Hazard Analysis of Critical Control Points Assessment as a Tool to Respond to Emerging Infectious Disease Outbreaks

Highly pathogenic avian influenza virus (HPAI) strain H5N1 has had direct and indirect economic impacts arising from direct mortality and control programmes in over 50 countries reporting poultry outbreaks. HPAI H5N1 is now reported as the most widespread and expensive zoonotic disease recorded and continues to pose a global health threat. The aim of this research was to assess the potential of utilising Hazard Analysis of Critical Control Points (HACCP) assessments in providing a framework for a rapid response to emerging infectious disease outbreaks. This novel approach applies a scientific process, widely used in food production systems, to assess risks related to a specific emerging health threat within a known zoonotic disease hotspot. We conducted a HACCP assessment for HPAI viruses within Vietnam’s domestic poultry trade and relate our findings to the existing literature. Our HACCP assessment identified poultry flock isolation, transportation, slaughter, preparation and consumption as critical control points for Vietnam’s domestic poultry trade. Introduction of the preventative measures highlighted through this HACCP evaluation would reduce the risks posed by HPAI viruses and pressure on the national economy. We conclude that this HACCP assessment provides compelling evidence for the future potential that HACCP analyses could play in initiating a rapid response to emerging infectious diseases

Warped Riemannian metrics for location-scale models

The present paper shows that warped Riemannian metrics, a class of Riemannian metrics which play a prominent role in Riemannian geometry, are also of fundamental importance in information geometry. Precisely, the paper features a new theorem, which states that the Rao-Fisher information metric of any location-scale model, defined on a Riemannian manifold, is a warped Riemannian metric, whenever this model is invariant under the action of some Lie group. This theorem is a valuable tool in finding the expression of the Rao-Fisher information metric of location-scale models defined on high-dimensional Riemannian manifolds. Indeed, a warped Riemannian metric is fully determined by only two functions of a single variable, irrespective of the dimension of the underlying Riemannian manifold. Starting from this theorem, several original contributions are made. The expression of the Rao-Fisher information metric of the Riemannian Gaussian model is provided, for the first time in the literature. A generalised definition of the Mahalanobis distance is introduced, which is applicable to any location-scale model defined on a Riemannian manifold. The solution of the geodesic equation is obtained, for any Rao-Fisher information metric defined in terms of warped Riemannian metrics. Finally, using a mixture of analytical and numerical computations, it is shown that the parameter space of the von Mises-Fisher model of $n$-dimensional directional data, when equipped with its Rao-Fisher information metric, becomes a Hadamard manifold, a simply-connected complete Riemannian manifold of negative sectional curvature, for $n = 2,\ldots,8$. Hopefully, in upcoming work, this will be proved for any value of $n$.Comment: first version, before submissio

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Effect of changes in climate and emissions on future sulfate-nitrate-ammonium aerosol levels in the United States

Global simulations of sulfate, nitrate, and ammonium aerosols are performed for the present day and 2050 using the chemical transport model GEOS-Chem. Changes in climate and emissions projected by the IPCC A1B scenario are imposed separately and together, with the primary focus of the work on future inorganic aerosol levels over the United States. Climate change alone is predicted to lead to decreases in levels of sulfate and ammonium in the southeast U.S. but increases in the Midwest and northeast U.S. Nitrate concentrations are projected to decrease across the U.S. as a result of climate change alone. In the U.S., climate change alone can cause changes in annually averaged sulfate-nitrate-ammonium of up to 0.61 μg/m^3, with seasonal changes often being much larger in magnitude. When changes in anthropogenic emissions are considered (with or without changes in climate), domestic sulfate concentrations are projected to decrease because of sulfur dioxide emission reductions, and nitrate concentrations are predicted to generally increase because of higher ammonia emissions combined with decreases in sulfate despite reductions in emissions of nitrogen oxides. The ammonium burden is projected to increase from 0.24 to 0.36 Tg, and the sulfate burden to increase from 0.28 to 0.40 Tg S as a result of globally higher ammonia and sulfate emissions in the future. The global nitrate burden is predicted to remain essentially constant at 0.35 Tg, with changes in both emissions and climate as a result of the competing effects of higher precursor emissions and increased temperature

Acute effects of fine particulate air pollution on ST segment height: A longitudinal study

