Post-Weaning Protein Malnutrition Increases Blood Pressure and Induces Endothelial Dysfunctions in Rats

Malnutrition during critical periods in early life may increase the subsequent risk of hypertension and metabolic diseases in adulthood, but the underlying mechanisms are still unclear. We aimed to evaluate the effects of post-weaning protein malnutrition on blood pressure and vascular reactivity in aortic rings (conductance artery) and isolated-perfused tail arteries (resistance artery) from control (fed with Labina®) and post-weaning protein malnutrition rats (offspring that received a diet with low protein content for three months). Systolic and diastolic blood pressure and heart rate increased in the post-weaning protein malnutrition rats. In the aortic rings, reactivity to phenylephrine (10−10–3.10−4 M) was similar in both groups. Endothelium removal or L-NAME (10−4 M) incubation increased the response to phenylephrine, but the L-NAME effect was greater in the aortic rings from the post-weaning protein malnutrition rats. The protein expression of the endothelial nitric oxide isoform increased in the aortic rings from the post-weaning protein malnutrition rats. Incubation with apocynin (0.3 mM) reduced the response to phenylephrine in both groups, but this effect was higher in the post-weaning protein malnutrition rats, suggesting an increase of superoxide anion release. In the tail artery of the post-weaning protein malnutrition rats, the vascular reactivity to phenylephrine (0.001–300 µg) and the relaxation to acetylcholine (10−10–10−3 M) were increased. Post-weaning protein malnutrition increases blood pressure and induces vascular dysfunction. Although the vascular reactivity in the aortic rings did not change, an increase in superoxide anion and nitric oxide was observed in the post-weaning protein malnutrition rats. However, in the resistance arteries, the increased vascular reactivity may be a potential mechanism underlying the increased blood pressure observed in this model

R497K polymorphism in epidermal growth factor receptor gene is associated with the risk of acute coronary syndrome

<p>Abstract</p> <p>Background</p> <p>Previous studies suggested that genetic polymorphisms in the epidermal growth factor receptor (EGFR) gene had been implicated in the susceptibility to some tumors and inflammatory diseases. EGFR has been recently implicated in vascular pathophysiological processes associated with excessive remodeling and atherosclerosis. Acute coronary syndrome (ACS) is a clinical manifestation of preceding atherosclerosis. Our purpose was to investigate the association of the EGFR polymorphism with the risk of ACS. In this context, we analyzed the HER-1 R497K and EGFR intron 1 (CA)_nrepeat polymorphisms in 191 patients with ACS and 210 age- and sex-matched controls in a Chinese population, using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) strategy and direct sequencing.</p> <p>Results</p> <p>There were significant differences in the genotype and allele distribution of R497K polymorphism of the EGFR gene between cases and controls. The <it>Lys </it>allele had a significantly increased risk of ACS compared with the <it>Arg </it>allele (adjusted OR = 1.49, 95% CI: 1.12–1.98, adjusted <it>P </it>= 0.006). However, no significant relationship between the number of (CA)_nrepeats of EGFR intron 1 (both alleles < 20 or any allele ≥ 20) and the risk of ACS was observed (adjusted OR = 0.97, 95% CI: 0.58–1.64, adjusted <it>P </it>= 0.911). Considering these two polymorphisms together, there was no statistically significant difference between the two groups.</p> <p>Conclusion</p> <p>R497K polymorphism of the EGFR gene is significantly associated with the risk of ACS. Our data suggests that R497K polymorphism may be used as a genetic susceptibility marker of the ACS.</p

Best practices in heterotrophic high-cell-density microalgal processes: achievements, potential and possible limitations

