bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative metabolomic and transcriptomic analyses reveals the accumulation patterns of key metabolites associated with flavonoids and terpenoids of Gynostemma pentaphyllum (Thunb.) Makino
Authors: Zhao Xiaomeng , Ge Weiwei , Miao Zhi 
Published: April 2024

AbstractGynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.
No difference in postprandial mesenteric blood flow between healthy younger and elderly individuals
Authors: Siebner Thomas Hartwig , Hove Jens Dahlgaard , Madelung Christopher Fugl , Hulme Oliver James , Bendtsen Flemming , Siebner Hartwig Roman , Barløse Mads 
Published: April 2024

AbstractWe recently used phase-contrast magnetic resonance imaging (PC-MRI) to demonstrate an attenuated postprandial blood flow response in the superior mesenteric artery (SMA) in patients with Parkinson's disease compared to age- and sex-matched healthy controls. Since both groups showed substantial inter-individual variations, we extended the cohort of controls with a group of young individuals to investigate possible age-related effects. Seventeen healthy young subjects aged < 30 years and 17 elderly subjects aged > 50 years underwent serial PC-MRI to measure the postprandial blood flow response in the SMA after ingestion of a standardized liquid test meal (∼400 kcal). Postprandial blood flow dynamics in SMA did not differ between young and elderly subjects. A noticeable inter-individual variation in postprandial intestinal blood flow increase was found, and approximately 30% of the variation could be explained by the preprandial blood flow. Regardless of age, some subjects showed a remarkable transient SMA blood flow increase immediately after meal intake. This study provides tentative evidence that postprandial blood flow dynamics in SMA in healthy young and elderly subjects do not substantially differ, indicating that age is without impact on vascular response in SMA as an indicator for regulation of mesenteric perfusion in response to food intake.
The application of improved densenet algorithm in accurate image recognition
Authors: Hou Yuntao , Wu Zequan , Cai Xiaohua , Zhu Tianyu 
Published: April 2024

AbstractImage recognition technology belongs to an important research field of artificial intelligence. In order to enhance the application value of image recognition technology in the field of computer vision and improve the technical dilemma of image recognition, the research improves the feature reuse method of dense convolutional network. Based on gradient quantization, traditional parallel algorithms have been improved. This improvement allows for independent parameter updates layer by layer, reducing communication time and data volume. The introduction of quantization error reduces the impact of gradient loss on model convergence. The test results show that the improvement strategy designed by the research improves the model parameter efficiency while ensuring the recognition effect. Narrowing the learning rate is conducive to refining the updating granularity of model parameters, and deepening the number of network layers can effectively improve the final recognition accuracy and convergence effect of the model. It is better than the existing state-of-the-art image recognition models, visual geometry group and EfficientNet. The parallel acceleration algorithm, which is improved by the gradient quantization, performs better than the traditional synchronous data parallel algorithm, and the improvement of the acceleration ratio is obvious. Compared with the traditional synchronous data parallel algorithm and stale synchronous parallel algorithm, the optimized parallel acceleration algorithm of the study ensures the image data training speed and solves the bottleneck problem of communication data. The model designed by the research improves the accuracy and training speed of image recognition technology and expands the use of image recognition technology in the field of computer vision.Please confirm the affiliation details of [1] is correct.The relevant detailed information in reference [1] has been confirmed to be correct.
RACGAP1 promotes lung cancer cell proliferation through the PI3K/AKT signaling pathway
Authors: Xu Zhiyang , Wu Shaohang , Tu Jiahua , Wang Mingyang , Liang Weicheng , Cheng Jiangdong , Guan Jun , Xu Jianxin 
Published: April 2024

