bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Methionine Allocation Nanoregulator for the Suppression of Cancer Stem Cells and Support to the Immune Cells by Epigenetic Regulation
Authors: Su Boyu , Chen Qinjun , Li Xuwen , Fang Mingzhu , Wang Yu , Song Haolin , You Haoyu , Zhou Zheng , Wu Yuxing , Zhao Zhenhao , Chen Yun , Fan Hongrui , Li Chufeng , Jiang Chen , Sun Tao 
Published: February 2025

AbstractEpigenetic dysregulation is prevalent in human cancers, affecting gene expression and metabolic patterns to meet the demands of malignant evolution and abnormal epigenetic processes, and resulting in a protumor immune microenvironment. Tumors require a steady supply of methionine for maintaining epigenetic flexibility, which is the only exogenous precursor of methyl donor S‐adenosylmethionine for methylation, crucial for their resistance to therapies and survival in a nutrient‐deficient microenvironment. Thus, tumor cells upregulate the Lat4 transporter to compete and deprive methionine in the microenvironment, sustaining their malignant phenotypes and also impairing immune cell functions. Addressing this methionine addiction is the key to overcoming drug resistance and improving immune response. Despite the challenge of lacking specific Lat4 inhibitors, an oxaliplatin prodrug crosslinked fluorinated polycation/anti‐Lat4 small interfering RNA complex nanoregulator (AS‐F‐NP) has been designed and developed here. This nanoregulator restricted the greedy methionine uptake of tumor cells by knocking down Lat4, which in turn inhibited the malignant evolution of the tumor while restoring the viability and function of tumor‐infiltrating immune cells.
Fundamentals and Applications of Dual‐Frequency Magnetic Particle Spectroscopy: Review for Biomedicine and Materials Characterization
Authors: Krause Hans‐Joachim , Engelmann Ulrich M. 
Published: February 2025

AbstractSuperparamagnetic nanoparticles (MNP) offer exciting applications for engineering and biomedicine in imaging, diagnostics, and therapy upon magnetic excitation. Specifically, if excited at two distinct frequencies f1 and f2, MNP responds with magnetic intermodulation frequencies m·f1 ± n·f2 caused by their nonlinear magnetization. These mixing frequencies are highly specific for MNP properties, uniquely characterizing their presence. In this review, the fundamentals of frequency mixing magnetic detection (FMMD) as a special case of magnetic particle spectroscopy (MPS) are reviewed, elaborating its functional principle that enables a large dynamic range of detection of MNP. Mathematical descriptions derived from Langevin modeling and micromagnetic Monte‐Carlo simulations show matching predictions. The latest applications of FMMD in nanomaterials characterization as well as diagnostic and therapeutic biomedicine are highlighted: analysis of the phase of the FMMD signal characterizes the magnetic relaxation of MNP, allowing to determine hydrodynamic size and binding state. Variation of excitation amplitudes or magnetic offset fields enables determining the size distribution of the particles’ magnetic cores. This permits multiplex detection of polydisperse MNP in magnetic immunoassays, realized successfully for various biomolecular targets such as viruses, bacteria, proteins, and toxins. A portable magnetic reader enables portable immunodetection at point‐of‐care. Future applications toward theranostics are summarized and elaborated.
Achieving High‐Performance Organic Long Persistent Luminescence Materials via Manipulation of Radical Cation Stability
Authors: Gao Hongxin , Wang Guangming , Wang Tengyue , Ye Zi , Yan Qianqian , Chong Qianhui , Chan Chin‐Yiu , Wang Biaobing , Zhang Kaka 
Published: February 2025

AbstractOrganic long persistent luminescence (OLPL) materials, with their hour‐long afterglow, hold great promise across numerous applications, yet their performance lags behind that of inorganic counterparts. A deeper understanding of the underlying photophysical mechanisms, particularly the effective control of radical intermediates, is essential for developing high‐performance OLPL materials; while systematic studies on the intrinsic stability of radical intermediates and their impact on OLPL performance remain scarce. Here biphenyl groups is introduced into a luminophore‐matrix‐donor three‐component OLPL system. By varying substituents at the ortho‐position of the biphenyl groups, the stability of radical cations is systematically modulated, and their influence on OLPL properties is investigated. Combined experimental results and theoretical calculations reveal that increased flexibility of the biphenyl bond and adjustable conformations lead to higher stability of radical cations, thereby significantly enhancing OLPL performance. Based on this understanding, a luminophore with two biphenyl groups is designed to successfully achieve remarkable afterglow brightness close to inorganic Sr2Al14O25/Eu2+, Dy3+ materials. Furthermore, these OLPL materials exhibit time‐encoded afterglow properties and promising applications in advanced anti‐counterfeiting, as well as background‐independent bioimaging functions. This work not only provides a novel strategy for constructing high‐performance OLPL materials but also lays a foundation for their widespread application in various fields.
Enhanced Photoredox Activity in Nitrogen‐Doped Carbon Nitride for Heterogeneous Nitrogen and Oxygen Radical Reactions
Authors: Qin Lan , Liu Huan , Wei Yi , Chen Lian‐Qing , Hu Xiao‐Qiang 
Published: February 2025

