bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Gene Delivery: Synergy between Alkyl Chain Length and Lipoic Acid for PDMAEMA Hydrophobic Copolymers
Authors: Mapfumo Prosper P. , Reichel Liên S. , Hoeppener Stephanie , Traeger Anja 
Published: January 2024

AbstractIn the field of gene delivery, hydrophobic cationic copolymers hold great promise. They exhibit improved performance by effectively protecting genetic material from serum interactions while facilitating interactions with cellular membranes. However, managing cytotoxicity remains a significant challenge, prompting an investigation into suitable hydrophobic components. A particularly encouraging approach involves integrating nutrient components, like lipoic acid, which is known for its antioxidant properties and diverse cellular benefits such as cellular metabolism and growth. In this study, a copolymer library comprising 2‐(dimethylamino)ethyl methacrylate (DMAEMA) and lipoic acid methacrylate (LAMA), combined with either n‐butyl methacrylate (nBMA), ethyl methacrylate (EMA), or methyl methacrylate (MMA), is synthesized. This enables to probe the impact of lipoic acid incorporation while simultaneously exploring the influence of pendant acyclic alkyl chain length. The inclusion of lipoic acid results in a notable boost in transfection efficiency while maintaining low cytotoxicity. Interestingly, higher levels of transfection efficiency are achieved in the presence of nBMA, EMA, or MMA. However, a positive correlation between pendant acyclic alkyl chain length and cytotoxicity is observed. Consequently, P(DMAEMA‐co‐LAMA‐co‐MMA), emerges as a promising candidate. This is attributed to the optimal combination of low cytotoxic MMA and transfection‐boosting LAMA, highlighting the crucial synergy between LAMA and MMA.
In silico construction of a focused fragment library facilitating exploration of chemical space**
Authors: Han Weijie , Xu Xiaohe , Fan Qing , Yan Yingchao , Zhang YanMin , Chen Yadong , Liu Haichun 
Published: January 2024

AbstractFragment‐based drug design (FBDD) has emerged as a captivating subject in the realm of computer‐aided drug design, enabling the generation of novel molecules through the rearrangement of ring systems within known compounds. The construction of focused fragment library plays a pivotal role in FBDD, necessitating the compilation of all potential bioactive ring systems capable of interacting with a specific target. In our study, we propose a workflow for the development of a focused fragment library and combinatorial compound library. The fragment library comprises seed fragments and collected fragments. The extraction of seed fragments is guided by receptor information, serving as a prerequisite for establishing a focused libraries. Conversely, collected fragments are obtained using the feature graph method, which offers a simplified representation of fragments and strikes a balance between diversity and similarity when categorizing different fragments. The utilization of feature graph facilitates the rational partitioning of chemical space at fragment level, enabling the exploration of desired chemical space and enhancing the efficiency of screening compound library. Analysis demonstrates that our workflow enables the enumeration of a greater number of entirely new potential compounds, thereby aiding in the rational design of drugs.
Dietary Ferulic Acid Increases Endurance Capacity by Promoting Skeletal Muscle Oxidative Phenotype, Mitochondrial Function, and Antioxidant Capacity
Authors: Huang Tengteng , Li Huawei , Chen Xiaoling , Chen Daiwen , Yu Bing , He Jun , Luo Yuheng , Yan Hui , Zheng Ping , Yu Jie , Huang Zhiqing 
Published: January 2024

ScopeEndurance capacity is essential for endurance athletes’ achievement and individuals’ health. Nutritional supplements are a proven way to enhance endurance capacity. Previous studies have shown that ferulic acid (FA) enhances endurance capacity, but the underlying mechanism is unclear. The study is aimed to investigate the mechanism by which FA increases endurance capacity.Methods and resultsForty mice are divided into control and 0.5% FA‐supplemented groups, and an exhaustive swimming test demonstrates increased endurance capacity with FA supplementation. This study investigates the underlying mechanism for this effect of FA. Firstly, RT‐PCR and western blot analysis find that FA increases the transformation from fast to slow muscle fiber. Additionally, adenosine triphosphate concentration, metabolic enzyme activity, and mitochondrial DNA analysis find that FA increases mitochondrial biogenesis and activates nuclear factor erythroid 2‐related factor (NRF)1 signaling pathway in muscle. Besides, through antioxidant capacity analysis, this study finds that FA activates NRF2 signaling pathway and improves the antioxidant capacity in muscle. Moreover, inhibiting NRF2 eliminates FA's effect on muscle fiber transformation in C2C12 cells.ConclusionOur results suggest that FA increases endurance capacity by promoting skeletal muscle oxidative phenotype, mitochondrial function, and antioxidant capacity, which may be related to the NRF1 and NRF2 signaling pathways.
Prediction of proton stopping power ratios using dual‐energy CT basis material decomposition
Authors: Pettersson Erik , Thilander‐Klang Anne , Bäck Anna 
Published: January 2024

