Mass spectrometry is a widely used method to study molecules and processes in medicine, life sciences, chemistry, catalysis, and industrial product quality control, among many other applications. One of the main features of some mass spectrometry techniques is the extensive level of characterization (especially when coupled with chromatography and ion mobility methods, or a part of tandem mass spectrometry experiment) and a large amount of generated data per measurement. Terabyte scales can be easily reached with mass spectrometry studies. Consequently, mass spectrometry has faced the challenge of a high level of data disappearance. Researchers often neglect and then altogether lose access to the rich information mass spectrometry experiments could provide. With the development of machine learning methods, the opportunity arises to unlock the potential of these data, enabling previously inaccessible discoveries. The present perspective highlights reevaluation of mass spectrometry data analysis in the new generation of methods and describes significant challenges in the field, particularly related to problems involving the use of electrospray ionization. We argue that further applic
We compare the network of aggregated journal-journal citation relations provided by the Journal Citation Reports (JCR) 2012 of the Science and Social Science Citation Indexes (SCI and SSCI) with similar data based on Scopus 2012. First, global maps were developed for the two sets separately; sets of documents can then be compared using overlays to both maps. Using fuzzy-string matching and ISSN numbers, we were able to match 10,524 journal names between the two sets; that is, 96.4% of the 10,936 journals contained in JCR or 51.2% of the 20,554 journals covered by Scopus. Network analysis was then pursued on the set of journals shared between the two databases and the two sets of unique journals. Citations among the shared journals are more comprehensively covered in JCR than Scopus, so the network in JCR is denser and more connected than in Scopus. The ranking of shared journals in terms of indegree (that is, numbers of citing journals) or total citations is similar in both databases overall (Spearman's \r{ho} > 0.97), but some individual journals rank very differently. Journals that are unique to Scopus seem to be less important--they are citing shared journals rather than bein
Quantification of Ge in Si1-xGex structures (0.092<x<0.78) was carried by time-of-flight secondary ion mass spectrometry (TOF-SIMS) and electron-gas secondary neutral mass spectrometry (SNMS). A good linear correlation (R2>0.9997) of intensity ratios of GeCs2+/SiCs2+ and 74Ge-/30Si- secondary ions and post-ionized 70Ge+/28Si+ sputtered neutrals with Ge concentration was obtained. The calibration data were used for quantitative depth profiling of [10x(12.3 nm Si0.63Ge0.37/34 nm Si)] structures on Si. Satisfactory compliance of the quantified Ge concentration in SiGe layers with the data measured by high-resolution X-ray diffraction was obtained for both techniques. Both SIMS and SNMS experimental profiles were fitted using the Hofmann mixing-roughness-information depth (MRI) model. In case of TOF-SIMS the quality of the reconstruction was higher than for SNMS since not only the progressing roughening, but also crater effect and other processes unaccounted in the MRI simulation could have significant impact on plasma sputter depth profiling.
Rankings of scholarly journals based on citation data are often met with skepticism by the scientific community. Part of the skepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of authors. This paper focuses on analysis of the table of cross-citations among a selection of Statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care in order to avoid potential over-interpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's Research Assessment Exercise shows strong correlation at aggregate level between assessed research quality and journal citation `export scores' within the discipline of Statistics.
Weighing particles above MegaDalton mass range has been a persistent challenge in commercial mass spectrometry. Recently, nanoelectromechanical systems-based mass spectrometry (NEMS-MS) has shown remarkable performance in this mass range, especially with the advance of performing mass spectrometry under entirely atmospheric conditions. This advance reduces the overall complexity and cost, while improving the limit of detection. However, this technique required the tracking of two mechanical modes, and the accurate knowledge of mode shapes which may deviate from their ideal values especially due to air damping. Here, we used a NEMS architecture with a central platform, which enables the calculation of mass by single mode measurements. Experiments were conducted using polystyrene and gold nanoparticles to demonstrate the successful acquisition of mass spectra using a single mode, with improved areal capture efficiency. This advance represents a step forward in NEMS-MS, bringing it closer to becoming a practical application for mass sensing of nanoparticles.
