bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel variant in the DSE gene leads to Ehlers–Danlos musculocontractural type 2 in a Pakistani family
Authors: Ullah Ikram , Aamir Muhammad , Ilyas Muhammad , Ahmed Akmal , Jelani Musharraf , Ullah Wahid , Abbas Muhammad , Ishfaq Muhammad , Ali Fawad , Yip Janice , Efthymiou Stephanie , Ahmed Habib , Houlden Henry 
Published: June 2021

AbstractThe Ehlers–Danlos syndrome (EDS) is a group of heritable connective tissue disorders. Common features of EDS include skin hyperextensibility, articular hypermobility, and tissue fragility. It is classified into 13 subtypes, caused by variations of more than 19 different genes. Among these two subtypes, EDS musculocontractural type 1 (EDSMC1/mcEDS‐CHST14; MIM# 601776) is caused by biallelic mutations in the CHST14 gene (MIM# 608429) on chromosome 15q14 and EDS musculocontractural type 2 (EDSMC2/mcEDS‐DSE;MIM#615539) is caused by a mutation in DSE (MIM# 605942) on chromosome 6q22. In this study, clinical and molecular diagnoses have been performed for a consanguineous Pakistani (Pakhtun) family with five affected siblings, presenting mcEDS‐DSE phenotype. Whole‐exome sequencing analysis identified a novel homozygous DSE variant (NM_001080976.1; c.2813T>A, p.Val938Asp) in the proband. Sanger sequencing in all available affected members and their obligate carriers confirmed autosomal recessive segregation of the diseased allele. To the best of our knowledge, this variant identified is novel and expands the DSE pathogenicity leading to EDS, musculocontractural type 2. The result obtained has the potential to help in early diagnosis, genetic counseling, and possible therapeutic inventions.
Texture Browser: Feature‐based Texture Exploration
Authors: Luo Xuejiao , Scandolo Leonardo , Eisemann Elmar 
Published: June 2021

AbstractTexture is a key characteristic in the definition of the physical appearance of an object and a crucial element in the creation process of 3D artists. However, retrieving a texture that matches an intended look from an image collection is difficult. Contrary to most photo collections, for which object recognition has proven quite useful, syntactic descriptions of texture characteristics is not straightforward, and even creating appropriate metadata is a very difficult task. In this paper, we propose a system to help explore large unlabeled collections of texture images. The key insight is that spatially grouping textures sharing similar features can simplify navigation. Our system uses a pre‐trained convolutional neural network to extract high‐level semantic image features, which are then mapped to a 2‐dimensional location using an adaptation of t‐SNE, a dimensionality‐reduction technique. We describe an interface to visualize and explore the resulting distribution and provide a series of enhanced navigation tools, our prioritized t‐SNE, scalable clustering, and multi‐resolution embedding, to further facilitate exploration and retrieval tasks. Finally, we also present the results of a user evaluation that demonstrates the effectiveness of our solution.
Accessible Visualization: Design Space, Opportunities, and Challenges
Authors: Kim N. W. , Joyner S. C. , Riegelhuth A. , Kim Y. 
Published: June 2021

AbstractVisualizations are now widely used across disciplines to understand and communicate data. The benefit of visualizations lies in leveraging our natural visual perception. However, the sole dependency on vision can produce unintended discrimination against people with visual impairments. While the visualization field has seen enormous growth in recent years, supporting people with disabilities is much less explored. In this work, we examine approaches to support this marginalized user group, focusing on visual disabilities. We collected and analyzed papers published for the last 20 years on visualization accessibility. We mapped a design space for accessible visualization that includes seven dimensions: user group, literacy task, chart type, interaction, information granularity, sensory modality, assistive technology. We described the current knowledge gap in light of the latest advances in visualization and presented a preliminary accessibility model by synthesizing findings from existing research. Finally, we reflected on the dimensions and discussed opportunities and challenges for future research.
A Deeper Understanding of Visualization‐Text Interplay in Geographic Data‐driven Stories
Authors: Latif Shahid , Chen Siming , Beck Fabian 
Published: June 2021