AbstractA nitrogen‐doped carbon nitride (NCN) has been synthesized and utilized for the sustainable generation of reactive nitrogen and oxygen radicals under mild photocatalytic conditions. This material exhibits a significant improvement in the separation and transfer of photoexcited charge carriers, which facilitates the direct activation of N─H and O─H bonds to achieve a variety of radical carboamination, oxyamination and deoxygenation reactions. The NCN catalyst has further demonstrated its robust photoredox activity through several successful applications, including the aerobic oxidation of boronic acids and the controllable oxidation of alcohols to aldehydes and carboxylic acids. Moreover, the NCN catalyst maintains its reactivity and efficiency even after multiple cycles of use, showcasing its durability and potential for practical applications in sustainable chemistry.
2D ferroelectric AgInP2Se6 for Ultra‐Steep Slope Transistor with SS Below 10 mV Decade−1
Authors: Yang Yujue , Liu Zihao , Liu Xueting , Dong Huafeng , Zhang Xin , Yang Juehan , Wu Fugen , Li Jingbo , Huo Nengjie 
Published: February 2025

AbstractAlong with continuous size shrinking, conventional silicon based transistors face the the challenges of both manufacture complexity and physical limitations. The negative capacitance transistors (NC‐FETs) using 2D ferroelectric materials as dielectric insulators are emerging as reliable solutions owing to their advantages of breaking the Boltzmann limitation and Complementary Metal‐Oxide Semiconductor (CMOS) compatibility. Here, the room temperature ferroelectricity of 2D AgInP2Se6 is discovered which is further integrated with MoS2 channel into ultra‐steep NC‐FETs for low‐power electronic applications. Due to the negative capacitance effect of AgInP2Se6 during the polarization reversal process, the transistor breaks the Boltzmann limitation with a subthreshold swing (SS) of less than 10 mV decade−1. By optimizing the thickness of AgInP2Se6, superior transistor performance with a minimum SS of 7.75 mV dec−1 and a high on/off ratio of up to 5.88 × 104 can be achieved. This work develops a new 2D ferroelectric AgInP2Se6 with room temperature ferroelectricity, providing promising material platforms for small‐size, ultra‐steep, and low‐power electronics.
A study of online monitoring for two‐phase flow patterns in a microchannel based on deep learning
Authors: Wang Zhenlun , Wang Yuhan , Chen Pengli , Xin Zhiling , Shang Minjing , Su Yuanhai 
Published: February 2025

AbstractA low‐cost, low‐noise, high‐frequency microchannel photoelectric detection device based on a photodiode was developed. Based on this device, photoelectric waveforms of gas–liquid and liquid–liquid two‐phase flows in a microchannel were collected, and then online flow pattern detection was realized by using artificial intelligence algorithms. Light intensity distribution characteristics of slug flow were simulated using COMSOL software, and detailed analyses were conducted to examine the relationship between waveform variations and slug flow morphology. After denoising the collected data with wavelet analysis filtering, artificial intelligence algorithms were employed to identify flow patterns for gas–liquid and liquid–liquid two‐phase flows. It was found that the recognition accuracy of the Convolutional Neural Networks algorithm in a variety of fluid systems reaches 100%. Based on this work, a general automatic gas–liquid/liquid–liquid flow pattern recognition platform was developed, which can automatically and quickly identify flow patterns and generate flow pattern graphs from the collected data.
Role of tau versus TDP‐43 pathology on medial temporal lobe atrophy in aging and Alzheimer's disease
Authors: Wisse Laura E. M. , Wuestefeld Anika , Murray Melissa E. , Jagust William , La Joie Renaud 
Published: February 2025

