bluuebunny/crossref_metadata_2025_split huggingface dataset:
Paint: a ubiquitous yet disregarded piece of the microplastics puzzle
Authors: Diana Zoie T , Chen Yuying , Rochman Chelsea M 
Published: January 2025

Abstract
Microplastics are widespread pollutants. Microplastics generated from the wear and tear of paints and coatings have recently been modeled to be a large source of microplastics to the environment. Yet, studies focused on microplastics broadly frequently overlook paint microplastics. In this article, we systematically reviewed the primary literature (turning up 53 relevant articles) on paint microplastic sources, identification methods, environmental concentrations, and toxicity to model organisms. Examples of sources of paint microplastics include paints from buildings and murals, crafts and hobbies, cars and roads, marine boats and structures, and industrial systems like pipes, sewers, and other infrastructure. Paint microplastics have been quantified in several marine samples from Europe and, to a lesser extent, East Asia. Reported concentrations of paint microplastics are up to 290,000 particles per kilogram of sediments, with the greatest concentration reported near a graffiti wall. Out of the toxicity studies testing paint microplastics, there have been 68 tested effects in total across all endpoints and organisms and 17 quantified lethal concentration 50% doses (ranging from 0.001 to 20 g/L). Of the tested effects, 45 observed endpoint values in the paint treatment were significantly different from the control (66%)—most of which were tests using antifouling paints. Overall, the number of studies on paint microplastics is small, limiting a holistic understanding of microplastics. Based on our synthesis of the state of the science on paint microplastics, we suggest a research agenda moving forward informed by research gaps.
The effects of a microplastic mixture on wood frogs (Rana sylvatica) across multiple life stages in an outdoor mesocosm experiment
Authors: Gene Sam M , Katzenback Barbara A , Wilson Jessica , Mallory Mark L , Provencher Jennifer F , Steel Elisabeth , Orihel Diane M 
Published: January 2025

Abstract
Microplastics have been found across the globe in the habitats of many amphibians. To investigate how exposure to microplastics affects hatching success, survival, growth, and development of wood frogs (Rana sylvatica), as well as how these animals may act as vectors for microplastics, a 96-day outdoor mesocosm experiment was conducted at the Queen’s University Biological Station (Ontario, Canada). Wood frogs were allocated to a negative control group or exposed to an additive-containing microplastic mixture (equal parts polypropylene, polystyrene, and polyethylene terephthalate) at nominal water concentrations of 0.069 g/L or 0.691 g/L. Whereas hatchling survival, hatching success, and hatchling size did not differ among experimental groups, exposure to microplastics caused increased larval growth at both microplastic concentrations and delayed larval development at the highest concentration. However, there was little evidence that survival, body size, or development of metamorphs were affected by exposure to microplastics. We found microplastics in the gastrointestinal tract and on the skin of wood frogs and also inside the liver and leg muscle. In addition, the presence of frogs enhanced the flux of positively buoyant microplastics between the aquatic and terrestrial environment. This study provides new insights into how microplastic pollution affects the growth and development of wood frogs and suggests that amphibians with a biphasic life cycle may act as biovectors of plastics across water–land interfaces.
Using digital pathology to standardize and automate histological evaluations of environmental samples
Authors: Tanabe Philip , Schlenk Daniel , Forsgren Kristy L , Pampanin Daniela M 
Published: January 2025

Abstract
Histological evaluations of tissues are commonly used in environmental monitoring studies to assess the health and fitness status of populations or even whole ecosystems. Although traditional histology can be cost-effective, there is a shortage of proficient histopathologists and results can often be subjective between operators, leading to variance. Digital pathology is a powerful diagnostic tool that has already significantly transformed research in human health but has rarely been applied to environmental studies. Digital analyses of whole slide images introduce possibilities of highly standardized histopathological evaluations, as well as the use of artificial intelligence for novel analyses. Furthermore, incorporation of digital pathology into environmental monitoring studies using standardized bioindicator species or groups such as bivalves and fish can greatly improve the accuracy, reproducibility, and efficiency of the studies. This review aims to introduce readers to digital pathology and how it can be applied to environmental studies. This includes guidelines for sample preparation, potential sources of error, and comparisons to traditional histopathological analyses.
Presence, removal, and risks of psychopharmaceuticals in wastewater streams
Authors: Davey Charlie J E , Hartelust Anne Kiki , Helmus Rick , Praetorius Antonia , van Wezel Annemarie P , ter Laak Thomas L 
Published: January 2025

