Endogenous monoclonal immunoglobulins analyzed using the EXENT® solution and LC-MS.

Introduction: The EXENT® Solution, a fully automated system, is a recent advancement for identifying and quantifying monoclonal immunoglobulins in serum. It combines immunoprecipitation with MALDI-TOF mass spectrometry. Compared to gel-based methods, like SPEP and IFE, it has demonstrated the ability to detect monoclonal immunoglobulins in serum at lower levels. In this study, samples that tested negative using EXENT® were reflexed to LC-MS to determine if the more sensitive LC-MS method could identify monoclonal immunoglobulins missed by EXENT®. Objectives: To assess whether monoclonal immunoglobulins that are not detected by EXENT® can be detected by LC-MS using a low flow LC system coupled to a Q-TOF mass spectrometer. Methods: Samples obtained from patients confirmed to have multiple myeloma (MM) were diluted with pooled polyclonal human serum and analyzed using EXENT®. If a specific monoclonal immunoglobulin was not detected by EXENT®, the sample was then subjected to analysis by LC-MS. For the LC-MS analysis, the sample eluate, obtained after the MALDI-TOF MS spotting step, was collected and transferred to an autosampler tray for subsequent analysis using LC-MS. Conclusion: LC-MS has the capability to detect monoclonal immunoglobulins that are no longer detected by EXENT®. Reflexing samples to LC-MS for analysis does not involve additional sample handling, allowing for a faster time-to-result compared to current approaches, such as Next-Generation Sequencing, Next-Generation Flow, and clonotypic peptide methods. Notably, LC-MS offers equivalent sensitivity in detecting these specific monoclonal immunoglobulins.

Protocol for programing a degree-to-careers dashboard in R using Posit and Shiny.

Here, we present a protocol for programing a degree-to-careers dashboard in R using Posit and Shiny. We describe steps for installing software, obtaining datasets, and munging and joining data. We then detail procedures for programing and publishing the dashboard in Shiny web application that includes a filtered data table. The resulting dashboard links academic programs with careers and income data and may be useful to inform decision-making by higher education leaders and policymakers. For complete details on the use and execution of this protocol, please refer to Perkins and Carrier (2023).1.

Device innovation in cardiovascular medicine: a report from the European Society of Cardiology Cardiovascular Round Table.

Research performed in Europe has driven cardiovascular device innovation. This includes, but is not limited to, percutaneous coronary intervention, cardiac imaging, transcatheter heart valve implantation, and device therapy of cardiac arrhythmias and heart failure. An important part of future medical progress involves the evolution of medical technology and the ongoing development of artificial intelligence and machine learning. There is a need to foster an environment conducive to medical technology development and validation so that Europe can continue to play a major role in device innovation while providing high standards of safety. This paper summarizes viewpoints on the topic of device innovation in cardiovascular medicine at the European Society of Cardiology Cardiovascular Round Table, a strategic forum for high-level dialogue to discuss issues related to the future of cardiovascular health in Europe. Devices are developed and improved through an iterative process throughout their lifecycle. Early feasibility studies demonstrate proof of concept and help to optimize the design of a device. If successful, this should ideally be followed by randomized clinical trials comparing novel devices vs. accepted standards of care when available and the collection of post-market real-world evidence through registries. Unfortunately, standardized procedures for feasibility studies across various device categories have not yet been implemented in Europe. Cardiovascular imaging can be used to diagnose and characterize patients for interventions to improve procedural results and to monitor devices long term after implantation. Randomized clinical trials often use cardiac imaging-based inclusion criteria, while less frequently trials randomize patients to compare the diagnostic or prognostic value of different modalities. Applications using machine learning are increasingly important, but specific regulatory standards and pathways remain in development in both Europe and the USA. Standards are also needed for smart devices and digital technologies that support device-driven biomonitoring. Changes in device regulation introduced by the European Union aim to improve clinical evidence, transparency, and safety, but they may impact the speed of innovation, access, and availability. Device development programmes including dialogue on unmet needs and advice on study designs must be driven by a community of physicians, trialists, patients, regulators, payers, and industry to ensure that patients have access to innovative care.

Combining Thermal Desorption with Selected Ion Flow Tube Mass Spectrometry for Analyses of Breath Volatile Organic Compounds.

