Search Results (7,252)

Environmental scientists are increasingly monitoring therapeutic drugs and their metabolites in water systems, requiring knowledge of human drug metabolism and excretion. Many published studies, however, rely on data from small-scale human metabolism trials, typically involving around six (healthy, young, male) volunteers. Their generalizability to real-world drug users may be limited, potentially biasing environmental monitoring efforts. Here, we leveraged untargeted LC-SWATH/MS pharmacometabolomics data from 283 potential living kidney donors and 688 kidney transplant recipients to characterize the 24 h urinary excretion profiles of two widely used diuretics frequently monitored in wastewater, hydrochlorothiazide and furosemide. Both are expected to be excreted largely unchanged, which our analyses confirmed. For hydrochlorothiazide, however, we also identified (using reference standards) the previously underreported transformation products chlorothiazide and salamide. These findings highlight the relevance and capability of using untargeted metabolomics data from human excreta to provide insights from large, real-world cohorts into which chemicals enter wastewater systems, with both drugs serving as exemplary case studies for analogous analyses of other drugs. In particular, the qualitative information obtained (e.g., accurate mass, retention time, fragment spectra) may inform targeted biomonitoring and highlight cases where consensus-based estimates of excreted drug or metabolite fractions are overestimated. Full article

Capital is classified as tangible and is used in the production process. It is a resource or collection of resources that can be accumulated or depleted, exchanged for other forms of capital, and unequally distributed. This study proposes holistic capital (HolC) as the synergistic value derived from the combined effects of multiple capitals, including human, behavioral, social, and spiritual capitals. Holistic capital is defined as the complex integration of human, behavioral, social, and spiritual resources that collectively enable individuals to function, thrive, and contribute meaningfully to their organizations and societies. It reflects a comprehensive spectrum that provides growth, transience, performance, thriving, and sustainability beyond customary financial or human capital models. Human capital theory, on which this proposed study is based, has a profound impact on multiple disciplines and is of deep interest to academicians and social scientists. Though the theory is a subject of severe criticism, it has easily survived and expanded its influence since its inception. Not surprisingly, a considerable number of criticisms have been made in response to this expansion. Based on this theory and to bridge gaps in the literature and present them systematically, the proposed study adopts a holistic approach. This review article examines theories across four dimensions: theoretical, methodological, empirical, and practical. In this manner, the proposed study intends to conceptualize a new capital—the holistic capital. Full article

Scientists estimate that humanity has exceeded seven of nine planetary boundaries, threatening the entire planet with potentially catastrophic consequences for all species. We therefore have a moral imperative for future generations and other species to return to the safe side of those boundaries. Threats to these boundaries take the form of social dilemmas, defined as situations in which individuals acting in their own interest undermine collective welfare, which can only be solved through cooperation. Western economic theory has conditioned us to believe that humans are inherently selfish. This assumption has led economists, scientists, and policymakers to increasingly pursue market-based solutions to conservation approaches, which have yielded limited success. In contrast, this article argues that humans are inherently cooperative. We employ Multi-Level Selection Theory (MLS) to depict the evolutionary advantages of cooperation and to define morality as putting the group ahead of the individual. We examine two examples of MLS in action: Territories of Life (TOL) and Ubuntu. The paper provides guidance for pathways of Ecozoic governance, planning, and restoration. Applied in a Western context in Burlington, Vermont, the philosophies hold true, showing that social norms and group identity already shape ecological behavior in Burlington residents’ lawn care practices. Ultimately, providing an alternative economic model built on these ethical foundations, we introduce the Neighbor’s Goodwill that reframes social dilemmas in a game theory context. The Neighbor’s Goodwill demonstrates how loyalty, reciprocity, and social belonging alter payoff structures. This research is founded on the fact that humans are inherently social and tend to make decisions in the interest of the whole group over their own. Full article

