bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced electrocatalytic activity by nanoconfinement effects at nanoporous indium tin oxide electrodes
Authors: Seo Minjee , Bae Je Hyun 
Published: November 2024

AbstractAmong various strategies to enhance electrocatalytic activity, nanoporous structured electrodes have been widely utilized owing to their improved performance. Along with enlarged electrode surface, modified crystalline facets, and surface defects of nanoporous electrodes, recent studies have reported their unique electrocatalytic characteristics originating from the nanoconfined space, denoted as the nanoconfinement effect. Introducing nanoporous electrodes with controllable thickness made of indium tin oxide, an electrochemically inert material, has provided an optimal platform for analyzing the contribution of nanoporous structures to the catalytic effects. Nevertheless, the scope of reactants that has been studied based on this system so far is mostly limited to ferric/ferrous redox species in sulfate anion environment. Here, using the nanoporous indium tin oxide electrodes, we demonstrate the nanoconfinement effect toward the ferric/ferrous reaction in a different chemical environment that alters its electrokinetic characteristics compared to the previous studies. Furthermore, a complex multi‐electron transfer reaction of oxygen reduction is employed to explore the effects of nanoporous structure toward inner‐sphere reactions. Our work suggests that the nanoconfinement effects can be applied to a wider range of electrochemical reactions taking place in nanoporous electrodes.
Do SMEs have an ESG communication strategy? Exploring the quality and influencing factors of voluntary ESG disclosures using web‐based and annual report channels
Authors: Cardoni Andrea , Kiseleva Evgeniia 
Published: November 2024

AbstractThis paper evaluates the influencing factors and disparities between web‐based and annual report channels for environmental, social and governance (ESG) disclosures by small and medium‐sized enterprises (SMEs). In contrast to the prevalent use of case‐studies in the context of SMEs, a quantitative study was conducted by performing a content analysis of the websites and annual reports of 100 manufacturing SMEs in Italy. Based on the collected evidence, SMEs exhibited a higher level of web‐based disclosures compared to annual reports. These disclosure channels appear to be independent of each other, with financial resources significantly influencing the quality of annual reports (i.e. profitability as a proxy) and size impacting information available on websites (i.e. turnover as a proxy). Both channels may be explained by the resource‐based view, while agency characteristics (such as having a Big Four external auditor or board size) have a relevant effect on the overall voluntary ESG disclosure score.
Predicting Pancreatic Cancer in New‐Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large‐Scale Prospective Cohort Study
Authors: Sun Yongji , Hu Chaowen , Hu Sien , Xu Hongxia , Gong Jiali , Wu Yixuan , Fan Yiqun , Lv Changming , Song Tianyu , Lou Jianyao , Zhang Kai , Wu Jian , Li Xiawei , Wu Yulian 
Published: November 2024

ABSTRACTIntroductionIndividuals who develop new‐onset diabetes have been identified as a high‐risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identifying high‐risk individuals among those with new‐onset diabetes.MethodsEmploying the UK Biobank cohort, we focused on those developing new‐onset diabetes during follow‐up. Genetic and clinical characteristics available at registration were considered as candidate predictors. We conducted univariate regression analysis to identify potential indicators and used a 5‐fold cross‐validation method to select optimal predictors for model development. Five machine learning algorithms were used for model development.ResultsAmong 12,735 patients with new‐onset diabetes, 100 (0.8%) were diagnosed with PC within 2 years. The final model (area under the curve, 0.897; 95% confidence interval, 0.865–0.929) included 5 clinical predictors and 24 single nucleotide polymorphisms. Two threshold cut‐offs were established: 1.28% and 5.26%. The recommended 1.28% cut‐off, based on model performance, reduces definitive testing to 13% of the total population while capturing 76% of PC cases. The high‐risk threshold is 5.26%. Utilizing this threshold, only 2% of the population needs definitive testing, capturing nearly half of PC cases.ConclusionsWe, for the first time, combined clinical and genetic data to develop and validate a model to determine the risk of pancreatic cancer in patients with new‐onset diabetes using machine learning algorithms. By reducing the number of unnecessary tests while ensuring that a substantial proportion of high‐risk patients are identified, this tool has the potential to improve patient outcomes and optimize healthcare sources.
Design and Synthesis of Novel Thiazole Linked Tetrahydropyridine Analogues as Anticancer Agents
Authors: Mohan Malothu Ram , Thalari Gangadhar 
Published: November 2024

