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Exosomes are cell-derived vesicles and are abundant in biological fluids; they contain RNA molecules which may serve as potential diagnostic biomarkers in 'precision medicine'. To promote the clinical application of exosomal RNA (exoRNA), many isolation methods must be compared and validated. Exosomes in cell culture medium (CCM) and serum may be isolated using ultracentrifugation (UC), ExoQuick or Total Exosome Isolation Reagent (TEI), and exoRNA may be extracted using TRIzol-LS, SeraMir, Total Exosome RNA Isolation (TER), HiPure Liquid RNA/miRNA kit (HLR), miRNeasy or exoRNeasy. ExoRNA was assessed using NanoDrop, Bioanalyzer 2100, quantitative polymerase chain reaction and high-throughput sequencing. UC showed the lowest recovery of particles, but the highest protein purity for exosome isolation. For isolation of exoRNA, we found that combinations of the TEI and TER methods resulted in high extraction efficiency and purity of small RNA obtained using CCM. High yield and a narrow size distribution pattern of small RNA were shown in exoRNA isolated by exoRNeasy from serum. In RNA profile analysis, the small RNA constituent ratio, miRNA content and amount varied as a result of methodological differences. This study showed that different methods may introduce variations in the concentration, purity and size of exosomes and exoRNA. Herein we discuss the advantages and disadvantages of each method and their application to different materials, therefore providing a reference according to research design.

A bstract Enhanced glycolysis in cancer cells has been linked to cell protection from DNA damaging signals, although the mechanism is largely unknown. The 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) catalyzes the generation of fructose-2,6-bisphosphate, a potent allosteric stimulator of glycolysis. Intriguingly, among the four members of PFKFB family, PFKFB3 is uniquely localized in the nucleus, although the reason remains unclear. Here we show that chemotherapeutic agent cisplatin promotes glycolysis, which is suppressed by PFKFB3 deletion. Mechanistically, cisplatin induces PFKFB3 acetylation at lysine 472 (K472), which impairs activity of the nuclear localization signal (NLS) and accumulates PFKFB3 in the cytoplasm. Cytoplasmic accumulation of PFKFB3 facilitates its phosphorylation by AMPK, leading to PFKFB3 activation and enhanced glycolysis. Inhibition of PFKFB3 sensitizes tumor to cisplatin treatment in a xenograft model. Our findings reveal a mechanism for cells to stimulate glycolysis to protect from DNA damage and potentially suggest a therapeutic strategy to sensitize tumor cells to genotoxic agents by targeting PFKFB3. Enhanced glycolysis in cancer cells has been associated with protection from DNA damage. Here the authors show that DNA damaging signals induce acetylation of PFKFB3 at lysine K472 and promote its cytosolic accumulation, which enhances glycolysis, resulting in protection from cisplatin-induced cell death.

Natural antioxidants are widely distributed in food and medicinal plants. These natural antioxidants, especially polyphenols and carotenoids, exhibit a wide range of biological effects, including anti-inflammatory, anti-aging, anti-atherosclerosis and anticancer. The effective extraction and proper assessment of antioxidants from food and medicinal plants are crucial to explore the potential antioxidant sources and promote the application in functional foods, pharmaceuticals and food additives. The present paper provides comprehensive information on the green extraction technologies of natural antioxidants, assessment of antioxidant activity at chemical and cellular based levels and their main resources from food and medicinal plants.

Fibrotic skin disease represents a major global healthcare burden, characterized by fibroblast hyperproliferation and excessive accumulation of extracellular matrix. Fibroblasts are found to be heterogeneous in multiple fibrotic diseases, but fibroblast heterogeneity in fibrotic skin diseases is not well characterized. In this study, we explore fibroblast heterogeneity in keloid, a paradigm of fibrotic skin diseases, by using single-cell RNA-seq. Our results indicate that keloid fibroblasts can be divided into 4 subpopulations: secretory-papillary, secretory-reticular, mesenchymal and pro-inflammatory. Interestingly, the percentage of mesenchymal fibroblast subpopulation is significantly increased in keloid compared to normal scar. Functional studies indicate that mesenchymal fibroblasts are crucial for collagen overexpression in keloid. Increased mesenchymal fibroblast subpopulation is also found in another fibrotic skin disease, scleroderma, suggesting this is a broad mechanism for skin fibrosis. These findings will help us better understand skin fibrotic pathogenesis, and provide potential targets for fibrotic disease therapies. Fibroblasts are found to be heterogeneous in multiple fibrotic diseases, but fibroblast heterogeneity in fibrotic skin diseases is not well characterized. Here the authors employ scRNA-seq to explore fibroblast heterogeneity in keloid, a paradigm of fibrotic skin diseases.

