bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sustainable dye extraction: Annatto powder production in a fountain confined spouted bed
Authors: Almeida Natalia Pazin , Duarte Cláudio Roberto , Tellabide Mikel , Estiati Idoia , Olazar Martin , de Souza Barrozo Marcos Antonio 
Published: May 2024

AbstractThis study proposes an efficient and sustainable process for annatto powder production using a fountain confined spouted bed. With widespread applications in industries such as food, pharmaceuticals, and cosmetics, conventional extraction methods face environmental and economic challenges. Our study explores a solvent‐free and eco‐friendly approach using mechanical attrition within a fountain confined spouted bed, offering a cost‐effective solution for annatto cultivation. We systematically investigated the impact of four parameters—fountain confiner position and length, draft tube diameter, and airflow velocity—employing experimental design, multiple regression analysis, particle swarm optimization, and computational fluid dynamics–discrete element method (CFD‐DEM) simulations. The proposed optimization condition shows significantly higher collision intensity, improving annatto powder production compared to other central composite design tests. This study contributes to developing of a sustainable and economically viable method for dye production, with potential implications for annatto‐producing regions globally.
Side‐Chain Engineering of Non‐Fullerene Acceptors with Trialkylsilyloxy Groups for Enhanced Photovoltaic Performance†
Authors: Wang Qingyuan , Chen Qi , Meng Shixin , Tian Li , Wang Haiqiao , Chen Yu , Liu Zitong , Xue Lingwei , Zhang Zhi‐Guo 
Published: May 2024

Comprehensive SummarySide‐chain engineering has emerged as a highly effective strategy for tailoring the aggregation behavior and charge transport properties of non‐fullerene small molecule acceptors (SMAs). In this study, we designed and synthesized two SMAs, namely BTPSi‐Bu and BTPSi‐Pr, respectively incorporating tributylsilyloxy and triisopropylsilyloxy groups in their outer positions. Notably, BTPSi‐Bu exhibited better planarity, crystallization, and favorable phase separation when paired with PM6 donor polymer compared to its counterpart, BTPSi‐Pr. The resulting organic solar cells, utilizing the PM6:BTPSi‐Bu blend, demonstrated a remarkable power conversion efficiency of 17.41% and a high open‐circuit voltage of 0.859 V. These findings underscore the significance of integrating trialkylsilyloxy side chains into SMAs as a rational design approach for enhancing the performance of photovoltaic systems.
CSR and ownership structure: Moderating role of board characteristics in an emerging country context
Authors: Kaimal Anjali , Uzma Shigufta Hena 
Published: May 2024

AbstractThe existing literature on the impact of ownership structure on corporate social responsibility (CSR) showed inconsistent results and disregarded the possibility of non‐linear patterns in the relationship. The present study examines the non‐linear relationship between ownership structure (family, foreign, institutional, and government) and CSR expenditure of listed non‐financial service sector firms in India. Further, the moderating effect of board variables, including board size, board independence, multiple directorships and gender diversity, is explored in the ownership structure‐CSR nexus. Based on a balanced panel dataset of 243 non‐financial service sector companies listed in India, the study observed an inverse U‐relationship between institutional ownership and CSR. The study also found that family, foreign, and government ownership positively influence the firm's social engagement. However, the study could find partial support for the moderating role of the four board characteristics; board size, board independence, multiple directorships and gender diversity in ownership‐CSR association. The study contributes to existing CSR and corporate governance literature by exploring one of the major factors (ownership structure) impacting CSR and the role of board variables in the association.
Connecting the dots: A systematic review of corporate social responsibility, information asymmetry, and economic implications
Authors: Wang Yadong , Albitar Khaldoon , Chbib Imad 
Published: May 2024

AbstractThis paper conducts a comprehensive review of the theoretical and empirical connections between Corporate Social Responsibility (CSR), Information Asymmetry (IA), and their economic consequences. It employs a bibliometric analysis on 73 Web of Science manuscripts using VOSviewer1.6.18 software, combining this analysis with a literature review. The results reveal four thematic areas categorized into three clusters: CSR and IA, the impact of CSR and IA on internal risk control and corporate performance, and the broader effects of CSR and IA. The systematic literature review finds a prevailing consensus that CSR can alleviate IA issues, leading to positive economic outcomes like increased stock liquidity, enhanced investment efficiency, and reduced cost of capital. This study's uniqueness lies in its integration of bibliometric analysis and systematic literature review to provide a holistic summary of both theoretical frameworks and the economic implications of the CSR‐IA relationship. It offers valuable insights and recommendations for future research in this field.
Spatial and physical characteristics of bison wallows in the Flint Hills of Kansas
Authors: Horne Eva A. , Blackmore Pam , Bello Nora M. , Taylor Jeffrey , Skibbe Adam 
Published: May 2024

