Environmental Health Applications Research Articles

A review of geospatial exposure models and approaches for health data integration

Abstract Background Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health. Objective Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications. Methods We conduct a literature review and synthesis. Results First, we discuss key concepts and terminology for geospatial exposure data and models. Second, we provide an overview of workflows in geospatial exposure model development and health data integration. Third, we review modeling approaches, including proximity-based, statistical, and mechanistic approaches, across diverse exposure types, such as air quality, water quality, climate, and socioeconomic factors. For each model type, we provide descriptions, general equations, and example applications for environmental exposure assessment. Fourth, we discuss the approaches used to integrate geospatial exposure data and health data, such as methods to link data sources with disparate spatial and temporal scales. Fifth, we describe the landscape of open-source tools supporting these workflows.

Growing prominence of deep-sea life in marine bioprospecting

AbstractMarine bioprospecting, which involves the exploration of genetic and biochemical material from marine organisms, can be used towards addressing a broad range of public and environmental health applications such as disease treatment, diagnostics and bioremediation. Marine genetic resources are important reservoirs for such bioprospecting efforts; however, the extent to which they are used commercially for natural product discovery and the marine sources from which they are derived are not well understood. Here we introduce a comprehensive database of marine genes referenced in patent filings, the Marine Bioprospecting Patent database. It includes 92,550 protein-coding sequences associated with 4,779 patent filings, identified by analysing all relevant records from genetic sequence databases. Three companies alone—BASF, IFF and DuPont—included sequences from 949 species (more than half of referenced species with identified marine origin). Microbial life in the deep sea, a vast and remote biome predominantly beyond national jurisdiction, is already attracting substantial economic interest; the top ten patent holders have all filed marine gene patents referencing sequences from deep-sea life. Our findings provide an updated understanding of the marine bioprospecting landscape, contribute to the sustainable use of marine biodiversity and underscore the need for policymakers to ensure stewardship of deep-sea ecosystems.

Dynamic Schwarz Meta-Foams: Customizable Solutions for Environmental Noise Reduction.

In an era marked by increasing environmental challenges affecting human well-being, traditional acoustic materials struggle to effectively handle the diverse and multi-frequency nature of harmful environmental noises. This has spurred a demand for innovative acoustic metamaterial solutions by utilizing sustainable design strategies. This research introduces tunable Schwarz metamaterial capable of transforming into a soft meta-foam to solve the complex problems of varying environmental noises. This study primarily focuses on adjusting single to multiple sound-blocking bandgaps mechanism using a multi-layered approach, incorporating the Schwarz P-type triply periodic minimal surface (TPMS) and its elective soft foam counterpart, known as tunable Schwarz meta-foams (TSMF-x). The tunable design parameters of the unit cell, multi-layered TPMS, and soft programmable TSMF-lichen version are comprehensively explored including a fire-safety test. The results demonstrate these enhanced flame retardant meta-foam families have the potential to be used for mid-to-high-frequency environmental noises in industrial equipment and smart homes for sustainable architecture and environmental health applications.

Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case.

BackgroundThe Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental exposures data. ICEES is equipped with tools to support basic statistical exploration of the integrated data in a completely open manner.ObjectiveThis study aims to further develop and apply ICEES as a novel tool for openly exposing and exploring integrated clinical and environmental data. We focus on an asthma use case.MethodsWe queried the ICEES open application programming interface (OpenAPI) using a functionality that supports chi-square tests between feature variables and a primary outcome measure, with a Bonferroni correction for multiple comparisons (α=.001). We focused on 2 primary outcomes that are indicative of asthma exacerbations: annual emergency department (ED) or inpatient visits for respiratory issues; and annual prescriptions for prednisone.ResultsOf the 157,410 patients within the asthma cohort, 26,332 (16.73%) had 1 or more annual ED or inpatient visits for respiratory issues, and 17,056 (10.84%) had 1 or more annual prescriptions for prednisone. We found that close proximity to a major roadway or highway, exposure to high levels of particulate matter ≤2.5 μm (PM2.5) or ozone, female sex, Caucasian race, low residential density, lack of health insurance, and low household income were significantly associated with asthma exacerbations (P<.001). Asthma exacerbations did not vary by rural versus urban residence. Moreover, the results were largely consistent across outcome measures.ConclusionsOur results demonstrate that the open-source ICEES can be used to replicate and extend published findings on factors that influence asthma exacerbations. As a disease-agnostic, open-source approach for integrating, exposing, and exploring patient-level clinical and environmental exposures data, we believe that ICEES will have broad adoption by other institutions and application in environmental health and other biomedical fields.

