Mitoxantrone changes spectrin-aminophospholipid interactions

Understanding drug-membrane and drug-membrane protein interactions would be a crucial step towards understanding the action and biological properties of anthracyclines, as the cell membrane with its integral and peripheral proteins is the first barrier encountered by these drugs. In this paper, we briefly describe mitoxantrone-monolayer and mitoxantrone-bilayer interactions, focusing on the effect of mitoxantrone on the interactions between erythroid or nonerythroid spectrin with phosphatidylethanolamine-enriched mono- and bilayers. We found that mitoxantrone markedly modifies the interaction of erythroid and nonerythroid spectrins with phosphatidylethanolamine/phosphatitydcholine (PE/PC) monolayers. The change in Δπ induced by spectrins is several-fold larger in the presence of 72?nM mitoxantrone than in its absence: spectrin/mitoxantrone complexes induced a strong compression of the monolayer. Spin-labelling experiments showed that spectrin/mitoxantrone complexes caused significant changes in the order parameter measured using a 5′-doxyl stearate probe in the bilayer, but they practically did not affect the mobility of 16′-doxyl stearate. These results indicate close-to-surface interactions/penetrations without significant effect on the mid-region of the hydrophobic core of the bilayer. The obtained apparent equilibrium dissociation constants indicated relatively similar mitoxantrone-phospholipid and mitoxantrone-spectrin (erythroid and nonerythroid) binding affinities. These results might in part, explain the effect of mitoxantrone on spectrin distribution in the living cells.     

Structural crown properties of Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica [L.]) in mixed versus pure stands revealed by terrestrial laser scanning

How tree morphology develops in mixed-species stands is essential for understanding and modelling mixed-stand dynamics. However, research so far focused on the morphological variation between tree species and neglected the variation within a species depending on intra- and interspecific competition. Our study, in contrast, addresses crown properties of nine mature Norway spruces (Picea abies [L.] Karst.) of a pure stand and compares them with ten spruces growing in mixture with European beech (Fagus sylvatica [L.]). The same was done with 11 pure stand beeches and 12 beeches growing in mixture with spruce. Through application of a terrestrial laser scanner and a new skeletonization approach, we deal with both species’-specific morphological traits such as branch angle, branch length, branch bending, crown volume and space occupation of branches within the crown, some of which were hardly accessible so far. Special attention is paid to distinct differences between trees growing in mixed and pure stands: for spruce, our study reveals significantly longer branches and greater crown volumes in the mixed stand when compared to the pure stand. In case of European beech, individuals growing in mixture show flatter branch angles, more distinct ramification, greater crown volumes and a lower share of a single branch’s space occupation in the total crown volume. The results show that the presented methods yield detailed information on the morphological traits analyzed in this study and that interspecific competition on its own may have a significant impact on crown structures. Implications for production ecology and stand dynamics of mixed-species forests are discussed.     

Influence of microalgae cell wall characteristics on protein extractability and determination of nitrogen-to-protein conversion factors

Additional evidence about the influence of the cell wall physical and chemical characteristics on protein extractability was determined by calculating the conversion factors of five different microalgae known to have different cell wall composition, and their protein extracts. The conversion factors obtained for crude rigid cell walled Chlorella vulgaris, Nannochloropsis oculata and Haematococcus pluvialis were 6.35, 6.28 and 6.25, respectively, but for their protein extracts the values were lower with 5.96, 5.86 and 5.63. On the other hand, conversion factor obtained for fragile cell walled microalgae Porphyridium cruentum and Athrospira platensis was 6.35 for the former and 6.27 for the latter, with no significant difference for their protein extract with 6.34 for the former and 6.21 for the latter. In addition, the highest hydro-soluble protein percentage recovered from total protein was for P. cruentum 80.3 % and A. platensis 69.5 % but lower for C. vulgaris with 43.3 %, N. oculata with 33.3 % and H. pluvialis with 27.5 %. The study spotted the light on the influence of the cell wall on evaluating the conversion factor and protein extractability. In addition, it showed the necessity of finding the conversion factor every time accurate protein quantification is required, and proved that there is not a universal conversion factor that can be recommended.     

Evaluation of the protein quality of Porphyridium cruentum

The amino acid profile of the red microalga Porphyridium cruentum and its protein extract have been determined in order to assess the nutritional quality of this biomass for human consumption. Total protein determined by elemental analysis represented 56 % of its dry weight. Hydro-soluble proteins extracted at pH 12 and 40 °C were analysed by the Lowry method giving 47 %, which represented 84 % of total protein per dry weight. The amino acid sequence of the biomass and the protein extract was composed of a set of essential (39 % for the former and 37 % for the latter) and non-essential amino acids (61 % for the former and 63 % for the latter) that compares favourably with the standard protein/amino acid requirements proposed by Food and Agricultural Organisation and World Health Organisation.     

