Oxetanes: Recent Advances in Synthesis, Reactivity and Medicinal Chemistry

The 4-membered oxetane ring has been increasingly exploited for its behaviors, i.e. influence on physicochemical properties as a stable motif in medicinal chemistry, and propensity to undergo ring opening reactions as a synthetic intermediate. These applications have driven numerous studies into the synthesis of new oxetane derivatives. This review takes an overview of the literature for the synthesis of oxetane derivatives, concentrating on advances in the last 5 years up to the end of 2015. These methods are clustered by strategy for preparation of the ring (Sections 3 and 4), and further derivatisation of preformed oxetane-containing building blocks (Sections 5-7). Examples of the use of oxetanes in medicinal chemistry are reported, including a collation of oxetane derivatives appearing in recent patents for medicinal chemistry applications. Finally examples of oxetane derivatives in ring opening and ring expansion reactions are described

Oxetane ethers are formed reversibly in the lithium-catalyzed Friedel-Crafts alkylation of phenols with oxetanols: synthesis of dihydrobenzofurans, diaryloxetanes, and oxetane ethers

Studies on the mechanism and intermediate products in the Friedel–Crafts reaction between oxetanols and phenols are presented. Formation of O-alkylated intermediates is identified using 1H NMR spectroscopy, in a reversible formation of the kinetic oxetane ether products. An interesting relationship between the electronic nature of the nucleophile and the degree of O-alkylation is uncovered. For phenols substituted with an electron withdrawing group such as CN, oxetane ethers are the only products isolated regardless of reaction time. Increasing the electron rich nature of the phenol leads to an increased proportion of the thermodynamic C-alkylated Friedel–Crafts products after just one hour and as the sole product/s after extended reaction times. These studies have enabled a more complete catalytic cycle to be proposed. Using the same lithium catalyst and carefully selected reaction times, several examples of oxetane ethers are successfully isolated as novel bioisosteres for ester groups

The application of statistical network models in disease research

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Host social structure is fundamental to how infections spread and persist, and so the statistical modelling of static and dynamic social networks provides an invaluable tool to parameterise realistic epidemiological models. We present a practical guide to the application of network modelling frameworks for hypothesis testing related to social interactions and epidemiology, illustrating some approaches with worked examples using data from a population of wild European badgers Meles meles naturally infected with bovine tuberculosis. Different empirical network datasets generate particular statistical issues related to non-independence and sampling constraints. We therefore discuss the strengths and weaknesses of modelling approaches for different types of network data and for answering different questions relating to disease transmission. We argue that statistical modelling frameworks designed specifically for network analysis offer great potential in directly relating network structure to infection. They have the potential to be powerful tools in analysing empirical contact data used in epidemiological studies, but remain untested for use in networks of spatio-temporal associations. As a result, we argue that developments in the statistical analysis of empirical contact data are critical given the ready availability of dynamic network data from bio-logging studies. Furthermore, we encourage improved integration of statistical network approaches into epidemiological research to facilitate the generation of novel modelling frameworks and help extend our understanding of disease transmission in natural populations.M.J.S. is funded by a NERC standard grant (NE/M004546/1) awarded to R.A.M., D.P.C., D.J.H. and M.B., with the APHA team at Woodchester Park, UK (lead scientist is R.J.D.) as project partners

Seasonal variation in daily patterns of social contacts in the European badger Meles meles

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Social interactions among hosts influence the persistence and spread of infectious pathogens. Daily 20 and seasonal variation in the frequency and type of social interactions will play an important role in 21 disease epidemiology, and alongside other factors may have an influence on wider disease dynamics 22 by causing seasonal forcing of infection, especially if the seasonal variation experienced by a 23 population is considerable. We explored temporal variation in within-group contacts in a high-24 density population of European badgers Meles meles naturally-infected with bovine tuberculosis. 25 Summer contacts were more likely and of longer duration during the daytime, while the frequency 26 and duration of winter contacts did not differ between day and night. In spring and autumn within-27 group contacts peaked at dawn and dusk, corresponding with when they were of shortest duration 28 with reduced potential for aerosol transmission of pathogens. Summer and winter could be critical 29 for bovine tuberculosis transmission in badgers, due to the high frequency and duration of contacts 30 during resting periods, and we discuss the links between this result and empirical data. This study 31 reveals clear seasonality in daily patterns of contact frequency and duration in species living in stable 32 social groups, suggesting that changes in social contacts could drive seasonal forcing of infection in 33 wildlife populations even when the number of individuals interacting remains similar.MJS is funded by NERC grant NE/M004546/1 awarded to RAM, DPC, DJH and MB, with RJD and the 386 APHA team at Woodchester Park, UK as project partners. Data were collected for NW’s PhD, funded 387 by Defra. We thank Jared Wilson-Aggarwal and two anonymous reviewers for useful comments and 388 Keith Silk for providing the photograph for Figure 1

