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COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2:a prospective observational cohort study
No full textThe Delta (B.1.617.2) variant was the predominant UK circulating SARS-CoV-2 strain between May and December 2021. How Delta infection compares with previous variants is unknown. This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly the predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. 3581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta versus Alpha infection (including fever, sore throat, and headache) and some vice versa (dyspnoea). Symptom burden in the first week was higher with Delta versus Alpha infection; however, the odds of any given symptom lasting ≥ 7 days was either lower or unchanged. Illness duration ≥ 28 days was lower with Delta versus Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.49) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly reduced the risk of Delta infection (by 69-84%). We conclude that COVID-19 from Delta or Alpha infections is similar. The Delta variant is more transmissible than Alpha; however, current vaccines showed good efficacy against disease. This research framework can be useful for future comparisons with new emerging variants
COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2:a prospective observational cohort study
No full textThe Delta (B.1.617.2) variant was the predominant UK circulating SARS-CoV-2 strain between May and December 2021. How Delta infection compares with previous variants is unknown. This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly the predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. 3581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta versus Alpha infection (including fever, sore throat, and headache) and some vice versa (dyspnoea). Symptom burden in the first week was higher with Delta versus Alpha infection; however, the odds of any given symptom lasting ≥ 7 days was either lower or unchanged. Illness duration ≥ 28 days was lower with Delta versus Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.49) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly reduced the risk of Delta infection (by 69-84%). We conclude that COVID-19 from Delta or Alpha infections is similar. The Delta variant is more transmissible than Alpha; however, current vaccines showed good efficacy against disease. This research framework can be useful for future comparisons with new emerging variants
Southampton, Bristol, Cardiff, Exeter, KCL, UCL Royal Free Block Allocation Group (BAG)
No full textThis BAG coordinates activities of groups from the South of the UK. The focus is on projects in immunology, transcriptional regulation, and enzymology. Particular strengths are antimicrobial resistance research (AMR), drug development, and the macromolecular complexes that several of our groups target. A highlighted presented with mid-term report is rational drug design for antibodies (biologicals) in cancer immunology (Southampton). We are interested in dynamic structural biology and use spectroscopy and SAXS in addition to gain this insight; several members of this bag are also active users of ID29 serial. Our projects listed here apply for time on crystallographic beamlines, SAXS, and spectroscopy (BM07 and icOS)
Silence Speaks Volumes:The Role of Workplace Ostracism and Ethical Leadership in Shaping Moral Identity at Work and Ethical Voice
No full textDrawing upon an integrated perspective based on working self-concept theory, we propose that being ostracized in the workplace undermines employees’ moral identity at work and thus their engagement in ethical voice behaviors. We also propose that ethical leadership can mitigate the detrimental effects of workplace ostracism. In Study 1 (N = 291), time-lagged data revealed a mediation effect of moral identity at work, even controlling for ego depletion and moral emotions. In Study 2, results from an employee sample in China (N = 144) reveal that workplace ostracism is more detrimental to employees’ moral identity at work when ethical leadership is lower compared to higher. In Studies 3 and 4, we provide additional evidence to support our model using an experiment in which we manipulate workplace ostracism and ethical leadership (N = 283) as well as multi-sourced, time-lagged field data (N = 125), respectively. Implications for theory and practice are discussed
Secondary natural vegetation gains in the Atlantic Forest do not offset losses of carbon stocks and conservation of priority areas
No full textSince secondary natural vegetation cover (NVC) constitutes an important factor for the provision of ecosystem services (e.g., helping to tackle both the climate and biodiversity crises), understanding its dynamics is essential for effective forest restoration. Yet, this has seldom been evaluated in prior studies. We examined 37 years (1985–2021) of primary NVC loss, secondary NVC dynamics (persistent and ephemeral regeneration), and their impacts on carbon stocks and on the conservation of priority areas in Brazil's Atlantic Forest biome, a global biodiversity hotspot. We developed a new framework analyzing spatial landscape configurations over time, and found that Atlantic Forest NVC decreased by 4.2 Mha driven by a gross loss of 12.8 Mha of primary NVC (~1.4 Gt of carbon lost). Secondary NVC gained 8.6 Mha (~0.170 Gt of carbon, with potential for ~0.987 Gt in 80 years) but ephemeral regeneration (i.e., loss of secondary NVC) resulted in a loss of 3.8 Mha. Deforestation caused a net loss of 1.2 Mha in priority conservation areas. Results of this study demonstrate that understanding the dynamics of ephemeral regeneration is important for evaluating restoration efforts and ecosystem services in the Atlantic Forest. Our study also demonstrates that secondary forest regeneration plays an important role in reconnecting landscapes, although its instability threatens biodiversity and ecosystem services as it fails to offset the loss of primary vegetation. Thus, halting deforestation remains the single most urgent and vital action to prevent irreversible biodiversity loss and reduce carbon emissions