Background Metastasis was the major cause of the high mortality in ovarian cancer. Although some mechanisms of metastasis in ovarian cancer were proposed, few have been targeted in the clinical practice. In the study, we aimed to identify novel genes contributing to metastasis and poor clinical outcome in ovarian cancer from bioinformatics databases. Methods Studies collecting matched primary tumors and metastases from ovarian cancer patients were searched in the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by software R language. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for the DEGs were implemented by Metascape. Venn diagram was plotted to present overlapping DEGs. The associations between the overlapping DEGs and prognosis were tested by Cox proportional hazard regression model using a cohort of ovarian cancer patients from the TCGA database. Genes affecting patients’ outcomes significantly were served as hub genes. The mechanisms of the hub genes in promoting ovarian cancer metastasis were then predicted by R software. Results Two gene expression profiles (GSE30587 and GSE73168) met the inclusion criteria and were finally analyzed. A total of 259 genes were significantly differentially expressed in GSE30587, whereas 712 genes were in GSE73168. In GSE30587, DEGs were mainly involved in extracellular matrix (ECM) organization; For GSE73168, most of DEGs showed ion trans-membrane transport activity. There were 9 overlapping genes between the two datasets (RUNX2, FABP4, CLDN20, SVEP1, FAM169A, PGM5, ZFHX4, DCN and TAS2R50). ZFHX4 was proved to be an independent adverse prognostic factor for ovarian cancer patients (HR = 1.44, 95%CI: 1.13–1.83, p  = 0.003). Mechanistically, ZFHX4 was positively significantly correlated with epithelial-mesenchymal transition (EMT) markers ( r  = 0.54, p  = 2.59 × 10 −29 ) and ECM-related genes ( r  = 0.52, p  = 2.86 × 10 −27 ). Conclusions ZFHX4 might promote metastasis in ovarian cancer by regulating EMT and reprogramming ECM. For clinical applications, ZFHX4 was expected to be a prognostic biomarker for ovarian cancer metastasis.

The purpose of this review is to provide medical researchers, especially those without a bioinformatics background, with an easy-to-understand summary of the concepts and technologies used in microbiome research. First, we define primary concepts such as microbiota, microbiome, and metagenome. Then, we discuss study design schemes, the methods of sample size calculation, and the methods for improving the reliability of research. We emphasize the importance of negative and positive controls in this section. Next, we discuss statistical analysis methods used in microbiome research, focusing on problems with multiple comparisons and ways to compare β-diversity between groups. Finally, we provide step-by-step pipelines for bioinformatics analysis. In summary, the meticulous study design is a key step to obtaining meaningful results, and appropriate statistical methods are important for accurate interpretation of microbiome data. The step-by-step pipelines provide researchers with insights into newly developed bioinformatics analysis methods.

Overproduction of oxidants (reactive oxygen species and reactive nitrogen species) in the human body is responsible for the pathogenesis of some diseases. The scavenging of these oxidants is thought to be an effective measure to depress the level of oxidative stress of organisms. It has been reported that intake of vegetables and fruits is inversely associated with the risk of many chronic diseases, and antioxidant phytochemicals in vegetables and fruits are considered to be responsible for these health benefits. Antioxidant phytochemicals can be found in many foods and medicinal plants, and play an important role in the prevention and treatment of chronic diseases caused by oxidative stress. They often possess strong antioxidant and free radical scavenging abilities, as well as anti-inflammatory action, which are also the basis of other bioactivities and health benefits, such as anticancer, anti-aging, and protective action for cardiovascular diseases, diabetes mellitus, obesity and neurodegenerative diseases. This review summarizes recent progress on the health benefits of antioxidant phytochemicals, and discusses their potential mechanisms in the prevention and treatment of chronic diseases.

