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An award-winning Oxford-based international project to tackle antibiotic resistance has achieved its one millionth classification.
Evolution of methods to detect paraneoplastic antibodies.
An adaptive immune response in less than 1% of people who develop cancer produces antibodies against neuronal proteins. These antibodies can be associated with paraneoplastic syndromes, and their accurate detection should instigate a search for a specific cancer. Over the years, multiple systems, from indirect immunofluorescence to live cell-based assays, have been developed to identify these antibodies. As the specific antigens were identified, high throughput, multi-antigen substrates such as line blots and ELISAs were developed for clinical laboratories. However, the evolution of assays required to identify antibodies to membrane targets has shone a light on the importance of antigen conformation for antibody detection. This chapter discusses the early antibody assays used to detect antibodies to nuclear and cytosolic targets and how new approaches are required to detect antibodies to membrane targets. The chapter presents recent data that support international recommendations against the sole use of line blots for antibody detection and highlights a new antigen-specific approach that appears promising for the detection of submembrane targets.
Single-cell glycolytic activity regulates membrane tension and HIV-1 fusion
ABSTRACTThere has been resurgence in determining the role of host metabolism in viral infection yet deciphering how the metabolic state of single cells affects viral entry and fusion remains unknown. Here, we have developed a novel assay multiplexing genetically encoded biosensors with single virus tracking (SVT) to evaluate the influence of global metabolic processes on the success rate of virus entry in single cells. We found that cells with a lower ATP:ADP ratio prior to virus addition were less permissive to virus fusion and infection. These results indicated a relationship between host metabolic state and the likelihood for virus-cell fusion to occur. SVT revealed that HIV-1 viruses were arrested at hemifusion in glycolytically-inactive cells. Interestingly, cells acutely treated with glycolysis inhibitor 2-deoxyglucose (2-DG) become resistant to virus infection and also display less surface membrane cholesterol. Addition of cholesterol in these in glycolytically-inactive cells rescued the virus entry block at hemifusion and enabled completion of HIV-1 fusion. Further investigation with FRET-based membrane tension and membrane-order reporters revealed a link between host cell glycolytic activity and host membrane order and tension. Indeed, cells treated with 2-DG possessed lower plasma membrane lipid order and higher tension values, respectively. Our novel imaging approach that combines lifetime imaging (FLIM) and SVT revealed not only changes in plasma membrane tension at the point of viral fusion, but also that HIV is less likely to enter cells at areas of higher membrane tension. We therefore have identified a connection between host cell glycolytic activity and membrane tension that influences HIV-1 fusion in real-time at the single-virus fusion level in live cells. As glycolytic activity sets membrane tension levels by altering cellular cholesterol surface levels, our results suggest additional previously unknown benefits of cholesterol-lowering medication in HIV-1 infection.
AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: The RAVEN cohort study.
OBJECTIVES: Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. METHODS: Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. RESULTS: Over 4.5 million AZD1222 recipients were matched (mean follow-up ∼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the 'fit' (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). CONCLUSIONS: Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed.
What is the environmental impact of a blood transfusion? A life cycle assessment of transfusion services across England.
BACKGROUND: Healthcare activities significantly contribute to greenhouse gas (GHG) emissions. Blood transfusions require complex, interlinked processes to collect, manufacture, and supply. Their contribution to healthcare emissions and avenues for mitigation is unknown. STUDY DESIGN AND METHODS: We performed a life cycle assessment (LCA) for red blood cell (RBC) transfusions across England where 1.36 million units are transfused annually. We defined the process flow with seven categories: donation, transportation, manufacturing, testing, stockholding, hospital transfusion, and disposal. We used direct measurements, manufacturer data, bioengineering databases, and surveys to assess electrical power usage, embodied carbon in disposable materials and reagents, and direct emissions through transportation, refrigerant leakage, and disposal. RESULTS: The central estimate of carbon footprint per unit of RBC transfused was 7.56 kg CO2 equivalent (CO2 eq). The largest contribution was from transportation (2.8 kg CO2 eq, 36% of total). The second largest was from hospital transfusion processes (1.9 kg CO2 eq, 26%), driven mostly by refrigeration. The third largest was donation (1.3 kg CO2 eq, 17%) due to the plastic blood packs. Total emissions from RBC transfusion are ~10.3 million kg CO2 eq/year. DISCUSSION: This is the first study to estimate GHG emissions attributable to RBC transfusion, quantifying the contributions of each stage of the process. Primary areas for mitigation may include electric vehicles for the blood service fleet, improving the energy efficiency of refrigeration, using renewable sources of electricity, changing the plastic of blood packs, and using methods of disposal other than incineration.