AbstractA library of new thiazole linked tetrahydropyridines (6a–q) synthesized and screened for their invitro anticancer activity against human breast adeno carcinoma cell viz. MCF‐7 and MDA‐MB‐231. The two compounds 6d containing −F and −Cl functions in para and meta position of phenyl ring (9.94±1.02 μM, 9.78±1.08 μM) and 6e with −Cl and −NH2 functions on pyridine ring (9.72±0.91 μM, 9.54±0.95 μM) demonstrated outstanding activity against both the cell lines when compared to Doxorubicin. The benzofuran analogue 6o presented good activity with an IC50 value of 12.19±1.03 μM (MCF‐7) and 12.22±1.07 μM (MDA‐MB‐231). The molecular docking study of potent molecule 6e against crystal structure of breast tumor kinase presented promising docking score and binding interactions. Predicted pharmacokinetics properties of compounds 6a–q and presented boiled diagram of compounds 6d and 6e implied favourable drug‐likeness properties.
COF‐SO3H‐Catalyzed Synthesis of Pyrazoline‐Pyridine Hybrids with Dual Antioxidant and Anti‐Inflammatory Activity Targeting PDE4B
Authors: Khan Nida , Hussain Mohd Kamil , Khan Mohammad Faheem , Siddiqui Zeba N. 
Published: November 2024

AbstractThis study explores new anti‐inflammatory agents by synthesizing pyrazoline‐pyridine hybrids with N‐butylsulfonated covalent organic framework (COF‐SO3H) as a recyclable catalyst, achieving excellent yields in just one minute. The protocol was successfully scaled up to a multi‐gram scale, highlighting its robustness and efficiency, and it operates without the need for column chromatography. Among the synthesized hybrids, compound 5d, a pyrazoline‐pyridine hybrid bearing an indole moiety, emerged as a potent anti‐inflammatory and antioxidant agent. It effectively inhibited PDE4B activation with an IC50 value of 99.38 nM, without adversely affecting HEK cells. Compound 5d demonstrated its dual activity by significantly reducing ROS production and restoring mitochondrial health in LPS‐stimulated A549 and HEK cells, while also downregulating IL‐1β and NF‐ĸB/p65 expression in LPS‐stimulated A549 cells. In silico studies confirmed compound 5d’s strong binding to PDE4B, with stable RMSD and RMSF values, indicating its potential as a stable and effective PDE4B inhibitor. The compound exhibited favorable physicochemical properties, met drug‐likeness criteria, and showed low toxicity as predicted in silico. These findings suggest that compound 5d has significant potential as a therapeutic agent for inflammatory diseases due to its dual anti‐inflammatory and antioxidant activities.
Unveiling Biodiesel Production: Exploring Reaction Protocols, Catalysts, and Influential Factors
Authors: Ullah Zahoor , Bustam Mohamad Azmi , Ullah Mohib , Mamoon‐Ur‐Rashid  , Khan Amir Sada , Shah Syed Nasir , Shah Mansoor Ul Hassan , Ahmad Pervaiz , Sohail Muhammad , Khan Khalid Ali 
Published: November 2024

