bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metal concentrations and KIM-1 levels in school-aged children: a cross-sectional study
Authors: Mendoza‐Cano Oliver , Ríos‐Silva Mónica , Gonzalez-Curiel Irma , Camacho-delaCruz Arlette A. , Romo-García María Fernanda , Cuevas-Arellano Herguin Benjamin , Quintanilla‐Montoya Ana Luz , Martínez-Preciado Miguel A. , Rincón-Avalos Pedro , Hilerio-López Ángel Gabriel , Murillo‐Zamora Efrén 
Published: June 2024

AbstractEnvironmental exposure to heavy metals and metalloids, originating from sources such as mining and manufacturing activities, has been linked to adverse renal effects. This cross-sectional study assessed children's exposure to these elements and its association with urinary kidney injury molecule-1 (KIM-1). We analyzed data from 99 school-aged children residing in nine localities within the state of Colima, Mexico, during the latter half of 2023. Levels of 23 metals/metalloids and urinary KIM-1 were measured using inductively coupled plasma mass spectrometry (ICP-MS) and enzyme-linked immunosorbent assay, respectively. Detectable levels of these contaminants were found in over 91% of participants, with varied exposure profiles observed across locations ($$p$$
p
= 0.019). After adjusting for confounding factors like gender, age, and locality, higher levels of six metals/metalloids (boron, cadmium, cesium, lithium, selenium, zinc) were significantly associated with increased KIM-1 levels. Tailored mitigation efforts are crucial to protect children from regional pollutant burdens. However, limitations exist, as our study did not capture all potential factors influencing heavy metal/metalloid and KIM-1 levels.
Molluscs generate preferred crystallographic orientation of biominerals by organic templates, the texture and microstructure of Caudofoveata (Aplacophora) shells
Authors: Yin X. , Castro-Claros J. D. , Griesshaber E. , Salas C. , Sancho Vaquer A. , Checa A. G. , Schmahl W. W. 
Published: June 2024

AbstractCaudofoveata are molluscs that protect their vermiform body with a scleritome, a mosaic of unconnected blade/lanceolate-shaped aragonite sclerites. For the speciesFalcidens gutturosusandScutopus ventrolineatuswe studied the crystallographic constitution and crystal orientation texture of the sclerites and the scleritome with electron-backscatter-diffraction (EBSD), laser-confocal-microscopy (LCM) and field-emission electron microscopy (FE-SEM) imaging. Each sclerite is an aragonite single crystal that is completely enveloped by an organic sheath. Adjacent sclerites overlap laterally and vertically are, however, not connected to each other. Sclerites are thickened in their central portion, relative to their periphery. Thickening increases also from sclerite tip towards its base. Accordingly, cross-sections through a sclerite are straight at its tip, curved and bent towards the sclerite base. Irrespective of curved sclerite morphologies, the aragonite lattice within the sclerite is coherent. Sclerite aragonite is not twinned. For each sclerite the crystallographic c-axis is parallel to the morphological long axis of the sclerite, the a-axis is perpendicular to its width and the b-axis is within the width of the sclerite. The single-crystalinity of the sclerites and their mode of organization in the scleritome is outstanding. Sclerite and aragonite arrangement in the scleritome is not given by a specific crystal growth mode, it is inherent to the secreting cells. We discuss that morphological characteristics of the sclerites and crystallographic preferred orientation (texture) of sclerite aragonite is not the result of competitive growth selection. It is generated by the templating effect of the organic substance of the secreting cells and associated extracellular biopolymers.
Applying taper function models for black locust plantations in Greek post-mining areas
Authors: Wilms Florian , Berendt Ferréol , Bronisz Karol , Bashutska Ulyana , Fotelli Mariangela , Radoglou Kalliopi , Spyroglou Gavriil 
Published: June 2024

