Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

IsoForma: An R Package for Quantifying and Visualizing Positional Isomers in Top-Down LC-MS/MS Data

Proteoforms, the different forms of a protein with sequence variations including post-translational modifications (PTMs), execute vital functions in biological systems, such as cell signaling and epigenetic regulation. Advances in top-down mass spectrometry (MS) technology have permitted the direct characterization of intact proteoforms and their exact number of modification sites, allowing for the relative quantification of positional isomers (PI). Protein positional isomers refer to a set of proteoforms with identical total mass and set of modifications, but varying PTM site combinations. The relative abundance of PI can be estimated by matching proteoform-specific fragment ions to top-down tandem MS (MS2) data to localize and quantify modifications. However, the current approaches heavily rely on manual annotation. Here, we present IsoForma, an open-source R package for the relative quantification of PI within a single tool. Benchmarking IsoForma's performance against two existing workflows produced comparable results and improvements in speed. Overall, IsoForma provides a streamlined process for quantifying PI, reduces the analysis time, and offers an essential framework for developing customized proteoform analysis workflows. The software is open source and available at https://github.com/EMSL-Computing/isoforma-lib.

Mapping microhabitats of lignocellulose decomposition by a microbial consortium

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

Metabolomic, photoprotective, and photosynthetic acclimatory responses to post-flowering drought in sorghum

Climate change is globally affecting rainfall patterns, necessitating the improvement of drought tolerance in crops. Sorghum bicolor is a relatively drought-tolerant cereal. Functional stay-green sorghum genotypes can maintain green leaf area and efficient grain filling during terminal post-flowering water deprivation, a period of ~10 weeks. To obtain molecular insights into these characteristics, two drought-tolerant genotypes, BTx642 and RTx430, were grown in replicated control and terminal post-flowering drought field plots in California's Central Valley. Photosynthetic, photoprotective, and water dynamics traits were quantified and correlated with metabolomic data collected from leaves, stems, and roots at multiple timepoints during control and drought conditions. Physiological and metabolomic data were then compared to longitudinal RNA sequencing data collected from these two genotypes. The unique metabolic and transcriptomic response to post-flowering drought in sorghum supports a role for the metabolite galactinol in controlling photosynthetic activity through regulating stomatal closure in post-flowering drought. Additionally, in the functional stay-green genotype BTx642, photoprotective responses were specifically induced in post-flowering drought, supporting a role for photoprotection in the molecular response associated with the functional stay-green trait. From these insights, new pathways are identified that can be targeted to maximize yields under growth conditions with limited water.

mzapy: An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format

Analysis of ion mobility spectrometry (IMS) data has been challenging and limited the full utility of these measurements. Unlike liquid chromatography-mass spectrometry, where a plethora of tools with well-established algorithms exist, the incorporation of the additional IMS dimension requires upgrading existing computational pipelines and developing new algorithms to fully exploit the advantages of the technology. We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of core libraries in popular programming languages with standard mass spectrometry utilities will facilitate fast software development and broader adoption of the format. To this end, we present a Python package, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format, especially for complex data containing ion mobility spectrometry dimension. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python and having minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multiomics domain. The mzapy package is free and open-source, includes comprehensive documentation, and is structured to support future extension to meet the evolving needs of the MS community. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

LipidOz enables automated elucidation of lipid carbon-carbon double bond positions from ozone-induced dissociation mass spectrometry data

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich spectra challenges existing data storage and access technologies, therefore precluding informatics advancements. We present MZA (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed of a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and cross-programming language access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable, example MS-data and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

Online Hydrophilic Interaction Chromatography (HILIC) Enhanced Top-Down Mass Spectrometry Characterization of the SARS-CoV-2 Spike Receptor-Binding Domain