Abstract
Psychopharmaceuticals are used to treat psychological disorders and other conditions relating to the nervous system and are known to affect nontarget organisms at low concentrations. Their occurrence in the water cycle remains an understudied topic, with data lacking for many compounds, and risks not accounted for in removal targets. Therefore, this study aimed to provide insights into the presence, removal, and risks of psychopharmaceuticals in wastewater. Furthermore, the use of risk assessment in the context of proposed legislation is discussed. Thirty highly used psychopharmaceuticals were studied during 1 week in the wastewater of the Amsterdam West Wastewater Treatment Plant (WWTP) using solid phase extraction and ultra high performance liquid chromatography–quadrupole time of flight–high resolution mass spectrometry. Twenty target compounds were detected in the influent (17 ng–99 µg/L) and 16 in the effluent (34 ng/L–17 µg/L). Removal efficiencies during treatment ranged from 24% to &gt;99%. Paracetamol, amphetamine, fluoxetine, levetiracetam, phenacetin, and sertraline demonstrated almost complete removal, whereas tramadol, lidocaine, lamotrigine, fluvoxamine, and carbamazepine had removals below 50%, with lidocaine demonstrating the lowest removal (24%). Utilizing existing ecotoxicity data, a preliminary risk assessment was performed to contextualize the calculated removal efficiencies. Here, sertraline and ibuprofen still demonstrated a potential risk, despite high removal efficiencies of both compounds. This study highlights that wastewater contains abundant numbers and ecotoxicologically relevant concentrations of psychopharmaceuticals that are insufficiently removed by the WWTP. The implementation of risk-based removal targets in legislation is discussed to facilitate the reduction in emissions of psychopharmaceuticals, for example, by adequate WWTP upgrades with advanced treatments to ensure a toxic-free environment.
Double-blind peer review is detrimental to scientific integrity
Authors: Mebane Christopher A 
Published: January 2025

Abstract
I make six arguments for why double-blind peer review practices increase vulnerability to scientific integrity lapses over more transparent peer review practices: (1) obscuring data from reviewers is detrimental; (2) obscuring sponsorship makes bias harder to detect; (3) author networks can be revealing; (4) undue trust and responsibility are placed on editors; (5) double-blind reviews are not really all that blind; and (6) willful blindness is not the answer to prestige bias. I offer an alternative approach that could provide a more transparent approach for improving scientific integrity and equity in publishing.
Factors affecting microplastic pollution of sandboxes in urban residential areas: Simple methodology for quality control in the context of potential exposure assessment for children
Authors: Krzciuk Karina , Dołęgowska Sabina , Gałuszka Agnieszka , Michalik Artur 
Published: January 2025

Abstract
Occurrence of microplastics in the environment is well studied, but our knowledge of their distribution in specific locations, such as the sandboxes, which are integral parts of popular playgrounds for children, is limited. Pioneering research on the factors affecting the microplastic pollution of sandboxes in urban residential areas was conducted within three estates in Kielce, Poland. Sand samples (Σ27) were collected from nine sandboxes and examined for the presence of microplastics, using a simple quality control methodology proposed by the authors. Microplastics were found in each sample and their contents ranged from 60 to 5,540 items/kg of sand. Fragments and fibers were the most prevalent types of microplastics in the samples. They contributed to approximately 95% of all microplastics found. Transparent fibers were the most abundant among fibers (63%) and red particles (57%) among fragments. A strong, positive, and significant correlation (rSpearman = 0.90) was found between the number of microplastic items and the location of sandboxes (above sea level). There was no correlation between the population density of the estates (rSpearman  =  0.03), the distance of the estates from the center (rSpearman  =  0.02), and the distance of the estates from main roads (rSpearman  =  0.43). Considering that sandboxes can be a potential source of microplastics for children, and assuming that sand ingestion by children is similar to the estimated daily soil ingestion rate, our results indicate that the number of microplastics ingested could be 1,106. Inhalation, dermal transport, and ingestion of microplastic particles from sandboxes pose a potential threat to children's health. However, more research is needed to better understand the health risks associated with this source of microplastics.
From water to land—Usage of Generalized Unified Threshold models of Survival (GUTS) in an above-ground terrestrial context exemplified by honeybee survival data
Authors: Bürger Leonhard Urs , Focks Andreas 
Published: January 2025