AbstractData‐driven stories comprise of visualizations and a textual narrative. The two representations coexist and complement each other. Although existing research has explored the design strategies and structure of such stories, it remains an open research question how the two representations play together on a detailed level and how they are linked with each other. In this paper, we aim at understanding the fine‐grained interplay of text and visualizations in geographic data‐driven stories. We focus on geographic content as it often includes complex spatiotemporal data presented as versatile visualizations and rich textual descriptions. We conduct a qualitative empirical study on 22 stories collected from a variety of news media outlets; 10 of the stories report the COVID‐19 pandemic, the others cover diverse topics. We investigate the role of every sentence and visualization within the narrative to reveal how they reference each other and interact. Moreover, we explore the positioning and sequence of various parts of the narrative to find patterns that further consolidate the stories. Drawing from the findings, we discuss study implications with respect to best practices and possibilities to automate the report generation.
Implicit Modeling of Patient‐Specific Aortic Dissections with Elliptic Fourier Descriptors
Authors: Mistelbauer G. , Rössl C. , Bäumler K. , Preim B. , Fleischmann D. 
Published: June 2021

AbstractAortic dissection is a life‐threatening vascular disease characterized by abrupt formation of a new flow channel (false lumen) within the aortic wall. Survivors of the acute phase remain at high risk for late complications, such as aneurysm formation, rupture, and death. Morphologic features of aortic dissection determine not only treatment strategies in the acute phase (surgical vs. endovascular vs. medical), but also modulate the hemodynamics in the false lumen, ultimately responsible for late complications. Accurate description of the true and false lumen, any communications across the dissection membrane separating the two lumina, and blood supply from each lumen to aortic branch vessels is critical for risk prediction. Patient‐specific surface representations are also a prerequisite for hemodynamic simulations, but currently require time‐consuming manual segmentation of CT data. We present an aortic dissection cross‐sectional model that captures the varying aortic anatomy, allowing for reliable measurements and creation of high‐quality surface representations. In contrast to the traditional spline‐based cross‐sectional model, we employ elliptic Fourier descriptors, which allows users to control the accuracy of the cross‐sectional contour of a flow channel. We demonstrate (i) how our approach can solve the requirements for generating surface and wall representations of the flow channels, (ii) how any number of communications between flow channels can be specified in a consistent manner, and (iii) how well branches connected to the respective flow channels are handled. Finally, we discuss how our approach is a step forward to an automated generation of surface models for aortic dissections from raw 3D imaging segmentation masks.
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization
Authors: Yan Lin , Masood Talha Bin , Sridharamurthy Raghavendra , Rasheed Farhan , Natarajan Vijay , Hotz Ingrid , Wang Bei 
Published: June 2021

AbstractIn topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. We present a state‐of‐the‐art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time‐varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.
Point cloud computing algorithm on object surface based on virtual reality technology
Authors: Zhang Wanyi , Fu Xiuhua , Li Wei 
Published: June 2021

AbstractVirtual reality technology is also known as VR technology. Accurately acquiring the three‐dimensional model of the point cloud on the surface of an object is a key part of virtual reality technology, and is also a research hotspot of virtual reality technology. The purpose of this article is to study the object surface point cloud computing algorithm based on virtual reality technology and its application problems and to solve the problems in the virtual reality technology object surface point cloud data algorithm, by reconstructing the geometry of the object surface in VR technology. The calculation rules at the time of data acquisition have been carried out in detailed research on the point cloud space carving algorithm based on the surface of multi‐eye visual objects. The research results show that the point cloud space carving algorithm on the surface of the virtual reality technology has a high degree of independence and the algorithm is very flexible. Compared with other algorithms, it reduces the operation steps by 35%, the 3D effect is increased by 21%, and the operation cost is reduced by 30%. The object surface point cloud computing algorithm based on virtual reality technology can greatly improve the computing efficiency, compared with the traditional two‐dimensional visual image integration algorithm, the efficiency is increased by 35%, and the computing accuracy in virtual reality technology is the same as the traditional two The accuracy of the integrated algorithm of dimensional visual pictures is improved by 44% compared to the accuracy. The experimental results verify the feasibility of applying the spatial carving algorithm to the three‐dimensional reconstruction of point cloud data on the surface of virtual reality technology objects.
A nutrient‐rich traditional insect for improving food security and reducing biodiversity loss in Madagascar and sub‐Saharan Africa
Authors: Borgerson Cortni , Fisher Brian L. , Razafindrapaoly Be Noel , Rasolofoniaina Be Jean Rodolph , Randriamanetsy Jeanne Mathilde , Razafindrapaoly Be Lexion , Rajaona Delox , Herrera Patsy , Van Itterbeeck Joost , Martinez Kenneth M. , Aardema Matthew L. 
Published: June 2021

