bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of percolation threshold of spray‐dried cellulose nanocrystals in homopolymer polypropylene composites
Authors: Wang Xueqi , Wang Pixiang , Liu Shaoyang , Zhan Ke , Via Brian , Gallagher Tom , Smidt Mathew , Gardner Douglas J. , Elder Thomas , Peng Yucheng 
Published: April 2024

AbstractUnderstanding the percolation threshold is essential for determining the performance of particle‐reinforced polymer composites. Spray‐dried cellulose nanocrystals (SDCNC) of micrometer size reinforced homopolymer polypropylene (HPP) composites at 20, 30, 40, and 50 wt.% were prepared to investigate the percolation threshold of SDCNC particles in HPP. The effect of a compatibilizer (maleic anhydride polypropylene (MAPP)) at 3, 5, and 7 wt.%, on the SDCNC percolation networks and composites performance were also studied. The results indicated that SDCNC particle percolation networks in HPP were established between 30 and40 wt.%. For composites without MAPP, the impact strength significantly increased by up to 23% below the percolation threshold and declined beyond it. The peak crystallization temperature of HPP was steadily increased until 30 wt.% SDCNC particles were added due to the SDCNC saturated nucleation function at the threshold. Introducing MAPP significantly improved tensile strength (58%), tensile strain (61%), flexural strength (45%), and impact strength (91%) compared with the corresponding composites without MAPP, attributed to the enhanced interfacial adhesion between the SDCNC particles and HPP. Water absorption results indicated that adding MAPP changed the SDCNC particle distribution networks within the matrix above the percolation threshold but did not change it below the threshold.
Design and synthesis of phenoxy methyl‐oxadiazole compounds against Alzheimer's disease
Authors: Evren Asaf E. , Nuha Demokrat , Özkan Begüm N. S. , Kahraman Çiğdem , Gönülalan Ekrem M. , Yurttaş Leyla 
Published: April 2024

AbstractThis study examines the synthesis and evaluation of 11 newly developed compounds as potential anti‐Alzheimer's agents that occur via cholinesterase and β‐secretase inhibition. The compounds were tested for their inhibitory activity against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) using the modified Ellman method. The results showed that several compounds exhibited significant inhibition of AChE, particularly compounds 6d, 7a, and 7e, which demonstrated high inhibitory activity at lower concentrations, with IC50 values of 0.120, 0.039, and 0.063 µM, respectively. However, the compounds showed limited effectiveness against BChE, with only a few compounds exhibiting moderate inhibition. Compound 7e showed an inhibitory effect against BACE‐1 close to that of the standard drug. Structural analysis revealed that the compounds with substituted benzothiazole and thiazole moieties exhibited the most promising inhibitory activity. This study provides valuable insights into the potential of these synthesized derivatives as a treatment against Alzheimer's disease. Moreover, the structure, stability, and properties of the active compounds were further investigated using density functional theory calculations. As a final note, the utilization of molecular docking and molecular dynamics simulation studies allowed us to elucidate the action mechanism of the active compounds and gain insights into the structure–activity relationship against AChE and β‐secretase proteins. These computational techniques provide valuable information on the binding modes, interactions with target enzymes, dynamic behavior, and conformational changes of the compounds, enabling a comprehensive understanding of their biological activity.
Anatomical variation is the norm: A novel curriculum framework
Authors: Kimmorley Annabelle L. , Reynolds Mikaela S. , Gregory Laura S. 
Published: April 2024

