bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Expression of Angiogenesis Genes is Related to Immune Microenvironment and Prognosis of Lung Adenocarcinoma
Authors: Wang Xue , Liu Xijian , Wang Lu , Li Jiuwei , Li Ling , Li Yaxing , Huang Hailiang , Han Tao 
Published: February 2023

Abstract
Objective: Lung adenocarcinoma (LC), the main type of non-small cell lung cancer, has a 5-year survival rate of only 14.6%. Tumor angiogenesis is the primary factor leading to the progression of LC. This study aimed to discuss the role of angiogenesis-related genes(ARGs) in the development and diagnosis of LC.
Methods: Clinical and transcriptomic data of LC patients were downloaded from TCGA and GEO databases and divided into training cohorts and validation cohorts. Combined with the ARGs of the Molecular Signatures Database, cluster analysis was performed to identify new clusrer subgroups. Enrichment analyses were performed to elucidate the underlying mechanisms of subpopulation differences. MCPCounter, CIBERSORT and xCell analysis was used to determine the tumor immune microenvironment (TIM) and the immune status of identified subgroups. Lasso algorithm and multivariate Cox regression analysis were used to construct the prognostic risk model, and combined with the clinical information of patients with LC to verify the effectiveness of the risk model.
Results: We identified 2 cluster subgroups that could significantly predict differential survival based on LC survival prognostic genes and ARGs. Among them, cluster 2 showed a better prognosis and was associated with a high immune score, a high abundance of immune infiltrating cells, and a relatively high immune status. Enrichment analysis revealed that DEGs between the two subgroups were mainly enriched in angiogenesis and immune related pathways. Combined with clinical features, higher risk scores were positively associated with LC worsening of disease progression, predicting poor survival. The validation cohort GSE68465 corroborates the validity of the risk model.
Conclusion: The abnormal expression of ARGs is closely related to the TIM of LC patients. The ARG risk model we constructed can be used to accurately predict the survival prognosis of LC.
Physical characterization of the cage culture of Oreochromis niloticus L. 1758, in the Bukavu sub-basin on Lake Kivu, Democratic Republic of the Congo
Authors: Baguma Gabriel , Cocquyt Christine , Alfred Cubaka Kabagale , Alicet Irenge BwanaMudogo , Furaha Nakangu , Balagizi Akonkwa , Muloingaibalu Mbalassa 
Published: February 2023

Abstract

This work consisted in physically characterizing the floating cages used for farming Tilapia Nile in four bays of the sub-basin of Bukavu on Lake Kivu. The measurement of several parameters such as the depth of the water column and the distance of the cage taken by D-173 Bricodis decameter. The result shows that there are 218 cages of which 156 are exploited and 62 non-exploited. 76 cages are installed at 50 m and 58 cages are located at 6–49 m of the coast. The fact that the water of Lake Kivu is essentially pelagic pushes the fish farmers to place the cages on the littoral. Local cages are more abundant than those offered by FPI/IITA. 54% of the Oreochromis niloticus fry came from the D.R. Congo and 46% from Rwanda. Anthropogenic activities on a catchment scale cause benthic modification and reduce site characteristics. The diverse origin of fry should be discouraged to avoid new exotic species. Environmental impact studies of this culture on the biology and physicochemical parameters in the bays would help to address the environmental challenges of this culture in the Lake Kivu ecosystem.
Assessing the impact of university students’ involvement in the first year of Nurture-U: A national student wellbeing research project
Authors: Dooley Jemima , Ghezal Amina , Gilpin Thomas , Basri Husna Hassan , Humberstone Katy , Lahdelma Amber , Misurya Pranati , Marshall Ellen , Watkins Ed 
Published: February 2023