AbstractBackgroundProton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single‐energy computed tomography (SECT). Various studies have shown that multi‐energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age‐related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection‐based MECT systems for SPR prediction.PurposeTo present and evaluate a novel proton SPR prediction method based on MD images from dual‐energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.MethodsA theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non‐tissue materials, by minimizing the root‐mean‐square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD‐SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data‐fitting. The goodness of fit of the MD‐SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head‐ and an abdomen‐sized phantom setup, were acquired with a clinical projection‐based fast‐kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non‐tissue materials in the phantoms, as well as used for input to the MD‐SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image‐based consecutive scan DECT for the same phantom setups.ResultsThe predicted SPRs of the tissue surrogates were similar for MD‐SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non‐adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between −0.7% and −1.8%. The SPRs of the non‐tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD‐SPR images, compared to 6.8% for DirectSPR.ConclusionsThe MD‐SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non‐tissue materials.
Hyperpolarized 13C metabolic imaging of the human abdomen with spatiotemporal denoising
Authors: Nickles Tanner M. , Kim Yaewon , Lee Philip M. , Chen Hsin‐Yu , Ohliger Michael , Bok Robert A. , Wang Zhen J. , Larson Peder E. Z. , Vigneron Daniel B. , Gordon Jeremy W. 
Published: January 2024

AbstractPurposeImproving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13C MRI studies with a patch based global–local higher‐order singular value decomposition (GL‐HOVSD) spatiotemporal denoising approach.MethodsDenoising performance was first evaluated using the simulated [1‐13C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL‐HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1‐13C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients).ResultsThe parameterization of kglobal = 0.2 and klocal = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (conversion rate of pyruvate‐to‐metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground‐truth metabolic conversion rates when there is adequate SNR (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine‐fold gain in peak [1‐13C]pyruvate, [1‐13C]lactate, and [1‐13C]alanine apparent SNRAUC. The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA. After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5‐fold increase in the number of voxels reliably fit across abdominal FOVs for kPL and kPA quantification maps.ConclusionSpatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1‐13C]alanine and quantification of [1‐13C]pyruvate metabolism in large FOV HP 13C MRI studies of the human abdomen.
Pore size estimation in axon‐mimicking microfibers with diffusion‐relaxation MRI
Authors: Canales‐Rodríguez Erick J. , Pizzolato Marco , Zhou Feng‐Lei , Barakovic Muhamed , Thiran Jean‐Philippe , Jones Derek K. , Parker Geoffrey J. M. , Dyrby Tim B. 
Published: January 2024

AbstractPurposeThis study aims to evaluate two distinct approaches for fiber radius estimation using diffusion‐relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power‐law approach and a T2‐based pore size estimation technique.Theory and MethodsA general diffusion‐relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI‐visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images.ResultsBoth methods show a linear relationship between effective radii estimated from MRI data and ground‐truth radii distributions, although some discrepancies were observed. The spherical mean power‐law method overestimated fiber radii. Conversely, the T2‐based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material‐specific relaxation changes.ConclusionThe study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2‐based technique, unlike the spherical mean power‐law method, does not demand ultra‐high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.
Assessment of blood–brain barrier leakage and brain oxygenation in Connexin‐32 knockout mice with systemic neuroinflammation using pulse electron paramagnetic resonance imaging techniques
Authors: Epel Boris , Viswakarma Navin , Hameed Safa , Freidin Mona M. , Abrams Charles K. , Kotecha Mrignayani 
Published: January 2024

