bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and validation of a five-necroptosis-related lncRNAs signature for prognostic prediction in hepatocellular carcinoma
Authors: Chen Hao , Lan Tian , Hou Guimin , Xue Shuai , Xu Lin , Feng Qingbo , Wang Haichuan , Zeng Yong 
Published: October 2023

Abstract
Background
Hepatocellular carcinoma (HCC) is one of the most common digestive malignant tumors with poor prognosis. As a kind of death receptor-mediated regulated programmed death, necroptosis has the dual characteristics of necrosis and apoptosis. Long non-coding RNAs (lncRNAs) are reported to be key regulators in tumor necroptosis. This study aimed to identify the necroptosis-related lncRNAs (np-lncRNA) in HCC and investigate their relationships with prognosis.
Method
The RNA-sequencing data and clinicopathological and survival information of patients with HCC were retrieved from The Cancer Genome Atlas (TCGA) database. The np-lncRNAs were analyzed to predict the prognosis of patients with HCC. Stepwise multivariate Cox regression analysis was used to construct prognostic signatures related to necroptosis. Kaplan-Meier (KM) analysis was used to compare the prognosis of patients. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) was used to assess the accuracy of the prognostic signature. Quantitative real-time polymerase chain reaction(qPCR) was used to validate the lncRNAs expression among samples from an independent cohort.
Results
The np-lncRNAs ZFPM2-AS1, AC099850.3, BACE1-AS, KDM4A-AS1 and MKLN1-AS were identified as potential prognostic biomarkers. The area under the curve (AUC) of the prognostic signature constructed by these np-lncRNAs reached 0.773. Patients were divided into two groups based on the risk score calculated by the signature, and poorer overall survival was shown in the high-risk group. Gene Set Enrichment Analysis (GSEA) suggested that tumor-related pathways (mTOR, MAPK and p53 signaling pathways) and immune-related functions (T cell receptor signaling pathway and natural killer cell mediated cytotoxicit) were significantly different between the low risk and high risk group. The increased expression of np-lncRNAs was confirmed in another independent HCC cohort.
Conclusions
This signature is a reliable tool for predicting the prognosis of HCC patients. Our findings provide a subset of np-lncRNA biomarkers for prognosis prediction and personalized treatment of HCC patients.
Long-term alcohol exposure aggravates ischemic stroke-induced damage by promoting pericyte NLRP3 inflammasome activation via the TLR4/NF-κB pathway in rats
Authors: Wang Kaixin , Yang Lingfei , Li Qingsheng , Yang Xuan , Chen Ziyi , Xu Yudi , Chen Yufei , Jia Yanjie , Gong Zhe 
Published: October 2023

Abstract
Background: Alcohol consumption is a common lifestyle worldwide and a manageable risk factor for ischemic stroke. Chronic ethanol exposure reportedly causes blood-brain barrier (BBB) dysfunction and neuroinflammation. Pericytes participate in neuroinflammation during cerebral ischemia. However, whether pericytes are involved in alcohol-induced cerebral ischemia/reperfusion injury remains unclear. Therefore, we investigated the activation of Nod-like receptor protein 3 (NLPR3) inflammasome and Toll-like receptor 4 (TLR4)/ nuclear factor kappa-B (NF-κB) pathway in the pericytes in vivo and in vitro.
Methods: Rat models of long-term alcohol intake followed by transient middle cerebral artery occlusion stroke (EtOH+tMCAO group) and cell models of oxygen-glucose deprivation/reoxygenation (OGD/R) with alcohol co-treatment were constructed.
Results: Worsened infarct volume, neurological scores, and BBB disruption were observed after reperfusion in the EtOH+tMCAO group. Immunofluorescence staining showed increased NLPR3 inflammasome activation in the pericytes at the ischemic penumbra in the alcohol intake group than in the control group. Western blotting showed increased expression of the NLRP3 inflammasome in the pericytes after OGD/R that was significantly amplified by alcohol pretreatment. Alcohol-activated TLR4 in the pericytes in vivo and elevated levels of TLR4/NF-κB pathway-associated protein were observed in the pericytes following alcohol treatment in vitro. Transfecting with TLR4-short hairpin RNA to block TLR4 signaling in OGD/R models with alcohol co-treatment markedly reversed NLRP3 inflammasome activation. In vivo, TAK-242 inhibited TLR4 expression in the EtOH+tMCAO group and alcohol-mediated neurological impairment was significantly alleviated.
Conclusion: Long-term alcohol pretreatment aggravated ischemic stroke-induced brain damage by activating NLRP3 inflammasome and TLR4/NF-κB signaling pathway in the pericytes.
Prognostic characteristics and immunological role of angiogenic factors in epithelial ovarian cancer
Authors: Li Xiaoying , Wu Yingnan , Peng Yanqing , Jia Tianshuang , Gong Liping , Dong Shuang , Sun Litao 
Published: October 2023