AbstractHippocampal atrophy on magnetic resonance imaging is an important biomarker in Alzheimer's disease (AD). While hippocampal atrophy was thought to result from tau tangles in AD, different neuropathologies can lead to hippocampal atrophy, especially TAR DNA‐binding protein 43 (TDP‐43) pathology. In this narrative review, we evaluate existing studies on the relative contribution of tau and TDP‐43 pathology to medial temporal lobe (MTL) atrophy. We report a clear association of both tau and TDP‐43 neuropathology with MTL atrophy, even after correcting for other neuropathologies. Next, we discuss a potential synergism between tau and TDP‐43 and the relative timing of the effects of both neuropathologies. Finally, avenues for future research will be discussed. A better understanding of the interplay between tau and TDP‐43 neuropathologies and their effect on atrophy will help with the development of more specific biomarkers for limbic‐predominant age‐related TDP‐43 encephalopathy and pinpointing of the optimal timing for testing anti‐tau and anti‐TDP‐43 treatments in trials.Highlights
Both tau and TAR DNA‐binding protein 43 (TDP‐43) pathology contribute to medial temporal lobe atrophy.
There is a positive association between tau and TDP‐43 and potentially a synergism.
It is unclear if tau and TDP‐43 have an additive or synergistic effect on atrophy.
The relative timing of the tau and TDP‐43 effects on atrophy remains unclear.
Clarifying the interplay between tau and TDP‐43 will help improve magnetic resonance imaging biomarkers.
Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data
Authors: Karlsson Linda , Vogel Jacob , Arvidsson Ida , Åström Kalle , Strandberg Olof , Seidlitz Jakob , Bethlehem Richard A. I. , Stomrud Erik , Ossenkoppele Rik , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Palmqvist Sebastian , Smith Ruben , Janelidze Shorena , La Joie Renaud , Rabinovici Gil D. , Binette Alexa Pichet , Mattsson‐Carlgren Niklas , Hansson Oskar 
Published: February 2025

AbstractINTRODUCTIONTau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, but its routine clinical use is limited by cost and accessibility barriers.METHODSWe thoroughly investigated the ability of various machine learning models to predict clinically useful tau‐PET composites (load and laterality index) from low‐cost and non‐invasive features, for example, clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI).RESULTSModels including plasma biomarkers yielded the most accurate predictions of tau‐PET burden (best model: R‐squared = 0.66–0.69), with especially high contribution from plasma phosphorylated tau‐217 (p‐tau217). MRI variables were the best predictors of asymmetric tau load between the two hemispheres (best model: R‐squared = 0.28–0.42). The models showed high generalizability to external test cohorts with data collected at multiple sites. Through a proof‐of‐concept two‐step classification workflow, we also demonstrated possible model translations to a clinical setting.DISCUSSIONThis study highlights the promising and limiting aspects of using machine learning to predict tau‐PET from scalable cost‐effective variables, with findings relevant for clinical settings and future research.Highlights
Accessible variables showed potential in estimating tau tangle load and distribution.
Plasma phosphorylated tau‐217 (p‐tau217) and magnetic resonance imaging (MRI) were the best predictors of different tau‐PET (positron emission tomography) composites.
Machine learning models demonstrated high generalizability across AD cohorts.
Setup and Characterization of a Fiber Brillouin Amplifier Module for Optical Frequency Transfer Over Interferometric Fiber Links
Authors: Kuhl Alexander , Koke Sebastian , Koczwara Andreas , Waterholter Thomas , Grosche Gesine 
Published: February 2025

AbstractThe details of fiber Brillouin amplifier modules developed for optical frequency dissemination and installed on the fiber link between Braunschweig and Strasbourg for performing optical clock comparisons are described and documented. The performance of these fiber Brillouin amplification modules is characterized in terms of gain, one‐way phase shift, and signal‐to‐noise ratio across a wide parameter space of signal and pump powers. Finally, upper estimates are derived for the frequency transfer uncertainty contributions resulting from the non‐reciprocity induced by the fiber Brillouin amplifier modules based on the characterized one‐way phase shift.
Photoexcited Transition‐Metal Catalyzed Carbon‐Halogen Bond Formation
Authors: Arora Ramon , Samokhin Philip , Lautens Mark 
Published: February 2025