AbstractBison have long been considered a keystone species of North American prairies, increasing plant and animal diversity through a number of unique behaviors. One such behavior is wallowing, in which the repeated rolling of bison in the same spot leads to the formation of small, shallow, oval depressions called wallows. The objective of this study was to characterize spatial and physical attributes of bison wallows at the Konza Prairie Biological Station, a tallgrass prairie preserve in northeastern Kansas. We used aerial imagery from two different years (2011 and 2019) to assess the abundance and spatial distribution of these wallows in relation to fire frequency, elevation, and slope. We also recorded physical characteristics (2020) for a randomly selected subset of wallows and analyzed these data in relation to the same landscape features. Results from the analysis of the aerial images indicated that wallows were more abundant in areas characterized by combinations of more frequent burning, higher elevations, and little or no slope. In the 2020 physical measurements, we found that wallows were smaller in areas burned more often and shallower at higher elevations, particularly when located on grazing lawns. Terrestrial plants were found in approximately 72.1% of the wallows that were physically sampled, and their prevalence increased with increasing slope. We found some quantity of aquatic plants in approximately 7.1% of the sampled wallows. The probability of finding aquatic vegetation in wallows was higher on grazing lawns and in areas burned less frequently, particularly every 20 years. This study enhances the understanding of the distribution of wallows and their physical characteristics as a type of disturbance that could alter relationships within grassland communities.
Disparate home range dynamics reflect nutritional inadequacies on summer range for a large herbivore
Authors: Wagler Brittany L. , Smiley Rachel A. , Courtemanch Alyson B. , Lutz Daryl , McWhirter Doug , Brimeyer Doug , Hnilicka Patrick , Monteith Kevin L. 
Published: May 2024

AbstractThe spatial distribution of animals has consequences for nutrition, predator–prey dynamics, spread of diseases, and population dynamics in general. Animals must establish a home range to secure adequate resources to fuel their energy needs. Home ranges, therefore, are temporally and spatially dynamic, given the changing requirements of an animal and the availability of resources on the landscape. We used data from two populations of bighorn sheep with contrasting population dynamics following pneumonia epizootics and different habitat quality on their summer range to test the hypothesis that the distribution and size of home ranges are influenced by environmental conditions and reproductive status. We used a combination of data from 768 vegetation transects and remotely sensed metrics to index forage quality of consecutive biweekly home ranges for 27 bighorn sheep, June–August 2019–2021. There were population differences in home range dynamics that were consistent with resource limitations in the population declining in abundance. Animals in both populations increased the size of their home range through the summer in association with declining forage quality indexed by plant phenology. Furthermore, animals in the Whiskey Mountain population without offspring had home ranges more than twice the size of animals with offspring, whereas there were no differences in the home range size between animals with and without offspring in Jackson. We demonstrated that limitations young offspring impose on space use of a mother may have consequences for animals living where larger home ranges are needed to secure adequate resources—sheep on Whiskey Mountain had to travel 1000 m from escape terrain to access the same amount of biomass that the Jackson sheep could access directly adjacent to escape terrain. Forage quality and availability influence movement and space use. In the presence of disease, movement and space use may influence pathogen transmission and persistence. Thus, forage availability may play an indirect role in population dynamics in the presence of disease, which is another line of evidence for how environmental and nutritional conditions may influence population dynamics when coping with disease.
Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis
Authors: Jabbar Al‐Rikabi Saad Ayyal , Etemadi Ali , Morad Maher Mohammed , Nowrouzi Azin , Panahi Ghodratollah , Mondeali Mozhgan , Toorani‐ghazvini Mahsa , Nasli‐Esfahani Ensieh , Razi Farideh , Bandarian Fatemeh 
Published: May 2024

ABSTRACTObjectiveThis study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC).DesignIn this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients.MethodsThe nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes.ResultsAmino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups.ConclusionsThese findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.
Quantitative analysis of therapeutic peptides by CZE using multiple sample injection in hydrodynamically closed separation system
Authors: Stefanik Ondrej , Mikus Peter , Piestansky Juraj 
Published: May 2024

