Intense Ion Research Articles

Can fragment ion intensity be used for fatty acid sn-position determination of food phospholipids?

Can fragment ion intensity be used for fatty acid sn-position determination of food phospholipids?

Accurate determination of matrix composition in Cd x Zn 1 − x O semiconductor material using MS-SIMS and ToF-SIMS methods

Abstract This study focuses on the method for determining the exact composition for Cd x Zn 1 − x O semiconducting material using secondary ion mass spectrometry. The calibration curve method is employed to establish a quantitative relationship between the intensity of secondary ions and the concentrations of elements in Cd x Zn 1 − x O thin films. Additionally, the study compares the relative sensitivity factors with the calibration curve method for determining the value of x in Cd x Zn 1 − x O . A comparison between the performances of Time of Flight and Magnetic Sector SIMS in analyzing Cd x Zn 1 − x O thin films is also presented. This approach aims to enhance the accuracy and reliability of quantitative analysis in SIMS for Cd x Zn 1 − x O thin films.

Effects of Hydrogen Dissociation During Gas Flooding on Formation of Metal Hydride Cluster Ions in Secondary Ion Mass Spectrometry

The application of hydrogen flooding was recently shown to be a simple and effective approach for improved layer differentiation and interface determination during secondary ion mass spectrometry (SIMS) depth profiling of thin films, as well as an approach with potential in the field of quantitative SIMS analyses. To study the effects of hydrogen further, flooding of H2 molecules was compared to reactions with atomic H on samples of pure metals and their alloys. H2 was introduced into the analytical chamber via a capillary, which was heated to approximately 2200 K to achieve dissociation. Dissociation of H2 up to 30% resulted in a significant increase in the intensity of the metal hydride cluster secondary ions originating from the metallic samples. Comparison of the time scales of possible processes provided insight into the mechanism of hydride cluster secondary ion formation. Cluster ions presumably form during the recombination of the atoms and molecules from the sample and atoms and molecules adsorbed from the gas. This process occurs on the surface or just above it during the sputtering process. These findings coincide with those of previous mechanistic and computational studies.

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models.

Temperature Changes in Luminescence of Mixed Complexes of Terbium and Samarium with Organic Ligands Based on 2,2-bipyridyldicarboxamides

Solutions in acetonitrile of three mixed complexes of rare earth elements (terbium and samarium) with organic ligands with various pyridine substituents were studied in this work. The ratios of ligands and metals in the resulting complexes were determined, and the stability constants of samarium complexes were calculated using the spectrophotometric titration method. Measurements of absorption, emission and excitation spectra of luminescence, luminescence kinetics of solutions of mixed complexes of rare earth elements with an excess of metal relative to the ligand were carried out at various temperatures in the range 298–328 K. An increase of luminescence intensity of a samarium ion in complex upon heating has been discovered for the first time. The dependences of the luminescence quantum yield and lifetime of mixed complexes on temperature were obtained. A thermometric parameter — the ratio of the integral luminescence intensities of samarium and terbium ions — was proposed, and the temperature sensitivity coefficient of this parameter was determined for different complexes.

Bias disk boost technique for pulsed-operation electron cyclotron resonance ion sources

A simple, effective technique to increase the intensity of multiply charged ions has been developed for pulsed-operation electron cyclotron resonance ion sources (ECRISs). The technique is realized simply by applying an additional boost voltage of about −1 kV to a negative constant voltage on the bias disk. The technique can be applied to general ECRISs by adding electric devices to the bias disk circuit, such as a high-voltage power supply, a fast high-voltage switch, and a diode. The effect of the technique depends on the ion species, and we obtained a maximum ion intensity increase of 66% for O6+ compared with the conventional bias disk method. In particular, the technique can be applied to the existing pulsed-operation ECRISs used at a heavy-ion cancer therapy facility where multi-ion treatment with multiply charged oxygen and neon ions is planned to be introduced.

Mobile Phase Contaminants Affect Neutral Lipid Analysis in LC-MS-Based Lipidomics Studies.

