bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robotic versus laparoscopic abdominoperineal resections for low rectal cancer: A single‐center randomized controlled trial
Authors: Feng Qingyang , Tang Wentao , Zhang Zhiyuan , Wei Ye , Ren Li , Chang Wenju , Zhu Dexiang , Liang Fei , He Guodong , Xu Jianmin 
Published: August 2022

AbstractBackground and ObjectivesRobotic surgery for rectal cancer is gaining popularity, but persuasive evidence on reducing surgical trauma is still lacking. This study compared robotic and laparoscopic abdominoperineal resections (APRs) for the risk of postoperative complications in low rectal cancer.MethodsBetween December 2013 and 2016, patients with rectal cancer ≤5 cm from anal verge, cT1‐T3 N0‐1, or ycT1‐T3 Nx stage, and no distant metastases were enrolled in a single‐center, randomized, controlled trial. Eligible patients were randomly allocated to robotic or laparoscopic APRs at 1:1 ratio. The primary outcome was 30‐day postoperative complication rate (Clavien−Dindo grade II or higher) of the intent‐to‐treat population. The trial registration number is NCT01985698 (http://www.clinicaltrials.gov).ResultsTotally 347 eligible patients were enrolled: 174 in robotic and 173 in laparoscopic group. Robotic APRs significantly reduced postoperative complication rate (13.2% vs. 23.7%, p = 0.013), also reduced open conversion rate (0% vs. 2.9%, p = 0.030), intraoperative hemorrhage (median, 100 vs. 130 ml; p < 0.001), 30‐day readmission rate (2.3% vs. 6.9%; p = 0.044), postoperative hospital stay (median, 5.0 vs. 7.0 days; p < 0.001), and improved urinary and sexual function. No significant difference was observed in long‐term oncological outcomes.ConclusionsCompared with laparoscopic APRs, robotic APRs significantly reduced surgical trauma and promoted postoperative recovery.
Consumer reactions to AI design: Exploring consumer willingness to pay for AI‐designed products
Authors: Zhang Hao , Bai Xiaofei , Ma Zengguang 
Published: August 2022

AbstractCompanies are increasingly using artificial intelligence (AI) technology to generate promising concepts for new products which are then marketed to consumers as “AI‐designed.” Drawing on four studies and follow‐up studies, this paper explores consumer perceptions of AI design. Based on the information gap model, the studies determine that, compared with professional‐designed products, consumers are more willing to pay for products designed by AI, in which process curiosity plays an intermediary role (Study 1). Crucially, this research also predicts the boundary conditions for the positive effects of AI design. High levels of consumer knowledge lead to an attenuation in consumer curiosity regarding AI design, thereby decreasing the willingness to pay (Study 2), while the product type also has a moderating effect on the influence of the product design sources. Consumers are more willing to pay for utilitarian products designed by AI than hedonic products (Study 3). In addition, we reverify that consumers prefer AI‐designed products through a field study (Study 4). Finally, the research sheds light on how to utilize AI to promote the success of new product innovation from a marketing perspective, providing important theoretical knowledge and actionable managerial implications for future research.
Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review
Authors: Pasquini Jacopo , Firbank Michael J. , Ceravolo Roberto , Silani Vincenzo , Pavese Nicola 
Published: August 2022

AbstractMultiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty‐four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Specific Gait Changes in Prodromal Hereditary Spastic Paraplegia Type 4: preSPG4 Study
Authors: Laßmann Christian , Ilg Winfried , Schneider Marc , Völker Maximilian , Haeufle Daniel F.B. , Schüle Rebecca , Giese Martin , Synofzik Matthis , Schöls Ludger , Rattay Tim W. 
Published: August 2022