Prediction Errors in Learning Drug Response from Gene Expression Data – Influence of Labeling,Sample Size,and Machine Learning Algorithm

Model-based prediction is dependent on many choices ranging from the sample collection and prediction endpoint to the choice of algorithm and its parameters. Here we studied the effects of such choices, exemplified by predicting sensitivity (as IC50) of cancer cell lines towards a variety of compounds. For this, we used three independent sample collections and applied several machine learning algorithms for predicting a variety of endpoints for drug response. We compared all possible models for combinations of sample collections, algorithm, drug, and labeling to an identically generated null model. The predictability of treatment effects varies among compounds, i.e. response could be predicted for some but not for all. The choice of sample collection plays a major role towards lowering the prediction error, as does sample size. However, we found that no algorithm was able to consistently outperform the other and there was no significant difference between regression and two- or three class predictors in this experimental setting. These results indicate that response-modeling projects should direct efforts mainly towards sample collection and data quality, rather than method adjustment.     

Parameter set for computer-assisted texture analysis of fetal brain

Background

Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images. We proposed a wavelet-based parameter and two novel histogram-based parameters for Fisher texture analysis in three-dimensional space.

Results

Wavenhl, focus index, and dispersion index revealed better quality for 3 T. Though both 1.5 and 3 T images were 16-bit DICOM encoded, nearly 16 and 12 usable bits were measured in 3 and 1.5 T images, respectively. The four-bit padding observed in 1.5 T K-space encoding mimics noise by adding illusionistic details, which are not really part of the image. In contrast, zero-bit padding in 3 T provides space for storing more details and increases the likelihood of noise but as well as edges, which in turn are very crucial for differentiation of closely related anatomical structures.

Conclusions

Both encoding modes are possible with both units, but higher 3 T resolution is the main difference. It contributes to higher perceived and available dynamic range. Apart from surprisingly larger Fisher coefficient, no significant difference was observed when testing was conducted with down-converted 8-bit BMP images.

     

Negative effects of density on space use of small mammals differ with the phase of the masting‐induced population cycle

Home range size generally decreases with increasing population density, but testing how this relationship is influenced by other factors (e.g., food availability, kin structure) is a difficult task. We used spatially explicit capture–recapture models to examine how home range size varies with population density in the yellow‐necked mouse (Apodemus flavicollis). The relationship between population density and home range size was studied at two distinct phases of population fluctuations induced by beech (Fagus sylvatica) masting: post‐mast peak in abundance (first summer after mast, n = 2) and subsequent crash (second summer after mast, n = 2). We live‐trapped mice from June to September to avoid the confounding effects of autumn seedfall on home range size. In accordance with general predictions, we found that home range size was negatively associated with population density. However, after controlling for the effect of density, home ranges of mice were larger in post‐mast years than during the crash phase. This indicates a higher spatial overlap among neighbors in post‐mast years. We suggest that the increased spatial overlap is caused by negative density‐dependent dispersal that leads to high relatedness of individuals within population in the peak phase of the cycle.     

The Relationships between Polymorphisms in Genes Encoding the Growth Factors TGF-β1, PDGFB,EGF, bFGF and VEGF-A and the Restenosis Process in Patients with Stable Coronary Artery Disease Treated with Bare Metal Stent

Background

Neointima forming after stent implantation consists of vascular smooth muscle cells (VSMCs) in 90%. Growth factors TGF-β1, PDGFB, EGF, bFGF and VEGF-A play an important role in VSMC proliferation and migration to the tunica intima after arterial wall injury. The aim of this paper was an analysis of functional polymorphisms in genes encoding TGF-β1, PDGFB, EGF, bFGF and VEGF-A in relation to in-stent restenosis (ISR).

Materials and Methods

265 patients with a stable coronary artery disease (SCAD) hospitalized in our center in the years 2007–2011 were included in the study. All patients underwent stent implantation at admission to the hospital and had another coronary angiography performed due to recurrence of the ailments or a positive result of the test assessing the coronary flow reserve. Angiographically significant ISR was defined as stenosis >50% in the stented coronary artery segment. The patients were divided into two groups–with angiographically significant ISR (n = 53) and without significant ISR (n = 212). Additionally, the assessment of late lumen loss (LLL) in vessel was performed. EGF rs4444903 polymorphism was genotyped using the PCR-RFLP method whilst rs1800470 (TGFB1), rs2285094 (PDGFB) rs308395 (bFGF) and rs699947 (VEGF-A) were determined using the TaqMan method.

Results

Angiographically significant ISR was significantly less frequently observed in the group of patients with the A/A genotype of rs1800470 polymorphism (TGFB1) versus patients with A/G and G/G genotypes. In the multivariable analysis, LLL was significantly lower in patients with the A/A genotype of rs1800470 (TGFB1) versus those with the A/G and G/G genotypes and higher in patients with the A/A genotype of the VEGF-A polymorphism versus the A/C and C/C genotypes. The C/C genotype of rs2285094 (PDGFB) was associated with greater LLL compared to C/T heterozygotes and T/T homozygotes.

Conclusions

The polymorphisms rs1800470, rs2285094 and rs6999447 of the TGFB1, PDGFB and VEGF-A genes, respectively, are associated with LLL in patients with SCAD treated by PCI with a metal stent implantation.