126 research outputs found

    Effect of sodium butyrate on glucose and lipid metabolism, insulin expression and apoptosis of β-cells in obese pregnant rats

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    Purpose: To study the influence of sodium butyrate on the metabolism of lipid and glucose, insulin expression and apoptosis of β-cells in obese pregnant rats. Methods: Three groups of one hundred and twenty 4-week-old female C5BL/6J mice were used: control, high-fat diet and sodium butyrate groups. Insulin, triglycerides and total cholesterol were evaluated by enzyme-linked immunosorbent assay (ELISA). Insulin levels, as well as area and quality of islet β-cells were assessed using Image Pro Plus software. The number of DAPI-positive islet cells, positive expression of bcl-2 in each islet cell, and apoptosis of islet β-cells in each group were determined. Results: The expression levels of insulin in high-fat diet group and butyrate group were significantly reduced, relative to control, but insulin expression level in Na butyrate group increased, relative to high- fat diet mice (p < 0.01). The area and quality of islet β-cells in high-fat diet and sodium butyrate groups were markedly higher in sodium butyrate group than in high-fat diet group (p < 0.01). The bcl-2 expression in islet β-cells rose in mice given high-fat diet, relative to control and sodium butyrate groups (p < 0.01). Conclusion: Sodium butyrate facilitates glucose and lipid metabolism, but increases insulin expression, and effectively inhibits apoptosis of islet β-cells in obese pregnant mice. Thus, sodium butyrate may be useful in the prevention and treatment of metabolic disorders due to diabetes mellitus (DM)

    Metabolic engineering of Corynebacterium glutamicum for efficient production of optically pure (2R,3R)-2,3-butanediol

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    Background: 2,3-butanediol is an important platform compound which has a wide range of applications, involving in medicine, chemical industry, food and other fields. Especially the optically pure (2R,3R)-2,3-butanediol can be employed as an antifreeze agent and as the precursor for producing chiral compounds. However, some (2R,3R)-2,3-butanediol overproducing strains are pathogenic such as Enterobacter cloacae and Klebsiella oxytoca. Results: In this study, a (3R)-acetoin overproducing C. glutamicum strain, CGS9, was engineered to produce optically pure (2R,3R)-2,3-butanediol efficiently. Firstly, the gene bdhA from B. subtilis 168 was integrated into strain CGS9 and its expression level was further enhanced by using a strong promoter Psod and ribosome binding site (RBS) with high translation initiation rate, and the (2R,3R)-2,3-butanediol titer of the resulting strain was increased by 33.9%. Then the transhydrogenase gene udhA from E. coli was expressed to provide more NADH for 2,3-butanediol synthesis, which reduced the accumulation of the main byproduct acetoin by 57.2%. Next, a mutant atpG was integrated into strain CGK3, which increased the glucose consumption rate by 10.5% and the 2,3-butanediol productivity by 10.9% in shake-flask fermentation. Through fermentation engineering, the most promising strain CGK4 produced a titer of 144.9\ua0g/L (2R,3R)-2,3-butanediol with a yield of 0.429\ua0g/g glucose and a productivity of 1.10\ua0g/L/h in fed-batch fermentation. The optical purity of the resulting (2R,3R)-2,3-butanediol surpassed 98%. Conclusions: To the best of our knowledge, this is the highest titer of optically pure (2R,3R)-2,3-butanediol achieved by GRAS strains, and the result has demonstrated that C. glutamicum is a competitive candidate for (2R,3R)-2,3-butanediol production

    Segmentation of the Prostatic Gland and the Intraprostatic Lesions on Multiparametic Magnetic Resonance Imaging Using Mask Region-Based Convolutional Neural Networks

