bluuebunny/crossref_metadata_2025_split huggingface dataset:
Individualised compared to off‐the‐shelf total knee arthroplasty results in lower and less variable patellar tilt
Authors: Beel Wouter , Sappey‐Marinier Elliot , Latifi Roshan ,   ReSurg, Aït‐Si‐Selmi Tarik , Bonnin Michel P. 
Published: June 2024

AbstractPurposeThe purpose of this study was to compare postoperative patellar tilt at 4 months follow‐up in a consecutive series of randomised patients that received individualised or off‐the‐shelf (OTS) primary total knee arthroplasty (TKA). The hypothesis was that patellar tilt would be lower and less variable in patients who received individualised TKA compared to patients who received OTS TKA.MethodsA consecutive series of 385 patients randomised (1:1) to receive either OTS TKA or individualised TKA were analysed. Pre‐ and postoperative radiographs at 4 months were obtained of weight‐bearing long leg, anterior–posterior and lateral knee views and a skyline view at 30° of flexion. Postoperative patellar tilt was measured between the anterior femoral line and patellar resection surface (β) and the anterior femoral line and mediolateral patellar axis (σ). Postoperative patellar tilt (absolute value) was compared between the individualised and OTS TKA groups based on preoperative phenotypes of their femoral mechanical angle, tibial mechanical angle and hip–knee–ankle angle. Variability in postoperative patellar tilt was compared using the 95% confidence intervals (CIs).ResultsComparisons of baseline patient characteristics revealed no difference between the individualised and OTS TKA groups. Comparison of absolute postoperative patellar tilt revealed significant differences between individualised and OTS TKA (|β|, 1.0° ± 1.0° and 2.5° ± 2.2°, respectively, p < 0.001; |σ|, 1.7° ± 1.6° and 2.8° ± 2.3°, respectively, p < 0.001). The 95% CI of postoperative patellar tilt (|β|) was narrower in patients that received individualised compared to OTS TKA (0.0° to 3.8° and 0.1° to 8.3°, respectively), irrespective of their preoperative phenotype.ConclusionPatients who underwent individualised TKA had lower and less variable postoperative patellar tilt than those with OTS TKA, irrespective of preoperative phenotype. Individualised TKA allows the decoupling of the tibiofemoral and patellofemoral joints, replicating anatomical trochlear orientation and improving patellar tilt, which could facilitate better clinical outcomes.Clinical Trial RegistrationThis study constitutes a part of a larger registered randomised controlled trial comparing patient satisfaction following OTS versus individualised TKA (NCT04460989).Level of EvidenceLevel II.
Long‐term preservation of lean mass and sustained loss of fat mass after completion of an intensive lifestyle intervention in older adults with obesity and type 2 diabetes
Authors: Memelink Robert G , Hijlkema Aveline , Valentin Bas , Streppel Martinet T , Pasman Wilrike J , Wopereis Suzan , de Vogel‐van den Bosch Johan , Tieland Michael , Schoufour Josje D , Bautmans Ivan , Weijs Peter JM 
Published: June 2024

AbstractIntroductionLifestyle interventions combining caloric restriction with resistance exercise have the potential to preserve lean mass during weight loss. Additional protein intake can further improve lean mass. However, it is unclear whether these effects are sustained after completion of the intervention. This study aimed to evaluate the long‐term effect of a 3‐month lifestyle intervention, with or without supplementation of a protein drink, to preserve lean mass in older adults with obesity and type 2 diabetes at 6 months post‐intervention.MethodsAdults (n = 123) aged ≥55 years with obesity and type 2 diabetes were enrolled in a 3‐month intensive lifestyle intervention including a hypocaloric diet, resistance exercise and high‐intensity interval training. Participants were randomized to either receive a leucine and vitamin D‐enriched protein drink or an isocaloric control drink. The 3‐month intervention was followed by a 6‐month phase without intervention. At baseline, 3 and 9 months (follow‐up) body composition, physical functioning, physical activity and quality of life were assessed. Statistical analyses were performed using linear mixed models.ResultsBody weight loss was largely sustained at follow‐up (−2.1 kg compared to baseline, 95% CI [−2.8, −1.5]) and comprised a sustained loss of fat mass (−2.6 kg, 95% CI [−3.2, −2.0]) with a simultaneous gain of lean mass (+0.7 kg, 95% CI [+0.2, +1.2]). Improvements in 400 m walk speed (+0.05 m/s, 95% CI [+0.03, +0.08]) and chair stand test time (−1.5 s, 95% CI [−1.9, −1.1]) were sustained at follow‐up. There were no differences in these changes between the protein supplementation group and the control group at follow‐up.ConclusionsOlder adults with obesity and type 2 diabetes preserved their lean mass, their loss of fat mass and their improvements in physical functioning at 6 months post‐intervention. Protein supplementation during intervention did not affect outcomes at follow‐up.
Highly Efficient Two‐Photon Photodynamic Therapy Using Light‐Sheet Excitation
Authors: Pang Wen , Wang Chen , Wu Wenbo , Wei Xunbin , Gu Bobo 
Published: June 2024