Microalgae of numerous heterotrophic genera (obligate or facultative) exhibit considerable metabolic versatility and flexibility but are currently underexploited in the biotechnological manufacturing of known plant-derived compounds, novel high-value biomolecules or enriched biomass. Highly efficient production of microalgal biomass without the need for light is now feasible in inexpensive, well-defined mineral medium, typically supplemented with glucose. Cell densities of more than 100 g l−1 cell dry weight have been achieved with Chlorella, Crypthecodinium and Galdieria species while controlling the addition of organic sources of carbon and energy in fedbatch mode. The ability of microalgae to adapt their metabolism to varying culture conditions provides opportunities to modify, control and thereby maximise the formation of targeted compounds with non-recombinant microalgae. This review outlines the critical aspects of cultivation technology and current best practices in the heterotrophic high-cell-density cultivation of microalgae. The primary topics include (1) the characteristics of microalgae that make them suitable for heterotrophic cultivation, (2) the appropriate chemical composition of mineral growth media, (3) the different strategies for fedbatch cultivations and (4) the principles behind the customisation of biomass composition. The review confirms that, although fundamental knowledge is now available, the development of efficient, economically feasible large-scale bioprocesses remains an obstacle to the commercialisation of this promising technology

Influence of Forest Management Regimes on Forest Dynamics in the Upstream Region of the Hun River in Northeastern China

Balancing forest harvesting and restoration is critical for forest ecosystem management. In this study, we used LANDIS, a spatially explicit forest landscape model, to evaluate the effects of 21 alternative forest management initiatives which were drafted for forests in the upstream region of the Hun River in northeastern China. These management initiatives included a wide range of planting and harvest intensities for Pinus koraiensis, the historically dominant tree species in the region. Multivariate analysis of variance, Shannon's Diversity Index, and planting efficiency (which indicates how many cells of the target species at the final year benefit from per-cell of the planting trees) estimates were used as indicators to analyze the effects of planting and harvesting regimes on forests in the region. The results showed that the following: (1) Increased planting intensity, although augmenting the coverage of P. koraiensis, was accompanied by decreases in planting efficiency and forest diversity. (2) While selective harvesting could increase forest diversity, the abrupt increase of early succession species accompanying this method merits attention. (3) Stimulating rapid forest succession may not be a good management strategy, since the climax species would crowd out other species which are likely more adapted to future climatic conditions in the long run. In light of the above, we suggest a combination of 30% planting intensity with selective harvesting of 50% and 70% of primary and secondary timber species, respectively, as the most effective management regime in this area. In the long run this would accelerate the ultimate dominance of P. koraiensis in the forest via a more effective rate of planting, while maintaining a higher degree of forest diversity. These results are particularly useful for forest managers constrained by limited financial and labor resources who must deal with conflicts between forest harvesting and restoration

Evaluation of 309 Environmental Chemicals Using a Mouse Embryonic Stem Cell Adherent Cell Differentiation and Cytotoxicity Assay

The vast landscape of environmental chemicals has motivated the need for alternative methods to traditional whole-animal bioassays in toxicity testing. Embryonic stem (ES) cells provide an in vitro model of embryonic development and an alternative method for assessing developmental toxicity. Here, we evaluated 309 environmental chemicals, mostly food-use pesticides, from the ToxCast™ chemical library using a mouse ES cell platform. ES cells were cultured in the absence of pluripotency factors to promote spontaneous differentiation and in the presence of DMSO-solubilized chemicals at different concentrations to test the effects of exposure on differentiation and cytotoxicity. Cardiomyocyte differentiation (α,β myosin heavy chain; MYH6/MYH7) and cytotoxicity (DRAQ5™/Sapphire700™) were measured by In-Cell Western™ analysis. Half-maximal activity concentration (AC50) values for differentiation and cytotoxicity endpoints were determined, with 18% of the chemical library showing significant activity on either endpoint. Mining these effects against the ToxCast Phase I assays (∼500) revealed significant associations for a subset of chemicals (26) that perturbed transcription-based activities and impaired ES cell differentiation. Increased transcriptional activity of several critical developmental genes including BMPR2, PAX6 and OCT1 were strongly associated with decreased ES cell differentiation. Multiple genes involved in reactive oxygen species signaling pathways (NRF2, ABCG2, GSTA2, HIF1A) were strongly associated with decreased ES cell differentiation as well. A multivariate model built from these data revealed alterations in ABCG2 transporter was a strong predictor of impaired ES cell differentiation. Taken together, these results provide an initial characterization of metabolic and regulatory pathways by which some environmental chemicals may act to disrupt ES cell growth and differentiation