W-TSS: A Wavelet-Based Algorithm for Discovering Time Series Shapelets.

Many approaches to time series classification rely on machine learning methods. However, there is growing interest in going beyond black box prediction models to understand discriminatory features of the time series and their associations with outcomes. One promising method is time-series shapelets (TSS), which identifies maximally discriminative subsequences of time series. For example, in environmental health applications TSS could be used to identify short-term patterns in exposure time series (shapelets) associated with adverse health outcomes. Identification of candidate shapelets in TSS is computationally intensive. The original TSS algorithm used exhaustive search. Subsequent algorithms introduced efficiencies by trimming/aggregating the set of candidates or training candidates from initialized values, but these approaches have limitations. In this paper, we introduce Wavelet-TSS (W-TSS) a novel intelligent method for identifying candidate shapelets in TSS using wavelet transformation discovery. We tested W-TSS on two datasets: (1) a synthetic example used in previous TSS studies and (2) a panel study relating exposures from residential air pollution sensors to symptoms in participants with asthma. Compared to previous TSS algorithms, W-TSS was more computationally efficient, more accurate, and was able to discover more discriminative shapelets. W-TSS does not require pre-specification of shapelet length.

A Survey of Systematic Evidence Mapping Practice and the Case for Knowledge Graphs in Environmental Health and Toxicology.

Systematic evidence mapping offers a robust and transparent methodology for facilitating evidence-based approaches to decision-making in chemicals policy and wider environmental health (EH). Interest in the methodology is growing; however, its application in EH is still novel. To facilitate the production of effective systematic evidence maps for EH use cases, we survey the successful application of evidence mapping in other fields where the methodology is more established. Focusing on issues of “data storage technology,” “data integrity,” “data accessibility,” and “transparency,” we characterize current evidence mapping practice and critically review its potential value for EH contexts. We note that rigid, flat data tables and schema-first approaches dominate current mapping methods and highlight how this practice is ill-suited to the highly connected, heterogeneous, and complex nature of EH data. We propose this challenge is overcome by storing and structuring data as “knowledge graphs.” Knowledge graphs offer a flexible, schemaless, and scalable model for systematically mapping the EH literature. Associated technologies, such as ontologies, are well-suited to the long-term goals of systematic mapping methodology in promoting resource-efficient access to the wider EH evidence base. Several graph storage implementations are readily available, with a variety of proven use cases in other fields. Thus, developing and adapting systematic evidence mapping for EH should utilize these graph-based resources to ensure the production of scalable, interoperable, and robust maps to aid decision-making processes in chemicals policy and wider EH.

Discovering co-location patterns with aggregated spatial transactions and dependency rules

Co-location pattern mining focuses on finding associations among spatial features. Existing co-location pattern mining techniques mainly rely on frequency based thresholds which discard the rare patterns and find the noisy patterns. This could be avoided by evaluating co-location patterns based on their statistical significance. Recent studies focused on association rule mining have successfully adopted statistical tests to find significant rules. By transforming spatial data to transaction data, the co-location pattern mining problem can be reduced to an association rule mining problem and such methods can be used to find co-location patterns robustly. A transactionization mechanism has been recently proposed to achieve this. However, this method ignores the effect of general instances, with non-overlapping buffer regions, on the reference instances in their proximity. Addressing this, we propose a novel approach, AGT-Fisher, to robustly transform spatial data to transaction data and use statistically significant dependency rule searching methods to find co-location rules from them. Our work is motivated by an application in environmental health to investigate potential associations between air pollution and adverse birth outcomes in Canada. We used AGT-Fisher to find such associations from real datasets. The discovered co-location patterns were evaluated based on their statistical dependency and the empirical evidence, and results showed that our approach is more robust. Furthermore, we evaluated the resulting patterns to find spatial common and contrast sets, which are two special types of co-location patterns, to compare spatial regions and gain more insights.

A Highly Sensitive Enzymatic Catalysis System for Trace Detection of Arsenic in Water

Arsenic (As) is an extremely toxic element that exists in the environment in different chemical forms. The detection of arsenic in potable water remains a challenging task. This study presents a highly sensitive enzymatic catalysis system for trace sensing of inorganic arsenic in water. This is the first enzyme-catalyzed fluorescence assay capable of detecting arsenic at concentrations below the allowable level adopted by the World Health Organization (10 ppb in drinking water). The enzyme catalytically produces fluorescent NADH in the presence of arsenate, which enables facile detection of arsenate at concentrations in the 0-200 ppb range. Calibration curves made at a set time interval allow accurate determination of unknown arsenic samples. This method holds potential for interfacing with automated analytical sampling systems to allow arsenic determinations in environmental health applications.