Lipidomics is a well-established field, enabled by modern liquid chromatography mass spectrometry (LC-MS) technology, rapidly generating large amounts of data. Lipid extracts derived from biological samples are complex, and most spectral features in LC-MS lipidomics data sets remain unidentified. In-depth analyses of commercial triacylglycerol, diacylglycerol, and cholesterol ester standards revealed the expected ammoniated and sodiated ions as well as five additional unidentified higher mass peaks with relatively high intensities. The identities and origin of these unknown peaks were investigated by modifying the chromatographic mobile-phase components and LC-MS source parameters. Tandem MS (MS/MS) of each unknown adduct peak yielded no lipid structural information, producing only an intense ion of the adducted species. The unknown adducts were identified as low-mass contaminants originating from methanol and isopropanol in the mobile phase. Each contaminant was determined to be an alkylated amine species using their monoisotopic masses to calculate molecular formulas. Analysis of bovine liver extract identified 33 neutral lipids with an additional 73 alkyl amine adducts. Analysis of LC-MS-grade methanol and isopropanol from different vendors revealed substantial alkylated amine contamination in one out of three different brands that were tested. Substituting solvents for ones with lower levels of alkyl amine contamination increased lipid annotations by 36.5% or 27.4%, depending on the vendor, and resulted in >2.5-fold increases in peak area for neutral lipid species without affecting polar lipid analysis. These findings demonstrate the importance of solvent selection and disclosure for lipidomics protocols and highlight some of the major challenges when comparing data between experiments.

Transforming waste into multifunctional nanomaterials: Mg-doped carbon dots from cow dung for Y(III) detection and biomedical applications

Rare earth metal Yttrium (Y3+) plays a vital role in many electronic devices however, discarding these devices eventually contaminates the environmental sources. Herein, we have developed a Mg-doped carbon dots (M-CDs) as a fluorescent probe for selective and sensitive determination of Y3+ in water bodies. The M-CDs having maximum emission at 420 nm upon 310 nm excitation with 20 % quantum yield and which was synthesized from upcycling of agricultural waste i.e., cow dung by simple carbonization followed by hydrothermal method. M-CDs were confirmed using different analytical and characterization techniques as well as stable in different pH and ionic strength solutions. The M-CDs was highly selective towards Y3+ ions over different metal ions with significant blue shift. This fluorescent probe performs a good linear relationship between the different concentrations of Y3+ ion and fluorescence intensity (R2 = 0.99) within the range of 0.2 to 20 μg/mL with a detection limit of 0.019 µg/mL. The study indicates quenching of Y3+ was result of dynamic quenching and the Inner Filter Effect (IFE) effect. Also, the cytotoxicity of M-CDs was checked via CAM assay and significant growth in blood vascularization with healthy growth of chick embryo confirmed the M-CDs were biocompatible. The nontoxic M-CDs was employed for MCF-7 breast cancer cell imaging which gives bright blue fluoresce under UV light excitation. Further, aiming to a circular economy approach the residual carbon remaining after hydrothermal was used as reactivated carbon for the abatement of environmental pollutants. The sustainable, cost-effective and agricultural waste-derived Mg-doped CDs have potential applications in analytical, environmental, forensic as well as biomedical fields.

Plasmoids and Magnetic Field Dipolarizations During Juno's First 47 Orbits: Is Ion Acceleration Always Observed in the Dipolarizations?

AbstractPlasmoids and magnetic field dipolarizations are reconnection‐related phenomena often resulting in reconfiguration of the magnetic field and energetic particle acceleration in planetary magnetotail. Building on the work of Blöcker et al. (2023) (10.1029/2023JA031312), we selected seven specific events from their magnetic field dipolarization analysis, each exhibiting distinct ion dynamics during the time interval of the magnetic field dipolarizations. To gain further insights into the understanding why certain events were associated with ion intensity variations while others were not, we analyzed plasma moments, specifically ion flow velocity and density, for these selected events. Our findings revealed that certain magnetic field dipolarizations within our database exhibit sub‐Alfvénic flows and lack the properties typically associated with reconnection‐related magnetic field dipolarizations. These magnetic field dipolarizations also do not accelerate ions. Furthermore, we present a survey of Jovian plasmoids and magnetic field dipolarizations during the first 47 orbits of Juno. Applying Juno magnetic field data, we identified 119 magnetic field dipolarizations and 94 plasmoids within a local time range of 18:00–06:00. The majority of plasmoids were detected in the predawn sector, whereas magnetic field dipolarizations were observed closer to Jupiter and were not limited to a specific local time. Combining the statistics of plasmoids and dipolarizations is useful for contextualizing them within the framework of reconnection.

