bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient and highly reproducible production of red blood cell-derived extracellular vesicle mimetics for the loading and delivery of RNA molecules
Authors: Biagiotti Sara , Canonico Barbara , Tiboni Mattia , Abbas Faiza , Perla Elena , Montanari Mariele , Battistelli Michela , Papa Stefano , Casettari Luca , Rossi Luigia , Guescini Michele , Magnani Mauro 
Published: June 2024

AbstractExtracellular vesicles (EVs) are promising natural nanocarriers for the delivery of therapeutic agents. As with any other kind of cell, red blood cells (RBCs) produce a limited number of EVs under physiological and pathological conditions. Thus, RBC-derived extracellular vesicles (RBCEVs) have been recently suggested as next-generation delivery systems for therapeutic purposes. In this paper, we show that thanks to their unique biological and physicochemical features, RBCs can be efficiently pre-loaded with several kinds of molecules and further used to generate RBCEVs. A physical vesiculation method, based on “soft extrusion”, was developed, producing an extremely high yield of cargo-loaded RBCEV mimetics. The RBCEVs population has been deeply characterized according to the new guidelines MISEV2023, showing great homogeneity in terms of size, biological features, membrane architecture and cargo. In vitro preliminary results demonstrated that RBCEVs are abundantly internalized by cells and exert peculiar biological effects. Indeed, efficient loading and delivery of miR-210 by RBCEVs to HUVEC has been proven, as well as the inhibition of a known mRNA target. Of note, the bench-scale process can be scaled-up and translated into clinics. In conclusion, this investigation could open the way to a new biomimetic platform for RNA-based therapies and/or other therapeutic cargoes useful in several diseases.
Crystal structure of l-2-keto-3-deoxyfuconate 4-dehydrogenase reveals a unique binding mode as a α-furanosyl hemiketal of substrates
Authors: Akagashi Miyu , Watanabe Seiya , Kwiatkowski Sebastian , Drozak Jakub , Terawaki Shin-ichi , Watanabe Yasunori 
Published: June 2024

Abstractl-2-Keto-3-deoxyfuconate 4-dehydrogenase (l-KDFDH) catalyzes the NAD+-dependent oxidization of l-2-keto-3-deoxyfuconate (l-KDF) to l-2,4-diketo-3-deoxyfuconate (l-2,4-DKDF) in the non-phosphorylating l-fucose pathway from bacteria, and its substrate was previously considered to be the acyclic α-keto form of l-KDF. On the other hand, BDH2, a mammalian homolog with l-KDFDH, functions as a dehydrogenase for cis-4-hydroxy-l-proline (C4LHyp) with the cyclic structure. We found that l-KDFDH and BDH2 utilize C4LHyp and l-KDF, respectively. Therefore, to elucidate unique substrate specificity at the atomic level, we herein investigated for the first time the crystal structures of l-KDFDH from Herbaspirillum huttiense in the ligand-free, l-KDF and l-2,4-DKDF, d-KDP (d-2-keto-3-deoxypentonate; additional substrate), or l-2,4-DKDF and NADH bound forms. In complexed structures, l-KDF, l-2,4-DKDF, and d-KDP commonly bound as a α-furanosyl hemiketal. Furthermore, l-KDFDH showed no activity for l-KDF and d-KDP analogs without the C5 hydroxyl group, which form only the acyclic α-keto form. The C1 carboxyl and α-anomeric C2 hydroxyl groups and O5 oxygen atom of the substrate (and product) were specifically recognized by Arg148, Arg192, and Arg214. The side chain of Trp252 was important for hydrophobically recognizing the C6 methyl group of l-KDF. This is the first example showing the physiological role of the hemiketal of 2-keto-3-deoxysugar acid.
The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson’s disease
Authors: Gabbert Carolin , Blöbaum Leonie , Lüth Theresa , König Inke R. , Caliebe Amke , Sendel Sebastian , Laabs Björn-Hergen , Klein Christine , Trinh Joanne 
Published: June 2024