AbstractA key process in forest management planning is the estimation of tree volume and, more specifically, merchantable volume. The ability to predict the cumulative stem volume relative to any upper stem diameter on standing trees or stands is essential for forest inventories and the management of forest resources. In the 1980s, the Hellenic Public Power Corporation (HPPC) started the rehabilitation of lignite post-mining areas in Greece by planting mainly black locust (Robinia pseudoacacia, L.). Today, these plantations occupy an area of approximately 2570 ha, but the stem volume has not yet been estimated. Therefore, we aimed to estimate the over- and under-bark stem volume using taper function models for 30 destructively sampled trees. Of the nineteen calibrated fixed-effects models, Kozak’s (2004) equation performed best for both the over-bark and under-bark datasets, followed by Lee’s (2003) and Muhairwe’s (1999) equations. Two fixed effect models were compared with fitted coefficients from Poland and the United States confirming that the local model fits were better suited, as the foreign model coefficients caused an increase in root mean square error (RMSE) for stem diameter predictions of 13% and 218%, respectively. The addition of random effects on a single-stem basis for two coefficients of Kozak’s (2004) equation improved the model fit significantly at 86% of the over-bark fixed effect RMSE and 69% for the under-bark model. Integrated taper functions were found to slightly outperform three volume equations for predictions of single stem volume over and under bark. Ultimately it was shown that these models can be used to precisely predict stem diameters and total stem volume for the population average as well as for specific trees of the black locust plantations in the study area.
Green synthesis of zinc oxide nanoparticles using Rhus coriaria extract and their anticancer activity against triple-negative breast cancer cells
Authors: Mongy Youssef , Shalaby Thanaa 
Published: June 2024

AbstractThe growing interest in using plant extracts for the biogenic synthesis of zinc oxide nanoparticles (ZnO NPs) stems from their facile, eco-friendly, and biologically safe approach instead of chemical routes. For the first time, ZnO NPs were successfully biosynthesized using Rhus coriaria fruit aqueous extract as a reducing and capping agent. Characterization revealed that the biosynthesized ZnO NPs possessed a maximum absorbance of approximately 359 nm and closely resembled the hexagonal ZnO wurtzite crystalline structure, with an average crystalline size of 16.69 nm. The transmission electron microscope (TEM) showed the presence of spherical and hexagonal morphologies, with an average grain size of 20.51 ± 3.90 nm. Moreover, the elemental composition of the synthesized ZnO NPs was assessed via energy-dispersive X-ray spectrometry (EDX), and the presence of phytocompounds on their surface was subsequently verified through FT-IR analysis. The ζ-potential of ZnO NPs was recorded at − 19.9 ± 0.1663 mV. Regarding anti-cancer properties, ZnO NPs were found to possess potent anti-tumor effects on MCF-7 and MDA-MB-231 breast cancer cells. Their efficacy was dose-dependent, with IC50 values ranging from 35.04–44.86 μg/mL for MCF-7 and 55.54–63.71 µg/mL for MDA-MB-231 cells. Mechanistic studies in MDA-MB-231 cells revealed apoptosis induction, validated by DAPI staining, confocal microscopy, and Annexin V/PI staining, showing apoptosis by 12.59% and 81.57% at ½ IC50 and IC50 values, respectively. Additionally, ZnO NPs were observed to provoke S-phase arrest and inhibit colony-forming and metastatic potential by modulating apoptosis and metastasis-related genes. This study unravels new insights into how ZnO NPs provoke cancer cell death and inhibit metastasis, revealing new prospects in cancer nanotechnology.
Improving prediction accuracy of laser-induced shock wave velocity prediction using neural networks
Authors: Yang Haoyu 
Published: June 2024