Sputtering of targets in high-intensity heavy-ion beam experiments

Based on available models and experimental data, the sputtering of target atoms in long-term experiments with intense heavy ion (HI) beams has been considered. The experiments on the synthesis of superheavy nuclei (SHN), which are carried out in laboratories around the world, are examples of such experiments encountering the target atoms sputtering in specific conditions. Rotating wheels with a relatively large target annulus area are used in these experiments to reduce the temperature and radiation loads on the target. Large areas of rotating targets allow one to reduce the sputtering yields of target atoms significantly. The question arises about the reliability of these yields in experiments on the synthesis of SHN with Z>118. These nuclei can be produced with extremely low cross sections, requiring HI beam doses exceeding 10 20 particles passed through the target to observe several decay events of the thus synthesized SHN. Estimates based on approximations and simulations considered in this work are presented and compared with some data on actinide target sputtering obtained in experiments performed on the synthesis of SHN.

Tracking Detectors in Low-Energy Nuclear Physics: An Overview

Advances in accelerator technology have enabled the use of exotic and intense radioactive ion beams. Enhancements to tracking detectors are necessary to accommodate increased particle rates. Recent advancements in digital electronics have led to the construction or planning of next-generation detectors. To conduct kinematically complete measurements, it is essential to track and detect all particles produced as a result of the reaction. Furthermore, the need for high-precision physics experiments has led to significant developments in the detector field. In recent years, highly efficient and highly granular tracking detectors have been developed. These detectors significantly enhance the physics programme at dedicated facilities. An overview of charged-particle tracking detectors in low-energy nuclear physics will be given.

PyMS-Vis, an Open-Source Python Application for Visualizing and Investigating Deconvoluted Top-Down Mass Spectrometric Experiments: A Histone Proteoform Case Study.

We report the development of an open-source Python application that provides quantitative and qualitative information from deconvoluted liquid-chromatography top-down mass spectrometry (LC-TDMS) data sets. This simple-to-use program allows users to search masses-of-interest across multiple LC-TDMS runs and provides visualization of their ion intensities and elution characteristics while quantifying their abundances relative to one another. Focusing on proteoform-rich histone proteins from the green microalga Chlamydomonas reinhardtii, we were able to quantify proteoform abundances across different growth conditions and replicates in minutes instead of hours typically needed for manual spreadsheet-based analysis. This resulted in extending previously published qualitive observations on Chlamydomonas histone proteoforms into quantitative ones, leading to an exciting new discovery on alpha-amino termini processing exclusive to histone H2A family members. Lastly, the script was intentionally developed with readability and customizability in mind so that fellow mass spectrometrists can modify the code to suit their lab-specific needs.

Effect of Terminal Phosphate Groups on Collisional Dissociation of RNA Oligonucleotide Anions.

The increasing need for mass spectrometric analysis of RNA molecules calls for a better understanding of their gas-phase fragmentation behaviors. In this study, we investigate the effect of terminal phosphate groups on the fragmentation spectra of RNA oligonucleotides (oligos) using high-resolution mass spectrometry (MS). Negative-ion mode collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) were carried out on RNA oligos containing a terminal phosphate group on either end, both ends, or neither end. We find that terminal phosphate groups affect the fragmentation behavior of RNA oligos in a way that is dependent on the precursor charge state and the oligo length. Specifically, for precursor ions of RNA oligos of the same sequence, those with 5'- or 3'-phosphate, or both, have a higher charge state distribution and lose the phosphate group(s) in the form of a neutral (H3PO4 or HPO3) or an anion ([H2PO4]- or [PO3]-) upon CID or HCD. Such a neutral or charged loss is most conspicuous for precursor ions of an intermediate charge state, e.g., 3- for 4-nt oligos or 4- and 5- for 8-nt oligos. This decreases the intensity of sequencing ions (a-, a-B, b-, c-, d-, w-, x-, y-, z-ions) and hence is unfavorable for sequencing by CID or HCD. Removal of terminal phosphate groups by calf intestinal alkaline phosphatase improved MS analysis of RNA oligos. Additionally, the intensity of a fragment ion at m/z 158.925, which we identified as a dehydrated pyrophosphate anion ([HP2O6]-), is markedly increased by the presence of a terminal phosphate group. These findings expand the knowledge base necessary for software development for MS analysis of RNA.