Abstract
In regulatory aquatic risk assessment, toxicokinetic-toxicodynamic (TKTD) methods, such as the generalized unified threshold model of survival (GUTS), are already established and considered ready for use, whereas TKTD methods for aboveground terrestrial species, like arthropods, are less developed and currently not intended for risk assessment. This could be due to the fact that exposure in aboveground terrestrial systems is more event-based (feeding, contact, overspray, etc.), whereas exposure in aquatic systems is simply related to substance concentrations in the surrounding water. To provide a generic TKTD framework for terrestrial invertebrates, we propose a new GUTS variant that includes an intermediate buffer between the external exposure and inside of the organism. This buffer can be interpreted as residues on the exoskeleton or in the stomach, depending on the uptake route. Such an uptake behavior is mechanistically reasonable and observable in laboratory experiments. This GUTS variant, BufferGUTS, is particularly suitable for discrete or discretized exposure scenarios. Testing our model on honeybee datasets for 13 pesticides reveals a similar or better reproduction of survival curves than existing models (GUTS-RED and BeeGUTS) while keeping the number of parameters the same and making no substance or species-specific assumptions. The proposed new BufferGUTS approach can prospectively be used to derive TKTD parameters for a variety of terrestrial arthropod species. A standardized model definition for terrestrial species will facilitate the comparison and extrapolation of parameters between species and the applicability for terrestrial risk assessments.
Observational studies on per- and polyfluoroalkyl substance toxicity in marine species: hints for the extrapolation of a screening value
Authors: Miniero Roberto , Brambilla Gianfranco , Maffucci Fulvio , Hochscheid Sandra , Esposito Mauro 
Published: January 2025

Abstract
A statistical procedure has been developed to derive a screening value from an observational study related to the developmental toxicity observed in loggerhead turtle (Caretta caretta) eggs exposed to long chain per- and polyfluoroalkyl substances (PFAS). A dataset of 41 nests in which the hatching rate was inversely correlated with the increase in the PFAS concentration in unhatched eggs was processed via a categorical regression approach. After outliers identification and removal, categorical regression analysis tested the relationships of the outcomes with the following parameters: perfluoro-nonanoic (PFNA), decanoic (PFDA), undecanoic (PFUdA), and dodecanoic (PFDoA) acids; perfluoroctansulfonate (PFOS); polychlorobiphenyls (PCBs) 28, 52, 101, 138, 153, 180; lead (Pb), total mercury (Hgtot), and cadmium (Cd); and other factors, such as “nest site,” “clutch size,” “incubation duration,” and “nest minimum depth,” as confounders/modifiers of the hatching rate. Among considered contaminants, PFOS, PFDA, and PFNA only were significant (p ˂ 0.05), as were “nest site,” “clutch size,” and “incubation duration,” confirming their possible role in decreasing the hatching rate of sea turtle eggs. According to a chemical-specific visual strategy, PFOS only showed a typical monotonic dose/response curve, which allowed the identification of provisional hypothetical thresholds of PFOS, 1,386 (CI95 = 1,080–1,692) ng/kg, corresponding to average hatching rates of 93.3% (CI95 = 91.4%–95.2%). Our preliminary results indicate the feasibility of the extrapolation of a screening value from observational studies under the following requirements: (a) individuation of most influencing factors for the outcome; (b) datasets referred to baseline contamination; (c) selection of undisturbed nests; (d) appropriate statistical multivariate methodology. This work aims to contribute to the New Approach Methods (NAMs) to assess PFAS early-stage embriotoxicity in marine biota.
Acute-to-chronic ratios of aquatic phototoxicity of polycyclic aromatic hydrocarbons and the prediction of chronic phototoxicity using the phototoxic target lipid model
Authors: Tillmanns Angeline , Marzooghi Solmaz , Kennedy Christopher J 
Published: January 2025

