Sampling, composition, and biological effects of Mexico City airborne particulate matter from multiple periods

Air pollution is a worldwide environmental problem with an impact on human health. Particulate matter of ten micrometers or less aerodynamic diameter (PM10) as well as its fine fraction (PM2.5) is related to multiple pulmonary diseases. The impact of air pollution in Mexico City, and importantly, particulate matter has been studied and considered as a risk factor for two decades ago. Previous studies have reported the composition of Mexico City particulate matter, as well as the biological effects induced by this material. However, material collected and used in previous studies is a limited resource, and sampling and particle recovery techniques have been improved. In this study, we describe the methods used in our laboratory for Mexico City airborne particulate matter PM10 and PM2.5 sampling, considering the years 2017, 2018 and 2019. We also analyzed the PM10 and PM2.5 samples obtained to determine their composition. Finally, we exposed lung cell line cultures to PM10 and PM2.5 to evaluate the biological effect of the material in terms of cell viability, cell death, inflammatory response, and cytogenetic alterations. Our results showed that PM10 composition includes inorganic, organic and biological compounds, while PM2.5 is a mixture of more enriched organic compounds. PM10 and PM2.5 treatment in lung cells does not significantly impact cell viability/cell death. However, PM10 and PM2.5 increase the secretion levels of IL-6. Moreover, PM10 as well as PM2.5 induce cytogenetic alterations, such as micronuclei, anaphase bridges, trinucleated cells and apoptotic cells in lung cells. Our results update the evidence of the composition and biological effects of Mexico City particulate matter and provide us a reliable basis for future approaches.

Distributed source modeling of stereoencephalographic measurements of ictal activity

OBJECTIVES

Stereoelectroencephalography (SEEG) can define the epileptogenic zone (EZ). However, SEEG is susceptible to the sampling bias, where no SEEG recording is taken within a circumscribed EZ.

METHODS

Nine patients with medically refractory epilepsy underwent SEEG recording, and brain resection got positive outcomes. Ictal neuronal currents were estimated by distributed source modeling using the SEEG data and individual's anatomical magnetic resonance imaging. Using a retrospective leave-one-out data sub-sampling, we evaluated the sensitivity and specificity of the current estimates using MRI after surgical resection or radio-frequency ablation.

RESULTS

The sensitivity and specificity in detecting the EZ were indistinguishable from either the data from all electrodes or the sub-sampled data (rank sum test: rank sum = 23719, p = 0.13) when at least one remaining electrode contact was no more than 20 mm away.

CONCLUSIONS

The distributed neuronal current estimates of ictal SEEG data can mitigate the challenge of delineating the boundary of the EZ in cases of missing an electrode implanted within the EZ and a required second SEEG exploration.

SIGNIFICANCE

Distributed source modeling can be a tool for clinicians to infer the EZ by allowing for more flexible planning of the electrode implantation route and minimizing the number of electrodes.

Sampling of microplastics at a materials recovery facility

Detecting, separating, and characterizing airborne microplastics from other airborne particulates is currently challenging due to the various instrumental constraints and related sample preparation hurdles that must be overcome. The ability to measure these real-world environments is needed to better assess the risks associated with microplastics. To that end, the current study focused on developing a methodology for sampling and characterizing airborne microplastics. Particulate sampling was carried out at a municipal materials recovery facility near a conveyer belt containing sorted plastic materials to collect airborne environmental particles on filters. Nucleopore filters were mounted on Teflon support rings, coated with 100 nm aluminum to reduce the background signal for micro-Raman spectroscopy, and marked with a fiducial pattern using a laser engraver. The fiducial pattern was crucial in identifying samples, relocating particles, and efficiently enabling orthogonal measurements on the same samples. Optimum sampling conditions of 2 h at 25 L/min were determined using light microscopy to evaluate the particle loadings. The filters were then cut into slices which were attached to sections of thin beryllium-copper sheeting for easy transfer of the filter between microscopy platforms. Scanning electron microscopy was used to identify carbon-rich particles. Light microscopy was used to identify colored particles which were also carbon-rich which were then analyzed using micro-Raman spectroscopy to identify specific polymers.

Air sampling and ATP bioluminescence for quantitative detection of airborne microbes

Exposure to bioaerosol contamination has detrimental effects on human health. Recent advances in ATP bioluminescence provide more opportunities for the quantitative detection of bioaerosols. Since almost all active organisms can produce ATP, the amount of airborne microbes can be easily measured by detecting ATP-driven bioluminescence. The accurate evaluation of microorganisms mainly relies on following the four key steps: sampling and enrichment of airborne microbes, lysis for ATP extraction, enzymatic reaction, and measurement of luminescence intensity. To enhance the effectiveness of ATP bioluminescence, each step requires innovative strategies and continuous improvement. In this review, we summarized the recent advances in the quantitative detection of airborne microbes based on ATP bioluminescence, which focuses on the advanced strategies for improving sampling devices combined with ATP bioluminescence. Meanwhile, the optimized and innovative strategies for the remaining three key steps of the ATP bioluminescence assay are highlighted. The aim is to reawaken the prosperity of ATP bioluminescence and promote its wider utilization for efficient, real-time, and accurate detection of airborne microbes.

Attributes of Anopheles gambiae swarms in South Central Uganda

BACKGROUND

Anopheles gambiae continues to be widespread and an important malaria vector species complex in Uganda. New approaches to malaria vector control are being explored including population suppression through swarm reductions and genetic modification involving gene drives. Designing and evaluating these new interventions require good understanding of the biology of the target vectors. Anopheles mosquito swarms have historically been hard to locate in Uganda and therefore have remained poorly characterized. In this study we sought to identify and characterize An. gambiae s.l mosquito swarms in three study sites of high An. gambiae s.l prevalence within Central Uganda.

METHODS

Nine sampling visits were made to three villages over a 2-year period. Sampling targeted both wet and dry seasons and was done for 2 days per village during each trip, using sweep nets. All swarm data were analysed using the JMP 14 software (SAS Institute, Inc., Cary, NC, USA), parametrically or non-parametrically as appropriate.

RESULTS

Most of the An. gambiae s.s. swarms sampled during this study were single-species swarms. However, some mixed An. gambiae s.s. and Culex spp. mosquito swarms were also observed. Swarms were larger in the wet season than in the dry season. Mean swarm height ranged from 2.16 m to 3.13 m off the ground and only varied between villages but not by season. Anopheles gambiae mosquitoes were present in all three villages, preferred to swarm over bare ground markers, and could be effectively sampled by field samplers.

CONCLUSIONS

This study demonstrated that An. gambiae s.l swarms could be effectively located and sampled in South Central Uganda and provided in-depth descriptions of hitherto poorly understood aspects of An. gambiae local swarm characteristics. Swarms were found close to inhabited households and were greater in size and number during the rainy season. Anopheles gambiae s.s swarms were significantly associated with bare ground markers and were sometimes at heights over 4 m above the ground, showing a necessity to develop tools suitable for swarm sampling at these heights. While mixed species swarms have been reported before elsewhere, this is the first documented instance of mixed genus swarms found in Uganda and should be studied further as it could have implications for swarm sampling explorations where multiple species of mosquitoes exist.