AbstractWe aimed to investigate the expression and clinic significance of Rac GTPase Activating Protein 1 (RACGAP1) in human lung adenocarcinoma (LUAD). Online database analysis revealed a significant increase in RACGAP1 mRNA expression among 26 types of tumor tissues, including LUAD tissues. Online database and tissue microarray analyses indicated that RACGAP1 expression was significantly upregulated in LUAD tissues. Genetic variation analysis identified four different genetic variations of RACGAPs in LUAD. Moreover, online database analysis showed that RACGAP1 upregulation was correlated with shorter survival in patients with LUAD. After silencing RACGAP1 expression in A549 cells using siRNA and assessing its protein levels via Western blotting, we found that RACGAP1 knockdown inhibited cell growth and induced apoptosis determined using the Cell Counting Kit-8 assay, colony formation assay, and flow cytometry. Mechanistically, western blot analysis indicated that Bax expression increased, whereas Bcl-2 expression decreased. Moreover, RACGAP1 knockdown attenuated PI3K/AKT pathway activation in lung cancer cells. Taken together, our findings showed that RACGAP1 was overexpressed in LUAD tissues and played an important role in lung cancer by increasing cell growth through the PI3K/AKT signaling pathway. This study suggests recommends evaluating RACGAP1 in clinical settings as a novel biomarker and potential therapeutic target for lung cancer.
Experimental analysis and safety assessment of thermal runaway behavior in lithium iron phosphate batteries under mechanical abuse
Authors: Chai Zhixiong , Li Junqiu , Liu Ziming , Liu Zhengnan , Jin Xin 
Published: April 2024

AbstractMechanical abuse can lead to internal short circuits and thermal runaway in lithium-ion batteries, causing severe harm. Therefore, this paper systematically investigates the thermal runaway behavior and safety assessment of lithium iron phosphate (LFP) batteries under mechanical abuse through experimental research. Mechanical abuse experiments are conducted under different conditions and battery state of charge (SOC), capturing force, voltage, and temperature responses during failure. Subsequently, characteristic parameters of thermal runaway behavior are extracted. Further, mechanical abuse conditions are quantified, and the relationship between experimental conditions and battery characteristic parameters is analyzed. Finally, regression models for battery safety boundaries and the degree of thermal runaway risk are established. The research results indicate that the extracted characteristic parameters effectively reflect internal short circuit (ISC) and thermal runaway behaviors, and the regression models provide a robust description of the battery's safety boundaries and thermal runaway risk degree. This work sheds light on understanding thermal runaway behavior and safety assessment methods for lithium-ion cells under mechanical abuse.
Machine learning-powered estimation of malachite green photocatalytic degradation with NML-BiFeO3 composites
Authors: Salahshoori Iman , Yazdanbakhsh Amirhosein , Baghban Alireza 
Published: April 2024

AbstractThis study explores the potential of photocatalytic degradation using novel NML-BiFeO3 (noble metal-incorporated bismuth ferrite) compounds for eliminating malachite green (MG) dye from wastewater. The effectiveness of various Gaussian process regression (GPR) models in predicting MG degradation is investigated. Four GPR models (Matern, Exponential, Squared Exponential, and Rational Quadratic) were employed to analyze a dataset of 1200 observations encompassing various experimental conditions. The models have considered ten input variables, including catalyst properties, solution characteristics, and operational parameters. The Exponential kernel-based GPR model achieved the best performance, with a near-perfect R2 value of 1.0, indicating exceptional accuracy in predicting MG degradation. Sensitivity analysis revealed process time as the most critical factor influencing MG degradation, followed by pore volume, catalyst loading, light intensity, catalyst type, pH, anion type, surface area, and humic acid concentration. This highlights the complex interplay between these factors in the degradation process. The reliability of the models was confirmed by outlier detection using William’s plot, demonstrating a minimal number of outliers (66–71 data points depending on the model). This indicates the robustness of the data utilized for model development. This study suggests that NML-BiFeO3 composites hold promise for wastewater treatment and that GPR models, particularly Matern-GPR, offer a powerful tool for predicting MG degradation. Identifying fundamental catalyst properties can expedite the application of NML-BiFeO3, leading to optimized wastewater treatment processes. Overall, this study provides valuable insights into using NML-BiFeO3 compounds and machine learning for efficient MG removal from wastewater.
Individuals vary in their overt attention preference for positive images consistently across time and stimulus types
Authors: Guy Nitzan , Sklar Asael Y. , Amiaz Revital , Golan Yael , Livny Abigail , Pertzov Yoni 
Published: April 2024

