Historic object analysis and the knowledge of composition play an important role in restoration processes. Based on this information, restoration works are conducted. This paper introduces a non-invasive technique of plaster and mortar material decomposition using reflectance spectroscopy. For this purpose, a NIRQuest512-2,5 from Ocean Optics®/Ocean Insight®, is used to create a unique spectral library consisting of various materials. They were carefully selected to include those that were and still are commonly used for a plaster and mortar production. Each material of the spectral library was mapped in detail, verified using scanning electronic microscope (SEM) data, and the results were compared to a previously determined spectral signature. The new spectral library was then tested on 11 unknown plaster and mortar samples and verified using a scanning electronic microscope. It was found that reflectance spectroscopy provides a powerful tool for plaster and mortar material decomposition, although at the moment it cannot fully replace invasive techniques like chemical analyses or other invasive techniques. It provides relevant information that can be used for restoration works.

• Klíčová slova
• material decomposition, reflectance spectroscopy, spectral library,
• Publikační typ
• časopisecké články MeSH

To address the lack of high-resolution electron ionisation mass spectral libraries (HR-[EI+]-MS) for environmental chemicals, a retention-indexed HR-[EI+]-MS library has been constructed following analysis of authentic compounds via GC-Orbitrap MS. The library is freely provided alongside a compound database of predicted physicochemical properties. Currently, the library contains over 350 compounds from 56 compound classes and includes a range of legacy and emerging contaminants. The RECETOX Exposome HR-[EI+]-MS library expands the number of freely available resources for use in full-scan chemical exposure studies and is available at: https://doi.org/10.5281/zenodo.4471217.

• Klíčová slova
• chemical exposure, electron ionization [EI+], gas chromatography mass spectrometry, high-resolution, spectral library,
• MeSH
• data management MeSH
• expozom * MeSH
• plynová chromatografie s hmotnostně spektrometrickou detekcí MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Spectrum-averaged cross sections (SACS) is an important quantity usable in validation of nuclear cross sections. Especially in case of dosimetrical reactions there is a request on precise validation. This paper presents SACS measured in the reference 252Cf(sf) neutron field for neutron dosimetry reactions to validate recently updated IRDFF-II library intended mainly for neutron metrology applications. It covers 46Ti(n,p)46Sc, 47Ti(n,p)47Sc, 48Ti(n,p)48Sc, 58Ni(n,p)58Co, 60Ni(n,p)60Co, 58Ni(n,2n)57Ni, 24Mg(n,p)24Na, 27Al(n,α)24Na and 63Cu(n,α)60Co threshold reactions. Measurement of 60Ni(n,p)60Co SACS is included in NEA's High Priority Nuclear Data Request List since existing data are discrepant. Spectral averaged cross sections were derived from experimentally determined reaction rates by gamma spectrometry using a same high-purity germanium detector to measure all irradiated samples. Measured spectrum-averaged cross sections agree very well within quoted uncertainties with those calculated using the IRDFF-II library. No other library achieves such good performance. Thus, the presented data support use of the cross sections of the mentioned reactions from IRDFF-II library.

• Klíčová slova
• (252)Cf, IRDFF-II, Spectral averaged cross sections,
• Publikační typ
• časopisecké články MeSH

Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and an in silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

• Klíčová slova
• High-resolution mass spectrometry, In silico spectral library, Liquid chromatography, Metabolite identification in Eisenia fetida and Lactuca sativa, Pharmaceuticals, Software prediction,
• MeSH
• chromatografie kapalinová metody   MeSH
• hmotnostní spektrometrie metody   MeSH
• látky znečišťující půdu analýza   metabolismus   MeSH
• léčivé přípravky metabolismus   chemie   analýza   MeSH
• Oligochaeta * metabolismus   chemie   MeSH
• počítačová simulace MeSH
• salát (hlávkový) * metabolismus   chemie   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• látky znečišťující půdu MeSH
• léčivé přípravky MeSH

Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.

• Klíčová slova
• Library cleaning, Mass spectrometry, Metabolomics, Metadata, Python Package,
• Publikační typ
• časopisecké články MeSH

Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs. To help bridge this gap and enable hundreds of stakeholders to collect more affordable soil data by leveraging a centralized open resource, the Soil Spectroscopy for Global Good initiative has created the Open Soil Spectral Library (OSSL). In this paper, we describe the procedures for collecting and harmonizing several SSLs that are incorporated into the OSSL, followed by exploratory analysis and predictive modeling. The results of 10-fold cross-validation with refitting show that, in general, mid-infrared (MIR)-based models are significantly more accurate than visible and near-infrared (VisNIR) or near-infrared (NIR) models. From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). Although many soil properties are well predicted, total sulfur, extractable sodium, and electrical conductivity performed poorly in all spectral regions, with some other extractable nutrients and physical soil properties also performing poorly in one or two spectral regions (VisNIR or NIR). Hence, the use of predictive models based solely on spectral variations has limitations. This study also presents and discusses several other open resources that were developed from the OSSL, aspects of opening data, current limitations, and future development. With this genuinely open science project, we hope that OSSL becomes a driver of the soil spectroscopy community to accelerate the pace of scientific discovery and innovation.

