Subjective awareness of sleepiness while driving in younger and older adults.

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subjective sleepiness ratings in predicting subsequent driving impairment and physiological drowsiness, 16 younger (21-33 years) and 17 older (50-65 years) adults drove an instrumented vehicle for 2 h on closed loop under two conditions: well-rested and 29 h sleep deprivation. Sleepiness ratings (Karolinska Sleepiness Scale, Likelihood of Falling Asleep scale, Sleepiness Symptoms Questionnaire) were obtained every 15min, alongside lane deviations, near crash events, and ocular indices of drowsiness. All subjective sleepiness measures increased with sleep deprivation for both age groups (p < 0.013). While most subjective sleepiness ratings significantly predicted driving impairment and drowsiness in younger adults (OR: 1.7-15.6, p < 0.02), this was only apparent for KSS, likelihood of falling asleep, and "difficulty staying in the lane for the older adults" (OR: 2.76-2.86, p = 0.02). This may be due to an altered perception of sleepiness in older adults, or due to lowered objective signs of impairment in the older group. Our data suggest that (i) younger and older drivers are aware of sleepiness; (ii) the best subjective scale may differ across age groups; and (iii) future research should expand on the best subjective measures to inform of crash risk in older adults to inform tailored educational road safety campaigns on signs of sleepiness.

Environmental DNA Metabarcoding Supporting Community Assessment of Environmental Stressors in a Field-Based Sediment Microcosm Study.

Conventional ecological risk assessment on toxic stressors in sediment is limited to a small and selected fraction of benthic communities. Ecogenomic approaches provide unprecedented capacity to monitor the changes of biodiversity and community composition in the field, but how to utilize it to assess ecological impact by contaminates remains largely unexplored. Here, an environmental DNA (eDNA) metabarcoding approach was used to assess the effect of copper on changes in biodiversity and community composition across the tree of life (including bacteria, protists, algae, fungi, and metazoa) in a field-based microcosm. Many microorganisms across a broad range of taxa groups changed their relative abundance in response to increased copper concentrations in sediments. Changes in community structure of microbiota appeared to be more sensitive to copper than survival of laboratory-bred organisms and indigenous macroinvertebrates. Copper caused a significant shift in prokaryotic community composition via substitution of dominant species. Network heterogeneity and Shannon diversity of the bacterial community decreased in the high copper treatments. eDNA metabarcoding assessed the effects of copper-contaminated sediment with less effort than manually processing samples. Our study highlighted the value of community profiling by an eDNA-based approach in prospective and retrospective risk assessment of environmental stressors.

Bifenthrin Causes Toxicity in Urban Stormwater Wetlands: Field and Laboratory Assessment Using Austrochiltonia (Amphipoda).

Stormwater wetlands are engineered to accumulate sediment and pollutants from stormwater and provide environmental value to urban environments. Therefore, contaminated sediment risks causing toxicity to aquatic fauna. This research identifies contaminants of concern in urban wetland sediments by assessing sediment toxicity using the amphipod Austrochiltonia subtenuis. Sediments from 98 wetlands were analyzed for contaminants, and laboratory bioassays were performed with A. subtenuis. Wild Austrochiltonia spp. were also collected from wetlands to assess field populations. Random forest modeling was used to identify the most important variables predicting survival, growth, and field absence of Austrochiltonia spp. Bifenthrin was the most frequently detected pesticide and also the most important predictor of Austrochiltonia spp. responses. Copper, permethrin, chromium, triclosan, and lead were also important. The median lethal effect concentration (LC50) of bifenthrin to laboratory-based A. subtenuis (1.09 (±0.08) µg/gOC) exposed to wetland sediments was supported by a bifenthrin-spiked sediment experiment, indicating A. subtenuis is a suitable test species. Furthermore, Austrochiltonia spp. were absent from all sites that exceeded the calculated bifenthrin LC50, demonstrating the impact of this contaminant on wild populations. This research demonstrates the sensitivity of Austrochiltonia spp. to urban sediment contamination and identifies bifenthrin as a contaminant of concern in urban wetlands.

Accurate detection of acute sleep deprivation using a metabolomic biomarker-A machine learning approach.

Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography-mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through "fitness for duty" or "post-accident analysis" assessments.

Awareness of sleepiness: Temporal dynamics of subjective and objective sleepiness.

We systematically examined the temporal relationships between subjective sleepiness and both physiological drowsiness and performance impairment in a controlled laboratory setting. Eighteen healthy young adults (8 women; MAGE  = 21.44 ± 3.24 years) underwent 40 hr of extended wakefulness, completing a bihourly Karolinska Sleepiness Scale (KSS) and 10-min Psychomotor Vigilance Task (PVT). Microsleeps and slow eye movements (SEMs) were scored during the PVT. KSS scores increased 3 hr prior to performance impairment (p < .001) and 4-6 hr prior to physiological sleepiness (p < .001). There were strong within-subject correlations between KSS and PVT lapses (r = 0.75, p < .001) and physiological drowsiness (r > 0.60, p < .001). Between-subjects product-moment correlations were more modest but showed a significant positive increase across time awake, suggesting that subjective sleepiness and objective outcomes were more tightly correlated after sleep loss. Cross-correlations showed significant positive correlations at 0-lag (p < .034); however, a high proportion of participants showed maximal correlations at positive lags, suggesting KSS was associated with future objective impairment. Within individuals, subjective sleepiness was highly correlated with objective impairment, between-subject correlations were more modest, possibly due to interindividual vulnerability to sleep loss. These results suggest that subjective sleepiness represents an inbuilt early warning system for subsequent drowsiness and performance impairment.

