bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon Nanotubes Enhance the Mechanical and Corrosion Properties of Thermally Sprayed Ceramic Coatings
Authors: Kalangi Chaithanya , Veeram Mahidhar Reddy 
Published: September 2023

Abstract
In order to evaluate the coating's characteristics, thermally sprayed ceramic coatings with varied weight percentages of carbon nanotube (CNT) reinforcement were examined. AISI 1020 steel was coated with yttria-stabilized zirconia (ZrO2 + 8% Y2O3) using the air plasma spraying (APS) method. The study examined the CNT dispersion in the coating microstructure and evaluated the porosity, bond strength, and corrosion resistance of the coating. In addition, the coatings' thickness was measured. The coatings were characterised using a variety of techniques, including optical microscopy, scanning electron microscopy, image analysis, bond strength testing, and corrosion analysis. According to the findings, adding CNTs to the coatings improved their mechanical characteristics, particularly their hardness and wear resistance. Notably, the best levels of hardness and wear resistance were seen in coatings with a 5 percent CNT reinforcement. Additionally, the coatings' corrosion resistance was enhanced by the inclusion of CNTs. The results of this work show that the mechanical and corrosion properties of thermally sprayed ceramic coatings can be successfully improved by the inclusion of CNTs. This means that these CNT-reinforced coatings have a lot of potential for a variety of applications, such as wear-resistant, corrosion-resistant, and thermal barrier coatings.
The endocrine disruptor cadmium modulates the androgen-estrogen receptors ratio and induces inflammatory cytokines in luminal (A) cell models of breast cancer
Authors: Bimonte Viviana M. , Catanzaro Giuseppina , Po Agnese , Trocchianesi Sofia , Besharat Zein Mersini , Spinello Zaira , Curreli Mariaignazia , Fabi Alessandra , Bei Roberto , Milella Michele , Vacca Alessandra , Ferretti Elisabetta , Migliaccio Silvia 
Published: September 2023

Abstract
Purpose: Breast cancer (BC) is the most common malignancy that affects women, and it is, to date, their leading cause of death. Luminal A molecular subtype accounts for 40% of BC and is characterized by hormone receptors positive/human epidermal growth factor 2 expression and current treatment consists of surgery plus aromatase inhibitor therapy. Interestingly, several studies demonstrated that the heavy metal cadmium (Cd), classified as a group 1 human carcinogen and widely spread in the environment, exerts estrogen-like activities in several tissues and suggested an intriguing relationship between increased Cd exposure and BC incidence. Thus, aim of this study was to evaluate effects of Cd on Luminal A BC estrogen receptor (ER) positive/progesterone receptor positive cell models in vitro to characterize the mechanism(s) involved in breast cell homeostasis disruption.
Methods: T47D and MCF7 were exposed to Cd (0.5-1µM) for 6-24 hrs to evaluate potential alterations in: cells viability, steroid receptors and intracellular signaling by western blot Moreover, we evaluated the expression of inflammatory cytokines interleukin by RT-PCR.
Results: Our results showed a significant induction of androgen receptor (AR) and an increased AR/ER ratio. Further, Cd exposure increased pro-inflammatory cytokines interleukin (IL)6, IL8 and tumor necrosis factor α levels. Finally, as previously demonstrated by our group, Cd alters pathways such as mitogen-activated protein kinase family and protein kinase B.
Conclusion: In conclusion, our study demonstrates that Cd modifies the expression and pattern of ERs and AR in BC cell lines, suggesting an alteration of BC cells homeostasis, likely predisposing to a carcinogenetic microenvironment.
A microbial ecosystem enhanced by regulating soil carbon and nitrogen balance using biochar and nitrogen fertiliser five years after application
Authors: Meng Fanhao , Yang Hengshan , Fan Xiuyan , Gao Xin , Tai Jicheng , Sa Rula , Ge Xuanliang , Yang Xuezhen , Liu Qingyi 
Published: September 2023

