bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring the effects of motion corruption in fetal fMRI
Authors: Taymourtash Athena , Schwartz Ernst , Nenning Karl‐Heinz , Licandro Roxane , Kienast Patric , Hielle Veronika , Prayer Daniela , Kasprian Gregor , Langs Georg 
Published: January 2025

AbstractIrregular and unpredictable fetal movement is the most common cause of artifacts in in utero functional magnetic resonance imaging (fMRI), affecting analysis and limiting our understanding of early functional brain development. The accurate detection of corrupted functional connectivity (FC) resulting from motion artifacts or preprocessing, instead of neural activity, is a prerequisite for reliable and valid analysis of FC and early brain development. Approaches to address this problem in adult data are of limited utility in fetal fMRI. In this study, we evaluate a novel technique for robust computational assessment of motion artifacts, and the quantitative comparison of regression models for artifact removal in fetal FC analysis. It exploits the association between dynamic FC and non‐stationarity of fetal movement, to detect residual noise. To validate our motion artifact detection technique in detail, we used a parametric generative model for neural events and fMRI blood oxygenation level‐dependent (BOLD) signal. We conducted a systematic evaluation of 11 commonly used regression models in a sample of 70 fetuses with gestational age of 19–39 weeks. Results demonstrate that the proposed method has better accuracy in identifying corrupted FC compared to methods designed for adults. The technique, suggests that censoring, global signal regression and anatomical component‐based regression models are the most effective models for compensating motion. The benchmarking technique, and the generative model for realistic fetal fMRI BOLD enables investigators conducting in utero fMRI analysis to effectively quantify the impact of fetal motion and evaluate alternative regression strategies for mitigating this impact. The code is publicly available at: https://github.com/cirmuw/fetalfMRIproc.
Somatic mutations and DNA methylation identify a subgroup of poor prognosis within lower‐risk myelodysplastic syndromes
Authors: Rombaut David , Sandmann Sarah , Tekath Tobias , Crouch Simon , de Graaf Aniek O. , Smith Alexandra , Painter Daniel , Kosmider Olivier , Tobiasson Magnus , Lennartsson Andreas , van der Reijden Bert A. , Park Sophie , D'Aveni Maud , Slama Borhane , Clappier Emmanuelle , Fenaux Pierre , Adès Lionel , van de Loosdrecht Arjan , Langemeijer Saskia , Symeonidis Argiris , Čermák Jaroslav , Preudhomme Claude , Savic Aleksandar , Germing Ulrich , Stauder Reinhard , Bowen David , van Marrewijk Corine , Bernard Elsa , de Witte Theo , Varghese Julian , Hellström‐Lindberg Eva , Dugas Martin , Martens Joost , Malcovati Luca , Jansen Joop H. , Fontenay Michaela ,   MDS‐RIGHT consortium
Published: January 2025

AbstractLower risk (LR) myelodysplastic syndromes (MDS) are heterogeneous hematopoietic stem and progenitor disorders caused by the accumulation of somatic mutations in various genes including epigenetic regulators that may produce convergent DNA methylation patterns driving specific gene expression profiles. The integration of genomic, epigenomic, and transcriptomic profiling has the potential to spotlight distinct LR‐MDS categories on the basis of pathophysiological mechanisms. We performed a comprehensive study of somatic mutations and DNA methylation in a large and clinically well‐annotated cohort of treatment‐naive patients with LR‐MDS at diagnosis from the EUMDS registry (ClinicalTrials.gov.NCT00600860). Unsupervised clustering analyses identified six clusters based on genetic profiling that concentrate into four clusters on the basis of genome‐wide methylation profiling with significant overlap between the two clustering modes. The four methylation clusters showed distinct clinical and genetic features and distinct methylation landscape. All clusters shared hypermethylated enhancers enriched in binding motifs for ETS and bZIP (C/EBP) transcription factor families, involved in the regulation of myeloid cell differentiation. By contrast, one cluster gathering patients with early leukemic evolution exhibited a specific pattern of hypermethylated promoters and, distinctly from other clusters, the upregulation of AP‐1 complex members FOS/FOSL2 together with the absence of hypermethylation of their binding motif at target gene enhancers, which is of relevance for leukemic initiation. Among MDS patients with lower‐risk IPSS‐M, this cluster displayed a significantly inferior overall survival (p < 0.0001). Our study showed that genetic and DNA methylation features of LR‐MDS at early stages may refine risk stratification, therefore offering the frame for a precocious therapeutic intervention.
Simplified Multireference Coupled‐Cluster Methods: Hybrid Approaches With Averaged Coupled Pair Theories
Authors: Waigum Alexander , Suchaneck Sarah , Köhn Andreas 
Published: January 2025