The consensus recommendations in 2018 from The Chinese Society of Hematology (CSH) on indications, conditioning regimens and donor selection for allogeneic hematopoietic stem cell transplantation (allo-HSCT) facilitated the standardization of clinical practices of allo-HSCT in China and progressive integration with the world. There have been new developments since the initial publication. To integrate recent developments and further improve the consensus, a panel of experts from the CSH recently updated the consensus recommendations, which are summarized as follows: (1) there is a new algorithm for selecting appropriate donors for allo-HSCT candidates. Haploidentical donors (HIDs) are the preferred donor choice over matched sibling donors (MSDs) for patients with high-risk leukemia or elderly patients with young offspring donors in experienced centers. This replaces the previous algorithm for donor selection, which favored MSDs over HIDs. (2) Patients with refractory/relapsed lymphoblastic malignancies are now encouraged to undergo salvage treatment with novel immunotherapies prior to HSCT. (3) The consensus has been updated to reflect additional evidence for the application of allo-HSCT in specific groups of patients with hematological malignancies (intermediate-risk acute myeloid leukemia (AML), favorable-risk AML with positive minimal residual disease, and standard-risk acute lymphoblastic leukemia). (4) The consensus has been updated to reflect additional evidence for the application of HSCT in patients with nonmalignant diseases, such as severe aplastic anemia and inherited diseases. (5) The consensus has been updated to reflect additional evidence for the administration of anti-thymocyte globulin, granulocyte colony-stimulating factors and post-transplantation cyclophosphamide in HID-HSCT.

Informing reservoirs with forecasts is highly important for real‐time flood control. This study proposed a forecast‐informed methodology framework for reservoir flood control operation under uncertainty. A new combination of two post‐processing methods, that is, the Cloud model and error‐based copula functions, were developed to merge individual AI‐based forecasts to ensemble flood forecasts, so called stochastic errors‐based Cloud (SE‐Cloud). A multi‐objective robust optimization model (MRO) integrating the risk, resilience, and vulnerability was then proposed to tackle flood control problems under ensemble forecasts; for comparison, a two‐objective stochastic optimization model (TSO) was developed to minimize the expected highest reservoir level and peak release. The proposed methodology was applied to the Lishimen reservoir in the Shifeng River subbasin, China, aiming to comprehensively verify the relationships among deterministic forecasts, ensemble forecasts, and flood control performance. Results showed that the Cloud model could effectively integrate different models and improve forecast accuracy. But a higher deterministic forecast quality did not consistently result in improved flood control performance. SE‐Cloud could capture the peak flow and effectively characterize forecast uncertainties and increased hypervolume values by 13.14%–39.65% compared to the Cloud model, indicating the superiority of ensemble forecasts in generating robust solutions over individual deterministic forecasts. MRO released more inflow than TSO, decreasing the expected highest water level by 0.05 m and incrementing the expected peak release by 4.29%. However, with downstream resilience value remaining at zero, it is demonstrated that MRO improving upstream vulnerability did not necessarily diminish resilience. The enhanced robustness highlights the potential of AI‐based ensemble forecasts in flood control. Key Points Flood scenarios characterized by forecast errors were developed using Cloud model and Copula functions based on individual AI‐based forecasts A multi‐objective robust optimization model integrating the risk, resilience, and vulnerability was proposed to enhance model robustness Ensemble forecasts can be more valuable than deterministic forecasts in the flood control operation

Mastitis is an inflammatory disease caused by microbial infection. Chlorogenic acid (CGA), one of the major phenolic acids in Taraxacum officinale , has natural antioxidant and anti-inflammatory properties in various cell types; however, the effects of CGA on Lipoteichoic acid (LTA)-induced bovine mammary epithelial cells (BMECs) have not been investigated. In this study, the CGA content in T . officinale was determined by High-performance liquid chromatography (HPLC). BMECs were infected with LTA to induce the mastitis model. Different concentrations of CGA were administered after establishing the LTA infection. The results showed that the T . officinale contained CGA 1.36 mg/g. CGA significantly reduced the pro-inflammatory gene and protein expression of TNF-α, IL-6, and IL-1β. In addition, CGA downregulated the NO, TLR2, and NF-κB signaling pathways in LTA-infected bovine mammary epithelial cells. Our results indicate that CGA reduced the expression of TNF-α, IL-6, IL-1β, and TLR2 by inhibiting the phosphorylation of proteins in the NF-κB signaling pathways in a dose-dependent manner. This finding suggests that CGA may be a potential agent for the treatment of mastitis in dairy cows.