Carbonated Drinks Impact Follicle Development, Expression of Ovarian FSHR and Serum Caspase-3 in Mice

Objectives: The present study aimed to assess the effects of Coca-Cola and Pepsi-Cola on the development of ovaries and follicles, and on the reproduction of animals

A simulation study for comparing testing statistics in response-adaptive randomization

<p>Abstract</p> <p>Background</p> <p>Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically. However, the small sample properties of commonly used test statistics in response-adaptive randomization are not fully studied.</p> <p>Methods</p> <p>Simulations are systematically conducted to characterize the statistical properties of eight test statistics in six response-adaptive randomization methods at six allocation targets with sample sizes ranging from 20 to 200. Since adaptive randomization is usually not recommended for sample size less than 30, the present paper focuses on the case with a sample of 30 to give general recommendations with regard to test statistics for contingency tables in response-adaptive randomization at small sample sizes.</p> <p>Results</p> <p>Among all asymptotic test statistics, the Cook's correction to chi-square test (<it>T</it>_<it>MC</it>) is the best in attaining the nominal size of hypothesis test. The William's correction to log-likelihood ratio test (<it>T</it>_<it>ML</it>) gives slightly inflated type I error and higher power as compared with <it>T</it>_<it>MC</it>, but it is more robust against the unbalance in patient allocation. <it>T</it>_{<it>MC </it>}and <it>T</it>_{<it>ML </it>}are usually the two test statistics with the highest power in different simulation scenarios. When focusing on <it>T</it>_{<it>MC </it>}and <it>T</it>_<it>ML</it>, the generalized drop-the-loser urn (GDL) and sequential estimation-adjusted urn (SEU) have the best ability to attain the correct size of hypothesis test respectively. Among all sequential methods that can target different allocation ratios, GDL has the lowest variation and the highest overall power at all allocation ratios. The performance of different adaptive randomization methods and test statistics also depends on allocation targets. At the limiting allocation ratio of drop-the-loser (DL) and randomized play-the-winner (RPW) urn, DL outperforms all other methods including GDL. When comparing the power of test statistics in the same randomization method but at different allocation targets, the powers of log-likelihood-ratio, log-relative-risk, log-odds-ratio, Wald-type Z, and chi-square test statistics are maximized at their corresponding optimal allocation ratios for power. Except for the optimal allocation target for log-relative-risk, the other four optimal targets could assign more patients to the worse arm in some simulation scenarios. Another optimal allocation target, <it>R</it>_{<it>RSIHR</it>}, proposed by Rosenberger and Sriram (<it>Journal of Statistical Planning and Inference</it>, 1997) is aimed at minimizing the number of failures at fixed power using Wald-type Z test statistics. Among allocation ratios that always assign more patients to the better treatment, <it>R</it>_{<it>RSIHR </it>}usually has less variation in patient allocation, and the values of variation are consistent across all simulation scenarios. Additionally, the patient allocation at <it>R</it>_{<it>RSIHR </it>}is not too extreme. Therefore, <it>R</it>_{<it>RSIHR </it>}provides a good balance between assigning more patients to the better treatment and maintaining the overall power.</p> <p>Conclusion</p> <p>The Cook's correction to chi-square test and Williams' correction to log-likelihood-ratio test are generally recommended for hypothesis test in response-adaptive randomization, especially when sample sizes are small. The generalized drop-the-loser urn design is the recommended method for its good overall properties. Also recommended is the use of the <it>R</it>_{<it>RSIHR </it>}allocation target.</p

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications.

Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression

Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline

The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable genetic elements, particularly retrotransposons. There are many different types of retrotransposon in mammalian genomes, and these target different points in germline development to amplify and integrate into new genomic locations. Germ cells, and their pluripotent developmental precursors, have evolved a variety of genome defence mechanisms that suppress retrotransposon activity and maintain genome stability across the generations. Here, we review recent advances in understanding how retrotransposon activity is suppressed in the mammalian germline, how genes involved in germline genome defence mechanisms are regulated, and the consequences of mutating these genome defence genes for the developing germline

Integration of Solexa sequences on an ultradense genetic map in Brassica rapa L.

<p>Abstract</p> <p>Background</p> <p>Sequence related amplified polymorphism (SRAP) is commonly used to construct high density genetic maps, map genes and QTL of important agronomic traits in crops and perform genetic diversity analysis without knowing sequence information. To combine next generation sequencing technology with SRAP, Illumina's Solexa sequencing was used to sequence tagged SRAP PCR products.</p> <p>Results</p> <p>Three sets of SRAP primers and three sets of tagging primers were used in 77,568 SRAP PCR reactions and the same number of tagging PCR reactions respectively to produce a pooled sample for Illumina's Solexa sequencing. After sequencing, 1.28 GB of sequence with over 13 million paired-end sequences was obtained and used to match Solexa sequences with their corresponding SRAP markers and to integrate Solexa sequences on an ultradense genetic map. The ultradense genetic bin map with 465 bins was constructed using a recombinant inbred (RI) line mapping population in <it>B. rapa</it>. For this ultradense genetic bin map, 9,177 SRAP markers, 1,737 integrated unique Solexa paired-end sequences and 46 SSR markers representing 10,960 independent genetic loci were assembled and 141 unique Solexa paired-end sequences were matched with their corresponding SRAP markers. The genetic map in <it>B. rapa </it>was aligned with the previous ultradense genetic map in <it>B. napus </it>through common SRAP markers in these two species. Additionally, SSR markers were used to perform alignment of the current genetic map with other five genetic maps in <it>B. rapa </it>and <it>B. napus</it>.</p> <p>Conclusion</p> <p>We used SRAP to construct an ultradense genetic map with 10,960 independent genetic loci in <it>B. rapa </it>that is the most saturated genetic map ever constructed in this species. Using next generation sequencing, we integrated 1,878 Solexa sequences on the genetic map. These integrated sequences will be used to assemble the scaffolds in the <it>B. rapa </it>genome. Additionally, this genetic map may be used for gene cloning and marker development in <it>B. rapa </it>and <it>B. napus</it>.</p

