The methoxyls and C-5/C-6/C-8 were the main sites prone to be metabolized via demethylation and oxidation, and further glucuronic acid conjugation and sulfuric acid conjugation. Compared with literature, we can newly discover 17 metabolites in bile, and, for the first time, report the metabolites of DHC from rat urine and feces. Conclusively, the presented PIL-DDA and DIA-MDF strategies are powerful in elucidating the drug metabolites, which thus provides reference to characterizing the metabolic profiles of traditional Chinese medicine components.

Mass Defect Filtering-Oriented Identification of Resin Glycosides from Root of Convolvulus scammonia Based on Quadrupole-Orbitrap Mass Spectrometer.

This work aimed to develop and evaluate a post-acquisition data processing strategy, referred to as a mass defect filter (MDF), for rapid target the resin glycosides in root of Convolvulus scammonia by setting mass rang and mass defect range from high-resolution MS data. The full-scan mass data were acquired by high-performance liquid chromatography coupled with Q Exactive Plus hybrid quadrupole-orbitrap mass spectrometer that featured high resolution, mass accuracy, and sensitivity. To screen resin glycosides, three parent filter m/z 871, m/z 853, and m/z 869 combined with diagnostic fragment ions (DFIs) approach were applied to remove the interference from complex herbal extract. The targeted components were characterized based on detailed fragment ions. Using this approach, 80 targeted components, including 22 glycosidic acids and 58 resin glycosides were tentatively identified. The present results suggested that the proposed MDF strategy would be adaptable to the analysis of complex system in relevant filed.

Time-gated interferometric detection increases Raman scattering to fluorescence signal ratio in biological samples.

Attainable levels of signal-to-background ratio (SBR) in Raman spectroscopy of biological samples is limited by the presence of endogenous fluorophores. It is customary to remove the ubiquitous fluorescence background using postacquisition data processing. However, new approaches are needed to reduce background contributions and maximize the fraction of the sensor dynamical range occupied by Raman photons. Time-resolved detection using pulsed lasers and time-gated measurements can be used to address the signal-to-background problem in biological samples by limiting light detection to nonresonant interaction phenomena with relaxation time scales occurring on sub-nanosecond time scales, thereby excluding contributions from resonant phenomena such as fluorescence. A time-gated Fourier-transform spectrometer was assembled using a commercially available interferometer, a single channel single-photon avalanche diode and time tagging electronics. A time gate of 300 ps increased the signal-to-background-ratio of the 1440 cm-1 Raman band from 36% to 69% in an olive oil sample hereby demonstrating the potential of this approach for autofluorescence suppression.

Direct infusion–tandem mass spectrometry combining with data mining strategies enables rapid chemome characterization of medicinal plants: A case study of Polygala tenuifolia

Data-independent MS2 spectrum acquisition after fragmenting the precursor ion cohort with 1 Da bin, termed as MS/MSALL ®, offers an opportunity to achieve rapid chemome characterization when being coupled with direct infusion (DI). Some post-acquisition data processing strategies, such as mass defect filtering (MDF), diagnostic fragment ion filtering (DFIF), and neutral loss filtering (NLF), facilitate data extraction from massive dataset, and moreover, molecular weight (MW) imprinting allows rapid capturing those reported components. Here, DI–MS/MSALL ® was employed to acquire cubic spectral dataset, and the strategies such as MW imprinting, MDF, DFIF, and NLF, were subsequently applied to filter the structural information. The integrated pipeline was utilized for the chemome characterization of Polygala tenuifolia, a famous edible medicinal plant. To aid information filtering, an in-house chemical library was built by comprehensively collecting structural information from some available databases. A single analytical run was completed within 5 min. For MS1 spectrum processing, MW imprinting was firstly applied to capture the compounds in the chemical library, and “five-point” MDF frames were employed to pursue saponins, oligosaccharide esters, and xanthones. Regarding MS2 spectral plot, DFIF and NLF were deployed to search information-of-interest. Structural identification was accomplished by carefully correlating precursor ions and MS2 spectra, applying the well-defined mass cracking rules, and referring to literature information as well as available databases. A total of 109 compounds, mainly saponins (40 ones), oligosaccharide esters (29 ones), and xanthones (19 ones), were captured and structurally annotated. MS1 spectra were also implemented for chemome comparison between Polygala tenuifolia and several similar plants belonging to Polygala genus, resulting in the observation of significant inter- and intra-species differences. Above all, DI–MS/MSALL ® is a promising choice for high-throughput chemome profiling of, but not limited to, medicinal plants, in particular when being integrated with post-acquisition data processing strategies.

