Co-occurrence network and functional profiling of the bacterial community in the industrial pile fermentation of Qingzhuan tea: Understanding core functional bacteria.

The distinct quality of Qingzhuan tea is greatly influenced by the bacterial community but was poorly characterized. Therefore, this study investigated the Co-occurrence network and functional profiling of the bacterial community, with special attention paid to core functional bacteria in the industrial pile fermentation. Microbiomics analysis indicated that Klebsiella and Pantoea dominated raw tea leaves, and were rapidly replaced by Pseudomonas in pile fermentation, but substituted mainly by Burkholderia and Saccharopolyspora in final fermented tea. Bacterial taxa were grouped into 7 modules with the dominant in module I, III, and IV, which were involved in flavor formation and biocontrol production. Functional profiling revealed that "penicillin and cephalosporin biosynthesis" increased in pile fermentation. Twelve bacterial genera were identified as core functional bacteria, in which Klebsiella, Pantoea, and Pseudomonas also dominated the pile fermentation. This work would provide theoretical basis for its chemical biofortification and quality improvement by controlling bacterial communities.

Exploring core functional fungi driving the metabolic conversion in the industrial pile fermentation of Qingzhuan tea.

The distinct sensory quality of Qingzhuan tea is mainly formed in pile fermentation by a group of functional microorganisms but the core functional ones was poorly characterized. Therefore, this study investigated the dynamic changes in the fungal community and metabolic profile by integrating microbiomics and metabolomics, and explored the core functional fungi driving the metabolic conversion in the industrial pile fermentation of Qingzhuan tea. Indicated by microbiomics analysis, Aspergillus dominated the entire pile-fermentation process, while Thermoascus, Rasamsonia, and Cylindrium successively abounded in the different stages of the pile fermentation. A total of 50 differentially changed metabolites were identified, with the hydrolysis of galloyl/polymeric catechins, biosynthesis of theabrownins, oxidation of catechins, N-ethyl-2-pyrrolidinone substitution of catechins, and deglycosylation of flavonoid glucosides. Nine fungal genera were identified as core functional fungi, in which Aspergillus linked to the hydrolysis of polymeric catechins and insoluble polysaccharides as well as biosynthesis of theabrownins, while Thermoascus participated in the biosynthesis of theabrownins, deglycosylation of flavonoid glucosides, and N-ethyl-2-pyrrolidinone substitution of catechins. These findings would advance our understanding of the quality formation of Qingzhuan tea and provide a benchmark for precise inoculation for its quality improvement.

Effects of Solitaire AB stent thrombectomy with tirofiban and butylphthalide on neurological function and inflammatory factors in acute cerebral infarction patients.

BACKGROUND: Acute cerebral infarction profoundly affects patients' neurological function and quality of life. This study explores the impact of Solitaire AB stent thrombectomy, combined with tirofiban and butylphthalide, on neurological function and inflammatory factors in patients with acute cerebral infarction. METHODS: Seventy-three eligible patients treated between 2021 and 2023 were divided into a control group (Solitaire AB stent thrombectomy) and a treatment group (Solitaire AB stent thrombectomy with tirofiban and butylphthalide). Postoperative neurological function scores and inflammatory factor levels were analyzed. RESULTS: The treatment group demonstrated a higher clinical effective rate, lower National Institutes of Health Stroke Scale scores at one day and seven days and higher Mini-Mental State Examination and Montreal Cognitive Assessment scores post-treatment. Inflammatory factor levels (Neuron Specific Enolase (NSE), S100-ß, TNF-α and IL-6) were lower in the treatment group. No significant differences in adverse outcomes were observed. CONCLUSION: Solitaire AB stent thrombectomy with tirofiban and butylphthalide shows superior efficacy, improving neurological function and inflammatory factors without increasing adverse outcomes. This offers valuable insights for clinical treatment of acute cerebral infarction.

HEMU: An integrated comparative genomics database and analysis platform for Andropogoneae grasses.

This study reports an online database and analysis platform HEMU, which integrates 75 genome assemblies from 20 unique species, large amounts of multi-omics data, and six sophisticated analysis toolkits. HEMU will facilitate comparative genomics analysis within the tribe Andropogoneae.

Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest.

