bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation, enrollment, and engagement in an opt‐out telehealth pharmacist‐assisted tobacco treatment program for patients seen in oncology outpatient clinics
Authors: Cummings K. Michael , Toll Benjamin A. , Talbot Vincent , Roberson Avery , Wilson Dianne , Dunlap Martha , Ware Emily C. , Palmer Amanda M. , Bliss Asia A. , Anokye Vincent S. , Warren Graham 
Published: March 2024

AbstractObjectiveTo describe the workflow, reach, cost, and self‐reported quit rates for an opt‐out tobacco treatment program (TTP) for patients seen in 43 oncology outpatient clinics.MethodsBetween May 25, 2021, and December 31, 2022, adult patients (≥18 years) visiting clinics affiliated with the Medical University of South Carolina Hollings Cancer Center were screened for smoking status. Those currently smoking were referred to a telehealth pharmacy‐assisted TTP. An attempt was made to contact referred patients by phone. Patients reached were offered free smoking cessation counseling and a 2‐week starter kit of nicotine replacement medication. A random sample of 420 patients enrolled in the TTP were selected to participate in a telephone survey to assess smoking status 4 to 12 months after enrollment.ResultsDuring the reference period 35,756 patients were screened and 9.3% were identified as currently smoking. Among the 3319 patients referred to the TTP at least once, 2393 (72.1%) were reached by phone, of whom 426 (12.8%) were ineligible for treatment, 458 (13.8%) opted out of treatment, and 1509 (45.5%) received treatment. More than 90% of TTP enrollees smoked daily, with an average of 13.1 cigarettes per day. Follow‐up surveys were completed on 167 of 420 patients, of whom 23.4% to 33.5% reported not smoking; if all nonresponders to the survey are counted as smoking, the range of quit rates is 9.3% to 13.3%.ConclusionThe findings demonstrate the feasibility of reaching and delivering smoking cessation treatments to patients from a diverse set of geographically dispersed oncology clinics.
A 2‐1‐1 multi‐level perspective of understanding the relationship between green human resource management practices, green psychological climate, and green employee behavior
Authors: Gupta Rohit , Kaur Sukhpreet 
Published: March 2024

AbstractThis study examines the mediating role played by green psychological climate between green human resource management practices and green employee behavior relationship. A cross‐sectional, survey‐based, multi‐level approach was adopted to understand the relationship among the variables. Data was collected from 77 HR managers and 445 employees using online and offline methods of data collection. Drawing on social exchange theory and social cognitive theory, the results of the study revealed that green psychological climate partially mediates the relationship between green human resource management practices and green employee behavior. The study is first in itself to empirically examine the relationship among the variables using multi‐level approach. Multi‐level approach of decoding the relationships in organization behavior is considered as a better way of unlocking the relationships since it addresses several methodological concerns. The study attempts to bind the ideas of social exchange theory, social cognitive theory and strategic HRM with green concept paving way for green strategic HRM. Green human resource management practices foster eco‐friendly HR practices, green psychological climate assesses the organizational atmosphere, and green employee behavior reflects sustainable behavior among employees. This comprehensive view allows organizations to integrate corporate social responsibility and environmental management seamlessly, ensuring that sustainable principles are embedded throughout the company's culture, operations, and employee actions, thereby promoting a more environmentally responsible and socially accountable corporate environment.
Controlled Enzymatic Synthesis of Polyesters Based on a Cellulose–Derived Triol Monomer: A Design of Experiment Approach
Authors: Warne Cicely M. , Fadlallah Sami , Allais Florent , Guebitz Georg M. , Pellis Alessandro 
Published: March 2024

AbstractRegioselective enzymatic polycondensation of the bio–based cellulose derived polyol, Triol–citro, and dimethyl adipate using Candida antarctica Lipase B (CaLB) was investigated. A Design of Experiment approach with MODDE® Pro 13 was used to determine important factors in the branching behavior of this polymer, and reactant ratio, temperature, reaction time and enzyme wt % were the studied factors. Multifunctional polyesters with pendant hydroxy groups were synthesized and fully characterized using 2D NMR techniques to determine degree of branching. Branching was minimal, with a maximum of 16 % observed, and monomer ratio, temperature and reaction time were all determined to be significant factors. In this work, Mn of up to 13 kDa were achieved, while maintaining degree of branching below 15 %, resulting in a linear polyester with the potential to be further functionalized.
Fully Conjugated Covalent Organic Framework Nanosheets for Visible–Light–Driven Organic Synthesis in Water
Authors: Ma Si , Hou Yuxin , Yang Liuliu , Yue Huijuan , Xia Hong , Liu Xiaoming 
Published: March 2024