ABSTRACTBackgroundIn hereditary spastic paraplegia type 4 (SPG4), subclinical gait changes might occur years before patients realize gait disturbances. The prodromal phase of neurodegenerative disease is of particular interest to halt disease progression by future interventions before impairment has manifested.ObjectiveThe objective of this study was to identify specific movement abnormalities before the manifestation of gait impairment and quantify disease progression in the prodromal phase.MethodsSeventy subjects participated in gait assessment, including 30 prodromal SPAST pathogenic variant carriers, 17 patients with mild‐to‐moderate manifest SPG4, and 23 healthy control subjects. An infrared‐camera‐based motion capture system assessed gait to analyze features such as range of motion and continuous angle trajectories. Those features were correlated with disease severity as assessed by the Spastic Paraplegia Rating Scale, neurofilament light chain as a fluid biomarker indicating neurodegeneration, and motor‐evoked potentials.ResultsCompared with healthy control subjects, we found an altered gait pattern in prodromal pathogenic variant carriers during the swing phase in the segmental angle of the foot (Dunn's post hoc test, q = 3.1) and heel ground clearance (q = 2.8). Furthermore, range of motion of segmental angle was reduced for the foot (q = 3.3). These changes occurred in prodromal pathogenic variant carriers without quantified leg spasticity in clinical examination. Gait features correlated with neurofilament light chain levels, central motor conduction times of motor‐evoked potentials, and Spastic Paraplegia Rating Scale score.ConclusionsGait analysis can quantify changes in prodromal and mild‐to‐moderate manifest SPG4 patients. Thus, gait features constitute promising motor biomarkers characterizing the subclinical progression of spastic gait and might help to evaluate interventions in early disease stages. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
Technical note: Characterization of novel iterative reconstructed cone beam CT images for dose tracking and adaptive radiotherapy on L‐shape linacs
Authors: Lim Rebecca , Penoncello Gregory P. , Hobbis Dean , Harrington Daniel P. , Rong Yi 
Published: August 2022

AbstractBackgroundCone‐beam computed tomography (CBCT) allows for patient setup and positioning, and potentially dose verification or adaptive replanning prior to each treatment delivery. Poor CBCT image quality due to scatter artifacts and patient motion has been a major limiting factor. A new image reconstruction algorithm was recently clinically implemented for improving image quality through iterative reconstruction (iCBCT).PurposeThis study aims to characterize iCBCT image quality, establish image value (HU)‐to‐relative electron density (RED) calibration curves for dose calculation, and assess the dosimetric accuracy for different anatomical sites.Material and methodsBoth conventional CBCT and iCBCT scans were acquired from a Varian TrueBeam On‐Board Imager system. A Catphan 604 phantom was scanned to compare image quality between the traditional Feldkamp–Davis–Kress (FDK) and novel iterative reconstruction techniques. Computerized Imaging Reference Systems (CIRS) electron density phantom was used to construct site‐specific HU‐RED curves corresponding to various scan settings. The CIRS Dynamic Thorax phantom, Rando pelvis phantom, and BrainLab head phantom were used for assessing dosimetric accuracy calculated on iCBCT images, compared to that on traditional FDK‐based CBCT images. All phantoms were scanned on a computed tomography (CT) to obtain baseline HU values for comparison.ResultsTest results obtained from Catphan showed statistically significant improvement with iCBCT, compared to FDK CBCT. Average HU differences from the baseline CT values were improved to within ±30 HU for iCBCT, compared to FDK CBCT for phantom studies. Dose calculated on iCBCT for both phantoms and patient cases directly using baseline HU‐RED calibration from CT showed 0.5%–2.0% accuracy from the baseline dose calculated on CT, which is comparable to doses calculated using site‐specific HU‐RED calibration curves.ConclusioniCBCT provides improved image quality, improved HU accuracy compared to CT baseline, and has potential to provide online dose verification as part of the adaptive radiotherapy workflow directly using the baseline HU‐RED calibration curve from CT.
Self‐gated, dynamic contrast‐enhanced magnetic resonance imaging with compressed‐sensing reconstruction for evaluating endothelial permeability in the aortic root of atherosclerotic mice
Authors: Calcagno Claudia , David John A. , Motaal Abdallah G. , Coolen Bram F. , Beldman Thijs , Corbin Alexandra , Kak Arnav , Ramachandran Sarayu , Pruzan Alison , Sridhar Arthi , Soler Raphael , Faries Christopher M. , Fayad Zahi A. , Mulder Willem J. M. , Strijkers Gustav J. 
Published: August 2022

High‐risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self‐gated, dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe−/− atherosclerotic mice during natural disease progression. Twenty‐four, 8‐week‐old, female Apoe−/− mice were divided into four groups (n = 6 each) and imaged with self‐gated DCE‐MRI at 4, 8, 12, and 16 weeks after high‐fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high‐fat diet and imaged longitudinally at the same time points. Aortic‐root pseudo‐concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash‐in and washout slopes (b1 and b2) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b2, indicating contrast agent washout, was significantly higher in mice kept on an high‐fat diet for longer periods of time (p = 0.03). Group comparison revealed significant differences between mice on a high‐fat diet for 4 versus 16 weeks (p = 0.03). Macrophage density also significantly increased with diet duration (p = 0.009). Spearman correlation between b2 from DCE‐MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE‐MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single‐slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease.
Civil society organizations and the prevention of mass atrocities: Perspectives from south Sudan
Authors: Appe Susan , Rubaii Nadia , Whigham Kerry 
Published: August 2022