AbstractAnatomical variation is an inherent part of every health curriculum, due in large to the negative clinical consequences that can ensue if anatomical variation is not thoroughly understood. However, current literature fails to describe any structured whole‐of‐course pedagogy for the teaching of anatomical variation in higher education. This study therefore aimed to (i) propose a whole‐of‐course curriculum framework to guide academic development and implementation of anatomical variation resources and assessment; and (ii) assess the depth of anatomical variation knowledge in a multiyear undergraduate health‐science cohort (n = 152) at the Queensland University of Technology. Current anatomical variation pedagogy, and subsequently the need for the curriculum framework, were explored using a scoping review protocol. As part of this study, anatomical variation was novelly defined as macroscopic differences in morphology (shape and size), topography (location), developmental timing, or frequency (number) of an anatomical structure between individuals that form during embryological or subadult development and result in no substantive, observable interruption to physiological function. The framework incorporated three themes of anatomical variation learning outcomes: description of anatomical variation, theories of the professional implications of variation, and investigation of variant formation. These themes were strongly aligned with the concepts recommended for teaching identified through the scoping review. Significant deficits in anatomical variation student knowledge were identified, with the third‐year cohort recording a mean total score of only 54.6%. A strong recommendation to implement the anatomical variation curriculum framework in all medical and health‐science curricula is made to intentionally develop student understanding of anatomical variation and improve future clinical practice.
Parameterization to fault detection filtering for Itô stochastic T‐S fuzzy systems
Authors: Han Yingying , Zhou Shaosheng 
Published: April 2024

AbstractThis article focuses on the fault detection filtering problem for Itô stochastic Takagi–Sugeno (T‐S) fuzzy systems. In terms of line integral Lyapunov function, a sufficient condition of exponential stability in mean square and extended dissipativity for the systems under consideration is established which has less conservatism than the one based on quadratic Lyapunov function. The obtained sufficient condition is nonlinear, which makes the synthesis of fault detection filter being difficult and challenging. By choosing general matrix variables and constructing the appropriate orthogonal complement matrices, the nonlinear sufficient condition can be converted into linear one ingeniously via utilizing Finsler's lemma twice. Thus, the fault detection filter can be developed by virtue of parameterization. It should be pointed out that our filter determined by the parameterization approach includes the one obtained by the equivalent transformation method as a special case. Finally, we demonstrate the feasibility and superiority of our proposed approach through three numerical examples.
Design of finite‐time convergent functional observer for descriptor systems: Application to fault estimation
Authors: Ríos‐Ruiz Carlos , Osorio Gordillo Gloria Lilia , Darouach Mohamed , Souley Ali Harouna , Astorga‐Zaragoza Carlos Manuel 
Published: April 2024

AbstractIn this paper, a finite‐time functional observer design for linear time‐invariant descriptor systems is presented. A generalized observer based on additional degrees of freedom is developed. This observer can be considered of a general structure since the existing proportional observer (PO) and proportional‐integral observer (PIO) constitute its particular cases. The main contribution is to generate a finite‐time convergent functional observer for descriptor systems by combining two generalized functional observers. The obtained results are applied to the simultaneous state, sensor, and actuator faults estimation. A numerical example is given to illustrate the approach. The obtained results show that the observer is robust in presence of uncertainties, compared to its particular cases.
Integration of just‐in‐time learning with variational autoencoder for cell culture process monitoring based on Raman spectroscopy
Authors: Rashedi Mohammad , Khodabandehlou Hamid , Wang Tony , Demers Matthew , Tulsyan Aditya , Garvin Christopher , Undey Cenk 
Published: April 2024

AbstractProtein production in the biopharmaceutical industry necessitates the utilization of multiple analytical techniques and control methodologies to ensure both safety and consistency. To facilitate real‐time monitoring and control of cell culture processes, Raman spectroscopy has emerged as a versatile analytical technology. This technique, categorized as a Process Analytical Technology, employs chemometric models to establish correlations between Raman signals and key variables of interest. One notable approach for achieving real‐time monitoring is through the application of just‐in‐time learning (JITL), an industrial soft sensor modeling technique that utilizes Raman signals to estimate process variables promptly. The conventional Raman‐based JITL method relies on the K‐nearest neighbor (KNN) algorithm with Euclidean distance as the similarity measure. However, it falls short of addressing the impact of data uncertainties. To rectify this limitation, this study endeavors to integrate JITL with a variational autoencoder (VAE). This integration aims to extract dominant Raman features in a nonlinear fashion, which are expressed as multivariate Gaussian distributions. Three experimental runs using different cell lines were chosen to compare the performance of the proposed algorithm with commonly utilized methods in the literature. The findings indicate that the VAE–JITL approach consistently outperforms partial least squares, convolutional neural network, and JITL with KNN similarity measure in accurately predicting key process variables.
Improved sieving coefficient in perfusion cell culture with reduced effective filtration length of hollow fibers
Authors: Vu Jimmy , Gadberry J. Alex , Coffman Jon , Lee Ken 
Published: April 2024