Fish identification and classification tasks allow scientists greater data on the sustainability and diversity of fisheries. Advances in computer vision, particularly convolutional neural networks (CNNs), have enabled automated fish detection at scale; however, increased model depth may not justify the additional time and computational cost. This study examines the ResNet family of models for binary fish identification to assess whether deeper networks provide meaningful performance advantages over simpler configurations. We compare ResNet-18, ResNet-50, ResNet-101, and ResNet-152 using both non-pretrained and pretrained initializations. We introduce an Energy-Weighted Score (EWS) to enable comparison of computational resource usage using cost-based weighting. A reliable fish versus no-fish classification can be achieved with as few as 18 layers, yielding 99.975% accuracy which improved to 100% accuracy following threshold optimization. For binary fish identification, increasing ResNet depth provides increased EWS scores with little impact on accuracy returns over shallower models. Overall, models with fewer layers outperformed deeper models with more parameters, and additional depth and tuning techniques were unable to outperform simpler configurations while delivering higher EWS scores. Full article

Accurate and continuous monitoring of flood dynamics is fundamental to understanding wetland hydrological processes and their ecological implications, yet it remains challenging due to the inherent trade-off between spatial and temporal resolution in remote sensing observations. This study advances flood monitoring methodology by developing and validating a spatiotemporal fusion framework specifically designed for multi-source Synthetic Aperture Radar (SAR) data—an approach that has remained underdeveloped despite its critical importance for all-weather wetland observation. We propose the Fusion SAR Operational Monitoring (FSOM) framework, which integrates three established components—the Flexible Spatiotemporal Data Fusion (FSDAF) model, the Sentinel-1 Dual-Polarized Water Index (SDWI), and automated thresholding classification—into a coherent processing chain that generates consistent high-resolution flood extent time series from multi-sensor SAR data (Sentinel-1 and GF-3). The FSOM was applied to the Chen Lake Wetland from 2020 to 2024, producing a monthly flood map dataset at 5 m spatial resolution. Quantitative validation demonstrated the superiority of the FSOM-derived products. Compared to water classifications using original Sentinel-1 data, the FSOM results achieved a significantly higher overall accuracy (exceeding 90%) and Kappa coefficient (>0.90) than the Sentinel-1 results, which had overall accuracy (exceeding 86%) and Kappa coefficient (>0.75). Critically, the producer’s accuracy for water bodies consistently surpassed 91%, indicating a substantial reduction in omission errors and markedly improved detection of small water bodies. These results confirm the effectiveness of the proposed FSOM framework in mitigating the spatiotemporal resolution trade-off, thereby providing a reliable high-fidelity data foundation to support precise wetland conservation and flood disaster emergency response. The framework thus offers a practical tool for scientists and water resource managers seeking to enhance monitoring capabilities in the world’s most dynamic and ecologically significant wetland ecosystems. Full article

Background/Objectives: Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is linked to poorer overall survival and a higher risk of brain metastases compared to HER2-negative breast cancer. Current preclinical studies lack robust HER2+ metastatic syngeneic mouse models for investigating targeted and immunomodulatory therapies. This study aims to develop effective HER2+ mouse models to investigate response dynamics to HER2-targeted therapy and immunotherapy. Methods: The human HER2 gene (WT or mutant p.A775_G776insYVMA, GFP-tagged at the C-terminus) was introduced into triple-negative breast cancer (TNBC) mouse mammary carcinoma cells with known metastatic potential (4T1 and EO771) via lentiviral transduction. HER2 expression and phosphorylation were analyzed using Western blotting and immunohistochemistry. Tumors were treated with HER2-targeted therapy (trastuzumab and tucatinib), immune checkpoint blockade (anti-PD-1 and anti-CTLA-4), and anti-HER2 antibody–drug conjugate (ADC) to evaluate treatment efficacy. Metastatic potential was assessed with brain fluorescence imaging. Statistical analysis included ANOVA and Kaplan–Meier tests. Results: Newly established lines demonstrated expression of HER2+, with HER2^YVMA lines showing higher phosphorylation than HER2^WT lines. Cells were tumorigenic, demonstrating in vivo tumor take rates at 100% for 4T1-HER2 and 15–30% for EO771-HER2. HER2 overexpression led to a 30% increase in spontaneous brain metastasis in the 4T1-HER2 models. Trastuzumab alone did not reduce primary tumor size but significantly reduced brain GFP signal by 17% ± 8% and 26% ± 7% in the 4T1-HER2^WT and 4T1-HER2^YVMA models, respectively. Combinational therapies with anti-HER2 therapy and immune checkpoint blockade effectively suppressed primary tumor growth and prolonged survival in EO771-HER2^YVMA model. T-Dxd, but not T-DM1, demonstrated partial treatment response in the EO771-HER2^WT model. Conclusions: HER2+ syngeneic tumor models were developed that spontaneously metastasize to the brain and demonstrate variable responses to immunotherapies and ADCs. These models are valuable for advancing molecular imaging modalities for HER2+ brain metastasis, studying blood–brain barrier penetration of HER2-targeted drugs, and exploring the combination of therapies, including immunotherapy. Full article

