bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends in medication use at the onset of and during the COVID‐19 pandemic in the Republic of Ireland: An interrupted time series study
Authors: Mattsson Molly , Hong Jung Ah , Frazer John Scott , Frazer Glenn Ross , Moriarty Frank 
Published: October 2023

AbstractThe COVID‐19 pandemic had a substantial impact on healthcare delivery, particularly in general practice. This study aimed to evaluate how dispensing of medications in primary care in Ireland changed following the COVID‐19 pandemic's onset compared to expected trends. This interrupted time series study used data on medications prescribed in general practice 2016–2022 to patient eligible for state health cover, approximately one third of the population. Dispensing volumes for all therapeutic subgroups (ATC2 codes) and commonly dispensed medications were summarized. Pre‐pandemic data were used to forecast expected trends (with 99% prediction intervals) using the Holt‐Winters method, and these were compared to observed dispensing from March 2020 onwards. Many (31/77) therapeutic subgroups had dispensing significantly different from forecast in March 2020. Drugs for obstructive airway disease had the largest difference, with dispensing 26.2% (99%CI 19.5%–33.6%) higher than forecasted. Only two subgroups were significantly lower than forecasted, other gynaecologicals (17.7% lower, 99%CI 6.3%–26.6%) and dressings (11.6%, 99%CI 9.4%–41.6%). Dispensing of amoxicillin products and oral prednisolone were lower than forecasted in the months following the pandemic's onset, particularly during winter 2020/2021. There was a spike in dispensing for many long‐term medications in March 2020, while pandemic restrictions likely contributed to reductions for other medications.
The academic point‐of‐care anti‐CD19 chimeric antigen receptor T‐cell product varnimcabtagene autoleucel (ARI‐0001 cells) shows efficacy and safety in the treatment of relapsed/refractory B‐cell non‐Hodgkin lymphoma
Authors: Martínez‐Cibrián Núria , Ortiz‐Maldonado Valentín , Español‐Rego Marta , Blázquez Andrea , Cid Joan , Lozano Miquel , Magnano Laura , Giné Eva , Correa Juan G. , Mozas Pablo , Rodríguez‐Lobato Luis Gerardo , Rivero Andrea , Montoro‐Lorite Mercedes , Ayora Pilar , Navarro Sergio , Alserawan Leticia , González‐Navarro E. Azucena , Castellà Maria , Sánchez‐Castañón María , Cabezón Raquel , Benítez‐Ribas Daniel , Setoaín Xavier , Rodríguez Sonia , Brillembourg Helena , Varea Sara , Olesti Eulalia , Guillén Elena , Sáez‐Peñataro Joaquín , de Larrea Carlos Fernández , López‐Guillermo Armando , Pascal Mariona , Urbano‐Ispizua Álvaro , Juan Manel , Delgado Julio 
Published: October 2023

SummaryVarnimcabtagene autoleucel (var‐cel) is an academic anti‐CD19 chimeric antigen receptor (CAR) product used for the treatment of non‐Hodgkin lymphoma (NHL) in the CART19‐BE‐01 trial. Here we report updated outcomes of patients with NHL treated with var‐cel. B‐cell recovery was compared with patients with acute lymphoblastic leukaemia (ALL). Forty‐five patients with NHL were treated. Cytokine release syndrome (any grade) occurred in 84% of patients (4% grade ≥3) and neurotoxicity in 7% (2% grade ≥3). The objective response rate was 73% at Day +100, and the 3‐year duration of response was 56%. The 3‐year progression‐free and overall survival were 40% and 52% respectively. High lactate dehydrogenase was the only covariate with an impact on progression‐free survival. The 3‐year incidence of B‐cell recovery was lower in patients with NHL compared to ALL (25% vs. 60%). In conclusion, in patients with NHL, the toxicity of var‐cel was manageable, while B‐cell recovery was significantly prolonged compared to ALL. This trial was registered as NCT03144583.
Death from mantle cell lymphoma limits sequential therapy, particularly after first relapse: Patterns of care and outcomes in a series from Australia and the United Kingdom
Authors: Minson Adrian , Hamad Nada , Di Ciaccio Pietro , Talaulikar Dipti , Ku Matthew , Ratnasingam Sumita , Cheah Chan , Yannakou Costas K. , Bishton Mark , Ng Zi Yun , Agrawal Shivam , McQuillan Andrew , Johnston Anna , Choong Emily , Wong Kimberly , McQuillan James , Beekman Ashley , Hawkes Eliza , Dickinson Michael 
Published: October 2023

