bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide analysis of C-repeat binding factor (CBF) family members in Pennisetum glaucum and the function of PgCBF21 under cold stress
Authors: Li Wei , Li Tian , Dong Ying , He Junyi , Wu Bo , Wang Hui , Guan Cong 
Published: October 2024

Abstract

Background
Pennisetum hybrid (Pennisetum glaucum x Pennisetum purpureum), a perennial forage grass of the Poaceae family, it has a well-developed root system, strong tillering ability, high biomass yield, and rich nutritional content, making it a premium forage grass. However, Pennisetum genera grasses are sensitive to low-temperature stress and lacks the ability to adapt to cold environments, severely limiting its cultivation in temperate and high-altitude regions.
Results
We identified 23 PgCBF genes, unevenly distributed across chromosomes 1 to 7. Physicochemical property analysis revealed that the amino acid count of PgCBF family members ranged from 187 to 324, with molecular weights between 19688.36 and 34271.70 Da and theoretical isoelectric points between 4.57 and 9.82. Promoter region analysis of PgCBF genes indicated the presence of various cis-acting elements involved in hormone response, tissue-specific expression, and stress response. Additionally, qRT-PCR results showed significant upregulation of PgCBF11 expression in stems following cold treatment, with increasing over 40-fold after 32 hours of cold treatment and about 20-fold after 8 hours of cold treatment. PgCBF21 exhibited a strong response in leaves after 8 hours of cold treatment, with expression levels rising more than 37-fold. Furthermore, through the overexpression of PgCBF21, we ascertained its capacity to enhance cold tolerance in yeast.
Conclusion
This study analyzed the molecular characteristics of the PgCBF family members in Pennisetum glaucum and identified several candidate genes responsive to cold stress, providing a theoretical foundation for future research on the innovative utilization of cold-resistant resources.
Steric colloidal stabilization of cellulose nanocrystals by dextran grafting
Authors: Tanaka Takahide , Araki Jun , Kuga Shigenori , Yabuki Akihiro 
Published: October 2024

Abstract

In this study, enhanced dispersion stability of cellulose nanocrystal was achieved by terminal grafting of dextran (a-1,6 glucan) onto the surface of nanocrystals. The 6-position carbon of the nanocrystal was first oxidized by TEMPO method, and the introduced carboxyl group on the surface of cellulose nanocrystal was coupled with terminal amino group of terminally aminated dextran using N-hydroxysuccinimide and 1-ethyl-3-3-dimethylaminopropyl carbodiimide. Terminally aminated dextran was obtained by reductive amination using sodium cyanoborohydride and ammonium chloride. The weight gain by grafting reached 184% of the carboxylated cellulose nanocrystal, resulting in high dispersion stability. We evaluated the dispersion stability by the change in viscosity before and after adding salt. Cellulose nanocrystals are colloids, and adding salt reduces their dispersion stability and increases their viscosity. However, addition of 50 mM CaCl2 to the suspension of dextran grafted cellulose nanocrystal did not cause noticeable increase in viscosity or in turbidity. This enhanced stability indicates the effectiveness of coating cellulose nanocrystal by water-soluble polymers.
Green Cleaner: Advanced Decontamination Algorithm for Catheterized Urine 16S rRNA Sequencing Data
Authors: Yoon Sung Min , Ki Chang-Seok , Song Ju Sun 
Published: October 2024