AbstractWhat humans look at strongly determines what they see. We show that individual differences in the tendency to look at positive stimuli are stable across time and across contents, establishing gaze positivity preference as a perceptual trait that determines the amount of positively valence stimuli individuals select for visual processing. Furthermore, we show that patients with major depressive disorder exhibit consistently low positivity preference before treatment. In a subset of patients, we also assessed the positivity preference after two months of treatment in which positivity gaze preference increased to levels similar to healthy individuals. We discuss the possible practical diagnostic applications of these findings, as well as how this general gaze-related trait may influence other behavioral and psychological aspects.
Assessing soil erosion and farmers’ decision of reducing erosion for sustainable soil and water conservation in Burji woreda, southern Ethiopia
Authors: Djillo Shibru Chuda , Wolka Kebede , Tofu Daniel Assefa 
Published: April 2024

AbstractInadequate conservation practice affects the sustainable production of agricultural watersheds due to erosion and fertility decline. Understanding soil erosion and implementing site-specific conservation practice could enhance agriculture-based rural development. The study was aimed to document soil erosion problem and soil and water conservation effort. The specific objectives of this study were to assess soil erosion severity, practices to reduce erosion, and determinants of the decision to reduce erosion. Data were collected by interviewing 198 farm household heads, undertaking four focus group discussions, and assessing rill erosion in 10 farm fields in Morayo and Wacho sub-watersheds of southern Ethiopia. Descriptive statistics and binary logit model were applied to analyze the data. Results indicated that many of the farm households, 63% in Morayo and 83% in the Wacho sub-watershed, perceived moderate to severe soil erosion, which is characterized by big rills and small gullies on the farmlands. Rill densities of 231.4 m ha−1 and 84.1 m ha−1 in the Morayo and Wacho sub-watersheds were observed, respectively. The estimated annual soil loss due to rills was 61.2 and 23.4 Mg ha−1 in the Morayo and Wacho sub-watersheds, respectively. The soil erosion from rills alone exceeds the expected tolerable soil erosion (11 tons ha−1 year−1). Due to erosion, about 90% of farmers perceived farmland degradation as described by a progressive decline in crop yield. Farmers used to practice traditional techniques to reduce erosion and government introduced conservation measures such as soil and stone bunds. However, many farmers did not use well-promoted conservation measures such as bunds, which could have negative impact on long-term erosion control effort and sustainable implementation of the conservation options. Among the assessed explanatory variables, educational level, farm distance from home, slope of the cultivated land, and frequency of extension contact were significantly affected (p < 0.05) farmers’ sustainable use of conservation measures. Development planners and policy makers are advised to consider site-specific and innovative approaches to implement conservation measures in sustainable approach in the smallholder crop-livestock mixed agriculture system.
Analysis of immune cell infiltration characteristics in severe acute pancreatitis through integrated bioinformatics
Authors: Xiao Shuai , Han Xiao , Bai Shuhui , Chen Rui 
Published: April 2024