AbstractThe objective of this study was to investigate the association between a Parkinson’s disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD. We included data from 4367 patients with idiopathic PD, 159 patients with GBA1-PD, and 3090 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The association between PGS and lifestyle factors on AAO was assessed with linear and Cox proportional hazards models. The PGS showed a negative association with AAO (β = − 1.07, p = 6 × 10–7) in patients with idiopathic PD. The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p = 0.0001), 44% (p < 2 × 10–16), and 55% (p < 2 × 10–16), compared to no use. An additive effect of aspirin (β = 7.62, p = 9 × 10–7) and PGS (β = − 1.58, p = 0.0149) was found for AAO without an interaction (p = 0.9993) in the linear regressions, and similar effects were seen for tobacco. In contrast, no association between aspirin intake and AAO was found in GBA1-PD (p > 0.05). In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect.
5-fluorouracil and Rumex obtusifolius extract combination trigger A549 cancer cell apoptosis: uncovering PI3K/Akt inhibition by in vitro and in silico approaches
Authors: Ginovyan Mikayel , Javrushyan Hayarpi , Hovhannisyan Svetlana , Nadiryan Edita , Sevoyan Gohar , Harutyunyan Tigran , Gevorgyan Smbat , Karabekian Zaruhi , Maloyan Alina , Avtandilyan Nikolay 
Published: June 2024

AbstractThe continuous increase in cancer rates, failure of conventional chemotherapies to control the disease, and excessive toxicity of chemotherapies clearly demand alternative approaches. Natural products contain many constituents that can act on various bodily targets to induce pharmacodynamic responses. This study aimed to explore the combined anticancer effects of Rumex obtusifolius (RO) extract and the chemotherapeutic agent 5-fluorouracil (5-FU) on specific molecular targets involved in cancer progression. By focusing on the PI3K/Akt signaling pathway and its related components, such as cytokines, growth factors (TNFa, VEGFa), and enzymes (Arginase, NOS, COX-2, MMP-2), this research sought to elucidate the molecular mechanisms underlying the anticancer effects of RO extract, both independently and in combination with 5-FU, in non-small lung adenocarcinoma A549 cells. The study also investigated the potential interactions of compounds identified by HPLC/MS/MS of RO on PI3K/Akt in the active site pocket through an in silico analysis. The ultimate goal was to identify potent therapeutic combinations that effectively inhibit, prevent or delay cancer development with minimal side effects. The results revealed that the combined treatment of 5-FU and RO demonstrated a significant reduction in TNFa levels, comparable to the effect observed with RO alone. RO modulated the PI3K/Akt pathway, influencing the phosphorylated and total amounts of these proteins during the combined treatment. Notably, COX-2, a key player in inflammatory processes, substantially decreased with the combination treatment. Caspase-3 activity, indicative of apoptosis, increased by 1.8 times in the combined treatment compared to separate treatments. In addition, the in silico analyses explored the binding affinities and interactions of RO's major phytochemicals with intracellular targets, revealing a high affinity for PI3K and Akt. These findings suggest that the combined treatment induces apoptosis in A549 cells by regulating the PI3K/Akt pathway.
Exploring the evolution of mass density and thickness of N-doped Ge-rich GeSbTe during multistep crystallization
Authors: Remondina Jacopo , Portavoce Alain , Le Friec Yannick , Benoit Daniel , Petroni Elisa , Putero Magali 
Published: June 2024

AbstractAmong phase change materials, Ge-rich GeSbTe alloys (GGST) are key alloys for the next generation of embedded phase change memories because of their good thermal stability, allowing their use for the automotive applications. Several studies have investigated GGST crystallization, which takes place in several stages, including phase separation in the amorphous material, the crystallization of the cubic Ge and GST phases before a complete crystallization for higher thermal budget. So far, however, no information is available on the possible changes in density and thickness of such alloys. This paper investigates such variations in density and thickness for a N-doped GGST layer (GGSTN) during isothermal annealing, following the four main stages of its multistep crystallization process. X-ray reflectivity (XRR) and X-ray diffraction were employed for analysis. The study reveals that density and thickness exhibit distinct changes during crystallization, with density increasing by approximately 9% during transition from amorphous to crystalline states. These changes are attributed to alterations in layer morphology, particularly at the Ge crystallization temperature and at the onset of GST crystal formation. Additionally, at high thermal budgets, discrepancies between XRR analysis methods suggest the formation of a thin, lower density layer near the top interface of the GGSTN layer. These results provide insights into the structural evolution of the GGSTN layer, which is crucial for phase change random access memory applications.
A new sliding window decoding algorithm based on check relationship improvement
Authors: Wang Liqian , Song Xiaoming , Zhao Yatong , Zhu Miao , Wang Weiming , Tao Kai , Shi Yinlong 
Published: June 2024