JUE insight:Efficiency of bus priority infrastructure
No full textWe use bus GPS data across 500 routes to estimate the impact of priority infrastructure on buses’ speed and ridership in Chile. Almost 100 million bus trips allow us to leverage within-route variation in the proportion of the route in which buses travel along bus lanes or Bus Rapid Transit (BRT) corridors. Corridors increase bus speeds by 20% at peak hours. Bus lanes, often seen as an equally effective but cheaper alternative to a BRT corridor, are, on average, ineffective. However, bus lanes achieve the same travel time savings as BRT corridors only when fully isolated from private vehicles, coupled with monitoring cameras and enforcement.</p
Joint detection of psychosis or bipolar disorder risk in clinical practice in the UK:development and validation of a clinical prediction model
No full textBackgroundEfficient detection of individuals at risk of developing psychotic disorders (PSY) or bipolar disorders (BD) is the first critical step to improving mental health outcomes in young people. A novel, transdiagnostic approach to jointly detect individuals at risk for either PSY or BD would maximise the impact of prevention. The aim of the current study is to develop and validate an individualised prediction model to detect the risk of developing PSY or BD in the UK.MethodsThis RECORD- and TRIPOD+AI-compliant study describes the development and validation of a clinical prediction model to estimate the risk of developing PSY or BD using data from patients with an index diagnosis of a non-organic, non-PSY and non-BD mental disorder recorded in electronic health records from South London and Maudsley (SLaM in the UK) secondary mental healthcare between 1st January 2008 and 10th August 2021. Exclusion criteria included receiving long-acting injectables or clozapine before BD/PSY diagnosis, no recorded contact with SLaM services after index date and an index date falling within the period 01/01/2008-30/06/2008. A LASSO-regularised Cox proportional hazards model was developed to estimate the 6-year risk of developing PSY or BD, incorporating sociodemographic and clinical predictors at index date (n=5), whereas medication (n=4), hospitalisation (n=2) and natural language processing-derived symptom and substance use (n=66) predictors were derived using a 6-month look-back period. Model performance was assessed using internal–external validation, sequentially leaving one borough out for testing and averaging performance across all boroughs. The final model was fit with data across all the boroughs. Performance was assessed via discrimination (C-index), calibration (calibration slope, calibration-in-the-large) and potential clinical utility (decision curve analysis) during internal-external cross-validation. Individuals with lived experience of BD or PSY were not involved in the research or writing process.FindingsIn total, data from 127,868 patients were included. The sample was composed of 64,980 (50.8%) male, 62,711 (49.0%) female and 89 (0.1%) other gender. For self-assigned ethnicity, it had 71,390 (55.8%) white, 18,025 (14.1%) black, 7,257 (5.7%) other, 6,270 (4.9%) Asian and 5,022 (3.9%) mixed. The mean age was 33.4 years (SD: 18.8, IQR: 17.9-44.9). The cumulative risk incidence of PSY or BD was 0·0827 (95%CI:0·0784-0·0870) within six years (mean follow-up 622 days [SD:687]). The model showed the following performance in internal-external validation: C-index=0·78 (95%CI: 0·78-0·81); calibration slope=1·02, SD:0·14; calibration-in-the-large=0·06, SD:0·02. Decision curve analysis showed that use of the model would detect three additional PSY or BD cases early per 100 patients screened compared to default assessment strategies.InterpretationsThis study shows that the transdiagnostic clinical prediction model can identify patients at risk of developing PSY or BD and displayed excellent performance. Such a novel approach would enable systematic early detection of young people at risk of PSY or BD, advancing preventive care in real-world clinical practice
The <sup>68</sup>Ga-siderophore approach to infection imaging:evaluation of [68Ga]Ga-DFO in patients with vascular graft infection
No full textPurpose: Gallium-68 complexes with siderophores, typically isostructural with their iron(III) analogues and recognized by microbial Fe(III)-siderophore complex receptors, are candidates for PET imaging of microbial infection. Here we evaluate [68Ga]Ga-desferrioxamine-B complex ([68Ga]Ga-DFO) for imaging in patients with infected aortic grafts.Methods: The trial was registered on clinical trials.gov, NCT05285072 registered 16 March 2022. [68Ga]Ga-DFO was produced from 68Ga-generator eluate in acetate buffer and characterized by radioHPLC, iTLC and LCMS. Its stability in human serum was evaluated in vitro by protein precipitation and size exclusion chromatography, and its biodistribution, pharmacokinetics and dosimetry determined by PET imaging in healthy mice. PET imaging in two patients with aortic graft infections was performed over 90 minutes, with blood and urine sampling in one patient.Results: Analysis of [68Ga]Ga-DFO identified it as a 1:1 complex of 68Ga with DFO, with >95% radiochemical purity, stable in human serum in the absence of bicarbonate at high DFO:protein ratio, but not in the presence of bicarbonate with low DFO:protein ratio. It was rapidly cleared renally from healthy mice but in humans, clearance was much slower consistent with significant protein binding. There was no specific uptake at infection sites identified by [18F]FDG scanning.Conclusion: We conclude that future clinical evaluation of the [68Ga]Ga-siderophore approach to infection imaging requires a deeper understanding of the kinetics and thermodynamics of transchelation of 68Ga between the siderophores and transferrin.<br/