SARS-CoV-2 cellular infection is mediated by the heavily glycosylated spike protein. Recombinant versions of the spike protein and the receptor-binding domain (RBD) are necessary for seropositivity assays and can potentially serve as vaccines against viral infection. RBD plays key roles in the spike protein's structure and function, and thus, comprehensive characterization of recombinant RBD is critically important for biopharmaceutical applications. Liquid chromatography coupled to mass spectrometry has been widely used to characterize post-translational modifications in proteins, including glycosylation. Most studies of RBDs were performed at the proteolytic peptide (bottom-up proteomics) or released glycan level because of the technical challenges in resolving highly heterogeneous glycans at the intact protein level. Herein, we evaluated several online separation techniques: (1) C2 reverse-phase liquid chromatography (RPLC), (2) capillary zone electrophoresis (CZE), and (3) acrylamide-based monolithic hydrophilic interaction chromatography (HILIC) to separate intact recombinant RBDs with varying combinations of glycosylations (glycoforms) for top-down mass spectrometry (MS). Within the conditions we explored, the HILIC method was superior to RPLC and CZE at separating RBD glycoforms, which differ significantly in neutral glycan groups. In addition, our top-down analysis readily captured unexpected modifications (e.g., cysteinylation and N-terminal sequence variation) and low abundance, heavily glycosylated proteoforms that may be missed by using glycopeptide data alone. The HILIC top-down MS platform holds great potential in resolving heterogeneous glycoproteins for facile comparison of biosimilars in quality control applications.

Effectiveness of a decision aid for patients with knee osteoarthritis: a randomized controlled trial

OBJECTIVE

To assess the effectiveness of a Patient Decision Aid (PtDA) for knee osteoarthritis.

METHOD

Randomized controlled trial, in which 193 patients were allocated to the PtDA or usual care. Outcome measures were the Decisional Conflict Scale (DCS), knowledge of osteoarthritis and arthroplasty, satisfaction with the decision-making process (SDMP) and treatment preference, assessed immediately after the intervention. At 6 months, the same measures were applied in non-operated patients, whereas those who underwent arthroplasty completed the SDMP and the Decisional Regret Scale (DRS).

RESULTS

The PtDA produced a significant immediate improvement of decisional conflict (MD = -11.65, 95%CI: -14.93, -8.37), objective knowledge (MD = 10.37, 99%IC: 3.15, 17.70) and satisfaction (MD = 6.77, 99%CI: 1.19, 12.34), and a different distribution of preferences (χ² = 8.74, p = 0.033). Patients with less than secondary education obtained a stronger effect on decisional conflict (p = 0.015 for the interaction) but weaker for knowledge (p = 0.051). At 6 months, there were no significant differences in any variable, including the rate of total knee replacement. Operated patients showed a low level of regret, which was not affected by the intervention.

CONCLUSION

The PtDA is effective immediately after its application, but it shows no effects in the medium-term. Future research should investigate which subgroups of patients could benefit more from this intervention, as well as the longitudinal evolution of decision-related psychological variables.

A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

AutoCCS: Automated collision cross section calculation software for ion mobility spectrometry-mass spectrometry

MOTIVATION

Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion's collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required.

RESULTS

We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: 1) stepped-field methods for drift tube-based IMS (DTIMS), 2) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and 3) non-linear calibration methods for traveling wave based-IMS (TWIMS) in Waters Synapt and Structures for Lossless Ion Manipulations (SLIM). We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes, and collision gases, without requiring manual processing.

AVAILABILITY

https://github.com/PNNL-Comp-Mass-Spec/AutoCCS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of LC-MS data is constrained by proteomics visualization software designed for particular workflows or vendor-specific tools without open-source code. We built PSpecteR, an open-source and interactive R Shiny web application for visualization of LC-MS data, with support for several steps of proteomics data processing, including reading various mass spectrometry files, running open-source database search engines, labeling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open-source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing/pspecter) is available for easy local installation.

