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The comet assay is one of the most popular tests for genotoxicity in cell cultures, non-animal species, animals and humans. It has high sensitivity to detect low levels of DNA damage, can be applied to non-proliferating cells, requires relatively few cells, is technically simple, and is low cost. The Organisation for Economic Co-operation and Development (OECD) adopted in 2016 the in vivo comet assay for measurement of DNA strand breaks in animal tissues. There is a desire to expand the comet assay to genotoxicity testing in cell cultures, including the detection of oxidatively damaged DNA by incubation of gel-embedded nucleoids with DNA repair enzymes, especially formamidopyrimidine DNA glycosylase (Fpg) which converts oxidised purines to DNA breaks. Based on available information in the literature, this review provides a retrospective evaluation of the validation status of this assay, focusing on accuracy and reliability in genotoxicity testing in vitro. Information on accuracy is scarce, although limited evidence suggests levels of Fpg-sensitive sites are similar to those obtained by Fpg-linked alkaline unwinding and alkaline elution assays. Several ring studies have shown that estimated background levels of DNA breaks vary within and between laboratories. However, ring studies indicate good intra- and inter-laboratory reproducibility of the standard assay on ionizing radiation-exposed and the Fpg-linked assay on potassium bromate exposed cells. Further studies are needed to assess the reproducibility in multiple laboratories using coded samples of non-genotoxins and genotoxins. Nevertheless, the available results indicate the comet assay is a reliable in vitro genotoxicity test.
2026
Abstract Methane is a powerful greenhouse gas with a shorter lifetime than carbon dioxide (CO 2 ), making it an important target for near‐term climate action. The Global Methane Pledge (GMP) aims to cut anthropogenic methane emissions by 30% from 2020 levels by 2030. Using an Earth system model with interactive CH 4 sources and sinks, we assess the Pledge's impact through 2050. Results show that current GMP commitments deliver only a 10% cut by 2030—well below the target. Only the maximum technically feasible reduction (MTFR) pathway can achieve the 30% goal. By 2050, current GMP commitments lowers methane concentrations by 3% relative to 2025, while MTFR achieves 8%. Both pathways slow warming slightly, avoiding about 0.1°C of global temperature rise, with the Arctic seeing the greatest benefits (up to 2°C less warming). Without wider participation, the GMP with current signatories will fall short of its targets and Paris Agreement goals.
2026
Scaling number concentration measurements from bioaerosol monitors using Hirst-type samplers
The instruments used for routine pollen monitoring are gradually changing from traditional impactors with manual data processing to automated pollen monitors using deterministic and/or machine-learning algorithms for data analysis. This manuscript compares pollen number concentration of Alnus sp., Betula sp., Corylus sp., and Poaceae measured by Hirst-type bioaerosol samplers and the SwisensPoleno automated bioaerosol monitor in Switzerland and Norway. Due to physical particle losses and the classification rate of the algorithms being well below unity, scaling factors had to be applied to the measurements of the SwisensPoleno to match those of the Hirst impactor. These scaling factors depended on the geographic location, i.e. differed significantly between Switzerland and Norway. The importance of adjusting the scaling factors according to the location of the monitoring network and the need for reporting the numerical values of these scaling factors in future scientific publications is emphasized.
2026
Urban areas experience elevated air pollution levels which pose significant health risks. Reducing exposure to poor air quality and mitigating the associated negative health impacts requires informed policy measures. This study advances urban air quality modelling by developing an air quality model (baseline model) and further integrating measurements from a network of low-cost sensors and regulatory monitors into the model output (data fusion model). The resulting data fusion model provides accurate air quality data in high spatiotemporal resolution. The data fusion model showed higher PM2.5 concentrations during evening hours and winter months, with a population-weighted exposure to PM2.5 almost twice as high as predicted by the baseline model during these months. The models exhibited different spatial patterns, with the data fusion model showing a shift in peak concentrations from the city centre to residential areas, where levels were up to 10 µg/m3 higher than the baseline model. These differences are likely attributable to an underestimation of residential emissions in the baseline model. While both models were FAIRMODE compliant, the data fusion model showed a reduced bias for most monitoring stations compared to the baseline model. The data fusion model enabled a more accurate assessment of existing policies, specifically those aimed at reducing urban air pollution from solid fuel burning. Moreover, by identifying locations and sectors which contribute significantly to high levels of PM2.5, the data fusion model supports the formation of targeted air quality policies. This enables cities to maximise reductions in air pollution and exposures, thereby safeguarding public health.