A Monte Carlo Method for Analyzing Systematic and Random Uncertainty in Quantitative Nuclear Magnetic Resonance Measurements.

Quantitative nuclear magnetic resonance (qNMR) is a powerful analytical technology that is capable of quantifying the concentration of any analyte with exquisite accuracy and precision so long as it contains at least one nonlabile nuclear magnetic resonance (NMR)-active nucleus. Unlike with traditional analytical technologies, the concentrations of analytes do not directly influence the uncertainty in the quantification of NMR signals because an ideal NMR response depends only on the nature and amount of the nucleus being observed. Rather, in the absence of spectral artifacts and under favorable experimental conditions, the measurement uncertainty may be influenced by the following factors: (1) spectroscopic parameters such as the spectral width, number of time domain points, and acquisition time; (2) postacquisition data processing, such as apodization and zero-filling; (3) the signal-to-noise ratios (SNRs) and lineshapes of the two signals being used in a qNMR measurement; and (4) the method of signal quantification employed, such as numerical integration or lineshape fitting (LF). Here, a general Monte Carlo (MC) method that considers these factors is presented, with which the random and systematic contributions to qNMR measurement uncertainty may be calculated. Autocorrelation analysis of synthetic and experimental noise is used in a fingerprint-like approach to demonstrate the validity of the simulations. The MC method allows for a general quantitative assessment of measurement uncertainty without the need to acquire spectral replicates and without reference to the molecular structures and concentrations of analytes. Representative examples of qNMR measurement uncertainty simulations are provided in which the metrological performances of integration and LF are contrasted for signal pairs obtained using various acquisition and processing schemes in the low-SNR regime-an area where application of the proposed MC method may prove to be particularly salient.

Direct Flavonoid-Focused Chemical Comparison among Three Epimedium Plants by Online Liquid Extraction-High Performance Liquid Chromatography-Tandem Mass Spectrometry.

It is usually a tedious task to profile the chemical composition of a given herbal medicine (HM) using high performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) due to the time-consuming sample preparation and laborious post-acquisition data processing procedures. Even worse, some labile compounds may face degradation risks when exposed to organic solvents for a relatively long period. As one of the most popular HMs, the promising therapeutic benefits of Epimedii Herba (Chinese name: Yinyanghuo) are well defined; however, the chemical profile, and in particular those flavonoids that have been claimed to be responsible for the efficacy, remains largely unknown. Attempts are devoted here to achieve direct LC–MS measurement and efficient post-acquisition data processing, and chemome comparison among three original sources of Epimedii Herba, such as Epimedium sagittatum (Esa), E. pubescens (Epu), and E. koreanum (Eko) was employed to illustrate the strategy utility. A home-made online liquid extraction (OLE) module was introduced at the front of the analytical column to comprehensively transfer the compounds from raw materials onto the LC–MS instrument. A mass defect filtering approach was programmed to efficiently mine the massive LC–MS dataset after which a miniature database was built involving all chemical information of flavonoids from the genus Epimedium to draw a pentagonal frame to rapidly capture potential quasi-molecular ions (mainly [M–H]−). A total of 99 flavonoids (66 in Esa, 84 in Eko, and 66 in Epu) were captured, and structurally annotated by summarizing the mass fragmentation pathways from the mass spectrometric data of authentic compounds and an in-house data library as well. Noteworthily, neutral loss of 144 Da was firstly assigned to the neutral cleavage of rhamnosyl residues. Significant species-differences didn’t occur among their chemical patterns. The current study proposed a robust strategy enabling rapid chemical profiling of, but not limited to, HMs.