AbstractTwo‐photon photodynamic therapy (TP‐PDT), which utilizes near‐infrared light to excite photosensitizer via two‐photon excitation (TPE), is a promising modality in the treatment of deeply seated tumors or thick tumors. However, the TPE domain is much smaller than the tumor volume, significantly limiting the therapeutical outcomes of TP‐PDT. Here, a light‐sheet TPE system is designed and constructed using a cylindrical lens for highly efficient TP‐PDT. The light‐sheet TPE performance is characterized and optimized via theoretical analysis and experimental studies in solution, phantom, and tumor. The optimized excitation system can reach a large TPE domain of 2.6 × 2.7 × 0.09 mm in the tumor, which is not achievable using conventional TPE methods, enabling TPE and subsequently generated reactive oxygen species to cover the whole tumor under line‐scanning. Outstanding TP‐PDT therapeutic performance of 70% tumor growth inhibition rate is achieved under line‐scanned light‐sheet TPE, making the proposed light‐sheet excited TP‐PDT a potential therapeutic tool for future translational research.
Trends in predicted age at maturity of Sablefish from 22 years of surveys
Authors: Rodgveller C. J. , Echave K. B. 
Published: June 2024

Abstract

Objective
Our aim was to predict the maturity (will spawn or immature) of Sablefish Anoplopoma fimbria in Alaska for past years during a period when macroscopic data are not of utility and histological observations are not available.

Methods
In a previous study, female maturity was determined using histology and a model was developed that predicted maturity using maternal length, age, and relative condition. We used this published model to predict the maturity of individual Sablefish collected annually in the same area on the same dates. The maturity predictions were used to create predicted time series of maturity at age for surveys conducted over 22 years.

Result
A k-means cluster analysis of annual maturity parameters revealed that data should be split into two clusters. These groups were chronologically sequential (1998–2010 and 2011–2019), with two exceptions: 2015 and 2017 were assigned to the early time period. We created two chronological time blocks by incorporating the two outlier years into the late period post hoc, as we are not aware of mechanisms that may have caused these two outliers, and it is important for stock assessment to capture the signal and not the noise. Sablefish in the later period were predicted to mature later than fish in the earlier period; age at 50% maturity was 5.5 years in the early period and 6.8 years in the later period, and the slope was shallower in the later period.

Conclusion
There are often gaps in reliable maturity data. This case study illustrates that limited histological data sets can be used to predict maturity in years without ovary samples and illustrates how these data can be grouped based on similarities and chronology for use in stock assessment. We recommend more histological studies in the future to test assumptions of the predictive model, and we recommend evaluations of other factors, such as environmental time series, that may be drivers of annual maturity.
Virtual screening of natural products to enhance melanogenosis
Authors: Bournez Colin , Gally José‐Manuel , Aci‐Sèche Samia , Bernard Philippe , Bonnet Pascal 
Published: June 2024

AbstractNatural products have long been an important source of inspiration for medicinal chemistry and drug discovery. In the cosmetic field, they remain the major elements of the composition and serve as marketing asset. Recent research showed the implication of salt‐inducible kinases on the melanin production in skin via MITF regulation. Finding new potent modulators on such target could open the way to several cosmetic applications to attenuate visible signs of photoaging and improve the tan without sun. Since virtual screening can be a powerful tool for detecting hit compounds in the early stages of a drug discovery process, we applied this method on salt‐inducible kinase 2 to discover potential interesting compounds. Here, we present the different steps from the construction of a database of natural products, to the validation of a docking protocol and the results of the virtual screening. Hits from the screening were tested in vitro to confirm their efficiency and results are discussed.
Vitamin D and Atherosclerosis: Unraveling the Impact on Macrophage Function
Authors: Wang Dongxia , Sun Zhen , Yin Yajuan , Xiang Jingyi , Wei Yuzhe , Ma Yuxia , Wang Le , Liu Gang 
Published: June 2024

