bluuebunny/crossref_metadata_2025_split huggingface dataset:
RNA Interference of Sitobion avenae Voltage-gated Sodium Channels for improved grain aphid resistance
Authors: Shafqat Javeria , Afroz Amber 
Published: January 2024

Abstract

Sitobion avenae presents a major challenge, leading to significant reductions in wheat yield per year. This study aimed to explore the potential of targeting Voltage-gated Sodium Channels (VGSCs) in S. avenae through RNA interference as a means to combat this pest. Two-dimensional polyacrylamide gel electrophoresis was conducted to identify RNAi targets in S. avenae. VGSCs were amplified by reverse transcriptase PCR, sequenced, and deposited in Gen Bank. The ID allotted was OR777606. ERNAi was utilized to generate 143 small interfering RNA (siRNA) sequences and one double-stranded RNA target. Phylogenetic analysis revealed evolutionary links between the VGSCs gene in grain aphids and related aphid species like peach, potato, pea, and Russian wheat aphids. VGSCs are essential transmembrane proteins crucial for nerve cell action potentials and are common targets in commercial insecticides. While RNAi has traditionally been employed in functional genomics, it is increasingly recognized as a promising tool for agricultural pest control. Quantitative real-time PCR analysis revealed aphid mortality, decreased fecundity, and shortened lifespan; attributable to the down-regulation of VGSCs gene expression (35%), and mortality up to 61% among 3rd instar nymphs. Additionally, adult aphids exposed to dsVGSCs during their nymph stage exhibited reduced reproductive capacity and longevity. The findings suggest VGSCs as a promising RNAi target; having potential applications in agricultural pest management.
Aurora-A Regulating Cervical Cancer Invasion and Metastasis through ARPC4
Authors: Yue Yaqing , Mu Zhaoxia , Wang Xibo , Liu Yan 
Published: January 2024

Abstract
Objective：To investigate the impact of ARPC4 knockdown on cervical cancer cells with Aurora-A overexpression in terms of proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT).
Methods:Gene expression profiling by RNA-seq, qPCR, and Western blotting were used to identify genes potentially regulated by Aurora-A. The proliferation, migration, and invasion abilities of the control and experimental groups were assessed using EDU fluorescence detection, cloning, scratch, and transwell assays. The molecular mechanism underlying ARPC4 regulation by Aurora-A was explored using Western blot analysis.
Results:ARPC4 expression was found to decrease in Aurora-A knockdown cells and increase in Aurora-A overexpression cells. Patients with high ARPC4 expression had significantly shorter overall survival compared to those with low expression. Knockdown of ARPC4 counteracted the proliferation of cervical cancer cells induced by Aurora-A overexpression. Migration and invasion capabilities were suppressed in Aurora-A overexpression cell lines following ARPC4 knockdown. Aurora-A activation of the NF-κB p65 signaling pathway led to an upregulation of ARPC4 expression.
Conclusion:ARPC4 expression is regulated by Aurora-A, and its knockdown mitigates the effects of Aurora-A overexpression on cervical cancer cells. Aurora-A activation of the NF-κB p65 signaling pathway upregulates ARPC4 expression, providing a potential therapeutic target for cervical cancer treatment.
Overexpression of ADAM10 correlates with poor prognosis and immune infiltrates in breast cance
Authors: Lin Lishuang , Sun Renjing , Hu Xiaomu , Du Zunguo , Zhou Zhongwen , Chen Zhongqing , Tang Feng , Cheng Yuanyuan 
Published: January 2024