Abstract
Indiscriminate use of nitrogen fertiliser (NF) is a barrier to improving soil quality and crop yields. However, the effect of the combined use of biochar and NF on soil microbial ecosystem (SME) and crop yields is unknown. In the western Liaohe Plain of China, we conducted a five-year field experiment to assess the effects of the combination of biochar and NF on soil structure, C-to-N ratio (CNR), microbial biomass, and spring maize yield. Biochar and NF were applied at 0, 8, 16, and 24 t/ha and 0, 150, and 300 kg/ha, respectively. Compared to their individual use, combination of biochar and NF resulted in a solid–liquid–gas ratio closer to the ideal value. Biochar alone and in combination with NF significantly increased the C, N, and CNR. Moderate use of biochar and NF resulted in the best biological and chemical properties of the soil. A comprehensive evaluation of soil and maize revealed that SME was enhanced by applying biochar and NF at moderate levels (8 t/ha and 150 kg/ha, respectively). The highest yield represents a 24.25% increase compared to the control. Moderate use of biochar and NF has potential as a valuable strategy in regions with similar climate.
Causal relationships between sleep duration and risk of breast tumors: A two-sample bi-directional Mendelian randomization study
Authors: Shao Litong , Zhao Dan , Ji Jing , Lu Yajie 
Published: September 2023

Abstract
Background Previous observational studies reported that sleep traits were associated with breast tumors. However, the causal relationship between sleep duration and breast tumors is not clear.
Methods We performed a two-sample bi-directional Mendelian randomization (MR) analysis with publicly available GWAS summary statistics to detect the causal relationship between genetically predicted sleep duration and the risk of breast tumors, including breast cancer (estrogen receptor (ER)+/ER-, human epidermal growth factor receptor (HER)2+/HER2-), benign breast tumors, and carcinoma in situ of the breast. The inverse variance weighting (IVW) method was used as the gold standard for MR results, and MR Egger regression, weighted median, weighted mode, and simple mode methods were taken as auxiliary analyses. We also conducted sensitivity analyses, including tests for heterogeneity, horizontal pleiotropy, and leave-one-out analysis, to evaluate the validity of the detected causal relationships. An additional reverse-direction MR analysis was further performed to explore the causal effect of breast tumors on sleep duration.
Results Suggestive evidence for the causal effect of genetically predicted sleep duration on breast cancer was identified (odds ratio (OR) = 1.328, 95% confidence interval (CI): 1.013 – 1.741, p = 0.04). When distinguished by molecular phenotype, we found a causal association trend between sleep duration and ER+ and ER- breast cancer (ER+ breast cancer p = 0.051, ER- breast cancer p = 0.077). We did not detect a causal effect of sleep duration on benign breast tumors (OR = 1.002, 95%CI: 0.999 – 1.005, p = 0.242) or carcinoma in situ of the breast (OR = 1.090, 95%CI: 0.403 – 2.947, p = 0.08). Reverse MR analysis did not indicate that having breast cancer could affect sleep duration (OR = 0.998, 95%CI: 0.989 – 1.006, p = 0.670).
Conclusions The results of this study identified a causative effect of genetically predicted sleep duration on breast cancer, suggesting that ensuring appropriate sleep duration and avoiding excessive sleep might be helpful for preventing breast cancer.
Comparative Study With Deep Learning Driven in Two Stocks
Authors: Ghosh Prokarsha 
Published: September 2023