Estimation and usefulness of measurement uncertainty from sampling at different spatial scales: microns to kilometres

Uncertainty of measurement values (MU) is crucial to their reliable geochemical interpretation. MU can be estimated using the Duplicate Method, which requires the taking of a small proportion of duplicated samples, and can be applied at any spatial scale. The distance between the duplicated samples is selected to reflect the effect of analyte heterogeneity on the measurement result (i.e. estimated concentration) within each sampling target, at the particular scale of investigation. Three published case studies, at different spatial scales, are used to explain how the Duplicate Method can be applied to estimate MU. They also illustrate how MU can be used to improve geochemical interpretation and validate measurement procedures (that include sampling) by judging their fitness for purpose. At the kilometre scale, measurements from the GEMAS survey of agricultural soils across Europe are used to estimate their MU for the first time. The MU for 53 elements range from an uncertainty factor of 1.01 to over 10. The MU contributes more that 20% to the total variance for 8 of the 53 elements, showing that the measurement procedure was not fit for purpose in those cases. At the micron scale, measurements of oxygen isotopes in candidate quartz reference materials had MU that was dominated by its sampling component, caused by sometimes unacceptable heterogeneity. A third case study of Pb in soils at 12 UK sites showed that the Duplicate Method can also be used to quantify the heterogeneity (as factor 1.03 to 2.4), and that it can indicate different possible sources of an element.

Simple techniques for a complex problem: Sampling malaria vectors in Africa

Disease surveillance, including entomological surveillance, serves as the basis for all vector control program activities. How to do this in the most ecologically sensible way, so that the most suitable, naturalistic method, of control for that population can be identified, should be a priority. Here we describe a set of techniques, whose only energy requirement is a torch (flashlight), that can be used to collect both endo and exophagic and endo and exophilic malaria vectors. The data obtained over a number of years from an individual sentinel house in a village in Mozambique and from a village in Cambodia using these kinds of collection techniques, is presented.

The decline and fall of the mammalian stem

The mammalian crown originated during the Mesozoic and subsequently radiated into the substantial array of forms now extant. However, for about 100 million years before the crown's origin, a diverse array of stem mammalian lineages dominated terrestrial ecosystems. Several of these stem lineages overlapped temporally and geographically with the crown mammals during the Mesozoic, but by the end of the Cretaceous crown mammals make up the overwhelming majority of the fossil record. The progress of this transition between ecosystems dominated by stem mammals and those dominated by crown mammals is not entirely clear, in part due to a distinct separation of analyses and datasets. Analyses of macroevolutionary patterns tend to focus on either the Mammaliaformes or the non-mammalian cynodonts, with little overlap in the datasets, preventing direct comparison of the diversification trends. Here I analyse species richness and biogeography of Synapsida as a whole during the Mesozoic, allowing comparison of the patterns in the mammalian crown and stem within a single framework. The analysis reveals the decline of the stem mammals occurred in two discrete phases. The first phase occurred between the Triassic and Middle Jurassic, during which the stem mammals were more restricted in their geographic range than the crown mammals, although within localities their species richness remained at levels seen previously. The second phase was a decline in species richness, which occurred during the Lower Cretaceous. The results show the decline of stem mammals, including tritylodontids and several mammaliaform groups, was not tied to a specific event, nor a gradual decline, but was instead a multiphase transition.

Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: application to the Healthcare and Social Survey

BACKGROUND

Surveys have been used worldwide to provide information on the COVID-19 pandemic impact so as to prepare and deliver an effective Public Health response. Overlapping panel surveys allow longitudinal estimates and more accurate cross-sectional estimates to be obtained thanks to the larger sample size. However, the problem of non-response is particularly aggravated in the case of panel surveys due to population fatigue with repeated surveys.

OBJECTIVE

To develop a new reweighting method for overlapping panel surveys affected by non-response.

METHODS

We chose the Healthcare and Social Survey which has an overlapping panel survey design with measurements throughout 2020 and 2021, and random samplings stratified by province and degree of urbanization. Each measurement comprises two samples: a longitudinal sample taken from previous measurements and a new sample taken at each measurement.

RESULTS

Our reweighting methodological approach is the result of a two-step process: the original sampling design weights are corrected by modelling non-response with respect to the longitudinal sample obtained in a previous measurement using machine learning techniques, followed by calibration using the auxiliary information available at the population level. It is applied to the estimation of totals, proportions, ratios, and differences between measurements, and to gender gaps in the variable of self-perceived general health.

CONCLUSION

The proposed method produces suitable estimators for both cross-sectional and longitudinal samples. For addressing future health crises such as COVID-19, it is therefore necessary to reduce potential coverage and non-response biases in surveys by means of utilizing reweighting techniques as proposed in this study.

Variation vs. specialization: the dose-time-effect of technical and physiological variety in the development of elite swimmers

OBJECTIVE

It is heavily discussed whether larger variety or specialization benefit elite performance at peak age. Therefore, this study aimed to determine technical (number of different swimming strokes) and physiological (number of different race distances) variety required to become an international-class swimmer (> 750 swimming points) based on 1'522'803 race results.

RESULTS

Correlation analyses showed lower technical variety in higher ranked swimmers (P < 0.001), yet with small effects (0.11-0.30). However, Poisson distribution revealed dose-time-effects and specified number of swimming strokes required during each age group. Specifically, freestyle swimmers showed highest chances when starting to compete in three to four swimming strokes but reduced their variety to three swimming strokes at the ages of 12/13yrs with another transition to two swimming strokes at the ages of 19/21yrs (female/male swimmers, respectively). Although both sexes showed similar specialization pattern throughout their career, earlier specialization was generally evident in female compared to male swimmers. At peak performance age, freestyle was most frequently combined with butterfly. Swimmers who either kept competing in all five swimming strokes or focused on only one at the beginning of their careers showed lowest probability of becoming an international-class swimmer. Physiological variety increased during junior age but declined again to three race distances towards elite age.

Biomolecular dynamics in the 21st century

The relevance of motions in biological macromolecules has been clear since the early structural analyses of proteins by X-ray crystallography. Computer simulations have been applied to provide a deeper understanding of the dynamics of biological macromolecules since 1976, and are now a standard tool in many labs working on the structure and function of biomolecules. In this mini-review we highlight some areas of current interest and active development for simulations, in particular all-atom molecular dynamics simulations.

Evaluating rural household well-being and empowerment among women and young farmers in Senegal

This article provides a description of baseline survey data that was collected in Senegal in the regions of Sedhiou and Tambacounda in 2020, respectively, and as part of an agricultural development project aimed at improving the well-being and resilience of farming households. The survey was implemented using a structured questionnaire administered among 1503 households, 70% of whom are women and 30% are young people, in the two regions. This paper contains data that can helps in understanding the socioeconomic well-being and resilience of smallholder farming households, especially among women and youth. This data helps to associate information on: (i) the socioeconomic project area variables, (ii) the extent of use of irrigated and climate change-adapted crops; (iii) the level of soil and water resource management in the study regions; and (iv) the food security and dietary diversity with the well-being and empowerment of women and young smallholder farming households. In addition, the dataset can be used as a baseline or reference point to track the economic empowerment and climate resilience building achieved in the study regions.