AbstractThe hollow fiber filter is the primary cell‐retention device used in high‐density perfusion cell culture and often used in an alternating tangential flow (ATF) configuration. The limited commercially available diaphragm pumps for ATF prevent utilization of vertical space when scaling beyond 500 L. Stacking hollow fiber filters coupled with viscous cell culture imposes vacuum pressure exceeding facility capabilities. Additionally, the longer filter assembly increases the hold‐up volume and exceeds the diaphragm pump's fluid exchange capacity. The conventional tangential flow filtration (TFF) configuration circumvents this issue by exchanging culture from the bioreactor and cell‐retention device in a unidirectional recirculation loop; however, the increased filter length when scaled up exacerbates the TFF's inherent issue with product retention from Starling flow. Stacking commercially available 20 cm TFF filters to make up the similar single‐module length TFF used for the platform 3 and 50 L perfusion process at 41.5 and 65 cm, respectively, attempts to reduce fouling caused by Starling flow. The permeate of a single‐module filter is partitioned into short independent segments through serially stacked filters, each harvested separately. By partitioning the permeate, the sieving coefficient increased for both 3 and 50 L scales. Reduction of Starling flow was confirmed with lower total hydraulic membrane resistance throughout the culture. This work demonstrates a method for increasing sieving coefficient and filter capacity by stacking TFF filters with independent permeate streams.
Prerequisite knowledge‐based automated course planning with semantics consideration
Authors: Yoo John J.‐W. , Balachandranath Preamnath , Saboury Saeed 
Published: April 2024

AbstractThe knowledge‐based prerequisite framework (KPF) is an alternative to the course‐based prerequisite framework (CPF), which is widely used for curriculum design. The KPF is more flexible because it only requires essential prerequisite knowledge, while the CPF is more rigid and requires students to take all prerequisite courses. Since the number of prerequisite knowledge terms is, in general, much greater than the number of prerequisite courses, flexibility can cause additional complexity. Furthermore, the KPF inevitably requires handling semantics of defined knowledge terms. This work presents a novel Artificial Intelligence (AI) Planning mathematical model that enables the KPF by automatically verifying prerequisite knowledge and incorporating hierarchical semantic relationships among knowledge terms into the model. The proposed model significantly improves the quality of course planning solutions by finding hidden or better solutions that could not be obtained without semantics consideration. The results of the comprehensive experiments show the optimality of the solutions obtained by the mathematical model and demonstrate the outperformance of incorporation of the semantics into the mathematical model, in terms of the quality of solutions. Finally, the experimental results on scalability show the necessity of the development of efficient heuristic algorithms.
Identification of a disulfidptosis‐related prognostic signature for prediction of the effect of treatment in patients with endometrial carcinoma
Authors: Peng Lu , Gao Yuan , Cao Zifeng , Pang Yingxin 
Published: April 2024

AbstractBackgroundDisulfide, an essential compounds family, has diverse biological activity and can affect the dynamic balance between physiological and pathological states. A recently published study found that aberrant accumulation of disulfide had a lethal effect on cells. This mechanism of cell death, named disulfidptosis, differs from other known cell death mechanisms, including cuproptosis, apoptosis, necroptosis, and pyroptosis. The relationship between disulfidptosis and development of cancer, in particular endometrial carcinoma, remains unclear.MethodsTo address this knowledge gap, we performed a preliminary analysis of samples from The Cancer Genome Atlas database. The samples were divided equally into a training group and a test group. A total of 2308 differentially expressed genes were extracted, and 11 were used to construct a prognostic model.ResultsBased on the risk score calculated using the prognostic model, the samples were divided into a high‐risk group and a low‐risk group. Survival time, tumor mutation burden, and microsatellite instability scores differed significantly between the two groups. Furthermore, a between‐group difference in treatment effect was predicted. Comparison with other models in the literature indicated that this prognostic model had better predictive anility.ConclusionThe results of this study provide a general framework for understanding the relationship between disulfidptosis and endometrial cancer that could be used for clinical evaluation and selection of appropriate personalized treatment strategies.
PAI‐1 transfected‐conditioned media promotes osteogenic differentiation of hBMSCs
Authors: Li Zhang , Kegui Hou , Piao Wang , Xuejiu Wang , Lim Ki‐Taek , Jin Hexiu 
Published: April 2024