Single-cell RNA sequencing analysis of vestibular schwannoma reveals functionally distinct macrophage subsets
Background: Vestibular schwannomas (VSs) remain a challenge due to their anatomical location and propensity to growth. Macrophages are present in VS but their roles in VS pathogenesis remains unknown. Objectives: The objective was to assess phenotypic and functional profile of macrophages in VS with single-cell RNA sequencing (scRNAseq). Methods: scRNAseq was carried out in three VS samples to examine characteristics of macrophages in the tumour. RT-qPCR was carried out on 10 VS samples for CD14, CD68 and CD163 and a panel of macrophage-associated molecules. Results: scRNAseq revealed macrophages to be a major constituent of VS microenvironment with three distinct subclusters based on gene expression. The subclusters were also defined by expression of CD163, CD68 and IL-1β. AREG and PLAUR were expressed in the CD68+CD163+IL-1β+ subcluster, PLCG2 and NCKAP5 were expressed in CD68+CD163+IL-1β− subcluster and AUTS2 and SPP1 were expressed in the CD68+CD163−IL-1β+ subcluster. RT-qPCR showed expression of several macrophage markers in VS of which CD14, ALOX15, Interleukin-1β, INHBA and Colony Stimulating Factor-1R were found to have a high correlation with tumour volume. Conclusions: Macrophages form an important component of VS stroma. scRNAseq reveals three distinct subsets of macrophages in the VS tissue which may have differing roles in the pathogenesis of VS.
Childhood growth during recovery from acute illness in Africa and South Asia: a secondary analysis of the childhood acute illness and nutrition (CHAIN) prospective cohort
Background: Growth faltering is well-recognized during acute childhood illness and growth acceleration during convalescence, with or without nutritional therapy, may occur. However, there are limited recent data on growth after hospitalization in low- and middle-income countries. Methods: We evaluated growth following hospitalization among children aged 2–23 months in sub-Saharan Africa and South Asia. Between November 2016 and January 2019, children were recruited at hospital admission and classified as: not-wasted (NW), moderately-wasted (MW), severely-wasted (SW), or having nutritional oedema (NO). We describe earlier (discharge to 45-days) and later (45- to 180-days) changes in length-for-age [LAZ], weight-for-age [WAZ], mid-upper arm circumference [MUACZ], weight-for-length [WLZ] z-scores, and clinical, nutritional, and socioeconomic correlates. Findings: We included 2472 children who survived to 180-days post-discharge: NW, 960 (39%); MW, 572 (23%); SW, 682 (28%); and NO, 258 (10%). During 180-days, LAZ decreased in NW (−0.27 [−0.36, −0.19]) and MW (−0.23 [−0.34, −0.11]). However, all groups increased WAZ (NW, 0.21 [95% CI: 0.11, 0.32]; MW, 0.57 [0.44, 0.71]; SW, 1.0 [0.88, 1.1] and NO, 1.3 [1.1, 1.5]) with greatest gains in the first 45-days. Of children underweight (
Ecological and evolutionary dynamics of cell-virus-virophage systems.
Microbial eukaryotes, giant viruses and virophages form a unique hyperparasitic system. Virophages are parasites of the virus transcription machinery and can interfere with virus replication, resulting in a benefit to the eukaryotic host population. Surprisingly, virophages can integrate into the genomes of their cell or virus hosts, and have been shown to reactivate during coinfection. This raises questions about the role of integration in the dynamics of cell-virus-virophage systems. We use mathematical models and computational simulations to understand the effect of virophage integration on populations of cells and viruses. We also investigate multicellularity and programmed cell-death (PCD) as potential antiviral defence strategies used by cells. We found that virophages which enter the cell independently of the host virus, such as Mavirus, are expected to integrate commonly into the genomes of their cell hosts. Our models suggest that integrations from virophages without an independent mode of entry like Sputnik, are less likely to become fixed in the cell host population. Alternatively, we found that Sputnik virophages can stably persist integrated in the virus population, as long as they do not completely inhibit virus replication. We also show that increasing virophage inhibition can stabilise oscillatory dynamics, which may explain the long-term persistence of viruses and virophages in the environment. Our results demonstrate that inhibition by virophages and multicellularity are effective antiviral strategies that may act in synergy against viral infection in microbial species.