An instrument integrating thermal desorption (TD) to selected ion flow tube mass spectrometry (SIFT-MS) is presented, and its application to analyze volatile organic compounds (VOCs) in human breath is demonstrated for the first time. The rationale behind this development is the need to analyze breath samples in large-scale multicenter clinical projects involving thousands of patients recruited in different hospitals. Following adapted guidelines for validating analytical techniques, we developed and validated a targeted analytical method for 21 compounds of diverse chemical class, chosen for their clinical and biological relevance. Validation has been carried out by two independent laboratories, using calibration standards and real breath samples from healthy volunteers. The merging of SIFT-MS and TD integrates the rapid analytical capabilities of SIFT-MS with the capacity to collect breath samples across multiple hospitals. Thanks to these features, the novel instrument has the potential to be easily employed in clinical practice.

Mass spectrometry-detected MGUS is associated with obesity and other novel modifiable risk factors in a high-risk population.

ABSTRACT: Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant condition of multiple myeloma with few known risk factors. The emergence of mass spectrometry (MS) for the detection of MGUS has provided new opportunities to evaluate its risk factors. In total, 2628 individuals at elevated risk for multiple myeloma were enrolled in a screening study and completed an exposure survey (PROMISE trial). Participant samples were screened by MS, and monoclonal proteins (M-proteins) with concentrations of ≥0.2 g/L were categorized as MS-MGUS. Multivariable logistic models evaluated associations between exposures and MS outcomes. Compared with normal weight (body mass index [BMI] of 18.5 to <25 kg/m2), obesity (BMI of ≥30 kg/m2) was associated with MS-MGUS, adjusting for age, sex, Black race, education, and income (odds ratio [OR], 1.73; 95% confidence interval [CI], 1.21-2.47; P = .003). High physical activity (≥73.5 metabolic equivalent of task (MET)-hours per week vs <10.5 MET-hours per week) had a decreased likelihood of MS-MGUS (OR, 0.45, 95% CI, 0.24-0.80; P = .009), whereas heavy smoking and short sleep had increased likelihood of MS-MGUS (>30 pack-years vs never smoker: OR, 2.19; 95% CI, 1.24-3.74; P = .005, and sleep <6 vs ≥6 hours per day: OR, 2.11; 95% CI, 1.26-3.42; P = .003). In the analysis of all MS-detected monoclonal gammopathies, which are inclusive of M-proteins with concentrations of <0.2 g/L, elevated BMI and smoking were associated with all MS-positive cases. Findings suggest MS-detected monoclonal gammopathies are associated with a broader range of modifiable risk factors than what has been previously identified. This trial was registered at www.clinicaltrials.gov as #NCT03689595.

Advancements in artificial intelligence-driven techniques for interventional cardiology.

This paper aims to thoroughly discuss the impact of artificial intelligence (AI) on clinical practice in interventional cardiology (IC) with special recognition of its most recent advancements. Thus, recent years have been exceptionally abundant in advancements in computational tools, including the development of AI. The application of AI development is currently in its early stages, nevertheless new technologies have proven to be a promising concept, particularly considering IC showing great impact on patient safety, risk stratification and outcomes during the whole therapeutic process. The primary goal is to achieve the integration of multiple cardiac imaging modalities, establish online decision support systems and platforms based on augmented and/or virtual realities, and finally to create automatic medical systems, providing electronic health data on patients. In a simplified way, two main areas of AI utilization in IC may be distinguished, namely, virtual and physical. Consequently, numerous studies have provided data regarding AI utilization in terms of automated interpretation and analysis from various cardiac modalities, including electrocardiogram, echocardiography, angiography, cardiac magnetic resonance imaging, and computed tomography as well as data collected during robotic-assisted percutaneous coronary intervention procedures. Thus, this paper aims to thoroughly discuss the impact of AI on clinical practice in IC with special recognition of its most recent advancements.

Accurate selected ion flow tube mass spectrometry quantification of ethylene oxide contamination in the presence of acetaldehyde.