AbstractTherapeutic peptides have emerged as an innovative and promising class of therapeutic compounds in modern medicine. Synthetic peptide analogs triptorelin and lanreotide are known for their pronounced clinical versatility and potency. In this study, we present the development and validation of novel methods based on capillary zone electrophoresis performed in hydrodynamically closed system (HCS) and paired with ultraviolet detection and repeated injection sample introduction. To the best of our knowledge, we developed the first capillary electrophoresis‐based method for the determination of lanreotide, and concurrently, the first HCS method for the determination of triptorelin. Maximal separation efficiency and signal intensity were achieved using background electrolytes composed of 50 mM formic acid with the addition of 0.05% (v/v) methyl‐hydroxyethyl cellulose. The proposed methods exhibit favorable performance characteristics, namely, calibration curve (r2 exceeding 0.99), low limits of detection (0.25 µg/mL in a water matrix and 0.5 µg/mL in synthetic urine), acceptable precision (relative standard deviation ranging from 2.2% to 9.6% for intraday repeatability and between 5.2% and 14.9% for interday reproducibility), and accuracy (relative errors falling within the 91.1%–107.8% range). The method for triptorelin determination was then used for its quantification in a commercially available drug dosage form (powder for injection) and in spiked synthetic urine samples. The developed methods were also evaluated according to the novel blue applicability grade index, revealing their superior applicability. The results collectively point out the potential of the proposed methods for both quality control and clinical investigations.
A GIS‐based approach to site vegetated buffer strips for erosion control within an agricultural catchment in southern England
Authors: Hudson Cat , Lovell Harold , Pearson Alastair W. , Schaefer Martin , Soar Philip J. 
Published: May 2024

AbstractAgricultural soil erosion is largely attributed to arable intensification and increased mechanization. Runoff from arable land and intensively managed grassland transports sediment and contaminants across the landscape and into watercourses, causing crop loss, land degradation, and water quality issues. One low‐cost and low‐maintenance nature‐based mitigation approach is the implementation of vegetated buffer strips (VBS): grassland sited along field margins to trap sediment and contaminants, reducing transportation and diffuse pollution rates. GIS modelling using remotely sensed landscape indices and land parcel data can provide an efficient means of identifying priority areas for intervention at sub‐catchment or farm system scales. We develop and test a scalable runoff risk model in the lower Rother catchment, West Sussex. The model uses the Normalized Difference Vegetation Index (NDVI) applied to satellite images as an erodibility proxy and identifies locations along pathways that are conceivably at greatest risk of sediment accumulation and transfer, guided by field observations. We assess current and historical field boundaries near high‐risk locations, evaluating the potential capacity of their margins to contribute to runoff risk reduction using an innovative ranking system. Recommendations are made for VBS implementation and the value of historical field boundary and margin restoration is discussed. Our method offers a rapid approach with minimal data requirements to identify high‐risk sediment runoff locations and priority sites for intervention. The tool has the potential to guide decision‐makers responsible for targeting and implementing soil erosion and runoff control measures such as VBS, while also maximizing agri‐environmental and cultural benefits.
The interaction of PRDX1 with Cofilin promotes oral squamous cell carcinoma metastasis
Authors: Shen Yajun , You Zixuan , Li Lingyu , Tang Xiaofei , Shan Xiaofeng 
Published: May 2024

AbstractPeroxiredoxin 1 (PRDX1) is an important member of the peroxiredoxin family (PRDX) and is upregulated in a variety of tumors. Previous studies have found that high PRDX1 expression is closely related to the metastasis of oral squamous cell carcinoma (OSCC), but the specific molecular mechanism is elusive. To elucidate the role of PRDX1 in the metastasis process of OSCC, we evaluated the expression of PRDX1 in OSCC clinical specimens and its impact on the prognosis of OSCC patients. Then, the effect of PRDX1 on OSCC metastasis and cytoskeletal reconstruction was explored in vitro and in nude mouse tongue cancer models, and the molecular mechanisms were also investigated. PRDX1 can directly interact with the actin‐binding protein Cofilin, inhibiting the phosphorylation of its Ser3 site, accelerating the depolymerization and turnover of actin, promoting OSCC cell movement, and aggravating the invasion and metastasis of OSCC. In clinical samples and mouse tongue cancer models, PRDX1 also increased lymph node metastasis of OSCC and was negatively correlated with the phosphorylation of Cofilin; PRDX1 also reduced the overall survival rate of OSCC patients. In summary, our study identified that PRDX1 may be a potential therapeutic target to inhibit OSCC metastasis.
Genomic landscape defines peritoneal metastatic pattern and related target of peritoneal metastasis in colorectal cancer
Authors: Hu Minhui , Luo Rui , Yang Keli , Yu Yang , Pan Qiwen , Yuan Mingming , Chen Rongrong , Wang Hui , Qin Qiyuan , Ma Tenghui , Wang Huaiming 
Published: May 2024