Data from Tumor pH and Protein Concentration Contribute to the Signal of Amide Proton Transfer Magnetic Resonance Imaging
<div>Abstract<p>Abnormal pH is a common feature of malignant tumors and has been associated clinically with suboptimal outcomes. Amide proton transfer magnetic resonance imaging (APT MRI) holds promise as a means to noninvasively measure tumor pH, yet multiple factors collectively make quantification of tumor pH from APT MRI data challenging. The purpose of this study was to improve our understanding of the biophysical sources of altered APT MRI signals in tumors. Combining <i>in vivo</i> APT MRI measurements with <i>ex vivo</i> histological measurements of protein concentration in a rat model of brain metastasis, we determined that the proportion of APT MRI signal originating from changes in protein concentration was approximately 66%, with the remaining 34% originating from changes in tumor pH. In a mouse model of hypopharyngeal squamous cell carcinoma (FaDu), APT MRI showed that a reduction in tumor hypoxia was associated with a shift in tumor pH. The results of this study extend our understanding of APT MRI data and may enable the use of APT MRI to infer the pH of individual patients' tumors as either a biomarker for therapy stratification or as a measure of therapeutic response in clinical settings.</p>Significance:<p>These findings advance our understanding of amide proton transfer magnetic resonance imaging (APT MRI) of tumors and may improve the interpretation of APT MRI in clinical settings.</p></div>
Exploring the burden, prevalence and associated factors of chronic musculoskeletal pain in migrants from North Africa and Middle East living in Europe: a scoping review
Background: Immigrants are exposed to numerous risk factors that may contribute to the development of chronic musculoskeletal pain. Recent political and environmental crises in North Africa and the Middle East have led to an increase in immigration to Europe that has challenged the healthcare system and especially the management of chronic conditions. Objective: The aims of this scoping review are to investigate the burden, prevalence, and associated factors of chronic musculoskeletal pain in immigrants from North Africa and the Middle East in Europe during the last decade. The intentions of the review are to inform healthcare policymakers, to identify gaps in the literature, and aid the planning of future research. Design: Online databases Medline, Embase, PubMed and Web of Science were used to identify epidemiological studies published from2012–2022 examining chronic pain in populations from North Africa and the Middle East with a migration background residing in Europe. Results: In total eleven studies were identified conducted in Norway (n = 3), Denmark (n = 3), Germany (n = 1), Austria (n = 1), Sweden (n = 1), and Switzerland (n = 1). Among the identified studies, eight studies were cross-sectional (n = 8), two were prospective cohort studies (n = 2) and one was a retrospective cohort study (n = 1). Data suggested that chronic pain is more prevalent, more widespread, and more severe in people with than without a migration background. Furthermore, immigrants who have resided in the destination country for a longer period experience a higher prevalence of chronic pain compared to those in the early phases of migration. The following factors were found to be associated with chronic pain in this population: female gender, lower education, financial hardship, being underweight or obese, time in transit during migration, experience of trauma, immigration status, anxiety, depression, and post-traumatic stress disorder. Conclusion: Several gaps in the literature were identified. Research is limited in terms of quantity and quality, does not reflect actual immigration trends, and does not account for immigration factors. Prospective cohort studies with long follow-ups would aid in improving prevention and management of chronic pain in populations with a migration background. In particular, they should reflect actual immigration trajectories, account for immigration factors, and have valid comparison groups in the countries of origin, transit and destination.
Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases.
BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. METHODS: Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness. RESULTS: Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%-94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock. CONCLUSION: Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology.