Abstract

Background
Contamination of low-biomass samples, such as urine, is a significant challenge in 16S rRNA sequencing. The presence of extraneous DNA in reagents and the environment often obscures microbial DNA, making it difficult to identify and remove contaminants. In silico decontamination algorithms developed so far still have some limitations in identifying and removing contaminants accurately. In this study, we developed a novel decontamination algorithm, Green Cleaner, to enhance the accuracy of 16S rRNA sequencing data by effectively distinguishing and removing contaminants especially from catheterized urine samples.
Results
We evaluated the performance of Green Cleaner against SCRuB using a series of vaginal microbiome dilution experiments as a proxy for low-biomass urine samples. Our results demonstrate that Green Cleaner outperforms SCRuB across all contamination levels, with higher accuracy, F1-score, and lower beta-dissimilarity. Specifically, Green Cleaner showed improved specificity and positive predictive value (PPV), correctly removing more contaminant amplicon sequence variant (ASV) features than SCRuB did. This was evidenced by the more diminished alpha diversity of the decontamination results in Green Cleaner than SCRuB, indicating a more precise elimination of contaminants by Green Cleaner.
Conclusions
Green Cleaner offers a robust solution for decontaminating 16S rRNA sequencing data from low-biomass samples, particularly catheterized urine samples, thus addressing the key limitations of the existing methods. By utilizing a single blank extraction control per batch and a set of intuitive and adjustable decontamination rules, Green Cleaner provides a practical and efficient approach for real-world applications. Our findings suggest that Green Cleaner has the potential to substantially advance urine microbiome research by providing more accurate and reliable microbial profiles.
Phylogeny and taxonomy of the polyploidy species that contains St genome (Triticeae; Poaceae) based on four nuclear DNA and three chloroplast genes
Authors: Pan XiaoYang , Zheng TingTing , Zhao Yuxin , Fan Xing , Sha Lina , Li Yinghui , Zhu Wei , Xu Lili , Wang Yi , Cheng Yiran , Zhang Haiqin , Kang Houyang , Zhou Yonghong , Wu Dandan 
Published: October 2024

Abstract

Background
The genus Pseudoroegneria (Nevski) Á. Löve with the St genome accounts for more than 60% of perennial Triticeae speciation. However, the strong dominant character of the St genome results in challenging to distinguish each species even genus based on single or combined morphological traits, the phylogeny and taxonomy of the St-containing polyploid genera remain under controversy.
Results
In this study, we used nuclear and chloroplast DNA-based phylogenetic analyses to reveal the systematic relationships of the St-containing polyploidy species. The maximum likelihood (ML) tree based on nuclear ribosomal internal transcribed spacer region (nrITS) and three single-copy nuclear genes data (Acc1 + Pgk1 + DMC1) showed that St-containing polyploid species were separated into StStHH, StStYY, StStYYHH, StStYYPP, StStYYWW, StStPP, and StStEE genome types and polyploidy species in Caucasus, America and Australia have unique polyploidization events. The ML tree for the chloroplast DNA fragments (matK + rbcL + trnL-trnF) displayed that the P genome serves as a maternal donor of Kengyilia melanthera and K. dingqinensis from the Hengduan Mountains region, while the St or StY genome serves as the maternal donor of other St genome containing species. Herein, we reported the genome constitution of Kengyilia tibetica, K. changduensis, and K. dingqinensis with the StStYYPP genome for the first time.
Conclusions
The St-containing polyploid species should be treated as distinct genera according to different genome constitutions, St-containing polyploid species experienced independent allopolyploidization events in different distribution regions and the St-containing polyploid species had two relatively independent maternal origins from the P genome or St/StYgenome. Besides, the Xp genome may have contributed to the unknown Y genome formation.
Integrated analysis unraveling the immunologic and clinical prognostic values of Synaptotagmin Like 4 in pan-cancer
Authors: Ren Yuehan , Wu Xiangbin , Li Jinlei , Zhou Zhenhua , Ni Shichang , Cai Jianhui 
Published: October 2024