AbstractThe etiopathogenesis of severe acute pancreatitis (SAP) remains poorly understood. We aim to investigate the role of immune cells Infiltration Characteristics during SAP progression. Gene expression profiles of the GSE194331 dataset were retrieved from the GEO. Lasso regression and random forest algorithms were employed to select feature genes from genes related to SAP progression and immune responses. CIBERSORT was utilized to estimate differences in immune cell types and proportions and the relationship between immune cells and gene expression. We performed pathway enrichment analysis using GSEA to examine disparities in KEGG signaling pathways when comparing the two groups. Additionally, CMap analysis was executed to identify prospective small molecular compounds. The three hub genes (CBLB, JADE2, RNF144A) were identified that can predict SAP progression. Analysis of CIBERSORT and TISIDB databases has shown that there are significant differences in immune cell expression levels between the normal and SAP groups, and three hub genes (CBLB, JADE2, RNF144A) were highly correlated with multiple immune cells, regulating the characteristics of immune cell infiltration in the microenvironment. Finally, drug prediction through the Connectivity Map database suggested that compounds such as Entecavir, KU-0063794, Y-27632, and Antipyrine have certain effects as potential targeted drugs for the treatment of SAP. CBLB, JADE2, and RNF144A are hub genes in SAP, potentially playing important roles in SAP progression. This finding further broadens the understanding of the etiopathogenesis of SAP and provides a feasible basis for future research on diagnostic and immunotherapeutic targets for SAP.
Intelligentization helps the green and energy-saving transformation of power industry-evidence from substation engineering in China
Authors: Liang Minxin , Liu Lingzi , Liang Weigao , Mi Wei , Ye Kaihui , Gao Jie 
Published: April 2024

AbstractThe coordinated development of intelligence and greening is an intrinsic demand for high-quality economic and social development. Intelligentization and greening are the leading directions of sustainable development of the power industry. This paper directs of sustainable development of the power industry. This paper empirically analyzes the effect and mechanism of intelligence on the green environmental friendliness of electric power substations by using a panel fixed-effects model and instrumental variable regression, using substation engineering data from China southern power grid during 2013–2022. It is found that the level of intelligence significantly promotes the green performance of substation projects, and this conclusion still holds after a series of robustness tests. Intelligence can reduce material waste and pollutant emissions by improving the engineering environmental monitoring capability and the refinement of engineering resource control, thus improving the environmental friendliness of the project. The research in this paper helps to promote the integrated development of intelligent and green power engineering, to better achieve economic and green goals.
Mitigating methane emissions and global warming potential while increasing rice yield using biochar derived from leftover rice straw in a tropical paddy soil
Authors: Somboon Saowalak , Rossopa Benjamas , Yodda Sujitra , Sukitprapanon Tanabhat-Sakorn , Chidthaisong Amnat , Lawongsa Phrueksa 
Published: April 2024

AbstractThe sustainable management of leftover rice straw through biochar production to mitigate CH4 emissions and enhance rice yield remains uncertain and undefined. Therefore, we evaluated the effects of using biochar derived from rice straw left on fields after harvest on greenhouse gas emissions, global warming potential (GWP), and rice yield in the paddy field. The experiment included three treatments: chemical fertilizer (CF), rice straw (RS, 10 t ha−1) + CF, and rice straw-derived biochar (BC, 3 t ha−1 based on the amount of product remaining after pyrolysis) + CF. Compared with CF, BC + CF significantly reduced cumulative CH4 and CO2 emissions, net GWP, and greenhouse gas emission intensity by 42.9%, 37.4%, 39.5%, and 67.8%, respectively. In contrast, RS + CF significantly increased cumulative CH4 emissions and net GWP by 119.3% and 13.8%, respectively. The reduced CH4 emissions were mainly caused by the addition of BC + CF, which did not increase the levels of dissolved organic carbon and microbial biomass carbon, consequently resulting in reduced archaeal abundance, unlike those observed in RS + CF. The BC + CF also enhanced soil total organic carbon content and rice grain yield. This study indicated that using biochar derived from leftover rice straw mitigates greenhouse gas emissions and improves rice productivity in tropical paddy soil.
OPN silencing reduces hypoxic pulmonary hypertension via PI3K-AKT-induced protective autophagy
Authors: Zhou Rui , Li Ran , Ding Qi , Zhang Yuwei , Yang Hui , Han Ying , Liu Chuanchuan , Liu Jie , Wang Shenglan 
Published: April 2024