The effects of inhaled corticosteroids on healthy airways
Background: The effects of inhaled corticosteroids (ICS) on healthy airways are poorly defined. Objectives: To delineate the effects of ICS on gene expression in healthy airways, without confounding caused by changes in disease-related genes and disease-related alterations in ICS-responsiveness. Methods: Randomised open-label bronchoscopy study of high dose ICS therapy in 30 healthy adult volunteers randomised 2:1 to i) fluticasone propionate 500 mcg bd daily or, ii) no treatment, for 4 weeks. Laboratory staff were blinded to allocation. Biopsies and brushings were analysed by immunohistochemistry, bulk RNA sequencing, DNA methylation array and metagenomics. Results: ICS induced small between-group differences in blood and lamina propria eosinophil numbers, but not in other immunopathological features, blood neutrophils, FeNO, FEV1, microbiome or DNA methylation. ICS treatment upregulated 72 genes in brushings and 53 genes in biopsies, and downregulated 82 genes in brushings and 416 genes in biopsies. The most downregulated genes in both tissues were canonical markers of type-2 inflammation (FCER1A, CPA3, IL33, CLEC10A, SERPINB10 and CCR5), T cell-mediated adaptive immunity (TARP, TRBC1, TRBC2, PTPN22, TRAC, CD2, CD8A, HLA-DQB2, CD96, PTPN7), B cell immunity (CD20, immunoglobulin heavy and light chains), and innate immunity, including CD48, Hobit, RANTES, Langerin and GFI1. An IL-17-dependent gene signature was not upregulated by ICS. Conclusions: In healthy airways, 4-week ICS exposure reduces gene expression related to both innate and adaptive immunity, and reduces markers of type-2 inflammation. This implies that homeostasis in health involves tonic type-2 signalling in the airway mucosa, which is exquisitely sensitive to ICS. Registered at ClincialTrials.gov: NCT02476825
Nanomedicines for the Delivery of Biologics.
A special symposium of the Academy of Pharmaceutical Sciences Nanomedicines Focus Group reviewed the current status of the use of nanomedicines for the delivery of biologics drugs. This meeting was particularly timely with the recent approval of the first siRNA-containing product Onpattro™ (patisiran), which is formulated as a lipid nanoparticle for intravenous infusion, and the increasing interest in the use of nanomedicines for the oral delivery of biologics. The challenges in delivering such molecules were discussed with specific emphasis on the delivery both across and into cells. The latest developments in Molecular Envelope Technology® (Nanomerics Ltd, London, UK), liposomal drug delivery (both from an academic and industrial perspective), opportunities offered by the endocytic pathway, delivery using genetically engineered viral vectors (PsiOxus Technologies Ltd, Abingdon, UK), Transint™ technology (Applied Molecular Transport Inc., South San Francisco, CA, USA), which has the potential to deliver a wide range of macromolecules, and AstraZeneca's initiatives in mRNA delivery were covered with a focus on their uses in difficult to treat diseases, including cancers. Preclinical data were presented for each of the technologies and where sufficiently advanced, plans for clinical studies as well as early clinical data. The meeting covered the work in progress in this exciting area and highlighted some key technologies to look out for in the future.
Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.
Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conformations can arise from these predictions despite not being present in the training data. Here we have used ABodyBuilder2, a deep learning antibody structure predictor, to predict the structures of ~1.5M paired antibody sequences. We examined the predicted structures of the canonical CDR loops and found that most of these predictions fall into the already described CDR canonical form structural space. We also found a small number of "new" canonical clusters composed of heterogeneous sequences united by a common sequence motif and loop conformation. Analysis of these novel clusters showed their origins to be either shapes seen in the training data at very low frequency or shapes seen at high frequency but at a shorter sequence length. To evaluate explicitly the ability of ABodyBuilder2 to extrapolate, we retrained several models whilst withholding all antibody structures of a specific CDR loop length or canonical form. These "starved" models showed evidence of generalisation across CDRs of different lengths, but they did not extrapolate to loop conformations which were highly distinct from those present in the training data. However, the models were able to accurately predict a canonical form even if only a very small number of examples of that shape were in the training data. Our results suggest that deep learning protein structure prediction methods are unable to make completely out-of-domain predictions for CDR loops. However, in our analysis we also found that even minimal amounts of data of a structural shape allow the method to recover its original predictive abilities. We have made the ~1.5 M predicted structures used in this study available to download at https://doi.org/10.5281/zenodo.10280181.