Abstract
Background
Students experience lower levels of wellbeing than the general, age-matched population. A whole-university approach to mental health is encouraged, which must work for individuals from all backgrounds and experiences. Student input is vital in researching and designing these solutions. Nurture-U is a national, large-scale research project exploring better ways to support student wellbeing, with a Student Advisory Group (SAG) that feeds into project decision making. With the first year of the project now completed, we now critically review the processes and effectiveness of the SAG and how well the project is engaging and working with students.
Method
Assessment of the SAG’s impact on the project, the student advisors, and the researchers was undertaken through a content analysis of team meetings and collection of advisor and researcher feedback using the Patient Engagement Quality Guidance Tool.
Results
142 students worked on different tasks in the first year of the Nurture-U project. The SAG was involved in the project branding and marketing, and in the development and co-design of interventions and tools. They reported a positive experience, with involvement boosting confidence. They felt valued but reported not always knowing whether their input was implemented in final decisions. They also recommended different methods of providing feedback. Researchers rated student input highly in their ability to communicate the viewpoint of a different generation and increase the relevance of the study, but also suggested improvements follow-up communication with students.
Conclusions
This critical reflection process of the SAG’s public advisor role in this large-scale research project was important in highlighting what worked well and areas to work on. As the project unfolds, we aim to adapt our methods of student input, increase the transparency of decision-making processes, and in turn increase student-led decision making within the project.
Removal of heavy metal ions from aqueous solution using biotransformed lignite as a low-cost adsorbent
Authors: Cheng Jianguo , Zhang Shanfei , Ma Litong , Duan Jianguo , Fang Xu , Li Rihong , Zhao Wenyuan , Liu Yunying , Wang Xiaoxia 
Published: February 2023

Abstract
Heavy metal pollution caused by industrial wastewater such as mining and metallurgical wastewater is a major global concern. Therefore, this study used modified lignite as a low-cost adsorbent for heavy metal ions. Pingzhuang lignite was dissolved and modified using Fusarium lignite B3 to prepare a biotransformed-lignite adsorbent (BLA). The O, H, and N contents of the BLA increased after transformation, and the specific surface area increased from 1.81 to 5.66 m2·g-1. Various adsorption properties were investigated using an aqueous solution of Cu(II). The kinetic and isothermal data were well fitted by pseudo-second-order and Langmuir models, respectively. The Langmuir model showed that the theoretical Cu(II) adsorption capacity was 71.47 mg·g-1. Moreover, large particles and a neutral pH were favorable for the adsorption of heavy metal ions. The adsorption capacities of raw lignite and BLA were compared for various ions. Microbial transformation greatly improved the adsorption capacity, and the BLA had good adsorption and passivation effects with Cu(II), Mn(II), Cd(II), and Hg(II). Investigation of the structural properties showed that the porosity and specific surface area increased after biotransformation, and there were more active groups such as –COOH, Ar–OH, and R–OH, which were involved in the adsorption performance.
Uncovering the ceRNA network related to the prognosis of stomach adenocarcinoma among 898 patient samples
Authors: LIU Zhe , LIU Fang , PETINRIN Olutomilayo Olayemi , WANG Fuzhou , ZHANG Yu , WONG Ka-Chun 
Published: February 2023

Abstract

Background. Stomach adenocarcinoma (STAD) patients are often associated with significantly high mortality rates and poor prognoses worldwide. Among STAD patients, competing endogenous RNAs (ceRNAs) play key roles in regulating one another at the post-transcriptional stage by competing for shared miRNAs.Methods. In this study, we aimed at elucidating the roles of lncRNAs in the ceRNA network of STAD, uncovering the molecular biomarkers for target therapy and prognosis. Specifically, a multitude of differentially expressed lncRNAs, miRNAs, and mRNAs (i.e. 898 samples in total) was collected and processed from TCGA. Cytoplasmic lncRNAs were kept for evaluating overall survival (OS) time and constructing the ceRNA network. Differentially expressed mRNAs in the ceRNA network were also investigated for functional and pathological insights.Results. Interestingly, we identified one ceRNA network including 13 lncRNAs, 25 miRNAs, and 9 mRNAs. Among them, 13 RNAs were found related to the patient survival time; their individual risk score can be adopted for prognosis inference. Finally, we constructed a comprehensive ceRNA regulatory network for STAD and developed our own risk-scoring system that can predict the OS time of STAD patients by taking into account the above.
Progressive inflammation reduces high frequency EEG activity and cortical dendritic arborisation in late gestation fetal sheep
Authors: Kelly Sharmony B. , Dean Justin M. , Zahra Valerie A. , Dudink Ingrid , Thiel Alison , Polglase Graeme R. , Miller Suzanne L. , Hooper Stuart B. , Bennet Laura , Gunn Alistair J. , Galinsky Robert 
Published: February 2023