AbstractForests, and the vertebrate species within them, are irreplaceable sources of food and nutrition for millions of people living in areas of high biodiversity. Unfortunately, many of these forests are being cleared for agriculture, and many animals are threatened with extinction from unsustainable hunting. Forest clearing and the hunting of threatened species are untenable solutions to long‐term food insecurity and adequate nutrition, jeopardizing these species' survival, the healthy functioning of ecosystems, and the cultural identities of local people. Working with communities to develop culturally appropriate ways for people to obtain sustainable and legal sources of food from forests outside of protected areas is a key component of improving both conservation and food security. We tested the feasibility, suitability, and viability of farming an abundant and traditionally eaten forest insect, Zanna tenebrosa (locally known as sakondry), in rural communities whose food security relies heavily on the hunting of threatened vertebrates. We found that the insect is high in macro‐ and micronutrients, and can be cheaply, easily, and sustainably cultivated to sustainably diversify forest food systems without increasing habitat loss. Given the range of Z. tenebrosa, which covers a broad swath of central Africa, increasing production of this native insect may support multipronged agroecological approaches to promoting food security, adequate nutrition, and wildlife conservation.
Association between dd‐cfDNA levels, de novo donor specific antibodies, and eGFR decline: An analysis of the DART cohort
Authors: Sawinski Deirdre L. , Mehta Shikha , Alhamad Tarek , Bromberg Jonathan S. , Fischbach Bernard , Aeschbacher Thomas , Ghosh Srinka , Shekhtman Grigoriy , Dholakia Sham , Brennan Daniel C. , Poggio Emilio , Bloom Roy D. , Jordan Stanley C. 
Published: June 2021

AbstractBackgroundDonor‐derived cell‐free DNA (dd‐cfDNA) is a marker of allograft injury in transplant recipients; however, the relationship between dd‐cfDNA and other clinical parameters associated with adverse allograft outcomes is not well‐characterized.MethodsWe performed a retrospective analysis of kidney transplant recipients from the DART cohort (ClinicalTrials.gov Identifier: NCT02424227) to evaluate the associations between eGFR decline, de novo donor‐specific antibodies (dnDSA), and dd‐cfDNA.ResultsBoth elevated dd‐cfDNA (≥1%) and dd‐cfDNA variability (≥.34%) in the first post‐transplant year were associated with decline in eGFR ≥25% in the second year (21.4% vs. 4.1%, P = .005; 25% vs. 3.6%, P = .002, respectively). Compared to samples from DSA negative patients, samples from patients with concurrent de novo HLA DSAs had higher dd‐cfDNA levels (P < .0001).DiscussionAbnormalities in dd‐cfDNA levels are associated with clinical parameters commonly used as surrogate endpoints for adverse allograft outcomes, raising the possibility that molecular injury as characterized by dd‐cfDNA could help identify patients at risk of these outcomes.
An endogenous analysis of early school leaving in Spain: The role of gender and regional inequalities
Authors: Bayón‐Calvo Siro , Lucas‐García Jezabel , Gómez‐García Rogelio 
Published: June 2021

