Antibody Fc Glycosylation Discriminates Between Latent and Active Tuberculosis

Background. Mycobacterium tuberculosis remains a global health problem and clinical management is complicated by difficulty in discriminating between latent infection and active disease. While M. tuberculosis-reactive antibody levels are heterogeneous, studies suggest that levels of IgG glycosylation differ between disease states. Here we extend this observation across antibody domains and M. tuberculosis specificities to define changes with the greatest resolving power. Methods. Capillary electrophoretic glycan analysis was performed on bulk non-antigen–specific IgG, bulk Fc domain, bulk Fab domain, and purified protein derivative (PPD)- and Ag85A-specific IgG from subjects with latent (n = 10) and active (n = 20) tuberculosis. PPD-specific isotype/subclass, PPD-specific antibody-dependent phagocytosis, cellular cytotoxicity, and natural killer cell activation were assessed. Discriminatory potentials of antibody features were evaluated individually and by multivariate analysis. Results. Parallel profiling of whole, Fc, and Fab domain-specific IgG glycosylation pointed to enhanced differential glycosylation on the Fc domain. Differential glycosylation was observed across antigen-specific antibody populations. Multivariate modeling highlighted Fc domain glycan species as the top discriminatory features, with combined PPD IgG titers and Fc domain glycans providing the highest classification accuracy. Conclusions. Differential glycosylation occurs preferentially on the Fc domain, providing significant discriminatory power between different states of M. tuberculosis infection and disease

A New Sustainability Model for Measuring Changes in Power and Access in Global Commodity Chains

High-value agricultural commodities face substantial economic, environmental and social sustainability challenges. As a result, commodity industries are adopting sustainable supply- and value-chain models to make production more efficient, traceable and risk-averse. These top-down models often focus on giving higher prices to smallholder producers. While an important component of sustainability, this focus on farm-gate prices has shown mixed results in part because they are less effective in highlighting the asymmetrical power relationships and the socio-economic and ecological complexity in high-value commodity production. Here, we use a novel method to measure and visualise changes in smallholder power in Madagascar’s northeast ‘vanilla triangle’—home to about 80% of the world’s high quality vanilla. Our results reveal the paradox that during the recent price surge an overall increase in smallholders’ multi-dimensional power to access economic benefits was accompanied by a decrease in many other equally important measures of sustainability. This illustrates how effective models for understanding global sustainable commodity chains should incorporate smallholders' perspectives that often emphasise complexity and uncertainty, and which aims to increase power and access for producers across both high and low price points

The association of cognitive functioning as measured by the DemTect with functional and clinical characteristics of COPD : results from the COSYCONET cohort

Alterations of cognitive functions have been described in COPD. Our study aimed to disentangle the relationship between the degree of cognitive function and COPD characteristics including quality of life (QoL). Data from 1969 COPD patients of the COSYCONET cohort (GOLD grades 1–4; 1216 male/ 753 female; mean (SD) age 64.9 ± 8.4 years) were analysed using regression and path analysis. The DemTect screening tool was used to measure cognitive function, and the St. George‘s respiratory questionnaire (SGRQ) to assess disease-specific QoL. DemTect scores were  =60 years of age. For statistical reasons, we used the average of both algorithms independent of age in all subsequent analyses. The DemTect scores were associated with oxygen content, 6-min-walking distance (6-MWD), C-reactive protein (CRP), modified Medical Research Council dyspnoea scale (mMRC) and the SGRQ impact score. Conversely, the SGRQ impact score was independently associated with 6-MWD, FVC, mMRC and DemTect. These results were combined into a path analysis model to account for direct and indirect effects. The DemTect score had a small, but independent impact on QoL, irrespective of the inclusion of COPD-specific influencing factors or a diagnosis of cognitive impairment. We conclude that in patients with stable COPD lower oxygen content of blood as a measure of peripheral oxygen supply, lower exercise capacity in terms of 6-MWD, and higher CRP levels were associated with reduced cognitive capacity. Furthermore, a reduction in cognitive capacity was associated with reduced disease-specific quality of life. As a potential clinical implication of this work, we suggest to screen especially patients with low oxygen content and low 6-MWD for cognitive impairment

Ethnic inequalities in older adults bowel cancer awareness: findings from a community survey conducted in an ethnically diverse region in England

