The Accelerating COVID-19 Therapeutic Interventions and Vaccines Therapeutic-Clinical Working Group members gathered critical recommendations in follow-up to lessons learned manuscripts released earlier in the COVID-19 pandemic. Lessons around agent prioritization, preclinical therapeutics testing, master protocol design and implementation, drug manufacturing and supply, data sharing, and public–private partnership value are shared to inform responses to future pandemics.

Among nursing home outbreaks of coronavirus disease 2019 (COVID-19) with ≥3 breakthrough infections when the predominant severe acute respiratory coronavirus virus 2 (SARS-CoV-2) variant circulating was the SARS-CoV-2 δ (delta) variant, fully vaccinated residents were 28% less likely to be infected than were unvaccinated residents. Once infected, they had approximately half the risk for all-cause hospitalization and all-cause death compared with unvaccinated infected residents.

While unobscured and radio-quiet active galactic nuclei are regularly being found at redshifts $z > 6$ , their obscured and radio-loud counterparts remain elusive. We build upon our successful pilot study, presenting a new sample of low-frequency-selected candidate high-redshift radio galaxies (HzRGs) over a sky area 20 times larger. We have refined our selection technique, in which we select sources with curved radio spectra between 72–231 MHz from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. In combination with the requirements that our GLEAM-selected HzRG candidates have compact radio morphologies and be undetected in near-infrared $K_{\rm s}$ -band imaging from the Visible and Infrared Survey Telescope for Astronomy Kilo-degree Infrared Galaxy (VIKING) survey, we find 51 new candidate HzRGs over a sky area of approximately $1200\ \mathrm{deg}^2$ . Our sample also includes two sources from the pilot study: the second-most distant radio galaxy currently known, at $z=5.55$ , with another source potentially at $z \sim 8$ . We present our refined selection technique and analyse the properties of the sample. We model the broadband radio spectra between 74 MHz and 9 GHz by supplementing the GLEAM data with both publicly available data and new observations from the Australia Telescope Compact Array at 5.5 and 9 GHz. In addition, deep $K_{\rm s}$ -band imaging from the High-Acuity Widefield K-band Imager (HAWK-I) on the Very Large Telescope and from the Southern Herschel Astrophysical Terahertz Large Area Survey Regions $K_{\rm s}$ -band Survey (SHARKS) is presented for five sources. We discuss the prospects of finding very distant radio galaxies in our sample, potentially within the epoch of reionisation at $z \gtrsim 6.5$ .

Typhoid fever is a major cause of illness and mortality in low- and middle-income settings. We investigated the association of typhoid fever and rainfall in Blantyre, Malawi, where multi-drug-resistant typhoid has been transmitting since 2011. Peak rainfall preceded the peak in typhoid fever by approximately 15 weeks [95% confidence interval (CI) 13.3, 17.7], indicating no direct biological link. A quasi-Poisson generalised linear modelling framework was used to explore the relationship between rainfall and typhoid incidence at biologically plausible lags of 1–4 weeks. We found a protective effect of rainfall anomalies on typhoid fever, at a two-week lag (P = 0.006), where a 10 mm lower-than-expected rainfall anomaly was associated with up to a 16% reduction in cases (95% CI 7.6, 26.5). Extreme flooding events may cleanse the environment of S. Typhi, while unusually low rainfall may reduce exposure from sewage overflow. These results add to evidence that rainfall anomalies may play a role in the transmission of enteric pathogens, and can help direct future water and sanitation intervention strategies for the control of typhoid fever.

Internet-based surveys have expanded public opinion data collection at the expense of monitoring respondent attentiveness, potentially compromising data quality. Researchers now have to evaluate attentiveness ex-post. We propose a new proxy for attentiveness—response-time attentiveness clustering (RTAC)—that uses dimension reduction and an unsupervised clustering algorithm to leverage variation in response time between respondents and across questions. We advance the literature theoretically arguing that the existing dichotomous classification of respondents as fast or attentive is insufficient and neglects slow and inattentive respondents. We validate our theoretical classification and empirical strategy against commonly used proxies for survey attentiveness. In contrast to other methods for capturing attentiveness, RTAC allows researchers to collect attentiveness data unobtrusively without sacrificing space on the survey instrument.

Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function.