Abstract

SYTL4 (Synaptotagmin Like 4) encodes a protein of synaptotagmin like protein family, which participates in intracellular membrane trafficking. Currently, its role and mechanisms in cancer remain unveiled, necessitating additional comprehensive analysis across different types of cancer to assess its potential in diagnosis, prognosis, chemotherapy, and immunotherapy in cancer. In our study, the mRNA level, threshold for copy number alterations, segmentation of masked copy number alterations, and methylation of SYTL4 DNA were analyzed based on data from TCGA pan-cancer cohort. miRNA, TCPA, mutation and clinical data were analyzed to evaluate diagnostic and prognostic significances of SYTL4. Then the results were checked using cBioPortal and GEO database. The protein levels were analyzed and evaluated based on HPA database and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Biological roles of SYTL4 in pan-cancer were explored by GSEA. We use multiple immune infiltration algorithms in TIMER2.0 and TISCH database to cross-verify the associations between SYTL4 expression and tumor immune microenvironment. Additionally, we depicted a pan-cancer survival map and explored the differences of gene expressions among cancers with different molecular subtypes. Through chemotherapy data from CellMiner, GDSC, CTRP database, we clarified the relationship between SYTL4 and drug resistance. Finally, we explored the chemical substances that affect SYTL4 expression through CTD database. This study systematically and comprehensively reveals the functions of SYTL4 and potential clinical diagnostic and therapeutic predictive values of SYTL4 in pan-cancer.
MSH6 as a prognostic biomarker in bladder cancer and its correlation with immunity
Authors: He Ning , Bao Lu-ri , Fu Zhen-li , Gao Wu-niri , Wang Jing-yuan , Chen Li-Gang , meng Yan 
Published: October 2024

Abstract

This study aims to investigate the role of MSH6 in the diagnosis and prognosis of bladder cancer and its association with immune responses.Various analyses were conducted on The Cancer Genome Atlas (TCGA) data, and the results were validated using the Gene Expression Omnibus (GEO) database. The potential mechanism of MSH6 in bladder cancer was revealed using R tools, Gene Set Enrichment Analysis (GSEA), and Gene Ontology (GO) analysis. Bladder cancer patients admitted to the Affiliated Hospital of Inner Mongolia Medical University from June 2023 to December 2023 were enrolled. Pathological specimens of bladder cancer and adjacent tissues were obtained. The expression of MSH6 protein in bladder cancer and adjacent tissues was assessed by immunohistochemistry. High expression of MSH6 was identified as an independent prognostic factor for bladder cancer. The occurrence of bladder cancer was also influenced by age, pathological T stage, and pathological stage. According to the Kaplan-Meier survival curve, the overall survival rate of the MSH6 high-expression group was lower (P=0.003). Immunohistochemical results showed the expression of MSH6 in bladder cancer tissues was higher than in adjacent tissues. GSEA revealed a close association between MSH6 and the immune system. MSH6 may play a key role in immune infiltration in bladder cancer. MSH6 is closely related to the diagnosis and prognosis of bladder cancer, suggesting its potential utility as a biomarker for the diagnosis and prognosis of bladder cancer. MSH6 is closely related to the tumor immune microenvironment, implying a significant role in immunotherapy.
Beyond the Hertzsprung-Russell Diagram: An Enhanced Three-Dimensional Model Unveiling the Multidimensional Cosmos of Stars
Authors: Kumar Rohan 
Published: October 2024

Abstract

Despite its utility in identifying patterns in celestial objects, the Hertzsprung-Russell diagram is not supported in dim or small stars; it struggles to provide insights into certain celestial objects such as brown dwarfs. The purpose of this experiment is to create an improved version of the diagram with a three-dimensional model that includes a third z-axis to accurately predict and chart the life cycles of all stars regardless of size. The values of the stars’ absolute magnitude and color indices were used to chart the surface gravity and metallicity, variables that were chosen due to their ease of collection and their likeliness to be within the range of values being assessed. To obtain the values for the model, data points from the database GAIA DR2 were utilized via the TAP protocol to query the SQL database. The data was transferred into a local CSV file to facilitate data manipulation. The data could be read and interpreted, as dim stars would likely have higher values of these variables, making it easier to include them in the diagram. The Pandas DataFrames tool on Python 3 was used to organize and manage the data efficiently. Matplotlib Graphs visualized the relationships between different stellar attributes by developing a linear regression line and an algorithm and creating scatter plots and sky maps (Figure 11) to explore trends, hence designing three–dimensional diagrams. It was determined that the surface gravity diagram had a higher efficacy than metallicity due to their standard deviations of 0.4641441715272741 and 0.786577627976148, respectively.
Difference in leaf and root stoichiometric characteristics of Quercus rehderiana Hand.-Mazz. in forests with rocky and non-rocky desertification in Southwest China
Authors: Bai Xiao-Long , Feng Tu , Zou Shun , He Bin , Chen Yang , Li Wang-Jun 
Published: October 2024

