Application of an optimized marker amplification protocol in immunohistochemistry — a valuable tool for visualizing antigenic sites of low signal strength or sparse distribution

Amplification of immunohistochemical markers received considerable attention during the 1980s and 1990s. The amplification approach was largely abandoned following the development of antigen retrieval and reporter amplification techniques, because the latter were incorporated more easily into high throughput automated procedures in industrial and diagnostic laboratories. There remain, however, a number of instances where marker amplification still has much to offer. Consequently, we examined experimentally the utility of an optimized marker amplification technique in diagnostically relevant tissue where either the original signal strength was low or positive sites were visible, but sparsely distributed. Marker amplification in the former case not only improved the visibility of existing positive sites, but also revealed additional sites that previously were undetectable. In the latter case, positive sites were rendered more intense and therefore more easily seen during low magnification examination of large areas of tissue.     

EFFECT OF VITAMIN E SUPPLEMENTATION AND PARTIAL SUBSTITUTION OF POLY- WITH MONO-UNSATURATED FATTY ACIDS IN PIG DIETS ON MUSCLE,AND MICROSOME EXTRACT a-TOCOPHEROL CONCENTRATION AND LIPID OXIDATION

The experiment was organized in a 3×2 factorial arrangement with three dietary fat blends and a basal (20 mg kg^?1 diet) or supplemented (220 mg kg^?1) level of α-tocopheryl acetate. Dietary vitamin E and monounsaturated to polyunsaturated fatty acid ratio (dietary MUFA/PUFA) affected muscle α-tocopherol concentration (α-tocopherol [log μg g^?1]=0.18 (±0.105)+0.0034 (±0.0003)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.39 (±0.122)·dietary MUFA/PUFA (P<0.0036)). An interaction between dietary α-tocopherol and dietary MUFA/PUFA exists for microsome α-tocopherol concentration (α-tocopherol [log μg g^?1]=1.14 (±0.169) (P<0.0001)+0.0056 (±0.00099)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.54 (±0.206)·dietary MUFA/PUFA (P<0.0131)?0.0033 (±0.0011)·dietary α-tocopherol [mg kg^?1)]×dietary MUFA/PUFA (P<0.0067)), and hexanal concentration in meat (hexanal [ng·g^?1]=14807.9 (±1489.8)?28.8 (±10.6) dietary α-tocopherol [mg·kg^?1] (P<0.01)?8436.6 (±1701.6)·dietary MUFA/PUFA (P<0.001)+24.0 (±11.22)·dietary α-tocopherol·dietary MUFA/PUFA (P<0.0416)). It is concluded that partial substitution of dietary PUFA with MUFA lead to an increase in the concentration of α-tocopherol in muscle and microsome extracts. An interaction between dietary α-tocopherol and fatty acids exists, in which at low level of dietary vitamin E inclusion, a low MUFA/PUFA ratio leads to a reduction in the concentration of α-tocopherol in microsome extracts and a concentration of hexanal in meat above the expected values.     

Quirks of dye nomenclature. 5. Rhodamines

Rhodamines were first produced in the late 19^th century, when they constituted a new class of synthetic dyes. These compounds since have been used to color many things including cosmetics, inks, textiles, and in some countries, food products. Certain rhodamine dyes also have been used to stain biological specimens and currently are widely used as fluorescent probes for mitochondria in living cells. The early history and current biological applications are sketched briefly and an account of the ambiguities, complications and confusions concerning dye identification and nomenclature are discussed.     

Quirks of dye nomenclature. 6. Malachite green

Malachite green was discovered independently by two researchers in Germany in the 19^th century and found immediate employment as a dye and a pigment. Subsequently, other uses, such as staining biological specimens, emerged. A much later application was the control of fungal and protozoan infections in fish, for which the dye remains popular, although illegal in many countries owing to a variety of toxicity problems. In solution, malachite green can exist as five different species depending on the pH. The location of the positive charge of the colored cation on a carbon atom or a nitrogen atom is still debated. The original names of this dye, and their origins, are briefly surveyed.     