Abstract
Introduction: Breast cancer is still challenging despite advanced therapies. Disintegrin and metalloproteinase 10 (ADAM10) is best known for shedding the extracellular domain of transmembrane proteins, such as Notch, EGFR, HER2, E-cadherin, CD44, thus participating in carcinogenesis. Here, we performed a comprehensive analysis about the clinicopathological features, predictive value of ADAM10 and immune profiles in breast cancer. Methods: ADAM10 genomic, transcriptome, prognostic data, and immune profiles in breast cancer were retrieved from the Oncomine, The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA) and Genotype-Tissue Expression (GTEx) databases. They were analysed with ggpolt2, survminer, GSVA R packages or online tools. Clinical data of breast cancer patients were collected from Huashan Hospital. ADAM10 protein expression was detected by immunohistochemistry. The correlation between clinicopathological characteristics and ADAM10 protein expression were analysed by logistic regression, and prognostic value of ADAM10 were evaluated by Kaplan-Meier method and Cox regression. Results: ADAM10 mRNA was overexpressed in breast cancer compared with normal tissues. Luminal A, luminal B and HER2-enriched subtypes showed higher ADAM10 mRNA levels of than basal-like group. Gene alterations in ADAM10, high mRNA and protein levels of ADAM10 correlate with worse prognosis. HER2-enriched subtype tended to have a favourable OS with low ADAM10 expression. In addition, ADAM10 is associated with specific immune cells (T helper, Tcm, Tem cells, etc) and is positively related to PD-L1. Conclusion: High mRNA and protein expression of ADAM10 is associated with adverse outcome. ADAM10 contributes as an independent prognostic factor and a promising therapeutic target in breast cancer.
Impact of Height-to-Mass Ratio on Physical Fitness of German Third-Grade Children
Authors: Bähr Florian , Wöhrl Toni , Teich Paula , Puta Christian , Kliegl Reinhold 
Published: January 2024

Abstract
Physical fitness (PF) is closely related to body constitution, with either height-to-mass ratio (HMR) or body mass index (BMI) as indicators. We compared these indicators for 24,777 third-grade children from 2017–2022 cohorts in cardiorespiratory endurance (6-min run), coordination (star-run), speed (20-m sprint), lower- (standing long jump) and upper limb (ball-push test) muscle power, and static balance (one-legged-stance test; eyes closed). Quadratic HMR predicts children’s physical fitness better than cubic BMI after adjustment for secular trends and the COVID-19 pandemic effects on PF. Except for powerUP, PF scores decreased with increasing body mass relative to height (low HMRs). Boys outperformed girls in five tests (exception balance), but their performance losses were larger with increasing overweight. Surprisingly, after adjustment for quadratic HMR trends, the main effects of sex favored girls (exception powerUP). We propose children’s motor performance, usually normed with age- and sex-specific categories, should be assessed with body height-to-mass ratio.
Surface ligand-regulated renal clearance of MRI/SPECT dual-modality nanoprobes for tumor imaging
Authors: Chen Can , Huang Baoxing , Zhang Ruru , Sun Chaoping , Chen Lei , Ge Jianxian , Zhou Dandan , Li Yueping , Wu Shuwang , Qian Zhiyuan , Zeng Jianfeng , Gao Mingyuan 
Published: January 2024

Abstract
Background
The general sluggish clearance kinetics of functional inorganic nanoparticles tend to raise potential biosafety concerns for in vivo applications. Renal clearance is a possible elimination pathway for functional inorganic nanoparticles delivered through intravenous injection, but largely depending on the surface physical chemical properties of a given particle apart from its size and shape.
Results
In this study, three small-molecule ligands that bear a diphosphonate (DP) group, but different terminal groups on the other side, i.e., anionic, cationic, and zwitterionic groups, were synthesized and used to modify ultrasmall Fe3O4 nanoparticles for evaluating the surface structure-dependent renal clearance behaviors. Systematic studies suggested that the variation of the surface ligands did not significantly increase the hydrodynamic diameter of ultrasmall Fe3O4 nanoparticles, nor influence their magnetic resonance imaging (MRI) contrast enhancement effects. Among the three particle samples, Fe3O4 nanoparticle coated with zwitterionic ligands, i.e., Fe3O4@DMSA, exhibited optimal renal clearance efficiency and reduced reticuloendothelial uptake. Therefore, this sample was further labeled with 99mTc through the DP moieties to achieve a renal-clearable MRI/single-photon emission computed tomography (SPECT) dual-modality imaging nanoprobe. The resulting nanoprobe showed satisfactory imaging capacities in a 4T1 xenograft tumor mouse model. Furthermore, the biocompatibility of Fe3O4@DMSA was evaluated both in vitro and in vivo through safety assessment experiments.
Conclusions
We believe that the current investigations offer a simple and effective strategy for constructing renal-clearable nanoparticles for precise disease diagnosis.
Unveiling Public Attitudes and Themes Towards Heart Failure in China on Baidu Tieba: A Data Mining Study
Authors: Yuan Qiuchen , Wei Xiaolei , Li Shuping , Gao Rui , Liang Tao 
Published: January 2024