ABSTRACTWe define an approximation to the internally contracted multireference coupled‐cluster method with single and double excitations by a hybrid approach. The rationale is to treat the external pair energy contributions by the coupled‐cluster method, which provides accurate results for a large part of the correlation energy while being tractable as the involved pair cluster operators commute. For the internal and semi‐internal contributions, for which the coupled‐cluster part becomes involved due to non‐commuting operators, a linearized approach based on the coupled‐electron pair approximation (CEPA) is used. For the latter, the CEPA(0) method, the averaged coupled pair functional (ACPF), the averaged quadratic coupled‐cluster (AQCC) method, and the averaged CEPA method are tested. We test the methods concerning size consistency, potential energy curves for C2, N2, CN, and O3 and for the singlet‐triplet splitting of ortho‐, meta‐, and para‐benzynes. Our results show that AQCC provides the most accurate results and stable performance. The main drawback of the method is that it shows small violations of size consistency.
Declining Urban–Rural Population Densities: How Do They Affect Natural Habitat?
Authors: Yang Liyan , Yang Tian , Chen Wanxu , Yang Meng , Liu Qingqing , Wang Guanzheng , Yuan Jintao , Xu Hang , Zeng Jie 
Published: January 2025

ABSTRACTThe decline in urban–rural population density (URPD) has consistently characterized China's rapid urbanization. Analyzing the spatiotemporal trends in URPD and their effects on habitats within the context of China's ecological civilization is crucial. However, quantitative studies on the decline in URPD are lacking, and the impact on natural habitats remains unclear. Therefore, using population census and land‐use data, we analyzed the spatiotemporal trends in URPD and habitat effects in China between 2000 and 2020. The results show that China's urban population density (UPD), rural population density (RPD), and habitat quality have decreased by 11.7%, 40.2%, and 2.1%, respectively, and they all tend to shift to lower values. The effects of UPD and RPD on natural habitats vary and exhibit regional heterogeneity. This study provides insights for promoting high‐quality urban–rural development and advancing ecological civilization.
Using Moving Least Square With Particle Swarm Optimization to Solve Nonlinear Transient Convective–Radiative Heat Transfer Problems in the Existence of a Magnetic Field
Authors: Mahmoodabadi M. J. , Atashafrooz M. , Ibrahim M. Yousef 
Published: January 2025

ABSTRACTIn the current research, a novel hybrid scheme is proposed to solve nonlinear equations arising in heat transfer through the combination of meta‐heuristic algorithms and interpolation methods. In order to define a proper objective function for minimization by particle swarm optimization (PSO), the constrained problem is converted into an unconstrained one through the penalty method. Furthermore, the moving least square (MLS) technique is implemented to interpolate and approximate the derivatives appeared in the equation. The main problem for challenging this combined scheme is nonlinear transient convective–radiative heat transfer in existence of a magnetic field. To study the efficiency of the MLS, the results would be contrasted with those extracted by a finite difference method (FDM) based PSO approach. Through five distinctive examples, the evolutionary diagrams as well as temperature distributions found by different methods are displayed, and the effects of the constant parameters are investigated. Besides, the simulations of this research work clearly depict good agreements of the numerical results obtained by the suggested idea with those reported in literature.
Qualitative Uncertainty Principles for the Nonisotropic Angular Stockwell Transforms
Authors: Wang Xinyu , Zheng Shenzhou 
Published: January 2025

ABSTRACTThe nonisotropic angular Stockwell transform (NAST) employs an angular, scalable and localized window function, to effectively capture directional characteristics and nonisotropic features presented in the signal. In this paper, our main contributions are to derive three distinct qualitative uncertainty principles (UPs) for the NAST: the Benedicks–Amrein–Berther UP, the logarithmic Sobolev‐type UP, and the Donoho–Stark UP. These uncertainty principles provide rather valuable insights into the behavior and limitations of the NAST regarding localization and concentration properties.
Disruption of Epistemic Trust in Borderline Personality Disorder: A Possible Adaptation to Avoid Making Costly Mistakes
Authors: Kurt Yağızcan 
Published: January 2025

