The synthesis and SAR of 2-arylsulfanyl-phenyl piperazinyl acetic acids as glyT-1 inhibitors

Elevation of glycine levels and activation of the NMDA receptor by inhibition of the glycine transporter 1 (GlyT-1) is a potential strategy for the treatment of schizophrenia. A novel series of GlyT-1 inhibitors have been identified containing the 2-arylsulfanyl-phenylpiperazine motif. The most prominent member of this series, (R)-4-[5-chloro-2-(4-methoxy-phenylsulfanyl)-phenyl]-2-methyl-piperazin-1-yl-acetic acid (31) is a potent glycine transporter-1 inhibitor (IC(50)=150 nM), which elevated glycine levels in rat ventral hippocampus as measured by microdialysis in vivo at doses of 1.2-4.6 mg/kg s.c.     

The Discovery of orally available thrombin inhibitors : Studies towards the optimisation of CGH1668

The chemical optimisation of CGH1668 1 is described employing an in vivo model of absorption to determine the influence on bioavailability of single point modifications to five key molecular templates. The discovery of an orally bioavailable and selective thrombin inhibitor, 24, highlights the utility of this approach.     

Decoding Diffusivity in Multiple Sclerosis: Analysis of Optic Radiation Lesional and Non-Lesional White Matter

Objectives

Diffusion tensor imaging (DTI) has been suggested as a new promising tool in MS that may provide greater pathological specificity than conventional MRI, helping, therefore, to elucidate disease pathogenesis and monitor therapeutic efficacy. However, the pathological substrates that underpin alterations in brain tissue diffusivity are not yet fully delineated. Tract-specific DTI analysis has previously been proposed in an attempt to alleviate this problem. Here, we extended this approach by segmenting a single tract into areas bound by seemingly similar pathological processes, which may better delineate the potential association between DTI metrics and underlying tissue damage.

Method

Several compartments were segmented in optic radiation (OR) of 50 relapsing-remitting MS patients including T2 lesions, proximal and distal parts of fibers transected by lesion and fibers with no discernable pathology throughout the entire length of the OR.

Results

Asymmetry analysis between lesional and non-lesional fibers demonstrated a marked increase in Radial Diffusivity (RD), which was topographically limited to focal T2 lesions and potentially relates to the lesional myelin loss. A relative elevation of Axial Diffusivity (AD) in the distal part of the lesional fibers was observed in a distribution consistent with Wallerian degeneration, while diffusivity in the proximal portion of transected axons remained normal. A moderate, but significant elevation of RD in OR non-lesional fibers was strongly associated with the global (but not local) T2 lesion burden and is probably related to microscopic demyelination undetected by conventional MRI.

Conclusion

This study highlights the utility of the compartmentalization approach in elucidating the pathological substrates of diffusivity and demonstrates the presence of tissue-specific patterns of altered diffusivity in MS, providing further evidence that DTI is a sensitive marker of tissue damage in both lesions and NAWM. Our results suggest that, at least within the OR, parallel and perpendicular diffusivities are affected by tissue restructuring related to distinct pathological processes.     

Covalent attachment of peptides to cytochrome C for automated sequence determination.

Because small peptides are lost into the organic solvents used, it is virtually impossible to obtain the complete amino acid sequence of a small peptide using only an automated peptide sequencer of the spinning cup type. To overcome this problem we have extended peptides at the carboxy terminus by attachment to equine cytochrome c by a water soluble carbodiimide, relying on the acetylated N-terminus of the cytochrome to minimize its direct contribution to recovery of PTH-amino acids. The Model Peptide H-Leu-Trp-Met-Arg-phe-Ala-OH was used for most experiments. After reaction of 3H-peptide with cytochrome c, about one-third of the tritium counts migrated with cytochrome c during gel filtration. After attachment, the amino acid sequence of the hexapeptide was readily determined with a single cleavage Quadrol program in a Beckman 890B sequencer, whereas only the N-terminal residue was recovered without attachment. The repetitive yield after attachment was 95-96%, with 21-27+ overlap and an initial yield of 18-20%. Sequence data with other peptides illustrate applications and present limitations of our approach.     

