Entamoeba bangladeshi nov. sp., Bangladesh.

: TO THE EDITOR: Diarrheal diseases have a major effect on global health, particularly the health of malnourished children (1). The enteric parasites Entamoeba histolytica and E. moshkovskii are potential causes of diarrheal disease in children (2). For the past 20 years, we have been studying Entamoeba infections in children from the urban slum of Mirpur in Dhaka, Bangladesh (3)

A murine specific expansion of the Rhox cluster involved in embryonic stem cell biology is under natural selection

BACKGROUND: The rodent specific reproductive homeobox (Rhox) gene cluster on the X chromosome has been reported to contain twelve homeobox-containing genes, Rhox1-12. RESULTS: We have identified a 40 kb genomic region within the Rhox cluster that is duplicated eight times in tandem resulting in the presence of eight paralogues of Rhox2 and Rhox3 and seven paralogues of Rhox4. Transcripts have been identified for the majority of these paralogues and all but three are predicted to produce full-length proteins with functional potential. We predict that there are a total of thirty-two Rhox genes at this genomic location, making it the most gene-rich homoeobox cluster identified in any species. From the 95% sequence similarity between the eight duplicated genomic regions and the synonymous substitution rate of the Rhox2, 3 and 4 paralogues we predict that the duplications occurred after divergence of mouse and rat and represent the youngest homoeobox cluster identified to date. Molecular evolutionary analysis reveals that this cluster is an actively evolving region with Rhox2 and 4 paralogues under diversifying selection and Rhox3 evolving neutrally. The biological importance of this duplication is emphasised by the identification of an important role for Rhox2 and Rhox4 in regulating the initial stages of embryonic stem (ES) cell differentiation. CONCLUSION: The gene rich Rhox cluster provides the mouse with significant biological novelty that we predict could provide a substrate for speciation. Moreover, this unique cluster may explain species differences in ES cell derivation and maintenance between mouse, rat and human

The utility and feasibility of routine use of a patient-reported outcome measure in paediatric dentistry

Within healthcare services, there is increasing emphasis to incorporate patient-reported outcome measures (PROMs), rather than relying solely on clinical outcomes. A 12-item caries-specific measure (CARIES-QC) has been developed and validated for children aged 5–16 years. To date, the routine use of PROMs in paediatric dentistry new patient clinics (NPC) has not been reported. The aim was to conduct a pilot study to assess the feasibility, utility and validity of routine use of a PROM in paediatric dentistry NPC in a UK teaching hospital. Children attending NPC over a four-week period were asked to complete CARIES-QC with an additional free-text box. Interviews were held with members of staff to assess the feasibility of using a PROM routinely. CARIES-QC was completed by 99 children. Almost half of the participants had caries (n = 49, 49.5%). CARIES-QC demonstrated good internal consistency (Cronbach’s alpha = 0.9) and reliability with the global question (r = 0.75, p = 0.01). Clinical staff valued the information provided by the PROM. An electronic delivery method would be beneficial to both clinical and administrative staff. CARIES-QC was able to capture impacts for children with a range of oral conditions. Its use aided treatment planning and future studies should investigate the use of an electronic delivery system to reduce the administrative burden

Grassmann Variables and the Jaynes-Cummings Model

This paper shows that phase space methods using a positive P type distribution function involving both c-number variables (for the cavity mode) and Grassmann variables (for the two level atom) can be used to treat the Jaynes-Cummings model. Although it is a Grassmann function, the distribution function is equivalent to six c-number functions of the two bosonic variables. Experimental quantities are given as bosonic phase space integrals involving the six functions. A Fokker-Planck equation involving both left and right Grassmann differentiation can be obtained for the distribution function, and is equivalent to six coupled equations for the six c-number functions. The approach used involves choosing the canonical form of the (non-unique) positive P distribution function, where the correspondence rules for bosonic operators are non-standard and hence the Fokker-Planck equation is also unusual. Initial conditions, such as for initially uncorrelated states, are used to determine the initial distribution function. Transformations to new bosonic variables rotating at the cavity frequency enables the six coupled equations for the new c-number functions (also equivalent to the canonical Grassmann distribution function) to be solved analytically, based on an ansatz from a 1980 paper by Stenholm. It is then shown that the distribution function is the same as that determined from the well-known solution based on coupled equations for state vector amplitudes of atomic and n-photon product states. The treatment of the simple two fermion mode Jaynes-Cummings model is a useful test case for the future development of phase space Grassmann distribution functional methods for multi-mode fermionic applications in quantum-atom optics.Comment: 57 pages, 0 figures. Version

Increased dispersion of oil from a deep water seabed release by energetic mesoscale eddies

Hydrodynamics play a critical role in determining the trajectory of an oil spill. Currents, stratification and mesoscale processes all contribute to how a spill behaves. Using an industry‑leading oil spill model, we compare forecasts of oil dispersion when forced with two different hydrodynamic models of the North-West European Shelf (7 km and 1.5 km horizontal resolution). This demonstrates how the trajectory of a deep water (>1000 m) release in the central Faroe-Shetland Channel is influenced by explicitly resolving mesoscale processes. The finer resolution hydrodynamic model dramatically enhances the horizontal dispersion of oil and transports pollutant further afield. This is a consequence of higher mesoscale variability. Stratification influences the depth of subsurface plume trapping and subsequently the far-field transport of oil. These results demonstrate that the choice of hydrodynamic model resolution is crucial when designing particle tracking or tracer release experiments