Given the equivocal literature on the relationship between internalizing symptoms and early adolescent alcohol use (AU) and AU disorder (AUD), the present study took a developmental perspective to understand how internalizing and externalizing symptoms may operate together in the etiology of AU and AUD. We pit the delayed onset and rapid escalation hypothesis (Hussong et al., 2011) against a synthesis of the dual failure model and the stable co-occurring hypothesis (Capaldi, 1992; Colder et al., 2013, 2018) to test competing developmental pathways to adolescent AU and AUD involving problem behavior, peer delinquency, and early initiation of AU. A latent transactional and mediational framework was used to test pathways to AUD spanning developmental periods before AU initiation (Mage = 11) to early and high risk for AUD (Mage = 14–15 and Mage = 17–18). The results supported three pathways to AUD. The first started with “pure” externalizing symptoms in early childhood and involved multiple mediators, including the subsequent development of co-occurring symptoms and peer delinquency. The second pathway involved stable co-occurring symptoms. Interestingly, chronically elevated pure internalizing symptoms did not figure prominently in pathways to AUD. Selection and socialization effects between early AU and peer delinquency constituted a third pathway.

A developing application of laser-driven currents is the generation of magnetic fields of picosecond–nanosecond duration with magnitudes exceeding $B=10~\text{T}$. Single-loop and helical coil targets can direct laser-driven discharge currents along wires to generate spatially uniform, quasi-static magnetic fields on the millimetre scale. Here, we present proton deflectometry across two axes of a single-loop coil ranging from 1 to 2 mm in diameter. Comparison with proton tracking simulations shows that measured magnetic fields are the result of kiloampere currents in the coil and electric charges distributed around the coil target. Using this dual-axis platform for proton deflectometry, robust measurements can be made of the evolution of magnetic fields in a capacitor coil target.

Childhood obesity is a common concern across global cities and threatens sustainable urban development. Initiatives to improve nutrition and encourage physical exercise are promising but are yet to exert significant influence on prevention. Childhood obesity in London is associated with distinct ethnic and socio-economic patterns. Ethnic inequalities in health-related behaviour endure, underpinned by inequalities in employment, housing, access to welfare services, and discrimination. Addressing these growing concerns requires a clearer understanding of the socio-cultural, environmental and economic contexts of urban living that promote obesity. We explore opportunities for prevention using asset based-approaches to nutritional health and well-being, with a particular focus on adolescents from diverse ethnic backgrounds living in London. We focus on the important role that community engagement and multi-sectoral partnership play in improving the nutritional outcomes of London's children. London's children and adolescents grow up in the rich cultural mix of a global city where local streets are characterised by diversity in ethnicities, languages, religions, foods, and customs, creating complex and fluid identities. Growing up with such everyday diversity we argue can enhance the quality of life for London's children and strengthen their social capital. The Determinants of young Adult Social well-being and Health longitudinal study of about 6500 of London's young people demonstrated the positive impact of cultural diversity. Born to parents from over a hundred countries and exposed to multi-lingual households and religious practices, they demonstrated strong psychological resilience and sense of pride from cultural straddling, despite material disadvantage and discrimination. Supporting the potential contribution of such socio-cultural assets is in keeping with the values of social justice and equitable and sustainable development. Our work signals the importance of community engagement and multisectoral partnerships, involving, for example, schools and faith-based organisations, to improve the nutrition of London's children.

The Virtual Personalities Model is a motive-based neural network model that provides both a psychological model and a computational implementation that explicates the dynamics and often large within-person variability in behavior that arises over time. At the same time the same model can produce—across many virtual personalities—between-subject variability in behavior that when factor analyzed yields familiar personality structure (e.g., the Big Five). First, we describe our personality model and its implementation as a neural network model. Second, we focus on detailing the neurobiological underpinnings of this model. Third, we examine the learning mechanisms, and their biological substrates, as ways that the model gets “wired up,” discussing Pavlovian and Instrumental conditioning, Pavlovian to Instrumental transfer, and habits. Finally, we describe the dynamics of how initial differences in propensities (e.g., dopamine functioning), wiring differences due to experience, and other factors could operate together to develop and change personality over time, and how this might be empirically examined. Thus, our goal is to contribute to the rising chorus of voices seeking a more precise neurobiologically based science of the complex dynamics underlying personality.