• MeSH
• algoritmy MeSH
• kalibrace MeSH
• monitorování životního prostředí metody   MeSH
• půda * chemie   MeSH
• strojové učení MeSH
• účast komunity MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• půda * MeSH

BACKGROUND: Cancer research often focuses on protein quantification in model cancer cell lines and cancer tissues. SWATH (sequential windowed acquisition of all theoretical fragment ion spectra), the state of the art method, enables the quantification of all proteins included in spectral library. Spectral library contains fragmentation patterns of each detectable protein in a sample. Thorough spectral library preparation will improve quantitation of low abundant proteins which usually play an important role in cancer. AIM: Our research is focused on the optimization of spectral library preparation aimed at maximizing the number of identified proteins in MCF-7 breast cancer cell line. First, we optimized the sample preparation prior entering the mass spectrometer. We examined the effects of lysis buffer composition, peptide dissolution protocol and the material of sample vial on the number of proteins identified in spectral library. Next, we optimized mass spectrometry (MS) method for spectral library data acquisition. CONCLUSION: Our thorough optimized protocol for spectral library building enabled the identification of 1,653 proteins (FDR < 1%) in 1 µg of MCF-7 lysate. This work contributed to the enhancement of protein coverage in SWATH digital biobanks which enable quantification of arbitrary protein from physically unavailable samples. In future, high quality spectral libraries could play a key role in preparing of patient proteome digital fingerprints.Key words: biomarker - mass spectrometry - proteomics - digital biobanking - SWATH - protein quantificationThis work was supported by the project MEYS - NPS I - LO1413.The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 7. 5. 2016Accepted: 9. 6. 2016.

• MeSH
• digitální knihovny * MeSH
• hmotnostní spektrometrie metody   MeSH
• lidé MeSH
• MFC-7 buňky MeSH
• proteom chemie   izolace a purifikace   MeSH
• proteomika metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• proteom MeSH

Spectrum-averaged cross sections (SACS) have been measured in the reference 252Cf(sf) neutron field for the following high-threshold (n,2n) neutron dosimetry reactions since they are especially important due to the high threshold which allows validation of upper parts of prompt fission neutron spectrum. This work includes 59Co(n,2n)58Co, 197Au(n,2n)196Au, 169Tm(n,2n)168Tm, 55Mn(n,2n)54Mn, 93Nb(n,2n)92 mNb and 89Y(n,2n)88Y and for the 59Co(n,p)59Fe threshold reactions. SACS were inferred from experimentally determined reaction rates by gamma spectrometry using a semiconductor high-purity germanium detector to measure irradiated samples. Measured reaction rates agree within quoted uncertainties with those calculated from the IRDFF-1.05 library, except for the reaction 55Mn(n,2n)54Mn, for which the measured value is underestimated by 16%. For this reaction the ENDF-B/VII.1 evaluation agrees with measured reaction rate within uncertainties.

• Klíčová slova
• (252)Cf, Cross section measurement, Nuclear data, Spectral averaged cross sections,
• Publikační typ
• časopisecké články MeSH

Renal cell carcinoma (RCC) represents 2.2% of all cancer incidences; however, prognostic or predictive RCC biomarkers at protein level are largely missing. To support proteomics research of localized and metastatic RCC, we introduce a new library of targeted mass spectrometry assays for accurate protein quantification in malignant and normal kidney tissue. Aliquots of 86 initially localized RCC, 75 metastatic RCC and 17 adjacent non-cancerous fresh frozen tissue lysates were trypsin digested, pooled, and fractionated using hydrophilic chromatography. The fractions were analyzed using LC-MS/MS on QExactive HF-X mass spectrometer in data-dependent acquisition (DDA) mode. A resulting spectral library contains 77,817 peptides representing 7960 protein groups (FDR = 1%). Further, we confirm applicability of this library on four RCC datasets measured in data-independent acquisition (DIA) mode, demonstrating a specific quantification of a substantially increased part of RCC proteome, depending on LC-MS/MS instrumentation. Impact of sample specificity of the library on the results of targeted DIA data extraction was demonstrated by parallel analyses of two datasets by two pan human libraries. The new RCC specific library has potential to contribute to better understanding the RCC development at molecular level, leading to new diagnostic and therapeutic targets.

• Klíčová slova
• assay library, data independent acquisition, mass spectrometry, proteomics, renal cell carcinoma,
• MeSH
• chromatografie kapalinová MeSH
• karcinom z renálních buněk * MeSH
• lidé MeSH
• nádory ledvin * MeSH
• proteom metabolismus   MeSH
• tandemová hmotnostní spektrometrie MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• proteom MeSH

The results of systematic evaluations of the spectrum-averaged cross section measurements performed in the spontaneous fission 252Cf neutron field are presented. The Following threshold reactions were investigated: 23Na(n,2n)22Na, 54Fe(n,p)54Mn, 54Fe(n,α) 51Cr, 27Al(n,p)27Mg, 27Al(n,α)24Na, 19F(n,2n)18F, 90Zr(n,2n)89Zr and 89Y(n,2n)88Y. The spectrum-averaged cross sections for 23Na(n,2n)22Na, 54Fe(n,α)51Cr and 89Y(n,2n)88Y reactions were measured for the first time. This quantity is compared with calculations carried with the IRDFF-v1.05 library. There is a notable disagreement exceeding uncertainties only for 54Fe(n,p)54Mn and 54Fe(n,α) 51Cr reactions. The spectrum-averaged cross sections were inferred from experimentally determined reaction rates. The experimental reaction rates were derived for irradiated samples from the Net Peak Areas measured using the semiconductor high purity germanium spectroscopy. The presented experimental data can be used to validate nuclear data libraries and reactions used in the practical reactor dosimetry and to specify high energy tail of the 252Cf neutron spectrum.

• Klíčová slova
• (252)Cf, Cross section measurement, Nuclear data, Spectral averaged cross sections,
• Publikační typ
• časopisecké články MeSH