bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative
Authors: De Rosa Alessandro Pasquale , Esposito Fabrizio , Valsasina Paola , d’Ambrosio Alessandro , Bisecco Alvino , Rocca Maria A. , Tommasin Silvia , Marzi Chiara , De Stefano Nicola , Battaglini Marco , Pantano Patrizia , Cirillo Mario , Tedeschi Gioacchino , Filippi Massimo , Gallo Antonio ,   the INNI Network, Altieri Manuela , Borgo Riccardo , Capuano Rocco , Storelli Loredana , Pagani Elisabetta , Sibilia Mauro , Piervincenzi Claudia , Ruggieri Serena , Petsas Nikolaos , Cortese Rosa , Stromillo Maria Laura 
Published: November 2022

AbstractThe Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.
ICH and US-FDA validated HPTLC methods with greenness assessments for the assay of mixtures prescribed in stroke prophylaxis: application to pharmaceutical preparations and human plasma
Authors: Hamdy Mohamed M. A. , Korany Mohamed A. , Ebied Shaza A. , Haggag Rim S. 
Published: November 2022

AbstractThe importance of the binary mixtures of the novel oral anticoagulants (NOACs): apixaban (APX), edoxaban tosylate (EDX) and rivaroxaban (RIV) with the lipid-lowering statin, rosuvastatin calcium (ROS) is highly emerging to save lives of cardiovascular patients as these combinations are used in prophylaxis from stroke. A high-performance thin-layer chromatography (HPTLC) method was developed for the quantitative assay of these life-saving mixtures in tablets and human plasma. Two mobile phases were developed for the assay in bulk and tablets; the first one: toluene‒ethyl acetate‒methanol‒25% ammonia (3.5:4.5:2:0.2, V/V) (method I) used for the three mixtures, and the second one: methanol‒25% ammonia (9.95:0.05, V/V) (method II) used for EDX/ROS mixture only. For analysis in human plasma, APX was used as internal standard in RIV/ROS and EDX/ROS mixtures using methods I and II, respectively, while RIV was used as internal standard in APX/ROS mixture using method I; the methods were validated according to the Food and Drug Administration (FDA) regulation for analysis in biological fluids. The method selectivity was demonstrated by its ability to simultaneously analyze the drugs in the presence of dosage form excipients and in the presence of plasma interferences (analysis in biological fluid) at single wavelength (291 nm) by use of the internal standard.
Mapping the Landscape of Care Providers’ Quality Assurance Approaches for AI in Diagnostic Imaging
Authors: Lundström Claes , Lindvall Martin 
Published: November 2022

AbstractThe discussion on artificial intelligence (AI) solutions in diagnostic imaging has matured in recent years. The potential value of AI adoption is well established, as are the potential risks associated. Much focus has, rightfully, been on regulatory certification of AI products, with the strong incentive of being an enabling step for the commercial actors. It is, however, becoming evident that regulatory approval is not enough to ensure safe and effective AI usage in the local setting. In other words, care providers need to develop and implement quality assurance (QA) approaches for AI solutions in diagnostic imaging. The domain of AI-specific QA is still in an early development phase. We contribute to this development by describing the current landscape of QA-for-AI approaches in medical imaging, with focus on radiology and pathology. We map the potential quality threats and review the existing QA approaches in relation to those threats. We propose a practical categorization of QA approaches, based on key characteristics corresponding to means, situation, and purpose. The review highlights the heterogeneity of methods and practices relevant for this domain and points to targets for future research efforts.
Calsyntenin-1 Promotes Doxorubicin-induced Dilated Cardiomyopathy in Rats
Authors: Zhu Mingxiang , Chen Yibing , Cheng Liting , Li Xin , Shen Yanying , Guo Ge , Xu Xiang , Li Hanlu , Yang Hao , Liu Chunlei , He Kunlun 
Published: November 2022

Abstract
Purpose
Doxorubicin is an important cancer chemotherapeutic agent with severe cardiotoxic effects that eventually lead to dilated cardiomyopathy (DCM). Calsyntenin-1(CLSTN1) plays a critical role in the nervous system, but its relevance in cardiovascular diseases is unknown. We investigated the significance of CLSTN1 in doxorubicin-induced DCM.