AbstractVitamin D plays a crucial role in preventing atherosclerosis and in the regulation of macrophage function. This review aims to provide a comprehensive summary of the clinical evidence regarding the impact of vitamin D on atherosclerotic cardiovascular disease, atherosclerotic cerebrovascular disease, peripheral arterial disease, and associated risk factors. Additionally, it explores the mechanistic studies investigating the influence of vitamin D on macrophage function in atherosclerosis. Numerous findings indicate that vitamin D inhibits monocyte or macrophage recruitment, macrophage cholesterol uptake, and esterification. Moreover, it induces autophagy of lipid droplets in macrophages, promotes cholesterol efflux from macrophages, and regulates macrophage polarization. This review particularly focuses on analyzing the molecular mechanisms and signaling pathways through which vitamin D modulates macrophage function in atherosclerosis. It claims that vitamin D has a direct inhibitory effect on the formation, adhesion, and migration of lipid‐loaded monocytes, thus exerting anti‐atherosclerotic effects. Therefore, this review emphasizes the crucial role of vitamin D in regulating macrophage function and preventing the development of atherosclerosis.
Image‐domain material decomposition for dual‐energy CT using unsupervised learning with data‐fidelity loss
Authors: Peng Junbo , Chang Chih‐Wei , Xie Huiqiao , Qiu Richard L. J. , Roper Justin , Wang Tonghe , Ghavidel Beth , Tang Xiangyang , Yang Xiaofeng 
Published: June 2024

AbstractBackgroundDual‐energy computed tomography (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise amplification, leading to severely degraded image signal‐to‐noise ratios (SNRs). While existing iterative algorithms perform noise suppression using different image priors, these heuristic image priors cannot accurately represent the features of the target image manifold. Although deep learning‐based decomposition methods have been reported, these methods are in the supervised‐learning framework requiring paired data for training, which is not readily available in clinical settings.PurposeThis work aims to develop an unsupervised‐learning framework with data‐measurement consistency for image‐domain material decomposition in DECT.MethodsThe proposed framework combines iterative decomposition and deep learning‐based image prior in a generative adversarial network (GAN) architecture. In the generator module, a data‐fidelity loss is introduced to enforce the measurement consistency in material decomposition. In the discriminator module, the discriminator is trained to differentiate the low‐noise material‐specific images from the high‐noise images. In this scheme, paired images of DECT and ground‐truth material‐specific images are not required for the model training. Once trained, the generator can perform image‐domain material decomposition with noise suppression in a single step.ResultsIn the simulation studies of head and lung digital phantoms, the proposed method reduced the standard deviation (SD) in decomposed images by 97% and 91% from the values in direct inversion results. It also generated decomposed images with structural similarity index measures (SSIMs) greater than 0.95 against the ground truth. In the clinical head and lung patient studies, the proposed method suppressed the SD by 95% and 93% compared to the decomposed images of matrix inversion.ConclusionsSince the invention of DECT, noise amplification during material decomposition has been one of the biggest challenges, impeding its quantitative use in clinical practice. The proposed method performs accurate material decomposition with efficient noise suppression. Furthermore, the proposed method is within an unsupervised‐learning framework, which does not require paired data for model training and resolves the issue of lack of ground‐truth data in clinical scenarios.
Calculation of intravoxel incoherent motion parameter maps using a kernelized total difference‐based method
Authors: Huang Hsuan‐Ming 
Published: June 2024