Precision and accuracy of common coral reef sampling protocols revisited with photogrammetry

The rapid decline of coral reefs calls for cost-effective benthic cover data to improve reef health forecasts, policy building, management responses and evaluation. Reef monitoring has been largely based on divers' observations along transects, and secondarily on quadrat-based protocols, video and photographic records. However, the accuracy and precision of the most common sampling approaches are not yet fully understood. Here, we compared benthic cover estimates from three common sampling protocols: Reef Check (RC), Atlantic and Gulf Rapid Reef Assessment (AGRRA) and photoquadrats (PQ). The reef cover of two contrasting sites was reconstructed with ∼450 m2 orthomosaics built with high resolution Structure-from-Motion (SfM) photogrammetry, which were used as references for comparisons among protocols. In addition, we explored sample size requirements for each protocol and provided cost-effectiveness comparisons. Our results evidenced between-reef differences in the accuracy and precision of estimates with the different protocols. The three protocols performed similarly in the reef with low macroalgal cover (<0.5%), but PQ were more accurate and precise in the reef with relatively high (∼20%) macroalgal cover. The sample size for estimating coral cover with a 20% error margin and a 0.05 significance level was lower for PQ, followed by AGRRA and RC. Considering performance, cost surrogates and equipment needs, cost-effectiveness was higher for PQ. We also discuss costs, limitations and advantages/disadvantages of SfM photogrammetry as a sampling approach for coral reef monitoring.

A new adsorptive 3D-printed sampling device for simultaneous determination of 63 urinary organic acids by LC-MS/MS

BACKGROUND

The detection and quantification of urinary metabolites play an important role in disease diagnosis. In most cases, urinary analyses are done with liquid urine samples, which must be quickly transported to the laboratory to avoid metabolites degradation that is associated with temperature fluctuations. Consequently, dried sampling devices have emerged to minimize analyte degradation. However, most commercial dried sampling devices are expensive, aggregate low volumes, and need better analytical sensitivity. Therefore, a new dry urine sampling device that is inexpensive, suitable for domestic sampling operation, and efficient for quantifying metabolites without requiring high-resolution instruments is proposed in the present study.

RESULTS

The newly designed dry urine sampling device was produced by 3D printing that efficiently determines 63 urinary organic acids using liquid chromatography coupled with mass spectrometry (LC-MS/MS). The system's efficiency was demonstrated with analytical figures of merit, such as precision, accuracy, and stability of analytes after the sampling and storing of ordinary urine samples. The limits of quantification ranged from 0.01 to 0.42 ng mL-1. Precision and accuracy tests showed relative standard deviations of less than 15 %. The urine stability in the sampling device was high within seven days without any significant degradation of the metabolites. The method was applied to the analysis of 10 human urine samples and compared to a conventional method without the use of the sampling device. The results showed no statistically significant differences, demonstrating the method's efficiency.

SIGNIFICANCE

The proposed 3-D printing device was developed with fast, low-cost manufacturing features and can be manufactured with different volumetric capacities, adaptable to the needs of each user. Furthermore, it is innovative because this is the first sampling device that is effective for the simultaneous storage and preservation of several important urinary metabolites. Thus, it is anticipated that its application would contribute significantly to the identification of metabolic disorders.

Estimating Hidden Population Size of COVID-19 Using Respondent- Driven Sampling Method - A Systematic Review

INTRODUCTION

Currently, the ongoing COVID-19 pandemic is posing a challenge to health systems worldwide. Unfortunately, the true number of infections is underestimated due to the existence of a vast number of asymptomatic infected individual's proportion. Detecting the actual number of COVID-19-affected patients is critical in order to treat and prevent it. Sampling of such populations, so-called hidden or hard-to-reach populations, is not possible using conventional sampling methods. The objective of this research is to estimate the hidden population size of COVID-19 by using respondent-driven sampling methods.

METHOD

This study is a systematic review. We have searched online databases of PubMed, Web of Science, Scopus, Embase, and Cochrane to identify English articles published from the beginning of December 2019 to December 2022 using purpose-related keywords. The complete texts of the final chosen articles were thoroughly reviewed, and the significant findings are condensed and presented in the table.

RESULTS

Of the 7 included articles, all were conducted to estimate the actual extent of COVID- 19 prevalence in their region and provide a mathematical model to estimate the asymptomatic and undetected cases of COVID-19 amid the pandemic. Two studies stated that the prevalence of COVID-19 in their sample population was 2.6% and 2.4% in Sierra Leone and Austria, respectively. In addition, four studies stated that the actual numbers of infected cases in their sample population were significantly higher, ranging from two to 50 times higher than the recorded reports.

CONCLUSIONS

In general, our study illustrates the efficacy of RDS sampling in the estimation of undetected asymptomatic cases with high cost-effectiveness due to its relatively trouble-free and low-cost methods of sampling the population. This method would be valuable in probable future epidemics.

Evaluating the effect of moss functional traits and sampling on elemental concentrations in Pleurozium schreberi and Ptilium crista-castrensis in Eastern Canada (Québec) black spruce forest

Characterizing atmospheric depositions allows evaluating the impact of air pollution on ecosystems, human health, and the economy. It also informs decision-makers about the implementation of regulations improving environmental quality. Biomonitoring uses organisms, such as mosses, as proxies to assess the presence of atmospheric contaminants (e.g., metals). This approach is cost-efficient and does not require complicated infrastructure or scientific skills, making it suitable for large-scale monitoring initiatives and citizen-based campaigns. Therefore, precise sampling protocols are needed to limit bias. Biomonitoring data remains scarce in North America, compared to e.g., Europe, and there is a need to develop large-scale and long-term biomonitoring initiatives to record current and future atmospheric depositions. As there is no standardized international sampling protocol, this study assessed the impact of parameters known to affect the elemental concentration of mosses, using samples collected along a 1000-km transect in Eastern Canada (Quebec) from 2016 to 2022. We specifically examined the effects of species, stem color, canopy opening, time of sampling, and stem length on 18 elements. Non-parametric statistical tests indicate that these factors have significant effects on some metals, but differences are generally low (<30 %), except for stem length. These results suggest that sampling protocols can be flexible in terms of species, canopy opening, time of sampling, and stem color. However, normalizing the length of the stems analyzed is required to account for differences in growth rates between sites. Moreover, since no large-scale biomonitoring campaign using mosses has been conducted in Eastern Canada, this paper also provides the first elemental baseline for moss in the region.

Reflections on the design and application of 'Surveypura': a simulation-based pedagogical tool for quantitative research methods in public health and social sciences

It has been reported from various contexts that learning quantitative methods for public health and social research is challenging for students. Based on our observations of these challenges, we designed a simulation-based pedagogical tool called Surveypura to support classroom-based learning of quantitative research methods. The tool includes a large illustration of a fictional village with 155 houses, alongside data for each of the households. The features of the houses, household characteristics, and the village have been carefully designed to give the visual feel of an actual village and better assist the pedagogical process. The tool was used by five facilitators with their masters' students at our university in courses on social research and epidemiology. Our observations of the sessions and interactions with facilitators and students suggested that the tool supported more engaged learning of quantitative research methods in a non-intimidating manner. We believe that Surveypura can be a useful simulation-based pedagogical tool to teach quantitative research methods in epidemiology and social sciences even in other contexts.