An immobilized metal ion affinity adsorption and scintillation proximity assay for receptor-stimulated phosphoinositide hydrolysis

A novel approach to measuring receptor-stimulated phosphoinositide hydrolysis was developed based on the principles of immobilized metal ion affinity chromatography (IMAC) and scintillation proximity assay (SPA). Hard Lewis metal ions, such as Zr(4+), Ga(3+), Al(3+), Fe(3+), Lu(3+), and Sc(3+), were immobilized on SPA beads via metal chelate and utilized as affinity ligands to entrap inositol phosphates. [3H]Inositol phosphates bound to IMAC-SPA beads through the strong interaction of their phosphate group with the immobilized metal ions. The binding brought [3H]inositol phosphates in close proximity to the scintillant embedded in the SPA beads, thereby allowing the radioactivity to be quantified. Quantification of [3H]inositol phosphate production in cells preincubated with [3H]inositol provided a highly sensitive measurement of phosphoinositide hydrolysis. The utility of this approach was demonstrated in measuring the response mediated by the G-protein-coupled neurokinin NK1 receptor and the tyrosine kinase-linked platelet-derived growth factor (PDGF) receptor. Substance P stimulated phosphoinositide hydrolysis concentration-dependently in CHO cells expressing NK1 receptors with a maximal 12-fold increase in inositol phosphate production. Similarly, PDGF-BB stimulated a 5-fold increase in phosphoinositide hydrolysis in quiescent Swiss 3T3 cells. This new approach is highly sensitive, fast, simple, easily performed on 96-well plates, and amenable for high-throughput screening.     

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Decreased caveolin‐1 levels contribute to fibrosis and deposition of extracellular IGFBP‐5

Our previous studies have demonstrated increased expression of insulin‐like growth factor binding protein‐5 (IGFBP‐5) in fibrotic tissues and IGFBP‐5 induction of extracellular matrix (ECM) components. The mechanism resulting in increased IGFBP‐5 in the extracellular milieu of fibrotic fibroblasts is unknown. Since Caveolin‐1 (Cav‐1) has been implicated to play a role in membrane trafficking and signal transduction in tissue fibrosis, we examined the effect of Cav‐1 on IGFBP‐5 internalization, trafficking and secretion. We demonstrated that IGFBP‐5 localized to lipid rafts in human lung fibroblasts and bound Cav‐1. Cav‐1 was detected in the nucleus in IGFBP‐5‐expressing fibroblasts, within aggregates enriched with IGFBP‐5, suggesting a coordinate trafficking of IGFBP‐5 and Cav‐1 from the plasma membrane to the nucleus. This trafficking was dependent on Cav‐1 as fibroblasts from Cav‐1 null mice had increased extracellular IGFBP‐5, and as fibroblasts in which Cav‐1 was silenced or lipid raft structure was disrupted through cholesterol depletion also had defective IGFBP‐5 internalization. Restoration of Cav‐1 function through administration of Cav‐1 scaffolding peptide dramatically increased IGFBP‐5 uptake. Finally, we demonstrated that IGFBP‐5 in the ECM protects fibronectin from proteolytic degradation. Taken together, our findings identify a novel role for Cav‐1 in the internalization and nuclear trafficking of IGFBP‐5. Decreased Cav‐1 expression in fibrotic diseases likely leads to increased deposition of IGFBP‐5 in the ECM with subsequent reduction in ECM degradation, thus identifying a mechanism by which reduced Cav‐1 and increased IGFBP‐5 concomitantly contribute to the perpetuation of fibrosis.     

Prostate cancer outcome: epidemiology and biostatistics

Substantial gaps exist in our ability to accurately predict prognosis, and these gaps limit our understanding of the complex mechanisms that contribute to the greatest cancer epidemic of our time, prostate cancer. This review addresses contemporary epidemiologic and biostatistical issues in prostate cancer. It covers the science of outcome prediction and biomarker evaluation, recognition of the need to combine biomarkers to improve the accuracy of our outcome estimates and an analysis of current outcome assessment methods, including the TNM staging system and multivariate regression models. The simplicity and intuitive ease of the current TNM staging system must be balanced against its serious limitations in predictive accuracy and its loss of clinical utility. Statistical regression methods are required as we move to the new era of personalized medicine. We must implement statistical approaches that integrate the new molecular biomarkers with existing prognostic biomarkers to accurately predict which patients require treatment and to determine the optimal therapy.