AbstractThe primary objective of this study is to develop a prediction model for peritoneal metastasis (PM) in colorectal cancer by integrating the genomic features of primary colorectal cancer, along with clinicopathological features. Concurrently, we aim to identify potential target implicated in the peritoneal dissemination of colorectal cancer through bioinformatics exploration and experimental validation. By analyzing the genomic landscape of primary colorectal cancer and clinicopathological features from 363 metastatic colorectal cancer patients, we identified 22 differently distributed variables, which were used for subsequent LASSO regression to construct a PM prediction model. The integrated model established by LASSO regression, which incorporated two clinicopathological variables and seven genomic variables, precisely discriminated PM cases (AUC 0.899; 95% CI 0.860–0.937) with good calibration (Hosmer–Lemeshow test p = .147). Model validation yielded AUCs of 0.898 (95% CI 0.896–0.899) and 0.704 (95% CI 0.622–0.787) internally and externally, respectively. Additionally, the peritoneal metastasis‐related genomic signature (PGS), which was composed of the seven genes in the integrated model, has prognostic stratification capability for colorectal cancer. The divergent genomic landscape drives the driver genes of PM. Bioinformatic analysis concerning these driver genes indicated SERINC1 may be associated with PM. Subsequent experiments indicate that knocking down of SERINC1 functionally suppresses peritoneal dissemination, emphasizing its importance in CRCPM. In summary, the genomic landscape of primary cancer in colorectal cancer defines peritoneal metastatic pattern and reveals the potential target of SERINC1 for PM in colorectal cancer.
The impact of inflation on inequality in the CEMAC and UEMOA zones of Sub‐Saharan Africa
Authors: Mutascu Mihai , Lessoua Albert , Ianc Nicolae Bogdan 
Published: May 2024

AbstractThis paper explores the impact of inflation on income inequality in Sub‐Saharan Africa, over the period from 1997 to 2019. The Bayesian model averaging method, à la De Luca and Magnus (2011), is employed to empirically support the main conclusions. The main finding highlights that inflation has an asymmetrical impact on inequality in the Sub‐Saharan African (SSA) region, diminishing income disparities among the wealthy while exacerbating them among the impoverished. The results are sensitive to the economic characteristics of the country as well as the level of income brackets. Education, health expenditures, size of agriculture, economic development and control of corruption play pivotal roles in modelling the relationship between inflation and income inequality in the SSA region. Social safety net programs, monetary policies aimed at addressing inflation, investments in education, fostering inclusive economic growth, enhancing access to financial services for the impoverished, reforms to advance land rights and promoting regional cooperation should be the primary policy objectives for SSA countries.
Risk prediction of advanced colorectal neoplasia among diabetic patients: A derivation and validation study
Authors: Wong Martin CS , Leung Eman YM , Wang Harry HX , Huang Junjie 
Published: May 2024

AbstractBackground and AimColorectal cancer (CRC) is the third most common cancer in the world. This study devises and validates a clinical scoring system for risk prediction of advanced colorectal neoplasia (ACN) to guide colonoscopy evaluation among diabetic patients.MethodsWe identified 55 964 diabetic patients who received colonoscopies from a large database in a Chinese population (2008–2018). We recruited a derivation cohort based on random sampling. The risk factors of CRC evaluated by univariate analysis were examined for ACN, defined as advanced adenoma, CRC, or any combination thereof using binary logistic regression analysis. We used the adjusted odds ratios (aORs) for independent risk factors to devise a risk score, ranging from 0 to 6: 0–4 “average risk” (AR) and 5–6 “high risk” (HR). The other subjects acted as an independent validation cohort.ResultsThe prevalence of ACN in both the derivation and validation cohorts was 2.0%. Using the scoring system constructed, 78.5% and 21.5% of patients in the validation cohort were classified as AR and HR, respectively. The prevalence of ACN in the AR and HR groups was 1.5% and 4.1%, respectively. Individuals in the HR group had a 2.78‐fold increased prevalence of ACN than the AR group. The concordance (c‐) statistics was 0.70, implying a good discriminatory capability of the risk score to stratify high‐risk individuals who should consider colonoscopy.ConclusionThe clinical risk scoring system based on age, gender, smoking, presence of hypertension, and use of aspirin is useful for ACN risk prediction among diabetic patients.