AbstractAn environmentally responsible and sustainable replacement for finite fossil fuels is biodiesel. Because of its amazing qualities, biodiesel is becoming more and more popular as a renewable fuel around the globe. The many approaches, feedstocks, catalysts, comparison standards, reaction kinetics, final product analysis, and final product characterization of biodiesel are covered in this review article. Researchers have used a variety of techniques to produce biodiesel throughout history, with transesterification emerging as the most effective approach in more recent times. Numerous studies on biodiesel feedstock and catalysts to produce high biodiesel yields have been published; nevertheless, it should be highlighted that the type of feedstock must be considered while choosing a catalyst. The review paper highlights the significance of several parameters that are crucial to the manufacture of biodiesel, without which achieving a high yield would be challenging. The literature has also discussed the limitations and advantages of different catalysts, and scientists are currently working to identify the ideal catalyst within certain optimal parameters for the manufacture of biodiesel. Homogeneous reaction‐based biodiesel synthesis has a number of drawbacks, though, such as water content, a laborious purification procedure, and a low tolerance for free fatty acids. To address these issues, scientists have started investigating heterogeneous reactions involving solid catalysts. A large pore network, a moderate‐to‐high density of strong acid sites, a hydrophobic surface, and the ability to control surface hydrophobicity to avoid deactivation are all desirable characteristics of an ideal solid catalyst. Ion exchange resins, sulfated oxides, heterogeneous base catalysts, boron group‐based heterogeneous catalysts, alkaline earth metal oxides, mixed metal oxides, alkali metal oxides, heterogeneous catalysts derived from waste materials, and different approaches to biodiesel synthesis that employ enzymes, carbon‐based heterogeneous catalysts, and ionic liquids as catalysts are among the categories of catalysts that can be used in the production of biodiesel. The finest benchmarks to compare the quality of biodiesel with European and American Society for Testing Material standards. For detailed characterization of the finished product, gas chromatography and nuclear magnetic resonance are the most effective methods.
Preventive catheter ablation for ventricular arrhythmias in patients with end‐stage heart failure referred for heart transplantation evaluation: Rationale for and design of the CASTLE‐VT trial
Authors: Sohns Christian , Fink Thomas , Crijns Harry J.G.M. , Costard‐Jaeckle Angelika , Marrouche Nassir F. , Sossalla Samuel , Schramm Rene , El Hamriti Mustapha , Moersdorf Maximilian , Didenko Maxim , Braun Martin , Sciacca Vanessa , Konietschke Frank , Rudolph Volker , Gummert Jan , Tijssen Jan G.P. , Sommer Philipp ,   for the CASTLE‐VT Investigators
Published: November 2024

AimsTimely referrals for transplantation and left ventricular assist device (LVAD) play a key role in favourable outcomes in patients with advanced heart failure (HF). Cardiovascular mortality, driven by sudden cardiac death, is the main reason for dying while waiting for heart transplantation (HTx). The purpose of the Preventive Catheter Ablation for ventricular arrhythmiaS in patients with end‐sTage heart faiLure rEferred for heart transplantation eValuaTion (CASTLE‐VT) trial is to test the hypothesis that prophylactic catheter ablation of arrhythmogenic ventricular scar tissue will reduce mortality, need for LVAD implantation, and urgent HTx in patients with end‐stage HF related to ischaemic cardiomyopathy (ICM).MethodsCASTLE‐VT is a randomized evaluation of prophylactic ablative treatment of arrhythmogenic ventricular scar in patients referred for HTx evaluation and diagnosed with ICM. Ablation will be performed with the use of a substrate‐based approach in which the myocardial scar is mapped and ablated while the heart remains predominantly in sinus rhythm. The primary endpoint is the composite of all‐cause mortality, worsening of HF requiring prioritized transplantation or LVAD implantation. The main secondary study endpoints are all‐cause mortality, cardiovascular mortality, incidence of implantable cardioverter‐defibrillator (ICD) therapy, hospitalizations, quality of life, time to first ICD therapy, number of device‐detected ventricular tachycardia/ventricular fibrillation episodes, left ventricular function, and exercise tolerance. CASTLE‐VT will randomize 160 patients with a follow‐up period of 2 years.ConclusionCASTLE‐VT will determine whether prophylactic catheter ablation of arrhythmogenic ventricular scar tissue reduces mortality in patients with end‐stage HF who are referred for HTx evaluation.
Psychological distress in heart failure patients: Implications for healthcare utilization and expenditure
Authors: Thyagaturu Harshith , Abugrin Mohamed , Awad Maan , Mensah Samuel Akaakole , Santer Matthew , Gonuguntla Karthik , Fonarow Gregg C , Balla Sudarshan 
Published: November 2024