Evaluation of Waveform Profiles for Traveling Wave Ion Mobility Separations in Structures for Lossless Ion Manipulations

Structures for lossless ion manipulations (SLIM) have recently enabled a powerful implementation of traveling wave ion mobility spectrometry (TWIMS) for ultrahigh resolution separations; however, experimental parameters have not been optimized, and potential significant gains may be feasible. Most TWIMS separations have utilized square-shaped waveforms applied by time-dependent voltage stepping across repeating sets of electrodes, but alternative waveforms may provide further improvements to resolution. Here, we characterize five waveforms (including square and sine) in terms of their transmission efficiency, IMS resolution, and resolving power, and explore the effects of TW amplitude and speed on the performance of each. We found, consistent with previous work, separations were generally improved with higher TW amplitudes, moderately improved by lower speeds (limited by ion "surfing" with the waves), and found decreases in signal intensity at the extremes of operating conditions. The triangle and asymmetric "ramp forward" shaped profiles were found to provide modestly greater resolution and resolving power, an observation we tentatively attribute to their relatively uniform fields and minimal low-field regions.

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

AB0906 PREVALENCE OF HYPOVITAMINOSIS D IN DIAGNOSTIC PATIENTS OF BREAST NEOPLASIA IS GREATER THAN EXPECTED FOR THE GENERAL POPULATION? SERIES OF 200 DIAGNOSTIC PATIENTS OF BREAST NEOPLASIA IN A TERTIARY HOSPITAL INITIATING TREATMENT WITH AROMATASE INHIBITORS

Background:

In our population the prevalence of hypovitaminosis D is high. A recent cross-sectional observational study conducted in Spain shows that 63% of postmenopausal women who receive osteoporosis (OP) therapy and 76% who do not receive treatment had 25 (OH) D levels below 30 ng / mL1.

The latest studies show a relationship between hypovitaminosis D and the development of systemic inflammatory and tumor diseases, determined by the presence of receptors in various tissues, including breast.

Objectives:

To determine which levels of serum 25 (OH) D, and secondarily calcium, phosphorus, PTH and CTX, present 200 patients diagnosed with breast cancer and taking hormonal treatment, referred to a monographic OP consultation of a tertiary hospital for the assessment of their bone metabolism, and if these values differ from what is expected for the general population.

Methods:

Retrospective cross-sectional study of 200 women diagnosed with breast cancer receiving treatment with aromatase inhibitors (AI), performed in a tertiary hospital. Blood levels of vitamin D, calcium, phosphorus, PTH and CTX have been collected, as well as other variables and risk factors.

Results:

200 patients with a mean age of 64.8 years and an ED of 9.5 were collected. The median is 64.5 (Q1 58 and Q3 72).

The vitamin D levels presented by the study patients were <10 ng/mL in 13 patients (6.67%), 11-20 ng/mL in 50 (25.64%), 21-30 ng/mL in 68 (34.87%), 31-70 ng/mL in 62 (31.79%), and> 70 ng/mL in 2 (1.03%). This implies that in 67.18% of the patients they had values below the optimal range.

92.31% of patients (180) presented PTH values within the normal range and only 7.69% presented values above normal.

The serum calcium and phosphorus levels of the patients selected for the study had ranges within normal (99.49%) except 1 case that presented high values (0.51%) for both.

The values of CTX (carboxyterminal telopeptide used as a marker of bone resorption) were in the normal range in 81.96% of patients (159), low values in 0.52% (1) and values above the normal range by 17.53% (34).

Conclusion:

The prevalence of insufficient levels of vitamin D in our study (Breast cancer + AI) is not greater than that estimated for the general population according to various studies.

Our study found that 67.18% of patients (2/3 of the selected population) had values below those considered optimal (<30 ng / mL) and 32% had values <20.

Only 7.69% of the patients presented PTH values above the normal range.

In 82% of patients, CTX used as a marker of bone resorption had normal values.

References:

[1]Quesada Gomez JM, Díaz Curiel M, Sosa Henríquez M, Malouf-Sierra J, Nogués-Solan X, Gómez-Alonso C, et al. Low calcium intake and insufficient serum vitamin D status in treated and non-treated postmenopausal osteoporotic women in Spain. J Steroid Biochem Mol Biol. 2013;136:175-7.

[2]Jian Sun et al., Vitamin D receptor expression in peripheral blood mononuclear cells is inversely associated with disease activity and inflammation in lupus patients; Clinical Rheumatology (2019) 38:2509–2518

Disclosure of Interests:

None declared

External validation of the CACE-HF risk score for mortality in patients with heart failure

AIMS

To validate externally the CACE-HF clinical prediction rule, which predicts 1-year mortality in patients with heart failure (HF).