Defining the cause of skewed X-chromosome inactivation in X-linked mental retardation by use of a mouse model

Extreme skewing of X-chromosome inactivation (XCI) is rare in the normal female population but is observed frequently in carriers of some X-linked mutations. Recently, it has been shown that various forms of X-linked mental retardation (XLMR) have a strong association with skewed XCI in female carriers, but the mechanisms underlying this skewing are unknown. ATR-X syndrome, caused by mutations in a ubiquitously expressed, chromatin-associated protein, provides a clear example of XLMR in which phenotypically normal female carriers virtually all have highly skewed XCI biased against the X chromosome that harbors the mutant allele. Here, we have used a mouse model to understand the processes causing skewed XCI. In female mice heterozygous for a null Atrx allele, we found that XCI is balanced early in embryogenesis but becomes skewed over the course of development, because of selection favoring cells expressing the wild-type Atrx allele. Unexpectedly, selection does not appear to be the result of general cellular-viability defects in Atrx-deficient cells, since it is restricted to specific stages of development and is not ongoing throughout the life of the animal. Instead, there is evidence that selection results from independent tissue-specific effects. This illustrates an important mechanism by which skewed XCI may occur in carriers of XLMR and provides insight into the normal role of ATRX in regulating cell fate.     

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background

While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.

Results

Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.

Conclusions

The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0106-8) contains supplementary material, which is available to authorized users.     

Response and inbreeding from a genomic selection experiment in layer chickens

Background

Genomic selection (GS) using estimated breeding values (GS-EBV) based on dense marker data is a promising approach for genetic improvement. A simulation study was undertaken to illustrate the opportunities offered by GS for designing breeding programs. It consisted of a selection program for a sex-limited trait in layer chickens, which was developed by deterministic predictions under different scenarios. Later, one of the possible schemes was implemented in a real population of layer chicken.

Methods

In the simulation, the aim was to double the response to selection per year by reducing the generation interval by 50 %, while maintaining the same rate of inbreeding per year. We found that GS with retraining could achieve the set objectives while requiring 75 % fewer reared birds and 82 % fewer phenotyped birds per year. A multi-trait GS scenario was subsequently implemented in a real population of brown egg laying hens. The population was split into two sub-lines, one was submitted to conventional phenotypic selection, and one was selected based on genomic prediction. At the end of the 3-year experiment, the two sub-lines were compared for multiple performance traits that are relevant for commercial egg production.

Results

Birds that were selected based on genomic prediction outperformed those that were submitted to conventional selection for most of the 16 traits that were included in the index used for selection. However, although the two programs were designed to achieve the same rate of inbreeding per year, the realized inbreeding per year assessed from pedigree was higher in the genomic selected line than in the conventionally selected line.

Conclusions

The results demonstrate that GS is a promising alternative to conventional breeding for genetic improvement of layer chickens.     

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

Background

The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information.

Methods

The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability.

Results

Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.     

Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer

Cancer patients spontaneously generate autoantibodies (AAb) to tumor-derived proteins. To detect AAb, we have probed novel high-density custom protein microarrays (NAPPA) expressing 4988 candidate tumor antigens with sera from patients with early stage breast cancer (IBC), and bound IgG was measured. We used a three-phase serial screening approach. First, a prescreen was performed to eliminate uninformative antigens. Sera from stage I-III IBC (n = 53) and healthy women (n = 53) were screened for AAb to all 4988 protein antigens. Antigens were selected if the 95th percentile of signal of cases and controls were significantly different (p < 0.05) and if the number of cases with signals above the 95th percentile of controls was significant (p < 0.05). These 761 antigens were screened using an independent set of IBC sera (n = 51) and sera from women with benign breast disease (BBD) (n = 39). From these, 119 antigens had a partial area under the ROC curve (p < 0.05), with sensitivities ranging from 9-40% at >91% specificity. Twenty-eight of these antigens were confirmed using an independent serum cohort (n = 51 cases/38 controls, p < 0.05). Using all 28 AAb, a classifier was identified with a sensitivity of 80.8% and a specificity of 61.6% (AUC = 0.756). These are potential biomarkers for the early detection of breast cancer.     

Human iron transporters

Human iron transporters manage iron carefully because tissues need iron for critical functions, but too much iron increases the risk of reactive oxygen species. Iron acquisition occurs in the duodenum via divalent metal transporter (DMT1) and ferroportin. Iron trafficking depends largely on the transferrin cycle. Nevertheless, non-digestive tissues have a variety of other iron transporters that may render DMT1 modestly redundant, and DMT1 levels exceed those needed for the just-mentioned tasks. This review begins to consider why and also describes advances after 2008 that begin to address this challenge.