In September 2020, traces of ethylene oxide (a toxic substance used as a pesticide in developing countries but banned for use on food items within the European Union) were found in foodstuffs containing ingredients derived from imported sesame seed products. Vast numbers of foodstuffs were recalled across Europe due to this contamination, leading to expensive market losses and extensive trace exposure of ethylene oxide to consumers. Therefore, a rapid analysis method is needed to ensure food safety by high-throughput screening for ethylene oxide contamination. Selected ion flow tube mass spectrometry (SIFT-MS) is a suitable method for rapid quantification of trace amounts of vapours in the headspace of food samples. It turns out, however, that the presence of acetaldehyde complicates SIFT-MS analyses of its isomer ethylene oxide. It was proposed that a combination of the H3O+ and NO+ reagent ions can be used to analyse ethylene oxide in the presence of acetaldehyde. This method is, however, not robust because of the product ion overlaps and potential interferences from other matrix species. Thus, we studied the kinetics of the reactions of the H3O+, NO+, OH- and O-˙ ions with these two compounds and obtained their rate coefficients and product ion branching ratios. Interpretation of these experimental data revealed that the OH- anions are the most suitable SIFT-MS reagents because the product ions of their reactions with acetaldehyde (CH2CHO- at m/z 43) and ethylene oxide (C2H3O2- at m/z 59) do not overlap.

Towards the development of a SARS-CoV-2 variant risk assessment tool: expert consultation on the assessment of scientific evidence on emerging variants.

A systematic approach is required for the development of an evidence-based risk assessment tool to robustly estimate the risks and implications of SARS-CoV-2 variants. We conducted a survey among experts involved in technical advisory roles for WHO to capture their assessment of the robustness of different study types that provide evidence for potential changes in transmissibility, antigenicity, virulence, treatability, and detectability of SARS-CoV-2 variants. The views of 62 experts indicated that studies could be grouped on the basis of robustness and reliability for the different risk indicators mentioned. Several study types that experts scored as providing reliable evidence and that can be performed in a timely manner were identified. Although experts from different technical areas had varying responses, there was agreement on the highest and lowest scoring study types. These findings can help to prioritise, harmonise, and optimise study designs for the further development of a systematic, evidence-based, SARS-CoV-2 variant risk assessment tool.

Comprehensive, Comparative Evaluation of 35 Manual SARS-CoV-2 Serological Assays.

The onset of the coronavirus disease 2019 (COVID-19) pandemic resulted in hundreds of in vitro diagnostic devices (IVDs) coming to market, facilitated by regulatory authorities allowing "emergency use" without a comprehensive evaluation of performance. The World Health Organization (WHO) released target product profiles (TPPs) specifying acceptable performance characteristics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) assay devices. We evaluated 26 rapid diagnostic tests and 9 enzyme immunoassays (EIAs) for anti-SARS-CoV-2, suitable for use in low- and middle-income countries (LMICs), against these TPPs and other performance characteristics. The sensitivity and specificity ranged from 60.1 to 100% and 56.0 to 100%, respectively. Five of 35 test kits reported no false reactivity for 55 samples with potentially cross-reacting substances. Six test kits reported no false reactivity for 35 samples containing interfering substances, and only one test reported no false reactivity with samples positive for other coronaviruses (not SARS-CoV-2). This study demonstrates that a comprehensive evaluation of the performance of test kits against defined specifications is essential for the selection of test kits, especially in a pandemic setting. IMPORTANCE The markets have been flooded with hundreds of SARS-CoV-2 serology tests, and although there are many published reports on their performance, comparative reports are far fewer and tend to be limited to only a few tests. In this report, we comparatively assessed 35 rapid diagnostic tests or microtiter plate enzyme immunoassays (EIAs) using a large set of samples from individuals with a history of mild to moderate COVID-19, commensurate with the target population for serosurveillance, which included serum samples from individuals previously infected, at undetermined time periods, with other seasonal human coronaviruses, Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-1. The significant heterogeneity in their performances, with only a few tests meeting WHO target product profile performance requirements, highlights the importance of independent comparative assessments to inform the use and procurement of these tests for both diagnostics and epidemiological investigations.

Probing the conserved roles of cut in the development and function of optically different insect compound eyes.

Astonishing functional diversity exists among arthropod eyes, yet eye development relies on deeply conserved genes. This phenomenon is best understood for early events, whereas fewer investigations have focused on the influence of later transcriptional regulators on diverse eye organizations and the contribution of critical support cells, such as Semper cells (SCs). As SCs in Drosophila melanogaster secrete the lens and function as glia, they are critical components of ommatidia. Here, we perform RNAi-based knockdowns of the transcription factor cut (CUX in vertebrates), a marker of SCs, the function of which has remained untested in these cell types. To probe for the conserved roles of cut, we investigate two optically different compound eyes: the apposition optics of D. melanogaster and the superposition optics of the diving beetle Thermonectus marmoratus. In both cases, we find that multiple aspects of ocular formation are disrupted, including lens facet organization and optics as well as photoreceptor morphogenesis. Together, our findings support the possibility of a generalized role for SCs in arthropod ommatidial form and function and introduces Cut as a central player in mediating this role.