This study examines the social media uptake of scientific journals on two different platforms - X and WeChat - by comparing the adoption of X among journals indexed in the Science Citation Index-Expanded (SCIE) with the adoption of WeChat among journals indexed in the Chinese Science Citation Database (CSCD). The findings reveal substantial differences in platform adoption and user engagement, shaped by local contexts. While only 22.7% of SCIE journals maintain an X account, 84.4% of CSCD journals have a WeChat official account. Journals in Life Sciences & Biomedicine lead in uptake on both platforms, whereas those in Technology and Physical Sciences show high WeChat uptake but comparatively lower presence on X. User engagement on both platforms is dominated by low-effort interactions rather than more conversational behaviors. Correlation analyses indicate weak-to-moderate relationships between bibliometric indicators and social media metrics, confirming that online engagement reflects a distinct dimension of journal impact, whether on an international or a local platform. These findings underscore the need for broader social media metric frameworks that incorporate locally dom
Mass spectrometry is the dominant technology in the field of proteomics, enabling high-throughput analysis of the protein content of complex biological samples. Due to the complexity of the instrumentation and resulting data, sophisticated computational methods are required for the processing and interpretation of acquired mass spectra. Machine learning has shown great promise to improve the analysis of mass spectrometry data, with numerous purpose-built methods for improving specific steps in the data acquisition and analysis pipeline reaching widespread adoption. Here, we propose unifying various spectrum prediction tasks under a single foundation model for mass spectra. To this end, we pre-train a spectrum encoder using de novo sequencing as a pre-training task. We then show that using these pre-trained spectrum representations improves our performance on the four downstream tasks of spectrum quality prediction, chimericity prediction, phosphorylation prediction, and glycosylation status prediction. Finally, we perform multi-task fine-tuning and find that this approach improves the performance on each task individually. Overall, our work demonstrates that a foundation model for
The identification of extraterrestrial life is one the most exciting and challenging endeavors in space research. The existence of extinct or extant life can be inferred from biogenic elements, isotopes, and molecules, but accurate and sensitive instruments are needed. In this whitepaper we show that Laser-based Mass Spectrometers are promising instrument for the in situ identification of atomic, isotopic, and molecular biosignatures. An overview of Laser ablation/Ionization Mass Spectrometry (LIMS) and Laser Desorption/Ionization Mass Spectrometry (LD-MS) instruments developed for space exploration is given. Their uses are discussed in the context of a Mars scenario and a Europa scenario. We show that Laser-based Mass Spectrometers are versatile and technologically mature instruments with many beneficial characteristics for the detection of life. Future planetary lander and rover missions should be encouraged to make use of Laser-based Mass Spectrometry instruments in their scientific payload.
Mass spectrometry is a widespread approach to work out what are the constituents of a material. Atoms and molecules are removed from the material and collected, and subsequently, a critical step is to infer their correct identities based from patterns formed in their mass-to-charge ratios and relative isotopic abundances. However, this identification step still mainly relies on individual user's expertise, making its standardization challenging, and hindering efficient data processing. Here, we introduce an approach that leverages modern machine learning technique to identify peak patterns in time-of-flight mass spectra within microseconds, outperforming human users without loss of accuracy. Our approach is cross-validated on mass spectra generated from different time-of-flight mass spectrometry(ToF-MS) techniques, offering the ToF-MS community an open-source, intelligent mass spectra analysis.
With upcoming sample return missions across the solar system and the increasing availability of mass spectrometry data, there is an urgent need for methods that analyze such data within the context of existing astrobiology literature and generate plausible hypotheses regarding the emergence of life on Earth. Hypothesis generation from mass spectrometry data is challenging due to factors such as environmental contaminants, the complexity of spectral peaks, and difficulties in cross-matching these peaks with prior studies. To address these challenges, we introduce AstroAgents, a large language model-based, multi-agent AI system for hypothesis generation from mass spectrometry data. AstroAgents is structured around eight collaborative agents: a data analyst, a planner, three domain scientists, an accumulator, a literature reviewer, and a critic. The system processes mass spectrometry data alongside user-provided research papers. The data analyst interprets the data, and the planner delegates specific segments to the scientist agents for in-depth exploration. The accumulator then collects and deduplicates the generated hypotheses, and the literature reviewer identifies relevant literat
Mass spectrometry imaging by Fourier transform ion cyclotron resonance yields hundreds of unique peaks, many of which cannot be resolved by lower performance mass spectrometers. The high mass accuracy and high mass resolving power allow confident identification of small molecules and lipids directly from biological tissue sections. Here, calibration strategies for Fourier transform ion cyclotron resonance mass spectrometry imaging were investigated. Sub parts-per-million mass accuracy is demonstrated over an entire tissue section. Ion abundance fluctuations are corrected for by addition of total and relative ion abundances for a root-mean-square error of 0.158 ppm on 16,764 peaks. A new approach for visualization of Fourier transform ion cyclotron resonance mass spectrometry imaging data at high resolution is presented. The Mosaic Data-cube provides a flexible means to visualize the entire mass range at a mass spectral bin width of 0.001 Dalton. The high resolution Mosaic Data-cube resolves spectral features not visible at lower bin widths, while retaining the high mass accuracy from the calibration methods discussed.