Abstract
Background
The prevalence of heart failure is continually increasing, impacting various regions and populations. The application of online communities in healthcare has emerged as a significant area of research. However, the exploration of Chinese public attitudes and content regarding heart failure from a popular perspective remains uncharted.
Objective
Describing the sentimental attitudes and main themes of Posts by Users on the “Heart Failure Bar” in Baidu Tieba.
Methods
Data were processed using Python programming. Comments from the "Heart Failure Bar" in Baidu Tieba were collected, followed by data cleaning, preprocessing, saving, and analysis.
Findings
A total of 37,495 comments were included, with themes encompassing “symptom and experience sharing”, “concerns about the quality of life”, “seeking advice and providing recommendations”, and “sharing resource”. Of the 22,371 "sentiment sentences" subjected to sentiment analysis, 2,258 were positive, 5,004 moderately positive, 6,765 neutral, 5,316 moderately negative, and 3,028 negative. The average sentiment score of the texts was 0.36, indicating an overall moderately negative public attitude towards heart failure.
Conclusions
Users related to heart failure in China have a strong desire for more professional medical services. Regional disparities in medical standards present a significant issue. Online communities demonstrate potential in bridging gaps in healthcare services.
Hopefulness and hopelessness rate in Iranian society: a cognitive view
Authors: Meshkinfam Mehrdad , Naghzguy-Kohan Mehrdad 
Published: January 2024

Abstract
This paper seeks to demonstrate the rate and cognitive model of hopelessness and hopefulness in the Iranian society over a period of five decades spanning from the 1970s up until the 2010s, in response to the perspective that Iranians are currently experiencing more hopelessness than in the past. The prevailing emotions within a society, including but not limited to hopelessness and hopefulness, could be reflected through language. In fact, these two, alongside others, are encoded in language using cognitive mechanisms such as the conceptual metaphor and linguistic construction. Based on the written and spoken corpus encompassing movies, novels, news broadcasts, official speeches and the models employed, namely Kövecses (2020) and the findings of Construction Grammar, it can be observed that hopefulness and hopelessness have exhibited a fluctuating pattern in every subset of the corpus over the mentioned five decades. The rationale for selecting these five decades is associated with pivotal political and social events, such as the Islamic revolution of Iran, the Iran-Iraq war, the reconstruction period, the reformation decade, and the post-reformation era. The results illustrate that the emotion of hopelessness has significantly and consistently increased in the Iranian society over the fifty-year period. Moreover, regarding the cognitive model of hope, it is worth mentioning that Iranians consider "hopelessness" as ‘inability’ and contrast it with "hopefulness" which is conceptualized by ‘object’ and ‘reliance on another entity’.
Deep Learning based Swapping Generative Framework for Rapid Cloth Retrieval
Authors: P Ajitha Gladis K. , R Srinivasan , S Sangeethapriya , P Jayapriya 
Published: January 2024

Abstract
Modern life is fast-paced, and every people is very busy with their daily routines. The online shopping option in E-commerce is a great time-saver in such a scenario. Moreover, it is crucial to extract accurate product features in order to search, recommend, classify, and retrieve images based on fashion queries.To overcome the forementioned challenges, a novel cloth swapping GAN based fashion retrieval has been introduced for rapid retrieval of relevant fashion based on the user query. Initially, to reduce the computational time, GrabCut is used to remove the background of the cloth images.The Cloth encoding decoding-based parsing Network is introduced to segment the bottom and top of the cloth. Then, the separated cloth region is fed into the GAN based on the user preference. The threshold neural network (TNN) is integrated with gates for efficient feature extraction in a small fraction of time. The feature extraction process is performed based on the feedback of the user. The extracted features such as dress length (long, medium, short), dress sleeve (sleeveless, full sleeve, half sleeve), and dress pattern (designs, dots, straights) are used to retrieve the relevant clothes for the users based on the query from the online shops. The proposed model achieves atotal accuracy of 99.29%. The proposed cloth retrieval system enhances the total accuracy by 14.24%, 8.75%, and 23.55% better than Alexnet, cGAN, and CNN, respectively.
Exploring the Influence of Lifestyle on Aquatic Product Preferences: An Investigation with Brazilian Consumers
Authors: Presenza Leandro , Armelin Danylo Augusto 
Published: January 2024