AbstractPurposeThe determination of blood–brain barrier (BBB) integrity and partial pressure of oxygen (pO2) in the brain is of substantial interest in several neurological applications. This study aimed to assess the feasibility of using trityl OX071‐based pulse electron paramagnetic resonance imaging (pEPRI) to provide a quantitative estimate of BBB integrity and pO2 maps in mouse brains as a function of neuroinflammatory disease progression.MethodsFive Connexin‐32 (Cx32)–knockout (KO) mice were injected with lipopolysaccharide to induce neuroinflammation for imaging. Three wild‐type mice were also used to optimize the imaging procedure and as control animals. An additional seven Cx32‐KO mice were used to establish the BBB leakage of trityl using the colorimetric assay. All pEPRI experiments were performed using a preclinical instrument, JIVA‐25 (25 mT/720 MHz), at times t = 0, 4, and 6 h following lipopolysaccharide injection. Two pEPRI imaging techniques were used: (a) single‐point imaging for obtaining spatial maps to outline the brain and calculate BBB leakage using the signal amplitude, and (b) inversion‐recovery electron spin echo for obtaining pO2 maps.ResultsA statistically significant change in BBB leakage was found using pEPRI with the progression of inflammation in Cx32 KO animals. However, the change in pO2 values with the progression of inflammation for these animals was not statistically significant.ConclusionsFor the first time, we show the ability of pEPRI to provide pO2 maps in mouse brains noninvasively, along with a quantitative assessment of BBB leakage. We expect this study to open new queries from the field to explore the pathology of many neurological diseases and provide a path to new treatments.
Accurate actual flip angle imaging (AFI) in the presence of fat
Authors: Samsonov Alexey A. , Yarnykh Vasily L. 
Published: January 2024

AbstractPurposeTo investigate the effect of incomplete fat spoiling on the accuracy of B1 mapping with actual flip angle imaging (AFI) and to propose a method to minimize the errors using the chemical shift properties of fat.Theory and MethodsDiffusion‐based dephasing is the main spoiling mechanism exploited in AFI. However, a very low diffusion in fat may make the spoiling insufficient, leading to ghosts in the B1 maps. As the errors retain the chemical‐shift signature of fat, their impact can be minimized using chemical‐shift‐based fat signal removal from AFI acquisition modified to include multi‐echo readout. The source of the errors and the proposed correction were studied in simulations and phantom and in‐vivo imaging experiments.ResultsOur results support that AFI artifacts are caused by the incomplete fat spoiling present in clinically attractive short TR acquisition regimes. The correction eliminated the ghosting and significantly improved the B1 mapping accuracy as well as the accuracy of R1 mapping performed with AFI‐derived B1 maps.ConclusionsThe incomplete fat signal spoiling may be a source of AFI B1 mapping errors, especially in subjects with high fat content. Achieving complete fat spoiling requires longer TR, which is undesirable in clinical applications. The proposed approach based on fat signal removal can reduce errors without significant prolongation of the AFI pulse sequence. We propose that, when attaining complete fat spoiling is not feasible, AFI mapping should be performed in a multi‐echo regime with appropriate fat separation or suppression to minimize these errors.
Normalized Newton method to solve generalized tensor eigenvalue problems
Authors: Pakmanesh Mehri , Afshin Hamidreza , Hajarian Masoud 
Published: January 2024

AbstractThe problem of generalized tensor eigenvalue is the focus of this paper. To solve the problem, we suggest using the normalized Newton generalized eigenproblem approach (NNGEM). Since the rate of convergence of the spectral gradient projection method (SGP), the generalized eigenproblem adaptive power (GEAP), and other approaches is only linear, they are significantly improved by our proposed method, which is demonstrated to be locally and cubically convergent. Additionally, the modified normalized Newton method (MNNM), which converges to symmetric tensors Z‐eigenpairs under the same ‐Newton stability requirement, is extended by the NNGEM technique. Using a Gröbner basis, a polynomial system solver (NSolve) generates all of the real eigenvalues for us. To illustrate the efficacy of our methodology, we present a few numerical findings.
Yoga as a non‐pharmacologic therapy to reduce dinutuximab‐induced pain in patients with neuroblastoma
Authors: Parisio Katie N. , Kulp Tonia , Heil Maureen , Li Yimei , Dalton Kristen , McGrath Margaret , Carlowicz Cecilia , Donnelly Meghan , Bagatell Rochelle , Jubelirer Tracey 
Published: January 2024