Abstract
Background
The combination of antiangiogenic and immune checkpoint inhibitor therapies has emerged as a breakthrough treatment for ovarian cancer (OC). However, the immune effects of angiogenesis-related factors in OC remain to be investigated.
Methods
Using OC single-cell RNA sequencing (scRNA-seq) data (GSE189843) obtained from Gene Expression Omnibus and bulk data from The Cancer Genome Atlas, we identified differentially expressed genes in OC epithelial cells. Furthermore, functional enrichment analysis and gene set enrichment analysis were performed using “clusterProfiler,” followed by univariate Cox regression to identify genes with prognostic significance. The efficiency of the prognostic risk scoring model was evaluated using receiver operating characteristic (ROC) analysis. Angiogenesis-related factors were identified using public databases, and immune analysis of these factors was performed using TIMER and TIDE data.
Results
The functional enrichment analysis revealed that the differentially expressed cancer genes identified in OC epithelial cells were associated with immune functions, including B-cell activation and immunoglobulin complex, and 13 genes were found to have significant prognostic implications. Subsequently, a prognostic risk model comprising four genes (IGKC, KRT19, JCHAIN, and SCNN1A) was constructed. ROC analysis showed favorable performance of the model in terms of discrimination efficiency. Additionally, we identified 25 angiogenic factors specifically expressed in epithelial cells. Importantly, the expressions of angiogenic factors clusterin (CLU) and ceruloplasmin (CP) were found to significantly affect the immune response in OC and showed a strong association with the prognosis of OC patients.
Conclusions
Our study identified prognostic factors in OC epithelial cells and established a prognostic risk model.
Research on SF-YOLONet metal gear end-face defect detection method based on evolutionary algorithm optimization
Authors: Yang Shuai , Zhou Lin , Wang Chen , Wang Shenghuai , Lv Jiang , Wang Qin 
Published: October 2023

Abstract
Some common problems, including the effect of non-detection regions on accuracy, the small size and multi-scale of defects,and the challenge of automatically optimizing neural network hyperparameters, are confronted during the metal gear end-face defect detection, lead to the inadequate performance of accuracy and efficiency, making them unsuitable for meeting the real-time online detection demands in industries. To address the problems above, this study proposes a method SF-YOLONet to detect defects on metal gear end faces by using the Optimized Evolutionary Algorithm. Firstly, a testing platform was constructed to detect surface defects on metal gear end-faces. Subsequently, in order to address the impact of non-detection regions on accuracy, this study introduces the SF algorithm, a visual saliency-based image extraction method, to eliminates interference between ineffective features in non-detection regions and edge burrs. Additionally, A network (YOLONet) for detecting end-face defects in metal gears is introduced, which integrates the CBAM module and BiFPN feature extraction strategy. These advancements enhance adaptive learning and feature extraction for small-sized defects on gear end-face, and combine low-resolution and deep-level semantic information, to detect small and multi-scale defects is enhanced. Finally, the ISSA algorithm is introduced to optimize the hyperparameters of the SF-YOLONet model, thereby avoiding the instability of manual parameterization. The experiment demonstrated that the SF-YOLONet model achieved an average precision of 98.01% and an F1 score of 0.99 on the Metal Gear end-face defect testing dataset. The average computation time for detection per image on the YOLONet model was 0.13 seconds. Compared to other deep learning models, the proposed SF-YOLONet model significantly improves precision and efficiency in detecting defects on gear end-face. This enhancement effectively meets the real-time online detection requirements of industries.
Detecting Potential Market Corner Risk of WTI: A Hybrid Algorithm Anomaly Detection Approach
Authors: LI DUN , Li Hongzhi , Crespi Noel , Minerva Roberto , Farahbakhsh Reza , Shao Wenhao , Raza syed-mohsan , Li Kuan-Ching 
Published: October 2023