2026
Maritime sector pathways toward net-zero emissions within global energy scenarios
Abstract The maritime sector’s transition toward decarbonization cannot occur in isolation, rather it will be tied to broader transformations in energy, economic, and societal systems. Yet, most existing studies often overlook this integrated perspective, focusing primarily on sector-specific strategies without considering broader societal changes and energy availability on a global scale. To address this gap, this study integrates the MariTeam ship emission model into the MESSAGEix-GLOBIOM integrated assessment framework. Through this approach, we assess how climate scenarios may influence the maritime sector’s trajectory toward achieving net-zero emissions by 2050, in line with the International Maritime Organization (IMO) targets. Our findings indicate that action before 2030 is crucial and it can be achieved through combining four key solutions: improvements in energy efficiency, biofuels, liquefied hydrogen, and ammonia. Furthermore, the results suggest that the maritime sector could have access to enough renewables to achieve substantial emissions reductions with increase in final product costs ranging from 2 to 30% (interquartile range) with variations across products and regions. On average, cost increases are estimated at 10.2% for Global North countries and 13.3% for Global South countries. This analysis highlights the urgency and scale of transformation required for the maritime industry to meet the IMO’s net-zero ambitions and align with broader global sustainability goals.
2026
Urban Living Labs as Inter- and Transdisciplinary Arenas for Sustainability Planning Research
The transition towards sustainable societies necessitates inter- and transdisciplinary knowledge, particularly in urban planning, where diverse knowledge traditions are crucial for decision-making. Despite this, planning practices often remain entrenched in institutional and legal frameworks that hinder the integration of multiple ways of knowing and undervalue lay knowledge. Researcher-led urban innovation processes are increasingly adopting experimental approaches for the multi-stakeholder co-creation of knowledge, addressing urban challenges through interdisciplinary approaches. This article addresses the interdisciplinary collaboration between researchers in experimental urban planning processes by examining a research project that focused on participatory environmental co-monitoring and planning for urban air quality in Nordic contexts. The study builds a bridge between theories of interdisciplinarity, urban experimentation, and planning theory. By presenting urban living labs (ULLs) as arenas for co-learning that integrate scientific and lay knowledge, the article explores how planning researchers can facilitate mutual learning and navigate the micropolitics of knowledge co-production. We develop the concept of cross-disciplinary unknowns to highlight the dynamics and challenges in research teams with diverse epistemological backgrounds. We argue that an explicit and structured approach for explicating epistemological differences can facilitate the detection of unreflected knowledge retention between disciplines.
2026
Gastrointestinal image classification with GIDNet CNN model and non-linear Tansh activation function
2026
This study investigates the contamination of both ingested plastics and plasma of northern fulmars (Fulmarus glacialis) with benzotriazole UV stabilisers (BUVSs) in Kongsfjorden and Isfjorden, Svalbard. Ingested plastics were collected from fulmars in 1997, 2009, 2013, 2020 and 2021. Additionally, plasma samples were collected specifically in 2020. BUVSs, including UV-320, UV-326, UV-327, UV-328 and UV-329, were detected in both ingested plastics and plasma, suggesting a potential for transfer from plastics to the bloodstream. However, additional studies are required to confirm such a transfer mechanism. BUVSs were detected as early as 1997 in ingested plastics, highlighting the potential long-term exposure of fulmars in Svalbard. UV-326, UV-328 and total BUVS concentrations in ingested plastics increased significantly between 1997 and 2021, but likely due to outliers. In plasma, there was no significant correlation between any of BUVS concentrations and the mass of ingested plastics except for UV-327, although relying on only three values above LOD. This study represents a first step in investigating the multiple exposures of fulmars, and more generally seabirds, to plastic and plastic related chemicals and their potential ecotoxicological risks. More specifically we recommend further studies extracting microplastics from seabirds to perform additional quantification of BUVSs or other additives to provide available datasets and deeper understanding of leaching from plastics and temporal trends.
2026
Polluted air is a major global health risk factor, yet the chemical composition and toxicity of airborne gases and particles remain underexplored due to their complexity and difficulties in sampling. We recently introduced how polydimethylsiloxane (PDMS) foam─or silicone foam─can be synthesized for passive air sampling, enabling simple and cost-effective nontarget chemical profiling of indoor air. Here, we demonstrate expanded applications, indoors and outdoors, with commercial PDMS-foam, including for: (i) wide-scope target analysis of >220 priority substances by quantitative liquid- and gas chromatography-high-resolution mass spectrometry, (ii) microscopic characterization and nontarget profiling of accumulated fine particles, and (iii) effect-guided discovery of harmful substances, combining toxicological data with nontarget analysis in silico. Median method quantification limits were 0.12 ng/mL, 90% of target analytes had absolute recoveries between 70 and 130%, and hazardous substances were discovered, including ethylene glycols, insecticides, and UV filters. Microscopy revealed the accumulation of abundant fine particles, and the automated characterization of the fluorescent fraction revealed that most were <4 μm. Extracts from outdoor samples reduced human lung cell viability, and multivariate modeling flagged families of potentially toxic substances in a virtual effect-directed analysis. PDMS-foam disks require field calibration to determine their linear sampling rate(s), but current results and applications establish PDMS-foam as a multimodal passive sampler, enabling integrated chemical quantitation, toxicological analysis, and molecular discovery in air.
2026
Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.
2026