bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact understanding of exosome therapy in COVID-19 and preparations for the future approaches in dealing with infectious diseases and inflammation
Authors: Nasiri Zeynab , Soleimanjahi Hoorieh , Baheiraei Nafiseh , Hashemi Seyed Mahmoud , Pourkarim Mahmoud Reza 
Published: March 2024

AbstractCytokine storms, which result from an abrupt, acute surge in the circulating levels of different pro-inflammatory cytokines, are one of the complications associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to assess the effect of exosomes on the release of pro-inflammatory cytokines in patients with coronavirus disease 2019 (COVID-19) and compare it with a control group. The cytokines evaluated in this study were TNF-α, IL-6, IL-17, and IFN-γ. The study compared the levels of these pro-inflammatory cytokines in the peripheral blood mononuclear cells (PBMCs) of five COVID-19 patients in the intensive care unit, who were subjected to both inactivated SARS-CoV-2 and exosome therapy, with those of five healthy controls. The cytokine levels were quantified using the ELISA method. The collected data was analyzed in SPSS Version 26.0 and GraphPad Prism Version 9. According to the study findings, when PBMCs were exposed to inactivated SARS-CoV-2, pro-inflammatory cytokines increased in both patients and healthy controls. Notably, the cytokine levels were significantly elevated in the COVID-19 patients compared to the control group P-values were < 0.001, 0.001, 0.008, and 0.008 for TNF-α, IL-6, IL-17, and IFN-γ, respectively. Conversely, when both groups were exposed to exosomes, there was a marked reduction in the levels of pro-inflammatory cytokines. This suggests that exosome administration can effectively mitigate the hyperinflammation induced by COVID-19 by suppressing the production of pro-inflammatory cytokines in patients. These findings underscore the potential safety and efficacy of exosomes as a therapeutic strategy for COVID-19.
The soil microbiome of Lolium perenne L. depends on host genotype, is modified by nitrogen level and varies across season
Authors: Paina Cristiana , Fois Mattia , Asp Torben , Jensen Just , Hansen Pernille Bjarup , Rohde Palle Duun 
Published: March 2024

AbstractGenotype by environment interactions (G × E) are frequently observed in herbage production. Understanding the underlying biological mechanisms is important for achieving stable and predictive outputs across production environments. The microbiome is gaining increasing attention as a significant contributing factor to G × E. Here, we focused on the soil microbiome of perennial ryegrass (Lolium perenne L.) grown under field conditions and investigated the soil microbiome variation across different ryegrass varieties to assess whether environmental factors, such as seasonality and nitrogen levels, affect the microbial community. We identified bacteria, archaea, and fungi operational taxonomic units (OTUs) and showed that seasonality and ryegrass variety were the two factors explaining the largest fraction of the soil microbiome diversity. The strong and significant variety-by-treatment-by-seasonal cut interaction for ryegrass dry matter was associated with the number of unique OTUs within each sample. We identified seven OTUs associated with ryegrass dry matter variation. An OTU belonging to the Solirubrobacterales (Thermoleophilales) order was associated with increased plant biomass, supporting the possibility of developing engineered microbiomes for increased plant yield. Our results indicate the importance of incorporating different layers of biological data, such as genomic and soil microbiome data to improve the prediction accuracy of plant phenotypes grown across heterogeneous environments.
Apigenin ameliorates genitourinary dysfunction in a type 1 diabetic rat model via Drp1 modulation
Authors: Khaled Mai , Salama Raghda A. M. , Aboughalia Azza , Tarek Mai , Mohamed Fawzy Nesma 
Published: March 2024