METHODS

We performed an external validation of the CACE-HF risk score in patients included in the RICA heart failure registry who had completed 1 year of follow-up, comparing the characteristics of the derivation and validation cohorts. The performance of the risk score was evaluated in terms of calibration, using calibration-in-the-large (a), calibration slope (b), and the Hosmer-Lemeshow test, and in terms of discrimination, using the area under the ROC curve.

RESULTS

In total, 3337 patients were included in the validation cohort. There were no significant differences between the derivation and validation cohorts in 1-year mortality (24.63% vs. 22.98%) or in the risk score and risk classes. The discrimination capacity in the validation cohort was slightly lower, 0.67 (95% CI: 0.65, 0.69), compared to that of the derivation cohort. Calibration results were a -0.05 (95% CI: -0.14, 0.03), indicating that the average predictions did not differ from the average outcome frequency, and b = 0.75 (95% CI: 0.64, 0.86), indicating a modest inconsistency in predictor effects. Observed mortality versus predicted mortality according to the deciles and risk classes were very similar in both cases, indicating good calibration.

CONCLUSIONS

The results of the external validation of the CACE-HF risk score show that although the capacity for discrimination was slightly lower than in the derivation cohort, the calibration was excellent. This tool, therefore, can assist in decision-making in the management of these patients.

Recommendations for reporting ion mobility Mass Spectrometry measurements

Here we present a guide to ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties of mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K0 ) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N; (ii) ion mobility does not measure molecular surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model; (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort toward establishing primary standards and reference materials for ion mobility, and provides recommendations to do so. © 2019 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Responsiveness and minimal clinically important difference of the Minnesota living with heart failure questionnaire

Background

The Minnesota Living with Heart Failure Questionnaire (MLHFQ) is one of the most widely used health-related quality of life questionnaires for patients with heart failure (HF). The objective of the present study was to explore the responsiveness of the MLHFQ by estimating the minimal detectable change (MDC) and the minimal clinically important difference (MCID) in Spain.

Methods

Patients hospitalized for HF in the participating hospitals completed the MLHFQ at baseline and 6 months, plus anchor questions at 6 months. To study responsiveness, patients were classified as having “improved”, remained “the same” or “worsened”, using anchor questions. We used the standardized effect size (SES), and standardized response mean (SRM) to measure the magnitude of the changes scores and calculate the MDC and MCID.

Results

Overall, 1211 patients completed the baseline and follow-up questionnaires 6 months after discharge. The mean changes in all MLHFQ domains followed a trend (P < 0.0001) with larger gains in quality of life among patients classified as “improved”, smaller gains among those classified as “the same”, and losses among those classified as “worsened”. The SES and SRM responsiveness parameters in the “improved” group were ≥ 0.80 on nearly all scales. Among patients classified as “worsened”, effect sizes were < 0.40, while among patients classified as “the same”, the values ranged from 0.24 to 0.52. The MDC ranged from 7.27 to 16.96. The MCID based on patients whose response to the anchor question was “somewhat better”, ranged from 3.59 to 19.14 points.

Conclusions

All of these results suggest that all domains of the MLHFQ have a good sensitivity to change in the population studied.

An algorithm to correct saturated mass spectrometry ion abundances for enhanced quantitation and mass accuracy in omic studies

The mass accuracy and peak intensity of ions detected by mass spectrometry (MS) measurements are essential to facilitate compound identification and quantitation. However, high concentration species can yield erroneous results if their ion intensities reach beyond the limits of the detection system, leading to distorted and non-ideal detector response (e.g. saturation), and largely precluding the calculation of accurate m/z and intensity values. Here we present an open source computational method to correct peaks above a defined intensity (saturated) threshold determined by the MS instrumentation such as the analog-to-digital converters or time-to-digital converters used in conjunction with time-of-flight MS. In this method, the isotopic envelope for each observed ion above the saturation threshold is compared to its expected theoretical isotopic distribution. The most intense isotopic peak for which saturation does not occur is then utilized to re-calculate the precursor m/z and correct the intensity, resulting in both higher mass accuracy and greater dynamic range. The benefits of this approach were evaluated with proteomic and lipidomic datasets of varying complexities. After correcting the high concentration species, reduced mass errors and enhanced dynamic range were observed for both simple and complex omic samples. Specifically, the mass error dropped by more than 50% in most cases for highly saturated species and dynamic range increased by 1-2 orders of magnitude for peptides in a blood serum sample.