On-road driving impairment following sleep deprivation differs according to age.

Impaired driving performance due to sleep loss is a major contributor to motor-vehicle crashes, fatalities, and serious injuries. As on-road, fully-instrumented studies of drowsy driving have largely focused on young drivers, we examined the impact of sleep loss on driving performance and physiological drowsiness in both younger and older drivers of working age. Sixteen 'younger' adults (M = 24.3 ± 3.1 years [21-33 years], 9 males) and seventeen 'older' adults (M = 57.3 ± 5.2, [50-65 years], 9 males) undertook two 2 h drives on a closed-loop track in an instrumented vehicle with a qualified instructor following (i) 8 h sleep opportunity the night prior (well-rested), and (ii) after 29-h of total sleep deprivation (TSD). Following TSD, both age groups displayed increased subjective sleepiness and lane departures (p < 0.05), with younger drivers exhibiting 7.37 × more lane departures, and 11 × greater risk of near crash events following sleep loss. While older drivers exhibited a 3.5 × more lane departures following sleep loss (p = 0.008), they did not have a significant increase in near-crash events (3/34 drives). Compared to older adults, younger adults had 3.1 × more lane departures (p = < 0.001), and more near crash events (79% versus 21%, p = 0.007). Ocular measures of drowsiness, including blink duration, number of long eye closures and PERCLOS increased following sleep loss for younger adults only (p < 0.05). These results suggest that for older working-aged adults, driving impairments observed following sleep loss may not be due to falling asleep. Future work should examine whether this is attributed to other consequences of sleep loss, such as inattention or distraction from the road.

Sensitive community responses of microbiota to copper in sediment toxicity test.

Sediment contamination is widespread and can be toxic to aquatic ecosystems and impair human health. Despite their significant ecological function, meio- and microbiota in aquatic ecosystems have been poorly studied in conventional sediment ecotoxicity tests because of the difficulty in sample collecting and identification. In the present study, a novel DNA metabarcoding method was used to assess the effects of spiked copper (Cu) on benthic eukaryotic and prokaryotic communities in laboratory sediment toxicity tests with macroinvertebrates, the chironomid Chironomus tepperi and the amphipod Austrochiltonia subtenuis. In addition to the obvious toxic effects to experimental animals, microbiota (bacteria, protists, algae, and fungi) were significantly altered by spiked Cu in the sediments. The phylogenetic diversity of eukaryotic communities was decreased after spiked-Cu exposure. Even a low-spiked Cu treatment (125 mg/kg) altered structures of eukaryotic and prokaryotic communities in the amphipod experiment. The present study demonstrates that measuring microbiota communities will expand our understanding of the influences of contaminants on aquatic ecosystems. Particularly, the alterations of phylogenetic biodiversity of eukaryotic communities and the structure of sedimentary communities are sensitive indicators for sediment contamination, which can be incorporated in the monitoring and assessment of sediment quality. Environ Toxicol Chem 2018;37:599-608. © 2017 SETAC.

Toxicant mixtures in sediment alter gene expression in the cysteine metabolism of Chironomus tepperi.

Sediment contamination can pose risks to the environment, and sediment toxicity tests have been developed to isolate the impact of sediment from other factors. Mixtures of contaminants often occur in sediments, and traditional endpoints used in toxicity testing, such as growth, reproduction, and survival, cannot discern the cause of toxicity from chemical mixtures because of complex interactions. In urban waterways, the synthetic pyrethroid bifenthrin and the metal copper are commonly found in mixtures, so the present study was designed to investigate how these contaminants cause toxicity in mixtures. To investigate this, Chironomus tepperi was exposed to environmentally relevant concentrations of copper and bifenthrin-spiked sediments in a 2-way factorial mixture for 5 d. Growth and expression profiles of cysteine metabolism genes were measured after exposure. Growth increased at low copper concentrations, decreased at high copper concentrations, and was unaffected by bifenthrin exposures. Copper exposures induced possible cellular repair by upregulating S-adenosylmethionine synthetase expression and downregulating expression of S-adenosylhomocysteine hydrolase and cystathionine-ß-synthase. Metallothionein upregulation was also observed. Bifenthrin exposure altered cysteine metabolism to a lesser extent, downregulating cystathionine-ß-synthase and γ-glutamylcysteine synthase. Synergistic, antagonistic, and dose-dependent interactions were observed, and there was evidence of conflicting modes of action and limited substrate production. These findings demonstrate how contextual gene expression changes can be sensitive and specific identifiers of toxicant exposure in mixtures. Environ Toxicol Chem 2017;36:691-698. © 2016 SETAC.