AbstractThe present study aimed to explore the potential ameliorative effect of apigenin (APG) against diabetes-associated genitourinary complications in rats. A diabetic rat model was induced by the intraperitoneal injection of streptozotocin (STZ). All experimental animals were treated with vehicle or vehicle plus APG at a dose of 0.78 mg/kg/day for 10 days, either once diabetes was confirmed or at the end of the 3rd week after confirmation of diabetes. Rats were sacrificed at the end of the fifth week. In addition to the histological assessment, an analysis of kidney function tests and serum testosterone was performed to assess diabetic genitourinary complications. Gene expression of the mitochondrial fission protein, dynamin related protein 1 (Drp1), was measured in renal and testicular tissues using qRT PCR. APG can increase body weight, reduce blood glucose levels, and improve renal and testicular functions in diabetic rats. APG decreased Drp1 overexpression in diabetic animals’ kidneys and testes. In summary, our current work discloses that APG attenuates diabetic genitourinary lesions in rats via suppressing Drp1 overexpression.
AtPCa-Net: anatomical-aware prostate cancer detection network on multi-parametric MRI
Authors: Zheng Haoxin , Hung Alex Ling Yu , Miao Qi , Song Weinan , Scalzo Fabien , Raman Steven S. , Zhao Kai , Sung Kyunghyun 
Published: March 2024

AbstractMulti-parametric MRI (mpMRI) is widely used for prostate cancer (PCa) diagnosis. Deep learning models show good performance in detecting PCa on mpMRI, but domain-specific PCa-related anatomical information is sometimes overlooked and not fully explored even by state-of-the-art deep learning models, causing potential suboptimal performances in PCa detection. Symmetric-related anatomical information is commonly used when distinguishing PCa lesions from other visually similar but benign prostate tissue. In addition, different combinations of mpMRI findings are used for evaluating the aggressiveness of PCa for abnormal findings allocated in different prostate zones. In this study, we investigate these domain-specific anatomical properties in PCa diagnosis and how we can adopt them into the deep learning framework to improve the model’s detection performance. We propose an anatomical-aware PCa detection Network (AtPCa-Net) for PCa detection on mpMRI. Experiments show that the AtPCa-Net can better utilize the anatomical-related information, and the proposed anatomical-aware designs help improve the overall model performance on both PCa detection and patient-level classification.
Numerical analysis of spray characterization of blends of hydrous ethanol with diesel and biodiesel
Authors: Shanthan Vardelli , Suryawanshi Jiwak , Tarodiya Rahul , Loyte Akshay , Devarajan Yuvarajan , Kaliappan Nandagopal 
Published: March 2024

AbstractThe spray characteristics of a fuel greatly influence the combustion as it affects the formation of an air–fuel mixture, which directly impacts the performance and emissions of the engine. This study investigates the physical injection spray characteristics of biofuels to optimize the engine operating parameters for their effective utilization. For the analysis of the spray characteristics of pure diesel (D100), 80% diesel—20% biodiesel (D80B20), 80% diesel—10% biodiesel—10% pure ethanol (D80B10E10), and 80% diesel—10% biodiesel—10% hydrous ethanol (D80B10HE10) are investigated. Computational Fluid Dynamics (CFD) modeling of a constant volume chamber under non-evaporative conditions is performed to conduct numerical analysis. The chamber pressure of 2 and 2.5 MPa and nozzle injection diameter of 0.126 mm, 0.15 mm, and 0.2 mm are considered to conduct the simulations. The variation in spray penetration length is analyzed and discussed for the injection of different fuel blends at different initial conditions. It is observed from numerical results that the high-density fuel blend D80B20 has a penetration length of 10.695% and 15.805% higher than pure diesel and D80B10HE10 blends, respectively. For pure diesel, with an increase in nozzle diameter from 0.126 mm to 0.15 mm and 0.2 mm, the penetration length is increased by 20% and 32%, respectively, and with an increase in pressure from 2 MPa to 2.5 MPa, penetration length is decreased by 14.62%. From this study, it can be concluded that biofuels like biodiesel and hydrous ethanol can be used with diesel in blended form over pure ethanol. Compared to pure ethanol, hydrous ethanol gives cost benefits and better spray characteristics.
The long noncoding RNA LAL contributes to salinity tolerance by modulating LHCB1s’ expression in Medicago truncatula
Authors: Zhao Yang , Liu Yafei , Zhang Feiran , Wang Zeng-Yu , Mysore Kirankumar S. , Wen Jiangqi , Zhou Chuanen 
Published: March 2024

