Novel naphthoquinone and quinolinedione inhibitors of CDC25 phosphatase activity with antiproliferative properties

CDC25 phosphatases are considered as attractive targets for anti-cancer therapy. To date, quinone derivatives are among the most potent inhibitors of CDC25 phosphatase activity. We present in this paper the synthesis and the biological evaluation of new quinolinedione and naphthoquinone derivatives, containing carboxylic or malonic acids groups introduced to mimic the role of the phosphate moieties of Cyclin-Dependent Kinase complexes. The most efficient compounds show inhibitory activity against CDC25B with IC(50) values in the 10 microM range, and are cytotoxic against HeLa cells.     

A database of microsatellite genotypes for <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

A system for genotyping Saccharomyces cerevisiae is described based on a multiplex of ten microsatellite loci and the MAT locus. A database of genotypes has been developed for 246 yeast strains, including a large set of commercial wine yeasts, as well as 35 sequenced natural isolates currently being sequenced. The latter allow us, for the first time, to make direct comparisons of the relationship between DNA sequence data and microsatellite-based genotypes. The genotyping system provides a rapid and valuable system for strain identification as well as studying population genetics of S. cerevisiae.     

Carbon accumulation in agricultural soils after afforestation: a meta-analysis

Deforestation usually results in significant losses of soil organic carbon (SOC). The rate and factors determining the recovery of this C pool with afforestation are still poorly understood. This paper provides a review of the influence of afforestation on SOC stocks based on a meta-analysis of 33 recent publications (totaling 120 sites and 189 observations), with the aim of determining the factors responsible for the restoration of SOC following afforestation. Based on a mixed linear model, the meta-analysis indicates that the main factors that contribute to restoring SOC stocks after afforestation are: previous land use, tree species planted, soil clay content, preplanting disturbance and, to a lesser extent, climatic zone. Specifically, this meta-analysis (1) indicates that the positive impact of afforestation on SOC stocks is more pronounced in cropland soils than in pastures or natural grasslands; (2) suggests that broadleaf tree species have a greater capacity to accumulate SOC than coniferous species; (3) underscores that afforestation using pine species does not result in a net loss of the whole soil-profile carbon stocks compared with initial values (agricultural soil) when the surface organic layer is included in the accounting; (4) demonstrates that clay-rich soils (> 33%) have a greater capacity to accumulate SOC than soils with a lower clay content (< 33%); (5) indicates that minimizing preplanting disturbances may increase the rate at which SOC stocks are replenished; and (6) suggests that afforestation carried out in the boreal climate zone results in small SOC losses compared with other climate zones, probably because trees grow more slowly under these conditions, although this does not rule out gains over time after the conversion. This study also highlights the importance of the methodological approach used when developing the sampling design, especially the inclusion of the organic layer in the accounting.     

Phytotoxicity of surface waters of the Thames and Brisbane River estuaries: a combined chemical analysis and bioassay approach for the comparison of two systems

The Thames Estuary, UK, and the Brisbane River, Australia, are comparable in size and catchment area. Both are representative of the large and growing number of the world's estuaries associated with major cities. Principle differences between the two systems relate to climate and human population pressures. In order to assess the potential phytotoxic impact of herbicide residues in the estuaries, surface waters were analysed with a PAM fluorometry-based bioassay that employs the photosynthetic efficiency (photosystem II quantum yield) of laboratory cultured microalgae, as an endpoint measure of phytotoxicity. In addition, surface waters were chemically analysed for a limited number of herbicides. Diuron, atrazine and simazine were detected in both systems at comparable concentrations. In contrast, bioassay results revealed that whilst detected herbicides accounted for the observed phytotoxicity of Brisbane River extracts with great accuracy, they consistently explained only around 50% of the phytotoxicity induced by Thames Estuary extracts. Unaccounted for phytotoxicity in Thames surface waters is indicative of unidentified phytotoxins. The greatest phytotoxic response was measured at Charing Cross, Thames Estuary, and corresponded to a diuron equivalent concentration of 180 ng L(-1). The study employs relative potencies (REP) of PSII impacting herbicides and demonstrates that chemical analysis alone is prone to omission of valuable information. Results of the study provide support for the incorporation of bioassays into routine monitoring programs where bioassay data may be used to predict and verify chemical contamination data, alert to unidentified compounds and provide the user with information regarding cumulative toxicity of complex mixtures.     