AbstractNowhere is the role of civil society organizations (CSOs) in development and democratization more critical than in countries at high risk of mass atrocities. In this article, we examine the actual and potential role of development CSOs in the prevention of mass atrocities based on an analysis of 302 CSOs in South Sudan. The article examines if and how service‐providing CSOs frame their work as contributing to the prevention of mass atrocities. The article seeks to understand how these CSOs deliver services and articulate their work regarding the prevention of large‐scale identity‐based violence. We aim to explore the degree to which organizations describe atrocity prevention as an intentional part of democratization efforts. The article is situated within the larger debates about the service delivery and civil society functions of CSOs. Specifically, we ask: To what extent do development CSOs articulate a contribution to the prevention of mass atrocities? We posit that the service delivery and civil society functions can be better achieved by giving deliberate attention to an atrocity prevention perspective.
A nomogram model to predict prognosis of patients with hepatoblastoma
Authors: Ke Meng , Zhou Yan , Chang‐zhen Yang , Li Long , Diao Mei 
Published: August 2022

AbstractBackgroundHepatoblastomas (HBs) are malignant liver tumors that most commonly develop in pediatric patients. Microvascular invasion may be a prognosis factor for patients with HBs. This study aimed to construct a model to predict the survival outcome in HBs.MethodsWe retrospectively analyzed the clinical data of 311 patients with HBs who underwent surgical resection at our institution between June 2014 and August 2021. First, patients were divided into two groups: those who had pathologic microvascular invasion (n = 146) and those who did not (n = 165). Propensity score‐matched (PSM) analysis was carried out between the two groups. The preoperative parameters and overall survival (OS) rate were compared between the two groups. Second, all 311 patients were randomly divided into the training and validation cohort in a ratio of 4:1. A nomogram was created in the training cohort to visualize the prediction of OS. Moreover, the validation cohort was used for validation.ResultsMultivariate analysis suggested that age, histology type, microvascular invasion, multifocality, distant metastasis, and macrovascular involvement are independent prognostic factors for HBs. The nomogram showed good predictive ability in the training and validation cohorts with a C‐index of 0.878 (95% CI, 0.831‐0.925) and 0.847 (95% CI, 0.757‐0.937), respectively. The calibration curve indicated good agreement between the prediction and observation for one‐, two‐, and three‐year OS probabilities.ConclusionBy combining preoperative imaging results and other clinical data, we established a nomogram to predict OS probability for patients with HB, which could be a potential tool to guide personalized treatment.
Copper Nanoclusters Loaded on SA/PVA Composite Films for Sensitive Detection of Trace Water in Organic Solvent
Authors: Wei Wei , Ding Juan , Hou Haoting , Miao Xirui , Wang Mao , Pang Shujie , Yang Xudong 
Published: August 2022

AbstractCopper nanoclusters (CuNCs), a new type of fluorescent material, have attracted extensive attention due to their excellent fluorescence properties and stability. In this paper, orange–red organic fluorescent CuNCs are prepared using reduced glutathione both as a template and reducing agent. CuNCs are then doped into a polymer matrix of alginate and polyvinyl alcohol using the aggregation‐induced emission enhancement effect to produce a kind of easy to use fluorescent composite films. The fluorescent composite films can realize the specific detection of trace water in the organic environment, and the detection limit can reach 0.0025% (volume ratio). Compared with the pure exposed CuNCs, the fluorescence intensity is greatly improved, and more importantly, the fluorescent composite films can be used repeatedly, saving resources and environmental protection.
Analysis of protein structures containing HEPES and MES molecules
Authors: Macnar Joanna Magdalena , Brzezinski Dariusz , Chruszcz Maksymilian , Gront Dominik 
Published: August 2022

AbstractX‐ray crystallography is the main experimental method behind ligand–macromolecule complexes found in the Protein Data Bank (PDB). Applying bioinformatics methods to such structural data can fuel drug discovery, albeit under the condition that the information is correct. Regrettably, a small number of structures in the PDB are of suboptimal quality due to incorrectly identified and modeled ligands in protein–ligand complexes. In this paper, we combine a theoretical‐graph approach, nuclear density estimates, bioinformatics methods, and prior chemical knowledge to analyze two non‐physiological ligands, HEPES and MES, that are frequent components of crystallization and purifications buffers. Our analysis includes quantum mechanics calculations and Cambridge Structure Database (CSD) queries to define the ideal conformation of these ligands, geometry analysis of PDB deposits regarding several quality factors, and a search for homologous structures to identify other small molecules that could bind in place of the parasitic ligand. Our results highlight the need for careful refinement of macromolecule–ligand complexes and better validation tools that integrate results from all relevant resources.
A two‐fluid single‐column model of turbulent shallow convection. Part 1: Turbulence equations in the multifluid framework
Authors: Thuburn John , Efstathiou Georgios A. , McIntyre William A. 
Published: August 2022