Abstract

Quercus rehderiana Hand.-Mazz. is a genus of Quercus in the Fagaceae family, which widely distributed in Guizhou Province in Southwest China. It has important ecological significance in soil and water conservation, species diversity maintenance, and climate regulation. To date, the researches on stoichiometric characteristics of Quercus mainly focus on leaves, and few studies on roots. However, the difference of leaf and root stoichiometric characteristics of Quercus between in forests with rocky and non-rocky desertification are still unclear. In this study, we compared leaf (15 individuals) and root (9 individuals) carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) concentrations and their stoichiometric ratios in five 20 x 20 m quadrants of forests with rocky and non-rocky desertification. The aim was to find their resource strategies of adaptation to nutrient deficient soil environments in forests with rocky desertification. Our results show that leaf P and K concentrations in forest with non-rocky desertification were significantly higher than those in forest with rocky desertification, Ca and Mg concentrations were opposite. Root N, Ca and Mg concentrations in forest with rocky desertification were significantly higher than that in forest with non-rocky desertification, P and K concentrations were opposite. The N:P of leaves were greater than the threshold value of phosphorus (16) both in forests with rock and non-rocky desertification. Leaf P concentration was positively correlated with N concentration in forest with non-rocky desertification. Root N concentration was positively correlated with P concentration in forest with non-rocky desertification. C concentration of leaves and roots in forest with rocky desertification was negatively correlated with Ca concentration. In conclusion, leaf and root showed an obvious difference in nutrients and stoichiometric characteristics between in forests with rocky and non-rocky desertification. The growth of Q. rehderiana both in forest with rocky and non-rocky desertification was mainly limited by P. The trade-offs and synergies of nutrient absorption and utilization by different plant organs are both similar and different in different forests. Therefore, proper addition of N and P nutrients in plant growth period can promote plant growth and development, and help to improve the stability of forest ecosystem. The research results have practical significance for the vegetation restoration and protection in forests with rocky desertification.
Study on Cardiac Transcriptomic Changes and Inflammatory Responses Induced by Acute Kidney Injury in a Cardiorenal Syndrome Model
Authors: DING Xiaolu , HE Yuchen , LIU Xiaodan , WANG Chen 
Published: October 2024

Abstract

Cardiorenal syndrome (CRS) is a multifaceted relationship between the heart and kidney, where acute kidneys injury (AKI) directly contributes to cardiac dysfunction. The present study aimed to explore the changes of early transcriptome in heart exposed AKI via a mouse unilateral ureteral obstruction (UUO) model. This study was designed to extract differentially expressed genes (DEGs) and their implicated biological processes as well as pathways from the GSE235751 dataset of high-throughput gene expression profile via bioinformatics tools. Preprocessing-introduction of Data was undergone for data integrity and quality check, Differential expression analysis that identified significant gene expressions changes in heart tissue associated with AKI. Pathway analysis and functional annotation revealed involvement of inflammation, cardiac repair, mitochondrial function and autophagy as the major pathways influencing differences in gene expression. Between unrelated groups, validation of distinctly expressed genes was performed using Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). Gene Set Enrichment Analysis (GSEA) showed downregulation of mitochondrial oxidative bioenergetics and autophagy, while upregulating cell proliferation inflammation pathways. These results indicate that AKI induces robust changes in cardiac gene expression, affecting many different pathways and provide novel information about the molecular mechanisms underlying CRS. These results identify possible early intervention and therapeutic targets for the better understanding and treatment of CRS.
The effects of PstR, a PadR family transcriptional regulatory factor, in Plesiomonas shigelloides are revealed by transcriptomics
Authors: Yan Junxiang , Zhang Zixu , Shi Hongdan , Xue Xinke , Li Ang , Liu Fenxia , Ding Peng , Guo Xi , Cao Boyang 
Published: October 2024