Use of a commercial tissue dissociation system to detect Salmonella-contaminated poultry products

Successful detection of bacterial pathogens in food can be challenging due to the physical and compositional complexity of the matrix. Different mechanical/physical and chemical methods have been developed to separate microorganisms from food matrices to facilitate detection. The present study benchmarked a commercial tissue digestion system that applies both chemical and physical methods to separate microorganisms from tissues against stomaching, a standard process currently utilized by commercial and regulatory food safety laboratories. The impacts of the treatments on the physical properties of the food matrix were characterized along with the compatibility of the methods with downstream microbiological and molecular detection assays. The results indicate the tissue digestion system can significantly reduce the average particle size of the chicken sample relative to processing via a stomacher (P < 0.001) without adversely affecting either real-time PCR (qPCR) or plate counting assays, which are typically used to detect Salmonella. Furthermore, inoculated chicken treated with the GentleMACS resulted in a significant increase (P < 0.003) in the qPCR's detection capabilities relative to stomached controls. Cohen kappa (κ) coefficient and McNemar's test indicate the plating assays and PCR results agree with measurements obtained via the 3 M Molecular Detection System as defined in the MLG standard (κ > 0.62; P > 0.08). Collectively, the results demonstrate that the technique enables detection of pathogens in meat at lower levels of contamination using current industry standard technologies.

Comparison of swabbing and cutting-out DNA collection methods from cotton, paper, and cardboard surfaces

Choosing an inappropriate method of sample collection can often have a detrimental impact on DNA recovery. Multiple studies highlight the importance of selecting the recovery method based on the type of surface the DNA sample is located on. This study aimed to investigate the efficacy of sample collection via the single cotton swabbing method in comparison to recovery directly from the material cut from the surface. The three types of surfaces included cotton, paper, and cardboard. DNA sources comprised cell-free and cellular DNA, as well as blood and saliva as examples of body fluids commonly encountered at crime scenes. The data analysis revealed that the cutting-out method resulted in higher DNA recovery from all but cardboard surfaces, making it the more efficient collection method. Despite its limitations, the cutting-out method should be considered as the DNA recovery method of choice when suitable.

Relation between sampling, sensitivity and precision in strain mapping using the Geometric Phase Analysis method in Scanning Transmission Electron Microscopy

The sensitivity and the precision of the Geometric Phase Analysis (GPA) method for strain characterization is a topic widely discussed in the literature and is usually difficult to quantify. Indeed, the GPA precision is intricately linked to the resolution of the strain maps defined when masking the periodic reflections in Fourier space. In this study an additional parameter, sampling, is proposed to be analyzed regarding the precision of GPA by developing the concept of a phase noise in the GPA equations. Both experimentally and theoretically, the following article demonstrates how the precision, and the sensitivity of the GPA method is improved when using a larger pixel spacing to record an electron micrograph in Scanning Transmission Electron Microscopy (STEM). The counterintuitive concept of increasing the field of view to improve the GPA precision results is an extension of the application of strain characterization methods in STEM towards low deformation levels.

Current trends and challenges in the analysis of marine environmental contaminants by isotope ratio mass spectrometry

An increasing number of organic and inorganic pollutants are being detected in the marine environment, posing a severe threat to the ecosystem and human health, even in trace concentrations. Isotope ratio mass spectrometry (IRMS) is one of the critical methods for determining the origin and fate of environmental pollutants and characterising their transformation processes. It has been used for a relatively long time for ecological monitoring of some well-studied industrial hydrocarbons at contaminated sites. However, the method still faces many analytical challenges. This review provides a comprehensive overview of recent technical advances concerning IRMS analysis of various contaminants and discusses typical pitfalls encountered in marine environment analysis. Particular attention is given to the study of sampling techniques and sample preparation for examination, often the keys to successful research given the complexity of marine matrices and the diverse and numerous nature of contaminants. Prospects for developing IRMS to monitor pollution sources and pollutant transformation in the marine environment are outlined.

Enabling strain imaging in realistic Eulerian ultrasound simulation methods

Cardiovascular strain imaging is continually improving due to ongoing advances in ultrasound acquisition and data processing techniques. The phantoms used for validation of new methods are often burdensome to make and lack flexibility to vary mechanical and acoustic properties. Simulations of US imaging provide an alternative with the required flexibility and ground truth strain data. However, the current Lagrangian US strain imaging models cannot simulate heterogeneous speed of sound distributions and higher-order scattering, which limits the realism of the simulations. More realistic Eulerian modelling techniques exist but have so far not been used for strain imaging. In this research, a novel sampling scheme was developed based on a band-limited interpolation of the medium, which enables accurate strain simulation in Eulerian methods. The scheme was validated in k-Wave using various numerical phantoms and by a comparison with Field II. The method allows for simulations with a large range in strain values and was accurate with errors smaller than -60 dB. Furthermore, an excellent agreement with the Fourier theory of US scattering was found. The ability to perform simulations with heterogeneous speed of sound distributions was demonstrated using a pulsating artery model. The developed sampling scheme contributes to more realistic strain imaging simulations, in which the effect of heterogenous acoustic properties can be taken into account.

Micropollutant concentration fluctuations in combined sewer overflows require short sampling intervals

Combined sewer overflows (CSOs) are an important pathway of organic micropollutants from urban areas to open water bodies. Understanding the temporal dynamics of these micropollutants during overflow events is crucial for applying appropriate sampling methods and implementing effective management strategies. Yet, little is known about the dynamics of micropollutants in CSOs, because most studies report concentrations from single grab samples or event mean concentrations (EMCs). With unique high temporal resolution measurements (3 min), we show the real dynamics of polar organic micropollutants in CSOs of one small (2,700 people: P) and one large (159,000 P) urban catchment, for two micropollutant categories: (i) 33 micropollutants in municipal wastewater and (ii) 13 micropollutants from urban surface runoff. The concentration dynamics depend on the substance source and the catchment size. Indoor substances such as pharmaceuticals show high temporal dynamics with changes of 1 to 2 orders of magnitude within 9 min in the CSO of the small catchment. In contrast, outdoor substances at the small catchment and all substances at the large catchment display considerably lower variation. We tested various time-proportional sampling strategies to assess the range of error when estimating EMCs. We recommend an interval of 3 min to capture the dynamics of indoor substances in CSOs from small catchments. The results highlight that both future monitoring campaigns and the planning and management of urban wet-weather treatment systems will benefit from high temporal sampling resolutions, not only to understand dynamics but also to minimize errors of estimated EMCs.

The role of episodic memory sampling in evaluation

Many models of choice assume that people retrieve memories of past experiences and use them to guide evaluation and choice. In this paper, we examine whether samples of recalled past experiences do indeed underpin our evaluations of options. We showed participants sequences of numerical values and asked them to recall as many of those values as possible and also to state how much they would be willing to pay for another draw from the sequence. Using Bayesian mixed effects modeling, we predicted participants' evaluation of the sequences at the group level from either the average of the values they recalled or the average of the values they saw. Contrary to the predictions of recall-based models, people's evaluations appear to be sensitive to information beyond what was actually recalled. Moreover, we did not find consistent evidence that memory for specific items is sufficient to predict evaluation of sequences. We discuss the implications for sampling models of memory and decision-making and alternative explanations.

