bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased Slc34a2 expression and paracellular phosphate permeability contribute to high intestinal phosphate absorption in young mice
Authors: MacDonald Tate , Beggs Megan R. , O'Neill Debbie , Kozuka Kenji , Dimke Henrik , Alexander R. Todd 
Published: August 2023

AbstractAimPhosphorus is a critical constituent of bone as a component of hydroxyapatite. Bone mineral content accrues rapidly early in life necessitating a positive phosphorus balance, which could be established by a combination of increased renal reabsorption and intestinal absorption. Intestinal absorption can occur via a transcellular pathway mediated by the apical sodium‐phosphate cotransporter, Slc34a2/NaPiIIb or via the paracellular pathway. We sought to determine how young mammals increase dietary phosphorus absorption from the small intestine to establish a positive phosphorus balance, a prerequisite for rapid bone growth.MethodsThe developmental expression profile of genes mediating phosphate absorption from the small intestine was determined in mice by qPCR and immunohistochemistry. Additionally, Ussing chamber studies were performed on small bowel of young (p7–p14) and older (8‐ to 17‐week‐old) mice to examine developmental changes in paracellular Pi permeability and transcellular Pi transport.ResultsBlood and urinary Pi levels were higher in young mice. Intestinal paracellular phosphate permeability of young mice was significantly increased relative to older mice across all intestinal segments. NaPiIIb expression was markedly increased in juvenile mice, in comparison to adult animals. Consistent with this, young mice had increased transcellular phosphate flux across the jejunum and ileum relative to older animals. Moreover, transcellular phosphate transport was attenuated by the NaPiIIb inhibitor NTX1942 in the jejunum and ileum of young mice.ConclusionOur results are consistent with young mice increasing phosphate absorption via increasing paracellular permeability and the NaPiIIb‐mediated transcellular pathway.
‘Being’ and ‘doing’ well in the moment: Theoretical and relational contributions of health geography to living well with dementia
Authors: Ward Meghánn Catherine , Milligan Christine , Rose Emma Elizabeth , Elliott Mary 
Published: August 2023

AbstractOver the past two decades, advancements have been made towards de‐medicalising the term ‘dementia’, attending to in‐the‐moment lived experiences of people with the condition, and exploring the connections between dementia and place, relations, activities, and well‐being. In the same timeframe, a range of prominent researchers within health geography have proposed new renegotiations of well‐being that consider it as something relational, process‐oriented, and emergent. Although these progressions in both dementia studies and health geography are ontologically aligned, the two lines of enquiry have only recently started to see crossover, pioneered by geographers seeking to better understand what it means to ‘live well with dementia in the moment’. In this theoretically driven paper, I celebrate these contributions to dementia and well‐being studies through a timely review of the literature that informed the theoretical underpinnings of my own doctoral studies. Through the literature, I consider how a relational well‐being lens can make supportive and empowering in‐the‐moment contributions to people living with dementia, who seek ways of ‘being well’ and ‘doing well’. As part of a special edition of Area, this paper takes us from the early inputs of health geographers to dementia and relational well‐being knowledge, through to present‐day literature and the future of dementia research framed around the in‐the‐moment movement. The contents of this paper ultimately support the importance of pushing the theoretical and conceptual boundaries of dementia research and well‐being studies, to subsequently broaden our understandings of dementia and provide a new well‐being lens that better captures the perspectives of those living with it.
Process evaluation of a pharmacist‐led intervention aimed at deprescribing and appropriate use of cardiometabolic medication among adult people with type 2 diabetes
Authors: Baas Gert , Crutzen Stijn , Smits Sanne , Denig Petra , Taxis Katja , Heringa Mette 
Published: August 2023