SummaryMantle cell lymphoma (MCL) is a B‐cell non‐Hodgkin lymphoma characterised by a heterogeneous clinical course. Patients can often receive sequential treatments, yet these typically yield diminishing periods of disease control, raising questions about optimal therapy sequencing. Novel agents, such as chimeric antigen receptor T‐cell therapies and bispecific antibodies, show promise in relapsed MCL, but are often reserved for later treatment lines, which may underserve patients with aggressive disease phenotypes who die early in the treatment journey. To assess the problem of patient attrition from lymphoma‐related death limiting sequential treatment, we performed a multicentre retrospective cohort analysis of 389 patients treated at Australian and UK centres over a 10‐year period. Deaths from MCL increased after each treatment line, with 7%, 23% and 26% of patients dying from uncontrolled MCL after first, second and third lines respectively. Patients with older age at diagnosis and early relapse after induction therapy were at particular risk of death after second‐line treatment. This limitation of sequential treatment by lymphoma‐related death provides support for the trial of novel therapies in earlier treatment lines, particularly in high‐risk patient populations.
Structure learning for 3D Point Cloud Generation from Single RGB Images
Authors: Charrada T. Ben , Laga H. , Tabia H. 
Published: October 2023

Abstract3D point clouds can represent complex 3D objects of arbitrary topologies and with fine‐grained details. They are, however, hard to regress from images using convolutional neural networks, making tasks such as 3D reconstruction from monocular RGB images challenging. In fact, unlike images and volumetric grids, point clouds are unstructured and thus lack proper parameterization, which makes them difficult to process using convolutional operations. Existing point‐based 3D reconstruction methods that tried to address this problem rely on complex end‐to‐end architectures with high computational costs. Instead, we propose in this paper a novel mechanism that decouples the 3D reconstruction problem from the structure (or parameterization) learning task, making the 3D reconstruction of objects of arbitrary topologies tractable and thus easier to learn. We achieve this using a novel Teacher‐Student network where the Teacher learns to structure the point clouds. The Student then harnesses the knowledge learned by the Teacher to efficiently regress accurate 3D point clouds. We train the Teacher network using 3D ground‐truth supervision and the Student network using the Teacher's annotations. Finally, we employ a novel refinement network to overcome the upper‐bound performance that is set by the Teacher network. Our extensive experiments on ShapeNet and Pix3D benchmarks, and on in‐the‐wild images demonstrate that the proposed approach outperforms previous methods in terms of reconstruction accuracy and visual quality.
Facial Image Shadow Removal via Graph‐based Feature Fusion
Authors: Zhang Ling , Chen Ben , Liu Zheng , Xiao Chunxia 
Published: October 2023

AbstractDespite natural image shadow removal methods have made significant progress, they often perform poorly for facial image due to the unique features of the face. Moreover, most learning‐based methods are designed based on pixel‐level strategies, ignoring the global contextual relationship in the image. In this paper, we propose a graph‐based feature fusion network (GraphFFNet) for facial image shadow removal. We apply a graph‐based convolution encoder (GCEncoder) to extract global contextual relationships between regions in the coarse shadow‐less image produced by an image flipper. Then, we introduce a feature modulation module to fuse the global topological relation onto the image features, enhancing the feature representation of the network. Finally, the fusion decoder integrates all the effective features to reconstruct the image features, producing a satisfactory shadow‐removal result. Experimental results demonstrate the superiority of the proposed GraphFFNet over the state‐of‐the‐art and validate the effectiveness of facial image shadow removal.
Multi‐Level Implicit Function for Detailed Human Reconstruction by Relaxing SMPL Constraints
Authors: Ma Xikai , Zhao Jieyu , Teng Yiqing , Yao Li 
Published: October 2023