Probelab ReImager: An Open-Source Software for Streamlining Image Processing in an Electron Microscopy Laboratory

Providing high-quality electron images and hyperspectral X-ray maps is a focus of many modern electron microscopy laboratories. Nevertheless, further image processing and annotations are often needed to prepare them for publications and reports. For multi-user facilities, accessibility to processing software can be a limitation either through license costs or availability of processing stations. Open-source software running on multiple platforms allows for post-acquisition data processing in-lab or on user-owned devices. We developed Probelab ReImager to supersede our vendor-supplied acquisition software's exportation by being efficient and highly customizable. This article describes its main features and capabilities.

Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post-Acquisition Data Processing, Visualization, and Structural Characterization.

Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 × 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision ≤6 × 10−4 (0.06%).

Identification and analysis of components in Shen-Fu-Shu granule extract and in rat plasma after oral administration by UPLC-ESI/Q-TOF-MS

Background and objectivesShen-Fu-Shu granule is traditional Chinese herb formula for acute and chronic renal failure. This work was aimed to identify the compounds in Shen-Fu-Shu granule extract and absorbed compounds in rat plasma following oral administration of Shen-Fu-Shu granule. MethodsA high-resolution and high-sensitivity ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight tandem mass spectrometry in positive and negative ion mode were established. The methodology of plasma pharmacochemistry was adopted to analyze the herbal components in vivo. A post-acquisition data processing software UNIFI could automatically, rapidly and accurately achieve the qualitative analysis of the chemical components in Shen-Fu-Shu granule extract and the absorbed components (and their metabolites) in rat plasma after oral administration of Shen-Fu-Shu granule. ResultsCombined with fragments and structure information of LC-Q-TOF-MS, a total of 264 compounds were detected and identified in Shen-Fu-Shu granule extract, while 66 absorbed components (including 38 prototype compounds and 28 metabolites) in plasma were discovered or tentatively characterized in rat plasma. ConclusionsThis study offers a systematically applicable approach for rapid screening and identification of absorbed components derived from multi-herb prescription. It is helpful for understanding the material basis of its therapeutic effects and provides useful information for further study of mechanism of action of Shen-Fu-Shu granule.

Integrated strategy for the extraction and profiling of bioactive metabolites from Passiflora mollissima seeds combining pressurized-liquid extraction and gas/liquid chromatography–high resolution mass spectrometry

An integrated analytical methodology based on pressurized-liquid extraction (PLE) in two steps, followed by in vitro assays and liquid chromatography/gas chromatography coupled to high-resolution mass spectrometry (HRMS), was developed and applied for the isolation and characterization of potential bioactive metabolites from Passiflora mollissima seeds. PLE was proposed in two sequential steps: 1) recovery of the lipidic fraction using nonpolar solvents, and 2) recovery of the phenolic fraction from the defatted seeds’ residue using polar solvents. Cyclohexane was selected as the most suitable extraction solvent for the seeds defatting process (20 min, 100 °C and 100 bar). PLE optimization by response surface methodology was carried out to obtain phenolics-rich extracts with the highest antioxidant activity. Optimal extraction yield (6.58%), total phenolic content (29.99 mg g−1), total flavonoids content (0.94 mg g−1) and antioxidant activity (6.94 mM trolox g-1 and EC50 of 2.66 μg mL−1) were obtained operating at 150 °C with EtOH (100%) as solvent. Untargeted and semi-targeted MS and MS/MS data-mining strategies were successfully implemented for the rapid and comprehensive profiling of the polar and lipidic PLE fractions analysed by UHPLC and GC, respectively, coupled to quadrupole time-of-flight mass spectrometry (q-TOF-MS/MS). Polyphenols-rich extracts from P. mollisima seeds were characterized for the first time applying this approach, showing a broad variety of flavonoids, genuine flavanols (e.g. (epi)fisetinidol) and abundant proanthocyanidins. This application can be considered a successful demonstration of the great potential of the proposed methodology to effectively obtain and characterize complex natural extracts with potential bioactivity, by making use of powerful integrated identification strategies to facilitate the challenging post-acquisition data processing of huge datasets generated by HRMS analysis.