Studying the complications of bariatric surgery with intravenous contrast-enhanced multidetector computed tomography

OBJECTIVE

To review the complications of bariatric surgery and their diagnosis with intravenous contrast-enhanced multidetector computed tomography (MDCT).

MATERIAL AND METHODS

We retrospectively studied all patients who underwent gastric bypass or sleeve gastrectomy at our center during 2013 or 2014. We classified complications into early complications (appearing within 30 days of the intervention) and late complications.

RESULTS

We reviewed 155 cases and found 24 complications in 22 patients: 16 early complications (7 intraperitoneal hematomas, 5 anastomotic dehiscences, 2 intestinal obstructions, and 2 external hernias) and 8 late complications (3 internal hernias, 3 intestinal perforations, and 2 marginal ulcers). Two patients died. All of these complications were diagnosed with intravenous contrast-enhanced MDCT, except one, which required a barium transit study.

CONCLUSION

The rate of complications in bariatric surgery is high and the associated mortality is not negligible. Radiologists need to know the normal findings in these patients so they can quickly identify possible complications, most of which can be diagnosed with intravenous contrast-enhanced MDCT.

Total knee replacement: Are there any baseline factors that have influence in patient reported outcomes?

BACKGROUND

There is conflicting evidence about what factors influence outcomes after total knee replacement (TKR). The objective is to identify baseline factors that differentiate patients who achieve both, minimal clinically important difference (MCID) and a patient acceptable symptom state (PASS) in pain and function, measured by WOMAC, after TKR from those who do not attain scores above the cutoff in either of these dimensions.

METHODS

One-year prospective multicentre study. Patients completed WOMAC, SF-12, EQ-5D, expectations, other joint problems and sociodemographic data while in the waiting list, and 1-year post-TKR. Dependent variable was a combination of MCID and PASS in both dimensions (yes/no). Univariate analysis was performed to identify variables associated. Exploratory factor analysis (EFA) was performed to study how these variables grouped into different factors.

RESULTS

Total sample comprised 492 patients. Mean (SD) age was 71.3 (6.9), and there were a 69.7% of women. Of the total, 106 patients did not attain either MCID or PASS in either dimension, and 230 exceeded both thresholds in both dimensions. In the univariate analysis, 13 variables were associated with belonging to one group or another. These 13 variables were included in EFA; 3 factors were extracted: expectations, mental health, and other joints problems. The percentage of variance explained by the 3 factors was 80.4%.

CONCLUSION

We have found 2 modifiable baseline factors, expectations and mental health, that should be properly managed by different specialist. Indication of TKR should take into account these modifiable factors for improving outcomes after TKR.

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 500 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrant ions or calibration like some other IMS techniques, they avoid calibration errors which can cause problems in distinguishing structurally similar molecules. All measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites analyzed to date have come from key metabolism pathways such as glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle, while the secondary metabolites consisted of classes such as terpenes and flavonoids, and the xenobiotics represented a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes and when urine features were matched to the database, the addition of the IMS dimension greatly reduced the possible number of candidate molecules. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added frequently.