ABSTRACTThis paper applies error management theory (EMT) (Haselton and Buss 2000) to explore how disruptions in epistemic trust—trust in communicated information—can be understood as adaptive responses to early adversity in individuals with borderline personality disorder (BPD). I propose that epistemic mistrust (EM) and epistemic credulity (EC), characterized by inappropriate trust patterns, arise from the differential costs of trusting unreliable versus mistrusting reliable information. Although these biases may seem maladaptive, they function as evolutionary survival mechanisms in response to harsh environments. Signal detection analysis can provide empirical evidence for these trust biases by assessing how individuals with BPD make trust‐related decisions. Clinically, understanding these biases as evolutionary adaptations helps reduce stigma and informs evolutionary‐informed interventions to recalibrate trust responses and improve interpersonal relationships. This approach highlights the significance of integrating evolutionary perspectives in treating trust disturbances in BPD.
The Pseudoenzyme β‐Amylase9 From Arabidopsis Activates α‐Amylase3: A Possible Mechanism to Promote Stress‐Induced Starch Degradation
Authors: Berndsen Christopher E. , Storm Amanda R. , Sardelli Angelina M. , Hossain Sheikh R. , Clermont Kristen R. , McFather Luke M. , Connor Mafe A. , Monroe Jonathan D. 
Published: January 2025

ABSTRACTStarch accumulation in plants provides carbon for nighttime use, for regrowth after periods of dormancy, and for times of stress. Both ɑ‐ and β‐amylases (AMYs and BAMs, respectively) catalyze starch hydrolysis, but their functional roles are unclear. Moreover, the presence of catalytically inactive amylases that show starch excess phenotypes when deleted presents questions on how starch degradation is regulated. Plants lacking one of these catalytically inactive β‐amylases, BAM9, have enhanced starch accumulation when combined with mutations in BAM1 and BAM3, the primary starch degrading BAMs in response to stress and at night, respectively. BAM9 has been reported to be transcriptionally induced by stress although the mechanism for BAM9 function is unclear. From yeast two‐hybrid experiments, we identified the plastid‐localized AMY3 as a potential interaction partner for BAM9. We found that BAM9 interacted with AMY3 in vitro and that BAM9 enhances AMY3 activity about three‐fold. Modeling of the AMY3‐BAM9 complex predicted a previously undescribed alpha–alpha hairpin in AMY3 that could serve as a potential interaction site. Additionally, AMY3 lacking the alpha–alpha hairpin is unaffected by BAM9. Structural analysis of AMY3 showed that it can form a homodimer in solution and that BAM9 appears to replace one of the AMY3 monomers to form a heterodimer. The presence of both BAM9 and AMY3 in many vascular plant lineages, along with model‐based evidence that they heterodimerize, suggests that the interaction is conserved. Collectively these data suggest that BAM9 is a pseudoamylase that activates AMY3 in response to cellular stress, possibly facilitating stress recovery.
A Commensurate Prior Model With Random Effects for Survival and Competing Risk Outcomes to Accommodate Historical Controls
Authors: Khanal Manoj , Logan Brent R. , Banerjee Anjishnu , Fang Xi , Ahn Kwang Woo 
Published: January 2025

ABSTRACTClinical trials (CTs) often suffer from small sample sizes due to limited budgets and patient enrollment challenges. Using historical data for the CT data analysis may boost statistical power and reduce the required sample size. Existing methods on borrowing information from historical data with right‐censored outcomes did not consider matching between historical data and CT data to reduce the heterogeneity. In addition, they studied the survival outcome only, not competing risk outcomes. Therefore, we propose a clustering‐based commensurate prior model with random effects for both survival and competing risk outcomes that effectively borrows information based on the degree of comparability between historical and CT data. Simulation results show that the proposed method controls type I errors better and has a lower bias than some competing methods. We apply our method to a phase III CT which compares the effectiveness of bone marrow donated from family members with only partially matched bone marrow versus two partially matched cord blood units to treat leukemia and lymphoma.
Taylor Series Approximation for Accurate Generalized Confidence Intervals of Ratios of Log‐Normal Standard Deviations for Meta‐Analysis Using Means and Standard Deviations in Time Scale
Authors: Chen Pei‐Fu , Dexter Franklin 
Published: January 2025