Wide-Scope Determination of Pharmaceuticals and Pesticides in Water Samples: Qualitative and Confirmatory Screening Method Using LC-qTOF-MS

Aquatic system contamination is a subject of concern due to the high number of contaminants with the potential to be hazardous for plant and animal species, including humans. A large number of analytical methods have been developed to evaluate the extension of water resource pollution, most of them focused on target residue analysis. Screening methods for potential target and non-target compounds are a potential alternative and could be used for a comprehensive evaluation of samples composition. Liquid chromatography coupled to time of flight mass spectrometry (LC-qTOF-MS/MS) was developed to provide full-spectrum data and high mass resolution with appropriate selectivity and sensitivity for monitoring of 300 pharmaceuticals and pesticides in environmental water samples. The validation was based on anti-doping analysis validation protocols, using three different concentration levels (0.01, 0.1, and 1.0 μg L−1). Confirmation analysis was achieved using two fragment ions monitoring for each analyte. Samples were extracted by solid-phase extraction and analyzed by LC-qTOF-MS/MS. The final method was able to detect 170 chemicals in wastewater treatment plant effluent and 198 chemicals in surface water. The advantage of using post-acquisition data processing provided by a qTOF-MS/MS system allowed for non-target analysis for an illicit drug metabolite determination. The method was successfully applied to real samples of wastewater and surface water.

Fall Creek Monitoring Station: Highly Resolved Temporal Sampling to Prioritize the Identification of Nontarget Micropollutants in a Small Stream.

The goal of this research was to comprehensively characterize the occurrence and temporal dynamics of target and nontarget micropollutants in a small stream. We established the Fall Creek Monitoring Station in March 2017 and collected daily composite samples for one year. We measured water samples by means of high-resolution mass spectrometry and developed and optimized a postacquisition data processing workflow to screen for 162 target micropollutants and group all mass spectral (MS) features into temporal profiles. We used hierarchical clustering analysis to prioritize nontarget MS features based their similarity to target micropollutant profiles and developed a high-throughput pipeline to elucidate the structures of prioritized nontarget MS features. Our analyses resulted in the identification of 31 target micropollutants and 59 nontarget micropollutants with varying levels of confidence. Temporal profiles of the 90 identified micropollutants revealed unexpected concentration-discharge relationships that depended on the source of the micropollutant and hydrological features of the watershed. Several of the nontarget micropollutants have not been previously reported including pharmaceutical metabolites, rubber vulcanization accelerators, plasticizers, and flame retardants. Our data provide novel insights on the temporal dynamics of micropollutant occurrence in small streams. Further, our approach to nontarget analysis is general and not restricted to highly resolved temporal data acquisitions or samples collected from surface water systems.

Optimization of the post-acquisition data processing for the non-targeted screening of trace leachable residues from reusable plastic bottles by high performance liquid chromatography coupled to hybrid quadrupole time of flight mass spectrometry

Food safety regulations for food contact materials (FCM) usually rely on the assessment of chemical migration in order to reduce human exposure to chemical residues that could leach from the FCM into the food. In this field, there is a need for non-targeted analytical tools which can identify unknown or unexpected leachable residues, and therefore avoid unwanted human exposure. In this study, a method based on high performance liquid chromatography coupled to hybrid quadrupole time of flight mass spectrometry (HPLC-QTOF-MS) was developed and optimized to investigate leachable residues from 30 reusable plastic bottles. Firstly, a method was validated for the targeted analysis of the 11 bisphenol analogues. None of the bisphenols were detected in the food simulants (ethanol/water; 50:50 v/v), indicating that all tested bottles are free of BPA, and that bisphenol analogues were not applied as BPA replacement in bottle manufacture. The effect of post-acquisition data processing parameters on the feature extraction in non-targeted analysis was then systematically investigated. Several parameters significantly reduced the number of correct identifications of some target trace residues, which confirms that data post-processing has to be carefully optimized to decrease the risk of false negatives. The optimized method was effectively applied to the 30 bottle samples, and monomethyl terephthalate was identified at trace level in food simulants in contact with Tritan™ bottles (migration rate of 0.054 ± 0.002–0.53 ± 0.021 µg cm−2 per 10 days at 40 °C). This method can therefore be applied to study the leachable residues from other FCMs and offer some novel information for human risk assessments.