AbstractThis study focuses on improving the sliding window decoding algorithm by introducing a threshold based on the posterior probability at the end of each decoding window. This threshold serves to evaluate the reliability of the message within the window. For unreliable windows, specific corrective factors were introduced to enhance the overall performance of the algorithm. Furthermore, modifications were implemented to the range within which the check relationship is applicable, aiming to address the issue of incomplete check relationships encountered during the decoding process. These enhancements effectively improved the overall performance of the algorithm. The performance of the improved algorithm can be improved by 0.1 to 0.2 dB according to different code lengths.
Energy harvesting face mask using a thermoelectric generator for powering wearable health monitoring sensors
Authors: Erturun Ugur , Yalim Cansu , West James E. 
Published: June 2024

AbstractA wearable energy harvester (EH) incorporating a face mask with a thermoelectric generator is demonstrated. The function of this device is to generate electrical power from the heat produced by the human body, particularly breath, with the specific aim of powering wearable sensor applications. A prototype was built using a commercially available N95 face mask, a thermoelectric generator, and a heatsink. The performance of this EH device was assessed using experimental and numerical methodologies. The experimentally tested power output of the prototype was found to be ≈100 µW, with a corresponding power density of ≈30 µW/cm3, for a temperature difference of 7°C.
Study on flow field of oil‐cooling permanent magnet synchronous motor with hairpin winding using porous medium model
Authors: Yang Chen , Cai Wei , Shao Baicheng 
Published: June 2024

AbstractThe oil cooling method has been widely used in the permanent magnet synchronous motor with hairpin winding. Because of the irregular shape of the hairpin end winding, there are complex oil circuits in the fluid domain, resulting in a large number of grids and a high computational cost. It is still a challenge to calculate the oil‐cooling performance of the hairpin end winding. Therefore, the porous medium model (PMM) is first proposed to replace the real hairpin end winding to analyse the oil‐cooling performance. By comparing oil volume fraction and velocity at different oil‐supplied conditions using three methods: experiments, real model (the non‐equivalent fluid domain model based on the real hairpin end winding) and PMM, the feasibility of using the PMM to calculate the oil‐cooling performance on the end winding is verified. The oil distribution of three methods is the same. The use of the PMM saves 80% of the number of grids, which improves the simulation efficiency. Relationships between the porosity, permeability and resistance coefficient and the geometry parameters of windings are determined. The results show that the flow field changes greatly with changes in porosity, permeability and resistance coefficient.
Novel dual‐resonance damped alternating current testing system for offline partial discharge measurement of power cables
Authors: Wang Li , Jin Lei , Chen Junbai , Li Hongjie 
Published: June 2024

AbstractTo accurately detect the early deterioration of electrical insulation in power cables, an energizing system is required for offline partial discharge (PD) measurements. The damped alternating current (DAC) testing system has emerged as an effective tool for inducing PD events. However, the existing systems often suffer from limitations such as signal interference, low sensitivity, and high costs. To address these issues, this study proposes a novel dual‐resonance DAC testing system that is simple in structure and cost‐effective. The prototype was built for testing 10‐kV distribution cables, and its effectiveness was validated through experimental tests on a cable sample. The results show that this approach significantly improves PD detection sensitivity and successfully completes PD localization. This research contributes to the development of more efficient and affordable DAC generation technology for power cable testing applications.
Research on a multi‐scale degradation fusion network in all‐in‐one image restoration
Authors: Shi Bohang , Xiong Bingqing , Yu Yuanhui 
Published: June 2024