Burning questions: Current practices and critical gaps in evaluating removal of per- and polyfluoroalkyl substances (PFAS) during pyrolysis treatments of biosolids

Concerns surrounding potential health and environmental impacts of per- and polyfluoroalkyl substances (PFAS) are growing at tremendous rates because adverse health impacts are expected with trace-level exposures. Extreme measures are required to mitigate potential PFAS contamination and minimize exposures. Extensive PFAS use results in the release of diverse PFAS species from domestic, industrial, and municipal effluents to wastewater, which partition to biosolids throughout secondary treatment. Biosolids generated during municipal wastewater treatment are a major environmental source of PFAS due to prevailing disposal practices as fertilizers. Pyrolysis is emerging as a viable, scalable technology for PFAS removal from biosolids while retaining nutrients and generating renewable, raw materials for energy generation. Despite early successes of pyrolysis in PFAS removal, significant unknowns remain about PFAS and transformation product fates in pyrolysis products and emissions. Applicable PFAS sampling methods, analytical workflows, and removal assessments are currently limited to a subset of high-interest analytes and matrices. Further, analysis of exhaust gases, particulate matter, fly ashes, and other pyrolysis end-products remain largely unreported or limited due to cost and sampling limitations. This paper identifies critical knowledge gaps on the pyrolysis of biosolids that must be addressed to assess the effectiveness of PFAS removal during pyrolysis treatment.

Locating what comes to mind in empirically derived representational spaces

Real-world judgements and decisions often require choosing from an open-ended set of options which cannot be exhaustively considered before a choice is made. Recent work has found that the options people do consider tend to have particular features, such as high historical value. Here, we pursue the idea that option generation during decision making may reflect a more general mechanism for calling things to mind, by which relevant features in a context-appropriate representational space guide what comes to mind. In this paper, we evaluate this proposal primarily based on what comes to mind in different familiar categories. We first introduce an empirical approach for deriving the space of features that people use to represent items in a particular category and for locating the category members that come to mind within that space. We show that in both familiar and ad hoc categories, a category member's location along certain dimensions of the derived feature space predicts its likelihood of coming to mind. Next, we show that category members from these feature space locations come to mind by default in a way that is somewhat impervious to conscious control. We then demonstrate that the extent to which a given dimension is a predictor of what comes to mind within a category is related to how relevant that feature is for representing the category in question, using a novel measure of general feature relevance. Finally, we illustrate the usefulness of this framework in the context of a decision making task. We close with the proposal that people call category members to mind according to their location in representational space, specifically based on the predicted usefulness of considering category members with particular features.

Comprehensive insights into advances in ambient bioaerosols sampling, analysis and factors influencing bioaerosols composition

While the study of bioaerosols has a long history, it has garnered heightened interest in the past few years, focusing on both culture-dependent and independent sampling and analysis approaches. Observations have been made regarding the seasonal fluctuations in microbial communities and their connection to particular ambient atmospheric factors. The study of airborne microbial communities is important in public health and atmospheric processes. Nevertheless, the establishment of standardized protocols for evaluating airborne microbial communities and utilizing microbial taxonomy as a means to identify distinct bioaerosols sources and seasonal patterns remains relatively unexplored. This article discusses the challenges and limitations of ambient bioaerosols sampling and analysis, including the lack of standardized methods and the heterogeneity of sources. Future prospects in the field of bioaerosols, including the use of high-throughput sequencing technologies, omics studies, spectroscopy and fluorescence-based monitoring to provide comprehensive incite on metabolic capacity, and activity are also presented. Furthermore, the review highlights the factors that affect bioaerosols composition, including seasonality, atmospheric conditions, and pollution levels. Overall, this review provides a valuable resource for researchers, policymakers, and stakeholders interested in understanding and managing bioaerosols in various environments.

Experimental studies of fission product release from model fuel elements at the physical start-up of the IVG.1M research reactor

During the physical start-up of the IVG.1M research reactor, which involved the conversion to low-enriched uranium fuel, various studies were conducted using physical mock-ups of the fuel assemblies. The mock-up consisted of 468 model low-enriched uranium fuel elements that were cut into three sections without end coatings at the cut locations. This configuration allowed for the simulation of fuel element decompression and the experimental determination of fission product release into the coolant. The coolant samples obtained from the mock-up were analyzed using a gamma-spectrometer equipped with a high-purity germanium detector. As a result of the studies, the activities of fission products in the coolant and the averaged relative fission product release were determined. The relative release is defined as the ratio of the release rate of reference fission products to its birth rate. For the first time, fission product release was experimentally obtained in a situation simulating the decompression of IVG.1M fuel cladding.

Easy and reliable assessment of the prevalence of porcine post-weaning diarrhoea

Post-weaning diarrhoea is a condition of increasing importance due to recent restrictions and bans on the preventive use of antimicrobials and medicinal zinc oxide. For various purposes, it is valuable to monitor the occurrence of post-weaning diarrhoea. The aim of this paper was to propose a protocol for easy and reliable assessment of the prevalence of post-weaning diarrhoea within a section of pigs as an alternative to clinical examination of a random sample of pigs. Two datasets were collected in two different observational field investigations, including more than 4000 individual clinical examinations of newly weaned pigs. First we identified a clinical marker for post-weaning diarrhoea. Second, we drew samples by simulation from our two dataset using different simplified sampling strategies and compared these to conventional random sampling strategies. The prediction error for estimates of the diarrhoea prevalence within a section was compared for the different sampling strategies. The study showed that pigs with diarrhoea had an increased risk of displaying diarrheic soiling of the hind part as well as dull, long, and bristly hair coat, and possibly also hollow flanks and a suboptimal body condition score. Diarrheic soiling of the hind part was the best clinical predictor of diarrhoea; our best estimate of the diagnostic sensitivity was 76.1% (95% credible interval: 72.0, 79.8), and the specificity was 97.1% (95% credible interval: 96.5 0.97.7). Diarrheic soiling of the hind is only a valid clinical predictor of diarrhoea for the first 14 days after insertion into the nursery unit. The precision and accuracy of prevalence estimates were similar for haphazard sampling compared to random sampling of the pigs. Likewise, sampling from a restricted number of pens produced prediction errors similar to sampling across all pens. Yet, the study had limitations regarding sample sizes, and furthermore it is difficult to provide certainty for absence of effects. We recommend sampling pigs haphazardly within at least three randomly selected pens for post-weaning diarrhoea prevalence surveys in order to easily obtain a reliable prevalence estimate. Based on our findings, we conclude the paper by proposing a simple four-step protocol for surveys of the within-section prevalence of post-weaning diarrhoea.

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Is There Just One Type of Multisport Pathway? A Scoping Review of Multisport Engagement in Early Athlete Development

Multisport engagement is positioned as the antithesis to specialization within youth development pathways. However, different terms are used to describe the multisport pathway, which may create confusion regarding what the pathway should look like. This review investigated all published research examining the multisport pathway, with a focus on terminology, and how different terms have led to varying interpretations of this research. Four databases were searched for all peer reviewed studies published up until December 2021. All included papers were full text, in English, and focusing on multisport athlete engagement. In total, 1974 abstracts were screened for inclusion eligibility, resulting in 82 articles included within this review. General results showed most studies are empirical (71%, n = 58) and looked at athlete development pathways using retrospective questionnaires aimed at investigating the specific pathway to sporting excellence. However, despite the consensus that multisport athletes play many sports in their lifetime, there is little investigation into when and the level of intensity (play versus practice) at which these sports are being played. Further, inconsistencies in the terminology used to describe this pathway have made it difficult to understand potential mechanisms that lead to any positive or negative effects. It is recommended that differences between the key terms of diversification and sampling are clarified and should not be regarded as synonymous as they may represent different paths within multisport development based on varying levels of intensity of play and practice.