AbstractAiming at enhancing the rationality and robustness of the results of single‐view image‐based human reconstruction and acquiring richer surface details, we propose a multi‐level reconstruction framework based on implicit functions. This framework first utilizes the predicted SMPL model (Skinned Multi‐Person Linear Model) as a prior to further predict consistent 2.5D sketches (depth map and normal map), and then obtains a coarse reconstruction result through an Implicit Function fitting network (IF‐Net). Subsequently, with a pixel‐aligned feature extraction module and a fine IF‐Net, the strong constraints imposed by SMPL are relaxed to add more surface details to the reconstruction result and remove noise. Finally, to address the trade‐off between surface details and rationality under complex poses, we propose a novel fusion repair algorithm that reuses existing information. This algorithm compensates for the missing parts of the fine reconstruction results with the coarse reconstruction results, leading to a robust, rational, and richly detailed reconstruction. The final experiments prove the effectiveness of our method and demonstrate that it achieves the richest surface details while ensuring rationality. The project website can be found athttps://github.com/MXKKK/2.5D‐MLIF.
Error‐bounded Image Triangulation
Authors: Fang Zhi‐Duo , Guo Jia‐Peng , Xiao Yanyang , Fu Xiao‐Ming 
Published: October 2023

AbstractWe propose a novel image triangulation method to reduce the complexity of image triangulation under the color error‐bounded constraint and the triangle quality constraint. Meanwhile, we realize a variety of visual effects by supporting different types of triangles (e.g., linear or curved) and color approximation functions (e.g., constant, linear, or quadratic). To adapt to these discontinuous and combinatorial objectives and constraints, we formulate it as a constrained optimization problem that is solved by a series of tailored local remeshing operations. The feasibility and practicability of our method are demonstrated over various types of images, such as organisms, landscapes, portraits and cartoons. Compared to state‐of‐the‐art methods, our method generates far fewer triangles for the same color error or much smaller color errors using the same number of triangles.
MAPMaN: Multi‐Stage U‐Shaped Adaptive Pattern Matching Network for Semantic Segmentation of Remote Sensing Images
Authors: Hong T. , Ma X. , Wang X. , Che R. , Hu C. , Feng T. , Zhang W. 
Published: October 2023

AbstractRemote sensing images (RSIs) often possess obvious background noises, exhibit a multi‐scale phenomenon, and are characterized by complex scenes with ground objects in diversely spatial distribution pattern, bringing challenges to the corresponding semantic segmentation. CNN‐based methods can hardly address the diverse spatial distributions of ground objects, especially their compositional relationships, while Vision Transformers (ViTs) introduce background noises and have a quadratic time complexity due to dense global matrix multiplications. In this paper, we introduce Adaptive Pattern Matching (APM), a lightweight method for long‐range adaptive weight aggregation. Our APM obtains a set of pixels belonging to the same spatial distribution pattern of each pixel, and calculates the adaptive weights according to their compositional relationships. In addition, we design a tiny U‐shaped network using the APM as a module to address the large variance of scales of ground objects in RSIs. This network is embedded after each stage in a backbone network to establish a Multi‐stage U‐shaped Adaptive Pattern Matching Network (MAPMaN), for nested multi‐scale modeling of ground objects towards semantic segmentation of RSIs. Experiments on three datasets demonstrate that our MAPMaN can outperform the state‐of‐the‐art methods in common metrics. The code can be available athttps://github.com/INiid/MAPMaN.
Anti‐PD‐1 treatment protects against seizure by suppressing sodium channel function
Authors: Yang Yuling , Chen Zhiyun , Zhou Jing , Jiang Shize , Wang Guoxiang , Wan Li , Yu Jiangning , Jiang Min , Wang Yulong , Hu Jie , Liu Xu , Wang Yun 
Published: October 2023