Control of contextual memory through interneuronal α5-GABAA receptors.

γ-Aminobutyric acid type A receptors that incorporate α5 subunits (α5-GABAARs) are highly enriched in the hippocampus and are strongly implicated in control of learning and memory. Receptors located on pyramidal neuron dendrites have long been considered responsible, but here we report that mice in which α5-GABAARs have been eliminated from pyramidal neurons (α5-pyr-KO) continue to form strong spatial engrams and that they remain as sensitive as their pseudo-wild-type (p-WT) littermates to etomidate-induced suppression of place cells and spatial engrams. By contrast, mice with selective knockout in interneurons (α5-i-KO) no longer exhibit etomidate-induced suppression of place cells. In addition, the strength of spatial engrams is lower in α5-i-KO mice than p-WT littermates under control conditions. Consistent with the established role of the hippocampus in contextual fear conditioning, α5-i-KO mice resisted etomidate's suppression of freezing to context, but so too did α5-pyr-KO mice, supporting a role for extra-hippocampal regions in the development of contextual fear memory. Overall, our results indicate that interneuronal α5-GABAARs serve a physiological role in promoting spatial learning and that they mediate suppression of hippocampus-dependent contextual memory by etomidate.

Changes in Memory, Sedation, and Receptor Kinetics Imparted by the ß2-N265M and ß3-N265M GABAA Receptor Point Mutations.

Point mutations in the ß2 (N265S) and ß3 (N265M) subunits of γ-amino butyric acid type A receptors (GABAARs) that render them insensitive to the general anesthetics etomidate and propofol have been used to link modulation of ß2-GABAARs to sedation and ß3-GABAARs to surgical immobility. These mutations also alter GABA sensitivity, and mice carrying the ß3-N265M mutation have been reported to have impaired baseline memory. Here, we tested the effects of the ß2-N265M and ß3-N265M mutations on memory, movement, hotplate sensitivity, anxiety, etomidate-induced sedation, and intrinsic kinetics. We found that both ß2-N265M and ß3-N265M mice exhibited baseline deficits in the Context Preexposure Facilitation Effect learning paradigm. Exploratory activity was slightly greater in ß2-N265M mice, but there were no changes in either genotype in anxiety or hotplate sensitivity. ß2-N265M mice were highly resistant to etomidate-induced sedation, and heterozygous mice were partially resistant. In rapid solution exchange experiments, both mutations accelerated deactivation two- to three-fold compared to wild type receptors and prevented modulation by etomidate. This degree of change in the receptor deactivation rate is comparable to that produced by an amnestic dose of etomidate but in the opposite direction, indicating that intrinsic characteristics of GABAARs are optimally tuned under baseline conditions to support mnemonic function.

Can the UK 'Netflix' Payment Model Boost the Antibacterial Pipeline?

The silent pandemic of antimicrobial resistance (AMR) is a global issue needing prompt attention. A comprehensive one-health approach across human and animal health, agriculture and the environment is needed to solve this, addressing overuse of antibacterials, and of course, optimising measures for preventing and controlling infection. We also need a robust pipeline of new antibacterials. However, the current pipeline is inadequate and several companies with new antibacterials have gone bankrupt due to low sales, leading to a 'broken market'. To address this, the UK has completed a project using novel approaches to value assessment and reimbursement for two antibacterials. The new funding arrangements for these products commenced on 1st July 2022, delinking reimbursement from volume of sales; a so-called 'pull incentive', with payments based on the added value to the whole-health and social-care system, not just to individual patients. This article describes how the project was devised, developed, and progressed. The learning from this work might help other countries to adopt or adapt the approach to fit with their national systems, and collectively achieve a global incentive to reinvigorate the antibacterial pipeline.

Using R Shiny to develop a dashboard using IPEDS, U.S. Census, and bureau of labor statistics data.

This paper describes the development of an RStudio (now known as Posit) dashboard derived from the Integrated Postsecondary Educational Data System, the United States Census Bureau, and the Bureau of Labor Statistics and provides the user with institutional, community, and career information of IPEDS reporting higher education institutions in the United States and its territories. With this dashboard, users can select and learn about institutions, explore enrollment trends and demographics, compare outcomes, and correlate community and institutional variables. Users can also link degrees to career projections and wages. This paper explains how the dashboard was developed with examples of R programming language.

SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs.

The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated COVID-19 epidemics in a prototypical low- and middle-income country to investigate how testing rates, sampling strategies and sequencing proportions jointly impact surveillance outcomes, and showed that low testing rates and spatiotemporal biases delay time to detection of new variants by weeks to months and can lead to unreliable estimates of variant prevalence, even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of approximately 100 tests per 100,000 people per day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.

Global disparities in SARS-CoV-2 genomic surveillance.

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.

Dose-dependent suppression of hippocampal contextual memory formation, place cells, and spatial engrams by the NMDAR antagonist (R)-CPP.

We recently reported that the competitive NMDAR antagonist (R,S)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP) does not suppress NMDAR-mediated field EPSPs (fEPSPNMDA) or long-term potentiation (LTP) in vitro at concentrations that block contextual conditioning in vivo. Here we tested one possible explanation for the mismatch - that the hippocampus is relatively resistant to CPP compared to other brain structures engaged in contextual fear conditioning. Using the context pre-exposure facilitation effect (CPFE) paradigm to separate the hippocampal and extra-hippocampal components of contextual learning, we found that the active enantiomer (R)-CPP suppressed the hippocampal component with an IC50 of 3.1 mg/kg, a dose that produces brain concentrations below those required to block fEPSPNMDA or LTP. Moreover, using in-vivo calcium imaging of place cells and spatial engrams to directly assess hippocampal spatial coding, we found that (R)-CPP dose-dependently reduced the development of place cells and interfered with the formation of stable spatial engrams when it was administered prior to exposing mice to a novel context. Both effects occurred at doses that interfered with freezing to context in CPFE experiments. We conclude that (R)-CPP blocks memory formation by interfering with hippocampal function, but that it does so by modulating NMDARs at sites that are not engaged in vitro in the same manner that they are in vivo - perhaps through interneuron circuits that do not contribute to fEPSPs and are not required to elicit LTP using standard induction protocols in vitro, but are essential for successful mnemonic function in vivo.

SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs.

The first step in SARS-CoV-2 genomic surveillance is testing to identify infected people. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (LMICs) (mean = 27 tests/100,000 people/day). We simulated COVID-19 epidemics in a prototypical LMIC to investigate how testing rates, sampling strategies, and sequencing proportions jointly impact surveillance outcomes and showed that low testing rates and spatiotemporal biases delay time-to-detection of new variants by weeks-to-months and can lead to unreliable estimates of variant prevalence even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of ~100 tests/100,000 people/day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.

Prevalence of monoclonal gammopathies and clinical outcomes in a high-risk US population screened by mass spectrometry: a multicentre cohort study.