AbstractQuantitative analysis of diffusion‐weighted magnetic resonance imaging (DW‐MRI) has been explored for many clinical applications since its development. In particular, the intravoxel incoherent motion (IVIM) model for DW‐MRI has been commonly utilized in various organs. However, because of the presence of excessive noise, the IVIM parameter maps obtained from pixel‐wise fitting are often unreliable. In this study, we propose a kernelized total difference‐based curve‐fitting method to estimate the IVIM parameters. Simulated DW‐MRI data at five signal‐to‐noise ratios (i.e., 10, 20, 30, 50, and 100) and real abdominal DW‐MRI data acquired on a 1.5‐T MRI scanner with nine b‐values (i.e., 0, 10, 25, 50, 100, 200, 300, 400, and 500 s/mm2) and six diffusion‐encoding gradient directions were used to evaluate the performance of the proposed method. The results were compared with those obtained by three existing methods: trust‐region reflective (TRR) algorithm, Bayesian probability (BP), and deep neural network (DNN). Our simulation results showed that the proposed method outperformed the other three comparing methods in terms of root‐mean‐square error. Moreover, the proposed method could preserve small details in the estimated IVIM parameter maps. The experimental results showed that, compared with the TRR method, the proposed method as well as the BP (and DNN) method could reduce the overestimation of the pseudodiffusion coefficient and improve the quality of IVIM parameter maps. For all studied abdominal organs except the pancreas, both the proposed method and the BP method could provide IVIM parameter estimates close to the reference values; the former had higher precision. The kernelized total difference‐based curve‐fitting method has the potential to improve the reliability of IVIM parametric imaging.
Matrix‐based implementation and GPU acceleration of hybrid FEM and peridynamic model for hydro‐mechanical coupled problems
Authors: Ni Tao , Zhang Jin , Zaccariotto Mirco , Galvanetto Ugo , Schrefler Bernhard A. 
Published: June 2024

AbstractThe hybrid finite element‐peridynamic (FEM‐PD) models have been evidenced for their exceptional ability to address hydro‐mechanical coupled problems involving cracks. Nevertheless, the non‐local characteristics of the PD equations and the required inversion operations when solving fluid equations result in prohibitively high computational costs. In this paper, a fast explicit solution scheme for FEM‐PD models based on matrix operation is introduced, where the graphics processing units (GPUs) are used to accelerate the computation. An in‐house software is developed in MATLAB in both CPU and GPU versions. We first solve a problem related to pore pressure distribution in a single crack, demonstrating the accuracy of the proposed method by a comparison of FEM‐PD solutions with those of PD‐only models and analytical solutions. Subsequently, several examples are solved, including a one‐dimensional dynamic consolidation problem and the fluid‐driven hydraulic fracture propagation problems in both 2D and 3D cases, to comprehensively validate the effectiveness of the proposed methods in simulating deformation and fracture in saturated porous media under the influence of hydro‐mechanical coupling. In the presented numerical results, some typical strong dynamic phenomena, such as stepwise crack advancement, crack branching, and pressure oscillations, are observed. In addition, we compare the wall times of all the cases executed on both the GPU and CPU, highlighting the substantial acceleration performance of the GPU, particularly when tackling problems with a significant computational workload.
Enhancing mechanical properties of natural waste‐based composites for automobile and plastic industry
Authors: Motaleb K. Z. M. Abdul , Repon Md. Reazuddin , Pranta Arnob Dhar , Milašius Rimvydas 
Published: June 2024

AbstractNatural fiber composites are a renewable and environmentally friendly alternative to conventional synthetic materials that combine the biodegradability and essential durability of natural fibers with adaptability. Improved adhesion between fibers and matrix can be accomplished by comparing surface treatments applied to sugarcane, water hyacinth, and banana plant wastes. This will allow us to produce composite materials that are more durable and sustainable. To study the mechanical and morphological characteristics of the composites, two surface treatments were applied: gamma radiation at a dose of 1, 2, 3, 4 and 5 kGy and alkali treatment at a concentration of 5, 10, and 15%. The study revealed that with the increasing treatment of alkali solution, improvements in the composite's mechanical characteristics whereas gamma irradiation treatment enhanced the mechanical properties to a certain extent (2 kGy) after that the mechanical traits dwindled significantly. SEM, XRD, and FTIR analysis of the developed composite samples also revealed the reasons for the improvements in mechanical properties after alkali and gamma radiation treatments. As an ecofriendly and lightweight substitute for conventional materials, bio epoxy composites reinforced with natural fibers can be used for car interior panels, eco‐friendly furniture and as a replacement for any plasticware offering eco‐sustainability for contemporary living space.Highlights
Natural fiber composites offer a renewable and eco‐friendly alternative to synthetic materials, combining biodegradability with durability.
Surface treatments like gamma radiation and alkali treatment enhance composite's mechanical properties.
Higher concentrations of alkali treatment improve mechanical characteristics, while gamma irradiation peaks at 2 kGy.
Surface treatments offer promising avenues for advancing environmentally friendly materials, contributing to sustainable innovations in material science.
Combined antibacterial and antifouling properties of polyethersulfone mixed matrix membranes with zwitterionic graphene oxide nanostructures
Authors: Castellanos Espinoza R. , Huhn Ibarra M. J. , Montes Luna A. J. , Aguilar‐Vega Manuel , Hernández Orozco M. M. , Luna Bárcenas Gabriel , Baldenegro Pérez L. A. , Guerra Balcázar Minerva , España Sánchez Beatriz Liliana 
Published: June 2024