Abstract
Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that can be toxic to aquatic life at environmentally relevant concentrations. The toxicity of some PAHs increases in the presence of ultraviolet radiation (UVR). The phototoxic target lipid model (PTLM) builds on the narcotic target lipid model and predicts acute phototoxicity by accounting for the light absorbed by PAHs. Given the lack of chronic data for PAHs exposed to UVR, an acute-to-chronic ratio (ACR) was proposed as a means for extending this model for predicting chronic toxicity. No information could be found on ACRs derived for phototoxic chemicals and therefore, this study had two objectives: (a) to generate acute and chronic toxicity data with and without exposure to UVR; and (b) to test the ability of the PTLM to predict chronic toxicity using an ACR. Acute and chronic bioassays were conducted on eight species, with each exposed to three PAHs and two light treatments: with and without UVR. Although there was a general trend of higher ACRs in UVR treatments, there was no statistical difference across all species in the ACR values for UVR treatments. Data generated herein were combined with data collated through a literature search to generate a global ACR of 11.6. Twenty of the 24 predicted phototoxic effect concentration affecting 10% of species (EC10) values calculated using the PTLM and ACR were within a factor of 10 of the observed phototoxic EC10 or lethal concentration affecting 5% of species values. This study demonstrates the capability of ACR to be applied in the context of phototoxicity and therefore proposes an unprecedented methodology to predict the chronic phototoxicity of PAHs.
Ancestral bisphenol A exposure led to non-alcoholic fatty liver disease and sex-specific alterations in proline and bile metabolism pathways in the liver
Authors: Chakraborty Sourav , Anand Santosh , Numan Muhammad , Bhandari Ramji Kumar 
Published: January 2025

Abstract
Endocrine-disrupting chemicals can induce metabolic alterations, resulting in diseases such as obesity, diabetes, and fatty liver disease, which can be inherited by offspring inhabiting uncontaminated environments. Bisphenol A (BPA), a well-known endocrine disruptor, can induce endocrine disruption, leading to metabolic disorders in subsequent generations without further exposure to BPA via nongenetic transgenerational inheritance. Using medaka as an animal model, we reported that ancestral BPA exposure leads to transgenerational nonalcoholic fatty liver disease (NAFLD) in grandchildren four generations after the initial exposure. It is unclear if transgenerational NAFLD developed because ancestral BPA exposure differs from that developed due to direct and continuous BPA exposure because the transgenerational disease develops in the absence of the stressor. We induced transgenerational NAFLD in medaka with ancestral BPA exposure (10 µg/L) at the F0 generation and examined transcriptional and metabolomic alterations in the liver of the F4 generation fish that continued to develop NAFLD. To understand the etiology of NAFLD in unexposed generations, we performed nontargeted liquid chromatography–mass spectrometry-based metabolomic analysis in combination with bulk RNA sequencing and determined biomarkers, co-expressed gene networks, and sex-specific pathways triggered in the liver. An integrated analysis of metabolomic and transcriptional alterations revealed a positive association with the severity of the NAFLD disease phenotype. Females showed increased NAFLD severity and had metabolic disruption involving proline metabolism, tryptophan metabolism, and bile metabolism pathways. The present results provide the transcriptional and metabolomic underpinning of metabolic disruption caused by ancestral BPA exposure, providing avenues for further research to understand the development and progression of transgenerational NAFLD caused by ancestral bisphenol A exposure.
Insight into the molecular initiating event of mutagenic N-nitrosamines: a computational study on DNA alkylation by their diazonium ions
Authors: Cheng Shiyang , Qiu Houjun , Ding Wen , Kong Chuiyuan , Ma Juchen , Hou Runze , Liu Chunsheng , Ji Li 
Published: January 2025