AbstractBackgroundA quasi‐experimental study investigated a pharmacist‐led intervention aimed at deprescribing and medication management among adult patients with type 2 diabetes at risk of hypoglycaemia.ObjectiveThis study aimed to evaluate the process of implementing the intervention consisting of a tailored clinical medication review (CMR) supported by a training and a toolbox.MethodsMixed‐methods study based on the Grant framework, including the domains “recruitment,” “delivery of intervention” and “response” of pharmacists and patients. Data collected were administrative logs, semi‐structured observations of patient consultations (n = 8), interviews with pharmacists (n = 16) and patient‐reported experience measure (PREM) questionnaires (n = 66).ResultsTailored CMRs were conducted largely as intended for 90 patients from 14 pharmacies. Although patient selection based on a medication‐derived hypoglycaemia risk score was considered useful, pharmacists experienced barriers to proposing deprescribing in patients with recent medication changes, without current hypoglycaemic events, or treated by medical specialists. The training and toolbox were evaluated positively by the pharmacists. Overall, patients were satisfied with the CMR.ConclusionPharmacists and patients valued the CMR focusing on deprescribing and medication management. To optimize implementation and effectiveness of the intervention, improvements can be made to the patient selection, pharmacist training and the collaboration between healthcare professionals.
Nothing if not family? Genetic ties beyond the parent/child dyad
Authors: Cutas Daniela 
Published: August 2023

AbstractInternationally, there is considerable inconsistency in the recognition and regulation of children's genetic connections outside the family. In the context of gamete and embryo donation, challenges for regulation seem endless. In this paper, I review some of the paths that have been taken to manage children' being closely genetically related to people outside their families. I do so against the background of recognising the importance of children's interests as moral status holders. I look at recent qualitative research involving donor‐conceived people and borrow their own words to make sense of a purported interest to know (of) their close genetic ties. I also review ways in which gamete donation may have facilitated new kinds of kinship, which are at the same time genetic and chosen. In short, in this paper, I explore what meaning there could be in genetic connections that is not about parenthood. Further, I argue that the focus on parenthood in previous work in this area may be detrimental to appreciating some of the goods that can be derived from close genetic connections.
PowerRTF: Power Diagram based Restricted Tangent Face for Surface Remeshing
Authors: Yao Yuyou , Liu Jingjing , Fei Yue , Wu Wenming , Zhang Gaofeng , Yan Dong‐Ming , Zheng Liping 
Published: August 2023

AbstractTriangular meshes of superior quality are important for geometric processing in practical applications. Existing approximative CVT‐based remeshing methodology uses planar polygonal facets to fit the original surface, simplifying the computational complexity. However, they usually do not consider surface curvature. Topological errors and outliers can also occur in the close sheet surface remeshing, resulting in wrong meshes. With this regard, we present a novel method named PowerRTF, an extension of the restricted tangent face (RTF) in conjunction with the power diagram, to better approximate the original surface with curvature adaption. The idea is to introduce a weight property to each sample point and compute the power diagram on the tangent face to produce area‐controlled polygonal facets. Based on this, we impose the variable‐capacity constraint and centroid constraint to the PowerRTF, providing the trade‐off between mesh quality and computational efficiency. Moreover, we apply a normal verification‐based inverse side point culling method to address the topological errors and outliers in close sheet surface remeshing. Our method independently computes and optimizes the PowerRTF per sample point, which is efficiently implemented in parallel on the GPU. Experimental results demonstrate the effectiveness, flexibility, and efficiency of our method.
HalfedgeCNN for Native and Flexible Deep Learning on Triangle Meshes
Authors: Ludwig I. , Tyson D. , Campen M. 
Published: August 2023

AbstractWe describe HalfedgeCNN, a collection of modules to build neural networks that operate on triangle meshes. Taking inspiration from the (edge‐based) MeshCNN, convolution, pooling, and unpooling layers are consistently defined on the basis of halfedges of the mesh, pairs of oppositely oriented virtual instances of each edge. This provides benefits over alternative definitions on the basis of vertices, edges, or faces. Additional interface layers enable support for feature data associated with such mesh entities in input and output as well. Due to being defined natively on mesh entities and their neighborhoods, lossy resampling or interpolation techniques (to enable the application of operators adopted from image domains) do not need to be employed. The operators have various degrees of freedom that can be exploited to adapt to application‐specific needs.
HexBox: Interactive Box Modeling of Hexahedral Meshes
Authors: Zoccheddu F. , Gobbetti E. , Livesu M. , Pietroni N. , Cherchi G. 
Published: August 2023