Online misinformation has grown significantly with the widespread use of the internet and the ease of sharing content through social media, often without rigorous fact-checking or scientific validation. In this context, we examined the effect of trust in scientists and conspiracy beliefs on online misinformation susceptibility and fake news detection. A cross-sectional study was carried out. We used valid questionnaires to collect our data. Trust in scientists was assessed using the Trust in Scientists Scale. Conspiracy beliefs were measured using the Conspiracy Mentality Questionnaire. Participants’ susceptibility to online misinformation was evaluated using the Online Misinformation Susceptibility Scale. Our multivariable analysis identified that lower trust in scientists is associated with higher online misinformation susceptibility. Participants who believed in conspiracy behaviors showed also higher levels of misinformation susceptibility. Our multivariable model showed that participants who believe in conspiracy beliefs had a lower ability to detect fake news. We found a positive association between trust in sciences and fake news detection. We identified a negative association between interest in politics and fake news detection. Our findings showed associations between trust in scientists, conspiracy beliefs, online misinformation susceptibility and fake news detection. Identification of predictors of these outcomes is crucial to define high-risk groups and develop appropriate interventions to confront these issues. Full article

Introduction: SLC6A1-related neurodevelopmental disorder (SLC6A1-NDD) is an epileptic encephalopathy linked to mutations in the SLC6A1 gene and is characterized by early-onset seizures and developmental delays. Despite the growing recognition of SLC6A1 as a major cause of early-onset epilepsy, the electrophysiological changes associated with the disorder remain inadequately characterized. This study aims to identify electrophysiological biomarkers of SLC6A1-NDD by characterizing EEG delta power using automated tools, EEGLAB (v2023.1) and Persyst 13, exploring age- and state-related effects. Methods: We analyzed EEG recordings from 20 patients with SLC6A1-NDD and 20 neurotypical age- and sex-matched controls using EEGLAB and Persyst, quantifying delta power and related metrics. The Wilcoxon signed-rank method tested for differences between patients and controls, area under the curve (AUC) values evaluated patient classifier models, and Pearson’s correlation assessed concordance between EEGLAB and Persyst. Results: Patients with SLC6A1-NDD exhibited significantly elevated delta power (19.4 ± 4.1) compared to controls (14.2 ± 3.0; p < 0.001). The mean delta power showed an age-dependent increasing trend in patients (b = 0.5), contrasting with a decline in controls (b = −1.0; p < 0.001). In Persyst, the frequency of delta activity above an optimized threshold best differentiated patients from controls in wake epochs (AUC = 0.93). Concordance between EEGLAB and Persyst was one-to-one but with moderate variability (R² = 0.644; p < 0.001). Conclusions: Elevated delta power is a notable feature of SLC6A1-NDD. Cross-platform comparison demonstrates the feasibility of quantitative EEG analysis, while imperfect concordance highlights the need for pipeline standardization. Future work should validate these findings in larger cohorts and, as suitable reference data emerge, benchmark delta power metrics against age-matched children with other developmental and epileptic encephalopathies. Full article

Geometric morphometrics is an important component of quantitative research on insect morphology, widely applied in taxonomy, intraspecific variation, and phylogenetic studies. However, systematic research in this field remains limited, with few comprehensive summaries of research trends, hotspots, and core theories. This study, based on scientometric methods, analyzed 1321 publications indexed in the Web of Science database up to 31 December 2025, and presents a meta-scientific review from a macro perspective, revealing the research trends, hotspots, and future directions in the field. The results show that: (1) annual publications exhibit overall growth, while research methods evolved from single landmark analysis to multimodal and interdisciplinary approaches; (2) scientists from Brazil, the USA, and France are major contributors, with studies spanning morphology, taxonomy, and ecology; (3) taxonomic studies centered on wing shape analysis constitutes a major research hotspot, closely related to phylogeny, allometry, and sexual dimorphism; (4) highly co-cited studies provide the main theoretical and methodological foundations for the field. Future research, building on existing hotspots, will further integrate geometric morphometrics with genomics, ecological functional data, three-dimensional geometric morphometrics, and artificial intelligence-assisted approaches to advance integrative taxonomy within interdisciplinary and data-driven frameworks. Full article