AbstractAimsAlthough programmed cell death protein 1 (PD‐1) typically serves as a target for immunotherapies, a few recent studies have found that PD‐1 is expressed in the nervous system and that neuronal PD‐1 might play a crucial role in regulating neuronal excitability. However, whether brain‐localized PD‐1 is involved in seizures and epileptogenesis is still unknown and worthy of in‐depth exploration.MethodsThe existence of PD‐1 in human neurons was confirmed by immunohistochemistry, and PD‐1 expression levels were measured by real‐time quantitative PCR (RT‐qPCR) and western blotting. Chemoconvulsants, pentylenetetrazol (PTZ) and cyclothiazide (CTZ), were applied for the establishment of in vivo (rodents) and in vitro (primary hippocampal neurons) models of seizure, respectively. SHR‐1210 (a PD‐1 monoclonal antibody) and sodium stibogluconate (SSG, a validated inhibitor of SH2‐containing protein tyrosine phosphatase‐1 [SHP‐1]) were administrated to investigate the impact of PD‐1 pathway blockade on epileptic behaviors of rodents and epileptiform discharges of neurons. A miRNA strategy was applied to determine the impact of PD‐1 knockdown on neuronal excitability. The electrical activities and sodium channel function of neurons were determined by whole‐cell patch‐clamp recordings. The interaction between PD‐1 and α‐6 subunit of human voltage‐gated sodium channel (Nav1.6) was validated by performing co‐immunostaining and co‐immunoprecipitation (co‐IP) experiments.ResultsOur results reveal that PD‐1 protein and mRNA levels were upregulated in lesion cores compared with perifocal tissues of surgically resected specimens from patients with intractable epilepsy. Furthermore, we show that anti‐PD‐1 treatment has anti‐seizure effects both in vivo and in vitro. Then, we reveal that PD‐1 blockade can alter the electrophysiological properties of sodium channels. Moreover, we reveal that PD‐1 acts together with downstream SHP‐1 to regulate sodium channel function and hence neuronal excitability. Further investigation suggests that there is a direct interaction between neuronal PD‐1 and Nav1.6.ConclusionOur study reveals that neuronal PD‐1 plays an important role in epilepsy and that anti‐PD‐1 treatment protects against seizures by suppressing sodium channel function, identifying anti‐PD‐1 treatment as a novel therapeutic strategy for epilepsy.
Repeat After Me? Both Children With and Without Autism Commonly Align Their Language With That of Their Caregivers
Authors: Fusaroli Riccardo , Weed Ethan , Rocca Roberta , Fein Deborah , Naigles Letitia 
Published: October 2023

AbstractLinguistic repetitions in children are conceptualized as negative in children with autism – echolalia, without communicative purpose – and positive in typically developing (TD) children – linguistic alignment involved in shared engagement, common ground and language acquisition. To investigate this apparent contradiction we analyzed spontaneous speech in 67 parent–child dyads from a longitudinal corpus (30 minutes of play activities at 6 visits over 2 years). We included 32 children with autism and 35 linguistically matched TD children (mean age at recruitment 32.76 and 20.27 months). We found a small number of exact repetitions in both groups (roughly 1% of utterances across visits), which increased over time in children with autism and decreased in the TD group. Partial repetitions were much more frequent: children reused caregivers' words at high rates regardless of diagnostic group (24% of utterances at first visit), and this increased in frequency (but not level) over time, faster for TD children (at final visit: 33% for autism, 40% for TD). The same happened for partial repetition of syntax and semantic alignment. However, chance alignment (as measured by surrogate pairs) also increased and findings for developmental changes were reliable only for syntactic and semantic alignment. Children with richer linguistic abilities also displayed a higher tendency to partially re–use their caregivers' language (alignment rates and semantic alignment). This highlights that all children commonly re–used the words, syntax, and topics of their caregivers, albeit with some quantitative differences, and that most repetition was at least potentially productive, with repeated language being re–contextualized and integrated with non–repeated language. The salience of echolalia in ASD might be partially explained by slight differences in frequency, amplified by lower semantic alignment, persistence over time, and expectations of echolalia. More in–depth qualitative and quantitative analyses of how repetitions are used and received in context are needed.
Fisheries outcomes of marine protected area networks: Levels of protection, connectivity, and time matter
Authors: Sève Charlotte , Belharet Mokrane , Melià Paco , Di Franco Antonio , Calò Antonio , Claudet Joachim 
Published: October 2023