Background The mechanisms for the relationship between particulate air pollution and cardiac disease are not fully understood. Air pollution-induced myocardial ischemia is one of the potentially important mechanisms. Methods We investigate the acute effects and the time course of fine particulate pollution (PM2.5) on myocardium ischemic injury as assessed by ST-segment height in a community-based sample of 106 healthy non-smokers. Twenty-four hour beat-to-beat electrocardiogram (ECG) data were obtained using a high resolution 12-lead Holter ECG system. After visually identifying and removing all the artifacts and arrhythmic beats, we calculated beat-to-beat ST-height from ten leads (inferior leads II, III, and aVF; anterior leads V3 and V4; septal leads V1 and V2; lateral leads I, V5, and V6,). Individual-level 24-hour real-time PM2.5 concentration was obtained by a continuous personal PM2.5 monitor. We then calculated, on a 30-minute basis, the corresponding time-of-the-day specific average exposure to PM2.5 for each participant. Distributed lag models under a linear mixed-effects models framework were used to assess the regression coefficients between 30-minute PM2.5 and ST-height measures from each lead; i.e., one lag indicates a 30-minute separation between the exposure and outcome. Results The mean (SD) age was 56 (7.6) years, with 41% male and 74% white. The mean (SD) PM2.5 exposure was 14 (22) μg/m3. All inferior leads (II, III, and aVF) and two out of three lateral leads (I and V6), showed a significant association between higher PM2.5 levels and higher ST-height. Most of the adverse effects occurred within two hours after PM2.5 exposure. The multivariable adjusted regression coefficients β (95% CI) of the cumulative effect due to a 10 μg/m3 increase in Lag 0-4 PM2.5 on ST-I, II, III, aVF and ST-V6 were 0.29 (0.01-0.56) μV, 0.79 (0.20-1.39) μV, 0.52 (0.01-1.05) μV, 0.65 (0.11-1.19) μV, and 0.58 (0.07-1.09) μV, respectively, with all p < 0.05. Conclusions Increased PM2.5 concentration is associated with immediate increase in ST-segment height in inferior and lateral leads, generally within two hours. Such an acute effect of PM2.5 may contribute to increased potential for regional myocardial ischemic injury among healthy individuals

Development of FRET Assay into Quantitative and High-throughput Screening Technology Platforms for Protein–Protein Interactions

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research and is a very powerful tool in elucidating protein interactions in many cellular processes. Ubiquitination and SUMOylation are multi-step cascade reactions, involving multiple enzymes and protein–protein interactions. Here we report the development of dissociation constant (Kd) determination for protein–protein interaction and cell-based high-throughput screening (HTS) assay in SUMOylation cascade using FRET technology. These developments are based on steady state and high efficiency of fluorescent energy transfer between CyPet and YPet fused with SUMO1 and Ubc9, respectively. The developments in theoretical and experimental procedures for protein interaction Kd determination and cell-based HTS provide novel tools in affinity measurement and protein interaction inhibitor screening. The Kd determined by FRET between SUMO1 and Ubc9 is compatible with those determined with other traditional approaches, such as isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR). The FRET-based HTS is pioneer in cell-based HTS. Both Kd determination and cell-based HTS, carried out in 384-well plate format, provide powerful tools for large-scale and high-throughput applications

Parent-Completed Developmental Screening in Premature Children: A Valid Tool for Follow-Up Programs

Our goals were to (1) validate the parental Ages and Stages Questionnaires (ASQ) as a screening tool for psychomotor development among a cohort of ex-premature infants reaching 2 years, and (2) analyse the influence of parental socio-economic status and maternal education on the efficacy of the questionnaire. A regional population of 703 very preterm infants (<35 weeks gestational age) born between 2003 and 2006 were evaluated at 2 years by their parents who completed the ASQ, by a pediatric clinical examination, and by the revised Brunet Lezine psychometric test with establishment of a DQ score. Detailed information regarding parental socio-economic status was available for 419 infants. At 2 years corrected age, 630 infants (89.6%) had an optimal neuromotor examination. Overall ASQ scores for predicting a DQ score ≤85 produced an area under the receiver operator curve value of 0.85 (95% Confidence Interval:0.82–0.87). An ASQ cut-off score of ≤220 had optimal discriminatory power for identifying a DQ score ≤85 with a sensitivity of 0.85 (95%CI:0.75–0.91), a specificity of 0.72 (95%CI:0.69–0.75), a positive likelihood ratio of 3, and a negative likelihood ratio of 0.21. The median value for ASQ was not significantly associated with socio-economic level or maternal education. ASQ is an easy and reliable tool regardless of the socio-economic status of the family to predict normal neurologic outcome in ex-premature infants at 2 years of age. ASQ may be beneficial with a low-cost impact to some follow-up programs, and helps to establish a genuine sense of parental involvement

Learning by exporting:lessons from high-technology SMEs

We investigate the learning by exporting hypothesis by examining the effect of exporting on the subsequent innovation performance of a sample of high-technology SMEs based in the UK. We find evidence of learning by exporting, but the pattern of this effect is complex. Exporting helps high-tech SMEs innovate subsequently, but does not make them more innovation intensive. There is evidence that consistent exposure to export markets helps firms overcome the innovation hurdle, but that there is a positive scale effect of exposure to export markets which allows innovative firms to sell more of their new-to-market products on entering export markets. Service sector firms are able to reap the benefits of exposure to export markets at an earlier (entry) stage of the internationalization process than are manufacturing firms. Innovation-intensive firms exhibit a different pattern of entry to and exit from export markets from low-intensity innovators, and this is reflected in different effects of exporting