Methods
CLSTN1 expression in doxorubicin-induced DCM rats and H9c2 cells was determined using western blotting. To further explore the functions of CLSTN1, a cardiac-specific CLSTN1 overexpression rat model was constructed. The rats were subjected to analysis using echocardiographic, hemodynamic, and electrocardiographic parameters. Potential downstream molecules in CLSTN1 overexpression heart tissue were investigated using proteomics and western blotting. Finally, a knockdown of CLSTN1 was constructed to investigate the rescue function on doxorubicin-induced cell toxicity.

Results
CLSTN1 protein expression increased drastically in doxorubicin-induced DCM rats and H9c2 cells. Under doxorubicin treatment, CLSTN1 protein-specific overexpression in the heart muscle promoted cardiac chamber enlargement and heart failure, while the knockdown of CLSTN1 reduced doxorubicin-induced cardiomyocyte toxicity in vitro. At the mechanistic level, overexpression of CLSTN1 downregulated SERCA2 expression and increased the phosphorylation levels of PI3K-Akt and CaMK2.

Conclusion
Our findings demonstrated that CLSTN1 promotes the pathogenesis of doxorubicin-induced DCM. CLSTN1 could be a therapeutic target to prevent the development of doxorubicin-induced DCM.
Policy making in the financial industry: A framework for regulatory impact analysis using textual analysis
Authors: Clapham Benjamin , Bender Micha , Lausen Jens , Gomber Peter 
Published: November 2022

AbstractRegulators conduct regulatory impact analyses (RIA) to evaluate whether regulatory actions fulfill the desired goals. Although there are different frameworks for conducting RIA, they are only applicable to regulations whose impact can be measured with structured data. Yet, a significant and increasing number of regulations require firms to comply by specifying and communicating textual data to consumers and supervisors. Therefore, we develop a methodological framework for RIA in case of unstructured data following the design science research paradigm. The framework enables the application of textual analysis and natural language processing to assess the impact of regulatory actions that result in unstructured data and offers guidance on how to map suitable methods to the dimensions impacted by the regulation. We evaluate the framework by applying it to the European financial market regulation MiFID II, specifically the recent regulatory changes regarding best execution. Thereby, we show that MiFID II failed to improve informativeness and comprehensibility of best execution policies.
Common and uncommon vascular injuries and endovascular treatment associated with pelvic blunt trauma: a real-world experience
Authors: Aoki Ryo , Nakajima Kento , Kobayashi Yusuke , Sakai Yodo , Kamide Hiroyuki , Yamamoto Toh , Furugori Shintaro , Sawamura Shungo , Terauchi Miki , Kamiyama Kazutoshi , Ikeda Shin , Tsuji Gengo , Koyama Shingo , Yoshigi Jun , Sekikawa Zenjiro , Utsunomiya Daisuke 
Published: November 2022

AbstractPelvic fractures are common in cases of blunt trauma, which is strongly associated with mortality. Transcatheter arterial embolization is a fundamental treatment strategy for fatal arterial injuries caused by blunt pelvic trauma. However, vascular injuries due to blunt pelvic trauma can show various imaging findings other than arterial hemorrhage. We present a pictorial review of common and uncommon vascular injuries, including active arterial bleeding, pseudoaneurysm, arteriovenous fistula, arterial occlusion, vasospasm, and active venous bleeding. Knowledge of these vascular injuries can help clinicians select the appropriate therapeutic strategy and thus save lives.
Bite Force Performance from wild Derived mice has Undetectable Heritability Despite Having Heritable Morphological Components
Authors: Ginot Samuel , Hallgrímsson Benedikt , Agret Sylvie , Claude Julien 
Published: November 2022

AbstractFitness-related traits tend to have low heritabilities. Conversely, morphology tends to be highly heritable. Yet, many fitness-related performance traits such as running speed or bite force depend critically on morphology. Craniofacial morphology correlates with bite performance in several groups including rodents. However, within species, this relationship is less clear, and the genetics of performance, morphology and function are rarely analyzed in combination. Here, we use a half-sib design in outbred wild-derivedMus musculusto study the morphology-bite force relationship and determine whether there is additive genetic (co-)variance for these traits. Results suggest that bite force has undetectable additive genetic variance and heritability in this sample, while morphological traits related mechanically to bite force exhibit varying levels of heritability. The most heritable traits include the length of the mandible which relates to bite force. Despite its correlation with morphology, realized bite force was not heritable, which suggests it is less responsive to selection in comparison to its morphological determinants. We explain this paradox with a non-additive, many-to-one mapping hypothesis of heritable change in complex traits. We furthermore propose that performance traits could evolve if pleiotropic relationships among the determining traits are modified.
Causality in statistics and data science education
Authors: Cummiskey Kevin , Lübke Karsten 
Published: November 2022