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    Purpose: Accurate delineation of the prostate gland and intraprostatic lesions (ILs) is essential for prostate cancer dose-escalated radiation therapy. The aim of this study was to develop a sophisticated deep neural network approach to magnetic resonance image analysis that will help IL detection and delineation for clinicians. Methods and Materials: We trained and evaluated mask region-based convolutional neural networks to perform the prostate gland and IL segmentation. There were 2 cohorts in this study: 78 public patients (cohort 1) and 42 private patients from our institution (cohort 2). Prostate gland segmentation was performed using T2-weighted images (T2WIs), although IL segmentation was performed using T2WIs and coregistered apparent diffusion coefficient maps with prostate patches cropped out. The IL segmentation model was extended to select 5 highly suspicious volumetric lesions within the entire prostate. Results: The mask region-based convolutional neural networks model was able to segment the prostate with dice similarity coefficient (DSC) of 0.88 ± 0.04, 0.86 ± 0.04, and 0.82 ± 0.05; sensitivity (Sens.) of 0.93, 0.95, and 0.95; and specificity (Spec.) of 0.98, 0.85, and 0.90. However, ILs were segmented with DSC of 0.62 ± 0.17, 0.59 ± 0.14, and 0.38 ± 0.19; Sens. of 0.55 ± 0.30, 0.63 ± 0.28, and 0.22 ± 0.24; and Spec. of 0.974 ± 0.010, 0.964 ± 0.015, and 0.972 ± 0.015 in public validation/public testing/private testing patients when trained with patients from cohort 1 only. When trained with patients from both cohorts, the values were as follows: DSC of 0.64 ± 0.11, 0.56 ± 0.15, and 0.46 ± 0.15; Sens. of 0.57 ± 0.23, 0.50 ± 0.28, and 0.33 ± 0.17; and Spec. of 0.980 ± 0.009, 0.969 ± 0.016, and 0.977 ± 0.013. Conclusions: Our research framework is able to perform as an end-to-end system that automatically segmented the prostate gland and identified and delineated highly suspicious ILs within the entire prostate. Therefore, this system demonstrated the potential for assisting the clinicians in tumor delineation

    Establishing chromosomal design-build-test-learn through a synthetic chromosome and its combinatorial reconfiguration

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    Chromosome-level design-build-test-learn cycles (chrDBTLs) allow systematic combinatorial reconfiguration of chromosomes with ease. Here, we established chrDBTL with a redesigned synthetic Saccharomyces cerevisiae chromosome XV, synXV. We designed and built synXV to harbor strategically inserted features, modified elements, and synonymously recoded genes throughout the chromosome. Based on the recoded chromosome, we developed a method to enable chrDBTL: CRISPR-Cas9-mediated mitotic recombination with endoreduplication (CRIMiRE). CRIMiRE allowed the creation of customized wild-type/synthetic combinations, accelerating genotype-phenotype mapping and synthetic chromosome redesign. We also leveraged synXV as a "build-to-learn" model organism for translation studies by ribosome profiling. We conducted a locus-to-locus comparison of ribosome occupancy between synXV and the wild-type chromosome, providing insight into the effects of codon changes and redesigned features on translation dynamics in vivo. Overall, we established synXV as a versatile reconfigurable system that advances chrDBTL for understanding biological mechanisms and engineering strains. </p

    Genetic Variants at 1p11.2 and Breast Cancer Risk: A Two-Stage Study in Chinese Women

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    BACKGROUND: Genome-wide association studies (GWAS) have identified several breast cancer susceptibility loci, and one genetic variant, rs11249433, at 1p11.2 was reported to be associated with breast cancer in European populations. To explore the genetic variants in this region associated with breast cancer in Chinese women, we conducted a two-stage fine-mapping study with a total of 1792 breast cancer cases and 1867 controls. METHODOLOGY/PRINCIPAL FINDINGS: Seven single nucleotide polymorphisms (SNPs) including rs11249433 in a 277 kb region at 1p11.2 were selected and genotyping was performed by using TaqMan® OpenArray™ Genotyping System for stage 1 samples (878 cases and 900 controls). In stage 2 (914 cases and 967 controls), three SNPs (rs2580520, rs4844616 and rs11249433) were further selected and genotyped for validation. The results showed that one SNP (rs2580520) located at a predicted enhancer region of SRGAP2 was consistently associated with a significantly increased risk of breast cancer in a recessive genetic model [Odds Ratio (OR)  =  1.66, 95% confidence interval (CI)  =  1.16-2.36 for stage 2 samples; OR  =  1.51, 95% CI  =  1.16-1.97 for combined samples, respectively]. However, no significant association was observed between rs11249433 and breast cancer risk in this Chinese population (dominant genetic model in combined samples: OR  =  1.20, 95% CI  =  0.92-1.57). CONCLUSIONS/SIGNIFICANCE: Genotypes of rs2580520 at 1p11.2 suggest that Chinese women may have different breast cancer susceptibility loci, which may contribute to the development of breast cancer in this population
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