Conserved Intramolecular Interactions Maintain Myosin Interacting-Heads Motifs Explaining Tarantula Muscle Super-Relaxed State Structural Basis

Tarantula striated muscle is an outstanding system for understanding the molecular organization of myosin filaments. Three-dimensional reconstruction based on cryo-electron microscopy images and single-particle image processing revealed that, in a relaxed state, myosin molecules undergo intramolecular head-head interactions, explaining why head activity switches off. The filament model obtained by rigidly docking a chicken smooth muscle myosin structure to the reconstruction was improved by flexibly fitting an atomic model built by mixing structures from different species to a tilt-corrected 2-nm three-dimensional map of frozen-hydrated tarantula thick filament. We used heavy and light chain sequences from tarantula myosin to build a single-species homology model of two heavy meromyosin interacting-heads motifs (IHMs). The flexibly fitted model includes previously missing loops and shows five intramolecular and five intermolecular interactions that keep the IHM in a compact off structure, forming four helical tracks of IHMs around the backbone. The residues involved in these interactions are oppositely charged, and their sequence conservation suggests that IHM is present across animal species. The new model, PDB 3JBH, explains the structural origin of the ATP turnover rates detected in relaxed tarantula muscle by ascribing the very slow rate to docked unphosphorylated heads, the slow rate to phosphorylated docked heads, and the fast rate to phosphorylated undocked heads. The conservation of intramolecular interactions across animal species and the presence of IHM in bilaterians suggest that a super-relaxed state should be maintained, as it plays a role in saving ATP in skeletal, cardiac, and smooth muscles.

Association of social support, functional status, and psychological variables with changes in health-related quality of life outcomes in patients with colorectal cancer

BACKGROUND

The aim of this study was to explore the association of social support received, and functional and psychological status of colorectal cancer patients before surgery with changes in health-related quality of life (HRQoL) outcomes measured by EORTC QLQ-C30 at 1-year post-intervention.

METHODS

Consecutive patients that were because of undergo therapeutic surgery for the first time for colon or rectum cancer in nine hospitals in Spain were eligible for the study. Patients completed questionnaires before surgery and 12 months afterwards: one HRQoL instrument, the EORTC QLQ-C30; a social network and social support questionnaire, the Duke-UNC Functional Social Support Questionnaire; the Hospital Anxiety and Depression Scale, to assess anxiety and depression; and the Barthel Index, to assess functional status; as well as questions about sociodemographic information. General linear models were built to explore the association of social support, functional status, and psychological variables with changes in HRQoL 12 months after intervention.

RESULTS

A total of 972 patients with colorectal cancer took part in the study. Patients' functional status, social support, and anxiety and depression were associated with changes in at least one HRQoL domain. The higher functional status, and the higher social support, the more they improved in HRQoL domains. Regarding anxiety and depression, the more anxiety and depression patients have at baseline, less they improve in HRQoL domains.

CONCLUSIONS

Patients with colorectal cancer who have more social support and no psychological distress may have better results in HRQoL domains at 1 year after surgery. Copyright © 2015 John Wiley & Sons, Ltd.

Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS

Data-independent acquisition LC-MS/MS techniques complement supervised methods for peptide quantification. However, due to the wide precursor isolation windows, these techniques are prone to interference at the fragment ion level, which, in turn, is detrimental for accurate quantification. The nonoutlier fragment ion (NOFI) ranking algorithm has been developed to assign low priority to fragment ions affected by interference. By using the optimal subset of high-priority fragment ions, these interfered fragment ions are effectively excluded from quantification. NOFI represents each fragment ion as a vector of four dimensions related to chromatographic and MS fragmentation attributes and applies multivariate outlier detection techniques. Benchmarking conducted on a well-defined quantitative data set (i.e., the SWATH Gold Standard) indicates that NOFI on average is able to accurately quantify 11-25% more peptides than the commonly used Top-N library intensity ranking method. The sum of the area of the Top3-5 NOFIs produces similar coefficients of variation as compared to that with the library intensity method but with more accurate quantification results. On a biologically relevant human dendritic cell digest data set, NOFI properly assigns low-priority ranks to 85% of annotated interferences, resulting in sensitivity values between 0.92 and 0.80, against 0.76 for the Spectronaut interference detection algorithm.

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition

As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

Changes in health-related quality of life and activities of daily living after hip fracture because of a fall in elderly patients: a prospective cohort study

BACKGROUND

The impact of hip fracture because of a fall on health-related quality of life (HRQoL) and activities of daily living (ADL) have not been well established.

AIM

To evaluate changes in HRQoL and the ability to conduct ADL among patients with hip fracture because of a fall and to compare these changes with patients who did not fall and break a hip, adjusting by gender and age.