Abstract
This abstract discusses the application of time series analysis in predicting the stock market trends in Indian financial market. While short-term market forecasting can be challenging due to the complexity and emotional factors involved, long-term trends can be effectively studied using data science techniques such as statistical and analytical tools. In the past, predicting stock market changes has been difficult due to the intricate nature of financial markets and the influence of investor emotions. However, the use of data science methods like machine learning and deep learning has gained popularity, particularly because long-term stock market patterns often exhibit a more predictable trajectory. In a recent study it has found that time series analysis is a successful data science approach for uncovering patterns and trends in the stock market. By utilizing Autoregressive Integrated Moving Average (ARIMA) models is one of the promising methods for forecasting future market movements based on historical data. Additionally, exploring the connections between different stocks can provide valuable insights into market trends and potential investment opportunities. Investigating these linkages may reveal essential details about market trends and potential investment prospects. It is expected that further research and development in this field will advance stock market analysis and forecasting, with Artificial Neural Networks (ANNs) and supervised machine learning advancements in data science playing a significant role in this progress. Despite the difficulties that come with stock market forecasting, the development of data science approaches has allowed for major breakthroughs in this area. Scholars have made significant progress thanks in large part to the use of statistical and analytical techniques. The analysis and forecasting of the stock market are positioned to further expand as research and development activities continue, offering useful information to experts and investors alike. These developments in stock market analysis and prediction are anticipated to be greatly aided by the ongoing investigation of cutting-edge data science approaches like machine learning and deep learning. The potential benefits of this continuous development include providing stakeholders with crucial information that will enable them to make wise decisions in the financial markets.
Beyond microRNAs: Analysis of chimeric reads characterises the diverse targetome of AGO2-mediated regulation
Authors: Hejret Vaclav , Varadarajan Nandan Mysore , Klimentova Eva , Gresova Katarina , Giassa Ilektra-Chara , Vanacova Stepanka , Alexiou Panagiotis 
Published: September 2023

Abstract
Argonaute proteins are instrumental in regulating RNA stability and translation. AGO2, the major mammalian Argonaute protein, is known to primarily associate with microRNAs, a family of small RNA ‘driver’ sequences, and identifies its targets primarily via a ‘seed’ mediated partial complementarity process Despite numerous studies, a definitive experimental dataset of AGO2 'driver'-'target' interactions remains elusive. Our study employs two experimental methods - AGO2 CLASH and AGO2 eCLIP, to generate thousands of AGO2 target sites verified by chimeric reads. These chimeric reads contain both the AGO2 loaded small RNA 'driver' and the target sequence, providing a robust resource for modeling AGO2 binding preferences. Our novel analysis pipeline reveals thousands of AGO2 target sites driven by microRNAs and a significant number of AGO2 'drivers' derived from fragments of other small RNAs such as tRNAs, YRNAs, snoRNAs, rRNAs, and more. We utilize convolutional neural networks to train machine learning models that accurately predict the binding potential for each 'driver' class and experimentally validate several interactions. In conclusion, our comprehensive analysis of the AGO2 targetome broadens our understanding of its 'driver' repertoire and potential function in development and disease. Moreover, we offer practical bioinformatic tools for future experiments and the prediction of AGO2 targets. All data and code from this study are freely available at https://github.com/ML-Bioinfo-CEITEC/HybriDetector/
Assessment of the mathematical modelling of thermophysical properties during the pyrolysis of coking coals
Authors: Kumaresh Selvakumar , Kim Man Young 
Published: September 2023

Abstract
In order to understand the coking process and the behavior of the coal, the coal carbonization was examined by a system of parallel first-order reactions, such that the kinetics of volatile gas release was described by the Arrhenius relationship following Merrick’s work. The specific heat of coal had been analysed based on Einstein quantum theory and temperature dependent fits to determine the variation with temperature during the thermal decomposition of coal. The endothermic reactions reported were directly responsible for the influence of high specific heat, and the main secondary volatile species, methane, rising at high temperature proves the significance of an exothermic reaction. The effect of porosity due to lump coke and fissures establishes the characteristics of the semi-coke porous structure, and an increase in total porosity increases the true density of the coke material. The parametric analyses for the coal ranks facilitate the investigation of thermal conductivity and density as a function of temperature. Finally, the thermal conductivity of solid coal and coke was explained based on the correlation between particulate and coke charge in terms of temperature and porosity, and thereby the abrupt increase in conductivity was found to be caused by the radiative contribution after the resolidification of coal.
Hydrogen embrittlement properties of several stainless steels
Authors: Okayasu Mitsuhiro , Matsuura Hisanobu 
Published: September 2023