AbstractReconstruction of injured bone remains challenging in the clinic owing to the lack of suitable bone grafts. The utilization of PAI‐1 transfected‐conditioned media (P‐CM) has demonstrated its ability to facilitate the differentiation process of mesenchymal stem cells (MSCs), potentially serving as a crucial mediator in tissue regeneration. This research endeavored to explore the therapeutic potential of P‐CM concerning the differentiation of human bone marrow mesenchymal stem cells (hBMSCs). To assess new bone formation, a rat calvaria critical defect model was employed, while in vitro experiments involved the use of the alizarin Red‐S mineral induction test. In the rat calvaria critical defect model, P‐CM treatment resulted in significan new bone formation. In vitro, P‐CM treated hBMSCs displayed robust osteogenesis compared to the control group, as demonstrated by the mineral induction test using alizarin Red‐S. P‐CM with hydroxyapatite/β‐tricalcium phosphate/fibrin gel treatment significantly exhibited new bone formation, and the expression of osteogenic associated markers was enhanced in the P‐CM‐treated group. In conclusion, results demonstrate that P‐CM treatment significantly enhanced the osteogenic differantiation efficiency and new bone formation, thus could be used as an ideal therapeutic biomolecule for constructing bone‐specific implants, especially for orthopedic and dental applications.
More than skin‐deep elbow pain in a psoriatic arthritis patient after phlebotomy
Authors: Kaur Ikwinder Preet , Kaeley Gurjit 
Published: April 2024

Key Clinical MessageBicipitoradial bursitis is an unusual cause of cubital fossa pain in PsA patients. Bedside Ultrasound is a valuable tool to correlate the source of pain in rheumatic and musculoskeletal diseases.
A case of cough syncope diagnosed by the Valsalva maneuver and cough induction test under invasive arterial pressure measurement
Authors: Kubota Yoshiro , Okajima Katsunori , Nagamatsu Yuichi , Nakanishi Tomoyuki , Shirai Takeaki , Kadotani Makoto , Ohnishi Yoshio 
Published: April 2024

Key Clinical MessageFollowing the loss of consciousness during the Valsalva maneuver and cough induction test, real‐time arterial pressure measurement could clarify the significant blood pressure decrease in a patient with cough syncope.
Understanding Flexdispersion: Structure‐Function Relationship Studies of Organic Amphiphilic Ligands
Authors: Sudo Tatsuya , Sagawa Masahiko , Adachi Sota , Kato Yusuke , Nakanishi Yuki , Nakamura Tatsuya , Yamashita Shohei , Kamiya Hidehiro , Okada Yohei 
Published: April 2024

AbstractSince inorganic nanoparticles have unique properties that differ from those of bulk materials, their material applications have attracted attention in various fields. In order to utilize inorganic nanoparticles for functional materials, they must be dispersed without agglomeration. Therefore, the surfaces of inorganic nanoparticles are typically modified with organic ligands to improve their dispersibility. Nevertheless, the relationship between the tail group structure in organic ligands and the dispersibility of inorganic nanoparticles in organic solvents remains poorly understood. We previously developed amphiphilic ligands that consist of ethylene glycol chains and alkyl chains to disperse inorganic nanoparticles in a variety of organic solvents. However, the structural requirements for amphiphilic ligands to “flexibly” disperse nanoparticles in less polar to polar solvents are still unclear. Here, we designed and synthesized several phosphonic acid ligands for structure−function relationship studies of flexdispersion. Dynamic light scattering analysis and visible light transmittance measurements revealed that the ratio of alkyl/ethylene glycol chains in organic ligands alone does not determine the dispersibility of the nanoparticles in organic solvents, but the arrangement of the individual chains also has an effect. From a practical application standpoint, it is preferable to design ligands with ethylene glycol chains on the outside relative to the particle surface.
An adding‐points strategy surrogate model for well control optimization based on radial basis function neural network
Authors: Chen Hongwei , Xu Chen , Li Yang , Xu Chi , Su Haoyu , Guo Yujun 
Published: April 2024