Introduction: With the advancement of RNA-seq technology and machine learning, training large-scale RNA-seq data from databases with machine learning models can generally identify genes with important regulatory roles that were previously missed by standard linear analytic methodologies. Finding tissue-specific genes could improve our comprehension of the relationship between tissues and genes. However, few machine learning models for transcriptome data have been deployed and compared to identify tissue-specific genes, particularly for plants. Methods: In this study, an expression matrix was processed with linear models (Limma), machine learning models (LightGBM), and deep learning models (CNN) with information gain and the SHAP strategy based on 1,548 maize multi-tissue RNA-seq data obtained from a public database to identify tissue-specific genes. In terms of validation, V-measure values were computed based on k-means clustering of the gene sets to evaluate their technical complementarity. Furthermore, GO analysis and literature retrieval were used to validate the functions and research status of these genes. Results: Based on clustering validation, the convolutional neural network outperformed others with higher V-measure values as 0.647, indicating that its gene set could cover as many specific properties of various tissues as possible, whereas LightGBM discovered key transcription factors. The combination of three gene sets produced 78 core tissue-specific genes that had previously been shown in the literature to be biologically significant. Discussion: Different tissue-specific gene sets were identified due to the distinct interpretation strategy for machine learning models and researchers may use multiple methodologies and strategies for tissue-specific gene sets based on their goals, types of data, and computational resources. This study provided comparative insight for large-scale data mining of transcriptome datasets, shedding light on resolving high dimensions and bias difficulties in bioinformatics data processing.

G6PD upregulates Cyclin E1 and MMP9 to promote clear cell renal cell carcinoma progression.

Background: Clear cell renal cell carcinoma (ccRCC) is a cell metabolic disease with high metastasis rate and poor prognosis. Our previous studies demonstrate that glucose-6-phosphate dehydrogenase (G6PD), the first and rate-limiting enzyme of the pentose phosphate pathway, is highly expressed in ccRCC and predicts poor outcomes of ccRCC patients. The aims of this study were to confirm the oncogenic role of G6PD in ccRCC and unravels novel mechanisms involving Cyclin E1 and MMP9 in G6PD-mediated ccRCC progression. Methods: Real-time RT-PCR, Western blot and immunohistochemistry were used to determine the expression patterns of G6PD, Cyclin E1 and MMP9 in ccRCC. TCGA dataset mining was used to identify Cyclin E1 and MMP9 correlations with G6PD expression, relationships between clinicopathological characteristics of ccRCC and the genes of interest, as well as the prognosis of ccRCC patients. The role of G6PD in ccRCC progression and the regulatory effect of G6PD on Cyclin E1 and MMP9 expression were investigated by using a series of cytological function assays in vitro. To verify this mechanism in vivo, xenografted mice models were established. Results: G6PD, Cyclin E1 and MMP9 were overexpressed and positively correlated in ccRCC, and they were associated with poor prognosis of ccRCC patients. Moreover, G6PD changed cell cycle dynamics, facilitated cells proliferation, promoted migration in vitro, and enhanced ccRCC development in vivo, more likely through enhancing Cyclin E1 and MMP9 expression. Conclusion: These findings present G6PD, Cyclin E1 and MMP9, which contribute to ccRCC progression, as novel biomarkers and potential therapeutic targets for ccRCC treatment.

Zero→Two-Dimensional Metal Nanostructures: An Overview on Methods of Preparation, Characterization, Properties, and Applications.

Metal nanostructured materials, with many excellent and unique physical and mechanical properties compared to macroscopic bulk materials, have been widely used in the fields of electronics, bioimaging, sensing, photonics, biomimetic biology, information, and energy storage. It is worthy of noting that most of these applications require the use of nanostructured metals with specific controlled properties, which are significantly dependent on a series of physical parameters of its characteristic size, geometry, composition, and structure. Therefore, research on low-cost preparation of metal nanostructures and controlling of their characteristic sizes and geometric shapes are the keys to their development in different application fields. The preparation methods, physical and chemical properties, and application progress of metallic nanostructures are reviewed, and the methods for characterizing metal nanostructures are summarized. Finally, the future development of metallic nanostructure materials is explored.

Overexpression of ERCC3 is associated with poor prognosis in patients with pancreatic cancer.

Pancreatic cancer is associated with poor prognosis due to limited therapeutic options. Excision repair cross-complementing 3 (ERCC3) is an important member of nucleotide excision repair (NER) that is overexpressed in some cancers and may be regarded as a poor prognostic factor. Yet, its role in pancreatic cancer remains unclear. This study aimed to investigate the expression and functions of ERCC3 in pancreatic cancer patients and its relation with clinicopathological features. Our data suggested that the protein expression level of ERCC3 was higher in tumor tissues than in adjacent tissues. In addition, the expression of ERCC3 has shown to be associated with the tumor extent (p=0.035). Besides, analysis of the dataset in The Cancer Genome Atlas (TCGA) revealed that high expression of ERCC3 was associated with poor overall survival in pancreatic cancer patients (p=0.0136). In Cox regression analysis, ERCC3 was an independent prognostic factor for overall survival in pancreatic cancer (p<0.001). Furthermore, our in vitro data further suggested that the overexpression of ERCC3 significantly promoted pancreatic cancer (BxPC-3, CFPAC-1, and PANC-1 cells) proliferation, invasion, and migration. Taken together, this study suggested that high expression of ERCC3 might be a poor prognostic factor in human pancreatic cancer and might be used as a promising therapeutic target for pancreatic cancer treatment.