Spatial Mapping of Bioactive Metabolites in the Roots of Three Bupleurum Species by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Bupleurum is a kind of medicinal plant that has made a great contribution to human health because of the presence of bioactive metabolites: Bupleurum saikosaponins and flavonoids. Despite their importance, it has been a challenge to visually characterize the spatial distribution of these metabolites in situ within the plant tissue, which is essential for assessing the quality of Bupleurum. The development of a new technology to identify and evaluate the quality of medicinal plants is therefore necessary. Here, the spatial distribution and quality characteristics of metabolites of three Bupleurum species: Bupleurum smithii (BS), Bupleurum marginatum var. stenophyllum (BM), and Bupleurum chinense (BC) were characterized by Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Twenty-nine metabolites, including saikosaponins, non-saikosaponins, and compounds from the saikosaponin synthesis pathway, were characterized. Some of these were successfully localized and visualized in the transverse section of roots. In these Bupleurum species, twelve saikosaponins, five non-saikosaponins, and five saikosaponin synthesis pathway compounds were detected. Twenty-two major influencing components, which exhibit higher ion intensities in higher quality samples, were identified as potential quality markers of Bupleurum. The final outcome indicates that BC has superior quality compared to BS and BM. MALDI-MSI has effectively distinguished the quality of these Bupleurum species, providing an intuitive and effective marker for the quality control of medicinal plants.

Development of an integrated strategy for comprehensive characterization of Sinomenii Caulis extract and metabolites in rats based on UPLC/Q-TOF-MS

Sinomenii Caulis (SC), a commonly used traditional Chinese medicine for its therapeutic effects on rheumatoid arthritis, contains rich chemical components. At present, most studies mainly focus on sinomenine, with little research on other alkaloids. In this study, a comprehensive profile of compounds in SC extract, and biological samples of rats (including bile, urine, feces, and plasma) after oral administration of SC extract was conducted via ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The fragmentation patterns and potential biotransformation pathways of six main types of alkaloids in SC were summarized, and the corresponding characteristic product ions, relative ion intensity, and neutral losses were obtained to achieve rapid classification and identification of complex components of SC from in vitro to in vivo. As a result, a total of 114 alkaloid compounds were identified, including 12 benzyl alkaloids, 4 isoquinolone alkaloids, 32 aporphine alkaloids, 28 protoberberine alkaloids, 34 morphinan alkaloids and 4 organic amine alkaloids. After administration of SC extract to rats, a total of 324 prototypes and metabolites were identified from rat plasma, urine, feces and bile, including 81 aporphines, 95 protoberberines, 117 morphinans and 31 benzylisoquinolines. The main types of metabolites were demethylation, hydrogenation, dehydrogenation, aldehydation, oxidation, methylation, sulfate esterification, glucuronidation, glucose conjugation, glycine conjugation, acetylation, and dihydroxylation. In summary, this integrated strategy provides an additional approach for the incomplete identification caused by compound diversity and low abundance, laying the foundation for the discovery of new bioactive compounds of SC against rheumatoid arthritis.

A novel single near-infrared luminescence of negative thermal quenching materials for optical temperature measurement

In recent years, upconversion (UC) luminescence has gained attention due to its unique optical properties, and the thermal response spectral characteristics of these materials have been widely utilized in various fields including temperature sensing and biomedical research. However, the photoluminescence (PL) intensity of most rare earth ions doped phosphors decreases with increasing temperature, and the visible fluorescence emission penetration is still limited. In the work, the pure phase of Yb3+ and Er3+ ions co-doped Sc2Mo3O12 was successfully prepared. The Sc2Mo3O12: Yb3+, Er3+ sample showed a single emission of UC near-infrared (NIR) light. The optimum doping concentrations of 0.2 for Yb3+ ions and 0.01 for Er3+ ions were achieved. The possible upconversion luminescence (UCL) mechanism was investigated by analysing the UCL spectra, the down-shift (DS) excitation and emission spectra of Sc2Mo3O12: Yb3+, Er3+ phosphor. The excitation path of NIR emission is mainly through Er3+ from 2H11/2 to 4I9/2 energy level. What's more, the temperature-dependent near-infrared UCL properties of sample is explored in the temperature range from 323 K to 673 K. The enhancement of upconversion luminescence intensity shows a linear relationship with increasing temperature. The study paves a new way for non-contact optical temperature measurement with single near-infrared UCL emission.

Novel hollow-electrode glow discharge mass spectrometry for the quantitative analysis of protein content in food.