Efficacy and Safety of Inhaled Carbon Monoxide during Pulmonary Inflammation in Mice

Background

Pulmonary inflammation is a major contributor to morbidity in a variety of respiratory disorders, but treatment options are limited. Here we investigate the efficacy, safety and mechanism of action of low dose inhaled carbon monoxide (CO) using a mouse model of lipopolysaccharide (LPS)-induced pulmonary inflammation.

Methodology

Mice were exposed to 0–500 ppm inhaled CO for periods of up to 24 hours prior to and following intratracheal instillation of 10 ng LPS. Animals were sacrificed and assessed for intraalveolar neutrophil influx and cytokine levels, flow cytometric determination of neutrophil number and activation in blood, lung and lavage fluid samples, or neutrophil mobilisation from bone marrow.

Principal Findings

When administered for 24 hours both before and after LPS, inhaled CO of 100 ppm or more reduced intraalveolar neutrophil infiltration by 40–50%, although doses above 100 ppm were associated with either high carboxyhemoglobin, weight loss or reduced physical activity. This anti-inflammatory effect of CO did not require pre-exposure before induction of injury. 100 ppm CO exposure attenuated neutrophil sequestration within the pulmonary vasculature as well as LPS-induced neutrophilia at 6 hours after LPS, likely due to abrogation of neutrophil mobilisation from bone marrow. In contrast to such apparently beneficial effects, 100 ppm inhaled CO induced an increase in pulmonary barrier permeability as determined by lavage fluid protein content and translocation of labelled albumin from blood to the alveolar space.

Conclusions

Overall, these data confirm some protective role for inhaled CO during pulmonary inflammation, although this required a dose that produced carboxyhemoglobin values close to potentially toxic levels for humans, and increased lung permeability.     

Polymorphic regions affecting human height also control stature in cattle

Orthologous positions of 55 genes associated with height in four human populations were located on the bovine genome. Single nucleotide polymorphisms close to eight of these genes were significantly associated with stature in cattle (Bos taurus and Bos indicus). This suggests that these genes may contribute to controlling stature across mammalian species.     

Associations between single nucleotide polymorphisms in 33 candidate genes and meat quality traits in commercial pigs

This study aimed to evaluate the effects of single nucleotide polymorphisms (SNPs) in candidate genes for meat quality using a custom 96‐SNP panel (Illumina Vera Code GoldenGate Assay) on 15 traits collected from 400 commercial pigs. Meat quality measurements included muscle pH, color (L*, a* and b*), drip loss, cooking loss, peak shear force and six sensory traits including appearance (outside and inside), tenderness, juiciness, flavor and overall liking as well as carcass weight and probe yield. Thirty‐five SNPs with minor allele frequencies > 0.10 remained for the multimarker association using the GLM procedure of sas 9.2. Results showed that 20 SNPs were significantly associated with at least one of the traits with either additive or dominance or both effects (P < 0.05). Among these significant SNPs, five of them in ADIPOQ, FTO, TNF, LEPR and AMPD1 had an effect on more than three traits simultaneously; those in MC4R, CAST, DGAT1 and MYF6 had an effect on two traits, while the others were associated with one trait. The results suggest that these markers could be incorporated into commercial pigs for marker‐assisted selection and breeding programs for carcass and meat quality trait improvement.     

Next generation modeling in GWAS: comparing different genetic architectures

The continuous advancement in genotyping technology has not been accompanied by the application of innovative statistical methods, such as multi-marker methods (MMM), to unravel genetic associations with complex traits. Although the performance of MMM has been widely explored in a prediction context, little is known on their behavior in the quantitative trait loci (QTL) detection under complex genetic architectures. We shed light on this still open question by applying Bayes A (BA) and Bayesian LASSO (BL) to simulated and real data. Both methods were compared to the single marker regression (SMR). Simulated data were generated in the context of six scenarios differing on effect size, minor allele frequency (MAF) and linkage disequilibrium (LD) between QTLs. These were based on real SNP genotypes in chromosome 21 from the Spanish Bladder Cancer Study. We show how the genetic architecture dramatically affects the behavior of the methods in terms of power, type I error and accuracy of estimates. Markers with high MAF are easier to detect by all methods, especially if they have a large effect on the phenotypic trait. A high LD between QTLs with either large or small effects differently affects the power of the methods: it impairs QTL detection with BA, irrespectively of the effect size, although boosts that of small effects with BL and SMR. We demonstrate the convenience of applying MMM rather than SMR because of their larger power and smaller type I error. Results from real data when applying MMM suggest novel associations not detected by SMR.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.