AbstractWe introduce HexBox, an intuitive modeling method and interactive tool for creating and editing hexahedral meshes. Hexbox brings the major and widely validated surface modeling paradigm of surface box modeling into the world of hex meshing. The main idea is to allow the user to box‐model a volumetric mesh by primarily modifying its surface through a set of topological and geometric operations. We support, in particular, local and global subdivision, various instantiations of extrusion, removal, and cloning of elements, the creation of non‐conformal or conformal grids, as well as shape modifications through vertex positioning, including manual editing, automatic smoothing, or, eventually, projection on an externally‐provided target surface. At the core of the efficient implementation of the method is the coherent maintenance, at all steps, of two parallel data structures: a hexahedral mesh representing the topology and geometry of the currently modeled shape, and a directed acyclic graph that connects operation nodes to the affected mesh hexahedra. Operations are realized by exploiting recent advancements in grid‐based meshing, such as mixing of 3‐refinement, 2‐refinement, and face‐refinement, and using templated topological bridges to enforce on‐the‐fly mesh conformity across pairs of adjacent elements. A direct manipulation user interface lets users control all operations. The effectiveness of our tool, released as open source to the community, is demonstrated by modeling several complex shapes hard to realize with competing tools and techniques.
Singularity‐Free Frame Fields for Line Drawing Vectorization
Authors: Guţan Olga , Hegde Shreya , Berumen Erick Jimenez , Bessmeltsev Mikhail , Chien Edward 
Published: August 2023

AbstractState‐of‐the‐art methods for line drawing vectorization rely on generated frame fields for robust direction disambiguation, with each of the two axes aligning to different intersecting curve tangents around junctions. However, a common source of topological error for such methods are frame field singularities. To remedy this, we introduce the first frame field optimization framework guaranteed to produce singularity‐free fields aligned to a line drawing. We first perform a convex solve for a roughly‐aligned orthogonal frame field (cross field), and then comb away its internal singularities with an optimal transport–based matching. The resulting topology of the field is strictly maintained with the machinery of discrete trivial connections in a final, non‐convex optimization that allows non‐orthogonality of the field, improving smoothness and tangent alignment. Our frame fields can serve as a drop‐in replacement for frame field optimizations used in previous work, improving the quality of the final vectorizations.
Variational Pruning of Medial Axes of Planar Shapes
Authors: Rong P. , Ju T. 
Published: August 2023

AbstractMedial axis (MA) is a classical shape descriptor in graphics and vision. The practical utility of MA, however, is hampered by its sensitivity to boundary noise. To prune unwanted branches from MA, many definitions of significance measures over MA have been proposed. However, pruning MA using these measures often comes at the cost of shrinking desirable MA branches and losing shape features at fine scales. We propose a novel significance measure that addresses these shortcomings. Our measure is derived from a variational pruning process, where the goal is to find a connected subset of MA that includes as many points that are as parallel to the shape boundary as possible. We formulate our measure both in the continuous and discrete settings, and present an efficient algorithm on a discrete MA. We demonstrate on many examples that our measure is not only resistant to boundary noise but also excels over existing measures in preventing MA shrinking and recovering features across scales.
Feature‐Preserving Offset Mesh Generation from Topology‐Adapted Octrees
Authors: Zint D. , Maruani N. , Rouxel‐Labb M. , Alliez P. 
Published: August 2023

AbstractWe introduce a reliable method to generate offset meshes from input triangle meshes or triangle soups. Our method proceeds in two steps. The first step performs a Dual Contouring method on the offset surface, operating on an adaptive octree that is refined in areas where the offset topology is complex. Our approach substantially reduces memory consumption and runtime compared to isosurfacing methods operating on uniform grids. The second step improves the output Dual Contouring mesh with an offset‐aware remeshing algorithm to reduce the normal deviation between the mesh facets and the exact offset. This remeshing process reconstructs concave sharp features and approximates smooth shapes in convex areas up to a user‐defined precision. We show the effectiveness and versatility of our method by applying it to a wide range of input meshes. We also benchmark our method on the Thingi10k dataset: watertight and topologically 2‐manifold offset meshes are obtained for 100% of the cases.
Partial Matching of Nonrigid Shapes by Learning Piecewise Smooth Functions
Authors: Bensaïd David , Rotstein Noam , Goldenstein Nelson , Kimmel Ron 
Published: August 2023