Protein content in food is an important indicator of nutritional value and food safety. Therefore, it is of great significance to accurately detect protein content in food. In this work, a combustion furnace and novel hollow-electrode glow discharge ion source-quadrupole mass spectrometry (HGD-MS) were designed, which were used to construct a "combustion furnace + mass spectrometry" experimental platform to detect the protein content in food. Five food standard samples were selected for the analysis. The food samples were combusted in the combustion furnace at a high temperature (1300 °C) in an oxygen-rich environment. The gas products were passed into the novel hollow electrode glow discharge ion source-quadrupole mass spectrometer. A standard curve of y = 635.06x + 11 082, R2 = 0.9994 was plotted by detecting the NO+ ion intensity at a relative standard deviation (RSD) of 1.8% to 5.7%. Using the same method, food samples no. 6 and 7 were combusted and NO+ ion intensity was measured to verify the accuracy of the quantitation curve. Subsequently, the protein content was determined using a nitrogen-to-protein conversion factor of 6.25. This method provides a rapid, accurate, and environmentally friendly approach for determining protein content in food.

Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer.

Chemical exposures may impact human metabolism and contribute to the etiology of neurodegenerative disorders like Alzheimer's Disease (AD). Identifying these small metabolites involves matching experimental spectra to reference spectra in databases. However, environmental chemicals or physiologically active metabolites are usually present at low concentrations in human specimens. The presence of noise ions can significantly degrade spectral quality, leading to false negatives and reduced identification rates. In response to this challenge, the Spectral Denoising algorithm removes both chemical and electronic noise. Spectral Denoising outperformed alternative methods in benchmarking studies on 240 tested metabolites. It improved high confident compound identifications at an average 35-fold lower concentrations than previously achievable. Spectral Denoising proved highly robust against varying levels of both chemical and electronic noise even with >150-fold higher intensity of noise ions than true fragment ions. For human plasma samples of AD patients that were analyzed on the Orbitrap Astral mass spectrometer, Denoising Search detected 2.3-fold more annotated compounds compared to the Exploris 240 Orbitrap instrument, including drug metabolites, household and industrial chemicals, and pesticides. This combination of advanced instrumentation with a superior denoising algorithm opens the door for precision medicine in exposome research.

Monitoring Epoxidized Soybean Oil Degradation Using Liquid Chromatography-Mass Spectrometry and In Silico Spectral Libraries.

Epoxidized soybean oil (ESO) is routinely used as a bioderived plasticizer and stabilizer in polyvinyl chloride (PVC), as it prolongs material integrity during dehydrochlorination. During this process, the epoxide moieties of ESO are progressively converted to chlorohydrins, which amplify ESO's inherent structural complexity. Past characterization efforts utilized separation-mass spectrometry (MS) analysis of the hydrolyzed acyl chains to simplify the complexity. However, this approach significantly increases the complexity of sample preparation and cannot directly monitor the chlorination of individual ESO species during aging. Here, we present a comprehensive LC-MS/MS data acquisition and in silico spectral library identification workflow optimized for intact ESO byproduct analysis. Detailed MS/MS fragmentation rules derived from synthesized standards were coupled with improved fragment ion intensity modeling capabilities to generate a high-fidelity spectral library for rapid ESO byproduct identification. Identification confidence was further bolstered by using retention time modeling to filter spurious MS/MS matches. Finally, we paired this informatic approach with an optimized extraction procedure and reversed-phase separation to generate a detailed timeline of more than 400 ESO species and byproducts during PVC thermal aging. These developments significantly improve our ability to detect, characterize, and understand ESO degradation in complex PVC formulations with new levels of molecular resolution.

Understanding proteome quantification in an interactive learning module on Google Cloud Platform.

This manuscript describes the development of a resource module that is part of a learning platform named 'NIGMS Sandbox for Cloud-based Learning' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on protein quantification in an interactive format that uses appropriate cloud resources for data access and analyses. Quantitative proteomics is a rapidly growing discipline due to the cutting-edge technologies of high resolution mass spectrometry. There are many data types to consider for proteome quantification including data dependent acquisition, data independent acquisition, multiplexing with Tandem Mass Tag reporter ions, spectral counts, and more. As part of the NIH NIGMS Sandbox effort, we developed a learning module to introduce students to mass spectrometry terminology, normalization methods, statistical designs, and basics of R programming. By utilizing the Google Cloud environment, the learning module is easily accessible without the need for complex installation procedures. The proteome quantification module demonstrates the analysis using a provided TMT10plex data set using MS3 reporter ion intensity quantitative values in a Jupyter notebook with an R kernel. The learning module begins with the raw intensities, performs normalization, and differential abundance analysis using limma models, and is designed for researchers with a basic understanding of mass spectrometry and R programming language. Learners walk away with a better understanding of how to navigate Google Cloud Platform for proteomic research, and with the basics of mass spectrometry data analysis at the command line. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.