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Abstract Alkaline mafic magmas forming intra-plate oceanic islands are believed to be strongly enriched in CO2 due to low-degree partial melting of enriched mantle sources. However, until now, such CO2 enhancement has not been verified by measuring CO2 degassing during a subaerial eruption. Here, we provide evidence of highly CO2-rich gas emissions during the 86-day 2021 Tajogaite eruption of Cumbre Vieja volcano on La Palma Island, in the Canary archipelago. Our results reveal sustained high plume CO2/SO2 ratios, which, when combined with SO2 fluxes, melt inclusion volatile contents and magma production rates at explosive and effusive vents, imply a magmatic CO2 content of 4.5 ± 1.5 wt%. The amount of CO2 released during the 2021 eruptive activity was 28 ± 14 Mt CO2. Extrapolating to the volume of alkaline mafic magmas forming La Palma alone (estimated as 4000 km3 erupted over 11 Ma), we infer a maximum CO2 emission into the ocean and atmosphere of 1016 moles of CO2, equivalent to 20% of the eruptive CO2 emissions from a large igneous province eruption, suggesting that the formation of the Canary volcanic archipelago produced a CO2 emission of similar magnitude as a large igneous province.

The mechanisms of B-cell diversification differ greatly between aves and mammals, but both produce B cells and antibodies capable of supporting an effective immune response. To see how differences in the generation of diversity might affect overall repertoire diversity, we have compared the diversity characteristics of immunoglobulin genes from domestic chickens to those from humans. Both use V(D)J gene rearrangement and somatic hypermutation, but only chickens use somatic gene conversion. A range of diversity analysis tools were used to investigate multiple aspects of amino acid diversity at both the germline and repertoire levels. The effect of differing amino acid usages on antibody characteristics was assessed. At both the germline and repertoire levels, chickens exhibited lower amino acid diversity in comparison to the human immunoglobulin genes, especially outside of the complementarity-determining region (CDR). Chickens were also found to possess much larger and more hydrophilic CDR3s with a higher predicted protein binding potential, suggesting that the antigen-binding site in chicken antibodies is more flexible and more polyreactive than that seen in human antibodies.

BackgroundThe COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum.MethodsSaliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques.ResultsPositive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified.ConclusionsIn this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.

Telomeres form the ends of linear chromosomes and usually comprise protein complexes that bind to simple repeated sequence motifs that are added to the 3′ ends of DNA by the telomerase reverse transcriptase (TERT). One of the primary functions attributed to telomeres is to solve the “end-replication problem” which, if left unaddressed, would cause gradual, inexorable attrition of sequences from the chromosome ends and, eventually, loss of viability. Telomere-binding proteins also protect the chromosome from 5′ to 3′ exonuclease action, and disguise the chromosome ends from the double-strand break repair machinery whose illegitimate action potentially generates catastrophic chromosome aberrations. Telomeres are of special interest in the blast fungus, Pyricularia, because the adjacent regions are enriched in genes controlling interactions with host plants, and the chromosome ends show enhanced polymorphism and genetic instability. Previously, we showed that telomere instability in some P. oryzae strains is caused by novel retrotransposons (MoTeRs) that insert in telomere repeats, generating interstitial telomere sequences that drive frequent, break-induced rearrangements. Here, we sought to gain further insight on telomeric involvement in shaping Pyricularia genome architecture by characterizing sequence polymorphisms at chromosome ends, and surrounding internalized MoTeR loci (relics) and interstitial telomere repeats. This provided evidence that telomere dynamics have played historical, and likely ongoing, roles in shaping the Pyricularia genome. We further demonstrate that even telomeres lacking MoTeR insertions are poorly preserved, such that the telomere-adjacent sequences exhibit frequent presence/absence polymorphism, as well as exchanges with the genome interior. Using TERT knockout experiments, we characterized chromosomal responses to failed telomere maintenance which suggested that much of the MoTeR relic-/interstitial telomere-associated polymorphism could be driven by compromised telomere function. Finally, we describe three possible examples of a phenomenon known as “Adaptive Telomere Failure,” where spontaneous losses of telomere maintenance drive rapid accumulation of sequence polymorphism with possible adaptive advantages. Together, our data suggest that telomere maintenance is frequently compromised in Pyricularia but the chromosome alterations resulting from telomere failure are not as catastrophic as prior research would predict, and may, in fact, be potent drivers of adaptive polymorphism.