Abstract
N-Nitrosamines are a class of compounds that includes the potent mutagenicity and carcinogenicity of many of its members and is distributed widely throughout the human environment. DNA alkylation by their diazonium ions formed metabolically acts as a molecular initiating event (MIE) that links molecular chemistry to mutagenicity. However, the regiochemistry for diazonium ions reacting with DNA bases is still under debate. Hence, density functional theory calculations involving SN2 alkylation of guanine (Gua) by 14 diverse diazonium ions are presented, the results of which showed the mutagenicity-related shift from GuaN7- to GuaO6-alkylation proceeds by increasing complexity of the alkylating agents, along with a greater proportion of SN1 characteristic in SN2 transition states. Hence, “high oxyphilic” and “low oxyphilic” alkylating agents may instead be “SN1” and “SN2” species, respectively. As the degree of MIE selectivity for hard−hard interactions can be quantified by hard and soft acids and bases theory, quantitative relationships were modeled between the nucleophilic index (ω-) and hydrophobicity (log P) of diazonium ions and their carcinogenic potency. Therefore, the mechanistic link from MIE to target toxicity can be bridged by computational chemistry.
Novel High-Quality Amoeba Genomes Reveal Widespread Codon Usage Mismatch Between Giant Viruses and Their Hosts
Authors: Willemsen Anouk , Manzano-Marín Alejandro , Horn Matthias 
Published: January 2025

Abstract
The need for high-quality protist genomes has prevented in-depth computational and experimental studies of giant virus–host interactions. In addition, our current knowledge of host range is highly biased due to the few hosts used to isolate novel giant viruses. This study presents 6 high-quality amoeba genomes from known and potential giant virus hosts belonging to 2 distinct eukaryotic clades: Amoebozoa and Discoba. We employ their genomic data to investigate the predictability of giant virus host range. Using a combination of long- and short-read sequencing, we obtained highly contiguous and complete genomes of Acanthamoeba castellanii, Acanthamoeba griffini, Acanthamoeba terricola, Naegleria clarki, Vermamoeba vermiformis, and Willaertia magna, contributing to the collection of sequences for the eukaryotic tree of life. We found that the 6 amoebae have distinct codon usage patterns and that, contrary to other virus groups, giant viruses often have different and even opposite codon usage with their known hosts. Conversely, giant viruses with matching codon usage are frequently not known to infect or replicate in these hosts. Interestingly, analyses of integrated viral sequences in the amoeba host genomes reveal potential novel virus–host associations. Matching of codon usage preferences is often used to predict virus–host pairs. However, with the broad-scale analyses performed in this study, we demonstrate that codon usage alone appears to be a poor predictor of host range for giant viruses infecting amoeba. We discuss the potential strategies that giant viruses employ to ensure high viral fitness in nonmatching hosts. Moreover, this study emphasizes the need for more high-quality protist genomes. Finally, the amoeba genomes presented in this study set the stage for future experimental studies to better understand how giant viruses interact with different host species.
Prediction of ground motion intensity measures using support vector machine in analysing spatial correlation
Authors: Wen Pan , Zhou Baofeng , Bi Xirong 
Published: January 2025

SUMMARY
Regional seismic risk assessments or engineering applications generally require the simultaneous estimation of ground motion intensity measures (IMs) at multiple stations. Spatial correlation plays a crucial role in characterizing the spatial distribution of IMs, typically as a function of the spatial separation distance. Previous studies using measured recordings have suggested that spatial correlation is additionally influenced by variations in site conditions or other earthquake parameters in the study regions. In this study, a machine learning method comprising multiple parameter inputs, called a support vector machine (SVM), is proposed to estimate the IMs of ground motions. This SVM model can inherit variations in the site conditions and earthquake information of the study region. Meanwhile, the generalization ability of the SVM model behaved distinctly, with a high similarity in the standard deviation between the training and test databases. Geostatistical analysis was performed to generate the spatial correlation of the IMs by introducing the SVM model. Considering the heterogeneous characteristics of the study region, the spatial correlation using the SVM model showed relatively low values, particularly for small separation distances and short periods, that is consistent with the results of previous studies. Finally, considering the high similarity of IMs at small separation distances (for example, less than 1 km in this study), the correlation was observed to be unsuitable for describing the spatial distribution of ground motion IMs at a small scale.