AbstractStatisticians and data scientists transform raw data into understanding and insight. Ideally, these insights empower people to act and make better decisions. However, data is often misleading especially when trying to draw conclusions about causality (for example, Simpson’s paradox). Therefore, developing causal thinking in undergraduate statistics and data science programs is important. However, there is very little guidance in the education literature about what topics and learning outcomes, specific to causality, are most important. In this paper, we propose a causality curriculum for undergraduate statistics and data science programs. Students should be able to think causally, which is defined as a broad pattern of thinking that enables individuals to appropriately assess claims of causality based upon statistical evidence. They should understand how the data generating process affects their conclusions and how to incorporate knowledge from subject matter experts in areas of application. Important topics in causality for the undergraduate curriculum include the potential outcomes framework and counterfactuals, measures of association versus causal effects, confounding, causal diagrams, and methods for estimating causal effects.
Is there evidence that emotional reasoning processing underlies emotional disorders in adults? A systematic review
Authors: Paredes-Mealla Macarena , Martínez-Borba Verónica , Miragall Marta , García-Palacios Azucena , Baños Rosa Mª , Suso-Ribera Carlos 
Published: November 2022

Abstract
The prevalence of emotional disorders has increased in recent times. Emotional Reasoning (ER), which is a transdiagnostic process, occurs when feelings, rather than objective evidence, are used as a source of information to make judgements about the valence of a situation. Differences in ER may explain the existence and maintenance of emotional disorders. The objective is to systematically review the role of ER in the occurrence and severity of emotional disorders. Following PRISMA guidelines, we searched through: PubMed, PsycInfo, Scopus and The Cochrane Library. Search terms were "Emotional Reasoning", "ex-consequentia reasoning", "Affect-as-information"; and "emotional disorders", "anxiety", "depression", "depressive". Nine articles were included. An association was demonstrated between ER and a greater degree of anxious symptomatological severity. In depressive symptomatology, no significant differences were found. One study reported the effect of Cognitive Behavioural Therapy on ER bias, finding no changes after the intervention. Finally, another study evaluated the efficacy of computerised experiential training in reducing ER bias, showing significant differences. There are few studies on ER and its evolution in research has not been uniform over time. Encouragingly, though, research to date suggests that ER is a transdiagnostic process involved in several anxiety disorders. More investigation is needed to dilucidate whether ER also underlies the onset and maintenance of depressive disorders.
Life aspirations, school engagement, social anxiety, social media use and fear of missing out among adolescents
Authors: Tanrikulu Gulfem , Mouratidis Athanasios 
Published: November 2022

AbstractFear of Missing Out (FoMO) – people’s intense concerns that they might miss pleasant moments that their peers may enjoy—has been found to relate to a variety of undesired outcomes, including poor academic functioning. Yet, little is known about why some students may exhibit more FoMO than others. In this cross-sectional study with a sample of Turkish adolescents (N1 = 506; 50.8% males; Mage = 15.8 years; SD = 0.83), we examined to what extent intrinsic and extrinsic life goals for using social media predict FoMO over and above social anxiety. We found through path analyses that extrinsic goals of attaining popularity, garnering attention, and conveying a positive image of oneself to others related to FoMO which in turn related to lower grades by means of in-class distraction and out-of-class study interference. Taken together, the present results suggest that the goals that adolescents try to attain through social media use may explain why FoMO might be more prevalent in that age group.
Is it worth being attached to the leader? Transformational leadership and various types of performance: The mediating role of leader as attachment figure
Authors: Lisá Elena , Greškovičová Katarína 
Published: November 2022