Flight Height and Diversity of Anastrepha (Diptera: Tephritidae) in an Anthropic Environment

Several fruit fly species are pest of fruit production in subtropical and tropical countries such as Brazil. Data about the fruit fly communities are relevant for understanding ecological aspects such as population dynamics, abundance, richness, and diversity. In these surveys, Multilure traps were hung about 2 m height accessible to collectors. Practically there are no data on the dynamics of fruit fly species in higher positions. Thus, a comparative analysis was performed to assess the influence of the Multilure traps height, 2 m and 10 m, to collect Anastrepha species in the agricultural and forest environments. The abundance of Anastrepha species was compared using GLM multivariate analysis and species diversity using Hill numbers for each tested height. The heat map graph, based on the Euclidean distance, was used to assess the interaction of species at each height. A total of 1080 females of Anastrepha were captured, with 722 and 358 specimens collected in traps hung at 10 and 2 m height, respectively. Fourteen species were collected, with most identified as A. fraterculus (Wiedemann) (lato sensu) (n = 435) and A. obliqua (Macquart) (n = 388). Species diversity of Anastrepha was greater at 2 m than at 10 m, as were the values of diversity indices corresponding to richness (q = 0), Shannon (q = 1), and Simpson (q = 2). We conclude that evaluations of aspects related to the distribution of Anastrepha species at different heights should be adopted in fruit fly population monitoring programs as a management strategy for pest species.

Methodological considerations for aqueous environmental RNA collection, preservation, and extraction

Environmental RNA (eRNA) analysis is expected to infer species' physiological information (health status, developmental stage, and environmental stress response) and their distribution and composition more correctly than environmental DNA (eDNA) analysis. With the prospect of such eRNA applications, there is an increasing need for technological development for efficient eRNA detection because of its physicochemical instability. The present study conducted a series of aquarium experiments using zebrafish (Danio rerio) and validated the methodologies for capture, preservation, and extraction of eRNA in a water sample. In the eRNA extraction experiment, an approximately 1.5-fold increase in lysis buffer volume resulted in a more than sixfold increase in target eRNA concentration. In the eRNA capture experiment, although GF/F and GF/A filters yielded similar eRNA concentrations, a GF/A filter may be capable of passing through more volume of water samples and consequently collecting more eRNA particles, given the time required for water filtration. In the eRNA preservation experiment, the use of RNA stabilization reagent (RNAlater) allowed for stably preserving target eRNA on a filter sample at - 20 and even 4 °C for 6 days at least. Altogether, the findings enable the improvement of eRNA availability from the field and easily preserve eRNA samples without deep-freezing, which will contribute to the refinement of eRNA analysis for biological and physiological monitoring in aquatic ecosystems.

Robustness of genetic diversity measures under spatial sampling and a new frequency-independent measure

The genetic diversity of a taxon has often been estimated by genetic diversity measures. However, they assume random sampling of individuals which is often inapplicable. Except when the distribution of the taxon is limited, researchers conventionally choose several sampling locations from the known distribution and then collect individuals from each location. Spatial sampling is a formalized version of the conventional sampling, which objectively provides geographically even sampling locations to cover genetic variation in a taxon assuming isolation by distance. To evaluate the validity of the spatial sampling in estimating genetic diversity, we conducted coalescent simulation experiments. The sampling locations were selected by spatial sampling and one sample was collected from each location for the sake of theoretical simplicity. We also devised a new measure of genetic diversity, ς, which assumes spatial sampling and is independent of allele frequency. This new measure places an emphasis on rare and phylogenetically distant alleles which have relatively small effect on nucleotide diversity. Therefore, it can complementarily serve for conservation studies although it cannot be used to estimate population mutation rate. We compared ς with the other diversity measures in the experiments. Nucleotide diversity, expected heterozygosity and ς showed within 3% relative biases on average while Watterson's theta was 31% overestimation on average. Thus, genetic diversities other than Watterson's theta held good robustness under the spatial sampling.

Identification of the driving factors of microplastic load and morphology in estuaries for improving monitoring and management strategies: A global meta-analysis

Estuaries are one of the primary pathways for transferring microplastics (MPs) from the land to the ocean. A comprehensive understanding of the load, morphological characteristics, driving factors, and potential risks of MPs in estuaries is imperative to inform reliable management in this critical transboundary area. Extracted from 135 publications, a global meta-analysis comprising 1477 observations and 124 estuaries was conducted. MP abundance in estuaries was tremendously variable, reaching a mean of 21,342.43 ± 122,557.53 items/m3 in water and 1312.79 ± 6295.73 items/kg in sediment. Fibers and fragments take up a majority proportion in estuaries. Polyester, polypropylene, and polyethylene are the most detected MP types. Around 68.73% and 85.51% of MPs detected in water and sediment are smaller than 1 μm. The redundancy analysis revealed that the explanatory factors influencing the morphological characteristics of MPs differed between water and sediment. Regression analysis shows that MP abundance in water is significantly inversely correlated with mesh/filter size, per capita plastic waste, and the Human Development Index, whereas it is significantly positively correlated with population density and share of global mismanaged plastic waste. MP abundance in sediment significantly positively correlated with aridity index and probability of plastic entering the ocean, while significantly negatively correlated with mesh/filter size. Analysis based on Geodector identified that the extraction method, density of flotation fluid, and sampling depth are the top three explanatory factors for MP abundance in water, while the share of global mismanaged plastic waste, the probability of plastic being emitted into the ocean, and population density are the top three explanatory factors for MP abundance in sediment. In the studied estuaries, 46.75% of the water and 2.74% of the sediment are categorized into extremely high levels of pollution, while 73.08% of the water and 43.48% of the sediment belong to class V of the potential ecological index.

Mathematical Characterization of Private and Public Immune Receptor Sequences

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define "publicness" or "privateness" and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models.

A holistic approach for the selection of forensic DNA swabs

In the present study, we compared the performance of five different ISO 18385 certified forensic swabs for DNA sampling in practice over a time period of five months. Comparisons were made for DNA profiling success rates, measured as the percentage of CODIS (Combined DNA Index System) suitable profiles as well as for practical suitability during sampling at the scene, measured through a survey among collaborators. More than forty members of our crime scene investigation (CSI) unit took part in the test series and provided structured feedback concerning different aspects of swab handling. A total number of 1094 "touch" DNA samples have been subjected to DNA analysis. Swabs performed significantly different in terms of DNA profiling success rates. We also observed significant differences in DNA extraction efficiency between swabs. The evaluation by the collaborators of various aspects of handling differed significantly between swabs. We can assume that a more convenient handling decreases the risk of contamination or sample mislabelling and increases sampling efficiency and staff satisfaction. Our results demonstrate that the selection of disposable sampling devices such as forensic swabs for DNA sampling should be made based on a holistic approach. To be able to select the best performing swab for a given combination of CSI and DNA laboratory procedures, it might not be sufficient to only perform DNA extraction comparisons and trace sampling under controlled laboratory conditions.