METHODS

Adults aged 65 or more who attended the emergency departments of seven public hospitals were recruited in a prospective double-cohort study (fracture cohort, n = 776; non-fracture cohort, n = 115). ADL and HRQoL were assessed at baseline (during the postfall hospitalisation or by telephone afterwards) and 6 months later using the Barthel Index and the Lawton Brody Index for ADL, and the Short Form Health Survey (SF-12) and Western Ontario and McMaster Universities Osteoarthritis Index short form (WOMAC-SF) for HRQoL.

RESULTS

Adjusting by gender, age and baseline status, a hip fracture was a strong predictor of decline in all outcomes measured except for mental quality of life among men (measured by SF-12). Hip fracture patients younger than 74 years reported significantly more pain (measured by WOMAC-SF) than the comparison group (p = 0.02), but this difference was not observed among older patients (p = 0.19 for 75-84 years; p = 0.39 for ≥ 85 years).

DISCUSSION

Hip fractures have profound effects on HRQoL and ADL in both men and women, regardless of age. This indicates the need for special follow-up care of elderly hip fracture patients in the immediate and late postfracture periods.

Validity of criteria for hospital admission in exacerbations of COPD

AIMS

To validate a previously developed set of explicit criteria for the appropriateness of hospital admission among these patients using the RAND/UCLA Appropriateness Methodology (RAM).

METHODS

We conducted a prospective cohort study of patients experiencing symptoms of COPD exacerbation seen in the emergency departments (ED) of 16 hospitals belonging to the Spanish National Health Service. Sociodemographic and clinical variables needed to assess appropriateness were recorded. Main outcomes were mortality, severe COPD evolution, complications at follow up, and three patient-reported measures: dyspnoea level, capacity for physical activity and perceived health status.

RESULTS

Appropriately admitted patients were more likely to die (6.70% vs. 2.68%, p = 0.0102) than inappropriately admitted patients, and were more likely to develop severe evolution (27.09% vs. 6.08%, p < 0.0001) and complications (18.72% vs. 11.92%, p = 0.0244). Among discharged patients, no significant differences were observed in clinical outcomes. All patients exhibited worse dyspnoea and capacity for physical activity after exacerbation, but changes among appropriately admitted patients were less than among appropriately discharged patients.

CONCLUSION

Our appropriateness criteria identified patients in worse condition at ED arrival who were more likely to benefit from admission in terms of mortality and COPD evolution.

Rehabilitation efficiency and destination on discharge after stroke

BACKGROUND

Predicting functional recovery of patients is key for setting the objectives of the rehabilitation programme and making decisions on their destination on discharge. Many variables have an impact on disability and quality of life after stroke, including patient age, comorbidity, severity of neurological deficit, state of mind and social risk. Accordingly, it is also essential from a care perspective to optimise the functional recovery and efficiency of rehabilitation programmes, exploring their relationship with these variables.

AIM

To analyze the efficiency of post-stroke rehabilitation, identifying factors that most strongly influence functional recovery and destination on discharge.

DESIGN

Multicentre prospective cohort study

SETTING/POPULATION

All patients admitted to the Rehabilitation Units of the two hospitals after stroke over eight months

METHODS

Collected data on sociodemographic characteristics, social risk (Gijón Scale), comorbidity (Charlson Index), neurological severity (National Institute of Health Stroke Scale), daily living functioning scale (Barthel Index), length of hospital stay and destination on discharge.

RESULTS

We included 241 patients, with a mean stay of 35±22 days, 81.5% returning home on discharge. On admission 45.2% were totally dependent, and this figure fell to 12.8% on discharge, the mean Barthel Index score increasing by 32.5 points. Neurological severity, hemiparetic severity, impairment of deep sensation and trunk control on admission were the mayor variables influence on rehabilitation efficiency (P<0.001). Destination on discharge was most closely associated with civil status, social risk and Barthel Index score (P<0.001). The likelihood of transferring to residential care is 3- and 2.71-fold higher among patients with total dependence and high comorbidity scores, respectively.