Social structure contains epidemics and regulates individual roles in disease transmission in a group-living mammal

This is the final version. Available from Wiley via the DOI in this record. Data accessibility: The original weighted adjacency matrix for the high‐density population of European badgers, as well as code used for simulating networks and disease simulations can be found online https://doi.org/10.5061/dryad.49n3878.Population structure is critical to infectious disease transmission. As a result, theoretical and empirical contact network models of infectious disease spread are increasingly providing valuable insights into wildlife epidemiology. Analyzing an exceptionally detailed dataset on contact structure within a high-density population of European badgers Meles meles, we show that a modular contact network produced by spatially structured stable social groups, lead to smaller epidemics, particularly for infections with intermediate transmissibility. The key advance is that we identify considerable variation among individuals in their role in disease spread, with these new insights made possible by the detail in the badger dataset. Furthermore, the important impacts on epidemiology are found even though the modularity of the Badger network is much lower than the threshold that previous work suggested was necessary. These findings reveal the importance of stable social group structure for disease dynamics with important management implications for socially structured populations.Natural Environment Research Council (NERC

A computational analysis of abnormal belief-updating processes and their association with psychotic experiences and childhood trauma in a UK birth cohort

BACKGROUND: Psychotic experiences emerge from abnormalities in perception and belief formation, and occur more commonly in those experiencing childhood trauma. Yet, which precise aspects of belief formation are atypical in psychosis is not well understood. We used a computational modelling approach to characterise belief-updating in young adults in the general population, examine their relationship with psychotic outcomes and trauma, and the extent to which they mediate the trauma-psychosis relationship. METHODS: We used data from 3,360 individuals from the Avon Longitudinal Study of Parents and Children birth cohort who completed assessments for psychotic outcomes, depression, anxiety, and two belief-updating tasks at age 24, and had data available on traumatic events assessed from birth to late adolescence. Unadjusted and adjusted regression and counterfactual mediation methods were used for the analyses. RESULTS: Basic behavioural measures of belief-updating ('draws to decision' and 'disconfirmatory updating') were not associated with psychotic experiences. However, computational modelling revealed an association between increased decision noise with both psychotic experiences and trauma exposure, although <3% of the trauma-psychotic experience association was mediated by decision noise. Belief-updating measures were also associated with intelligence and socio-demographic characteristics, confounding most of the associations with psychotic experiences. There was little evidence that belief-updating parameters were differentially associated with delusions compared to hallucinations, or that they were differentially associated with psychotic outcomes compared to depression or anxiety. CONCLUSIONS: These findings challenge the hypothesis that atypical belief-updating mechanisms (as indexed by the computational models and behavioural measures we employed) underlie the development of psychotic phenomena

Kinship dynamics: patterns and consequences of changes in local relatedness

This is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recordMounting evidence suggests that patterns of local relatedness can change over time in predictable ways, a process termed kinship dynamics. Kinship dynamics may occur at the level of the population or social group, where the mean relatedness across all members of the population or group changes over time, or at the level of the individual where an individual’s relatedness to its local group changes with age. Kinship dynamics are likely to have fundamental consequences for the evolution of social behaviour and life history because they alter the inclusive fitness payoffs to actions taken at different points in time. For instance, growing evidence suggests that individual kinship dynamics have shaped the evolution of menopause and age-specific patterns of helping and harming. To date, however, the consequences of kinship dynamics for social evolution have not been widely explored. Here we review the patterns of kinship dynamics that can occur in natural populations and highlight how taking a kinship dynamics approach has yielded new insights into behaviour and life history evolution. We discuss areas where analysing kinship dynamics could provide new insight into social evolution and we outline some of the challenges in predicting and quantifying kinship dynamics in natural populations.Natural Environment Research Council (NERC)Leverhulme Trus

Fear of predation drives stable and differentiated social relationships in guppies

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this record.Social relationships can have important consequences for fitness in animals. Whilst numerous studies have shown that individuals often join larger groups in response to perceived predation risk (i.e. fear of predation), the importance of predation risk in driving the formation and stability of social relationships within groups has been relatively ignored. We experimentally tested how predation threat influenced fine-scale social network structure using Trinidadian guppies (Poecilia reticulata). When perceived predation risk was high, individuals developed stable and more differentiated social ties compared to when perceived risk was low. Intriguingly, social differentiation coincided with shoals being somewhat smaller under high-perceived risk, suggesting a possible conflict between forming stable social relationships and larger social groups. Individuals most at risk of predation (large and bold individuals) showed the most exaggerated responses in several social measures. Taken together, we provide the first experimental evidence that proximate risk of predation can increase the intensity of social relationships and fine-scale social structure in animal populations.DPC acknowledges funding from the National Environmental Research Council (NE/E001181/1) and Leverhulme Trust (RPG-175) and SKD and DPC acknowledge funding from The Danish Council for Independent Research (DFF – 1323-00105)