Mediated behavioural change in human-machine networks: exploring network characteristics, trust and motivation

Human-machine networks pervade much of contemporary life. Network change is the product of structural modifications along with differences in participant be-havior. If we assume that behavioural change in a human-machine network is the result of changing the attitudes of participants in the network, then the question arises whether network structure can affect participant attitude. Taking citizen par-ticipation as an example, engagement with relevant stakeholders reveals trust and motivation to be the major objectives for the network. Using a typology to de-scribe network state based on multiple characteristic or dimensions, we can pre-dict possible behavioural outcomes in the network. However, this has to be medi-ated via attitude change. Motivation for the citizen participation network can only increase in line with enhanced trust. The focus for changing network dynamics, therefore, shifts to the dimensional changes needed to encourage increased trust. It turns out that the coordinated manipulation of multiple dimensions is needed to bring about the desired shift in attitude.Comment: Paper submitted to SocInfo, organised by the Oxford Internet Institute, September 201

Heterologous infection and vaccination shapes immunity against SARS-CoV-2 variants

[Figure: see text].The impact of initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infecting strain on downstream immunity to heterologous variants of concern (VOC) is unknown. Studying a longitudinal healthcare worker cohort, we found that after three antigen exposures (infection+two vaccine doses), S1 antibody, memory B cells and heterologous neutralization of B.1.351, P.1 and B.1.617.2 plateaued, while B.1.1.7 neutralization and spike T cell responses increased. Serology using Wuhan Hu-1 spike receptor binding domain poorly predicted neutralizing immunity against VOCs. Neutralization potency against VOCs changed with heterologous virus encounter and number of antigen exposures. Neutralization potency fell differentially depending on targeted VOCs over 5-months from the second vaccine dose. Heterologous combinations of spike encountered during infection and vaccination shape subsequent cross-protection against VOC, with implications for future-proof next-generation vaccines

Visualisation of trust and quality information for geospatial dataset selection and use:Drawing trust presentation comparisons with B2C e-Commerce

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. Part of the problem arises from the inconsistent and patchy nature of data quality information, which makes intercomparison very difficult. Over recent years, the production and availability of geospatial data has significantly increased, facilitated by the recent explosion of Web-based catalogues, portals, standards and services, and by initiatives such as INSPIRE and GEOSS. Despite this significant growth in availability of geospatial data and the fact that geospatial datasets can, in many respects, be considered commercial products that are available for purchase online, consumer trust has to date received relatively little attention in the GIS domain. In this paper, we discuss how concepts of trust, trust models, and trust indicators (largely derived from B2C e-Commerce) apply to the GIS domain and to geospatial data selection and use. Our research aim is to support data users in more efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for purpose. To achieve this, we propose a GEO label – a decision support mechanism that visually summarises availability of key geospatial data informational aspects. We also present a Web service that was developed to support generation of dynamic GEO label representations for datasets by combining producer metadata (from standard catalogues or other published locations) with structured user feedback

Effect of a 2-week interruption in methotrexate treatment versus continued treatment on COVID-19 booster vaccine immunity in adults with inflammatory conditions (VROOM study): a randomised, open label, superiority trial

BACKGROUND: Immunosuppressive treatments inhibit vaccine-induced immunity against SARS-CoV-2. We evaluated whether a 2-week interruption of methotrexate treatment immediately after the COVID-19 vaccine booster improved antibody responses against the S1 receptor-binding domain (S1-RBD) of the SARS-CoV-2 spike protein compared with uninterrupted treatment in patients with immune-mediated inflammatory diseases. METHODS: We did an open-label, prospective, two-arm, parallel-group, multicentre, randomised, controlled, superiority trial in 26 hospitals in the UK. We recruited adults from rheumatology and dermatology clinics who had been diagnosed with an immune-mediated inflammatory disease (eg, rheumatoid arthritis, psoriasis with or without arthritis, axial spondyloarthritis, atopic dermatitis, polymyalgia rheumatica, and systemic lupus erythematosus) and who were taking low-dose weekly methotrexate (≤25 mg per week) for at least 3 months. Participants also had to have received two primary vaccine doses from the UK COVID-19 vaccination programme. We randomly assigned the participants (1:1), using a centralised validated computer randomisation program, to suspend methotrexate treatment for 2 weeks immediately after their COVID-19 booster (suspend methotrexate group) or to continue treatment as usual (continue methotrexate group). Participants, investigators, clinical research staff, and data analysts were unmasked, while researchers doing the laboratory analyses were masked to group assignment. The primary outcome was S1-RBD antibody titres 4 weeks after receiving the COVID-19 booster vaccine dose, assessed in the intention-to-treat population. This trial is registered with ISRCT, ISRCTN11442263; following the pre-planned interim analysis, recruitment was stopped early. FINDINGS: Between Sept 30, 2021 and March 3, 2022, we recruited 340 participants, of whom 254 were included in the interim analysis and had been randomly assigned to one of the two groups: 127 in the continue methotrexate group and 127 in the suspend methotrexate group. Their mean age was 59·1 years, 155 (61%) were female, 130 (51%) had rheumatoid arthritis, and 86 (34%) had psoriasis with or without arthritis. After 4 weeks, the geometric mean S1-RBD antibody titre was 22 750 U/mL (95% CI 19 314-26 796) in the suspend methotrexate group and 10 798 U/mL (8970-12 997) in the continue methotrexate group, with a geometric mean ratio (GMR) of 2·19 (95% CI 1·57-3·04; p<0·0001; mixed-effects model). The increased antibody response in the suspend methotrexate group was consistent across methotrexate dose, administration route, type of immune-mediated inflammatory disease, age, primary vaccination platform, and history of SARS-CoV-2 infection. There were no intervention-related serious adverse events. INTERPRETATION: A 2-week interruption of methotrexate treatment for people with immune-mediated inflammatory diseases resulted in enhanced boosting of antibody responses after COVID-19 vaccination. This intervention is simple, low-cost, and easy to implement, and could potentially translate to increased vaccine efficacy and duration of protection for susceptible groups. FUNDING: National Institute for Health and Care Research

Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection

BACKGROUND: The majority of those infected by ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the UK first wave (starting March 2020) did not require hospitalisation. Most had a short-lived mild or asymptomatic infection, while others had symptoms that persisted for weeks or months. We hypothesized that the plasma proteome at the time of first infection would reflect differences in the inflammatory response that linked to symptom severity and duration. METHODS: We performed a nested longitudinal case-control study and targeted analysis of the plasma proteome of 156 healthcare workers (HCW) with and without lab confirmed SARS-CoV-2 infection. Targeted proteomic multiple-reaction monitoring analysis of 91 pre-selected proteins was undertaken in uninfected healthcare workers at baseline, and in infected healthcare workers serially, from 1 week prior to 6 weeks after their first confirmed SARS-CoV-2 infection. Symptom severity and antibody responses were also tracked. Questionnaires at 6 and 12 months collected data on persistent symptoms. FINDINGS: Within this cohort (median age 39 years, interquartile range 30-47 years), 54 healthcare workers (44% male) had PCR or antibody confirmed infection, with the remaining 102 (38% male) serving as uninfected controls. Following the first confirmed SARS-CoV-2 infection, perturbation of the plasma proteome persisted for up to 6 weeks, tracking symptom severity and antibody responses. Differentially abundant proteins were mostly coordinated around lipid, atherosclerosis and cholesterol metabolism pathways, complement and coagulation cascades, autophagy, and lysosomal function. The proteomic profile at the time of seroconversion associated with persistent symptoms out to 12 months. Data are available via ProteomeXchange with identifier PXD036590. INTERPRETATION: Our findings show that non-severe SARS-CoV-2 infection perturbs the plasma proteome for at least 6 weeks. The plasma proteomic signature at the time of seroconversion has the potential to identify which individuals are more likely to suffer from persistent symptoms related to SARS-CoV-2 infection. FUNDING INFORMATION: The COVIDsortium is supported by funding donated by individuals, charitable Trusts, and corporations including Goldman Sachs, Citadel and Citadel Securities, The Guy Foundation, GW Pharmaceuticals, Kusuma Trust, and Jagclif Charitable Trust, and enabled by Barts Charity with support from University College London Hospitals (UCLH) Charity. This work was additionally supported by the Translational Mass Spectrometry Research Group and the Biomedical Research Center (BRC) at Great Ormond Street Hospital

Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection.

BACKGROUND: SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. METHODS: Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements. FINDINGS: A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p<0.0001) but only anti-S1 measurements correlated with near-contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r = 0.57, p<0.0001). By 21 weeks' follow-up, 31/143 (21.7%) anti-S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling revealed faster clearance of anti-S1 compared to anti-NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%). INTERPRETATION: Mild SARS-CoV-2 infection is associated with heterogeneous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. In mild infection, anti-S1 serology alone may underestimate incident infections. The mechanisms that underpin faster clearance and lower rates of sustained anti-S1 production may impact on the longevity of humoral immunity. FUNDING: Charitable donations via Barts Charity, Wellcome Trust, NIHR

Rapid synchronous type 1 IFN and virus-specific T cell responses characterize first wave non-severe SARS-CoV-2 infections

Effective control of SARS-CoV-2 infection on primary exposure may reveal correlates of protective immunity to future variants, but we lack insights into immune responses before or at the time virus is first detected. We use blood transcriptomics, multiparameter flow cytometry, and T cell receptor (TCR) sequencing spanning the time of incident non-severe infection in unvaccinated virus-naive individuals to identify rapid type 1 interferon (IFN) responses common to other acute respiratory viruses and cell proliferation responses that discriminate SARS-CoV-2 from other viruses. These peak by the time the virus is first detected and sometimes precede virus detection. Cell proliferation is most evident in CD8 T cells and associated with specific expansion of SARS-CoV-2-reactive TCRs, in contrast to virus-specific antibodies, which lag by 1–2 weeks. Our data support a protective role for early type 1 IFN and CD8 T cell responses, with implications for development of universal T cell vaccines