Determination of microplastic contamination levels and trends in vast oceanic sediment areas with uncertainty

Small plastic particles, designated as microplastics, are known vehicles of several contaminants desorbed from their surface after being ingested by marine organisms. The monitoring of the levels and trends of microplastics in oceanic areas is essential to identify relevant threats and respective sources whose management should be improved to protect the environmental resources. However, the assessment of contamination trends in large oceanic areas is affected by contamination heterogeneity, sampling representativeness, and the uncertainty of collected sample analyses. Only contamination variations not justifiable by system heterogeneity and their characterisation uncertainty are meaningful and should be taken seriously by the authorities. This work describes a novel methodology for the objective identification of meaningful variation of microplastic contamination in vast oceanic areas by the Monte Carlo simulation of all uncertainty components. This tool was successfully applied to the monitoring of the levels and trends of microplastic contamination in sediments from a 700 km² oceanic area from 3 km to 20 km offshore Sesimbra and Sines (Portugal). This work allowed concluding that contamination has not varied between 2018 and 2019 (difference of mean total microplastic contamination between -40 kg^-1 and 34 kg^-1) but that microparticles made of PET are the major type of studied microplastics (in 2019, mean contamination is between 36 kg^-1 and 85 kg^-1). All assessments were performed for a 99 % confidence level.

Physical processes matters! Recommendations for sampling microplastics in estuarine waters based on hydrodynamics

Monitoring the abundance and characteristics of microplastics in estuarine waters is crucial for understanding the fate of microplastics at the land-sea continuum, and for developing policies and legislation to mitigate associated risks. However, if protocols to monitor microplastic pollution in ocean waters or beach sediments are well established, they may not be adequate for estuarine environments, due to the complex 3D hydrodynamics. In this note, we review and discuss sampling methods and strategies in relation to the main environmental forcing, estuarine hydrodynamics, and their spatio-temporal scales of variability. We propose recommendations about when, where and how to sample microplastics to capture the most representative picture of microplastic pollution. This note opens discussions on the urgent need for standardized methods and protocols to routinely monitor microplastics in estuaries which should, at the same time, be easily adaptable to the different systems to ensure consistency and comparability of data across different studies.

Validation of a carbon monoxide sampling method using polypropylene syringes: a reliable alternative method, easy to implement in the field or emergency situations

Carbon monoxide (CO) is a lethal gas, present during incomplete combustion of carbonaceous materials. CO may be present in certain occupational atmospheres or during accidental events such as fires. Colorless and odorless, its presence can only be detected analytically. Nevertheless, the measurement methods available today may either be lacking (not available, for example, for military people deployed in the field) or not completely adapted (interference for electrochemical detectors, cost for infrared detectors). Another solution is to take samples on the field and then analyze them in a laboratory. Tedlar® bags or canisters can be used for this purpose but are relatively cumbersome. An alternative, not well described in the literature and not metrologically validated, consists in using plastic syringes. In order to generalize the use of this system and to characterize it in terms of performance and stability over time, we conducted a validation study. This method was validated using a 50-cc polypropylene syringe, over a concentration range of 2 to 40 ppm. The sampling system is efficient (sample yields between 101 and 102%) and repeatable (relative standard deviations under 2%). Storage tests were conducted on syringes containing 2 and 20 ppm carbon monoxide, indicating that the syringes can be stored for up to 2 weeks in the dark at room temperature. Coupled with a laboratory infrared analysis, this technique allows a high sensitivity and specificity. Easy to implement, rugged, inexpensive, and energy self-sufficient, this sampling system is attractive and offers a new solution for field or accidental situations.

Vertical distribution of inorganic nanoparticles in a Norwegian fjord

Due to the analytical challenges of detecting and quantifying nanoparticles in seawater, the data on distributions of NPs in the marine environment is limited to qualitative studies or by ensemble measurements subject to various analytical artifacts. Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) allows determination of individual inorganic NPs at environmentally relevant concentrations, yet only few studies have been conducted on selected elements in surface sea water. Here, a sequential multi-element screening method was developed and implemented to provide a first survey of the horizontal and vertical distributions of inorganic nanoparticles and trace elements in a pristine Norwegian fjord prospect for submarine tailings deposition. Statistical control of false-positive detections while minimizing the size detection limit was ensured using a novel raw signal processing. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) gave confirmative and qualitative information regarding particle morphology and composition. Following SP-ICP-MS screening for particles of 16 elements, particulate Al, Fe, Mn, Pb, Si and Ti were found and determined to mass concentrations in ng/L of 1-399, 1-412, below limit of detection (<LOD) - 269, <LOD - 1, <LOD - 1981 and <LOD - 127 ng/L with particle number concentrations up to 10⁸ particles per liter. Total metals concentrations were at least an order of magnitude higher, at concentrations in μg/L of 1-12 for Al, 2-13 for Fe, 0.3-11 Mn, 0.02-0.5 for Pb, 46 to 318 Si and 0.04-0.4 for Ti. A strong depth dependence was observed for both trace elements and particles with concentrations increasing with depth. Our results provide a baseline for the fjord and new data on environmental levels of both total metals and metal containing nanoparticles including the vertical and horizontal distribution of natural nanoparticles.

Analysis and asymptotic theory for nested case-control designs under highly stratified proportional hazards models

Nested case-control sampled event time data under a highly stratified proportional hazards model, in which the number of strata increases proportional to sample size, is described and analyzed. The data can be characterized as stratified sampling from the event time risk sets and the analysis approach of Borgan et al. (Ann Stat 23:1749-1778, 1995) is adapted to accommodate both the stratification and case-control sampling from the stratified risk sets. Conditions for the consistency and asymptotic normality of the maximum partial likelihood estimator are provided and the results are used to compare the efficiency of the stratified analysis to an unstratified analysis when the baseline hazards can be semi-parametrically modeled in two special cases. Using the stratified sampling representation of the stratified analysis, methods for absolute risk estimation described by Borgan et al. (1995) for nested case-control data are used to develop methods for absolute risk estimation under the stratified model. The methods are illustrated by a year of birth stratified analysis of radon exposure and lung cancer mortality in a cohort of uranium miners from the Colorado Plateau.

Spatiotemporal distribution of veterinary and human drugs and its predictability in Japanese catchments

Little is known about the predictability of mass flows of veterinary drugs in Asian catchments, where effluent from livestock farms is a major source. We therefore conducted this study to understand the applicability and limitations of a population-based emission model, which assumed usage of veterinary and human drugs to be evenly distributed over the national livestock or human population throughout the year, and sources to be effluent discharges at livestock farms, households, and sewage treatment plants in Japanese catchments. We monitored five veterinary drugs (lincomycin, sulfamonomethoxine, tiamulin, tylosin, and tilmicosin), two human and livestock drugs (sulfamethoxazole and trimethoprim), two human drugs (carbamazepine and clarithromycin), and a metabolite (sulfapyridine) of a human drug once a month over 2 years in eight Japanese rivers which have active livestock farming in their catchments. Mass flows of carbamazepine and sulfapyridine were stable, while those of veterinary drugs fluctuated widely, especially sulfamonomethoxine and tilmicosin, whose 25 %-100 % ranges averaged 1.5 and 1.2 log units, respectively, attributable mainly to their usage patterns. The model accurately predicted mean mass flows of carbamazepine in the rivers with errors of <±0.3 log unit. Although it slightly to moderately overestimated those of the other four human-related compounds, the incorporation of an empirical correction factor, determined to minimize mean absolute error (MAE) among the rivers, substantially lowered their MAEs to <0.23 log units. However, the MAEs of the five veterinary drugs were as high as 0.42 (sulfamonomethoxine) to 0.60 (tiamulin) log units even with the coefficient, likely due mainly to the spatial distribution of their usage per capita. So as not to overlook spatiotemporal elevation of risks of veterinary drugs, a stochastic method should be applied in their management. This is the first study to assess the use of spatiotemporal homogeneity in usage per capita of veterinary drugs in Asian catchments.