This paper is centered on some historical aspects of nuclear masses, and their relations to major discoveries. Besides nuclear reactions and decays, the heart of mass measurements lies in mass spectrometry, the early history of which will be reviewed first. I shall then give a short history of the mass unit which has not always been defined as one twelfth of the carbon-12 mass. When combining inertial masses from mass spectrometry with energy differences obtained in reactions and decays, the conversion factor between the two is essential. The history of the evaluation of the nuclear masses (actually atomic masses) is only slightly younger than that of the mass measurements themselves. In their modern form, mass evaluations can be traced back to 1955. Prior to 1955, several tables were established, the oldest one in 1935.
Fingerprint analysis is a ubiquitous tool for pattern recognition with applications spanning from geolocation and DNA analysis to facial recognition and forensic identification. Central to its utility is the ability to provide accurate identification without an a priori mathematical model for the pattern. We report a data-driven fingerprint approach for nanoelectromechanical systems mass spectrometry (NEMS-MS) that enables mass measurements of particles and molecules using complex, uncharacterized nanoelectromechanical devices of arbitrary specification. NEMS-MS is based on the frequency shifts of the NEMS vibrational modes induced by analyte adsorption. The sequence of frequency shifts constitutes a fingerprint of this adsorption, which is directly amenable to pattern matching. Two current requirements of NEMS-based mass spectrometry are: (1) a priori knowledge or measurement of the device mode-shapes, and (2) a mode-shape-based model that connects the induced modal frequency shifts to mass adsorption. This may not be possible for advanced NEMS with three-dimensional mode-shapes and nanometer-sized features. The advance reported here eliminates this impediment, thereby allowing de
Mass spectrometry of intact nanoparticles and viruses can serve as a potent characterization tool for material science and biophysics. Inaccessible by widespread commercial techniques, the mass of single nanoparticles and viruses (>10MDa) can be readily measured by NEMS (Nanoelectromechanical Systems) based Mass Spectrometry, where charged and isolated analyte particles are generated by Electrospray Ionization (ESI) in air and transported onto the NEMS resonator for capture and detection. However, the applicability of NEMS as a practical solution is hindered by their miniscule surface area, which results in poor limit-of-detection and low capture efficiency values. Another hindrance is the necessity to house the NEMS inside complex vacuum systems, which is required in part to focus analytes towards the miniscule detection surface of the NEMS. Here, we overcome both limitations by integrating an ion lens onto the NEMS chip. The ion lens is composed of a polymer layer, which charges up by receiving part of the ions incoming from the ESI tip and consequently starts to focus the analytes towards an open window aligned with the active area of the NEMS electrostatically. With this int
The knowledge of absolute fluxes of reactive species such as radicals or energetic ions to the surface is crucial for understanding the growth or etching of thin films. These species have due to their high reactivity very low densities and their detection is therefore a challenging task. Mass spectrometry is a very sensitive technique and it will be demonstrated that it is a good choice for the study of plasma chemistry. Mass spectrometry measures the plasma composition directly at the surface and is not limited by existence of accessible optical transitions. When properly designed and carefully calibrated mass spectrometry provides absolute densities of the measured species. It can even measure internally excited metastable species. Here, measurement of neutral species and positive ions generated in an atmospheric pressure plasmas jet operated with He, hexamethyldisiloxane and O2 will be presented.