Abstract
The price of crude oil is one of the most critical factors of the world economy, as it is volatile and sensibly affected by the macro-economic, thus attracting large-scale speculative activities. Well known for its vulnerability, some price fluctuations are affected by external factors, such as the financial crisis and oil trade war, while others are due to manipulation. Due to such facts, this article aims to clarify the characteristics and features of the market corner in the crude oil future market and detect potential market corner risk in West Texas Intermediate (WTI), and a hybrid anomaly detection approach is proposed. After a detailed overview of the characteristics and definitions of the market corner, the features are extracted by processing actual market data. We first detect suspicious market corners with abnormal prices and volume through the Local Outlier Factor algorithm (LOF). Next, the detected results are used as pseudo-labels, and the entire month's trading behavior is trained and classified through the Support Vector Machine (SVM) and Random Forest (RF) algorithms to identify potential market corners.Experimental results show that the proposed model has excellent accuracy, precision, recall, and F-score, indicating that the model is feasible and has strong robustness. Furthermore, based on the successful detection of potential market corner risk, the model can be further used for individual risk control and overall supervision of the crude oil futures market.
Mitochondrial DNA D-loop A/G Transition at Position 869 as a Reproductive Performance Indicator in Gir Cattle
Authors: Malik Anuj , E.M Sadeesh 
Published: October 2023

Abstract
Reproduction is a critical aspect of livestock production, with mitochondria playing a pivotal role in providing the necessary energy for this high-demanding process. Maternally inherited mitochondria are known to influence various cellular functions, including ATP production and apoptotic regulation, and possess their own genome, including the Displacement loop (D-loop). This study aims to explore the mitochondrial DNA (mtDNA) D-loop SNPs and their potential association with reproductive traits in Gir cattle, an indigenous breed. Two groups of animals were categorized based on their reproductive performance, with good performers demonstrating shorter calving intervals, gestation lengths, days open, and fewer services per conception. Total DNA was isolated from blood samples, and mtDNA D-loop sequences were obtained through Sanger sequencing, resulting in 29 haplotypes. Comparative analysis revealed that animals with poor reproductive performance exhibited a higher number of polymorphic sites, transition/transversion biases, and occurrences of insertions/deletions (INDELs) compared to the good performers. Specifically, good performers showed higher A/G and G/A substitutions, while poor performers exhibited higher T/A, C/A, A/T, G/T, and G/C substitutions. The A/G transition at Position 869 was significantly associated with poor reproductive performance, impacting secondary structure stability and likely affecting energy efficiency. Validation of these findings in a larger Gir cattle population and exploring mtDNA polymorphisms in coding regions may establish a maternal lineage-based biomarker for assessing reproductive efficiency in this indigenous breed. This study sheds light on the significance of mitochondrial genetic factors in shaping reproductive traits and offers insights into sustainable livestock production.
Analysis of the chloroplast genome of Malus baccata var. gracilis
Authors: Qin Xin , Hao Qiang , Wang Xun , Liu Yangbo , Yang Chen , Sui Mengyi , Zhang Yawen , Hu Yanli , Chen Xuesen , Mao Zhiquan , Mao Yunfei , Shen Xiang 
Published: October 2023