AbstractThe multifluid equations are derived from the compressible Euler equations (or any of the usual approximate equation sets used in meteorology) by conditional filtering. They have the potential to provide the basis for an improved representation of cumulus convection and its coupling to the boundary layer and larger scale flow in numerical models. The present article derives the prognostic equations for subfilter‐scale turbulent second moments in the multifluid framework, along with certain systematic simplifications of them, thus providing a multifluid analogue of the well‐known Mellor and Yamada hierarchy of turbulence closures. As well as enabling a more accurate calculation of subfilter‐scale fluxes and the effects of subfilter‐scale variability on cloud fraction, liquid water, and buoyancy, the second moment information can be used to obtain a more accurate parameterization of entrainment and detrainment. A subset of the turbulence equations derived here is employed in the two‐fluid single‐column model described in Part 2 and applied to the simulation of shallow cumulus cases in Part 3.
Actuator fault detection for masonry robot manipulator arm with the interval observer
Authors: Zhao Jinbao , Zhang Ke , Hou Maxiao , Zhang Hao , Bai Yunfei , Huang Yanzheng , Li Jianan 
Published: August 2022

AbstractThe main construction method of building wall is artificial masonry, the main problem is that the process is associated with low construction efficiency and poor safety, workers are prone fall from high altitude. The research of automatic masonry robot has become an urgent need. The masonry mechanical arm system is the main executing part of the masonry robot, special attention should be paid to the robot fault. Therefore, it is necessary to establish a suitable model to detect the actuator faults of the manipulator system. In this paper, a dynamic model of manipulator fault is presented and a fault detection scheme of masonry robot manipulator arm is proposed based on the model. The model is simplified by analyzing the state parameters of each joint during robot masonry and the interval observer with more design freedom was designed based on the established mathematical model of actuator faults. In this paper, a joint method for solving S and L matrices is proposed, which avoids the limitation of the traditional method for solving L matrices by two‐step. In the presence of external interference, / performance are introduced into the generation process of residual interval, and the interval observer has better disturbance robustness and fault sensitivity. Simulation experiments verify that the scheme can effectively detect the actuator fault of the manipulator, and experiments are carried out on a 6‐axis manipulator. The experimental results show that when actuator faults occur at joints 2 and 3, the residual rapidly exceeds the threshold range, which proves the effectiveness of the fault detection scheme designed in this paper.
Remotely Temporal Scheduled Macrophage Phenotypic Transition Enables Optimized Immunomodulatory Bone Regeneration
Authors: Huang Donghua , Xu Kaicheng , Huang Xin , Lin Nong , Ye Yuxiao , Lin Suya , Zhang Jiamin , Shao Jiaqi , Chen Songfeng , Shi Mingmin , Zhou Xingzhi , Lin Peng , Xue Yucheng , Yu Chengcheng , Yu Xiaohua , Ye Zhaoming , Cheng Kui 
Published: August 2022

AbstractPrecise timing of macrophage polarization plays a pivotal role in immunomodulation of tissue regeneration, yet most studies mainly focus on M2 macrophages for their anti‐inflammatory and regenerative effects while the essential proinflammatory role of the M1 phenotype on the early inflammation stage is largely underestimated. Herein, a superparamagnetic hydrogel capable of timely controlling macrophage polarization is constructed by grafting superparamagnetic nanoparticles on collagen nanofibers. The magnetic responsive hydrogel network enables efficient polarization of encapsulated macrophage to the M2 phenotype through the podosome/Rho/ROCK mechanical pathway in response to static magnetic field (MF) as needed. Taking advantage of remote accessibility of magnetic field together with the superparamagnetic hydrogels, a temporal engineered M1 to M2 transition course preserving the essential role of M1 at the early stage of tissue healing, as well as enhancing the prohealing effect of M2 at the middle/late stages is established via delayed MF switch. Such precise timing of macrophage polarization matching the regenerative process of injured tissue eventually leads to optimized immunomodulatory bone healing in vivo. Overall, this study offers a remotely time‐scheduled approach for macrophage polarization, which enables precise manipulation of inflammation progression during tissue healing.