AbstractImage restoration aims to recover high‐quality clean images from degraded low‐quality ones. Deep learning‐based approaches have been a focal point in the field of image restoration. However, most methods focus solely on a single type of degradation and may not extend well to real‐world scenarios with unknown degradation. For this purpose, the present study introduces an all‐in‐one image restoration approach by designing a multi‐scale feature fusion UNet structure (MdfUNet). In summary, the proposed method exhibits two significant advantages. For starters, it implicitly fuses degradation information across multiple scales, enabling the network to extract rich hierarchical features and enhancing its generalization ability towards unknown degradations. Secondly, MdfUnet possesses strong image reconstruction capabilities. It utilizes a simple non‐linear feature optimizer to enhance skip connections, providing rich feature representations for the image reconstruction process, and ultimately generating high‐quality restored images. Extensive experimental results show the proposed method outperforms multiple baselines on deraining, dehazing, and denoising datasets.
Noise2Variance: Dual networks with variance constraint for self‐supervised real‐world image denoising
Authors: Tan Hanlin , Liu Yu , Zhang Maojun 
Published: June 2024

AbstractImage denoising aims to restore a clean image from a noisy image. Traditional methods utilizing convolutional neural networks (CNN) for denoising are trained using pairs of noisy and clean images to comprehend the transformation from a noisy image to a clean one. However, the acquisition of such image pairs in real‐world scenarios presents a challenge. Hence, numerous self‐supervised denoising techniques have been developed that do not require clean images for training. This study demonstrates that a straightforward loss design, concentrating on variance, can effectively train a standard CNN denoiser in a self‐supervised fashion. A novel theoretical framework is introduced for training a basic CNN denoising model using three constraints: mean, variance, and augmentation. The variance constraint is crucial as it prevents the trained model from converging to trivial solutions such as identity or zero mapping. This theory provides valuable insights for the development of new self‐supervised denoising methods. Furthermore, a method that applies this theory to proposed dual networks is developed, which consist of two standard CNN models predicting both the clean image and the noise. This approach enhances model capacity during training while minimizing computational costs during inference. This method exemplifies the implementation of the variance constraint and introduces a data constraint for dual networks. Notably, the proposed method only assumes the presence of additive white noise, irrespective of the noise distribution. This minimal assumption enhances the model's robustness against noise with complex or unknown distributions in real‐world distorted images. Experimental results indicate that the proposed Noise2Variance method exhibits commendable performance on peak signal noise ratio and structural similarity metrics compared to existing self‐supervised denoising techniques. Visual comparison of results further substantiates the efficacy of the proposed method. A comparison of model complexity reveals that the method is efficient among the compared CNN‐based techniques.
Navigating the complexity of tram ride comfort assessment in growing urban environments: A cloud theory perspective
Authors: Zhang Xinhuan , Li Dongping , Lauber Les , Li Cuiwei , Wu Jinhong 
Published: June 2024

AbstractThis study addresses the challenge of quantitatively assessing ride comfort in tram travel in Growing Urban Environments, where multiple influencing factors complicate developing a unified evaluation index system. A comprehensive evaluation framework based on cloud theory is proposed to overcome this challenge. The approach involves defining five‐level comfort evaluation grades to capture passengers' experiences and perceptions accurately. The Criteria Importance through Inter‐Criteria Correlation (CRITIC) method is employed to ensure objectivity to establish objective weights for evaluation indices. Subsequently, a cloud model algorithm is utilized to generate evaluation benchmark and actual result clouds, providing intuitive representations of the evaluation outcomes. The efficacy and rationality of the methodology is illustrated through a case study focusing on Suzhou Tram Line 2. This research contributes valuable insights for enhancing public transportation experiences in new urban settings by offering a systematic and objective approach to assessing tram ride comfort.
Analysis of mechanical properties in self‐compacting concrete enhanced with steel fibres
Authors: Karuppasamy Mukilan , Balakrishnan Baranitharan , Chandran Karthik , Gheisari Mehdi , Rezaeiye Payam Porkar , Andrievsky Boris 
Published: June 2024

