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Analysis of microplastics (MP) in environmental samples is an emerging field, which is performed with various methods and instruments based either on spectroscopy or thermoanalytical methods. In general, both approaches result in two different types of data sets that are either mass or particle number related. Depending on detection limits of the respective method and instrumentation the derived polymer composition trends may vary. In this study, we compare the results of hyperspectral Fourier-transform infrared (FTIR) imaging analysis and pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) analysis performed on a set of environmental samples that differ in complexity and degree of microplastic contamination. The measurements were conducted consecutively, and on exactly the same sample. First, the samples were investigated with FTIR using aluminum oxide filters; subsequently, these were crushed, transferred to glass fiber filters, in pyrolysis cups, and measured via Py-GC/MS. After a general data harmonization step, the trends in MP contamination were thoroughly investigated with regard to the respective sample set and the derived polymer compositions. While the overall trends in MP contamination were very similar, differences were observed in the polymer compositions. Furthermore, polymer masses were empirically calculated from FTIR data and compared with the Py-GC/MS results. Here, a most plausible shape-related overestimation of the calculated polymer masses was observed in samples with larger particles and increased particle numbers. Taking into account the different measurement principles of both methods, all results were examined and discussed, and future needs for harmonization of intermethodological results were identified and highlighted.

Foodborne pathogens, a major cause of foodborne illness due to their high virulence, pose a serious threat to public health. Consequently, identification of foodborne pathogens is essential for the prevention and treatment of foodborne infections. Consequently, there is an immediate need to establish a highly specific and precise approach for the concurrent detection of several foodborne pathogens. Herein, we developed a DNAzyme-based self-protecting dual-response nanoprobe for the simultaneous detection of two foodborne pathogens. The technique utilizes nanostructures to achieve logical signal input and output. In the presence of the target pathogen, the pathogen binds to the arch probe and releases the activation chain, which in turn activates a strand-displacement reaction and DNAzyme for signal amplification, producing different output signals to complete the simultaneous detection of multiple pathogens. The limits of detection for E. coli O157:H7 and S. typhimurium were determined to be 3.7 cfu/mL and 3.2 cfu/mL, with a measurement response time of 2 h. This approach enables ultrasensitive, specific, and simultaneous detection of two foodborne pathogens and is applicable for identifying foodborne pathogens in actual biological samples. The fluorescence detection of foodborne pathogens with a three-way Y-probe and DNAzyme coupling represents a novel approach for the concurrent identification of several foodborne diseases. Graphical Abstract A self-protective DNAzyme-based dual-responsive three-way Y-probe for the simultaneous determination of multiple pathogenic bacteria.

The application of contaminated paper sludge on arable land in southwest Germany caused the occurrence of a broad range of poly- and perfluoroalkyl substances (PFASs) on soil. Recently, the dead-end transformation products (TPs) perfluorooctanoic acid and perfluorooctanesulfonic acid were detected in groundwater and drinking water. The precursors and other transformation products mostly remained unknown. Therefore, HRMS screening by Kendrick mass analysis and assignment of homologous series in combination with suspect screening were applied to identify original PFASs and their TPs in four different soil samples from sites where contaminated paper sludge was applied. In total, twelve compound classes comprising more than 61 PFASs could be fully or tentatively identified. The data reveal that contamination mainly originates from polyfluorinated dialkylated phosphate esters (from 4:2/6:2 to 12:2/14:2), N-ethyl perfluorooctane sulfonamide ethanol–based phosphate diesters (only C8/C8) and transformation products of these precursors. Contamination patterns can be attributed to PFASs used for paper impregnation and can vary slightly from site to site.

Blood samples are widely used for PCR-based DNA analysis in fields such as diagnosis of infectious diseases, cancer diagnostics, and forensic genetics. In this study, the mechanisms behind blood-induced PCR inhibition were evaluated by use of whole blood as well as known PCR-inhibitory molecules in both digital PCR and real-time PCR. Also, electrophoretic mobility shift assay was applied to investigate interactions between inhibitory proteins and DNA, and isothermal titration calorimetry was used to directly measure effects on DNA polymerase activity. Whole blood caused a decrease in the number of positive digital PCR reactions, lowered amplification efficiency, and caused severe quenching of the fluorescence of the passive reference dye 6-carboxy-X-rhodamine as well as the double-stranded DNA binding dye EvaGreen. Immunoglobulin G was found to bind to single-stranded genomic DNA, leading to increased quantification cycle values. Hemoglobin affected the DNA polymerase activity and thus lowered the amplification efficiency. Hemoglobin and hematin were shown to be the molecules in blood responsible for the fluorescence quenching. In conclusion, hemoglobin and immunoglobulin G are the two major PCR inhibitors in blood, where the first affects amplification through a direct effect on the DNA polymerase activity and quenches the fluorescence of free dye molecules, and the latter binds to single-stranded genomic DNA, hindering DNA polymerization in the first few PCR cycles.