AbstractBackgroundAnti‐GD2 antibodies are key components of treatment for high‐risk neuroblastoma; however, they cause neuropathic pain. Yoga therapy may help reduce pain and distress associated with anti‐GD2 therapy.ProcedureChildren 3 years of age or older with neuroblastoma participated in individualized yoga therapy while receiving the anti‐GD2 antibody dinutuximab (DIN). Yoga therapy was deemed feasible if patients participated during 60% or more of DIN admissions. Patients and caregivers assessed pain/distress before and after yoga therapy with a distress thermometer (DT) and Wong‐Baker FACES pain rating scale and completed questionnaires regarding satisfaction with yoga therapy. Therapy was deemed efficacious if there was a ≥1 point pain score change and reduction in distress after yoga.ResultsEighteen patients were enrolled; 52 encounters (admissions for DIN) were evaluable. Ten of 18 were female, three of 18 were Hispanic, and 10/18 were White. Median age at enrollment was 5.5 years (range: 3–11). Yoga therapy was feasible in 39/52 (75%) encounters. Significant reductions in caregiver‐reported pain and distress and reductions in patient‐reported pain and distress after yoga therapy were reported. Twelve of 18 caregivers completed questionnaires: seven agreed/strongly agreed that yoga was valuable, and nine agreed/strongly agreed to continued participation in yoga. Thirty‐four of 36 clinicians reported that they would recommend yoga therapy for other patients receiving DIN.ConclusionsYoga therapy was feasible during DIN therapy and may be effective in reducing DIN‐associated pain and distress. Future studies are needed to evaluate changes in opioid usage with the addition of yoga therapy during anti‐GD2 antibody therapy.
The relationship between emotional interaction and learning engagement in online collaborative learning: Moderated mediating effect
Authors: Wang Wei , Wang Xiaoying , Li Shanshan , Ma Tianshu , Poni Liu M. N. , Sun Hongzhi 
Published: January 2024

AbstractThe prevalence of collaborative learning in online virtual environments is on the rise. It is vital to investigate the effect of emotional interaction on the learning engagement of students. The university students who participated in 16 h of online collaborative learning responded to an anonymous survey. The instruments included Collaborative Learning Emotional Interaction Scale, Loneliness Scale, Positive and Negative Rumination Scale, and Learning Engagement Scale. The mediating and moderating roles of variables were tested. Both positive and negative emotional interactions in online collaborative learning positively predicted learning engagement. Positive emotional interaction can inversely predict loneliness, while negative emotional interaction has a positive effect on loneliness. Loneliness inversely predicts learning engagement. In the low level of positive rumination, loneliness has a significant inhibitory effect on learning engagement, and the effect is much greater than that in the high level of positive rumination. In online collaborative learning, loneliness mediates the effect of learners' emotional interaction on learning engagement. The level of positive rumination moderated the connection between loneliness and learning engagement, the second part of the mediation model. We can begin by increasing learners' positive rumination and reducing the detrimental impact of negative emotional interaction and isolation on learning engagement in online collaborative learning.
Reading motivation and learning strategies among Chinese EFL learners
Authors: Li Hong , Wang Chuang , Gan Zhengdong , Hoi Cathy Ka Weng 
Published: January 2024

AbstractGiven the preeminent role of students' reading motivation in their academic success in reading, which determines the quality and intensity of cognition and behaviors, it is important to investigate the predicative effects of different aspects of reading motivation on students' learning strategies particularly in a foreign language learning context where students usually learn the target language mainly through reading. This study investigated reading motivation and learning strategies as well as the relationships between them among junior and senior Chinese secondary school students. Data were gathered from 405 English as a foreign language (EFL) students from a junior and a senior secondary school in southern China who completed two questionnaires used to measure their reading motivation and learning strategies. Confirmatory factor analyses results supported the fit of the two questionnaires in assessing students' motivational and learning strategy processes in an EFL context. The study found that while the students were largely motivated to engage in English reading extrinsically, these students were also found to adopt control and elaboration strategies frequently in their learning, which somewhat contradicts the stereotypical view of Chinese students as rote learners in the literature. The study revealed significant differences in reading motivation and learning strategies between junior and senior secondary students, which can be interpreted in terms of a competitive and pragmatic learning culture where examinations play an essential role in determining student admission into higher education. Findings of this study contribute to the theoretical and pedagogical discussions on reading motivation and learning strategies in learning EFL.