ABSTRACTWith contemporary anesthetic drugs, the efficacy of general anesthesia is assured. Health‐economic and clinical objectives are related to reductions in the variability in dosing, variability in recovery, etc. Consequently, meta‐analyses for anesthesiology research would benefit from quantification of ratios of standard deviations of log‐normally distributed variables (e.g., surgical duration). Generalized confidence intervals can be used, once sample means and standard deviations in the raw, time, scale, for each study and group have been used to estimate the mean and standard deviation of the logarithms of the times (i.e., “log‐scale”). We examine the matching of the first two moments versus also using higher‐order terms, following Higgins et al. 2008 and Friedrich et al. 2012. Monte Carlo simulations revealed that using the first two moments 95% confidence intervals had coverage 92%–95%, with small bias. Use of higher‐order moments worsened confidence interval coverage for the log ratios, especially for coefficients of variation in the time scale of 50% and for larger sample sizes per group, resulting in 88% coverage. We recommend that for calculating confidence intervals for ratios of standard deviations based on generalized pivotal quantities and log‐normal distributions, when relying on transformation of sample statistics from time to log scale, use the first two moments, not the higher order terms.
Lipid‐Lowering Drugs and Pulmonary Vascular Disease: A Mendelian Randomization Study
Authors: Yuan Xingya , Hong Peiwei , Zhou JinQiu 
Published: January 2025

ABSTRACTThe therapeutic value of lipid‐lowering drugs in pulmonary vascular disease remains uncertain due to insufficient studies and evidence. This study aims to investigate the causal effects of lipid‐lowering drugs (specifically, inhibitors of APOB, CETP, HMGCR, NPC1L1, and PCSK9) on pulmonary vascular diseases using a Mendelian randomization (MR) approach. We utilized summary‐level statistics from genome‐wide association studies (GWAS) to simulate the exposure to low‐density lipoprotein cholesterol (LDL‐C) and its outcomes on pulmonary arterial hypertension (PAH), pulmonary embolism (PE), and pulmonary heart disease (PHD). Single‐nucleotide polymorphisms (SNPs) within or near drug target‐associated LDL‐C loci were selected as proxies for the lipid‐lowering drugs. Data from the FinnGen cohort and UK Biobank (UKB) were incorporated to enhance the robustness and generalizability of the findings. The inverse variance weighted (IVW) and MR‐Egger methods were employed to estimate MR effects. Our MR analysis indicated that LDL‐C mediated by NPC1L1 (odds ratio [OR] = 104.76, 95% confidence interval [CI] = 2.01–5457.01, p = 0.021) and PCSK9 (OR = 10.20, 95% CI = 3.58–29.10, p < 0.001) was associated with an increased risk of PAH. In contrast, LDL‐C mediated by APOB was associated with a decreased risk of PE (FinnGen: OR = 0.74, 95% CI = 0.60–0.91, p = 0.005; UKB: OR = 0.998, 95% CI = 0.996–1.000, p = 0.031) and PHD (FinnGen: OR = 0.73, 95% CI = 0.59–0.91, p = 0.004). However, LDL‐C mediated by CETP and HMGCR did not show significant associations with the risks of PAH, PE, or PHD. This MR study revealed the causal effects of NPC1L1 and PCSK9 inhibitors on increased PAH risk, while APOB inhibitors appear to reduce the risks of PE and PHD. These findings enhance our understanding of the potential roles of lipid‐lowering drugs in pulmonary vascular disease.
Primary tracheo‐bronchial adenoid cystic carcinoma: A surgical series with literature review
Authors: Ben Amara Kaouther , Bouassida Imen , Ayadi Rahma , Affes Mariem , Abdelkbir Amina , Abdennadher Mahdi , Ben Othmen Salma , Ayadi‐Kaddour Ayda , Zribi Hazem , Marghli Adel 
Published: January 2025