AbstractWe assumed that the perception of the leader as an attachment figure would mediate the relationship between transformational leadership transformational leadership and leader/follower's reports of team performance. Leaders (N = 38) and employees (N = 204) completed separate questionnaire batteries. Team members assessed their perceptions of the leader as an attachment figure, transformational leadership of their leaders, and general and citizenship performance. Leaders assessed their transformational leadership style and the performance of their teams. We applied multi-level structural equation modeling (multi-level mediation). Perceptions of the leader as an attachment figure did not significantly mediate team or general performance prediction. But, the transformational leadership of the leader (team level) positively predicted the dimensions of the attachment figure (secure figure and separation distress – individual level). The secure figure positively and separation distress negatively predicted interpersonal and organizational citizenship performance at the team level. The perception of a leader as an attachment figure at the team level has different characteristics than at the individual level. The results indicate that the best scenario for team performance, as seen through the lens of transformational leadership, is a secure-figure leader and followers with low separation distress. The discussion meets the topics of the low statistical power and the need to differentiate a leader's attachment figure functions in organizations regarding the individual versus team level.
“Parents are gone”: Understanding the unique and interactive impacts of affective and cognitive empathy on left-behind youth’s academic engagement
Authors: Lan Xiaoyu 
Published: November 2022

AbstractAlthough several studies have shown that left-behind adolescents are vulnerable regarding emotional and behavioral functions, much less research has focused on this group’s academic engagement. The relationship between distinct empathy subcomponents and academic engagement in left-behind youth (versus non-left-behind youth) is therefore largely unknown. To fill these knowledge gaps, the current study compared the academic engagement between left-behind and non-left-behind youth. This study subsequently examined the unique and interactive relationships among affective empathy, cognitive empathy, and left-behind status with academic engagement in a combined sample of left-behind and non-left-behind youth. In total, 323 left-behind youth and 737 non-left-behind youth (Mage = 13.05; 49.5% females) participated in this study. Findings, after adjusting for participants’ sociodemographic characteristics, revealed that left-behind youth did not differ significantly in academic engagement compared to non-left-behind youth. A four-step hierarchical regression analysis showed that both empathy components were positively related to academic engagement. Interaction analyses further exhibited a cross-over effect of affective and cognitive empathy for left-behind youth. Specifically, left-behind youth with high cognitive empathy seemed more susceptible to the influence of affective empathy on academic engagement, for better and for worse. In the presence of high affective empathy, left-behind youth with higher cognitive empathy reported the highest academic engagement, whereas the youth with higher cognitive empathy, in the presence of low affective empathy, reported the lowest. The current study highlights the unique and interactive roles of affective and cognitive empathy in left-behind youth’s academic engagement, including important conceptual and practical implications.
Assessment of Early Childhood Mental Health in Immigrant and Local Children in Chile
Authors: Narea Marigen , Caqueo-Urízar Alejandra , Torres-Irribarra David , Treviño Ernesto , Flores Jerome , Gutiérrez-Rioseco Javiera 
Published: November 2022

AbstractLittle is known about mental health during early childhood and differences in mental health problems between migrant and local preschool children in Chile. This research aimed to study the early mental health of children and disparities in mental health indicators between immigrant and local children in the context of a middle-income country. Parents and teachers assessed immigrant (n = 120) and non-immigrant (n = 383) children between 3 and 4 years old with the Sistema de Evaluación de Niños y Adolescentes (Child and Adolescent Evaluation System, SENA). A multivariate analysis of covariance (MANCOVA) was used to study both main and interaction effects while controlling for the clustering of children on center-based care. Results show that immigrant parents tended to report more internalizing problems than locals’ parents did in terms of depression, anxiety, and somatic complaints. Also, they reported more attention problems, developmental delay, unusual behavior, rigidity, and isolation in immigrant children. However, teachers’ assessments regarding immigrant children were similar to non-immigrant children’s evaluations in many cases. Finally, girls presented fewer emotional and behavioral problems than boys. Our study shows the importance of assessing mental health during early childhood, especially in immigrant children, and the difficulty of carrying out this evaluation through different information sources from parents and early childhood teachers.
Profitability of private equity: mean reversion and transitory shocks
Authors: Gil-Alana Luis Alberiko , Puertolas-Montanes Francisco 
Published: November 2022

AbstractThis paper deals with the analysis of the statistical properties of the profitability yielded by Private Equity from a fractionally integrated viewpoint. Using quarterly data from 1981q2 to 2021q3, the results support the hypothesis of stationarity and mean reversion in all cases; however, we observe differences in the degree of persistence across regions, Europe being the closest to short memory while the US shows the highest degree of long range dependence and thus the longer lasting effects of shocks. Some policy recommendations of the results obtained are included at the end of the manuscript.