Background/Objectives: Chronic alcohol use accelerates biological and cognitive aging, yet it remains unclear how cognitive aging progresses during abstinence in alcohol use disorder (AUD). It is also unknown to what extent this follows models such as accelerated aging or the age-related decline as proposed by the vulnerability hypothesis. This study examined age-related changes and cognitive recovery during abstinence in patients with AUD. Methods: A total of 197 clinically admitted patients, referred for detoxification and extensive neuropsychological examination, were included. Neuropsychological testing was administered in the second and sixth week of admission using well-normed instruments. Using both multi-assessment and cross-sectional data, relationships between age and normed cognitive outcome scores were examined. Results: After six weeks of abstinence, age-related deviations were observed for perceptual reasoning (PRI), verbal comprehension (VCI), and short-term memory (SMI) but not for ten other cognitive indices. During admission, age significantly influenced the change in belonging to a specific recovery category. Each additional year of age reduced the odds of showing no cognitive impairment by 5% and reduced the odds of cognitive recovery by approximately 4%, compared to non-improvers. Conclusions: Age-related influences appear limited to specific cognitive functions and do not follow a uniform or easily interpretable pattern. Perceptual reasoning seems negatively affected after age 60 for participants with six weeks of abstinence. Older participants showed a reduced likelihood of cognitive recovery and a reduced likelihood of having no cognitive problems at all. The findings do not support accelerated aging and are still too weak to be considered evidence for the vulnerability hypothesis. Implications for future research are discussed. Full article

Within the payloads of JUICE and Europa Clipper, there are instruments suitable for the search of specific biosignatures that can diagnose life tracks in two ways. The payloads include mass spectrometers capable of measuring isotopic abundances for identifying life, and chromatography instruments testing whether ocean worlds harbor amphiphile mixtures, which would lead to a lipid-first origin of life. In this paper we describe how the two missions may begin to test whether there may be large detectable excursions of stable isotopes of chemical elements on the icy surfaces of the Jovian icy moons that are substantially shifted from their expected isotopic distributions. The detection of an unambiguous signal would suggest a biogenic origin, provided care is taken to exclude abiotic thermal isotopic fractionation. Our suggested tests should be confirmed independently with other techniques. Stable isotope geochemistry on the icy Jovian moons has not yet been thoroughly discussed in the literature. In addition, we enquire whether insights into life’s origin could be retrieved from Europa’s ocean and surface, including the question of the first steps in the evolution of life. Special emphasis has been put on an approach to seek on the surface of ocean worlds chemical phenomena that are rather primitive, such as reproducing lipid micelles as roots of protocells, but nevertheless can predict a path towards life with published models. Full article

The future of innovation and economic growth depends on our ability to nurture the next generation of scientists. The global shortage of qualified STEM (Science, Technology, engineering, Mathematics) teachers has led many countries to expedite the transition of subject-matter experts from industry and academia into teaching roles. These second-career science student teachers typically participate in accelerated training programs designed to address urgent shortages. This study addresses a gap in the literature regarding effective pedagogical interventions for career-changing professionals in STEM fields, focusing on the experience and transformation of second-career science student teachers. This qualitative case study explores how a Challenge-Based Learning (CBL) course fosters the development of pedagogical competences via developing an instructional unit collaboratively, among five second-career science student teachers enrolled in an accelerated teacher education program. Drawing on data collected through instructors’ field notes, iterative work-in-progress lesson drafts, and reflective final papers, the study employs qualitative content analysis to trace changes in participants’ instructional approaches and professional identity. Findings reveal that engagement with the CBL framework promoted a significant shift from teacher-centered to learner-centered instruction, as participants increasingly integrated collaborative learning, inquiry-based activities, and reflective practices into their lesson planning and classroom teaching. The iterative nature of CBL, which emphasizes real-world problem-solving and structured opportunities for reflection and peer feedback, was instrumental in supporting participants’ adaptive expertise and confidence as novice teachers. Moreover, the course experience contributed to the emergence of a professional teaching identity, with participants reporting greater self-efficacy, a stronger sense of belonging to the teaching community, and increased motivation to persist in the profession. The results underscore the potential of integrating CBL and learning sciences principles into accelerated teacher preparation programs to enhance both cognitive and affective dimensions of teacher development. Full article