AbstractThe velocity of laser-induced shock waves affects the efficiency and efficacy of laser-based processes. The ability to accurately estimate shock wave velocity is critical for optimizing experimental combinations, creating laser-based systems, and assuring desired results. Traditional approaches to predict shock wave velocity involve empirical equations and analytical models based on simplified assumptions. However, these methods often lack accuracy and fail to capture the complex dynamics of laser-matter interactions. To overcome these limitations, we used a combination of an artificial neural network and a genetic algorithm to predict shock wave velocity. In this method, the neural network structure is dynamically designed. The optimization method does this by modifying the neural network's weights and figuring out the network's structure on our behalf. Based on the findings, our suggested technique worked very well; it surpassed other comparison methods by achieving the lowest average errors in terms of RMSE and MAE, which are 4.38 and 3.74, respectively. Moreover, the analysis has shown that our proposed method has a high level of reliability in predicting impulsive wave velocity using a neural network.
Small RNA signatures of acute ischemic stroke in L1CAM positive extracellular vesicles
Authors: Manwani Bharti , Brathaban Nivetha , Baqai Abiya , Munshi Yashee , Ahnstedt Hilda W. , Zhang Mengqi , Arkelius Kajsa , Llera Ted , Amorim Edilberto , Elahi Fanny M. , Singhal Neel S. 
Published: June 2024

AbstractL1CAM-positive extracellular vesicles (L1EV) are an emerging biomarker that may better reflect ongoing neuronal damage than other blood-based biomarkers. The physiological roles and regulation of L1EVs and their small RNA cargoes following stroke is unknown. We sought to characterize L1EV small RNAs following stroke and assess L1EV RNA signatures for diagnosing stroke using weighted gene co-expression network analysis and random forest (RF) machine learning algorithms. Interestingly, small RNA sequencing of plasma L1EVs from patients with stroke and control patients (n = 28) identified micro(mi)RNAs known to be enriched in the brain. Weighted gene co-expression network analysis (WGCNA) revealed small RNA transcript modules correlated to diagnosis, initial NIH stroke scale, and age. L1EV RNA signatures associated with the diagnosis of AIS were derived from WGCNA and RF classification. These small RNA signatures demonstrated a high degree of accuracy in the diagnosis of AIS with an area under the curve (AUC) of the signatures ranging from 0.833 to 0.932. Further work is necessary to understand the role of small RNA L1EV cargoes in the response to brain injury, however, this study supports the utility of L1EV small RNA signatures as a biomarker of stroke.
Physical structure of the environment contributes to the development of diversity of microalgal assemblages
Authors: Lukács Áron , Szabó Sándor , T-Krasznai Enikő , Görgényi Judit , Tóth István , B-Béres Viktória , Lerf Verona , Nemes-Kókai Zsuzsanna , Borics Gábor 
Published: June 2024

AbstractAquatic macrophytes form a three dimensional complex structure in the littoral zones of lakes, with many physical, chemical and biological gradients and interactions. This special habitat harbours a unique microalgal assemblage called metaphyton, that differs both from the phytoplankton of the pelagial and from the benthic assemblages whose elements are tightly attached to the substrates. Since metaphytic assemblages significantly contribute to the diversity of lakes’ phytoplankton, it is crucial to understand and disentangle those mechanisms that ensure their development. Therefore, we focused on the question of how a single solid physical structure contribute to maintaining metaphytic assemblages. Using a laboratory experiment we studied the floristic and functional differences of microalgal assemblages in microcosms that simulated the conditions that an open water, a complex natural macrophyte stand (Utricularia vulgaris L.), or an artificial substrate (cotton wool) provide for them. We inoculated the systems with a species rich (> 326 species) microalgal assemblage collected from a eutrophic oxbow lake, and studied the diversity, trait and functional group composition of the assemblages in a 24 day long experimental period. We found that both natural and artificial substrates ensured higher species richness than the open water environment. Functional richness in the open water environment was lower than in the aquaria containing natural macrophyte stand but higher than in which cotton wool was placed. This means that the artificial physical structure enhanced functional redundancy of the resident functional groups. Elongation measures of microalgal assemblages showed the highest variation in the microcosms that simulated the open water environment. Our results suggest that assembly of metaphytic algal communities is not a random process, instead a deterministic one driven by the niche characteristics of the complex three dimensional structure created by the stands of aquatic macrophytes.
Circulating immunoglobulins and transient lymphocytopenia in a sub-study of CAPRISA 012B, testing HIV monoclonal antibodies in a phase 1 trial
Authors: Sobia Parveen , Mahomed Sharana , Sivro Aida , Paul Stephane , Osman Farzana , Harkoo Ishana , Garrett Nigel , Karim Quarraisha Abdool , Karim Salim S. Abdool , Archary Derseree 
Published: June 2024