Using the Scopus dataset (1996-2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained in the Journal Citation Reports (JCR) of the Institute of Scientific Information (ISI). Since the Scopus database contains a larger number of journals and covers also the humanities, one would expect richer maps. However, the matrix is in this case sparser than in the case of the ISI data. This is due to (i) the larger number of journals covered by Scopus and (ii) the historical record of citations older than ten years contained in the ISI database. When the data is highly structured, as in the case of large journals, the maps are comparable, although one may have to vary a threshold (because of the differences in densities). In the case of interdisciplinary journals and journals in the social sciences and humanities, the new database does not add a lot to what is possible with the ISI databases.
The common techniques to study protein-protein proximity in vivo are not well-adapted to the capabilities and the expertise of a standard proteomics laboratory, typically based on the use of mass spectrometry. With the aim of closing this gap, we have developed PUB-MS (for Proximity Utilizing Biotinylation and Mass Spectrometry), an approach to monitor protein-protein proximity, based on biotinylation of a protein fused to a biotin-acceptor peptide (BAP) by a biotin-ligase, BirA, fused to its interaction partner. The biotinylation status of the BAP can be further detected by either Western analysis or mass spectrometry. The BAP sequence was redesigned for easy monitoring of the biotinylation status by LC-MS/MS. In several experimental models, we demonstrate that the biotinylation in vivo is specifically enhanced when the BAP- and BirA- fused proteins are in proximity to each other. The advantage of mass spectrometry is demonstrated by using BAPs with different sequences in a single experiment (allowing multiplex analysis) and by the use of stable isotopes. Finally, we show that our methodology can be also used to study a specific subfraction of a protein of interest that was in pro
We demonstrate a Wiley-McClaren Time of Flight Mass Spectrometer modified to allow direct extraction of ions from a laser-induced plasma. Unlike many other methods that utilize mass spectrometry to investigate laser-induced plasmas, no collisional cooling or further ionization of the plasma is required prior to acceleration, allowing measurements of the plasma ion composition to be obtained directly. Furthermore, we show using the laser ablation of gadolinium as an example that we are able to obtain the translational energy distribution of the plasma directly and infer information about the relative composition of ions within different regions of the plasma plume. The approach is then applied to laser ablation of a uranium sample as a step toward probing the chemistry under conditions relevant to a nuclear fireball for nuclear forensics applications.
While studying nucleic acids to reveal the weak interactions responsible for their three-dimensional structure and for their interactions with drugs, we also contributed to the field of biomolecular mass spectrometry, both in terms of fundamental understanding and with new methodological developments. A first goal was to develop mass spectrometry approaches to detect non-covalent interactions between antitumor drugs and their DNA target. Twenty years ago, our attention turned towards specific DNA structures such as the G-quadruplex (a structure formed by guanine-rich strands). Mass spectrometry allows to discern which molecules interact with one another by measuring the masses of the complexes, and quantity the affinities by measuring their abundance. The most important findings came from unexpected masses. For example, we showed the formation of higher- or lower-order structures by G-quadruplexes used in traditional biophysical assays. We can also derive complete thermodynamic and kinetic description of G-quadruplex folding pathways by measuring cation binding, one at a time. Getting quantitative information required accounting for nonspecific adduct formation and for the response
The highest precision in direct mass measurements is obtained with Penning trap mass spectrometry. Most experiments use the interconversion of the magnetron and cyclotron motional modes of the stored ion due to excitation by external radiofrequency-quadrupole fields. In this work a new excitation scheme, Ramsey's method of time-separated oscillatory fields, has been successfully tested. It has been shown to reduce significantly the uncertainty in the determination of the cyclotron frequency and thus of the ion mass of interest. The theoretical description of the ion motion excited with Ramsey's method in a Penning trap and subsequently the calculation of the resonance line shapes for different excitation times, pulse structures, and detunings of the quadrupole field has been carried out in a quantum mechanical framework and is discussed in detail in the preceding article in this journal by M. Kretzschmar. Here, the new excitation technique has been applied with the ISOLTRAP mass spectrometer at ISOLDE/CERN for mass measurements on stable as well as short-lived nuclides. The experimental resonances are in agreement with the theoretical predictions and a precision gain close to a fac