Abstract
Background
Antenatal infection/inflammation is associated with disturbances in neuronal connectivity, impaired cortical growth and poor neurodevelopmental outcomes. The pathophysiological substrate that underpins these changes is poorly understood. We tested the hypothesis that progressive inflammation in late gestation fetal sheep would alter cortical neuronal microstructure and neural function assessed using electroencephalogram band power analysis.
Methods
Fetal sheep (0.85 of gestation) were surgically instrumented for continuous electroencephalogram (EEG) recording and randomly assigned to repeated saline (control; n = 9) or LPS (0 h = 300 ng, 24 h = 600 ng, 48 h = 1200 ng; n = 8) infusions to induce inflammation. Sheep were euthanized 4 days after the first LPS infusion for assessment of inflammatory gene expression, histopathology and neuronal dendritic morphology in the somatosensory cortex.
Results
LPS infusions increased delta power between 8 and 50 hours, with reduced beta power from 18 to 96 hours (P < 0.05 vs. control). Basal dendritic length, numbers of dendritic terminals, dendritic arborisation and numbers of dendritic spines were reduced in LPS exposed fetuses (P < 0.05 vs. control) within the somatosensory cortex. Numbers of microglia and interleukin (IL)-1β immunoreactivity were increased in LPS-exposed fetuses compared with controls (P < 0.05). There were no differences in total numbers of cortical NeuN + neurons or cortical area between the groups.
Conclusions
Exposure to antenatal infection/inflammation was associated with impaired dendritic arborisation, spine number and loss of high frequency EEG activity, that may contribute to disturbed cortical neuronal growth and connectivity.
Application of big data classification effects based on neural network in video English course and relevant optimization suggestions
Authors: Suyun Wen , Suying Zheng 
Published: February 2023

Abstract
Due to the improvement of Internet technology and information technology, more and more students hope to learn and consolidate knowledge through video in the classroom. Teachers are more accustomed to using video in the classroom to improve and improve their teaching quality. In the current English class, teachers and students are more accustomed to using video English for teaching. English teaching videos are informative, intuitive and efficient. Through video teaching, we can make the classroom atmosphere more interesting, thus simplifying complex problems. In this context, this paper analyzes how neural networks can improve the application effect of English video courses in the context of big data, optimizes the pdcno algorithm by using the neural network principle, and then discusses the impact of the optimized pdcno algorithm on classification and system performance. This improves the accuracy of English video, reduces the execution time of the algorithm and reduces the memory occupation. Compared with ordinary video, the training time required under the same training parameters is shorter, and the convergence speed of the model itself will be faster. From the students' attitude towards video teaching, we can see that students prefer video English teaching, which also reflects the effectiveness of neural network big data in English video teaching. This paper introduces the neural network and big data technology into the video English course to improve the teaching effectiveness.
Countering the Covid-19 pandemic in Hong Kong. A Successful Securitization in an Environment of Low Political Trust.
Authors: Stivas Dionysios , Cole Alistair 
Published: February 2023