Background: The COVID-19 pandemic has led to an unprecedented demand for testing - for diagnosis and prognosis - as well as for investigation into the impact of the disease on the host metabolism. Sebum sampling has the potential to support both needs by looking at what the virus does to us, rather than looking for the virus itself. Methods: In this pilot study, sebum samples were collected from 67 hospitalised patients (30 COVID-19 positive and 37 COVID-19 negative) by gauze swab. Lipidomics analysis was carried out using liquid chromatography mass spectrometry, identifying 998 reproducible features. Univariate and multivariate statistical analyses were applied to the resulting feature set. Findings: Lipid levels were depressed in COVID-19 positive participants, indicative of dyslipidemia; p-values of 0·022 and 0·015 were obtained for triglycerides and ceramides respectively, with effect sizes of 0·44 and 0·57. Partial Least Squares-Discriminant Analysis showed separation of COVID-19 positive and negative participants with sensitivity of 57% and specificity of 68%, improving to 79% and 83% respectively when controlled for confounding comorbidities. Interpretation: COVID-19 dysregulates many areas of metabolism; in this work we show that the skin lipidome can be added to the list. Given that samples can be provided quickly and painlessly, we conclude that sebum is worthy of future consideration for clinical sampling. Funding: The authors acknowledge funding from the EPSRC Impact Acceleration Account for sample collection and processing, as well as EPSRC Fellowship Funding EP/R031118/1, the University of Surrey and BBSRC BB/T002212/1. Mass Spectrometry was funded under EP/P001440/1.

Background: The American Thyroid Association Guidelines on Thyroid Disease During Pregnancy and the Postpartum (ATA Guidelines) were published in 2017, with an update not expected for another 5 years. Since release of the 2017 ATA Guidelines, greater than 500 articles have been published in the field. Furthermore, there are presently 14 prospective, interventional trials in progress registered at Clinicaltrials.gov Static guidelines updated every 5–7 years fail to provide timely evidence-based guidance to practicing clinicians. Consequently, guideline development should move toward the creation of dynamic documents. The present article reviews the literature published since the 2017 ATA Guidelines, both to benefit clinicians in practice and to make the case for Dynamic ATA Guidelines.Methods: Using the search terms “thyroid” and “pregnancy,” a systematic review of literature published in Pubmed from 3/1/2017 to 12/31/2018 was conducted. The titles and/or abstracts of all articles were reviewed. All articles were classified by subject headings used in the 2017 ATA Guidelines. English-text articles classified under “hypothyroidism” or “thyroid autoimmunity” were examined in full-text. Using the questions and recommendations put forth by the previous ATA Guidelines, relevant articles were selected for discussion in this review.Results: At the time of the search, 659 unique articles on “thyroid and pregnancy” were identified, including 66 original studies on hypothyroidism and 26 on thyroid autoimmunity. Of these, 26 studies on hypothyroidism and 18 studies on thyroid autoimmunity were selected for inclusion in this review based on specific questions in the 2017 ATA Guidelines. Based on these 44 articles, we propose two specific changes to the 2017 ATA Guidelines.Conclusion: Based on new research, we recommend the 2017 ATA Guidelines be updated to recommend against treating thyroid antibody-negative women diagnosed with subclinical hypothyroidism in the second trimester or later; to reflect new, moderate-quality evidence supporting the treatment of thyroid peroxidase antibody-negative women with elevated thyroid stimulating hormone levels in the first trimester or earlier; and to recommend against treatment of euthyroid, thyroid peroxidase antibody-positive women undergoing assisted reproductive technology. Transitioning to a Dynamic ATA Guidelines would allow for these and future recommendations to be implemented in real time.

During pregnancy, the thyroid gland must produce 50% more thyroid hormone to maintain the euthyroid state. Women with decreased thyroid reserve pre-conception, most typically due to Hashimoto’s thyroiditis, may develop hypothyroidism during pregnancy. Data over the last twenty years have reported a strong association between subclinical hypothyroidism and adverse maternal/fetal events. As a result of this association, an increasing number of women are being screened for thyroid disease either pre-conception or at the first prenatal visit. Consequently, an ever increasing number of women are being initiated on levothyroxine for the first time during pregnancy. At present, there are very limited guidelines related to the management of the thyroid disease in these women postpartum. Based on an understanding of the physiology of thyroid gland during pregnancy and postpartum, and the personal clinical experience of the author, recommendations for the postpartum management of women who were started on levothyroxine during pregnancy are presented.

Malignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.We conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.The SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease.We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES) that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC.This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels. Separate verification of classifier performance provides evidence against over-fitting and is encouraging for the next development phase, independent validation. This careful study provides a solid foundation to develop tests sorely needed to identify early stage lung cancer.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.