Abstract
Globally, the consumption of aquatic foods has experienced significant growth in recent decades, primarily propelled by the expansion of the aquaculture sector. This growth can be attributed to adopting more sustainable production practices, increased supply, and greater awareness of the health benefits of these foods. Aquatic foods represent a potential alternative for meeting the dietary needs of future populations, particularly as sources of animal-origin foods. Despite the considerable interest in promoting higher consumption levels of aquatic products, research is scarce on this sector's approaches to consumption and consumer perspectives, and it has been somewhat neglected. This study aimed to investigate the relationship between consumers' lifestyles and their patterns of aquatic foods consumption in Brazil. Various behaviors and consumption profiles related to aquatic foods were identified through a series of 13 questions addressing food preferences and decision-making criteria. These patterns were analyzed based on sociodemographic and cultural factors. It was observed that gender, age, region, and socioeconomic-demographic indicators significantly influenced lifestyle responses, impacting aquatic foods choices and consumption patterns. The results indicate that consumers of aquatic foods are aware of emerging concerns associated with food systems, particularly the balance between sustainability and the consumption of animal-origin products. However, variations were observed in different consumer groupings concerning the relationship between lifestyle and the consumption of aquatic foods.
Evaluation of QCNN-LSTM for Disability Forecasting in Multiple Sclerosis using Sequential Multisequence MRI
Authors: Mayfield John , Naqa Issam El 
Published: January 2024

Abstract
Introduction
Quantum Convolutional Neural Network (QCNN) - Long Short-Term Memory (LSTM) models were studied to provide sequential relationships for each timepoint in MRIs of patients with Multiple Sclerosis (MS). In this pilot study, we compare three QCNN-LSTM models for binary classification of MS disability benchmarked against classical neural network architectures. Our hypothesis is that quantum models will provide competitive performance.
Methods
Matrix Product State (MPS), Reverse Multistate Entanglement Renormalization Ansatz (MERA), and Tree-Tensor Network (TTN) circuits were paired with LSTM layer to process near-annual MRI data of patients diagnosed with MS. These were benchmarked against a Visual Geometry Group (VGG16)-LSTM and a Video Vision Transformer (ViViT). Predicted logits were measured against ground truth labels of each patient’s Extended Disability Severity Score (EDSS) using binary cross-entropy loss. Training/Validation/Holdout Testing was partitioned using 5-fold cross validation with a total split of 60:20:20. Levene’s test of variance was used to measure statistical difference and Student’s t-test for paired model differences in mean.
Results
The MPS-LSTM, Reverse MERA-LSTM, and TTN-LSTM had holdout testing ROC-AUC of 0.70, 0.77, and 0.81, respectively (p-value 0.915). VGG16-LSTM and ViViT performed similarly with ROC-AUC of 0.73 and 0.77, respectively (p-value 0.631). Overall variance and mean were not statistically significant (p-value 0.713), however, time to train was significantly faster for the QCNN-LSTMs (39.4 seconds per fold vs. 224.3 and 217.5, respectively, p-value <0.001).
Conclusion
QCNN-LSTM models perform competitively compared to their classical counterparts with greater efficiency in train time. Clinically, these can add value in terms of efficiency to time-dependent deep learning prediction of disease progression based upon medical imaging.
Effects of Autoclaving and Disinfection on 3D Dental Surgical Guides: Evaluating Mechanical Integrity and Dimensional Accuracy in LCD Technology for Implant Procedures
Authors: labakoum badreddine , Farhan Amr , taleb Lhoucine ben , Mouhsen Azeddine , lyazidi Aissam 
Published: January 2024