AbstractThis work introduces a new adding points strategy for augmenting the accuracy of reservoir proxy model and improving the effect of well control optimization. The method is based on the optimization process of a radial basis function neural network and genetic algorithm (GA), which aids in identifying the more important points to be included in the sample space. Notably, the uniqueness of this method lies in selecting the points of higher importance for subsequent optimization processes across the entire sample space. These selected points are then added to the surrogate model. The surrogate model is updated for each generation until the termination condition is satisfied, enabling the surrogate model to achieve improved accuracy. The results show that the new method is more effective, superior, and converges faster than the traditional method.
Revealing the Regulation Effect of Surface Charge at Aromatic Interface to Dynamic Conformational Changes of α‐Synuclein at Early Aggregation Stage
Authors: Zhang Yuqi , Wu Lie , Jiang Xiue 
Published: April 2024

Comprehensive SummaryThe aggregation of α‐synuclein (α‐syn) is strongly influenced by membrane interfaces, but the mechanism of transition from monomers to oligomers at early aggregation stage is not clear. Here, we investigate the adsorption and structure changes of α‐syn on oppositely charged aromatic interfaces through in‐situ surface‐enhanced infrared absorption (SEIRA) spectroscopy and nano‐IR technique. The results show that the synergy of electrostatic and hydrophobic interactions leads to a “fast‐slow” two‐step aggregation pathway on negatively charged interface. Surface adsorption induces the formation of an extended helix structure and subsequently partial helix unwinding in NAC region, which enables the hydrophobic stacking between nearby NAC regions. Stable antiparallel β‐sheet rich aggregates are gradually emerging as further interactions of monomers with the fast formed “first layer”. Monomers electrostatically adsorb on positively charged interface by C‐terminus with NAC region and N‐terminus stretched in solvent, which serve as an aggregation core and induce further adsorption and gradual formation of aggregates with C‐terminus exposure. Our results demonstrate the modulation of surface charge and synergy of electrostatic and hydrophobic interactions on the interaction modes and aggregation pathways, which provide insights into dynamic conformation changes of α‐syn at early aggregation stage and imply the important role of spatial‐temporal heterogeneity of membranes in α‐synucleinopathies.
Multistimuli‐Responsive Luminescent Porous Organic Polymers with Chiroptical Properties and Acid‐Induced Degradation
Authors: He Youling , Fan Dongyang , Zhang Liang , Wang Dong , Han Ting , Hu Rongrong , Tang Ben Zhong 
Published: April 2024

Comprehensive SummaryPorous organic polymers (POPs) have attracted great attention in past decades. Although diverse functional POPs have been developed, multistimuli‐responsive POPs with excellent aggregate‐state luminescence together with good chiroptical properties have rarely been reported. Herein, two pairs of Salen‐type enantiomeric POPs with multistimuli‐responsive luminescence and chiral features were designed and synthesized by facile polycondensation reactions between polyfunctional aggregation‐induced emission luminogen (AIEgen)‐containing salicylaldehyde derivatives and chiral diamines. With Salen units in polymer backbones as tetradentate ligands, a series of POP‐metal complexes were further prepared. The obtained POPs and metal complexes show good porosity, high thermal stability, and obvious circular dichroism signals. Moreover, benefiting from the coexistence of AIEgen and Salen units in polymer structures, these POPs exhibit excellent luminescence performance in aggregate states and tunable fluorescence behaviors in response to external stimuli of Zn2+ ion, mechanical forces, organic solvent, and acids. Due to the dynamic feature of Schiff base C=N bonds, the present POPs can efficiently undergo hydrolysis reactions under strong acidic conditions to reproduce the AIEgen‐ containing monomers, and such an acid‐induced degradation process can be directly visualized and dynamically monitored via fluorescence variation. These properties collectively make the POPs candidate materials for applications in heterogeneous asymmetric catalysis, fluorescence sensing, biomedicine, etc.