Plastic and microplastic (MP) pollution, along with alien species invasion, are of great concern for natural habitat preservation and human health, and are two important and concomitant likely causes for global biodiversity loss. In the present study, a Seabin, a device for buoyant waste collection in calm waters, was used to also characterize the waste collected in northernmost side of Lake Garda (Italy) in a period of very low anthropogenic pressure, the Winter season of 2024–2025. During the survey, 92.6 g of plastic was collected, i.e., a total of 540 pieces. About 6.9 mg of plastic per m³ of water was found, corresponding to about 0.04 plastic items per m³ and approximately 13 pieces of microplastics per day. Fourier-transform Infrared (FTIR) spectroscopy identification showed that the plastic was composed mainly of polyethylene (PE), polypropylene (PP), and polystyrene (PS). Microorganisms (Diatoms, Bacillariophyta) and microcrack formation with deposits of inorganic matter (mainly Si, Al, O, Ca) were also evidenced by SEM/EDX in all the observed aged MP. Qualitative evaluation of the captured biota highlighted the presence of at least five alien species, including invasive Dikerogammarus villosus. This study describes an easy and cost-effective novel methodology for simultaneously monitoring plastic waste and alien species presence in calm waters, which acts also as a mitigation tool for plastic pollution. The results could be of interest not only to policymakers and scientists, but also for public health and for environmental monitoring. Full article

Ants are vital bioindicators that contribute to soil health and food webs, making accurate identification essential for biodiversity monitoring and conservation. However, traditional taxonomic methods are time-consuming and require specialized expertise, limiting large-scale data collection and public participation. This paper presents AntID_APP, a web-based application designed to support citizen scientists in Taiwan by enabling real-time, image-based detection and the identification of native ant genera. Fine-tuned YOLO models first detect ants in user-uploaded images and then classify them at the genus level. The models were trained on a curated dataset of 60,429 open-access images from iNaturalist, covering 54 native ant species. To ensure robustness in real-world conditions, we applied targeted data augmentation and evaluated multiple YOLO versions (v9–v12). The best-performing model achieved a mean Average Precision (mAP50: 0.935–0.948, mAP50-95: 0.777–0.807) for the detection task, followed by accurate genus-level identification. The application features an intuitive interface and a lightweight asynchronous server architecture, allowing users to upload images and receive both visual detection results (bounding boxes) and genus predictions efficiently. By combining high accuracy with accessibility, AntID_APP offers a scalable solution for biodiversity monitoring and public engagement in ecological research. Full article

Common buckwheat (Fagopyrum esculentum Mill.) is a pseudocereal that has recently gained increasing interest among both farmers and scientists. Its low soil requirements, high adaptability, and high resistance to diseases and pests allow it to be cultivated in many regions of the world. It is recommended for various cultivation systems, especially for low-input and organic farming. Currently, buckwheat is grown mainly for seeds and less often for green fodder. Thanks to its above-average nutritional value and many benefits that support human health, it is considered one of the leaders in functional food. It can be a basic raw material for many food products such as flour, groats, and flakes, but can also be used as a valuable addition to crisps, bars and drinks. Recently, buckwheat’s usefulness in the energy industry, construction, medicine, and pharmacology has been confirmed. Buckwheat, as a plant species distinct from the dominant global crops, fits very well into the current standards and assumptions of sustainable development. Its cultivation and consumption are associated with a number of benefits not only for human health but also for the whole environment. It is considered a species that counteracts climate change. Buckwheat’s valuable properties include its positive impact on soil physicochemical properties, its enhancement of biodiversity, and its support for pollinators. It is considered a species that can be cultivated in a changing climate, generating a very low carbon footprint. The aim of this study was to determine the contemporary economic importance of buckwheat, its place among species supporting sustainable development, and to identify potential research areas that will contribute to strengthening buckwheat’s role in sustainable agriculture. Full article