Abstract
Malus baccata var. gracilis has high ornamental value and breeding significance, and comparative chloroplast genome analysis was applied to facilitate genetic breeding for desired traits and resistance and provide insight into the phylogeny of this genus. Using data from whole-genome sequencing, a tetrameric chloroplast genome with a length of 159,992 bp and a total GC content of 36.56% was constructed. The M. baccata var. gracilis chloroplast genome consists of a large single-copy area (88,100 bp), a short single-copy region (19,186 bp), and two inverted repeat regions, IRa (26,353 bp) and IRb (26,353 bp). This chloroplast genome contains 112 annotated genes, including 79 protein-coding genes (nine multicopy), 29 tRNA genes (eight multicopy), and four rRNA genes (all multicopy). Calculating the relative synonymous codon usage revealed a total of 32 high-frequency codons, and the codons exhibited a biased usage pattern towards A/U as the ending nucleotide. Interspecific sequence comparison and boundary analysis revealed significant sequence variation in the vast single-copy region as well as generally similar expansion and contraction of the SSC and IR sections for ten analyzed Malus species. M. baccata var. gracilis and Malus hupehensis were grouped together into one branch based on the phylogenetic analysis of chloroplast genome sequences. The chloroplast genome of Malus species provides an important foundation for species identification, genetic diversity analysis, and Malus chloroplast genetic engineering. Additionally, the results can facilitate the use of pendant traits to improve apple tree shape.
Necroptosis-associated long noncoding RNA predicts prognosis for cervical cancer in a microenvironment signature associated with anti-tumor immune responses
Authors: Yang Jun , Ma Zhenglai , Yu Haibin , Zhang Yuening 
Published: October 2023

Abstract

Background: Cancer has high incidence rate, poor prognosis and high intratumoral heterogeneity. Necrosis is an important cellular signaling pathway in tumor cells, which can overcome the resistance of tumor cells to apoptosis. To investigate the relationship between CC and necrosis, we established a prognostic model based on necrosis related genes to predict the overall survival (OS) of CC patients.
Methods: We obtained gene expression data and clinical information of cervical cancer patients from the Cancer Genome Map (TCGA). By detecting differential gene expression between tumors and normal tissues, 43 differentially expressed necrosis related lncRNAs (NRLs) were identified. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression and univariate and multivariate Cox regression analysis were used to screen for NRLs associated with patient prognosis. We have established prognostic markers including AC022137.3, AC024270.3, AC010542.5, AC010536.2, U91328.1, and AL021978.1. According to the prognosis model, patients are divided into high-risk or low-risk subgroups with different survival rates. The receiver operating characteristic (ROC) curve analysis is used to determine the predictive accuracy of the model. We conducted stratified analysis on different clinical variables to demonstrate the correlation between the expression level of NRLs identified and clinical variables. We also explored the relationship between the prognostic NRLs and immune-cell infiltration and immune checkpoints.
Results: Based on the differently expressed lncRNAs, we constructed lncRNA signatures. The area under the curve (AUC) of the ROC curve is used to predict 5-year survival rate with a characteristic of 0.757. Subsequent analysis indicates that our features can effectively distinguish adverse survival outcomes. High expression of immune checkpoint related lncRNAs is associated with low risk groups.
Conclusion: We have constructed a new necrosis related lncRNA signal for predicting the prognosis of CC patients and may play a key role in the progression and immune microenvironment of CC.
Systematic Seismic Events Discrimination Methods at the Kenya National Data Centre (N090)
Authors: Mulwa Josphat Kyalo 
Published: October 2023

Abstract
The International Data Centre (IDC) routinely applies event screening or discrimination using a multi-technology approach in order to characterize events as either natural or anthropogenic. Various event discriminants are presented in literature. At the Kenya National Data Centre (KE-NDC or N090), a systematic and step-by-step procedure of SEISMIC events discrimination is applied. Results from the discriminants adopted are obtained within a short time and the discriminants are relatively easy and fast to use. The discriminants used at KE-NDC (N090) are ranked in a hierarchy based on results obtained from one discriminant being applied in subsequent dsicriminants and ease of returning results within the shortest time possible to allow for events discrimination and dissemination of results. The discriminants applied and their hierarchy at KE-NDC include:- (i) event location (epicenter/hypocenter parameters) (ii) hypocenter parameters based on events relocation using HYPOCENTER, (iii) magnitude determination, (iii) mb:Ms criteria and (iv) focal mechanism determination. Two seismic events are used as case examples to demonstrate how events discrimination is achieved based on the discriminants presented herein. The two seismic events are the 20190324 and 20200503 seismic events in the southwestern and northern Kenya respectively. The choice of these two events is based on the fact that they were strong enough to be recorded by a number of global seismic stations and their magnitudes are comparable to the 2009, 2013 and 2016 but slightly lower than the 20170903 DPRK announced tests. Based on the discriminants used and presented herein, the two seismic events were categorized as being due to natural earthquakes.
Design a Hybrid Memory Array for Radiation-Hardened SRAM in Satellite Image Compression Systems
Authors: Sharma Priyanka , Neema Vaibhav 
Published: October 2023