AbstractHypoxic pulmonary hypertension (HPH) is a pulmonary vascular disease primarily characterized by progressive pulmonary vascular remodeling in a hypoxic environment, posing a significant clinical challenge. Leveraging data from the Gene Expression Omnibus (GEO) and human autophagy-specific databases, osteopontin (OPN) emerged as a differentially expressed gene, upregulated in cardiovascular diseases such as pulmonary arterial hypertension (PAH). Despite this association, the precise mechanism by which OPN regulates autophagy in HPH remains unclear, prompting the focus of this study. Through biosignature analysis, we observed significant alterations in the PI3K-AKT signaling pathway in PAH-associated autophagy. Subsequently, we utilized an animal model of OPNfl/fl-TAGLN-Cre mice and PASMCs with OPN shRNA to validate these findings. Our results revealed right ventricular hypertrophy and elevated mean pulmonary arterial pressure (mPAP) in hypoxic pulmonary hypertension model mice. Notably, these effects were attenuated in conditionally deleted OPN-knockout mice or OPN-silenced hypoxic PASMCs. Furthermore, hypoxic PASMCs with OPN shRNA exhibited increased autophagy compared to those in hypoxia alone. Consistent findings from in vivo and in vitro experiments indicated that OPN inhibition during hypoxia reduced PI3K expression while increasing LC3B and Beclin1 expression. Similarly, PASMCs exposed to hypoxia and PI3K inhibitors had higher expression levels of LC3B and Beclin1 and suppressed AKT expression. Based on these findings, our study suggests that OPNfl/fl-TAGLN-Cre effectively alleviates HPH, potentially through OPN-mediated inhibition of autophagy, thereby promoting PASMCs proliferation via the PI3K-AKT signaling pathway. Consequently, OPN emerges as a novel therapeutic target for HPH.
Label-free Brillouin endo-microscopy for the quantitative 3D imaging of sub-micrometre biology
Authors: La Cavera Salvatore , Chauhan Veeren M. , Hardiman William , Yao Mengting , Fuentes-Domínguez Rafael , Setchfield Kerry , Abayzeed Sidahmed A. , Pérez-Cota Fernando , Smith Richard J. , Clark Matt 
Published: April 2024

AbstractThis report presents an optical fibre-based endo-microscopic imaging tool that simultaneously measures the topographic profile and 3D viscoelastic properties of biological specimens through the phenomenon of time-resolved Brillouin scattering. This uses the intrinsic viscoelasticity of the specimen as a contrast mechanism without fluorescent tags or photoacoustic contrast mechanisms. We demonstrate 2 μm lateral resolution and 320 nm axial resolution for the 3D imaging of biological cells and Caenorhabditis elegans larvae. This has enabled the first ever 3D stiffness imaging and characterisation of the C. elegans larva cuticle in-situ. A label-free, subcellular resolution, and endoscopic compatible technique that reveals structural biologically-relevant material properties of tissue could pave the way toward in-vivo elasticity-based diagnostics down to the single cell level.
Cytoskeletal rearrangement precedes nucleolar remodeling during adipogenesis
Authors: Potolitsyna Evdokiia , Pickering Sarah Hazell , Bellanger Aurélie , Germier Thomas , Collas Philippe , Briand Nolwenn 
Published: April 2024

AbstractDifferentiation of adipose progenitor cells into mature adipocytes entails a dramatic reorganization of the cellular architecture to accommodate lipid storage into cytoplasmic lipid droplets. Lipid droplets occupy most of the adipocyte volume, compressing the nucleus beneath the plasma membrane. How this cellular remodeling affects sub-nuclear structure, including size and number of nucleoli, remains unclear. We describe the morphological remodeling of the nucleus and the nucleolus during in vitro adipogenic differentiation of primary human adipose stem cells. We find that cell cycle arrest elicits a remodeling of nucleolar structure which correlates with a decrease in protein synthesis. Strikingly, triggering cytoskeletal rearrangements mimics the nucleolar remodeling observed during adipogenesis. Our results point to nucleolar remodeling as an active, mechano-regulated mechanism during adipogenic differentiation and demonstrate a key role of the actin cytoskeleton in defining nuclear and nucleolar architecture in differentiating human adipose stem cells.