CONCLUSION

Many variables influence on outcomes of stroke inpatient rehabilitation.

CLINICAL REHABILITATION IMPACT

Comprehensive assessments are required to predict patient recovery, efficiency and plan for discharge.

Score to identify the severity of adult patients with influenza A (H1N1) 2009 virus infection at hospital admission

The objective of this paper was to develop a prognostic index for severe complications among hospitalized patients with influenza A (H1N1) 2009 virus infection. We conducted a prospective observational cohort study of 618 inpatients with 2009 H1N1 virus infection admitted to 36 Spanish hospitals between July 2009 and February 2010. Risk factors evaluated included host-related factors and clinical data at admission. We developed a composite index of severe in-hospital complications (SIHC), which included: mortality, mechanical ventilation, septic shock, acute respiratory distress syndrome, and requirement for resuscitation maneuvers. Six factors were independently associated with SIHC: age >45 years, male sex, number of comorbidities, pneumonia, dyspnea, and confusion. From the β parameter obtained in the multivariate model, a weight was assigned to each factor to compute the individual influenza risk score. The score shows an area under the receiver operating characteristic (ROC) curve of 0.77. The SIHC rate was 1.9 % in the low-risk group, 10.3 % in the intermediate-risk group, and 29.6 % in the high-risk group. The odds ratio for complications was 21.8 for the high-risk group compared with the low-risk group. This easy-to-score influenza A (H1N1) 2009 virus infection risk index accurately stratifies patients hospitalized for H1N1 virus infection into low-, intermediate-, and high-risk groups for SIHC.

Patient acceptable symptom state and OMERACT-OARSI set of responder criteria in joint replacement. Identification of cut-off values

OBJECTIVE

To identify new cut-off values beyond which patients can be considered as satisfied or as responders through patient acceptable symptom state (PASS) and OMERACT-OARSI (Outcome Measures in Rheumatology-Osteoarthritis Research Society International) set of responder criteria in total joint replacement.

METHODS

Secondary analysis of a 1-year prospective multicenter study of 861 patients, 510 with total knee replacement (TKR) and 351 with total hip prosthesis (THR). Pain and function data were collected by the reverse scoring option of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). PASS values were identified with the 25th centile estimation using an anchoring question about satisfaction with actual symptoms. OMERACT-OARSI set of responder criteria was based on a combination of absolute and relative change of pain, function and global patient's assessment. Receiver operating characteristic (ROC) analysis was used as a complementary approach.

RESULTS

The values for PASS were about 80 and 69 for pain and function in THR, while these values were 80 and 68 when using OMERACT-OARSI criteria. Regarding TKR, PASS values were about 75 and 67 in pain and function with both criteria. ROC values were slightly lower in all cases. PASS and OMERACT-OARSI values varied moderately across tertiles of baseline severity.

CONCLUSION

With the provided data we can establish when a patient can be considered as satisfied/responder in joint replacement. The scores achieved at 1 year were very similar according to both criteria.

Explicit criteria for hospital admission in exacerbations of chronic obstructive pulmonary disease

OBJECTIVE

To develop detailed, explicit criteria for determining the appropriateness of admission for patients with exacerbations of chronic obstructive pulmonary disease (COPD).

DESIGN

Using a modified Delphi process, a panel of seven pneumologists and five emergency department (ED) physicians was assembled to establish the appropriateness of hospital admission for 896 distinct theoretical scenarios. To assess the reliability of the criteria, a second national panel of five pneumologists and five ED physicians was assembled. We examined the influence of all variables on the first panel score using linear regression models. The explicit criteria developed were summarised by classification and regression tree analysis.

RESULTS

The appropriateness of the hospitalisation scenarios increased with the severity of COPD. The kappa of agreement between the two panels was 0.79. Predictors of appropriate hospitalisation were severity of current COPD exacerbation, response to previous treatment and expected adherence to treatment. The panel results were synthesised and presented in three decision trees. Misclassification error in the decision trees, as compared with the panel's original ratings, was 6.1%.

CONCLUSIONS

These explicit criteria can be used to help determine the appropriateness of admission for patients with exacerbations of COPD.