Background To date, research exploring the public’s awareness of bowel cancer has taken place with predominantly white populations. To enhance our understanding of how bowel cancer awareness varies between ethnic groups, and inform the development of targeted interventions, we conducted a questionnaire study across three ethnically diverse regions in Greater London, England. Methods Data were collected using an adapted version of the bowel cancer awareness measure. Eligible adults were individuals, aged 60+ years, who were eligible for screening. Participants were recruited and surveyed, verbally, by staff working at 40 community pharmacies in Northwest London, the Harrow Somali association, and St. Mark’s Bowel Cancer Screening Centre. Associations between risk factor, symptom and screening awareness scores and ethnicity were assessed using multivariate regression. Results 1013 adults, aged 60+ years, completed the questionnaire; half were of a Black, Asian or Minority ethnic group background (n = 507; 50.0%). Participants recognised a mean average of 4.27 of 9 symptoms and 3.99 of 10 risk factors. Symptom awareness was significantly lower among all ethnic minority groups (all p’s less than 0.05), while risk factor awareness was lower for Afro-Caribbean and Somali adults, specifically (both p's less than 0.05). One in three adults (n = 722; 29.7%) did not know there is a Bowel Cancer Screening Programme. Bowel screening awareness was particularly low among Afro-Caribbean and Somali adults (both p's less than 0.05). CONCLUSION: Awareness of bowel cancer symptoms, risk factors and screening varies by ethnicity. Interventions should be targeted towards specific groups for whom awareness of screening and risk factors is low

Antibody attributes that predict the neutralization and effector function of polyclonal responses to SARS-CoV-2

BACKGROUND: While antibodies can provide significant protection from SARS-CoV-2 infection and disease sequelae, the specific attributes of the humoral response that contribute to immunity are incompletely defined. METHODS: We employ machine learning to relate characteristics of the polyclonal antibody response raised by natural infection to diverse antibody effector functions and neutralization potency with the goal of generating both accurate predictions of each activity based on antibody response profiles as well as insights into antibody mechanisms of action. RESULTS: To this end, antibody-mediated phagocytosis, cytotoxicity, complement deposition, and neutralization were accurately predicted from biophysical antibody profiles in both discovery and validation cohorts. These models identified SARS-CoV-2-specific IgM as a key predictor of neutralization activity whose mechanistic relevance was supported experimentally by depletion. CONCLUSIONS: Validated models of how different aspects of the humoral response relate to antiviral antibody activities suggest desirable attributes to recapitulate by vaccination or other antibody-based interventions

Film as architectural theory

Publications on architectural theory have predominantly taken on the form of text-based books, monographs, and articles. With the rise of transdisciplinary and practice-based research in architecture, new opportunities are opening up for other forms of architectural theory, such as film-based mediums, which promise to expand and alter the convention of the written practice of theory. Two possible types of filmic theory are presented here. One follows the method of ethnographic documentary filmmaking inspired by Sarah Pinkfilm-based mediums, which promise to expand and alter thellows the line of art house filmmaking inspired by Kathryn Rameyyn Rameyg inspired by Sarah Pinkfilm-based mediums, which promise to expand ae to expand ad mediums, which promise to expand a convention of the written practice of theory. or constructing knowledge, new discourses on filmic theory can be opened up. It is argued here that film as architectural theory is part of this new discourse, broadening the audience’u engagement with architecture through not only “readership” but also “viewership.

ChAdOx1 nCoV-19 (AZD1222) vaccine-induced Fc receptor binding tracks with differential susceptibility to COVID-19

Despite the success of COVID-19 vaccines, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern have emerged that can cause breakthrough infections. Although protection against severe disease has been largely preserved, the immunological mediators of protection in humans remain undefined. We performed a substudy on the ChAdOx1 nCoV-19 (AZD1222) vaccinees enrolled in a South African clinical trial. At peak immunogenicity, before infection, no differences were observed in immunoglobulin (Ig)G1-binding antibody titers; however, the vaccine induced different Fc-receptor-binding antibodies across groups. Vaccinees who resisted COVID-19 exclusively mounted FcγR3B-binding antibodies. In contrast, enhanced IgA and IgG3, linked to enriched FcγR2B binding, was observed in individuals who experienced breakthrough. Antibodies unable to bind to FcγR3B led to immune complex clearance and resulted in inflammatory cascades. Differential antibody binding to FcγR3B was linked to Fc-glycosylation differences in SARS-CoV-2-specific antibodies. These data potentially point to specific FcγR3B-mediated antibody functional profiles as critical markers of immunity against COVID-19

Trade-Offs Between Reducing Complex Terminology and Producing Accurate Interpretations from Environmental DNA: Comment on “Environmental DNA: What\u27s behind the term?” by Pawlowski et al., (2020)

In a recent paper, “Environmental DNA: What\u27s behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring,” Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. This terminology is based on categories that are often difficult to assign and uninformative, and it overlooks a fundamental distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data