The effective rate of influenza reassortment is limited during human infection

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.CJRI is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 101239/Z/13/Z) and received support from the National Science Foundation Research Coordination Network on Infectious Disease Evolution Across Scales. KK, ASL, CWW, and MTM were funded by NIGMS U54-GM111274, the MIDAS Center for Inference and Dynamics of Infectious Disease. ASL acknowledges support from the MSTP training grant number T32 GM007171. GJDS was supported by the Duke-NUS Signature Research Programme funded by the Ministry of Health, Singapore and by contract HHSN272201400006C from the National Institute of Allergy and Infectious Disease, National Institutes of Health, Department of Health and Human Services, USA. DEW, RAH, XL, AR, TBS, SRD and also the influenza whole genome sequencing were supported with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract HHSN272200900007C. GSG was funded by the Defense Advanced Research Projects Agency under grant number DARPA-N66001-07-C-2024. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Evolution Across Scales. KK, ASL, CWW, and MTM were funded by NIGMS U54- GM111274, the MIDAS Center for Inference and Dynamics of Infectious Disease. DEW, RAH, XL, AR, TBS, and SRD were supported with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract HHSN272200900007C. GSG was funded by the Defense Advanced Research Projects Agency under grant number DARPA-N66001-07-C-2024. This work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council

Family social support, community “social capital” and adolescents’ mental health and educational outcomes: a longitudinal study in England

Purpose To examine the associations between family social support, community “social capital” and mental health and educational outcomes. Methods The data come from the Longitudinal Study of Young People in England, a multi-stage stratified nationally representative random sample. Family social support (parental relationships, evening meal with family, parental surveillance) and community social capital (parental involvement at school, sociability, involvement in activities outside the home) were measured at baseline (age 13–14), using a variety of instruments. Mental health was measured at age 14–15 (GHQ-12). Educational achievement was measured at age 15–16 by achievement at the General Certificate of Secondary Education. Results After adjustments, good paternal (OR = 0.70, 95% CI 0.56–0.86) and maternal (OR = 0.65, 95% CI 0.53–0.81) relationships, high parental surveillance (OR = 0.81, 95% CI 0.69–0.94) and frequency of evening meal with family (6 or 7 times a week: OR = 0.77, 95% CI 0.61–0.96) were associated with lower odds of poor mental health. A good paternal relationship (OR = 1.27, 95% CI 1.06–1.51), high parental surveillance (OR = 1.37, 95% CI 1.20–1.58), high frequency of evening meal with family (OR = 1.64, 95% CI 1.33–2.03) high involvement in extra-curricular activities (OR = 2.57, 95% CI 2.11–3.13) and parental involvement at school (OR = 1.60, 95% CI 1.37–1.87) were associated with higher odds of reaching the educational benchmark. Participating in non-directed activities was associated with lower odds of reaching the benchmark (OR = 0.79, 95% CI 0.70–0.89). Conclusions Building social capital in deprived communities may be one way in which both mental health and educational outcomes could be improved. In particular, there is a need to focus on the family as a provider of support

Resources, Capabilities, and Routines in Public Organizations

States, state agencies, multilateral agencies, and other non-market actors are relatively under-studied in strategic management and organization science. While important contributions to the study of public actors have been made within the agency-theoretic and transaction-cost traditions, there is little research in political economy that builds on resource-based, dynamic capabilities, and behavioral approaches to the firm. Yet public organizations can be characterized as stocks of human and non-human resources, including routines and capabilities; they can possess excess capacity in these resources; and they may grow and diversify in predictable patterns according to behavioral and Penrosean logic. This paper shows how resource-based, dynamic capabilities, and behavioral approaches to understanding public agencies and organizations shed light on their nature and governance

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change

The effective rate of influenza reassortment is limited during human infection

10.1371/journal.ppat.1006203PLoS Pathogens132e100620

Evaluating the Impact of Uncertainties in Clearance and Exposure When Prioritizing Chemicals Screened in High-Throughput Assays

The toxicity-testing paradigm has evolved to include high-throughput (HT) methods for addressing the increasing need to screen hundreds to thousands of chemicals rapidly. Approaches that involve in vitro screening assays, in silico predictions of exposure concentrations, and pharmacokinetic (PK) characteristics provide the foundation for HT risk prioritization. Underlying uncertainties in predicted exposure concentrations or PK behaviors can significantly influence the prioritization of chemicals, though the impact of such influences is unclear. In the current study, a framework was developed to incorporate absorbed doses, PK properties, and in vitro dose–response data into a PK/pharmacodynamic (PD) model to allow for placement of chemicals into discrete priority bins. Literature-reported or predicted values for clearance rates and absorbed doses were used in the PK/PD model to evaluate the impact of their uncertainties on chemical prioritization. Scenarios using predicted absorbed doses resulted in a larger number of bin misassignments than those scenarios using predicted clearance rates, when comparing to bin placement using literature-reported values. Sensitivity of parameters on the model output of toxicological activity was examined across possible ranges for those parameters to provide insight into how uncertainty in their predicted values might impact uncertainty in activity