AbstractEstablishing large networks of fully protected marine protected areas (MPAs) is challenging because of displacement costs for fisheries. The use of partially protected areas is often proposed as an alternative. However, how conservation and fisheries outcomes of MPA networks are mediated through time by the level of protection remains uncertain. Here we use a metapopulation model of a commercially exploited demersal coastal fish to assess conservation and fisheries outcomes of alternative management policies. We compare the temporal performances of nonspatial management, large MPAs, or networks of MPAs in an overfished case study. In addition, we assess how the magnitude of both outcomes is mediated by larval connectivity and level of protection. We distinguish the relative contribution to fisheries outcomes of unprotected areas in between MPAs, and unprotected areas further away, receiving less displaced fishing effort and potential biomass export. We show that spatial management outperforms nonspatial management, that conservation and fisheries outcomes increase with increasing levels of protection, that fisheries outcomes in areas in between MPAs are higher when connected through larval dispersal, and that increases in catch are preceded by a short‐term decrease. Our results call for an increase in protection levels to meet both ecological and fisheries management goals.
Longitudinal patterns of Alzheimer's disease subtypes: A follow‐up magnetic resonance imaging and single‐photon emission computed tomography study
Authors: Hanyu Haruo , Koyama Yumi , Horita Haruka , Watanabe Sadayoshi , Sato Tomohiko , Kanetaka Hidekazu , Shimizu Soichiro , Hirao Kentaro 
Published: October 2023

AimAlzheimer's disease (AD) is a biologically heterogenous disease. In a previous study, we classified 245 patients with probable AD into the typical AD (TAD), limbic‐predominant (LP), hippocampal‐sparing (HS) and minimal‐change (MC) subtypes based on their medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single‐photon emission computed tomography, and described differences in clinical features among the patients with different AD subtypes. This study aimed to clarify the longitudinal patterns of changes in patients with the various AD subtypes by follow‐up brain imaging analyses.MethodsFollow‐up magnetic resonance imaging or single‐photon emission computed tomography data obtained 12–48 months after the first brain imaging were investigated in 79 patients with probable AD, comprising 25 of the TAD subtype, 19 of the LP subtype, 17 of the HS subtype and 18 of the MC subtype.ResultsAll patients of the TAD subtype remained as the same subtype at follow up. Approximately 37% of patients of the LP subtype and 29% of patients of the HS subtype progressed to the TAD subtype, and 17%, 33% and 6% of the MC subtype progressed to the TAD, LP and HS subtypes, respectively. The group of patients showing subtype progression was associated only with a longer follow‐up duration.ConclusionsThere might be different progression patterns and progression rates of changes among the atypical AD subtypes. Further longitudinal brain imaging studies might provide information regarding the pathophysiological association between the various AD subtypes, and might be helpful for determining appropriate therapies and management methods. Geriatr Gerontol Int 2023; 23: 919–924.
Key topics in social science research on COVID‐19: An automated literature analysis
Authors: Cheng Xian , Zhao Ying , Liao Stephen Shaoyi 
Published: October 2023

AbstractBackgroundThe COVID‐19 pandemic has triggered a significant increase in academic research in the realm of social sciences. As such, there is an increasing need for the scientific community to adopt effective and efficient methods to examine the potential role and contribution of social sciences in the fight against COVID‐19.ObjectivesThis study aims to identify the key topics and explore publishing trends in social science research pertaining to COVID‐19 via automated literature analysis.MethodsThe automated literature analysis employed utilizes keyword analysis and topic modelling technique, specifically Latent Dirichlet Allocation, to highlight the most relevant research terms, overarching research themes and research trends within the realm of social science research on COVID‐19.ResultsThe focus of research and topics were derived from 9733 full‐text academic papers. The bulk of social science research on COVID‐19 centres on the following themes: ‘Clinical Treatment’, ‘Epidemic Crisis’, ‘Mental Influence’, ‘Impact on Students’, ‘Lockdown Influence’ and ‘Impact on Children’.ConclusionThis study adds to our understanding of key topics in social science research on COVID‐19. The automated literature analysis presented is particularly useful for librarians and information specialists keen to explore the role and contributions of social science topics in the context of pandemics.