AbstractCovalent organic framework (COF) nanosheets have recently garnered great attention as a new class of functional materials. As one of the sustainable processes, however, the photocatalytic organic synthesis in water has not been investigated using COF nanosheets as a photocatalyst to date. Herein, we reported the synthesis of a fully conjugated COF nanosheets with carboxyl functional group through a cooperative strategy of chemical exfoliation and group transformation. The new COF nanosheets was found to be an efficient heterogeneous photocatalyst for a wide range of organic synthesis including selective oxidation of sulfides and oxidative coupling of benzylamines in water under visible–light illumination. This work contributes a new roadmap for the design and synthesis of functional COF–based nanosheets, but also further extends the application boundary of the ultrathin COF nanosheets.
Examining the interaction between prenatal stress and polygenic risk for attention‐deficit/hyperactivity disorder on brain growth in childhood: Findings from the DREAM BIG consortium
Authors: López‐Vicente Mónica , Szekely Eszter , Lafaille‐Magnan Marie‐Elyse , Morton J. Bruce , Oberlander Tim F. , Greenwood Celia M. T. , Muetzel Ryan L. , Tiemeier Henning , Qiu Anqi , Wazana Ashley , White Tonya 
Published: March 2024

AbstractThis study explored the interactions among prenatal stress, child sex, and polygenic risk scores (PGS) for attention‐deficit/hyperactivity disorder (ADHD) on structural developmental changes of brain regions implicated in ADHD. We used data from two population‐based birth cohorts: Growing Up in Singapore Towards healthy Outcomes (GUSTO) from Singapore (n = 113) and Generation R from Rotterdam, the Netherlands (n = 433). Prenatal stress was assessed using questionnaires. We obtained latent constructs of prenatal adversity and prenatal mood problems using confirmatory factor analyses. The participants were genotyped using genome‐wide single nucleotide polymorphism arrays, and ADHD PGSs were computed. Magnetic resonance imaging scans were acquired at 4.5 and 6 years (GUSTO), and at 10 and 14 years (Generation R). We estimated the age‐related rate of change for brain outcomes related to ADHD and performed (1) prenatal stress by sex interaction models, (2) prenatal stress by ADHD PGS interaction models, and (3) 3‐way interaction models, including prenatal stress, sex, and ADHD PGS. We observed an interaction between prenatal stress and ADHD PGS on mean cortical thickness annual rate of change in Generation R (i.e., in individuals with higher ADHD PGS, higher prenatal stress was associated with a lower rate of cortical thinning, whereas in individuals with lower ADHD PGS, higher prenatal stress was associated with a higher rate of cortical thinning). None of the other tested interactions were statistically significant. Higher prenatal stress may promote a slower brain developmental rate during adolescence in individuals with higher ADHD genetic vulnerability, whereas it may promote a faster brain developmental rate in individuals with lower ADHD genetic vulnerability.
Environmental DNA reveals the ecology and seasonal migration of a rare sturgeon species in the Ural River
Authors: Abileva Gulmira , Turzhanova Ainur , Zhamangara Aizhan , Khapilina Oxana , Kalendar Ruslan 
Published: March 2024

