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There is a close relationship between urban green space and the physical and mental health of individuals. Most previous studies have discussed the impact of the structure of green space and its elements. This study focused on the emotional changes caused by common behaviors in urban green space (walking and sitting). We recruited 40 college students and randomly assigned them to walking and sitting groups (20 students per group). The two groups performed the same 8-min high-pressure learning task indoors and then performed 8-min recovery activities in a simulated urban green space (a bamboo-lawn space). We used the Emotiv EPOC+ EEG headset to dynamically measure six neural emotional parameters: “engagement,” “valence,” “meditation,” “frustration,” “focus,” and “excitement.” We conducted a pretest and posttest and used analysis of covariance (ANCOVA) to analyze the posttest data (with the pretest data as covariates). The results of the comparison of the two behaviors showed that the “valence” and “meditation” values of the walking group were higher than those of the sitting group, which suggests that walking in urban green space is more favorable for stress reduction. The sitting group had a higher “focus” value than did the walking group, which suggests that sitting in urban green space is better for attention restoration. The results of this study can provide guidance for urban green space planning and design as well as health guidance for urban residents.

Background Exposures to endocrine disrupting chemicals (EDCs) have been linked to chronic diseases including breast cancer, metabolic syndrome, diabetes, and infertility. Exposure during pregnancy may have a lifelong impact on the fetus. Services are needed to allow individuals to learn about their personal EDC exposures and how to reduce them. Million Marker (MM) aims to crowdsource and scale the biomonitoring of environmental chemicals and provide actionable results to empower individuals to proactively assess, track, and reduce their EDC exposures. In previous research, we developed and tested the first mobile EDC intervention service (mail-in urine testing and exposure report-back) for its efficacy in increasing EH literacy (EHL), willingness to reduce exposures (i.e., readiness to change, RtC), and system usability. After intervention, we found increased EHL, increased RtC in women (but not men), and decreased EDC exposure. However, some participants did not increase their RtC and had difficulty carrying out the intervention on their own. The reasons for these less optimal results were the difficulty in the EHL subject matter—participants still felt ill-prepared to apply their knowledge to making healthier lifestyle changes. Therefore, in this study, we will address these perceived limitations. Methods We will test a self-directed online interactive curriculum with live counseling sessions and individualized support modeled after the highly effective Diabetes Prevention Program (DPP). Recruiting from the Healthy Nevada Project (HNP), one of the largest population health cohorts in the world, we test the effectiveness of our EDC-specific online intervention curriculum via EHL and RtC surveys and determine changes in EDC exposure before and after intervention in a randomized controlled trial. We will also test for common clinical biomarkers via a commercially available at-home test (Siphox). We will recruit and randomize 300 women and 300 men of reproductive age (total n =600) from HNP. Our target population is men and women of reproductive age (18–44 years old). Discussion At the conclusion of this project, we will be well-positioned to scale our services to clinics and the general public, with the eventual aims of FDA approval, insurance coverage, and incorporation into routine clinical care.

Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent.

This manuscript reviews the state-of-the-art regarding human biological monitoring (HBM) of mycotoxins in plasma, serum and blood samples. After a comprehensive and systematic literature review, with a focus on the last five years, several aspects were analyzed and summarized: (a) the biomarkers analyzed and their encountered levels, (b) the analytical methodologies developed and (c) the relationship between biomarker levels and some illnesses. In the literature reviewed, aflatoxin B1-lysine (AFB1-lys) and ochratoxin A (OTA) in plasma and serum were the most widely studied mycotoxin biomarkers for HBM. Regarding analytical methodologies, a clear increase in the development of methods for the simultaneous determination of multiple mycotoxins has been observed. For this purpose, the use of liquid chromatography (LC) methodologies, especially when coupled with tandem mass spectrometry (MS/MS) or high resolution mass spectrometry (HRMS) has grown. A high percentage of the samples analyzed for OTA or aflatoxin B1 (mostly as AFB1-lys) in the reviewed papers were positive, demonstrating human exposure to mycotoxins. This review confirms the importance of mycotoxin human biomonitoring and highlights the important challenges that should be faced, such as the inclusion of other mycotoxins in HBM programs, the need to increase knowledge of mycotoxin metabolism and toxicokinetics, and the need for reference materials and new methodologies for treating samples. In addition, guidelines are required for analytical method validation, as well as equations to establish the relationship between human fluid levels and mycotoxin intake.

