nti-cholesterol and antioxidant potentialities.

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier suprediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.Sea cucumbers possess the remarkable capacity to regenerate their body parts or organs. Regeneration of host organs and/or body parts involves reconstruction of the host associated microbiota, however, the dynamics and contribution of microbiota to the regeneration process are largely unknown due to a lack of experimental models. To track the dynamics of individual gut microbiomes during gut regeneration, both caged mariculture and laboratory isolator systems of sea cucumbers (Apostichopus japonicus) were developed and longitudinal meta16S analyses were performed. Under natural environmental conditions in the caged mariculture system, both bacterial and eukaryotic communities in sea cucumbers’ guts appeared to be reconstructed within 4 months after evisceration. Using the laboratory isolator, which can trace daily dynamics, we found that fecal microbiota collected before evisceration were clearly different from those collected after evisceration. We also identified eight key bacteria, belonging to Alteromonadaceae, Rhodobacteraceae, Oceanospirillaceae and family-unassigned Gammaproteobacteria, suggesting that these bacteria might interact with the host during the gut regeneration process. Six of the eight key bacteria were isolated for further bioassay using the isolator developed in this study to test whether these isolates affect gut regeneration.As a complex microecological system, the gut microbiota plays crucial roles in many aspects, including immunology, physiology and development. The specific function and mechanism of the gut microbiota in birds are distinct due to their body structure, physiological attributes and life history. Data on the gut microbiota of the common kestrel, a second-class protected animal species in China, are currently scarce. With high-throughput sequencing technology, we characterized the bacterial community of the gut from nine fecal samples from a wounded common kestrel by sequencing the V3-V4 region of the 16S ribosomal RNA gene. Our results showed that Proteobacteria (41.078%), Firmicutes (40.923%) and Actinobacteria (11.191%) were the most predominant phyla. Lactobacillus (20.563%) was the most dominant genus, followed by Escherichia-Shigella (17.588%) and Acinetobacter (5.956%). Our results would offer fundamental data and direction for the wildlife rescue.

Alcohol use disorder (AUD) is a complex genetic disorder with very high heritability. This polygenic disorder not only results in increased morbidity and mortality, it is also a substantial social and economic burden on families and the nation. For past three decades, several genetic studies were conducted to identify genes and pathways associated with AUD. This review aims to summarize past efforts and recent advances in genetic association studies of AUD and related traits.

Initial genetic association studies achieved a limted success and suffered from low power due to small sample sizes. AUD is a polygenic trait and data from several thousands individuals was required to identify the genetic factors of small effect sizes. learn more The scenario changed recently with technological advances and significant reduction in cost of the genome wide association analyses (GWAS). This enabled researchers to generate genomic data on mega biobanks and cohorts with access to extensive clinical and non-clinical phenotypes. Pubtic studies of AUDs will definetely motivate researchers and lead to better therapeutic interventions for this complex disorder.

This article is to review recent technical developments and their clinical applications in cancer imaging quantitative measurement of cellular and vascular properties of the tumors.

Rapid development of fast Magnetic Resonance Imaging (MRI) technologies over last decade brought new opportunities in quantitative MRI methods to measure both cellular and vascular properties of tumors simultaneously.

Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.

Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.