AbstractLong non-coding RNAs (lncRNAs) are abundant in plants, however, their regulatory roles remain unclear in most biological processes, such as response in salinity stress which is harm to plant production. Here we show a lncRNA in Medicago truncatula identified from salt-treated Medicago truncatula is important for salinity tolerance. We name the lncRNA LAL, LncRNAANTISENSE to M. truncatulaLIGHT-HARVESTING CHLOROPHYLL A/B BINDING (MtLHCB) genes. LAL is an antisense to four consecutive MtLHCB genes on chromosome 6. In salt-treated M. truncatula, LAL is suppressed in an early stage but induced later; this pattern is opposite to that of the four MtLHCBs. The lal mutants show enhanced salinity tolerance, while overexpressing LAL disrupts this superior tolerance in the lal background, which indicates its regulatory role in salinity response. The regulatory role of LAL on MtLHCB1.4 is further verified by transient co-expression of LAL and MtLHCB1.4-GFP in tobacco leaves, in which the cleavage of MtLHCB1.4 and production of secondary interfering RNA is identified. This work demonstrates a lncRNA, LAL, functioning as a regulator that fine-tunes salinity tolerance via regulating MtLHCB1s’ expression in M. truncatula.
Modulatory effects of noradrenergic and serotonergic signaling pathway on neurovascular coupling
Authors: Renden Robert B. , Institoris Adam , Sharma Kushal , Tran Cam Ha T. 
Published: March 2024

AbstractDynamic changes in astrocyte Ca2+ are recognized as contributors to functional hyperemia, a critical response to increased neuronal activity mediated by a process known as neurovascular coupling (NVC). Although the critical role of glutamatergic signaling in this process has been extensively investigated, the impact of behavioral state, and the release of behavior-associated neurotransmitters, such as norepinephrine and serotonin, on astrocyte Ca2+ dynamics and functional hyperemia have received less attention. We used two-photon imaging of the barrel cortex in awake mice to examine the role of noradrenergic and serotonergic projections in NVC. We found that both neurotransmitters facilitated sensory stimulation-induced increases in astrocyte Ca2+. Interestingly, while ablation of serotonergic neurons reduced sensory stimulation-induced functional hyperemia, ablation of noradrenergic neurons caused both attenuation and potentiation of functional hyperemia. Our study demonstrates that norepinephrine and serotonin are involved in modulating sensory stimulation-induced astrocyte Ca2+ elevations and identifies their differential effects in regulating functional hyperemia.
Accelerated discovery of molecular nanojunction photocatalysts for hydrogen evolution by using automated screening and flow synthesis
Authors: Zhang Weiwei , Yu Miaojie , Liu Tao , Cong Muyu , Liu Xueyan , Yang Haofan , Bai Yang , Zhu Qiang , Zhang Shuo , Gu Hongxu , Wu Xiaofeng , Zhang Zhiyun , Wu Yongzhen , Tian He , Li Xiaobo , Zhu Wei-Hong , Cooper Andrew I. 
Published: March 2024

AbstractDiscovering and optimizing multicomponent organic semiconductors is typically a laborious process. High-throughput experimentation can accelerate this, but the results of small-scale screening trials are not always transferable to bulk materials production. Here we report the accelerated discovery of molecular nanojunction photocatalysts based on a combinatorial donor–acceptor molecular library assisted by high-throughput automated screening. The knowledge gained from this high-throughput batch screening is then transferred to a scaled-up, flow-based synthesis process. The scaled-up molecular nanojunction MTPA-CA:CNP147 (3-(4-(bis(4-methoxyphenyl)amino)phenyl)-2-cyanoacrylic acid:2,6-bis(4-cyanophenyl)-4-(4′-fluoro-[1,1′-biphenyl]-4-yl)pyridine-3,5-dicarbonitrile) exhibits a sacrificial hydrogen evolution rate of 330.3 mmol h−1 g−1 with an external quantum efficiency of 80.3% at 350 nm, which are among the highest reported for an organic photocatalyst. A one-dimensional nanofibre architecture is identified for this molecular nanojunction, which exhibits efficient charge separation. Electronic structure–property correlations across the photocatalyst library show that a moderate binding energy between the donor and the acceptor molecules is a potential factor for efficient molecular nanojunction formation.
The influence of the 2021 European flooding on pro-environmental attitudes and partial behaviour transition
Authors: Bulut Hamid , Samuel Robin 
Published: March 2024