Quantum properties of transverse pattern formation in second-harmonic generation

We investigate the spatial quantum noise properties of the one dimensional transverse pattern formation instability in intra-cavity second-harmonic generation. The Q representation of a quasi-probability distribution is implemented in terms of nonlinear stochastic Langevin equations. We study these equations through extensive numerical simulations and analytically in the linearized limit. Our study, made below and above the threshold of pattern formation, is guided by a microscopic scheme of photon interaction underlying pattern formation in second-harmonic generation. Close to the threshold for pattern formation, beams with opposite direction of the off-axis critical wave numbers are shown to be highly correlated. This is observed for the fundamental field, for the second harmonic field and also for the cross-correlation between the two fields. Nonlinear correlations involving the homogeneous transverse wave number, which are not identified in a linearized analysis, are also described. The intensity differences between opposite points of the far fields are shown to exhibit sub-Poissonian statistics, revealing the quantum nature of the correlations. We observe twin beam correlations in both the fundamental and second-harmonic fields, and also nonclassical correlations between them.Comment: 18 pages, 17 figures, submitted to Phys. Rev.

Opportunities and challenges of Integral Projection Models for modelling host-parasite dynamics

Summary Epidemiological dynamics are shaped by and may in turn shape host demography. These feedbacks can result in hard to predict patterns of disease incidence. Mathematical models that integrate infection and demography are consequently a key tool for informing expectations for disease burden and identifying effective measures for control. A major challenge is capturing the details of infection within individuals and quantifying their downstream impacts to understand population-scale outcomes. For example, parasite loads and antibody titres may vary over the course of an infection and contribute to differences in transmission at the scale of the population. To date, to capture these subtleties, models have mostly relied on complex mechanistic frameworks, discrete categorization and/or agent-based approaches. Integral Projection Models (IPMs) allow variance in individual trajectories of quantitative traits and their population-level outcomes to be captured in ways that directly reflect statistical models of trait–fate relationships. Given increasing data availability, and advances in modelling, there is considerable potential for extending this framework to traits of relevance for infectious disease dynamics. Here, we provide an overview of host and parasite natural history contexts where IPMs could strengthen inference of population dynamics, with examples of host species ranging from mice to sheep to humans, and parasites ranging from viruses to worms. We discuss models of both parasite and host traits, provide two case studies and conclude by reviewing potential for both ecological and evolutionary research

Zoonosis emergence linked to agricultural intensification and environmental change

A systematic review was conducted by a multidisciplinary team to analyze qualitatively best available scientific evidence on the effect of agricultural intensification and environmental changes on the risk of zoonoses for which there are epidemiological interactions between wildlife and livestock. The study found several examples in which agricultural intensification and/or environmental change were associated with an increased risk of zoonotic disease emergence, driven by the impact of an expanding human population and changing human behavior on the environment. We conclude that the rate of future zoonotic disease emergence or reemergence will be closely linked to the evolution of the agriculture–environment nexus. However, available research inadequately addresses the complexity and interrelatedness of environmental, biological, economic, and social dimensions of zoonotic pathogen emergence, which significantly limits our ability to predict, prevent, and respond to zoonotic disease emergence

Exploring a novel linked dataset and building linked data analytics skills in Public Health Intelligence teams in Sussex

Objectives Public health intelligence teams in Sussex wanted to use newly linked health and social care data, to gain insights into local patterns of multi-morbidity, service use, service provision and socio-demographic data. In this study we report initial exploration of this new linked dataset, in a partnership between university and local authority analysts. Approach The Sussex Integrated Dataset (SID) comprises person-level health and social care data on residents and services users across Sussex. During a 6-month secondment, two analysts evaluated the number of data sources available for each individual, evaluated data quality for identifying long-term conditions, developed presentation methods to compare SID outputs on demographics and condition prevalence with open source or expected distributions, and identified the skills-mix and infrastructure required in local authorities for future work. They worked alongside the SID data processing team to inform and improve data quality; and with university data-scientists to learn prediction modelling. Results Analysts established an efficient querying system to investigate the breadth of data available, more thoroughly focusing on encounters and demographic data in all sources. Long-term conditions were identified through code lists in a range of NHS data sources, to enable consideration of multi-morbidity by demographic. A range of quality issues were identified, such as non-current patients being uploaded into the SID, distorting prevalence estimates, and GP practice populations that did not match expected figures published by NHS digital. Results were represented in multi-morbidity plots, maps, and theographs. Through this data exploration, we have been able to identify the skills-mix needed for local Public Health Intelligence teams to maximise the use of linked data to achieve Public Health objectives. Conclusion We have made many conceptual breakthroughs, particularly in understanding data quality, however still need a more complete understanding of quality issues in SID for public health outputs to have meaningful use. Further investigation into the patterns of service use, as well as modelling of multi-morbidity to make predictions and target interventions, will be key next steps