Metabolic biomonitoring in humans is typically based on the sampling of blood, plasma or urine. Although established in the clinical routine, these sampling procedures are often associated with a variety of compliance issues, which are impeding time-course studies. Here, we show that the metabolic profiling of the minute amounts of sweat sampled from fingertips addresses this challenge. Sweat sampling from fingertips is non-invasive, robust and can be accomplished repeatedly by untrained personnel. The sweat matrix represents a rich source for metabolic phenotyping. We confirm the feasibility of short interval sampling of sweat from the fingertips in time-course studies involving the consumption of coffee or the ingestion of a caffeine capsule after a fasting interval, in which we successfully monitor all known caffeine metabolites as well as endogenous metabolic responses. Fluctuations in the rate of sweat production are accounted for by mathematical modelling to reveal individual rates of caffeine uptake, metabolism and clearance. To conclude, metabotyping using sweat from fingertips combined with mathematical network modelling shows promise for broad applications in precision medicine by enabling the assessment of dynamic metabolic patterns, which may overcome the limitations of purely compositional biomarkers. Biomonitoring of sweat from fingertips overcomes current limitations in time-resolved metabolomic profiling of humans and may prove to become a powerful, noninvasive tool for precision medicine. Here, in a feasibility study of short interval sampling of sweat from fingertips, the authors assay individual dynamic metabolic patterns of endogenous and exogenous molecules.

The accurate determination of analyte concentrations with selective, fast, and robust methods is the key for process control, product analysis, environmental compliance, and medical applications. Enzyme-based biosensors meet these requirements to a high degree and can be operated with simple, cost efficient, and easy to use devices. This review focuses on enzymes capable of direct electron transfer (DET) to electrodes and also the electrode materials which can enable or enhance the DET type bioelectrocatalysis. It presents amperometric biosensors for the quantification of important medical, technical, and environmental analytes and it carves out the requirements for enzymes and electrode materials in DET-based third generation biosensors. This review critically surveys enzymes and biosensors for which DET has been reported. Single- or multi-cofactor enzymes featuring copper centers, hemes, FAD, FMN, or PQQ as prosthetic groups as well as fusion enzymes are presented. Nanomaterials, nanostructured electrodes, chemical surface modifications, and protein immobilization strategies are reviewed for their ability to support direct electrochemistry of enzymes. The combination of both biosensor elements—enzymes and electrodes—is evaluated by comparison of substrate specificity, current density, sensitivity, and the range of detection.

Insect monitoring is critical to improve our understanding and ability to preserve and restore biodiversity, sustainably produce crops, and reduce vectors of human and livestock disease. Conventional monitoring methods of trapping and identification are time consuming and thus expensive. Automation would significantly improve the state of the art. Here, we present a network of distributed wireless sensors that moves the field towards automation by recording backscattered near-infrared modulation signatures from insects. The instrument is a compact sensor based on dual-wavelength infrared light emitting diodes and is capable of unsupervised, autonomous long-term insect monitoring over weather and seasons. The sensor records the backscattered light at kHz pace from each insect transiting the measurement volume. Insect observations are automatically extracted and transmitted with environmental metadata over cellular connection to a cloud-based database. The recorded features include wing beat harmonics, melanisation and flight direction. To validate the sensor’s capabilities, we tested the correlation between daily insect counts from an oil seed rape field measured with six yellow water traps and six sensors during a 4-week period. A comparison of the methods found a Spearman’s rank correlation coefficient of 0.61 and a p-value = 0.0065, with the sensors recording approximately 19 times more insect observations and demonstrating a larger temporal dynamic than conventional yellow water trap monitoring.