Abstract
In the context of the COVID-19 pandemic, authorities around the world securitized the virus and enforced unprecedented tactics. A successful securitization presupposes a common understanding between the authorities and the public about the calibre of the threat and the necessity of the extraordinary measures. A trustworthy government should securitize an issue of its preference easier than an untrustworthy government. Hong Kong, our case study, is unique because of the government’s success with securitizing the pandemic in a context of extremely low political trust. Among the exceptional mechanisms that the government of Hong Kong utilized to control the outbreak were smart technologies. This paper examines the extent to which trust in the government and trust in smart technologies influenced the success of the securitization of the COVID-19 pandemic in Hong Kong. To answer this question, we build on publicly available surveys assessing political trust in Hong Kong, on tailormade questionnaires investigating the sentiments of Hong Kong citizens towards smart technologies and on a Focus Group exercise with carefully selected residents of Hong Kong. The results of this study suggest that under certain circumstances, governments can successfully securitize a health-emergency even when they do not enjoy high levels of political trust.
Sine Wave Optimization: A Novel Elitism-Based Search Algorithm
Authors: KÜÇÜK Mustafa 
Published: February 2023

AbstractThis paper presents Sine Wave Optimization (SWO), a novel search algorithm developed to solve global optimization problems using evolutionary computing techniques. The proposed SWO was inspired by Fourier, who stated that a collection of sinusoidal waves could be used to represent any periodic waveform. Such a waveform was considered to be useful for balancing the exploration and exploitation search of the elitist evolution strategies. The exploration and exploitation seem to contradict each other, but their balanced combination is crucial to the success of any metaheuristic algorithm. The exploration enables the search in the solution space to efficiently and effectively explore as many places and regions as possible. On the other side, the exploitation uses the experience of the search process to speed up the convergence, when necessary, by limiting diversification. The proposed method is validated using some comparative mathematical and engineering problems commonly used in the field of optimization. The computational results show that the SWO method is very competitive against another member of the family of evolutionary algorithms, the Genetic algorithm (GA), and its various elitist options. The proposed method, with its simple and useful structure, is expected to have wide applications in real-world engineering problems as well as mathematical optimization problems.
Propagation characteristics of stress waves and failure modes in gray sandstone with a gypsum-filled joint under impact loading
Authors: Liu Huizhen , Yang Liyun , Fang Shizheng , Xu Peng 
Published: February 2023

Abstract
Dynamic mechanical properties of jointed rock mass have an important influence on the stability of geotechnical engineering. In this study, dynamic impacting experiment of gray sandstone samples with gypsum-filled joints was carried out by split Hopkinson pressure bar (SHPB) to study the influence of impact velocity and joint dip angle on wave propagation characteristics and fracture evolution of rock mass, and the failure process were captured by high-speed photography. To supplement and further study, numerical simulation was then presented. Hypermesh software was used to establish the numerical model, and then imported into LS-DYNA for calculation. The results show that the joint changes the stress wave propagation and particle vibration velocity significantly, and leads to a certain difference of stress distribution, which is the fundamental cause of different failure modes. Not only P waves but also shear waves perpendicular to the particle vibration direction are generated in the joint, and the particle vibration velocity in matrix at the non-loading end is obviously weaker than that at loading end. In addition, the initial damage and the dynamic compressive strength of rock mass increase with increasing impact velocity. The fracture is mainly caused by transverse tension in the axial direction and impact velocity influences the damage degree but cannot change the failure mode. The peak compressive strength of jointed gray sandstone decreases first and then increases with the joint dip angle, and the failure mode mainly presents as shear-tensile failure and the separation failure of joint and gray sandstone. Jointed gray sandstones are always under the dominant tensile action, especially with the joint dip angle of 45°.
Autophagy Modulation Attenuates Sorafenib Resistance In HCC Induced In Rats
Authors: Elleithi Yomna , El-Gayar Amal , Amin Mohamed N. 
Published: February 2023