Transition‐metal catalysis has proven useful in facilitating carbon‐halogen (C–X) bond formation. Despite the vast number of methodologies reported to furnish these bonds, limitations have remained, warranting continued development. The recent surge of metallaphotoredox‐based transformations has provided a novel gateway to bypass these limitations. Through the use of photoexcited species, the formation of C‐X bonds arise through new mechanistic pathways, finding alternatives to high reaction temperatures and stoichiometric additives. The discovery of this novel strategy has provided access to molecular space that has not been previously attainable. Herein, we report the recent advances on transition‐metal photocatalyzed C–X bond formation, in hopes to ease the synthetic endeavors for chemists in industrial and academic laboratories.
A Dual Biomarker Approach to Stress: Hair and Salivary Cortisol Measurement in Students via LC‐MS/MS
Authors: Hakeem Muhammad K. , Sallabi Sundas , Ahmed Raghda , Hamdan Hana , Mameri Amel , Alkaabi Mariam , Alsereidi Asmaa , Elangovan Sampath K. , Shah Iltaf 
Published: February 2025

AbstractStress is a significant issue among students, affecting both their mental and physical health. In this study, we investigated cortisol levels, a key biomarker for stress, in students at the United Arab Emirates University (UAEU) during their exam period. Using a sensitive liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) methodology we measured cortisol concentrations in hair and saliva samples and explored the potential correlation between exam‐induced stress and cortisol levels. The results revealed an increase in cortisol levels during the exam period, with male students showing an average hair cortisol concentration of 150.625 pg/mg and female students displaying an average of 77.756 pg/mg. Salivary cortisol levels ranged from 0.002 to 9.189 ng/mL, with an overall average of 4.505 ng/mL. Statistical analysis revealed significant differences in cortisol levels between male and female students, underscoring the impact of exam‐related stress on both acute and chronic stress markers. This study underscores the importance of addressing academic stress and suggests targeted strategies to mitigate its impact on student health ultimately fostering an environment encouraging both academic success and psychological well‐being within the student community. Future research directions include exploring additional clinical parameters and expanding the study population to further understand the long‐term effects of academic stress.
Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts
Authors: Alzetta Chiara , Torre Ilaria 
Published: February 2025

AbstractRelations between terms in texts have long been studied in linguistics and specialized knowledge domains, especially when occurring in educational materials like textbooks, where they play a crucial role in guiding instructional design and learning. Prerequisite relations (PR), which determine the sequence of presentation of domain terms, are particularly crucial for effective learning. Therefore, the authors consider them carefully when writing instructional texts. The reverse process of identifying PR within texts aims to extract the inherent knowledge structure they are based on and is a key task in the field of corpora annotation for educational knowledge modeling. Although there are tools for manual annotation, there is a need for specialized tools tailored to the unique properties of PR, enabling easy creation, analysis, and sharing of annotated datasets. In this paper, we introduce Prerequisite Relations Annotation Tool (PRAT), a novel tool designed for annotating PR based on a validated protocol. PRAT simplifies the process of capturing, analyzing, and visualizing prerequisite structures in educational texts. We outline PRAT's architecture and functionalities, emphasizing its unique features compared to existing corpora annotation tools. Through a user study involving users with diverse backgrounds, we show PRAT's effectiveness in real‐world scenarios.
Unboxing the intersections between self‐esteem and academic mindfulness with test emotions, psychological wellness and academic achievement in artificial intelligence‐supported learning environments: Evidence from English as a foreign language learners
Authors: Hou Lin 
Published: February 2025

AbstractThe integration of artificial intelligence (AI) into language education is rapidly transforming English as a foreign language (EFL) learning environments, presenting both opportunities and challenges. While AI‐supported tools offer potential benefits, they can also trigger complex test‐related emotions that may impact learners’ psychological and academic well‐being. Therefore, understanding the interplay between internal resources like self‐esteem and academic mindfulness, alongside these emotions, becomes crucial. This study investigated the correlations between self‐esteem and academic mindfulness with test emotions, psychological well‐being and academic achievement among EFL learners in AI‐supported contexts in China. To meet this purpose, a quantitative approach was employed, using data collected from a sample of 305 EFL university students (155 males and 150 females) in China selected through stratified random sampling. The analysis was conducted via confirmatory factor analysis and structural equation modelling using SMART PLS software. The results indicated that self‐esteem and academic mindfulness were strong predictors of test emotions, psychological wellness and academic achievement. Higher levels of academic self‐esteem and academic mindfulness were linked to higher test emotions, psychological well‐being and academic achievement. These findings stress the necessity of incorporating socio‐emotional skills into AI‐enhanced EFL learning, considering students’ psychological well‐being when deploying AI tools and designing interventions to address emotional challenges within AI‐supported environments.
Right Ventricular Systolic Dysfunction Predicts Recovery of Left Ventricular Systolic Function and Reduced Quality of Life in Patients With Arrhythmia‐Induced Cardiomyopathy
Authors: Körtl Thomas , Mühleck Franziska , Baum Paul , Resch Markus , Meindl Christine , Üçer Ekrem , Maier Lars S. , Wachter Rolf , Sossalla Samuel , Schach Christian 
Published: February 2025