ABSTRACTAimsPsychological distress is prevalent among heart failure (HF) patients, yet its impact on healthcare expenditure and utilization remains understudied. The aim of this study was to investigate the prevalence of psychological distress in HF patients and its impact on healthcare expenditure and utilization.Methods and resultsWe analysed data from the Medical Expenditure Panel Survey from January 2016 to December 2021, focusing on adults diagnosed with HF. We assessed the prevalence of psychological distress using the Kessler 6 (K6) questionnaire and examined its association with healthcare utilization and expenditures through multivariate regression models, adjusting for relevant covariates. Among 10 681 886 HF patients, 6.8% experienced psychological distress. The mean age was 69.9 years, and 50% were female. Multivariable analysis revealed significant associations between psychological distress and smoking (adjusted odds ratio [aOR] 2.87), Charlson comorbidity index ≥3 (aOR 3.05), and sleep disorders (aOR 2.82). Protective factors included exercise (aOR 0.40), higher education (aOR 0.89) and higher income levels (middle‐income: aOR 0.19, high‐income: aOR 0.20). HF patients with psychological distress incurred significantly higher annual total expenses ($14 709, p < 0.01), with inpatient costs ($6014, p = 0.02) and office‐based expenses ($3993, p = 0.04) being notably elevated. Additionally, these patients exhibited more frequent annual emergency room visits (0.07 visits, p < 0.01), hospital discharges (0.2 discharges, p = 0.01), and nights spent in the hospital (1.4 nights, p < 0.01).ConclusionPsychological distress in HF patients is associated with significantly higher medical expenditure and healthcare utilization. These findings underscore the need for integrated care approaches and present possible areas for intervention to address this significant healthcare burden.
Exploring the Reactivity of High Valent Iron Intermediates in Water
Authors: Sharma Parkhi , Kumar Rakesh , Awasthi Ayushi , Draksharapu Apparao 
Published: November 2024

AbstractThe exceptional reactivity observed in non‐heme iron enzymes can be attributed to their capability to access high‐valent iron oxygen species in their active site. Numerous inorganic model complexes have been reported to date, providing insights into the intricate structural and spectroscopic features of many iron‐containing enzymes and advancing our understanding of their enzymatic reaction pathways. While the reactivities of synthetic iron complexes have been evaluated using various oxidants, the investigation into the formation of reactive intermediates has primarily focused on acetonitrile. However, water, which serves as the medium in biological systems, has been less frequently employed in these studies. Motivated by this, we conducted a comprehensive study on the generation of key reactive species using various oxidants with a model complex, [(BnTPEN)Fe(II)(OTf)]+ (1) (where BnTPEN=N‐benzyl‐N,N,N‐tris(2‐pyridylmethyl)‐1,2‐diaminoethane) in water, which yielded important findings. In water, a quantitative yield of Fe(IV)=O species was achieved with the oxidant NaIO4. Additionally, we observed an equilibrium between side‐on Fe(III)−OO and Fe(III)−OOH, with the latter eventually converting to Fe(IV)=O. The insights gained from this study are likely to be relevant in the chemistry of other Fe(II) complexes with polypyridyl pentadentate ligands.
Optimization Simulation of Mooring System of Floating Offshore Wind Turbine Platform Based on SPH Method
Authors: Du Weibo , Jiao Peigang , Li Kangning , Ding Jiaming 
Published: November 2024

ABSTRACTIn this paper, the Smoothed Particle Hydrodynamics method is used to simulate the dynamic response of the floating offshore wind turbine mooring system in a complex marine environment by using its advantages of dealing with free surface flow and fluid–structure interaction. The single‐cable mooring system and the double‐cable mooring system are introduced into the numerical simulation model of fluid–solid coupling interaction. The first‐order irregular wave and the second‐order regular wave are used to simulate different wave conditions. The operating state of the platform in these two cases is analyzed, and the accurate data such as the velocity change of the geometric center of the platform and the change of six degrees of freedom are obtained. Using visual processing and data analysis, it is found that the optimized double‐cable mooring system structure improves the vibration reduction ability of the platform.
Performance Enhancement of Thermoelectric Generator‐Radiative Cooling System With Thermal and Electrical Energy Storage
Authors: Yigit Aysu , Yilmaz Muhammed , Yusuf Aminu , Ballikaya Sedat 
Published: November 2024

ABSTRACTA thermoelectric generator (TEG) converts thermal energy into electrical energy when temperature gradients are created across its two surfaces. Integrating the TEG with a phase change material (PCM) and radiative cooling (RC) can increase the temperature gradient across its two surfaces. In this study, a two‐layer RC paint has been developed and applied to the cold side of a TEG, and its performance was compared with TEG‐white paint and TEG‐no paint. The RC lowers the temperature of the cold side by 3.5°C and 4.7°C compared to TEGs with white paint and no paint, respectively. Integrating PCM with TEG–RC ensured a high electrical output, enabling continuous power for a typical weather sensor. The PCM–TEG–RC generated 2.7and 0.61 mW during summer and winter days in Istanbul, and nighttime outputs of 0.302 W and 0.395 mW, respectively. Despite similar costs, the electrical performance of TEG–RC was nearly double that of the TEG‐white paint. It has also been determined that a storage capacitor with a value of 0.5 F can provide 24‐h power backup to the typical weather sensor.
The interplay between epitranscriptomic RNA modifications and neurodegenerative disorders: Mechanistic insights and potential therapeutic strategies
Authors: Hashmi Muhammad Abu Talha Safdar , Fatima Hooriya , Ahmad Sadia , Rehman Amna , Safdar Fiza 
Published: November 2024