AbstractEarly school leaving is a major social problem and a socio‐political priority in knowledge‐based societies, especially in southern European countries that have a tendency for comparatively high dropout rates. The literature has focused strongly on the exogenous factors that cause students to leave school early. Meanwhile, endogenous factors, such as scholastic performance, educational attainment or the holistic needs of students are also important to consider. Early school leaving represents the culmination of a process of disengagement; this article analyses some of the endogenous factors behind it. To this end, we compare early school leaving with educational results from previous stages. We focus on regional and gender inequalities in Spain, where early school leaving rates are the highest in the European Union. The results confirm the correlation between weak scholastic performance and early school leaving. They also reveal that regional and gender imbalances persist.
Assessment of psychiatric comorbidities and serotonergic or noradrenergic medication use on blood pressure using 24‐hour ambulatory blood pressure monitoring
Authors: Niazi Shehzad K. , Memon Sobia H. , Lesser Elizabeth R. , Brennan Emily , Aslam Nabeel 
Published: June 2021

AbstractIn this study, the authors aimed to assess both nighttime and daytime blood pressure (BP) variability using 24‐hour ambulatory BP monitoring (ABPM) in persons with and without psychiatric conditions and with or without selective serotonin reuptake inhibitors (SSRIs) or serotonin‐norepinephrine reuptake inhibitors (SNRIs) treatment. In this retrospective study, patients who underwent psychiatric evaluation and ABPM within 6 months of each other between January 1, 2012 and December 31, 2017 were identified using billing data. Participants were divided into three groups—participants with no psychiatric diagnosis and no psychiatric medicine (−Diagnosis/−Medication), those with psychiatric diagnosis and on SSRIs/SNRIs (+Diagnosis/+Medication), and psychiatric diagnosis but no psychiatric medications (+Diagnosis/−Medication). Day and nighttime systolic and diastolic BPs were compared between groups controlling for relevant variables using multivariable linear regression models. A total of 475 participants met inclusion criteria including 135 in the −Diagnosis/−Medication group, 232 in the +Diagnosis/+Medication group, and 108 in the +Diagnosis/−Medication group. In adjusted multivariable analysis, the +Diagnosis/+Medication group had higher nighttime systolic BP (median 120 vs 110 mm (Hg); p = .01) and nighttime diastolic BP (median 68 vs 63 mm (Hg); p = .006) as compared to −Diagnosis/−Medication. No statistically significant differences in BPs between the −Diagnosis/−Medication and +Diagnosis/−Medication groups were observed, after adjustment. Use of SSRIs/SNRIs was associated with significantly higher nocturnal systolic and diastolic BP among patients with psychiatric diagnosis using SSRIs/SNRIs but not associated with psychiatric diagnosis without SSRI/SNRI use. SSRIs/SNRIs use may be associated with higher BP levels and this merits future prospective studies using ABPM to assess day and nighttime BP changes with SSRIs/SNRIs use.
Oncology clinical practice guidelines usage among physicians in Nepal
Authors: Bhandari Divya , Ozaki Akihiko , Ghimire Bikal , Sigdel Shailendra , Shrestha Ranish , Shrestha Sunil , Higuchi Asaka , Uprety Anup , Tsubokura Masaharu , Tanimoto Tetsuya , Singh Yogendra Prasad 
Published: June 2021

AbstractObjectiveOncology clinical practice guidelines (OCPGs) are systematically developed evidence‐based recommendations aimed to guide practitioners in decision making during the diagnosis, management, and treatment of cancer patients under specific circumstances, thereby optimizing clinical outcomes. However, little is known about the implementation of those guidelines in low and middle‐income countries including Nepal. This research aimed to identify the type of OCPGs used by Nepalese physicians working in oncology departments and to explore barriers and facilitators affecting their use.MethodsUsing the total population sampling technique, we conducted an online cross‐sectional survey from June 2020 to January 2021 among physicians working in the oncology departments of Nepal. Descriptive analyses were conducted to summarize the research findings.ResultsOut of 171 physicians approached for the study, 102 (59.6%) responded to the questionnaire. The sizable proportions of the participants were a senior group of physicians with 27.5% being consultants, 14.7% senior consultants, and 16.7% professors. The most commonly used guideline was the National Comprehensive Cancer Network guideline of the United States (75.5%) followed by the American Society of Clinical Oncology guideline (44.7%). While only 22.6% of physicians reported using OCPGs every time, more than half (56.9%) highlighted that OCPGs are not feasible to implement in Nepal. Insufficient facilities/equipment, physicians' unwillingness to change their usual practice, inability to discuss research with knowledgeable colleagues, and lack of time were commonly cited barriers.ConclusionFindings of our study highlighted that the OCPGs developed in high‐income countries may not be feasible for low resource settings like Nepal. Comprehensive local OCPGs should be developed considering the available resources, feasibility, and financial constraints of patients. Furthermore, a constant sharing and learning environment should be created to enhance the knowledge of practicing physicians and to promote the proper implementation of evidence‐based findings.
Too much for your own good: Excessive dopamine damages neurons and contributes to Parkinson's disease
Authors: Masato Anna , Bubacco Luigi , Greggio Elisa 
Published: June 2021