ABSTRACTIntroductionArrhythmia‐induced cardiomyopathy (AIC) is an underrecognized condition resulting in left ventricular systolic dysfunction (LVSD) that is primarily caused by atrial fibrillation (AFib). The relationship between AIC, right ventricular (RV) function, and quality of life (QoL) has not been well studied.MethodsWe performed a post‐hoc analysis of our AIC trial in which we prospectively screened for patients with tachyarrhythmia and newly diagnosed, otherwise unexplained LVSD. Following rhythm restoration, patients were followed up at 2, 4, and 6 months. Only patients with persistent sinus rhythm were analyzed. RV function was assessed via echocardiography (tricuspid annular plane systolic excursion [TASPE] and fractional area change [FAC]) and QoL by the Minnesota Living with Heart Failure Questionnaire.ResultsOf a total of 50 patients recovering from LVSD, 41 were diagnosed with AIC and 9 with non‐AIC. Initially, RV function was reduced in the AIC group and recovered after rhythm restoration, whereas no relevant changes were noted in the non‐AIC group. QoL was reduced in both groups and also improved after rhythm restoration. Regression analysis identified low TAPSE as a predictive parameter for AIC diagnosis and worse QoL in AIC patients.ConclusionWe demonstrated that RV function and QoL are impaired in patients with AIC. Six months after rhythm restoration, TAPSE may serve as an early indicator of AIC while also correlating with QoL. This underscores the importance of detailed echocardiographic evaluation with a focus on RV function in patients with concomitant tachyarrhythmia and LVSD.
The Neutrophil‐to‐Lymphocyte Ratio Is an Independent Inflammatory Biomarker for Adverse Events in Patients With Atrial Fibrillation: Insights From the Murcia AF Project II (MAFP‐II) Cohort Study
Authors: Soler‐Espejo Eva , Marín Francisco , López‐Gálvez Raquel , Ramos‐Bratos María Pilar , Sánchez‐Villalobos María , Esteve‐Pastor María Asunción , Lip Gregory Y. H. , Rivera‐Caravaca José Miguel , Roldán Vanessa 
Published: February 2025

ABSTRACTBackgroundSystemic inflammation plays a central role in atrial fibrillation (AF). The neutrophil‐to‐lymphocyte ratio (NLR) is a simple hematological index that has been shown to be associated with prognosis in different pathologies.HypothesisThe NLR is associated with an increased risk of adverse events in patients with AF.MethodsWe included a prospective cohort of AF patients who started vitamin K antagonists (VKAs) therapy between July 2016 and June 2018. NLR was assessed at baseline and classified into three categories: low (< 3), moderate (3–5), and high (> 5). During a 2‐year follow‐up period, all cardiovascular deaths, all‐cause deaths, and net clinical outcomes (NCO; either ischemic stroke/transient ischemic attack, major bleeding or all‐cause death), were recorded.ResultsA total of 1050 patients were included (51.4% women; median age 77 years). NLR was available in 936 patients: 507 (54.2%) had low NLR (< 3), 239 (25.5%) had moderate NLR (3–5), and 190 (20.3%) had high NLR (> 5). The primary endpoint was significantly increased in the high NLR category (p = 0.002 for cardiovascular death; p < 0.001 for all‐cause mortality, and p < 0.001 for NCO), with higher IRRs (all p < 0.001). Multivariate Cox regression analyses showed that high NLR was independently associated with an increased risk of cardiovascular death (aHR: 2.02; 95% CI: 1.04–3.92), all‐cause mortality (aHR: 2.51; 95% CI: 1.58–3.97), and NCO (aHR: 1.99; 95% CI: 1.37–2.87), compared to low NLR.ConclusionsIn this prospective AF cohort receiving VKAs, elevated NLR was significantly associated with an increased risk of adverse clinical outcomes. NLR has independent prognostic value beyond other classical risk factors.