AbstractLearning functions defined on non‐flat domains, such as outer surfaces of non‐rigid shapes, is a central task in computer vision and geometry processing. Recent studies have explored the use of neural fields to represent functions like light reflections in volumetric domains and textures on curved surfaces by operating in the embedding space. Here, we choose a different line of thought and introduce a novel formulation of partial shape matching by learning a piecewise smooth function on a surface. Our method begins with pairing sparse landmarks defined on a full shape and its part, using feature similarity. Next, a neural representation is optimized to fit these landmarks, efficiently interpolating between the matched features that act as anchors. This process results in a function that accurately captures the partiality. Unlike previous methods, the proposed neural model of functions is intrinsically defined on the given curved surface, rather than the classical embedding Euclidean space. This representation is shown to be particularly well‐suited for representing piecewise smooth functions. We further extend the proposed framework to the more challenging part‐to‐part setting, where both shapes exhibit missing parts. Comprehensive experiments highlight that the proposed method effectively addresses partiality in shape matching and significantly outperforms leading state‐of‐the‐art methods in challenging benchmarks. Code is available at https://github.com/davidgip74/Learning-Partiality-with-Implicit-Intrinsic-Functions
BPM: Blended Piecewise Möbius Maps
Authors: Rorberg Shir , Vaxman Amir , Ben‐Chen Mirela 
Published: August 2023

AbstractWe propose a novel Möbius interpolator that takes as an input a discrete map between the vertices of two planar triangle meshes, and outputs a continuous map on the input domain. The output map interpolates the discrete map, is continuous between triangles, and has low quasi‐conformal distortion when the input map is discrete conformal. Our map leads to considerably smoother texture transfer compared to the alternatives, even on very coarse triangulations. Furthermore, our approach has a closed‐form expression, is local, applicable to any discrete map, and leads to smooth results even for extreme deformations. Finally, by working with local intrinsic coordinates, our approach is easily generalizable to discrete maps between a surface triangle mesh and a planar mesh, i.e., a planar parameterization. We compare our method with existing approaches, and demonstrate better texture transfer results, and lower quasi‐conformal errors.
VOLMAP: a Large Scale Benchmark for Volume Mappings to Simple Base Domains
Authors: Cherchi G. , Livesu M. 
Published: August 2023

AbstractCorrespondences between geometric domains (mappings) are ubiquitous in computer graphics and engineering, both for a variety of downstream applications and as core building blocks for higher level algorithms. In particular, mapping a shape to a convex or star‐shaped domain with simple geometry is a fundamental module in existing pipelines for mesh generation, solid texturing, generation of shape correspondences, advanced manufacturing etc. For the case of surfaces, computing such a mapping with guarantees of injectivity is a solved problem. Conversely, robust algorithms for the generation of injective volume mappings to simple polytopes are yet to be found, making this a fundamental open problem in volume mesh processing. VOLMAP is a large scale benchmark aimed to support ongoing research in volume mapping algorithms. The dataset contains 4.7K tetrahedral meshes, whose boundary vertices are mapped to a variety of simple domains, either convex or star‐shaped. This data constitutes the input for candidate algorithms, which are then required to position interior vertices in the domain to obtain a volume map. Overall, this yields more than 22K alternative test cases. VOLMAP also comprises tools to process this data, analyze the resulting maps, and extend the dataset with new meshes, boundary maps and base domains. This article provides a brief overview of the field, discussing its importance and the lack of effective techniques. We then introduce both the dataset and its major features. An example of comparative analysis between two existing methods is also present.
Neural Representation of Open Surfaces
Authors: Christiansen T. V. , Bærentzen J. A. , Paulsen R. R. , Hannemose M. R. 
Published: August 2023