Field Performance of a Novel Passive Bioaerosol Sampler using Polarized Ferroelectric Polymer Films.

Passive bioaerosol samplers can improve environmental and health protection by enhancing the practicality and cost-effectiveness of air sampling. Here, we present the outdoor field testing of a novel, passive bioaerosol sampler, the Rutgers Electrostatic Passive Sampler (REPS), based on the use of polarized, ferroelectric polymer film (poly(vinylidene fluoride)). Four 10-day-long field campaigns were conducted to compare total (culturable + non-culturable) and culturable bioaerosol collection efficiencies of REPS to passive samplers (PTFE settling filters and agar settling plates). These collection efficiencies were calculated relative to performance of an active, reference Button Sampler. Compared to passive PTFE filters, which exclusively rely on gravitational particle deposition, REPS collected a 7-fold higher total microorganism quantity. Relative to the Button Sampler, REPS collected 25% of the total number of bacteria and fungi and 65% of the culturable bacteria. Furthermore, REPS achieved this performance without any air movers, pumps, batteries or external power. Since the Button Samplers operated at 4 L/min, REPS was calibrated to have equivalent sampling rates of 2.6 L/min and 1.0 L/min for culturable bacteria and total microorganisms, respectively. These results suggest that REPS can passively collect airborne microorganisms, including culturable bacteria, with high efficiency over long-term sampling durations. REPS can provide better preservation of bacterial culturability because it has no active airflow, which desiccates microbes in active samplers. Since there are limited options available for long-term, unattended bioaerosol sampling, REPS can complement currently available bioaerosol sampling technologies for numerous environmental health applications, such as exposure assessment for epidemiology and monitoring aeroallergen trends.

Development of a modified cortisol extraction procedure for intermediately sized fish not amenable to whole-body or plasma extraction methods.

The corticosteroid hormone cortisol is the central mediator of the teleost stress response. Therefore, the accurate quantification of cortisol in teleost fishes is a vital tool for addressing fundamental questions about an animal's physiological response to environmental stressors. Conventional steroid extraction methods using plasma or whole-body homogenates, however, are inefficient within an intermediate size range of fish that are too small for phlebotomy and too large for whole-body steroid extractions. To assess the potential effects of hatchery-induced stress on survival of fingerling hatchery-reared Spotted Seatrout (Cynoscion nebulosus), we developed a novel extraction procedure for measuring cortisol in intermediately sized fish (50-100 mm in length) that are not amenable to standard cortisol extraction methods. By excising a standardized portion of the caudal peduncle, this tissue extraction procedure allows for a small portion of a larger fish to be sampled for cortisol, while minimizing the potential interference from lipids that may be extracted using whole-body homogenization procedures. Assay precision was comparable to published plasma and whole-body extraction procedures, and cortisol quantification over a wide range of sample dilutions displayed parallelism versus assay standards. Intra-assay %CV was 8.54%, and average recovery of spiked samples was 102%. Also, tissue cortisol levels quantified using this method increase 30 min after handling stress and are significantly correlated with blood values. We conclude that this modified cortisol extraction procedure provides an excellent alternative to plasma and whole-body extraction procedures for intermediately sized fish, and will facilitate the efficient assessment of cortisol in a variety of situations ranging from basic laboratory research to industrial and field-based environmental health applications.

Preparation of needle trap samplers to extract air compounds from indoor electric-vaporizing sources

In this study, gaseous benzene, toluene, ethylbenzene, and o-xylene (BTEX) were extracted by passive needle trap samplers (NTS) using divinylbenzene (DVB) particles (mesh sizes 60–80, 80–100, and 100–120, respectively) as packed sorbents. An aspirating pump measured sampling flow rates of NTS, and the relations between BTEX mass and sampling flow rates were sufficient to maintain the extraction performance of these self-designed DVB-NTS. Furthermore, this investigation compared the extraction efficiency of NTS with that of the 100-µm polydimethylsiloxane solid-phase microextration (PDMS SPME) fiber when applied to sample heating products from electric-vaporization anti-mosquito mats, and the experimental results indicated that NTS effectiveness increased with decreasing adsorbent particle diameter. Substantially less mass of gaseous BTEX was extracted using 100-µm PDMS SPME fiber than with NTS of 100–120 mesh DVB for 60-min TWA sampling of anti-mosquito mats. The 100–120 mesh DVB-NTS primarily adsorbed 4.2 ng acetone, 13.3 ng dichloromethane, and 4.5–25.3 ng C10–C12 alkanes.Implications: The needle trap sampler (NTS) has been evaluated to be a device for sampling heating products from electric-vaporization anti-mosquito mats. Based on the experimental results, this investigation assessed NTS as suitable for occupational and environmental health applications.