Abstract
The utilization of surgical guides can improve the precision of implant placement and minimize procedural errors and their related complications. This research aims to evaluate the impact of disinfection and sterilization methods on the dimensional changes of drill guide templates and the mechanical characteristics of 3D-printed surgical guides produced using LCD technology. A total of 100 samples were produced. Forty surgical guides were fabricated to assess implant drill guides' surface and geometric properties. Sixty samples were subjected to mechanical tests to analyze the materials' tensile, flexural, and compressive properties. Based on each analytical method, the samples were classified into four groups: GC, control group; GA, subjected to autoclave sterilization at 121°C (+ 1 bar, 20 minutes); GB, subjected to autoclave sterilization at 134°C (+ 2 bar, 10 minutes); and GL, disinfected with 70% isopropyl alcohol for 20 minutes. The results show that sterilization at 121°C and 134°C affects the mechanical and geometric characteristics of the surgical guides, while disinfection with 70% isopropyl alcohol gives better results.
Genetic association between immune cells and gout: A Mendelian randomization study
Authors: Wang Qing , Liu Tian , Jia Changxin , Shen Liyan , Wang Ping , Li Chengqian , Wang Yangang , He Qing 
Published: January 2024

Abstract
Background
Numerous studies have demonstrated a significant correlation between immune cells and the initiation and progression of gout. Nevertheless, the existing body of evidence concerning immune cells implicated in gout and the establishment of a causal relationship remain limited.
Objective
To evaluate the causal connection between immune cells and gout, Mendelian randomization (MR) analysis was conducted using single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs).
Methods
This investigation revealed genetic variations known as single-nucleotide polymorphisms (SNPs) associated with 731 immune cell signatures from the International Working Group (IEU) open genome-wide association study (GWAS). The gout-associated GWAS dataset was obtained from ebi-a-GCST001790. The finn-b-M13_GOUT dataset was subsequently used for validation. We conducted MR analyses separately for the two gout datasets, followed by a meta-analysis. Causal effects were estimated using the inverse variance weighted (IVW) and MR‒Egger methods for MR analyses. Horizontal pleiotropy, heterogeneity and leave-one-out analyses were performed for sensitivity analysis. SNP annotations were performed to identify significant risk genes associated with immune cells and gout.
Results
IVW analyses revealed that 42 and 45 immunophenotypes were causally associated with gout in the discovery dataset and the validation dataset, respectively. A meta-analysis of the MR estimates from the two datasets revealed that CD25 on CD39 + CD4 + T cells and CD11b on CD14 + monocytes were risk factors for gout, while CD27 on switched memory B cells was a protective factor against gout. No evidence was found for horizontal pleiotropy or heterogeneity in the sensitivity analysis of any causal associations. At the locus-wide significance level of immunophenotyping, we annotated SNPs and identified 46 host genes that may be associated with the pathogenesis of gout.
Conclusion
The present study used MR analysis to demonstrate the causal associations between immune cells and gout via genetic means. This study provides some instructive suggestions for clinical treatment and experimental research in the future.
Traffic Sign Sensing: A Deep Learning approach for enhanced Road Safety
Authors: Gupta Amogh , Mhala Prit , Mangal Manan , Yadav Krish , Sharma Sanjeev 
Published: January 2024

Abstract

There exists paramount importance of traffic signs in ensuring road safety and efficiency, emphasizing their role in communicating vital informa- tion and regulations, transcending language barriers, and aiding drivers in navigating roads and avoiding potential dangers. In light of this significance, our study focuses on harnessing object detection technology, specifically ap- plied to traffic signs, with the goal of accident prevention and enhanced road safety. The dataset employed for our research is Road Sign Detection, and this paper has implemented the latest YOLOv8 versions and YOLO-NAS-l for object detection. Notably, this work achieved impressive mAP50 values, with YOLOv8m at 94.3%, YOLOv8x at 91.9%, YOLOv8l at 92%, YOLOv8s at 94.9%, and YOLOv8n at 95.3%. However, the best results were obtained by YOLO-NAS-l, with an outstanding mAP50 score of 95.72%. In addition to these individual results, this work conducted a comprehensive comparative study, demonstrating that our model leads to an 8% increase in performance over existing approaches. This paper is of great significance as it addresses a critical aspect of road safety and presents a cutting-edge solution that not only outperforms previous models but also sets a new standard for the industry. This research holds the potential to substantially reduce road accidents and enhance overall road safety, making it an invaluable contribution to the field of computer vision and its practical applications in the real world.