AbstractTracheo‐bronchial adenoid cystic carcinoma (TBACC) is a rare disease. Its treatment is mainly surgical. We herein describe the clinical and para‐clinical varieties of TBACC as well as their surgical treatment and prognosis. We conducted a retrospective study of eight patients operated on between 1994 and 2022 and whose definitive pathological examination concluded with primary TBACC. There were three men and five women with an average age of 44 years. The bronchoscopy found a budding formation reducing the tracheal lumen at the cervical (two cases), middle (two case) and distal trachea and carina (four cases). Bronchial anastomosis resection and sleeve pneumonectomy were the most common procedures. Surgical resections R0 were achieved in five patients. Surgery followed by adjuvant radiotherapy was performed in two patients with incomplete surgical resection R1. The overall survival for all patients with primary ACC was 72% at 5 years. TBACC is a rare and low‐to‐moderate grade malignant tumour. The choice of the surgical procedure and the appropriate approach is challenging to obtain a promising prognosis.
A Model for Sustainable Development in Territorial Production Systems
Authors: Sica Francesco , Tajani Francesco , Morano Pierluigi 
Published: January 2025

ABSTRACTThe territorial production system demand innovation and adaptability to provide the majority of decisions, especially when splitting up available resources among productive sectors by the lens of sustainable development. The system's economic units evolve in dimensional profile, technical execution, and management of productive process to approach the worldwide benchmark for sustainability, taking into account not only the environment, society, and economy, but also the twin transition to digitalisation. The study addresses the issue of allocation resources across territory's productive sectors by an inter‐sectorial model that accounts for both external and endogenous sustainability performance criteria. The model is developed starting from the Leontief input–output system and tested in the Italian production system. The sustainability perspective's individualization of the sector's top performer and the quantity of resources to be allocated in response to their respectable sustainable performance are provided as outputs. The political repercussions, model's potential and strengths, and its limits with regard to the sustainable development of territorial production frame are discussed in the conclusions.
Community Attachment, Emotional Solidarity, and Sustainable Tourism Support: Evidence From Sagarmatha National Park, Nepal
Authors: Chen Qian , Jiang Fei , Guo Yingzhi , Shrestha Raj Kush , Zhang Qingchuo 
Published: January 2025

ABSTRACTNational parks, such as Sagarmatha National Park in Nepal, serve as critical conservation areas and key attractions for nature‐based tourism, offering both opportunities and challenges to local communities. This study aims to address the underexplored perspectives of residents in economically disadvantaged, tourism‐dependent regions by investigating the factors influencing their support for sustainable tourism development. Specifically, it integrates Community Attachment Theory, Social Exchange Theory, and Emotional Solidarity Theory to examine how community attachment, perceived value, and emotional solidarity interact to shape residents' support for sustainable tourism. Data were collected from 260 residents in the Khumbu region and analyzed using SPSS and SmartPLS software. The findings reveal that strong community attachment enhances perceived value, which subsequently boosts support for sustainable tourism. Additionally, community attachment and perceived value significantly reinforce emotional solidarity, playing a crucial role in fostering positive resident attitudes towards sustainable tourism. The study also identifies gender as a moderating factor in the relationship between emotional solidarity dimensions—such as welcoming nature and sympathetic understanding—and tourism support. These insights contribute to the theoretical understanding of community dynamics in tourism and offer practical recommendations for policymakers to enhance resident engagement and promote sustainable tourism in sensitive environments.
A Fully Integrated ICP‐Enriched and Nanozyme‐Catalyzed Lateral Flow Assay for cfDNA Detection in Whole Blood
Authors: Cun Fei , Li Hanxue , Wang Haonan , Yang Bin , Kong Jilie , Chen Hui 
Published: January 2025

AbstractRapid and sensitive detection of Epstein−Barr virus cell‐free DNA (EBV cfDNA) is crucial for early diagnosis and monitoring of nasopharyngeal carcinoma (NPC), but accessibility to screening is limited by complicated and costly conventional DNA isolation and purification approaches. Here, a fully integrated ion concentration polarization (ICP)‐enriched and nanozyme‐catalyzed lateral flow assay (ICP‐cLFA) is developed, enabling total analysis of EBV cfDNA in whole blood samples, with DNA isolation, pre‐concentration, and amplification performed on a microfluidic chip, consequently providing the signal readout within 75 min. Specifically, ICP preconcentration and amplification steps, together with target recognition catalyzed by a platinum‐decorated mesoporous gold nanosphere (MGNS@Pt) nanozyme, result in an ultralow detection limit of 4 aM in standard cfDNA samples and 100 aM in whole blood from NPC‐bearing rats. The high sensitivity and specificity of the ICP‐cLFA suggest strong potential for cfDNA screening in resource‐limited clinical and field applications.