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Conductive and also injectable hyaluronic acid/gelatin/gold nanorod hydrogels regarding increased operative interpretation as well as bioprinting.
Objective Environmental factors can influence obesity by epigenetic mechanisms. The aim of this study was to investigate obesity-related epigenetic changes and the potential for reversal of these changes in the liver of Göttingen minipigs subjected to diet interventions. Methods High-throughput liquid hybridization capture-based bisulfite sequencing (LHC-BS) was used to quantify the methylation status of gene promotor regions in liver tissue in three groups of male castrated Göttingen minipigs a standard chow group (SD, N = 7); a group fed high fat/fructose/cholesterol diet (FFC, N = 10) and a group fed high fat/fructose/cholesterol diet during 7 months and reversed to standard diet for 6 months (FFC/SD, N = 12). Expression profiling by qPCR of selected metabolically relevant genes was performed in liver tissue from all pigs. Results The pigs in the FFC diet group became morbidly obese. The FFC/SD diet did not result in a complete reversal of the body weight to the same weight as in the SD group, but it resulted in reversal of all lipid related metabolic parameters. Here we identified widespread differences in the patterning of cytosine methylation of promoters between the different feeding groups. By combining detection of differentially methylated genes with a rank-based hypergeometric overlap algorithm, we identified 160 genes showing differential methylation in corresponding promoter regions in the FFC diet group when comparing with both the SD and FFC/SD groups. As expected, this differential methylation under FFC diet intervention induced de-regulation of several metabolically-related genes involved in lipid/cholesterol metabolism, inflammatory response and fibrosis generation. Moreover, five genes, of which one is a fibrosis-related gene (MMP9), were still perturbed after diet reversion. Conclusion Our findings highlight the potential of exploring diet-epigenome interactions for treatment of obesity.Type 1 and 2 diabetes (T1/2D) are complex metabolic diseases caused by absolute or relative loss of functional β-cell mass, respectively. Both diseases are influenced by multiple genetic loci that alter disease risk. For many of the disease-associated loci, the causal candidate genes remain to be identified. Remarkably, despite the partially shared phenotype of the two diabetes forms, the associated loci for T1D and T2D are almost completely separated. We hypothesized that some of the genes located in risk loci for T1D and T2D interact in common pancreatic islet networks to mutually regulate important islet functions which are disturbed by disease-associated variants leading to β-cell dysfunction. To address this, we took a dual systems genetics approach. All genes located in 57 T1D and 243 T2D established genome-wide association studies (GWAS) loci were extracted and filtered for genes expressed in human islets using RNA sequencing data, and then integrated with; (1) human islet expression quantitative traitnd cell death and survival. In summary, our study has identified a number of new plausible common candidate genes and pathways for T1D and T2D.Genetic testing has the potential to revolutionize primary care, but few health systems have developed the infrastructure to support precision population medicine applications or attempted to evaluate its impact on patient and provider outcomes. In 2018, Sanford Health, the nation's largest rural nonprofit health care system, began offering genetic testing to its primary care patients. To date, more than 11,000 patients have participated in the Sanford Chip Program, over 90% of whom have been identified with at least one informative pharmacogenomic variant, and about 1.5% of whom have been identified with a medically actionable predisposition for disease. This manuscript describes the rationale for offering the Sanford Chip, the programs and infrastructure implemented to support it, and evolving plans for research to evaluate its real-world impact.Lung cancer is one of the deadliest, most aggressive cancers. Abrupt changes in gene expression represent an important challenge to understand and fight the disease. Gene co-expression networks (GCNs) have been widely used to study the genomic regulatory landscape of human cancer. Here, based on 1,143 RNA-Seq experiments from the TCGA collaboration, we constructed GCN for the most common types of lung tumors adenocarcinoma (TAD) and squamous cells (TSCs) as well as their respective control networks (NAD and NSC). We compared the number of intra-chromosome (cis-) and inter-chromosome (trans-) co-expression interactions in normal and cancer GCNs. We compared the number of shared interactions between TAD and TSC, as well as in NAD and NSC, to observe which phenotypes were more alike. By means of an over-representation analysis, we associated network topology features with biological functions. We found that TAD and TSC present mostly cis- small disconnected components, whereas in control GCNs, both types have a er GCNs, a 73-fold larger intersection. This suggests that in lung cancer a process of de-differentiation may be occurring. To further investigate the implications of the loss of distant co-expression, it will become necessary to broaden the investigation with other omic-based