AbstractEnvironmental DNA (eDNA) technology is an essential tool for monitoring living organisms in ecological research. The combination of eDNA methods with traditional methods of ecological observation can significantly improve the study of the ecology of rare species. Here, we present the development and application of an eDNA approach to identify rare sturgeons in the lower reaches of the Ural River (Zhaiyk) (~1084 km). The presence of representatives of the genus Sturgeon was detected at all sites in spring (nine sites) and autumn (ten sites) while they were absent during the summer period, consistent with their semi‐anadromous ecology. Detection in spring and autumn indicates the passage of spring and winter forms to the lower and upper spawning grounds, respectively. This study confirms the difficulties of species‐specific identification of Eurasian sturgeon and provides the first documented eDNA detection of specimens of the genus Sturgeon in the Ural River. It also provides a biogeographic snapshot of their distribution, experimentally confirming their seasonal migrations in the lower reaches of the river. The successful detection of sturgeon motivates further eDNA surveys of this and other fish species for accurate species identification and population assessment, opening up prospects for the management of these threatened species.
LocalPoly interpolation: Generalizing tricubic for Cn continuity in M‐dimensional spaces
Authors: Åblad Edvin 
Published: March 2024

AbstractTricubic interpolation, originally introduced by Lekien and Marsden (Int J Numer Methods Eng. 2005; 63(3): 455–471), has been a cornerstone in the field of interpolation, providing continuous interpolations within three‐dimensional spaces. However, real‐world applications often demand higher levels of smoothness within ‐dimensional spaces. This paper introduces LocalPoly interpolation, a novel generalization of tricubic interpolation that extends to continuity and dimensions. A key property is the use of solely local data for interpolation, allowing for on‐demand computation of interpolation polynomials, which is particularly advantageous in scenarios where a minor subset of the space is of interest. We rigorously prove the continuity achieved by the LocalPoly interpolation method; the proof features a numerically exact method for computing polynomial coefficients. The enhanced continuity is of great relevance in optimization algorithms, where efficient convergence often relies on the availability of information. The paper explores the use of LocalPoly interpolation applied to a squared distance field in , offering insights into computational efficiency and practical implications. It also discusses future research directions to address the method's limitations in terms of dimensionality, making it a valuable addition to the toolbox of interpolation methods for various scientific and engineering applications.
Chemical characterization and effect of Ziziphora clinopodioides green‐synthesized silver nanoparticles on cytotoxicity, antioxidant, and antidiabetic activities in streptozotocin‐induced hepatotoxicity in Wistar diabetic male rats
Authors: Pirabbasi Elham , Zangeneh Mohammad Mahdi , Zangeneh Akram , Moradi Rohallah , Kalantar Mojtaba 
Published: March 2024

AbstractThe present research studied the cytotoxicity, antioxidant, and antidiabetic activities of biogenically synthesized silver nanoparticles (AgNPs) using Ziziphora clinopodioides (Z. clinopodioides) as a green mediator. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), and ultraviolet–visible spectroscopy (UV–Vis) were employed to determine AgNPs. In the in vivo experiment, the model rats were categorized into different groups receiving 50, 100, 200, and 400 μg/kg of AgNPs and diabetic, positive, and normal groups (n = 10) using a random division. A single dose of streptozotocin (STZ) at 60 mg/kg was administered to induce diabetes and hepatotoxicity in rats. The administration of AgNPs was performed via intragastric administration for 25 days. On the final day, the levels of glucose and biochemical enzymes, namely aspartate aminotransferase (AST), alkaline phosphatase (ALP), alanine transaminase (ALT), and gamma‐glutamyltransferase (GGT), were assessed in the serum. Following tissue processing, liver sections with a thickness of 5 μm were prepared. Later, the total volume of different liver components, such as hepatocytes, sinusoids, portal vein, central vein, hepatic arteries, and bile ducts, was measured. The portal vein and bile duct volumes did not vary significantly in groups treated by AgNPs. However, the volume of the central vein and hepatic arteries exhibited noticeable variations in groups treated by AgNPs. After administration of streptozotocin, the volume of hepatocytes and sinusoids increased significantly. However, treatment with a high dose of AgNPs significantly decreased the volume of hepatocytes and sinusoids. In diabetic rats, administering AgNPs reduced the fasting blood glucose levels compared to the model group. In addition, AgNPs decreased the elevated levels of AST and ALP enzymes in a manner that depended on the dosage of AgNPs used. This research demonstrates the hepatoprotective and antidiabetic properties of AgNPs, suggesting their potential implications as hepatoprotective and antidiabetic supplements to prevent diabetes.
Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition
Authors: Gong Changda , Feng Yanjun , Zhu Jieyu , Liu Guixia , Tang Yun , Li Weihua 
Published: March 2024

AbstractCytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug‐metabolizing P450s could alter drug metabolism and lead to undesirable drug–drug interactions. Therefore, it is of great significance to explore the inhibition of P450s in drug discovery. Currently, machine learning including deep learning algorithms has been widely used for constructing in silico models for the prediction of P450 inhibition. These models exhibited varying predictive performance depending on the use of machine learning algorithms and molecular representations. This leads to the difficulty in the selection of appropriate models for practical use. In this study, we systematically evaluated the conventional machine learning and deep learning models for three major P450 enzymes, CYP3A4, CYP2D6, and CYP2C9 from several perspectives, such as algorithms, molecular representation, and data partitioning strategies. Our results showed that the XGBoost and CatBoost algorithms coupled with the combined fingerprint/physicochemical descriptor features exhibited the best performance with Area Under Curve (AUC) of 0.92, while the deep learning models were generally inferior to the conventional machine learning models (average AUC reached 0.89) on the same test sets. We also found that data volume and sampling strategy had a minor effect on model performance. We anticipate that these results are helpful for the selection of molecular representations and machine learning/deep learning algorithms in the P450 model construction and the future model development of P450 inhibition.
Catalase‐functionalized ZnO and graphene oxide used as electrocatalyst for the selective detection of hydrogen peroxide
Authors: Sharma Swati , Jain Utkarsh , Rosario Warren , Singh Varshika , Hooda Vinita , Chauhan Nidhi 
Published: March 2024

AbstractBACKGROUNDThis study focuses on the fabrication of a biosensor for the electrocatalytic and selective hydrogen peroxide (H2O2) recognition with bovine liver catalase (CAT) immobilized over a cysteine (c) modified zinc oxide nanoparticles/graphene oxide (c‐ZnO/GO) interface. The selectivity and sensitivity of the biosensor were augmented by the use of CAT and GO, respectively. The problem of CAT activity inhibition by GO was specifically solved by the incorporation of ZnO. Also, the cystine functionalization helped in better immobilization of CAT.RESULTSThis unique approach was first validated with in silico computations that calculated the binding affinities to study the interactions between different components of the biosensor. The electrochemical studies confirmed the step‐by‐step modification of the sensor, where along with GO, c‐ZnO nanoparticles also showed excellent electro‐conductivity by fundamentally improving the peak currents towards H2O2. The proposed bio‐nano interface exhibited superb electrocatalytic performance and specific detection capability for H2O2 across a broad linear range (0.1 to 40 μmol L−1), featuring a low detection limit (0.1 μmol L−1), as well as commendable reproducibility and storage durability. Furthermore, the biosensor yielded satisfactory outcomes for H2O2 detection in milk samples.CONCLUSIONSensing performance of nano‐bio interfaces can be augmented by using the appropriate nano‐composites and their efficacy confirmed through computational techniques such as molecular docking. The biosensor can be further repurposed into a wearable device by integration with lab‐on‐a‐chip platforms. © 2024 Society of Chemical Industry (SCI).
A new Doppler index, cerebro‐placental‐uterine ratio, and fetal cardiac parameters in early onset preeclampsia
Authors: Oğuz Yüksel , Ağaoğlu Recep Taha , Ulusoy Can Ozan , Öztürk Özge , Özgürlük İzzet , Soysal Çağanay , Yılmaz Vural Zehra , Yakut Yücel Kadriye 
Published: March 2024