AbstractAcute, transient lymphocytopenia, not clinically significant was observed in the CAPRISA 012B phase 1 clinical trial following administration of broadly neutralizing antibodies (bnAb)-CAP256V2LS alone or with VRC07-523LS. Lymphocytopenia was assigned upon a > 50% decline in absolute lymphocyte counts following bnAb administration. We posited that systemic immunoglobulins (Igs), and cytokine profiles of eight women who developed lymphocytopenia were different to the 12 women without lymphocytopenia. Plasma Ig subclasses (IgG)/isotypes (IgM/IgA), and 27 cytokines were measured at enrolment (prior to bnAbs) and at days 1, 7, 28, 56 post-bnAb administration. IgG subclasses, IgM and total lymphocyte counts were significantly lower prior to bnAbs in women with gradable lymphocytopenia than those without. Gradable lymphocytopenia compared to non-lymphocytopenia women had significantly higher MIP-1β from enrolment up to day 56. TNF-α was significantly lower in gradable lymphocytopenia compared to non-lymphocytopenia women for enrolment, days 7, 28 and 56 except for day 1. Within the gradable and within the non-lymphocytopenia women, from enrolment to day 1, significantly elevated IL-6, IL-8, IP-10, MCP-1, G-CSF and IL-1RA were found. Additionally, within the gradable lymphocytopenia women, 9 additional cytokines (TNF-α, MIP-1α, MIP-1β, RANTES, Basic FGF, eotaxin, IFN-γ, IL-17A and IL-4) were significantly elevated at day 1 post-bnAbs compared to enrolment. This sub study presents preliminary findings to support the monitoring of baseline immunological markers including lymphocyte counts for assessing the development of transient lymphocytopenia. In high-risk settings conducting clinical trials testing bnAbs for HIV prevention, understanding factors that could amplify rates of lymphocytopenia, even if transient, remain undefined.
Integrated metaheuristic algorithms with extreme learning machine models for river streamflow prediction
Authors: Van Thieu Nguyen , Nguyen Ngoc Hung , Sherif Mohsen , El-Shafie Ahmed , Ahmed Ali Najah 
Published: June 2024

AbstractAccurate river streamflow prediction is pivotal for effective resource planning and flood risk management. Traditional river streamflow forecasting models encounter challenges such as nonlinearity, stochastic behavior, and convergence reliability. To overcome these, we introduce novel hybrid models that combine extreme learning machines (ELM) with cutting-edge mathematical inspired metaheuristic optimization algorithms, including Pareto-like sequential sampling (PSS), weighted mean of vectors (INFO), and the Runge–Kutta optimizer (RUN). Our comparative assessment includes 20 hybrid models across eight metaheuristic categories, using streamflow data from the Aswan High Dam on the Nile River. Our findings highlight the superior performance of mathematically based models, which demonstrate enhanced predictive accuracy, robust convergence, and sustained stability. Specifically, the PSS-ELM model achieves superior performance with a root mean square error of 2.0667, a Pearson’s correlation index (R) of 0.9374, and a Nash–Sutcliffe efficiency (NSE) of 0.8642. Additionally, INFO-ELM and RUN-ELM models exhibit robust convergence with mean absolute percentage errors of 15.21% and 15.28% respectively, a mean absolute errors of 1.2145 and 1.2105, and high Kling-Gupta efficiencies values of 0.9113 and 0.9124, respectively. These findings suggest that the adoption of our proposed models significantly enhances water management strategies and reduces any risks.
Expressive suppression mediates the relationship between sleep quality and generalized anxiety symptomology
Authors: Bendall Robert C. A. , Elton Sophie N. , Hughes Alun T. L. 
Published: June 2024

