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The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials.
Immunoassays, based on the recognition and capture of analytes by highly selective antibodies, are now used extensively in all areas of diagnostics, but the challenge is to further integrate them into online sensors. To improve the transition from laboratory immunoassays to immunosensors, we have developed a complete flow system, based on a microfluidic core flow cell to enable automated detection of one of the most commonly used immunoassay substrates, TMB, by chronoamperometry. The architecture and fluidic optimisation of the system showed that a specially designed 3D flow cell allows higher flow rates (500 μL min−1) than a standard enlarged microfluidic channel (50 μL min−1) resulting in a significantly shorter detection time of 30 seconds per sample and making the system more robust against interferences due to bubble formation in the chip. The electrochemical measurements showed an improved signal-to-noise ratio (SNR) and thus higher sensitivity for a model immunoassay for diclofenac (SNR = 59), compared to the analytical performance of a conventional laboratory microplate-based assay with optical detection (SNR = 19). In general, this system facilitates the conversion of any conventional immunoassay into an immunosensor with automatic and continuous detection.
BPA is a chemical commonly used in the production of polymer-based materials that can have detrimental effects on the thyroid gland and impact human reproductive health. Various expensive methods, such as liquid and gas chromatography, have been suggested for detecting BPA.
The fluorescence polarization immunoassay (FPIA) is an inexpensive and efficient homogeneous mix-and-read method that allows for high-throughput screening. FPIA offers high specificity and sensitivity and can be carried out in a single phase within a timeframe of 20–30 min. In this study, new tracer molecules were designed that linked the fluorescein fluorophore with and without a spacer to the bisphenol A moiety. To assess the influence of the C6 spacer on the sensitivity of an assay based on the respective antibody, hapten–protein conjugates were synthesized and assessed for performance in an ELISA setup, and this resulted in a highly sensitive assay with a detection limit of 0.05 µg/L. The lowest limit of detection was reached by employing the spacer derivate in the FPIA and was 1.0 µg/L, working range from 2 to 155 µg/L. The validation of the methods was conducted using actual samples compared to LC–MS/MS, which served as the reference method. The FPIA and ELISA both demonstrated satisfactory concordance.
A combination of TLC-bioautography, MALDI-TOF-MS and LC–MS/MS methods was used to identify flavonoids with anti-α-amylase activity in extracts of Lathyrus pratensis L. (herb), L. polyphillus L. (fruits), Thermopsis lanceolata R. Br. (herb) and S. japonica L. (buds). After the TLC-autobiography assay, substances with anti-amylase activity were identified by MALDI-TOF-MS followed by confirmation of the result by LC–MS/MS. Results of the study revealed that the flavonoids apigenin, luteolin, formononetin, genistein and kaempferol display marked anti-α-amylase activity. Formononetin showed the largest activity. Compared with LC–MS/MS, MALDI-TOF-MS is a quick and convenient method; results can be obtained within minutes; and only minor sample amounts are required which allows us to analyse mixtures of substances without preliminary separation. However, the inability to distinguish between isomers is the main limitation of the method.
A certain group of mycotoxins, the ergot alkaloids, has caused countless deaths throughout human history. They are found in rye and other cereals and ingesting contaminated foods can cause serious health problems. To identify contaminated food exceeding the legal limits for ergot alkaloids, a portable and cost-effective test system is of great interest to the food industry. Rapid analysis can be achieved by screening for a marker compound, for which we chose ergometrine. We developed a magnetic bead-based immunoassay for ergometrine with amperometric detection in a flow injection system using a handheld potentiostat and a smartphone. With this assay a limit of detection of 3 nM (1 μg/L) was achieved. In spiked rye flour, ergometrine levels from 25 to 250 μg/kg could be quantified. All results could be verified by optical detection. The developed assay offers great promise to meet the demand for on-site ergometrine detection in the food industry.