Abstract

The hydrogen embrittlement (HE) characteristics of various stainless steels were investigated. In this study, as-received, heated (1100°C, 15 h), and cold-rolled (30% strain) γ-austenite (AS), α-ferrite (FS), α′-martensite (MS), and γ–α duplex (DS) stainless steels were employed. For as-received stainless steels, severe HE occurred for DS and MS with static tensile loading, while no clear and weak HE was observed for AS and FS, respectively. This could be attributed to the different amounts of hydrogen diffusivity in the stainless steel. A large amount of hydrogen penetrated to (i) lattice vacancy with low atomic density for body-centered cubic FS, DS, and MS, compared to that for face-centered cubic (AS); (ii) the phase boundary between γ-austenite and α-ferrite for DS; and (iii) the boundary between the Cr base precipitate and the martensite matrix for MS. HE also occurred strongly for heated-DS owing to the grain growth, i.e., a high hydrogen concentration in grain and phase boundaries. Although no clear HE was detected in as-received AS with static loading, HE occurred in cold-rolled AS, where hydrogen penetrated lattice vacancies and α′-martensite formed through strain-induced martensite. Owing to strain-induced martensite created during cyclic loading, HE was detected even for as-received AS, which is dissimilar to the result of the tensile test. Details of HE characteristics of the strainless steels were examined using the four stainless steels with different microstructures, diferent strain level and oxide layer. Moreover, those were investigated under different loading conditions, such as constant, static, and cyclic loading.
Analysis of flowering-associated gene expressions and metabolic characteristics in adzuki bean (Vigna angularis L.) with different short-day induction
Authors: Dong Weixin , Li Dongxiao , Zhang Lei , Tao Peijun , Zhang Yuechen 
Published: September 2023

Abstract
Background
Adzuki bean is an important miscellaneous grain crop and a kind of typical short-day crop that is used in a variety of foods because of its high nutritional and medicinal value. The flowering time of adzuki beans is affected by multiple environmental factors, particularly the photoperiod. Adzuki bean can meet at flowering period, accelerate breeding process and avoid natural disasters by adjusting the day-length.Therefore, RNA-seq analysis was used to determine the effects of different day-length on the expression and metabolic characteristics of genes related to flowering time in adzuki beans.
Results
In this study, ‘Tangshan Hongxiaodu’ was used as experimental material. Transcriptome sequencing was performed under SD-5d, SD-10d and SD-15d treatments, respectively. The results showed that a total of 5,939 differentially expressed genes (DEGs) were identified by sequencing, Among these common genes, 38.09% were upregulated and 23.81% were downregulated in three groups. Gene Ontology (GO) enrichment analysis was performed on the target genes to identify common functions related to photosystem I and II. Kyoto Encyclopedia of Genes and Genomes (KEGG) enriched analysis was performed t o predict two pathways involved in antenna proteinand circadian rhythm. And that the flowering of adzuki beans was promoted by downregulating genes in the circadian rhythm pathway through the blue light metabolic pathway, whereas the antenna protein promoted flowering by enhancing the reception of light signals and accelerating electron transport. In these two metabolic pathways, the number of DEGs was the greatest changes in SD-5d vs SD-15d comparison group. Real-time qRT-PCR validation of eight DEGs in these two metabolic pathways was consistent with the transcriptome results, indicating that the sequencing results were accurate and reliable and that these genes may be candidate genes affecting the regulation of short-day induction at the adzuki bean seedling stage.
Conclusion
The results indicated that short-day induction can downregulate the expression of genes related to adzuki bean flowering in the circadian rhythm and upregulate the expression of some genes in the antenna protein pathway. In addition, the results not only provide a theoretical reference for the molecular mechanism of adzuki bean flowering induced by short days, but also provide multi-level information on the next steps in exploring the functional verification of key genes regulating adzuki bean flowering.
Micro propagation of Annona muricata using different concentration of 6-Benzylaminopurine (BAP).
Authors: s archana , hupparagi kulapati , P Prakasha D , K Hedge N , G Prabhulinga , Haveri Noorulla 
Published: September 2023