Plastics undergo successive fragmentation and chemical leaching steps in the environment due to weathering processes such as photo-oxidation. Here, we report the effects of leachates from UV-irradiated microplastics towards the chlorophyte Scenedesmus vacuolatus. The microplastics tested were derived from an additive-containing electronic waste (EW) and a computer keyboard (KB) as well as commercial virgin polymers with low additive content, including polyethylene (PE), polyethylene terephthalate (PET), polypropylene (PP), and polystyrene (PS). Whereas leachates from additive-containing EW and KB induced severe effects, the leachates from virgin PET, PP, and PS did not show substantial adverse effects in our autotrophic test system. Leachates from PE reduced algae biomass, cell growth, and photosynthetic activity. Experimental data were consistent with predicted effect concentrations based on the ionization-corrected liposome/water distribution ratios (Dlip/w) of polymer degradation products of PE (mono- and dicarboxylic acids), indicating that leachates from weathering PE were mainly baseline toxic. This study provides insight into algae toxicity elicited by leachates from UV-weathered microplastics of different origin, complementing the current particle- vs. chemical-focused research towards the toxicity of plastics and their leachates.

Reference materials (RMs) are vital tools in the validation of methods used to detect environmental pollutants. Microplastics, a relatively new environmental pollutant, require a variety of complex approaches to address their presence in environmental samples. Both interlaboratory comparison (ILC) studies and RMs are essential to support the validation of methods used in microplastic analysis. Presented here are results of quality assurance and quality control (QA/QC) performed on two types of candidate microplastic RMs: dissolvable gelatin capsules and soda tablets. These RMs have been used to support numerous international ILC studies in recent years (2019–2022). Dissolvable capsules containing polyethylene terephthalate (PET), polyvinyl chloride (PVC), polyethylene (PE), and polystyrene (PS), in different size fractions from 50 to 1000 µm, were produced for one ILC study, obtaining relative standard deviation (RSD) from 0 to 24%. The larger size fraction allowed for manual addition of particles to the capsules, yielding 0% error and 100% recovery during QA/QC. Dissolvable capsules were replaced by soda tablets in subsequent ILC studies and recovery test exercises because they were found to be a more reliable carrier for microplastic RMs. Batches of soda tablets were produced containing different single and multiple polymer mixtures, i.e., PE, PET, PS, PVC, polypropylene (PP), and polycarbonate (PC), with RSD ranging from 8 to 21%. Lastly, soda tablets consisting of a mixture of PE, PVC, and PS (125–355 µm) were produced and used for recovery testing during pretreatment of environmental samples. These had an RSD of 9%. Results showed that soda tablets and capsules containing microplastics >50 µm could be produced with sufficient precision for internal recovery tests and external ILC studies. Further work is required to optimize this method for smaller microplastics (< 50 µm) because variation was found to be too large during QA/QC. Nevertheless, this approach represents a valuable solution addressing many of the challenges associated with validating microplastic analytical methods.

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that are used in countless products and applications. Due to the high stability of their C-F bonds, PFAS or their transformation products (TPs) are persistent in the environment, leading to ubiquitous detection in various samples worldwide. Since PFAS are industrial chemicals, the availability of authentic PFAS reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for a more comprehensive characterization. NTS usually is a time-consuming process, since only a small fraction of the detected chemicals can be identified. Therefore, efficient prioritization of relevant HRMS signals is one of the most crucial steps. We developed PFΔScreen, a Python-based open-source tool with a simple graphical user interface (GUI) to perform efficient feature prioritization using several PFAS-specific techniques such as the highly promising MD/C-m/C approach, Kendrick mass defect analysis, diagnostic fragments (MS2), fragment mass differences (MS2), and suspect screening. Feature detection from vendor-independent MS raw data (mzML, data-dependent acquisition) is performed via pyOpenMS (or custom feature lists) with subsequent calculations for prioritization and identification of PFAS in both HPLC- and GC-HRMS data. The PFΔScreen workflow is presented on four PFAS-contaminated agricultural soil samples from south-western Germany. Over 15 classes of PFAS (more than 80 single compounds with several isomers) could be identified, including four novel classes, potentially TPs of the precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). PFΔScreen can be used within the Python environment and is easily automatically installable and executable on Windows. Its source code is freely available on GitHub (https://github.com/JonZwe/PFAScreen).