Optimization of sample preparation and green color imaging using the mNeonGreen fluorescent protein in bacterial cells for photoactivated localization microscopy

mNeonGreen fluorescent protein is capable of photo-switching, hence in principle applicable for super-resolution imaging. However, difficult-to-control blinking kinetics that lead to simultaneous emission of multiple nearby mNeonGreen molecules impedes its use for PALM. Here, we determined the on- and off- switching rate and the influence of illumination power on the simultaneous emission. Increasing illumination power reduces the probability of simultaneous emission, but not enough to generate high quality PALM images. Therefore, we introduce a simple data post-processing step that uses temporal and spatial information of molecule localizations to further reduce artifacts arising from simultaneous emission of nearby emitters. We also systematically evaluated various sample preparation steps to establish an optimized protocol to preserve cellular morphology and fluorescence signal. In summary, we propose a workflow for super-resolution imaging with mNeonGreen based on optimization of sample preparation, data acquisition and simple post-acquisition data processing. Application of our protocol enabled us to resolve the expected double band of bacterial cell division protein DivIVA, and to visualize that the chromosome organization protein ParB organized into sub-clusters instead of the typically observed diffraction-limited foci. We expect that our workflow allows a broad use of mNeonGreen for super-resolution microscopy, which is so far difficult to achieve.

A comprehensive protocol for chemical analysis of flame combustion emissions by secondary ion mass spectrometry.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is used to provide detailed information on the surface chemical composition of soot. An analytical protocol is proposed and tested on a laboratory flame, and the results are compared with our previous measurements provided by two-step laser mass spectrometry (L2MS). This work details: (1) the development of a dedicated apparatus to sample combustion products from atmospheric flames and deposit them on substrates suitable for TOF-SIMS analysis; (2) the choice of the deposition substrate and the material of the sampling line, and their effect on the mass spectra; (3) a method to separate the contributions of soot and condensable gas based on impact deposition; and finally (4) post-acquisition data processing. Compounds produced during flame combustion are detected on the surface of different deposition substrates and attributed a molecular formula based on mass defect analysis. Silicon and titanium wafers perform similarly, while the surface roughness of glass microfiber filters results in a reduced mass resolution. The mass spectra obtained from the analysis of different locations of the deposits obtained by impaction show characteristic patterns that are attributed to soot/condensable gas. A working method for the analysis of soot samples and the extraction of useful data from mass spectra is proposed. This protocol should help to avoid common experimental issues like sample contamination, while optimizing the setup performance by maximizing the achievable mass resolution.

Comments on “Nanoscale Investigation of Carrier Lifetime on the Cross Section of Epitaxial Silicon Solar Cells Using Kelvin Probe Force Microscopy”

In recent years, there has been an increasing interest on the study of the complex interplay between the nanostructure and phototransport mechanism in many emerging photovoltaic technologies. Recently, Kelvin probe force microscopy has emerged as a powerful technique for probing photocarrier dynamics and gaining access to carrier lifetime at the nanoscale in a wide range of photovoltaic materials. In the paper entitled “Nanoscale investigation of carrier lifetime on the cross section of epitaxial silicon solar cells using Kelvin Probe Force Microscopy” by Narchi et al . ( IEEE J. Photovolt ., vol. 6, no. 6, pp. 1576–1580, Nov. 2016), an innovative method to asses minority carrier lifetime at the nanoscale using Kelvin probe force microscopy under frequency modulated electrical bias on the cross section of an epitaxial silicon solar cell was demonstrated. The purpose of this note is to complement the results obtained by Narchi et al ., by showing that two-dimensional images of the photocarrier dynamics of different photophysical processes can be obtained upon the implementation of a postacquisition data processing. In this note, we also discuss how this photocarrier dynamical images can be linked with the underlying physical processes that take place in the sample upon carrier injection.