BACKGROUND: Prevalence estimates for monoclonal gammopathy of undetermined significance (MGUS) are based on predominantly White study populations screened by serum protein electrophoresis supplemented with immunofixation electrophoresis. A prevalence of 3% is reported for MGUS in the general population of European ancestry aged 50 years or older. MGUS prevalence is two times higher in individuals of African descent or with a family history of conditions related to multiple myeloma. We aimed to evaluate the prevalence and clinical implications of monoclonal gammopathies in a high-risk US population screened by quantitative mass spectrometry. METHODS: We used quantitative matrix-assisted laser desorption ionisation-time of flight (MALDI-TOF) mass spectrometry and EXENT-iQ software to screen for and quantify monoclonal gammopathies in serum from 7622 individuals who consented to the PROMISE screening study between Feb 26, 2019, and Nov 4, 2021, and the Mass General Brigham Biobank (MGBB) between July 28, 2010, and July 1, 2021. M-protein concentrations at the monoclonal gammopathy of indeterminate potential (MGIP) level were confirmed by liquid chromatography mass spectrometry testing. 6305 (83%; 2211 from PROMISE, 4094 from MGBB) of 7622 participants in the cohorts were at high risk for developing a monoclonal gammopathy on the basis of Black race or a family history of haematological malignancies and fell within the eligible high-risk age range (30 years or older for PROMISE cohort and 18 years or older for MGBB cohort); those over 18 years were also eligible if they had two or more family members with a blood cancer (PROMISE cohort). Participants with a plasma cell malignancy diagnosed before screening were excluded. Longitudinal clinical data were available for MGBB participants with a median follow-up time from serum sample screening of 4·5 years (IQR 2·4-6·7). The PROMISE study is registered with ClinicalTrials.gov, NCT03689595. FINDINGS: The median age at time of screening was 56·0 years (IQR 46·8-64·1). 5013 (66%) of 7622 participants were female, 2570 (34%) male, and 39 (<1%) unknown. 2439 (32%) self-identified as Black, 4986 (65%) as White, 119 (2%) as other, and 78 (1%) unknown. Using serum protein electrophoresis with immunofixation electrophoresis, the MGUS prevalence was 6% (101 of 1714) in high-risk individuals aged 50 years or older. Using mass spectrometry, we observed a total prevalence of monoclonal gammopathies of 43% (1788 of 4207) in this group. We termed monoclonal gammopathies below the clinical immunofixation electrophoresis detection level (<0·2 g/L) MGIPs, to differentiate them from those with higher concentrations, termed mass-spectrometry MGUS, which had a 13% (592 of 4207) prevalence by mass spectrometry in high-risk individuals aged 50 years or older. MGIP was predominantly of immunoglobulin M isotype, and its prevalence increased with age (19% [488 of 2564] for individuals aged <50 years, 29% [1464 of 5058] for those aged ≥50 years, and 37% [347 of 946] for those aged ≥70 years). Mass-spectrometry MGUS prevalence increased with age (5% [127 of 2564] for individuals aged <50 years, 13% [678 of 5058] for those aged ≥50 years, and 18% [173 of 946] for those aged ≥70 years) and was higher in men (314 [12%] of 2570) compared with women (485 [10%] 5013; p=0·0002), whereas MGIP prevalence did not differ significantly by gender. In those aged 50 years or older, the prevalence of mass spectrometry was significantly higher in Black participants (224 [17%] of 1356) compared with the controls (p=0·0012) but not in those with family history (368 [13%] of 2851) compared with the controls (p=0·1008). Screen-detected monoclonal gammopathies correlated with increased all-cause mortality in MGBB participants (hazard ratio 1·55, 95% CI 1·16-2·08; p=0·0035). All monoclonal gammopathies were associated with an increased likelihood of comorbidities, including myocardial infarction (odds ratio 1·60, 95% CI 1·26-2·02; p=0·00016 for MGIP-high and 1·39, 1·07-1·80; p=0·015 for mass-spectrometry MGUS). INTERPRETATION: We detected a high prevalence of monoclonal gammopathies, including age-associated MGIP, and made more precise estimates of mass-spectrometry MGUS compared with conventional gel-based methods. The use of mass spectrometry also highlighted the potential hidden clinical significance of MGIP. Our study suggests the association of monoclonal gammopathies with a variety of clinical phenotypes and decreased overall survival. FUNDING: Stand Up To Cancer Dream Team, the Multiple Myeloma Research Foundation, and National Institutes of Health.

Untargeted selected ion flow tube mass spectrometry headspace analysis: High-throughput differentiation of virgin and recycled polyethylene pellets.

RATIONALE: Recycled plastics are increasingly used for packaging of fast-moving consumer goods (FMCG). Compared with packaging made from virgin polymers, there is greater risk of taints entering products due to prior use of the polymers and incomplete cleaning. Increased quality assurance testing of polymer feedstock is required for recycled packaging. Selected ion flow tube mass spectrometry (SIFT-MS) analysis coupled with multivariate statistical data processing can provide high-throughput untargeted screening of recycled polymers at low cost per sample. METHODS: SIFT-MS is a direct-injection MS technique that provides high-throughput automated headspace analysis of polymer samples when coupled with a syringe-injection autosampler (12 incubated samples per hour). Full-scan SIFT-MS data were processed using multivariate statistical analysis (specifically, the soft independent modeling by class analogy (SIMCA) algorithm). RESULTS: SIFT-MS full-scan data were acquired for ten replicates each of ten recycled and four virgin high-density polyethylene (HDPE) pellet products from multiple manufacturers. The samples varied approximately 20-fold in terms of total volatile residue, while showing very high repeatability across replicates. SIFT-MS scan data were dominated by aliphatic and monoterpene hydrocarbon residues, and - to a lesser extent - alcohols. Application of the SIMCA algorithm to the data resulted in successful classification by both individual samples and manufacturers. CONCLUSIONS: Automated, untargeted SIFT-MS analysis coupled with multivariate statistical data analysis has the potential to provide rapid, effective screening of recycled polymer products, which would provide increased quality assurance of recycled polymers used for FMCG.