Chemical modification by peroxynitrite enhances TLR4 activation of the grass pollen allergen Phl p 5
(2023)
The chemical modification of aeroallergens by reactive oxygen and nitrogen species (ROS/RNS) may contribute to the growing prevalence of respiratory allergies in industrialized countries. Post-translational modifications can alter the immunological properties of proteins, but the underlying mechanisms and effects are not well understood. In this study, we investigate the Toll-like receptor 4 (TLR4) activation of the major birch and grass pollen allergens Bet v 1 and Phl p 5, and how the physiological oxidant peroxynitrite (ONOO–) changes the TLR4 activation through protein nitration and the formation of protein dimers and higher oligomers. Of the two allergens, Bet v 1 exhibited no TLR4 activation, but we found TLR4 activation of Phl p 5, which increased after modification with ONOO– and may play a role in the sensitization against this grass pollen allergen. We attribute the TLR4 activation mainly to the two-domain structure of Phl p 5 which may promote TLR4 dimerization and activation. The enhanced TLR4 signaling of the modified allergen indicates that the ONOO–-induced modifications affect relevant protein-receptor interactions. This may lead to increased sensitization to the grass pollen allergen and thus contribute to the increasing prevalence of allergies in the Anthropocene, the present era of globally pervasive anthropogenic influence on the environment.
Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly
(2023)
Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody–antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69–99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.
For the gradual introduction of hydrogen in the energy market, the study of the properties of mixtures of hydrogen with typical components of natural gas (NG) and liquefied petroleum gas (LPG) is of great importance. This work aims to provide accurate experimental (p, rho, T) data for three hydrogen-propane mixtures with nominal compositions (amount of substance, mol/mol) of (0.95 H2 + 0.05 C3H8), (0.90 H2 + 0.10 C3H8), and (0.83 H2 + 0.17 C3H8), at temperatures of 250, 275, 300, 325, 350, and 375 K, and pressures up to 20 MPa. A single-sinker densimeter was used to determine the density of the mixtures. Experimental density data were compared to the densities calculated from two reference equations of state: the GERG-2008 and the AGA8-DC92. Relative deviations from the GERG-2008 EoS are systematically larger than those from the AGA8-DC92. They are within the ±0.5% band for the mixture with 5% of propane, but deviations are higher than 0.5% for the mixtures with 10% and 17% of propane, especially at low temperatures and high pressures. Finally, the sets of new experimental data have been processed by the application of two different statistical equations of state: the virial equation of state, through the second and third virial coefficients, B(T, x) and C(T, x), and the PC-SAFT equation of state.
Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.
Constant interactions between tumor cells and the extracellular matrix (ECM) influence the progression of prostate cancer (PCa). One of the key components of the ECM are collagen fibers, since they are responsible for the tissue stiffness, growth, adhesion, proliferation, migration, invasion/metastasis, cell signaling, and immune recruitment of tumor cells. To explore this molecular marker in the content of PCa, we investigated two different tumor volumes (500 mm3 and 1000 mm3) of a xenograft mouse model of PCa with molecular magnetic resonance imaging (MRI) using a collagen-specific probe. For in vivo MRI evaluation, T1-weighted sequences before and after probe administration were analyzed. No significant signal difference between the two tumor volumes could be found. However, we detected a significant difference between the signal intensity of the peripheral tumor area and the central area of the tumor, at both 500 mm3 (p < 0.01, n = 16) and at 1000 mm3 (p < 0.01, n = 16). The results of our histologic analyses confirmed the in vivo studies: There was no significant difference in the amount of collagen between the two tumor volumes (p > 0.05), but within the tumor, higher collagen expression was observed in the peripheral area compared with the central area of the tumor. Laser ablation with inductively coupled plasma mass spectrometry further confirmed these results. The 1000 mm3 tumors contained 2.8 +- 1.0% collagen and the 500 mm3 tumors contained 3.2 +- 1.2% (n = 16). There was a strong correlation between the in vivo MRI data and the ex vivo histological data (y = 0.068x + 1.1; R2 = 0.74) (n = 16). The results of elemental analysis by inductively coupled plasma mass spectrometry supported the MRI data (y = 3.82x + 0.56; R2 = 0.79; n = 7). MRI with the collagen-specific probe in PCa enables differentiation between different tumor areas. This may help to differentiate tumor from healthy tissue, potentially identifying tumor areas with a specific tumor biology.