AbstractNeurodegenerative disorders encompass a group of age‐related conditions characterized by the gradual decline in both the structure and functionality of the central nervous system (CNS). RNA modifications, arising from the epitranscriptome or RNA‐modifying protein mutations, have recently been observed to contribute significantly to neurodegenerative disorders. Specific modifications like N6‐methyladenine (m6A), N1‐methyladenine (m1A), 5‐methylcytosine (m5C), pseudouridine and adenosine‐to‐inosine (A‐to‐I) play key roles, with their regulators serving as crucial therapeutic targets. These epitranscriptomic changes intricately control gene expression, influencing cellular functions and contributing to disease pathology. Dysregulation of RNA metabolism, affecting mRNA processing and noncoding RNA biogenesis, is a central factor in these diseases. This review underscores the complex relationship between RNA modifications and neurodegenerative disorders, emphasizing the influence of RNA modification and the epitranscriptome, exploring the function of RNA modification enzymes in neurodegenerative processes, investigating the functional consequences of RNA modifications within neurodegenerative pathways, and evaluating the potential therapeutic advancements derived from assessing the epitranscriptome.
Parasympathetic regulation and maternal parenting as longitudinal predictors of preschooler inhibitory control
Authors: Phillips Jennifer J. , Williams Cheyenne A. , Hunter John H. , Bell Martha Ann 
Published: November 2024

AbstractMeasures of parasympathetic regulation, such as respiratory sinus arrhythmia (RSA), predict executive function outcomes, including inhibitory control, across childhood. Respiratory sinus arrhythmia augmentation tends to be associated with more maladaptive outcomes, compared to RSA suppression, but the literature regarding RSA profiles and inhibitory control development across infancy and early childhood is contradictory. The goal of our current study was to examine the longitudinal and interactive effects of infant RSA during a frustrating task with negative maternal characteristics on inhibitory control during early childhood. Participants included 410 children (209 girls, 77.6% White, 92.9% non‐Hispanic) and their mothers. With small to moderate effect sizes (r
2 range from 0.124 to 0.143), we demonstrated that maternal negative affect when children were 36 months old moderated the association between 10‐month‐old RSA during a frustrating task and 48‐month‐old inhibitory control, such that RSA suppression predicted higher levels of inhibitory control, but only when mothers exhibited high levels of negative affect. Our results highlight the biosocial framework under which child inhibitory control develops.
Multi‐Deep Learning Approach With Transfer Learning for 7‐Stages Diabetic Retinopathy Classification
Authors: Khan Abdul Qadir , Sun Guangmin , Khalid Majdi , Farrash Majed , Bilal Anas 
Published: November 2024

ABSTRACTProposed novel investigation focused on leveraging an innovative diabetic retinopathy (DR) dataset comprising seven severity stages, an approach not previously examined. By capitalizing on this unique resource, this study′s findings set a new benchmark for DR classification, highlighting the transformative potential of incorporating advanced data into AI models. This study developed a Vgg16 transfer learning model and gauged its performance against established algorithms including Vgg‐19, AlexNet, and SqueezeNet. Remarkably, our results achieved accuracy rates of 96.95, 96.75, 96.09, and 92.96, respectively, emphasizing the contribution of our work. We strongly emphasized comprehensive severity rating, yielding perfect and impressive F1‐scores of 1.00 for “mild NPDR” and 97.00 for “no DR signs.” The Vgg16‐TL model consistently outperformed other models across all severity levels, reinforcing the value of our discoveries. Our deep learning training process, carefully selecting a learning rate of 1e‐05, allowed continuous refinements in training and validation accuracy. Beyond metrics, our investigation underscores the vital clinical importance of precise DR classification for preventing vision loss. This study conclusively establishes deep learning as a powerful transformative tool for developing effective DR algorithms with the potential to improve patient outcomes and advance ophthalmology standards.