AbstractThis study explores the effect of incorporating steel fibres and fly ash into self‐compacting concrete (SCC) in various combinations on its mechanical properties. The study begins with thoroughly investigating the fresh properties to ensure compliance with SCC standards when adding steel fibres. Subsequently, mixes that meet SCC standards are evaluated for their mechanical properties. The study aims to enhance the mechanical properties of SCC while maintaining its flowability, filling ability, and passing ability. The research findings provide valuable insights into the optimal combination of steel fibres and fly ash for improving the mechanical properties of SCC. The addition of hooked end type steel fibres increases the compressive strength. When compared to crimped type the mechanical properties increased to 14.4%; however, the strength decreases beyond 1% of steel fibres. Satisfactory results are obtained for fresh properties test.
Combination of the biologically inspired coupled system and high‐frequency surface wave radar at signal level
Authors: Li Hongbo , Liu Aijun , Yang Qiang , Yu Changjun , Lyv Zhe 
Published: June 2024

AbstractVirtual aperture extension of small aperture array has attracted wide attention in high‐frequency surface wave radar (HFSWR). A biologically inspired coupled (BIC) system is employed to virtually extend the array aperture. However, the existing researches on BIC only consider the array signal processing model and do not combine it with actual radar signal principle. To indeed apply the BIC system to HFSWR, two detailed methods which combine the BIC and HFSWR at signal level are proposed. A three‐dimensional signal model of HFSWR considering array processing was established and the entire signal processing was derived. Then, two combination methods, namely fast‐time domain (FTD)‐BIC and slow‐time domain (STD)‐BIC are proposed. The former implements the BIC before fast‐time processing, while the latter implements the BIC before slow‐time processing. The authors demonstrate that they can virtually extend the array aperture without affecting the target detection. Meanwhile, their capabilities in multi‐target scenarios are analysed and satisfactory conclusions are obtained. By numerical simulations and experiments, the array aperture and range‐Doppler (RD) spectrum of the standard HFSWR and BIC‐HFSWR are compared. The results show that while the performance of their RD spectrum is almost the same, BIC‐HFSWR has an enlarged virtual aperture than standard HFSWR.
The cosmic microwave background lensing imprint of cosmic voids detected in the WISE-Pan-STARRS luminous red galaxy catalog
Authors: Camacho-Ciurana G. , Lee P. , Arsenov N. , Kovács A. , Szapudi I. , Csabai I. 
Published: June 2024

Context. The cross-correlation of cosmic voids with the lensing convergence (κ) map of cosmic microwave background (CMB) fluctuations offers a powerful tool with which to refine our understanding of the dark sector in the consensus cosmological model.
Aims. Our principal aim is to compare the lensing signature of our galaxy dataset with simulations based on the concordance model and to characterize the results with an Aκ consistency parameter normalized to unity. In particular, our measurements contribute to the understanding of the “lensing-is-low” tension of the ΛCDM model.
Methods. In this analysis, we selected luminous red galaxies (LRGs) from the WISE-Pan-STARRS dataset, enabling an extended cross-correlation measurement using a 14 200 deg2 sky area, which offers a more precise measurement than previous studies. We created 2D and 3D void catalogs to cross-correlate their locations with the Planck CMB lensing map and studied their average imprint signal using a stacking methodology. Applying the same procedure, we also generated a mock galaxy catalog from the WebSky simulation to serve as a basis for comparison.
Results. The 2D void analysis reveals a good agreement with the standard cosmological model, with Aκ ≈ 1.06 ± 0.08 amplitude; that is, S/N = 13.3, showing a higher signal-to-noise than previous studies using voids detected in the Dark Energy Survey (DES) dataset. The 3D void analysis exhibited a lower signal-to-noise ratio and demonstrated worse agreement with our mock catalog than the 2D voids. These deviations might be attributed to limitations in the mock catalog, such as imperfections in the LRG selection, as well as a potential asymmetry between the northern and southern patches of the WISE-Pan-STARRS dataset in terms of data quality.
Conclusions. Overall, we present a significant detection of a CMB lensing signal associated with cosmic voids, largely consistent with the concordance model. Future analyses using even larger datasets also hold great promise of further sharpening these results, given their complementary nature to large-scale structure analyses.