AbstractThe impact of zwitterionic graphene oxide (GO‐Arg) nanostructures into polyethersulfone (PES) membranes was studied, aiming to perform mixed matrix membranes (MMMs) with combined antibacterial and antifouling properties. For this purpose, 0.25, 0.50, and 1.0 wt% of GO‐Arg were incorporated through the phase inversion method. The chemical composition reveals that the electrostatic interactions of PES, polyvinylpyrrolidone, and GO‐Arg occur by enhancing the CH/NH vibrations associated with the intrinsic MMMs and their combined antibacterial and antifouling performance. Well‐defined finger‐like morphology was observed, performing the pore distribution and the finger‐cavity inclination induced by the electrostatic charge of GO‐Arg. As a result, GO‐Arg MMM's hydrophobic properties decreased from 77.8° to 52.3°, inducing a partially hydrophilic surface and improved water flux. The isoelectric point of nanostructured membranes slightly changes by the charge modulation produced by zwitterionic GO‐Arg. The antibacterial activity against Gram (−) Escherichia coli was improved, closing the complete bacterial inhibition after 24 h. As a result, antifouling performance was improved, avoiding bacterial adhesion into the membrane surface and the possibility of promoting biofilm formation. Our results demonstrate that zwitterionic nanomaterials in MMMs perform the multifunctional capacity of materials, emerging as an effective alternative with potential application in wastewater treatment.Highlights
The incorporation of zwitterionic GO‐Arg improves the mechanical properties of MMMs.
GO‐Arg‐enhanced well‐defined porous finger‐like morphology in MMMs.
GO‐Arg improves the antibacterial/antifouling performance of PES‐based MMMs.
Effect of graphene nanoplatelets and nano zinc oxide on gas barrier and antibacterial properties of thermoplastic nanocomposites
Authors: Ghosh Suman Kumar , Ganguly Soumya Sarathi , Paul Sangit , Ghosh Trisita , Das Amit Kumar , Das Narayan Ch. 
Published: June 2024

AbstractGraphene‐loaded thermoplastic nanocomposite films must be evaluated for antibacterial activity, mechanical, and barrier properties before being utilized as food packaging. Herein, economically feasible linear low‐density polyethylene (LLDPE)‐based flexible packaging materials were developed via the melt compounding technique at 170°C temperature by taking advantage of both graphene nanoplatelets (GNP) and nano zinc oxide (ZnO) fillers. Morphological studies reveal that in composites loaded with GNP/ZnO hybrid fillers, ZnO nanoparticles form a network‐like structure throughout the polymer matrix. Simultaneously, GNPs are uniformly dispersed. The inclusion of hybrid nanofiller considerably reduces both the oxygen transmission rate and the water vapor transmission rate (WVTR) in LLDPE nanocomposites. A maximum decrease of 36% and 67%, respectively, in both oxygen transmission rate and WVTR is observed for 3 wt% of hybrid filler loading in a thermoplastic matrix containing 1 wt% of nano ZnO. The antibacterial efficacy of the derived nanocomposite films is obvious against gram‐positive (Bacillus subtilis) and gram‐negative (Escherichia coli) bacterial strains. These nanocomposite films have the potential to be successfully utilized as flexible packaging materials owing to their improved thermal, barrier, and antibacterial effectiveness.Highlights
GNP/ZnO was used as a hybrid reinforcing filler in the LLDPE matrix.
ZnO nanoparticles establish a network‐like morphology.
LLDPE nanocomposite films exhibited excellent antibacterial activity.
Oxygen and water vapor barrier properties were significantly improved.
The thermoplastic composite films could be used as food packaging materials.