AbstractOne of the reasons why people do not act pro-environmentally might be a lack of experience with the consequences of climate change. Studies have shown that higher levels of environmental attitudes and more environmentally friendly behaviours have been observed among people affected by extreme weather events. It is unclear, however, whether the events caused the changes or whether the affected people simply differed in their characteristics from those who were unaffected. We draw on a natural experiment to examine the causal link between flooding experiences, pro-environmental attitudes and pro-environmental behaviour using national survey data collected from 2058 individuals aged 16-29 years across Luxembourg. After people experienced the 2021 European flooding, their pro-environmental attitudes increased significantly. The effect was stronger in regions that were more affected by floods. Higher levels of environmental attitudes partly translated into greater willingness to act in a pro-environmental way. The results have important implications for advancing efforts to address climate change by demonstrating links between extreme weather events attributed to climate change and higher levels of environmental attitudes.
Metamaterial-based passive analog processor for wireless vibration sensing
Authors: Zhang Dajun , Polamarasetty Akhil , Shahid Muhammad Osama , Krishnaswamy Bhuvana , Ma Chu 
Published: March 2024

AbstractReal-time, low-cost, and wireless mechanical vibration monitoring is necessary for industrial applications to track the operation status of equipment, environmental applications to proactively predict natural disasters, as well as day-to-day applications such as vital sign monitoring. Despite this urgent need, existing solutions, such as laser vibrometers, commercial Wi-Fi devices, and cameras, lack wide practical deployment due to their limited sensitivity and functionality. Here we proposed a fully passive, metamaterial-based vibration processing device, fabricated prototypes working at different frequencies ranging from 5 Hz to 285 Hz, and verified that the device can improve the sensitivity of wireless vibration measurement methods by more than ten times when attached to vibrating surfaces. Additionally, the device realizes an analog real-time vibration filtering/labeling effect, and the device also provides a platform for surface editing, which adds more functionalities to the current non-contact sensing systems. Finally, the working frequency of the device is widely adjustable over orders of magnitudes, broadening its applicability to different applications, such as structural health diagnosis, disaster warning, and vital signal monitoring.
Trajectory optimization for maximization of energy efficiency with dynamic cluster and wireless power for UAV‐assisted maritime communication
Authors: Wang Xiaoxuan , Jiao Hengyuan , Gao Qinghe , Wu Yue , Jing Tao , Qian Jin 
Published: March 2024

AbstractNowadays, the digital development of marine ranching requires a communication system with wide coverage, high transmission rate and stable communication links. It is known that fixed‐wing unmanned aerial vehicles (UAVs) have great advantages in long‐range applications. They have the potential to serve as low‐altitude communication platforms for maritime communication. In this study, with a developmental perspective, considering the intense growth of marine terminals in the future, a new clustering algorithm applied to cluster nonorthogonal multiple access (C‐NOMA) is proposed and its advantages are investigated. In addition, considering the limited energy of marine terminals, combining the wireless power communication (WPC) technology for the UAV to charge terminals, the charging and communication time are optimized with the Lagrange multiplier method and the bisection search method. After completing the above optimization content of charging and communication, combined with the optimization results, it is found the trajectory that maximizes the energy efficiency of the UAV with the convex optimization technique. Experimental results show that the proposed clustering algorithm has good throughput performance, better fairness and lower algorithm complexity, and the proposed trajectory optimization scheme has better energy efficiency.
Integrating the circular economy model into the management and treatment of Fischer–Tropsch effluents—a conversion of waste to energy (biogas) opportunity
Authors: Moreroa Mabatho , Malematja Thapelo P. , Ijoma Grace Nkechinyere 
Published: March 2024