approaches. However, the present approach provides a basis for future work toward an integrative perspective of abnormal transcriptional regulatory programs in lung cancer.Egg production is an important economic trait in the commercial poultry industry. Ovarian follicle development plays a pivotal role in regulation of laying hen performance and reproductive physiology. However, the key genes and signaling pathways involved in the various-stages of laying hen follicular development remain poorly understood. In this study, transcriptomes of ovarian follicles at three developmental stages, the large white follicle (LWF), small yellow follicle (SYF), and large yellow follicle (LYF), were comparatively analyzed in hens with high (HR) and low (LR) egg-laying rates by RNA-sequencing. Eighteen cDNA libraries were constructed and a total of 236, 544, and 386 unigenes were significantly differentially expressed in the LWF, SYF, and LYF follicles of HR and LR hens, respectively. Among them, 47 co-transcribed differentially expressed genes (DEGs) in LWF and SYF, 68 co-expressed DEGs in SYF and LYF, and 54 co-expressed DEGs in LWF and LYF were mined. Thirteen co-expressed DEGs were found in LWF, SYF, and LYF follicles. Eighteen candidate genes, including P2RX1, CAB39L, BLK, CSMD3, GPR65, ADRB2, CSMD1, PLPP4, ATF3, PRLL, STMN3, RORB, PIK3R1, PERP1, ACSBG1, MRTO4, CDKN1A, and EDA2R were identified to be potentially related to egg production. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis indicated neuroactive ligand-receptor interaction, cell adhesion molecules, peroxisome proliferator-activated receptor pathway, and cAMP signaling pathway might elicit an important role in formation of egg-laying traits by influencing ovarian follicle development. This study represents the first transcriptome analysis of various-sized follicles between HR and LR hens. These results provide useful molecular evidence for elucidating the genetic mechanism underlying ovarian follicle development associated with egg production in chicken.Increasing studies show that long non-coding RNAs (lncRNAs) play essential roles in various fundamental biological processes. Long non-coding RNA growth arrest-specific transcript 5 (GAS5) showed differential expressions between young and old mouse brains in our previous RNA-Seq data, suggesting its potential role in senescence and brain aging. Examination using quantitative reverse transcription-polymerase chain reaction revealed that GAS5 had a significantly higher expression level in the old mouse brain hippocampus region than the young one. Cellular fractionation using hippocampus-derived HT22 cell line confirmed its nucleoplasm and cytoplasm subcellular localization. Overexpression or knockdown of GAS5 in HT22 cell line revealed that GAS5 inhibits cell cycle progression and promotes cell apoptosis. RNA-Seq analysis of GAS5-knockdown HT22 cells identified differentially expressed genes related to cell proliferation (e.g., DNA replication and nucleosome assembly biological processes). RNA pull-down assay using mouse brain hippocampus tissues showed that potential GAS5 interacting proteins could be enriched into several Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and some of them are involved in senescence-associated diseases such as Parkinson's and Alzheimer's diseases. These results contribute to understand better the underlying functional network of GAS5 and its interacting proteins in senescence at brain tissue and brain-derived cell line levels. Our study may also provide a reference for developing diagnostic and clinic biomarkers of GAS5 in senescence and brain aging.Transition to flowering is an important stage of plant development. learn more Many regulatory modules that control floral transition are conservative across plants. This process is best studied for the model plant Arabidopsis thaliana. The homologues of Arabidopsis genes responsible for the flowering initiation in legumes have been identified, and available data on their expression provide a good basis for gene network modeling. In this study, we developed several dynamical models of a gene network controlling transition to flowering in pea (Pisum sativum) using two different approaches. We used differential equations for modeling a previously proposed gene regulation scheme of floral initiation in pea and tested possible alternative hypothesis about some regulations. As the second approach, we applied neural networks to infer interactions between genes in the network directly from gene expression data. All models were verified on previously published experimental data on the dynamic expression of the main genes in the wild type and in three mutant genotypes. Based on modeling results, we made conclusions about the functionality of the previously proposed interactions in the gene network and about the influence of different growing conditions on the network architecture. It was shown that regulation of the PIM, FTa1, and FTc genes in pea does not correspond to the previously proposed hypotheses. The modeling suggests that short- and long-day growing conditions are characterized by different gene network architectures. Overall, the results obtained can be used to plan new experiments and create more accurate models to study the flowering initiation in pea and, in a broader context, in legumes.Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression.
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