Visualized exploratory spatiotemporal analysis of hand-foot-mouth disease in southern China

Objectives: In epidemiological research, major studies have focused on theoretical models; however, few methods of visual analysis have been used to display the patterns of disease distribution.Design: For this study, a method combining the space-time cube (STC) with space-time scan statistics (STSS) was used to analyze the pattern of incidence of hand-foot-mouth disease (HFMD) in Guangdong Province from May 2008 to March 2009. In this research, STC was used to display the spatiotemporal pattern of incidence of HFMD, and STSS were used to detect the local aggregations of the disease.Setting: The hand-foot-mouth disease data were obtained from Guangdong Province from May 2008 to March 2009, with a total of 68,130 cases.Results: The STC analysis revealed a differential pattern of HFMD incidence among different months and cities and also showed that the population density and average precipitation are correlated with the incidence of HFMD. The STSS analysis revealed that the most likely aggregation includes the Shenzhen, Foshan and Dongguan populations, which are the most developed regions in Guangdong Province.Conclusion: Both STC and STSS are efficient tools for the exploratory data analysis of disease transmission. STC clearly displays the spatiotemporal patterns of disease. Using the maximum likelihood ratio, the STSS model precisely locates the most likely aggregation

Stochastic Dominance Analysis of CTA Funds

In this paper, we employ the stochastic dominance approach to rank the performance of commodity trading advisors (CTA) funds. An advantage of this approach is that it alleviates the problems that can arise if CTA returns are not normally distributed by utilizing the entire returns distribution. We find both first-order and higher-order stochastic dominance relationships amongst the CTA funds and conclude that investors would be better off investing in the first-order dominant funds to maximize their expected utilities and expected wealth. However, for higher-order dominant CTA, riskaverse investors can maximize their expected utilities but not their expected wealth. We conclude that the stochastic dominance approach is more appropriate compared with traditional approaches as a filter in the CTA selection process given that a meaningful economic interpretation of the results is possible as the entire return distribution is utilized when returns are non-normal

Quantitative proteomic analysis of the influence of lignin on biofuel production by Clostridium acetobutylicum ATCC 824

Background: Clostridium acetobutylicum has been a focus of research because of its ability to produce high-value compounds that can be used as biofuels. Lignocellulose is a promising feedstock, but the lignin–cellulose–hemicellulose biomass complex requires chemical pre-treatment to yield fermentable saccharides, including cellulose-derived cellobiose, prior to bioproduction of acetone–butanol–ethanol (ABE) and hydrogen. Fermentation capability is limited by lignin and thus process optimization requires knowledge of lignin inhibition. The effects of lignin on cellular metabolism were evaluated for C. acetobutylicum grown on medium containing either cellobiose only or cellobiose plus lignin. Microscopy, gas chromatography and 8-plex iTRAQ-based quantitative proteomic technologies were applied to interrogate the effect of lignin on cellular morphology, fermentation and the proteome. Results: Our results demonstrate that C. acetobutylicum has reduced performance for solvent production when lignin is present in the medium. Medium supplemented with 1 g L−1 of lignin led to delay and decreased solvents production (ethanol; 0.47 g L−1 for cellobiose and 0.27 g L−1 for cellobiose plus lignin and butanol; 0.13 g L−1 for cellobiose and 0.04 g L−1 for cellobiose plus lignin) at 20 and 48 h, respectively, resulting in the accumulation of acetic acid and butyric acid. Of 583 identified proteins (FDR < 1 %), 328 proteins were quantified with at least two unique peptides. Up- or down-regulation of protein expression was determined by comparison of exponential and stationary phases of cellobiose in the presence and absence of lignin. Of relevance, glycolysis and fermentative pathways were mostly down-regulated, during exponential and stationary growth phases in presence of lignin. Moreover, proteins involved in DNA repair, transcription/translation and GTP/ATP-dependent activities were also significantly affected and these changes were associated with altered cell morphology. Conclusions: This is the first comprehensive analysis of the cellular responses of C. acetobutylicum to lignin at metabolic and physiological levels. These data will enable targeted metabolic engineering strategies to optimize biofuel production from biomass by overcoming limitations imposed by the presence of lignin