AbstractThe Fischer–Tropsch (FT) process converts coal, biomass, or natural gas into liquid hydrocarbons via syngas generation and catalytic conversion. However, FT produces byproducts and effluents with substantial environmental consequences. This review explores the circular economy model's potential as a sustainable wastewater management strategy for FT effluent management. Furthermore, the paper investigates ameliorative measures to overcome the limitations of one biological treatment method, anaerobic digestion of FT effluents by examining the combination of nutrient augmentation, microbial augmentation, and enrichment from the integration of wastes derived from other industrial sectors as pivotal to the implementation of circular economics modelling in FT effluents valuation. This approach to the circular economy model can help overcome the environmental concerns posed by FT effluents in its advocacy of resource sharing, reuse, and recycling. This review also promotes circular economy principles to improve resource recovery, recycling, and collaboration with other industrial sectors, such as agriculture and mining, with FT application industries to create a more sustainable economy and reduce their environmental footprints. However, since the chemical compositions of wastes vary with location and other parameters, future case studies should optimize the waste mixtures to determine the optimal balance before valorizing them.
Few‐shot learning for satellite characterisation from synthetic inverse synthetic aperture radar images
Authors: Heslinga Friso G. , Uysal Faruk , van Rooij Sabina B. , Berberich Sven , Caro Cuenca Miguel 
Published: March 2024

AbstractSpace situational awareness systems primarily focus on detecting and tracking space objects, providing crucial positional data. However, understanding the complex space domain requires characterising satellites, often involving estimation of bus and solar panel sizes. While inverse synthetic aperture radar allows satellite visualisation, developing deep learning models for substructure segmentation in inverse synthetic aperture radar images is challenging due to the high costs and hardware requirements. The authors present a framework addressing the scarcity of inverse synthetic aperture radar data through synthetic training data. The authors approach utilises a few‐shot domain adaptation technique, leveraging thousands of rapidly simulated low‐fidelity inverse synthetic aperture radar images and a small set of inverse synthetic aperture radar images from the target domain. The authors validate their framework by simulating a real‐case scenario, fine‐tuning a deep learning‐based segmentation model using four inverse synthetic aperture radar images generated through the backprojection algorithm from simulated raw radar data (simulated at the analogue‐to‐digital converter level) as the target domain. The authors results demonstrate the effectiveness of the proposed framework, significantly improving inverse synthetic aperture radar image segmentation across diverse domains. This enhancement enables accurate characterisation of satellite bus and solar panel sizes as well as their orientation, even when the images are sourced from different domains.
Advancing MRI capacitors: Design, fabrication, and characterization
Authors: Jebri Zaineb , Ali Mahfoudh Taleb , Juergen Nistler 
Published: March 2024

AbstractIn today's healthcare landscape, MRI (magnetic resonance imaging) plays a pivotal role in early diagnosis and treatment decisions. However, the quest for higher frequencies to achieve micron‐level resolutions poses technological challenges. This paper focuses on coils and capacitors, with special attention to air gap considerations for movable electrodes. The paper delves into the development of adjustable capacitors using high‐fired NP0 ceramic, tailored for 128‐MHz MRI systems. These capacitors boast impressive specs: a 3‐kV breakdown voltage (VBreakdown), a 3‐pF minimum capacitance (Cmin), a 30‐pF maximum capacitance (CMax), and a 1.5‐pF stepwise capacitance variation (Cvariation step). Notably, they enhance breakdown voltage while preserving frequency stability with MgTiCa ceramic between the fixed and mobile electrode, critical for adaptive blocks. Leveraging geometrical parameters analyzed through the ANSYS simulator, the authors meticulously designed an optimized 25–40 pF capacitor with a 15‐mm height and 1600 mm2 surface area. Post‐fabrication and sintering, extensive testing using a vector network analyzer across 10 MHz to 100 MHz validated performance against simulated expectations.