A Romanian case study

The scope of this study consists of setting up of an integrated cost-effective sampling & laboratory analyses procedure which delineates sampling, sub-sampling and analytical uncertainties in case of fine-grained extractive waste deposits. This procedure is designed to support the decision makers towards fine-grained waste deposits upcycling and land reclamation. This procedure consists of a balanced replicated sampling design (BRSD) coupled with a three split levels ANOVA data processing. The paper provides the readership with the mathematical backgrounds of the three split level ANOVA analysis (3L-ANOVA) and an Excel algorithm for its implementation. Also, the paper presents an example of implementation of the developed methods in the case of a Romanian iron ore tailings (IOT) old pond. The findings of the paper consist of: a) argues, based on OM, SEM-EDS, XRFS and XRD observations, that classical TOS is ineffective for fine-grained waste deposits; b) BRSD in conjunction with 3L-ANOVA analysis is the only approach fit for reliable characterization of the fine-grained stockpiles; c) sampling uncertainty is the critical factor of the uncertainty budget of the analyte concentration; d) Lilliefors approach is adequate for the hypothesis testing where or not the measurand is normal distributed; e) The outcomes of the BRDSD&3L-ANOVA investigations carried on Teliuc tailings, estimated at circa 5.5* 106 m3, consist mainly of mineral quantification at lot level i.e. quartz ∼54% (±7%), hematite ∼15% (±3%), calcite ∼11% (±3%), MgO 3% (±1%), Al2O3 9% (±2%). The concentrations of some CRMs like Ti, V, Ba, Y, W were found at ACE limits and their associated relative expanded uncertainties overpass 50%. Thus, the expanded uncertainties clearly depict the reliability of acquired data for the decision makers regarding waste valorization. f) The IOT into Teliuc can be upcycled as minerals for cement and ceramic industries as well as for geopolymer manufacture. Also, IOT can be downcycles as filler in road construction and mine closure. Finally, the Teliuc yard can be rehabilitated with zero-waste left behind. The data exactness provided by this procedure can be increased to any desirable level through increasing the number of collected items, but the cost of sampling and analyses increases proportionally. In such circumstances, the posted approach can be tailored at the stakeholder request as to safely underpin the decision to turn finegrained by-products into valuable secondary resources, facilitating a greater circularity of the mining industry.

Comparison of different approaches of soil sampling uncertainty determination

The ISO/IEC 17025 standard requires that all significant contributions have to be propagated to the measurement uncertainty, including also sampling uncertainties. We evaluated soil sampling uncertainties for gamma-ray spectrometry by using in-house and split-sample methods. By in-house method, the sampling uncertainty was determined by comparing standard deviations of measurement results and average analytical uncertainty. With split-sample method, it was calculated using between-sample and between-analysis variances. If analytical uncertainty is reliably determined, the in-house method is recommended because fewer measurements are needed.

Data-driven customer acceptance for attended home delivery

Home delivery services require the attendance of the customer during delivery. Hence, retailers and customers mutually agree on a delivery time window in the booking process. However, when a customer requests a time window, it is not clear how much accepting the ongoing request significantly reduces the availability of time windows for future customers. In this paper, we explore using historical order data to manage scarce delivery capacities efficiently. We propose a sampling-based customer acceptance approach that is fed with different combinations of these data to assess the impact of the current request on route efficiency and the ability to accept future requests. We propose a data-science process to investigate the best use of historical order data in terms of recency and amount of sampling data. We identify features that help to improve the acceptance decision as well as the retailer's revenue. We demonstrate our approach with large amounts of real historical order data from two cities served by an online grocery in Germany.

Whole fillet; differences in contaminant and nutrient contents

Risk- benefit assessments of seafood require high-quality food composition data. In accordance with EU regulations, Atlantic salmon (Salmo salar) has conventionally been sampled using the Norwegian Quality Cut (NQC), a sub-cut of the middle section of the fish, in Norwegian surveillance programs. By comparing the contents of nutrients and contaminants in 34 samples of farmed Atlantic salmon, we aimed to evaluate the representativeness of the NQC compared with the whole fillet. Of the 129 analytes evaluated, eight single analytes, in addition to 25 different fatty acids, showed significant differences between the cuts. Significant differences were evident for total fat, including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and sum PCB-6, but not for the sum of dioxins and dioxin-like PCBs. We further suggest that the NQC may still be used in large-scale sampling of Atlantic salmon, and that the whole fillet would be preferable when analysing the content of nutrients.

Detection of tick-borne encephalitis virus in ear tissue and dried blood spots from naturally infected wild rodents

BACKGROUND

Tick-borne encephalitis virus (TBEV) can cause severe neurological disease in humans. Its geographical distribution is expanding in Western Europe with unresolved causes and spatial patterns, necessitating enhanced surveillance. Monitoring the virus in the environment is complicated, as it usually relies on destructive sampling of small rodents to test organs for TBEV, which in addition to ethical considerations also raises issues for long-term monitoring or longitudinal studies. Moreover, even when the virus is not detected in the blood or organs of the rodent, TBEV can still be transmitted from an infected tick to uninfected ticks feeding nearby. This is due to the ability of TBEV to replicate and migrate locally within the epidermis of small mammals, including those that do not appear to have systemic infection. This suggests that the virus may be detectable in skin biopsies, which has been confirmed in experimentally infected laboratory rodents, but it remains unknown if this sample type may be a viable alternative to destructively obtained samples in the monitoring of natural TBEV infection. Here we test ear tissue and dried blood spot (DBS) samples from rodents to determine whether TBEV-RNA can be detected in biological samples obtained non-destructively.

METHODS

Rodents were live-trapped and sampled at three woodland areas in The Netherlands where presence of TBEV has previously been recorded. Ear tissue (n = 79) and DBSs (n = 112) were collected from a total of 117 individuals and were tested for TBEV-RNA by real-time RT-PCR.

RESULTS

TBEV-RNA was detected in five rodents (4.3% of tested individuals), all of which had a TBEV-positive ear sample, while only two out of four of these individuals (for which a DBS was available) had a positive DBS. This equated to 6.3% of ear samples and 1.8% of DBSs testing positive for TBEV-RNA.

CONCLUSIONS

We provide the first evidence to our knowledge that TBEV-RNA can be detected in samples obtained non-destructively from naturally infected wild rodents, providing a viable sampling alternative suitable for longitudinal surveillance of the virus.

Assessment of microplastics using microfluidic approach

Microplastics are plastic particles smaller than 5 mm, and microplastics have gradually become a severe environmental pollution source that exists in the atmosphere. The identification and quantification of microplastic particles are challenging, current approaches require expensive instruments and are usually time-consuming. In this study, a microfluidic method was introduced to detect and count microplastics using a polymer-based microfluidic chip. Microplastic particles were stained with Nile red, dispersed in the carrier fluid and passed through the microchannel. A fluorescence microscope filmed the whole process as microplastic particles passed through the microchannel. Finally, the software automatically analyzed the video footage for the microplastic particle counting and size analysis. The entire process is fully automated for microplastic particle counting and is much more efficient than the current manual counting method. The proposed study may have broad application potentials in the environmental field.