Abstract
A commercially feasible technique of micro propagation requires the successful appearance of healthy shoots and an improved multiplication rate, which heavily depends on the make-up of the media employed as well as the kind of explant used, reaction, growth of new shoots. In the current study, the impact of BAP on invitro propagation of nodal and leaves explants of Annona muricata was seen. Among the different concentration of BAP T5 (0.75 mg/L), T6 (1.0 mg/L) and T7 (1.50 mg/L) treatments respectively were selected as it showed higher response with minimum days for shoot initiation, higher shoot induction per cent, maximum number of shoots and higher length compared with other treatments for green nodal explants and same treatments were selected for leaves as it possesses least contamination, good health better survival of explants.
Identification novel Necroptosis-related LncRNAs to predict prognosis and screen the population benefiting from anti-PD-1/PDL-1 treatment in breast cancer
Authors: Yu Hui , Yi Limu , Lin Lin , Li Nani , Huang Zhijian 
Published: September 2023

Abstract
Background: Breast Cancer (BC) is the most common cancer in the world. The rapid development of tumor immunotherapy and necroptosis has brought new directions to the treatment of breast cancer. To improve the situation, this project aims to identify biomarkers that can help predict prognosis and determine a precise treatment.
Method: The Cancer Genome Atlas (TCGA) data was analyzed for coexpression relationships and univariate Cox regressions to identify lncRNAs associated with necroptosis.In addition, differential expression analysis, prognostic analysis, and time-dependent receiver operating characteristics (ROC) analysis were performed to determine whether Necroptosis-related lncRNA is an independent prognostic factor. Then, based on the risk model, principal component analysis (PCA), immune cell infiltration,immune functions, prediction of the half-maximal inhibitory concentration (IC50), and immune checkpoints were evaluated .Additionally, we divided the entire set into two clusters based on immunotherapy response between cold and hot tumors.
Results: We developed a signature consisting of seven necroptosis-related LncRNAs. Over 1, 3, and 5 years, the area's OS under the ROC curve (AUC) was 0.748, 0.753, and 0.714, respectively. High-risk group immune cells were infiltrated less frequently and had lower immune functions than low-risk group immune cells. In addition, using clusters as a means to make a distinction between a cold tumor and a hot tumor could provide more precise treatment options.In Cluster 2, the tumor is considered to be hot tumor, which is more sensitive to immunotherapy drugs, such as anti-PD-1/PDL-1. Conclusion: According to our findings, necroptosis-related lncRNA can be used to predict prognosis and to distinguish cold and hot tumors in BC, thereby optimizing individual treatment.
Gut microbiota and metabolic changes in children with idiopathic short stature
Authors: Yan Luyan , Ye Bin , Yang Min , Shan Yongsheng , Yan Dan , Fang Danfeng , Zhang Kaichuang , Yu Yongguo 
Published: September 2023

Abstract
Background
Idiopathic short stature (ISS) is characterized by short stature with unknown causes. Recent studies showed different gut microbiota flora and reduced fecal short-chain fatty acids in ISS children. However, the roles of the microbiome and metabolites in the pathogenesis of ISS remains largely unknown.
Methods
We recruited 51 Chinese subjects, comprising 26 ISS children and 25 normal-height control individuals. Untargeted metabolomics was performed to explore the fecal metabolic profiles between groups. A shotgun metagenomic sequencing approach was used to investigate the microbiome at the strains level. Mediation analyses were done to reveal correlations between the height standard deviation (SD) value, the gut microbiome and metabolites.
Results
We detected marked differences in the composition of fecal metabolites in the ISS group, particularly a significant increase in erucic acid and a decrease in spermidine, adenosine and L-5-Hydroxytryptophan, when compared to those of controls. We further identified specific groups of bacterial strains to be responsible for the different metabolic profile. Through mediation analysis, 50 linkages were established. KEGG pathway analysis of microbiota and metabolites indicated nutritional disturbances. 13 selected features were able to accurately distinguish the ISS children from the controls (AUC = 0.933 [95%CI, 79.9–100%]) by receiver operating characteristic (ROC) analysis.
Conclusion
Our study suggests that the microbiome and the microbial-derived metabolites play critical roles in children’s growth. These findings provide a new research direction for better understand the mechanism(s) underlying ISS.