Mobile assessment of on-road air pollution and its sources along the East-West Highway in Bhutan

Human exposures in transportation microenvironments are poorly represented by ambient stationary monitoring. A number of on-road studies using vehicle-based mobile monitoring have been conducted to address this. Most previous studies were conducted on urban roads in developed countries where the primary emission source was vehicles. Few studies have examined on-road pollution in developing countries in urban settings. Currently, no study has been conducted for roadways in rural environments where a substantial proportion of the population live. This study aimed to characterize on-road air quality on the East-West Highway (EWH) in Bhutan and identify its principal sources. We conducted six mobile measurements of PM10, particle number (PN) count and CO along the entire 570 km length of the EWH. We divided the EWH into five segments, R1-R5, taking the road length between two district towns as a single road segment. The pollutant concentrations varied widely along the different road segments, with the highest concentrations for R5 compared with other road segments (PM10 = 149 µg/m3, PN = 5.74 × 104 particles/cm-3, CO = 0.19 ppm), which is the final segment of the road to the capital. Apart from vehicle emissions, the dominant sources were road works, unpaved roads and roadside combustion activities. Overall, the highest contributions above the background levels were made by unpaved roads for PM10 (6 times background), and vehicle emissions for PN and CO (5 and 15 times background, respectively). Notwithstanding the differences in instrumentation used and particle size range measured, the current study showed lower PN concentrations compared with similar on-road studies. However, concentrations were still high enough that commuters, road maintenance workers and residents living along the EWH, were potentially exposed to elevated pollutant concentrations from combustion and non-combustion sources. Future studies should focus on assessing the dispersion patterns of roadway pollutants and defining the short- and long-term health impacts of exposure in Bhutan, as well as in other developing countries with similar characteristics.

Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Decision trees for detection of activity intensity in youth with cerebral palsy

PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.

Step based physical activity guidelines for preschool-aged children

OBJECTIVE Public health organizations recommend that preschool-aged children accumulate at least 3h of physical activity (PA) daily. Objective monitoring using pedometers offers an opportunity to measure preschooler's PA and assess compliance with this recommendation. The purpose of this study was to derive step-based recommendations consistent with the 3h PA recommendation for preschool-aged children. METHOD The study sample comprised 916 preschool-aged children, aged 3 to 6years (mean age=5.0+/-0.8years). Children were recruited from kindergartens located in Portugal, between 2009 and 2013. Children wore an ActiGraph GT1M accelerometer that measured PA intensity and steps per day simultaneously over a 7-day monitoring period. Receiver operating characteristic (ROC) curve analysis was used to identify the daily step count threshold associated with meeting the daily 3hour PA recommendation. RESULTS A significant correlation was observed between minutes of total PA and steps per day (r=0.76, p<0.001). The optimal step count for >/=3h of total PA was 9099 steps per day (sensitivity (90%) and specificity (66%)) with area under the ROC curve=0.86 (95% CI: 0.84 to 0.88). CONCLUSION Preschool-aged children who accumulate less than 9000 steps per day may be considered Insufficiently Active.

Chronic disease risks and use of a smartphone application during a physical activity and dietary intervention in Australian truck drivers

- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Influence of interleukin-1 beta on platelet-poor plasma clot formation: A potential impact on early bone healing

Objectives Hematoma quality (especially the fibrin matrix) plays an important role in the bone healing process. Here, we investigated the effect of interleukin-1 beta (IL-1β) on fibrin clot formation from platelet-poor plasma (PPP). Methods Five-milliliter of rat whole-blood samples were collected from the hepatic portal vein. All blood samples were firstly standardized via a thrombelastograph (TEG), blood cell count, and the measurement of fibrinogen concentration. PPP was prepared by collecting the top two-fifths of the plasma after centrifugation under 400 × g for 10min at 20°C. The effects of IL-1β cytokines on artificial fibrin clot formation from PPP solutions were determined by scanning electronic microscopy (SEM), confocal microscopy (CM), turbidity, and clot lysis assays. Results The lag time for protofibril formation was markedly shortened in the IL-1β treatment groups (243.8 ± 76.85 in the 50 pg/mL of IL-1β and 97.5 ± 19.36 in the 500 pg/mL of IL-1β) compared to the control group without IL-1β (543.8 ± 205.8). Maximal turbidity was observed in the control group. IL-1β (500 pg/mL) treatment significantly decreased fiber diameters resulting in smaller pore sizes and increased density of the fibrin clot structure formed from PPP (P < 0.05). The clot lysis assay revealed that 500 pg/mL IL-1β induced a lower susceptibility to dissolution due to the formation of thinner and denser fibers. Conclusion IL-1β can significantly influence PPP fibrin clot structure, which may affect the early bone healing process.

How can evaluative thinking and practice inform performance models for organizations and personnel

In the world today there are many ways in which we measure, count and determine whether something is worth the effort or not. In Australia and many other countries, new government legislation is requiring government-funded entities to become more transparent in their practice and to develop a more cohesive narrative about the worth, or impact, for the betterment of society. This places the executives of such entities in a position of needing evaluative thinking and practice to guide how they may build the narrative that documents and demonstrates this type of impact. In thinking about where to start, executives, project and program managers may consider this workshop as a professional development opportunity to explore both the intended and unintended consequences of performance models as tools of evaluation. This workshop will offer participants an opportunity to unpack the place of performance models as an evaluative tool through the following: · What shape does an ethical, sound and valid performance measure for an organization or personnel take? · What role does cultural specificity play in the design and development of a performance model for an organization or for personnel? · How are stakeholders able to identify risk during the design and development of such models? · When and where will dissemination strategies be required? · And so what? How can you determine that your performance model implementation has made a difference now or in the future?

Tumour islet Foxp3+ T-cell infiltration predicts poor outcome in nonsmall cell lung cancer

The impact of host immunity on outcome in nonsmall cell lung cancer (NSCLC) is controversial. We examined the relationship between lymphoid infiltration patterns in NSCLC and prognosis. Tumour- and stroma-infiltrating CD3+, CD8+ and forkhead box P3 (Foxp3)+ T-lymphocytes were identified using immunohistochemistry and a novel image analysis algorithm to assess total, cytotoxic and regulatory T-lymphocyte counts, respectively, in 196 NSCLC cases. The median cell count was selected as a cut-point to define patient subgroups and the ratio of the corresponding tumour islet:stroma (TI/S) counts was determined. There was a positive association between overall survival and increased CD8+ TI/S ratio (hazard ratio (HR) for death 0.44, p<0.001) but an inverse relationship between Foxp3+ TI/S ratio and overall survival (HR 4.86, p<0.001). Patients with high CD8+ islet (HR 0.48, p<0.001) and Foxp3+ stromal (HR 0.23, p<0.001) counts had better survival, whereas high CD3+ and CD8+ stromal counts and high Foxp3+ islet infiltration conferred a worse survival (HR 1.55, 2.19 and 3.14, respectively). By multivariate analysis, a high CD8+ TI/S ratio conferred an improved survival (HR 0.48, p=0.002) but a high Foxp3+ TI/S ratio was associated with worse survival (HR 3.91, p<0.001). Microlocalisation of infiltrating T-lymphocytes is a powerful predictor of outcome in resected NSCLC.