AbstractNeural implicit surfaces have emerged as an effective, learnable representation for shapes of arbitrary topology. However, representing open surfaces remains a challenge. Different methods, such as unsigned distance fields (UDF), have been proposed to tackle this issue, but a general solution remains elusive. The generalized winding number (GWN), which is often used to distinguish interior points from exterior points of 3D shapes, is arguably the most promising approach. The GWN changes smoothly in regions where there is a hole in the surface, but it is discontinuous at points on the surface. Effectively, this means that it can be used in lieu of an implicit surface representation while providing information about holes, but, unfortunately, it does not provide information about the distance to the surface necessary for e.g. ray tracing, and special care must be taken when implementing surface reconstruction. Therefore, we introduce the semi‐signed distance field (SSDF) representation which comprises both the GWN and the surface distance. We compare the GWN and SSDF representations for the applications of surface reconstruction, interpolation, reconstruction from partial data, and latent vector analysis using two very different data sets. We find that both the GWN and SSDF are well suited for neural representation of open surfaces.
Comparing the effects of GBA variants and onset age on clinical features and progression in Parkinson's disease
Authors: Ren Jingru , Zhan Xiaoyan , Zhou Hao , Guo Zhiying , Xing Yi , Yin Hangxing , Xue Chen , Wu Jun , Liu Weiguo 
Published: August 2023

AbstractObjectiveGlucosylceramidase (GBA) variants and onset age significantly affect clinical phenotype and progression in Parkinson's disease (PD). The current study compared clinical characteristics at baseline and cognitive and motor progression over time among patients having GBA‐related PD (GBA‐PD), early‐onset idiopathic PD (early‐iPD), and late‐onset idiopathic PD (late‐iPD).MethodsWe recruited 88 GBA‐PD, 167 early‐iPD, and 488 late‐iPD patients in this study. A subset of 50 GBA‐PD, 81 early‐iPD, and 223 late‐iPD patients was followed up at least once, with a 3.0‐year mean follow‐up time. Linear mixed‐effects models helped evaluate the rate of change in the Unified Parkinson's Disease Rating Scale motor and Montreal Cognitive Assessment scores.ResultsAt baseline, the GBA‐PD group showed more severe motor deficits and non‐motor symptoms (NMSs) than the early‐iPD group and more NMSs than the late‐iPD group. Moreover, the GBA‐PD group had more significant cognitive and motor progression, particularly bradykinesia and axial impairment, than the early‐iPD and late‐iPD groups at follow‐up. However, the early‐onset GBA‐PD (early‐GBA‐PD) group was similar to the late‐onset GBA‐PD (late‐GBA‐PD) group in baseline clinical features and cognitive and motor progression.ConclusionGBA‐PD patients exhibited faster cognitive and motor deterioration than early‐iPD and late‐iPD patients. Thus, subtype classification based on genetic characteristics rather than age at onset could enhance the prediction of PD disease progression.
Outcomes with transplanting kidneys offered through expedited allocation
Authors: Jadlowiec Caroline C. , Ohara Stephanie Y. , Punukollu Rachana , Wagler Josiah , Ruch Brianna , Kumm Kayla , Budhiraja Pooja , Me Hay Me , Mathur Amit K. , Reddy Kunam S. , Khamash Hasan , Heilman Raymond 
Published: August 2023

AbstractIntroductionExpedited out‐of‐sequence deceased donor kidney allocation is a strategy to avoid discards after early placement attempts have been unsuccessful. Our study aimed to assess outcomes and characteristics of these transplanted kidneys.MethodsKDPI matching was performed between expedited allocation (EA) and standard allocation (SA) deceased donor kidney transplants performed at our center.ResultsBetween 2018 and 2021, there were 225 EA offers, and 189 (84%) were transplanted. EA recipients were older (p = .007) and had shorter dialysis vintage (p < .0001). EA kidneys were likely to be nationally allocated (p < .001), have AKI (p < .0001) and longer CIT (p < .0001). There were no differences in EA and SA time‐zero kidney biopsies (ci, p = .07; ct, p = .89; cv, p = .95; ah, p = .79). EA kidneys had more DGF (p = .0006), but there were no differences in DGF duration (p = .83), hospital length of stay (p = .43), 1‐ and 2‐year eGFR (p = .16, p = .99), patient (p = .34), or death‐censored graft (p = .66) survival.ConclusionDuring this study period, our center transplanted 189 kidneys through EA following local‐regional declines. These kidneys often came from AKI donors and had more DGF but had similar outcomes to KDPI‐matched SA kidneys. Although it has been suggested that EA has the potential to worsen transplant disparities, transplant center level decisions on organ acceptance contribute to these variations.