Electrohydrodynamic nano-spraying of ethanolic natural plant extracts

Aerosol techniques have recently been used to process natural products for medical, pharmaceutical, and environmental health applications. In particular, electrohydrodynamic spraying, or electrospraying, which is a method of atomizing liquids by means of electrical forces, is a promising aerosol technology because it generates non-agglomerated particles due to repulsive electrical forces between particles with unipolar charges. We investigated the characteristics of natural-product nanoparticles generated via electrospraying. A plant extract containing a natural-product ( Sophora flavescens) was sprayed in steady cone-jet mode using a specially designed electrospray system with a point-to-orifice-plate configuration. The electrosprayed natural-product particles maintained their bimodal size distribution with good stability and uniformity for longer than 1 h. Compared to generation characteristics observed using a conventional nebulization process, the electrospray technique produced non-agglomerated, spherical particles and resulted in a narrow size range for both peaks. The size distribution of electrosprayed particles was controlled by varying the suspension flow rate of S. flavescens extract. Also, they had a high average charge per particle and positive polarity. The nanoparticles maintained the major chemical composition of the original S. flavescens ethanolic extract during electrospraying. Our investigation demonstrated that the electrospray process, driven by high-intensity electric fields, can be used to generate nanoscale particles from natural products.

Atomic layer deposition-based functionalization of materials for medical and environmental health applications.

Nanoporous alumina membranes exhibit high pore densities, well-controlled and uniform pore sizes, as well as straight pores. Owing to these unusual properties, nanoporous alumina membranes are currently being considered for use in implantable sensor membranes and water purification membranes. Atomic layer deposition is a thin-film growth process that may be used to modify the pore size in a nanoporous alumina membrane while retaining a narrow pore distribution. In addition, films deposited by means of atomic layer deposition may impart improved biological functionality to nanoporous alumina membranes. In this study, zinc oxide coatings and platinum coatings were deposited on nanoporous alumina membranes by means of atomic layer deposition. PEGylated nanoporous alumina membranes were prepared by self-assembly of 1-mercaptoundec-11-yl hexa(ethylene glycol) on platinum-coated nanoporous alumina membranes. The pores of the PEGylated nanoporous alumina membranes remained free of fouling after exposure to human platelet-rich plasma; protein adsorption, fibrin networks and platelet aggregation were not observed on the coated membrane surface. Zinc oxide-coated nanoporous alumina membranes demonstrated activity against two waterborne pathogens, Escherichia coli and Staphylococcus aureus. The results of this work indicate that nanoporous alumina membranes may be modified using atomic layer deposition for use in a variety of medical and environmental health applications.

Role of Exhaled Breath Biomarkers in Environmental Health Science

As a discipline of public health, environmental health science is the study of the linkage from environmental pollution sources to eventual adverse health outcome. This progression may be divided into two components, (1) “exposure assessment,” which deals with the source terms, environmental transport, human exposure routes, and internal dose, and (2) “health effects,” which deals with metabolism, cell damage, DNA changes, pathology, and onset of disease. The primary goal of understanding the linkage from source to health outcome is to provide the most effective and efficient environmental intervention methods to reduce health risk to the population. Biomarker measurements address an individual response to a common external environmental stressor. Biomarkers are substances within an individual and are subdivided into chemical markers, exogenous metabolites, endogenous response chemicals, and complex adducts (e.g., proteins, DNA). Standard biomarker measurements are performed in blood, urine, or other biological media such as adipose tissue and lavage fluid. In general, sample collection is invasive, requires medical personnel and a controlled environment, and generates infectious waste. Exploiting exhaled breath as an alternative or supplement to established biomarker measurements is attractive primarily because it allows a simpler collection procedure in the field for numerous individuals. Furthermore, because breath is a gas-phase matrix, volatile biomarkers become more readily accessible to analysis. This article describes successful environmental health applications of exhaled breath and proposes future research directions from the perspective of U.S. Environmental Protection Agency (EPA) human exposure research.

Developments in electrochemical sensors for occupational and environmental health applications

This paper provides an overview of recent advances in electrochemical sensors for industrial hygiene monitoring applications. Currently available instrument technologies as well as new devices under development are both exemplified. Progress in ruggedization and miniaturization of electroanalytical devices has led to significant improvements for on-site monitoring applications, e.g. in harsh environments and in biological monitoring. Sensor arrays and modified electrodes offer considerable promise for improved electrochemical sensing, i.e. through multi-species detection and enhanced selectivity. On-site electroanalytical detection and measurement in the field may become more widely used for applications in occupational health monitoring.