Abstract
In the satellite technology landscape, the satellite industry is crucial across military, meteorology, safety, climate monitoring, and landscape mapping sectors. The demand for high-quality satellite imagery has led to innovations in image processing and compression techniques to overcome challenges such as data storage limitations and slow upload speeds. This paper focuses on optimizing on-board SRAM memory cells for satellite image compression, addressing issues like radiation-induced errors, memory size, and power efficiency. A hybrid memory array is proposed, allocating reliable cells for Most Significant Bits (MSB) and less reliable cells for Least Significant Bits (LSB), optimizing area, power, and data integrity. The research evaluates SRAM cell sensitivity to radiation-induced Single Event Upsets (SEUs), with simulation results indicating smaller cell sizes and lower operating voltages increase susceptibility. Simulate a comparative analysis involving radiation-hardened SRAM cells, including CC18T, RHC14T, RHMC12T, SARP12T, SRRD12T, and PCELL10T, and proposed 12T. Proposed 12T cell is significantly 1.22x/3.77x/3.9x/4.1x/1.86x less write delay then CC18T/RHC14T/RHMC12T/SRRD12T/PCELL10T, respectively. Additionally, 2.27x/1.98x/71.29x lower read access time than RHMC12T/SARP12T/SRRD12T memory cells. The area occupied by our proposed cell is substantially smaller, with it being 2.03x/1.39x/1.18x/1.6x/1.09x less than CC18T/RHC14T/RHMC12T/ SRRD12T / PCELL10T. Furthermore, observed improvements in read, write and hold Noise Margins, and critical charge. Introduced an Electrical Quality Metric (EQM) to provide a comprehensive assessment of SRAM cell performance, and our proposed cell excels in terms of EQM compared to the others.
DNA methylation fine-tunes pro-and anti-inflammatory signalling pathways in inactive ulcerative colitis
Authors: Meng Wei , Fenton Christopher G. , Johnsen Kay-Martin , Taman Hagar , Florholmen Jon , Paulssen Ruth H. 
Published: October 2023

Abstract
Epigenetic changes, like DNA methylation, have been implied to play a role in the immune dysfunction associated with inflammatory bowel disease (IBD) and the disease development of ulcerative colitis (UC). Changes of the DNA methylation and correlated gene expression in patient samples with inactive UC might reveal possible regulatory features important for further treatment options for UC. Bisulfite sequencing and whole transcriptome sequencing were performed on mucosal biopsies from patients with active UC (UC, n = 14), inactive UC (RM, n = 20), and non-IBD patients (NN, n = 11) which served as controls. The differentially methylated regions (DMRs) were identified by DMRseq. Correlation analysis was performed between DMRs and their nearest differentially expressed genes (DEGs). Principal component analysis (PCA) was performed based on correlated DMR regulated genes. DMR regulated genes then were functional annotated. Cell-type deconvolutions were performed based on methylation levels. The comparisons revealed a total of 38 methylation-regulated genes in inactive UC that are potentially regulated by DMRs (correlation p value < 0.1). Several methylation-regulated genes could be identified in inactive UC participating in IL-10 and cytokine signalling pathways such as IL1B, STAT3. DNA methylation events in inactive UC seem to be fine-tuned by the balancing pro- and anti- inflammatory pathways to maintain a prevailed healing process to restore dynamic epithelium homeostasis.