Extracellular vesicles (EVs) have emerged as an attractive drug delivery system owing to their natural roles in intercellular communication. On account of the large intrinsic heterogeneity of EVs, it is highly desirable to evaluate not only the encapsulation efficiency but also the alteration of biological functionality after the drug-loading process at the single-particle level. However, the nanoscale size of EVs poses a great challenge. Taking advantage of nano-flow cytometry (nFCM) in the multiparameter analysis of single EVs as small as 40 nm, six commonly used drug-loading strategies (coincubation, electroporation, extrusion, freeze-thawing, sonication, and surfactant treatment) were exploited by employing doxorubicin (Dox) as the model drug. Encapsulation ratio, EV concentration, drug content, and membrane proteins of Dox-loaded EVs were measured at the single-particle level. Our data indicated that coincubation and electroporation outperformed other methods with an encapsulation ratio of approximately 45% and a higher Dox content in single EVs. Interestingly, the labeling ratios of membrane proteins indicated that varying degrees of damage to the surface proteins of EVs occurred upon extrusion, freeze-thawing, sonication, and surfactant treatment. Confocal fluorescence microscopy and flow cytometry analysis revealed that Dox-loaded EVs prepared by electroporation induced the strongest apoptosis followed by coincubation. These results correlated well with their cellular uptake rate and fundamentally with the Dox encapsulation efficiency of single EVs. nFCM provides a rapid and sensitive platform for single-particle assessment of drug-loading strategies for incorporating drugs into EVs. Graphical abstract

Untargeted analysis of a composite house dust sample has been performed as part of a collaborative effort to evaluate the progress in the field of suspect and nontarget screening and build an extensive database of organic indoor environment contaminants. Twenty-one participants reported results that were curated by the organizers of the collaborative trial. In total, nearly 2350 compounds were identified (18%) or tentatively identified (25% at confidence level 2 and 58% at confidence level 3), making the collaborative trial a success. However, a relatively small share (37%) of all compounds were reported by more than one participant, which shows that there is plenty of room for improvement in the field of suspect and nontarget screening. An even a smaller share (5%) of the total number of compounds were detected using both liquid chromatography–mass spectrometry (LC-MS) and gas chromatography–mass spectrometry (GC-MS). Thus, the two MS techniques are highly complementary. Most of the compounds were detected using LC with electrospray ionization (ESI) MS and comprehensive 2D GC (GC×GC) with atmospheric pressure chemical ionization (APCI) and electron ionization (EI), respectively. Collectively, the three techniques accounted for more than 75% of the reported compounds. Glycols, pharmaceuticals, pesticides, and various biogenic compounds dominated among the compounds reported by LC-MS participants, while hydrocarbons, hydrocarbon derivatives, and chlorinated paraffins and chlorinated biphenyls were primarily reported by GC-MS participants. Plastics additives, flavor and fragrances, and personal care products were reported by both LC-MS and GC-MS participants. It was concluded that the use of multiple analytical techniques was required for a comprehensive characterization of house dust contaminants. Further, several recommendations are given for improved suspect and nontarget screening of house dust and other indoor environment samples, including the use of open-source data processing tools. One of the tools allowed provisional identification of almost 500 compounds that had not been reported by participants.

The development of a sensitive and specific detection platform for exosomes is highly desirable as they are believed to transmit vital tumour-specific information (mRNAs, microRNAs, and proteins) to remote cells for secondary metastasis. Herein, we report a simple method for the real-time and label-free detection of clinically relevant exosomes using a surface plasmon resonance (SPR) biosensor. Our method shows high specificity in detecting BT474 breast cancer cell–derived exosomes particularly from complex biological samples (e.g. exosome spiked in serum). This approach exhibits high sensitivity by detecting as low as 8280 exosomes/μL which may potentially be suitable for clinical analysis. We believe that this label-free and real-time method along with the high specificity and sensitivity may potentially be useful for clinical settings.