A Novel Gene Signature for Molecular Diagnosis of Human Prostate Cancer by RT-qPCR

Prostate cancer (CaP) is one of the most relevant causes of cancer death in Western Countries. Although detection of CaP at early curable stage is highly desirable, actual screening methods present limitations and new molecular approaches are needed. Gene expression analysis increases our knowledge about the biology of CaP and may render novel molecular tools, but the identification of accurate biomarkers for reliable molecular diagnosis is a real challenge. We describe here the diagnostic power of a novel 8-genes signature: ornithine decarboxylase (ODC), ornithine decarboxylase antizyme (OAZ), adenosylmethionine decarboxylase (AdoMetDC), spermidine/spermine N(1)-acetyltransferase (SSAT), histone H3 (H3), growth arrest specific gene (GAS1), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and Clusterin (CLU) in tumour detection/classification of human CaP. METHODOLOGY/PRINCIPAL FINDINGS: The 8-gene signature was detected by retrotranscription real-time quantitative PCR (RT-qPCR) in frozen prostate surgical specimens obtained from 41 patients diagnosed with CaP and recommended to undergo radical prostatectomy (RP). No therapy was given to patients at any time before RP. The bio-bank used for the study consisted of 66 specimens: 44 were benign-CaP paired from the same patient. Thirty-five were classified as benign and 31 as CaP after final pathological examination. Only molecular data were used for classification of specimens. The Nearest Neighbour (NN) classifier was used in order to discriminate CaP from benign tissue. Validation of final results was obtained with 10-fold cross-validation procedure. CaP versus benign specimens were discriminated with (80+/-5)% accuracy, (81+/-6)% sensitivity and (78+/-7)% specificity. The method also correctly classified 71% of patients with Gleason score&lt;7 versus &gt; or =7, an important predictor of final outcome. CONCLUSIONS/SIGNIFICANCE: The method showed high sensitivity in a collection of specimens in which a significant portion of the total (13/31, equal to 42%) was considered CaP on the basis of having less than 15% of cancer cells. This result supports the notion of the "cancer field effect", in which transformed cells extend beyond morphologically evident tumour. The molecular diagnosis method here described is objective and less subjected to human error. Although further confirmations are needed, this method poses the potential to enhance conventional diagnosis

Classification of Camellia (Theaceae) Species Using Leaf Architecture Variations and Pattern Recognition Techniques

Leaf characters have been successfully utilized to classify Camellia (Theaceae) species; however, leaf characters combined with supervised pattern recognition techniques have not been previously explored. We present results of using leaf morphological and venation characters of 93 species from five sections of genus Camellia to assess the effectiveness of several supervised pattern recognition techniques for classifications and compare their accuracy. Clustering approach, Learning Vector Quantization neural network (LVQ-ANN), Dynamic Architecture for Artificial Neural Networks (DAN2), and C-support vector machines (SVM) are used to discriminate 93 species from five sections of genus Camellia (11 in sect. Furfuracea, 16 in sect. Paracamellia, 12 in sect. Tuberculata, 34 in sect. Camellia, and 20 in sect. Theopsis). DAN2 and SVM show excellent classification results for genus Camellia with DAN2's accuracy of 97.92% and 91.11% for training and testing data sets respectively. The RBF-SVM results of 97.92% and 97.78% for training and testing offer the best classification accuracy. A hierarchical dendrogram based on leaf architecture data has confirmed the morphological classification of the five sections as previously proposed. The overall results suggest that leaf architecture-based data analysis using supervised pattern recognition techniques, especially DAN2 and SVM discrimination methods, is excellent for identification of Camellia species