AbstractDopamine dyshomeostasis is a driving factor of nigrostriatal degeneration in Parkinson's disease (PD). Accumulation of cytosolic dopamine at striatal projections results in the buildup of autoxidation products, which generates protein adducts and exacerbate oxidative stress. Moreover, an excessive rate of dopamine degradation results in accumulation of 3,4‐dihydroxyphenylacetaldehyde (DOPAL), a toxic metabolite which rapidly reacts with other proteins. These events lead to protein misfolding and cross‐linking as well as mitochondrial and lysosomal dysfunction, the main pathological mechanisms underscoring dopaminergic neuron loss in PD. In this issue of Journal of Neurochemistry, Vecchio et al. generated and characterized a new in vivo model of chronic dopamine accumulation through the overexpression of a hyperactive form of tyrosine hydroxylase (TH‐HI), the rate‐limiting step enzyme in dopamine biosynthesis. At 3–5 months of age, TH‐HI mice displayed increased striatal dopamine content, exacerbated dopamine catabolism, and augmented responses to amphetamine. This correlated with enhanced oxidative stress and DOPAL buildup, highlighting a catechol‐induced neurotoxic vicious cycle that may anticipate a parkinsonian‐like phenotype in aged mice. This novel TH‐HI animal model represents an exciting new tool to unravel the molecular mechanisms underlying dopamine disequilibrium, catecholamine autotoxicity, and neurodegeneration in PD.
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Vasopressin and central control of the cardiovascular system: A 40‐year retrospective
Authors: Pittman Quentin J. 
Published: June 2021

AbstractIn the 40 years since vasopressin (AVP) was reported to have a central action with respect to raising blood pressure, the finding has been repeatedly replicated using a variety of complimentary approaches. The role of AVP as a central neurotransmitter involved in control of the cardiovascular system is now textbook material. However, it is evident that brain AVP plays, at best, a minor role in regulation of normal blood pressure. However, it appears to be an important player in a several cardiovascular‐associated pathologies, ranging from hypertension to neural changes associated with heart failure. There are many interventions that have been shown to affect neural function, many of which are associated with alterations in behaviour. Possible alterations in neuronal AVP actions relevant to cardiovascular control in the setting of chronic inflammatory disease, early‐life stress and inflammation are suggested areas for future research.
Self‐affirmation theory in educational contexts
Authors: Easterbrook Matthew J. , Harris Peter R. , Sherman David K. 
Published: June 2021

AbstractSelf‐affirmation, operationalized as value‐affirmation interventions, can have long‐term beneficial effects on the academic performance and trajectories of members of negatively stereotyped groups, thus reducing achievement gaps. Yet, there is significant heterogeneity in the effectiveness of value affirmations, and we do not yet have a clear understanding of why. In this introduction to the special issue, we review the literature on self‐affirmation theory in educational contexts, providing overviews of the heterogeneity in the effectiveness of affirmation interventions, the methods of implementation, potential moderators, and underling processes. We identify several questions that are important for researchers to address, the answers to which would progress the field towards being able to more confidently implement value‐affirmations in contexts in which, and/or for groups for whom, they are most likely to produce benefits. We then introduce the articles included in this special issue, which showcase several of the latest theoretical and empirical advances to self‐affirmation theory in educational contexts.