Abstract

Hepatocellular carcinoma (HCC) has risen as the villain of cancer-related death globally, with a usual cruel forecasting. For advanced HCC, sorafenib has been FDA approved as first line treatment. In spite of the bright potential that sorafenib demonstrated in studies, actual clinical results are limited owing to the massive occurrence of drug resistance. The tumor microenvironment (TME) has been linked to therapeutic resistance, indicating that current cellular level approaches may be inadequate to increase treatment efficacy. The involvement of autophagy in cancer is a double-edged knife. On one aspect, autophagy allows malignant cells to withstand strain, such as a hypoxic TME and starvation caused by therapy. on the other side, autophagy plays a vital function in damage prevention, which can decrease carcinogenesis. As a result, regulating autophagy is unquestionably a viable method in the therapy of malignancies. The aim if this study was to investigate the role of autophagy modulation in combination to sorafenib by comparing both induction and inhibition of autophagy to the sorafenib monotherapy of HCC induced in Sprague–Dawley rats. Autophagy, apoptosis and cell cycle were analyzed by using western blot, ELISA, Immunuhistochemistry, flow cytometry and Quantitive-PCR. Routine biochemical testing and pathological examination was carried out. Transmission electron microscope was used to visualize ultracellular structures and autophagic bodies. We found remarkable alleviation of chemotherapeutic resistance and hepatoprotective effects by both regimens. To the best of our knowledge, this study was the first to study the autophagic inhibition simultaneous with autophagic induction in sorafenib treatment in-vivo.
Gelatin-based active edible film with pH-sensing for maintaining and monitoring fish freshness
Authors: Pan Xiaxi , Kong Lingyue , Li Xinying , Li Defu , Mu Changdao , Xu Zhilang , Ge Liming 
Published: February 2023

Abstract
The development of intelligent edible films with food preservation and monitoring function is of great significance and applications. Herein, active intelligent edible films with pH-responsiveness, long term antioxidant and antibacterial activities were prepared base on gelatin. In this work, gelatin was chemically and physically combined with rosmarinic acid (RosA) and blueberry anthocyanins extract (BAE) to fabricate RosA-gelatin/BAE (RGA) films with the crosslinking of dialdehyde starch (DS). We found that the RGA films possess dense micromorphology, robust mechanical property, outstanding light barrier ability and good water resistance property. The introduction of rosmarinic acid and anthocyanins endows the RGA films with admirable long-term antioxidant and antibacterial activities. Significantly, the RGA films exhibit excellent pH/NH3 responsiveness to show visible color change. It is worth noting that the films can real-time monitor and delay the spoilage of fresh fish. Overall, the intelligent and active RGA films possess promising application for food preservation and real-time quality monitoring.
Histopathological Auxiliary System for Brain Tumour (HAS-Bt) based on Weakly Supervised Learning using a WHO CNS5-Style Pipeline
Authors: Ma Yixin , Shi Feng , Sun Tianyang , Chen Hong , Wu Shuai , Lu Junfeng , Zou Yaping , Zhang Jun , Jin Lei , Shen Dinggang , Wu Jinsong 
Published: February 2023

Abstract
Purpose
Classification and grading of central nervous system (CNS) tumours play a critical role in the clinic. When WHO CNS5 simplifies the histopathology diagnosis and places greater emphasis on molecular pathology, artificial intelligence (AI) has been widely used to meet the increased need for an automatic histopathology scheme that could liberate pathologists from laborious work. This study was to explore the diagnosis scope and practicality of AI.
Methods
A one-stop Histopathology Auxiliary System for Brain tumours (HAS-Bt) is introduced based on a pipeline-structured multiple instance learning (pMIL) framework developed with 1,385,163 patches from 1,038 hematoxylin and eosin (H&E) slides. The system provides a streamlined service including slide scanning, whole-slide image (WSI) analysis and information management. A logical algorithm is used when molecular profiles are available.
Results
The pMIL achieved an accuracy of 0.94 in a 9-type classification task on an independent dataset composed of 268 H&E slides. Three auxiliary functions are developed and a built-in decision tree with multiple molecular markers is used to automatically formed integrated diagnosis. The processing efficiency was 443.0 seconds per slide.
Conclusion
HAS-Bt shows outstanding performance and provides a novel aid for the integrated neuropathological diagnostic workflow of brain tumours using CNS 5 pipeline.