Abstract

Background: Plesiomonas shigelloides is a gram-negative opportunistic pathogen associated with gastrointestinal and extraintestinal diseases in humans. There have been reports of specific functional genes in the study of P. shigelloides, but there are also many unknown genes that may play a role in P. shigelloides pathogenesis as global regulatory proteins or virulence factors.
Results: In this study, we found a transcriptional regulator of the PadR family in P. shigelloides and named it PstR (GenBank accession number: EON87311.1), which is present in various pathogenic bacteria but whose function has rarely been reported. RNA sequencing (RNA-Seq) was used to analyze the effects of PstR on P. shigelloides, and the results indicated that PstR regulates approximately 9.83% of the transcriptome, which includes impacts on motility, virulence, and physiological metabolism. RNA-seq results showed that PstR positively regulated the expression of the flagella gene cluster, which was also confirmed by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and lux assays. Meanwhile, the ΔpstR mutant strains lacked flagella and were non-motile, as confirmed by motility assays and transmission electron microscopy (TEM). Additionally, RNA-seq, qRT-PCR, and lux assays demonstrated that PstR also positively regulates T3SS expression, which aids in P. shigelloides' capacity to infect Caco-2 cells. Meanwhile, we also revealed that PstR negatively regulates fatty acid degradation and metabolism, as well as the regulatory relationship between PsrA, a regulator of fatty acid degradation and metabolism, and its downstream genes in P. shigelloides.
Conclusions: Overall, we revealed the effects of PstR on motility, virulence, and physiological metabolism in P. shigelloides, which will serve as a foundation for future research into the intricate regulatory network of PstR in bacteria.
The effect of proprioceptive neuromuscular facilitation techniques compared to aerobic exercise on balance, fear of falling, and quality of life in older adults: a randomized controlled trial
Authors: Kajbafvala Mehrnaz , Eshlaghi Mina Ansari , ShahAli Shabnam , pourkazem Fateme , Hejazi Anahita 
Published: October 2024

Abstract

Background
Aging is a long-term and unalterable phenomenon with changes in various systems such as cardiovascular, respiratory, neuromusculoskeletal, and vestibular. Exercise and physical activity reduce the progression of aging complications. Therefore, we examined the effect of proprioceptive neuromuscular facilitation techniques compared to aerobic exercise on balance, fear of falling, and quality of life in older adults.
Methods
Fifty-two older adults aged over 60 years (31 males, 21 females) were included. After initial evaluation, individuals were randomly assigned into two treatment groups (PNF techniques and aerobic exercise). Both treatment groups received 12 treatment sessions over 4 weeks. Balance, fear of falling, and quality of life were assessed at baseline and after a 4-week intervention. Analysis of covariance (ANCOVA) and paired samples t-test were utilized to between and within-group changes of variables.
Results
The results showed no significant differences in balance, fear of falling, and quality of life between groups after the intervention (P > 0.05). In within-group comparison, only the berg balance scale (BBS) significantly improved after the intervention (P < 0.05).
Conclusion
The findings suggest that PNF techniques in comparison with aerobic exercise could not contribute to improvement in balance, fear of falling, and quality of life. Therefore, more clinical trial studies with a control group are needed to determine the exact effects of these techniques.
Trial Registration Number (TRN) and date of registration:
The trial was registered at the (https://www.irct.ir), (IRCT20210505051181N4) on 9/2/2023.
Forecasting and comparing between five moderate geomagnetic storms in 2022 using artificial neural networks
Authors: Hegy Mostafa , Nahool Tareq 
Published: October 2024

Abstract

The current work investigates the precursor that follows coronal mass ejection (CME), through studying five moderate geomagnetic storms in 2022. We have employed the Artificial Neural Network (ANN) and supervised machine learning models to predict the SYM-H for geomagnetic storms during the solar cycle. The estimation yielded satisfactory accuracy including mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and correlation coefficient (R2). To demonstrate the method's robustness, we have compared the predicted data set with real-world data and evaluated its performance against other supervised machine learning algorithms for regression problems, namely Decision Tree Regressor, Gradient Boosting Regressor, AdaBoost Regressor, and Linear Regression. Results revealed the proficiency of the ANN as an effective predicting tool over the Supervised machine learning for the SYM-H index.