Identify CTBP1-DT as an immunological biomarker that promotes lipid synthesis and apoptosis resistance in KIRC.

Recently, mounting evidence has highlighted the essential function of the C-terminal binding protein-1 divergent transcript (CTBP1-DT) in malignancies. However, its role in kidney renal clear cell carcinoma (KIRC) remains largely unknown. Our study aimed to identify the potential function of CTBP1-DT in KIRC. RT-qPCR, Kaplan-Meier survival analysis, Cox regression analysis, and nomogram analysis were utilized to determine the expression and effects of CTBP1-DT on survival. The subcellular localization of CTBP1-DT was determined using RNA fluorescence in situ hybridization (FISH). To investigate the functions of CTBP1-DT in regulating KIRC cell proliferation, migration, invasion, lipid synthesis, and apoptosis, we conducted CCK8, EdU, Transwell, and Oil Red O staining and cell apoptosis staining assays. The relationships between CTBP1-DT and the tumor microenvironment were investigated with multiple bioinformatics analysis algorithms and databases, including CYBERSORT, TIMER2, Spearman correlation test, tumor mutation burden (TMB), microsatellite instability (MSI), and immunophenoscore (IPS). According to our results, CTBP1-DT is a lncRNA located in the nucleus that is significantly upregulated in KIRC and is correlated with better clinical outcomes. Downregulating CTBP1-DT inhibited cell viability, migration, invasion, and lipid synthesis but triggered cell apoptosis. Additionally, we explored the potential effect of CTBP1-DT in regulating immune cell infiltration in KIRC and other malignancies. Furthermore, CTBP1-DT could be used to predict the effectiveness of targeted drugs and immune checkpoint inhibitors. In conclusion, we identified CTBP1-DT as a potential immunological biomarker and discovered the potential role of CTBP1-DT in regulating lipid synthesis and apoptosis resistance.

The Physicochemical Properties and Antioxidant Activity of Spirulina (Artrhospira platensis) Chlorophylls Microencapsulated in Different Ratios of Gum Arabic and Whey Protein Isolate.

Spirulina (Artrhospira platensis) is rich in chlorophylls (CH) and is used as a potential natural additive in the food industry. In this study, the CH content was extracted from spirulina powder after ultrasound treatment. Microcapsules were then prepared at different ratios of gum Arabic (GA) and whey protein isolate (WPI) through freeze-drying to improve the chemical stability of CH. As a result, a* and C* values of the microcapsules prepared from GA:WPI ratios (3:7) were -8.94 ± 0.05 and 15.44 ± 0.08, respectively. The GA fraction increased from 1 to 9, and encapsulation efficiency (EE) of microcapsules also increased by 9.62%. Moreover, the absorption peaks of CH at 2927 and 1626 cm-1 in microcapsules emerged as a redshift detected by FT-IR. From SEM images, the morphology of microcapsules changed from broken glassy to irregular porous flake-like structures when the GA ratio increased. In addition, the coated microcapsules (GA:WPI = 3:7) showed the highest DPPH free radical scavenging activity (SADPPH) (56.38 ± 0.19) due to low moisture content and better chemical stability through thermogravimetric analysis (TGA). Conclusively, GA and WPI coacervates as the wall material may improve the stability of CH extracted from spirulina.

Nitrifying Microbes in the Rhizosphere of Perennial Grasses are Modified by Biological Nitrification Inhibition.

Soil nitrification (microbial oxidation of ammonium to nitrate) can lead to nitrogen leaching and environmental pollution. A number of plant species are able to suppress soil nitrifiers by exuding inhibitors from roots, a process called biological nitrification inhibition (BNI). However, the BNI activity of perennial grasses in the nutrient-poor soils of Australia and the effects of BNI activity on nitrifying microbes in the rhizosphere microbiome have not been well studied. Here we evaluated the BNI capacity of bermudagrass (Cynodon dactylon L.), St. Augustinegrass (Stenotaphrum secundatum (Walt.) Kuntze), saltwater couch (Sporobolus virginicus), seashore paspalum (Paspalum vaginatum Swartz.), and kikuyu grass (Pennisetum clandestinum) compared with the known positive control, koronivia grass (Brachiaria humidicola). The microbial communities were analysed by sequencing 16S rRNA genes. St. Augustinegrass and bermudagrass showed high BNI activity, about 80 to 90% of koronivia grass. All the three grasses with stronger BNI capacities suppressed the populations of Nitrospira in the rhizosphere, a bacteria genus with a nitrite-oxidizing function, but not all of the potential ammonia-oxidizing archaea. The rhizosphere of saltwater couch and seashore paspalum exerted a weak recruitment effect on the soil microbiome. Our results demonstrate that BNI activity of perennial grasses played a vital role in modulating nitrification-associated microbial populations.

The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer.

AIM: Thyroid cancer is the most common endocrine cancer, the incidence rate has continuously increased worldwide. However, there are still lack of effective molecular biomarkers for the diagnosis and treatment of the disease. The study was conducted to identify driver genes that may serve as potential biomarkers for the disease. METHODS: The computational tools oncodriveCLUST, oncodriveFM, icages and drgap were used to detect driver genes in thyroid cancer using somatic mutations from The Cancer Genome Atlas database. Integrated analyses were performed on the driver genes using multiomics data from the TCGA database. RESULTS: A set of 291 driver genes were identified in thyroid cancer. BRAF, NRAS, HRAS, OTUD4, EIF1AX were the top 5 frequently mutated genes in thyroid cancer. The weighted gene co-expression network analysis identified 4 coexpression modules. The modules 1-3 were significantly associated with patients' tumor size, residual tumor, cancer stage, distant metastasis and multifocality. SEC24B, MET and ITGAL were the hub genes in the modules 1-3 respectively. Hierarchical clustering analysis of the 20 driver genes with the most frequent copy number changes revealed 3 clusters of PRAD patients. Cluster 1 tumors exhibited significantly older age, tumor size, cancer stages, and poorer prognosis than cluster 2 and 3 tumors. 16 genes were significantly associated with number of lymph nodes, tumor size and pathologic stage, such as IL7 R, IRS1, PTK2B, MAP3K3 and FGFR2. CONCLUSIONS: The set of cancer genes and subgroups of patients shed insight on the tumorigenesis of thyroid cancer and open up avenues for developing prognostic biomarkers and driver gene-targeted therapies in thyroid cancer.