The science of the total environment

openair is an R package primarily developed for the analysis of air pollution measurement data but which is also of more general use in the atmospheric sciences. The package consists of many tools for importing and manipulating data, and undertaking a wide range of analyses to enhance understanding of air pollution data. In this paper we consider the development of the package with the purpose of showing how air pollution data can be analysed in more insightful ways. Examples are provided of importing data from UK air pollution networks, source identification and characterisation using bivariate polar plots, quantitative trend estimates and the use of functions for model evaluation purposes. We demonstrate how air pollution data can be analysed quickly and efficiently and in an interactive way, freeing time to consider the problem at hand. One of the central themes of openair is the use of conditioning plots and analyses, which greatly enhance inference possibilities. Finally, some consideration is given to future developments.

openair - An R package for air quality data analysis

Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual-energy X-ray absorptiometry, in children aged 3–19 y

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.

A review and evaluation of intraurban air pollution exposure models

Metal-organic frameworks (MOFs) are typically highlighted for their potential application in gas storage, separations and catalysis. In contrast, the unique prospects these porous and crystalline materials offer for application in electronic devices, although actively developed, are often underexposed. This review highlights the research aimed at the implementation of MOFs as an integral part of solid-state microelectronics. Manufacturing these devices will critically depend on the compatibility of MOFs with existing fabrication protocols and predominant standards. Therefore, it is important to focus in parallel on a fundamental understanding of the distinguishing properties of MOFs and eliminating fabrication-related obstacles for integration. The latter implies a shift from the microcrystalline powder synthesis in chemistry labs, towards film deposition and processing in a cleanroom environment. Both the fundamental and applied aspects of this two-pronged approach are discussed. Critical directions for future research are proposed in an updated high-level roadmap to stimulate the next steps towards MOF-based microelectronics within the community.

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An updated roadmap for the integration of metal–organic frameworks with electronic devices and chemical sensors

Elevated protein O-GlcNAcylation is associated with change of glucose metabolism enzyme levels and their link to nNOS in Alzheimer’s disease postmortem brains

Infill development, which refers to new urban development on land blocks within the built-up area, has been advised and adopted as a policy tool to stop urban sprawl and to promote more sustainable travel patterns. This study compares travel patterns and attitudes of residents from three new infill neighborhoods in England’s Tyne and Wear metropolitan area, using results from questionnaire surveys carried out in the summer of 2015. The results show that residents’ travel behaviors differ in three neighborhoods, which have different levels of job opportunities, public transport services, walkability and other amenities. Their travel patterns have also changed a lot, comparing with before moving to the new neighborhoods. The results support the residential self-selection concept. However, it’s still necessary to build new neighborhoods which can make it easier for people to travel in their preferable ways, especially for the young people who are not so tied to private cars as their parents’ generations.

The Effects of Infill Developments on Residents’ Travel Behaviors

Acute exercise elicits dynamic transcriptional changes that, when repeated, form the fundamental basis of health, resilience, and performance adaptations. While moderate-intensity endurance training combined with conventional resistance training (traditional, TRAD) is often prescribed and recommended by public health guidance, high-intensity training combining maximal-effort intervals with intensive, limited-rest resistance training is a time-efficient alternative that may be used tactically (HITT) to confer similar benefits. Mechanisms of action of these distinct stimuli are incompletely characterized and have not been directly compared. We assessed transcriptome-wide responses in skeletal muscle and circulating extracellular vehicles (EVs) to a single exercise bout in young adults randomized to TRAD (n=21, 12M/9F, 22±3y) or HITT (n=19, 11M/8F, 22±2y). Next-generation sequencing captured small, long, and circular RNA in muscle and EVs. Analysis identified differentially expressed transcripts (|log2FC|>1, FDR≤0.05) immediately (h0, EVs only), h3, and h24 post-exercise within and between exercise protocols. Additionally, all apparently responsive transcripts (FDR<0.2) underwent singular value decomposition to summarize data structures into latent variables (LVs) to deconvolve molecular expression circuits and inter-regulatory relationships. LVs were compared across time and exercise protocol. TRAD, a longer but more sustained stimulus, generally elicited a stronger transcriptional response than HITT, but considerable overlap and key differences existed. Findings reveal shared and unique molecular responses to the exercise stimuli and lay groundwork toward establishing relationships between protein-coding genes and lesser-understood transcripts that serve regulatory roles following exercise. Future work should advance the understanding of these circuits and whether they repeat in other populations or following other types of exercise/stress.

Dynamic Transcriptomic Responses to Acute Exercise Stimuli in Young Adults.

Revealing the relationships in gene expression and behavior in mice exposed to systemic modulation of the O-GlcNAcylation pathway

Often air quality is considered as part of a multi-criteria decision making process, requiring dispersion modelling to be conducted alongside a multitude of co-determinants of possible management outcomes. This typically involves diverse information layers, such as socio-demographics, land use, travel patterns, utilising spatial statistics to establish the causeeffect relationship over the study domain. The integrated approach presented in this paper combines spatially-resolved (raster) information on emission sources (road traffic and/or industrial) with the published statistics (socio-demographic, epidemiology, etc.) to gain a priori information on the hotspots. This enables iterative enhancement of dispersion model parameterisation, mainly emissions in specific areas, to refine the air quality predictions. A case study is presented demonstrating the application of spatial statistics, utilising a combination of weighted-overlay and ordinary least-squares regression analyses for the dissimilar datasets included in the multi-criteria decision problem. All the datasets are generated at the Lower Super Output Area-level for the local administration boundaries of Stockton (UK), spatially mapping the distribution of potential locations of priority areas for model refinement. The study demonstrates the need for robust dataset while associating dispersion modelling outcomes with multi-criteria decision problems.

Margaret Bell

Papers

Elevated protein O-GlcNAcylation is associated with change of glucose metabolism enzyme levels and their link to nNOS in Alzheimer’s disease postmortem brains

The Effects of Infill Developments on Residents’ Travel Behaviors

Dynamic Transcriptomic Responses to Acute Exercise Stimuli in Young Adults.

Revealing the relationships in gene expression and behavior in mice exposed to systemic modulation of the O-GlcNAcylation pathway

Dispersion modelling for decision-making: combining spatial statistics with model parameterisation