AbstractObjectiveOur aim was to investigate the significance of cerebro‐placento‐uterine ratio CPUR, a new Doppler index, and fetal cardiac parameters (Mod MPI, EFT) in early–onset preeclampsia (EOPE) and to examine whether these parameters are related to perinatal outcome.Study designForty participants diagnosed with EOPE (preeclampsia cases diagnosed before 34 weeks of gestation) and 40 healthy pregnant women were included in this study. Demographic data were recorded. Doppler parameters such as middle cerebral artery (MCA), umbilical artery (UA), and uterine artery (Ut‐A), and left modified myocardial performance index (Mod–MPI) and epicardial fat thickness (EFT) were measured. Cerebroplacental ratio (CPR) was determined by dividing MCA pulsatility index (PI) by UA PI. CPUR was calculated as the ratio of CPR to mean UtA–PI (CPUR = CPR/UtA–PI). All parameters were compared between the EOPE and control groups. Correlation tests were used to examine the relationship between Doppler parameters and perinatal outcome. p values less than 0.05 were considered statistically significant.ResultsThe pulsatility index of the middle cerebellar artery, CPUR and CPR values were statistically lower in the EOPE group than in the control group (p = 0.002; p = <0.001; p = <0.001; respectively). No statistical differences were found between groups for isovolumetric contraction time (ICT), isovolumetric relaxation time (IRT), ejection time (ET), left mod‐MPI, EFT (p = 0.117; p = 0.093; p = 0.398; p = 0.882; p = 0.202, respectively). Umbilical artery Doppler pulsatility index (PI), mean uterine artery Doppler pulsatility index (PI), were higher in the EOPE group than in the control group (p = 0.006; and p = <0.001, respectively). The CPUR value for predicting EOPE was ≤1.3652 with 74. 4% sensitivity and 94.9% specificity. Positive correlations were found between CPUR, CPR, and some neonatal parameters.ConclusionCPUR, a new index combining fetal and uterine Doppler indices, may add contribution to predict adverse perinatal outcome and EOPE.
Comprehensive exploration on transfer and human health risk of potential toxic element in soil‐rice system from the Pearl River Delta
Authors: Huang Changchen , Hou Qingye , Yang Zhongfang , Yu Tao , You Yuanhang , Wu Zhiliang 
Published: March 2024

AbstractThe transfers of potential toxic elements (PTEs) from root soil to rice grains and its driving factors are of major worldwide concern. And it is still not clear whether the parent material has influence on the transfers of PTEs in soil. Thus, the aim of this study is to investigate the transfers of PTEs in soil‐rice system from different parent materials area, identify its driving factors and evaluate human health risk. 157 sets of root soil and rice grains samples collected from the areas with quaternary sediments, acidic magmatic rocks and terrigenous clastic rocks in the Pearl River Delta, China. Pearson correlation analysis, discriminant analysis, redundancy analysis, path analysis and human health risk model were utilized for data processing and analysis. The results reveal that parent materials play a primary role affecting the transfers of PTEs in soil‐rice system, and its influence on transfers of PTEs is achieved by governing physicochemical properties of soil. And physicochemical parameters like MgO, SiO2, Al2O3, TFe2O3, and organic matter (OM) exerted significant influence on transfers of PTEs. The influences of some physicochemical parameters on the transfers of PTEs are most significantly in the area of quaternary sediments. The values of the total non‐carcinogenic and the total carcinogenic risks for children and adults caused by rice consumption are much higher than the corresponding risk limits, and the main contributing elements are Pb, As, and As, Cd, respectively. The human health risks caused by rice consumption are greatest in the area with quaternary sediments.
2‐Pyran‐4‐Ylidene Malononitrile Based Conjugated Microporous Polymers as Metal‐Free Heterogeneous Photocatalysts for Organic Synthesis
Authors: Liu Yuanbo , Yang Liuliu , Hou Yuxin , Zhang Zhenwei , Xiao Xiao , Yue Huijuan , Liu Xiaoming 
Published: March 2024

AbstractPhotoactive conjugated microporous polymers (CMPs) as heterogeneous photocatalysts provide a sustainable alternative to classical metal‐based semiconductor photosensitizers. However, previously reported CMPs are typically synthesized through metal catalyzed coupling reactions, which bears product separation, but also increases the price of materials. Herein, a new type of sp2 carbon linked DCM‐CMPs are successfully designed and synthesized by organic base catalyzed Knoevenagel reaction using 2,6‐Dimethyl‐4H‐pyran‐4‐ylidene‐malononitrile and aromatic polyaldehydes as monomers. The new polymers feature inherent porosity, excellent stability, and fully π‐conjugated skeleton with broad visible‐light absorption. They effectively induce the synthesis of benzimidazole compounds under light irradiation, and exhibit wide substrate adaptability with outstanding recyclability.