A Fifth Face? The Evolving Threat of Nuclear Terrorism in the Age of Artificial Intelligence
No full textThe contemporary era is increasingly influenced by artificial intelligence (AI), a technology whose rapid development is reshaping industries, societies, and security around the world. From increasing the efficiency of complex systems to establishing new forms of communication, the transformative potential of AI has become hard to ignore. Yet despite its many benefits, AI also carries the potential to exacerbate existing security vulnerabilities and create new threats. These risks are particularly acute in the nuclear context, where an uncontrolled radiological release would threaten human and ecological life. Although the nuclear community is more sanguine about the prospect of nuclear terrorism two decades on from the alarmism of the 9/11 era, the threat still exists; and into the mix today is the growing risk that non-state actors could exploit AI for nefarious goals. Such use could manifest in a number of ways: terrorist groups might use AI tools to identify security gaps and automate reconnaissance of nuclear facilities; they might also use AI to manipulate cyber-physical systems to bypass important security measures; and in another scenario, AI could be used by non-state actors who intend to acquire or weaponize nuclear capabilities or sabotage nuclear facilities. With the visible lack of recent international attention on the specter of nuclear terrorism, it can be argued that with the advent of AI the risks are higher than at any point since the post-9/11 era. And this is in the context of official threat assessments that continue to emphasize the threats posed by non-state actors seeking diverse methods to cause harm for political purposes. As with all technologies, AI carries benefits as well as risks. Nuclear security involves the protection of nuclear facilities and materials, so advanced technologies can create efficiencies and improvements in the business of protecting critical infrastructure. For example, AI can be used for enhanced threat detection, predictive analytics, and insider risk mitigation. Thus, AI presents a sort of paradox. Most of its capabilities, including algorithms and computational techniques, are easily accessible and can be utilized to facilitate innovation within civilian sectors. However, AI’s ease of access and adaptive nature is equally attractive to those who seek to do harm, and could just as easily be utilized to enhance extremist violence.As AI introduces new elements into the nuclear security landscape, a paradigm shift is required in the nuclear industry. This shift should cover how risks are assessed as well as how mitigation strategies are formulated and implemented. In particular, AI has the potential to significantly lower the level of technical capabilities that have been traditionally required for non-state actors to plan and execute attacks against nuclear assets. With AI tools for image analysis, data processing, and complex system modeling now more accessible, specialized knowledge and software that were once exclusive to states have become more widespread. Consequently, non-state groups with limited capabilities could potentially leverage AI tools for reconnaissance, attack planning, or malicious campaigns against nuclear targets. Likewise, AI might increase the potential for a highly sophisticated cyber-physical attack against the digital control systems of nuclear facilities. The pace of AI development may outstrip existing governance structures and security protocols, which in turn could erode a critical window of vulnerability. In addition, emerging technologies tend to develop in an environment where regulation is still to catch up. Such dilemmas, where defensive and regulatory capacities lag behind the offensive potential, mean that AI tools may become accessible to threat actors before effective countermeasures are in place. This is no longer a theoretical concern but a real vulnerability that needs to be addressed. However, research into the malicious applications of AI remains underdeveloped, and the gap is especially pronounced when it comes to studying AI-enhanced terrorism with a chemical, biological, radiological, and nuclear (CBRN) lens.This article seeks to fill the scholarly gap through its exploration of the nexus of terrorism, AI, and nuclear security. It examines whether use of AI can lower the threshold for planning, optimizing attack vectors, and accessing sensitive materials—all of which make a nuclear terrorist attack more likely. The contributions of the article to the literature are twofold. First, it seeks to reignite debates over nuclear alarmism, revisiting such a discussion through the contemporary lens of AI and emerging technologies. Here, the article argues that previous dismissals of nuclear terrorism as unlikely under this paradigm are no longer true, as the “tremendous effort” of conducting a nuclear terrorist attack has arguably been lessened with the advent of AI. Second, it seeks to refresh nuclear scholarship and scenario building exercises, with a focus on updating Charles Ferguson and William Potter’s seminal work The Four Faces of Nuclear Terrorism for the digital age. In so doing, the article revisits the dormant debate of nuclear alarmism and pessimism over nuclear terrorism to argue that an updated AI lens requires a reckoning on the new vectors and manifestations of nuclear terrorism.<br/