Metabolomic Profiles of a Midge (Procladius villosimanus, Kieffer) Are Associated with Sediment Contamination in Urban Wetlands.

Metabolomic techniques are powerful tools for investigating organism-environment interactions. Metabolite profiles have the potential to identify exposure or toxicity before populations are disrupted and can provide useful information for environmental assessment. However, under complex environmental scenarios, metabolomic responses to exposure can be distorted by background and/or organismal variation. In the current study, we use LC-MS (liquid chromatography-mass spectrometry) and GC-MS (gas chromatography-mass spectrometry) to measure metabolites of the midge Procladius villosimanus inhabiting 21 urban wetlands. These metabolites were tested against common sediment contaminants using random forest models and metabolite enrichment analysis. Sediment contaminant concentrations in the field correlated with several P. villosimanus metabolites despite natural environmental and organismal variation. Furthermore, enrichment analysis indicated that metabolite sets implicated in stress responses were enriched, pointing to specific cellular functions affected by exposure. Methionine metabolism, sugar metabolism and glycerolipid metabolism associated with total petroleum hydrocarbon and metal concentrations, while mitochondrial electron transport and urea cycle sets associated only with bifenthrin. These results demonstrate the potential for metabolomics approaches to provide useful information in field-based environmental assessments.

A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc.

Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography-mass spectrometry (GC-MS) analysis and a targeted liquid chromatography-mass spectrometry (LC-MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary metabolomics analytical approaches was particularly useful for understanding the effects of zinc exposure and importantly, identified a suite of candidate biomarkers of zinc exposure useful for the development of biomonitoring programs.

Separating the effects of water physicochemistry and sediment contamination on Chironomus tepperi (Skuse) survival, growth and development: a boosted regression tree approach.

More comprehensive ecological risk assessment procedures are needed as the unprecedented rate of anthropogenic disturbances to aquatic ecosystems continues. Identifying the effects of pollutants on aquatic ecosystems is difficult, requiring the individual and joint effects of a range of natural and anthropogenic factors to be isolated, often via the analysis of large, complicated datasets. Ecotoxicologists have traditionally used multiple regression to analyse such datasets, but there are inherent problems with this approach and a need to consider other potentially more suitable methods. Sediment pollution can cause a range of negative effects on aquatic animals, and these are used as the basis for toxicity bioassays to measure the biological impact of pollution and the success of remediation efforts. However, experimental artefacts can also lead to sediments being incorrectly classed as toxic in such studies. Understanding the influence of potentially confounding factors will help more accurate assessments of sediment pollution. In this study, we analysed standardised sediment bioassays conducted using the chironomid Chironomus tepperi, with the aim of modelling the impact of sediment toxicants and water physico-chemistry on four endpoints (survival, growth, median emergence day, and number of emerging adults). We used boosted regression trees (BRT), a method that has a number of advantages over multiple regression, to model bioassay endpoints as a function of water chemistry, sediment quality and underlying geology. Endpoints were generally influenced most strongly by water quality parameters and nutrients, although some metals negatively influenced emergence endpoints. Sub-lethal endpoints were generally better predicted than lethal endpoints; median emergence day was the most sensitive endpoint examined in this study, while the number of emerging adults was the least sensitive. We tested our modelling results by experimentally manipulating sediment and observing the impact on C. tepperi endpoints. For survival, experimental observations were accurately predicted by models, which highlighted the importance of conductivity and dissolved oxygen for this endpoint. In comparison, experimental median emergence day was poorly modelled, most likely due to the influence of a wider range of predictors identified as being important influences on this endpoint in models. To demonstrate how BRT model results compare to more traditional techniques, we analysed survival data using multiple regression. Both models yielded similar results, but boosted regression trees offer important advantages over multiple regression. Our results illustrate how boosted regression trees can be used to analyse complex ecotoxicological datasets, and reinforces the importance of water chemistry in sediment toxicology.

Genes involved in cysteine metabolism of Chironomus tepperi are regulated differently by copper and by cadmium.

Freshwater invertebrates are often exposed to metal contamination, and changes in gene expression patterns can help understand mechanisms underlying toxicity and act as pollutant-specific biomarkers. In this study the expressions of genes involved in cysteine metabolism are characterized in the midge Chironomus tepperi during exposures to sublethal concentrations of cadmium and copper. These metals altered gene expression of the cysteine metabolism differently. Both metals decreased S-adenosylhomocysteine hydrolase expression and did not change the expression of S-adenosylmethionine synthetase. Cadmium exposure likely increased cystathionine production by up-regulating cystathionine-ß-synthase (CßS) expression, while maintaining control level cysteine production via cystathionine-γ-lyase (CγL) expression. Conversely, copper down-regulated CßS expression and up-regulated CγL expression, which in turn could diminish cystathionine to favor cysteine production. Both metals up-regulated glutathione related expression (γ-glutamylcysteine synthase and glutathione synthetase). Only cadmium up-regulated metallothionein expression and glutathione S-transferase d1 expression was up-regulated only by copper exposure. These different transcription responses of genes involved in cysteine metabolism in C. tepperi point to metal-specific detoxification pathways and suggest that the transsulfuration pathway could provide biomarkers for identifying specific metals.