AbstractAnxiety disorders are the most prevalent worldwide mental health disorder, resulting in high societal costs. Emotion regulation and sleep quality are associated with the development of psychopathologies including anxiety. However, it is unknown whether habitual emotion regulation strategy use can mediate the influence of sleep quality on anxiety symptomology. An opportunity sample in a healthy population completed the Pittsburgh Sleep Quality Index to provide a measure of sleep quality, the Emotion Regulation Questionnaire to assess habitual use of emotion regulation strategies, and the Generalized Anxiety Disorder Scale to record anxiety symptomology. Data were analysed using correlation and regression-based mediation analyses. Improved sleep quality was predictive of reduced habitual use of expressive suppression and reduced anxiety symptomology. Additionally, increased use of expressive suppression was predictive of greater anxiety symptomology. Cognitive reappraisal was not associated with sleep quality or anxiety severity. Further, novel findings using mediation analyses show that expressive suppression partially mediated the relationship between sleep quality and anxiety. Whilst longitudinal and experimental research are needed to establish causality, these findings suggest that simultaneously targeting improvements in sleep quality and the use of specific emotion regulation strategies, including expressive suppression, may improve the efficacy of interventions focussed on reducing anxiety-related symptomology.
In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions
Authors: Knoedler Leonard , Knoedler Samuel , Hoch Cosima C. , Prantl Lukas , Frank Konstantin , Soiderer Laura , Cotofana Sebastian , Dorafshar Amir H. , Schenck Thilo , Vollbach Felix , Sofo Giuseppe , Alfertshofer Michael 
Published: June 2024

AbstractChatGPT has garnered attention as a multifaceted AI chatbot with potential applications in medicine. Despite intriguing preliminary findings in areas such as clinical management and patient education, there remains a substantial knowledge gap in comprehensively understanding the chances and limitations of ChatGPT’s capabilities, especially in medical test-taking and education. A total of n = 2,729 USMLE Step 1 practice questions were extracted from the Amboss question bank. After excluding 352 image-based questions, a total of 2,377 text-based questions were further categorized and entered manually into ChatGPT, and its responses were recorded. ChatGPT’s overall performance was analyzed based on question difficulty, category, and content with regards to specific signal words and phrases. ChatGPT achieved an overall accuracy rate of 55.8% in a total number of n = 2,377 USMLE Step 1 preparation questions obtained from the Amboss online question bank. It demonstrated a significant inverse correlation between question difficulty and performance with rs = -0.306; p < 0.001, maintaining comparable accuracy to the human user peer group across different levels of question difficulty. Notably, ChatGPT outperformed in serology-related questions (61.1% vs. 53.8%; p = 0.005) but struggled with ECG-related content (42.9% vs. 55.6%; p = 0.021). ChatGPT achieved statistically significant worse performances in pathophysiology-related question stems. (Signal phrase = “what is the most likely/probable cause”). ChatGPT performed consistent across various question categories and difficulty levels. These findings emphasize the need for further investigations to explore the potential and limitations of ChatGPT in medical examination and education.
Money for operator: the impact of linked agricultural subsidy on incomes
Authors: Yi Haoping , Guo Dengwang , Wang Haomin , Yi Guohui , Min Longzhen 
Published: June 2024

AbstractThe reform of China’s “three subsidies” has shifted the method of subsidization from payment based on the contracted area to payment based on the actual operational area. Within this context, studying the income-generating impact of the “three subsidies” holds significant practical relevance. Using data from the 2018 China Labor-force Dynamic Survey, this paper employs basic estimation, mediating effect, and moderating effect models to analyze the heterogeneity of agricultural subsidies’ impact on rural household income, the mediating effect of agricultural mechanization, and the moderating effect of operation scale. Our findings indicate that agricultural subsidies, known as the “three subsidies”, have increased total rural household income and agricultural income while decreasing wage income. However, they have shown no significant impact on business income. Notably, agricultural subsidies have significantly elevated the income of food-producing households, with agricultural mechanization partially mediating this effect. Operation scale positively moderates the impact of agricultural subsidies on rural household income and agricultural mechanization. Heterogeneity analysis indicates that agricultural subsidies have a more significant impact on rural household income among agricultural producers in the eastern region.