As central place foragers, bees integrate information over large spatial scales on diet and pollutant exposure, offering insights into environmental impacts on their populations. Data from bee biomonitoring has strong applied and policy relevance, particularly when conducted over extensive spatial and temporal scales. However, practical challenges have limited large-scale sustainable implementation of such monitoring networks beyond relatively small-scale experimental studies. This paper describes the creation of a national, citizen science–led honeybee biomonitoring platform. Citizen scientist beekeepers provide biological samples at a national scale that would be cost prohibitive to replicate using conventional sampling strategies. Environmental DNA (eDNA) within honey allows quantification of spatial and temporal patterns in foraging resources. From 2018–2025, over 3,500 beekeepers have contributed 5,789 honey samples from across England, Wales, Scotland, and Northern Ireland. Most samples are collected between May and October and originate from intensively managed agricultural land (54% land use cover), urban and suburban areas (25%), forests (13%), and extensively managed landscapes (8%). eDNA analyses from 2018–2022 reveal strong temporal and spatial variation in plant resource use. Brassicas (wild and crop species such as oilseed rape), clovers (Trifolium spp.), and brambles (Rubus spp.) dominate honeybee diets, alongside notable use of invasive plants. Large-scale, long-term monitoring of floral resource use by honeybees establishes a benchmark for assessing resource availability to wider pollinator communities. The scheme provides data to interpret land-use change, agri-environmental policy outcomes, and climate-driven shifts in flowering resources. Archived honey samples also support future research on invasive species, bee pathogens, and chemical (including pesticide) exposure. The combination of citizen science and eDNA methods enables cost-effective, nationwide ecological monitoring at a scale unattainable through traditional approaches.

Biomonitoring is a very useful tool to evaluate human exposure to endocrine-disrupting compounds (EDCs), like bisphenols (BPs), which are widely used in the manufacture of plastics. The development of reliable analytical methods is key in the field of public health surveillance to obtain biomonitoring data to determine what BPs are reaching people’s bodies. This review discusses recent methods for the quantitative measurement of bisphenols and their derivatives in biological samples like urine, blood, breast milk, saliva, and hair, among others. We also discuss the different procedures commonly used for sample treatment, which includes extraction and clean-up, and instrumental techniques currently used to determine these compounds. Sample preparation techniques continue to play an important role in the analysis of complex matrices, for liquid matrices the most commonly employed is solid-phase extraction, although microextraction techniques are gaining importance in this field, and for solid samples ultrasound-assisted extraction. The main instrumental techniques used are liquid and gas chromatography coupled with mass spectrometry. Finally, we present data on the main parameters obtained in the validation of the revised methods. This review focuses on various methods developed and applied for trace analysis of bisphenols, their conjugates, halogenated derivatives, and diglycidyl ethers in biological samples to enable the required selectivity and sensitivity. For this purpose, a review is carried out of the most recent relevant publications from 2016 up to present.

In this review article, the research works covering the analytical determination of bisphenol A (BPA) and its structural analogues published from 2018 to present (February 2024) were examined. The review offers an overview of the concentration levels of these xenoestrogens in food and beverages, and discusses concerns that these may possibly pose to the human health and scrutinises, from an analytical perspective, the main biomonitoring approaches that are applied. This comes as a natural evolution of a previous review that covered the same topic but in earlier years (up to 2017). As compared to the past, while the volume of published literature on this topic has not necessarily decreased, the research studies are now much more homogeneous in terms of their geographical origin, i.e., Southern Europe (mainly Italy and Spain). For this reason, an estimated daily intake of the European population could not be calculated at this time. In terms of the analytical approaches that were applied, 67% of the research groups exploited liquid chromatography (LC), with a detection that was prevalently (71%) afforded by mass spectrometry, with over one-fourth of the research teams using fluorescence (26%) and a minority (3%) detecting the analytes with diode array detection. One-third of the groups used gas chromatography (GC)–mass spectrometry achieving comparatively superior efficiency as compared to LC. Derivatisation was performed in 59% of the GC studies to afford more symmetrical signals and enhanced sensitivity. Although the contamination levels are well below the threshold set by governments, routinely biomonitoring is encouraged because of the possible accumulation of these contaminants in the human body and of their interplay with other xenoestrogens.