Micro-CT based analysis of a new paradigm for vulnerable plaque rupture: cellular microcalcifications in fibrous caps

In this paper, we further investigate the new paradigm for the rupture of thin cap fibroatheroma (TCFA) proposed in Vengrenyuk et al. (2006 PNAS 103:14678) using a multilevel micro-CT based 3D numerical modeling. The new paradigm proposes that the rupture of TCFA is due to stress-induced interfacial debonding of cellular--level, 10-20 microm microcalcifications in the fibrous cap proper. Such microcalcifications, which lie below the visibility of current in vivo imaging techniques, were detected for the first time using confocal microscopy and high resolution microcomputed tomography (micro-CT) imaging in Vengrenyuk et al. (2006) In the present study, we use high resolution (7 microm) micro-CT imaging to construct accurate geometries of both these microcalcifications and larger mm size macrocalcifications at the cap shoulders to evaluate their biomechanical stability. The analysis shows that cellular-level calcifications by themselves are not dangerous unless they lie in a region of high background stress. This high level of background stress only occurs in caps whose thickness is < approximately 80 microm. Whereas a spherical microcalcification will increase peak circumferential stress (PCS) by a factor of two, in agreement with previous local analytical solutions, this can be increased several fold by elongated microcalcifications. The most dangerous situation is when a microinclusion appears in close proximity to a region where the PCS is already high. This stress will be substantially increased if the inclusion is elongated. In contrast, macrocalcifications at the cap shoulders are shown to actually increase plaque stability.     

Metabolic Basis for the Self-Referential Genetic Code

An investigation of the biosynthesis pathways producing glycine and serine was necessary to clarify an apparent inconsistency between the self-referential model (SRM) for the formation of the genetic code and the model of coevolution of encodings and of amino acid biosynthesis routes. According to the SRM proposal, glycine was the first amino acid encoded, followed by serine. The coevolution model does not state precisely which the first encodings were, only presenting a list of about ten early assignments including the derivation of glycine from serine—this being derived from the glycolysis intermediate glycerate, which reverses the order proposed by the self-referential model. Our search identified the glycine-serine pathway of syntheses based on one-carbon sources, involving activities of the glycine decarboxylase complex and its associated serine hydroxymethyltransferase, which is consistent with the order proposed by the self-referential model and supports its rationale for the origin of the genetic code: protein synthesis was developed inside an early metabolic system, serving the function of a sink of amino acids; the first peptides were glycine-rich and fit for the function of building the early ribonucleoproteins; glycine consumption in proteins drove the fixation of the glycine-serine pathway.     

Exposure to noise pollution across North American passerines supports the noise filter hypothesis

The noise filter hypothesis predicts that species using higher sound frequencies should be more tolerant of noise pollution, because anthropogenic noise is more intense at low frequencies. Recent work analysed continental‐scale data on anthropogenic noise across the USA and found that passerine species inhabiting more noise‐polluted areas do not have higher peak song frequency but have more complex songs. However, this metric of song complexity is of ambiguous interpretation, because it can indicate either diverse syllables or a larger frequency bandwidth. In the latter case, the finding would support the noise filter hypothesis, because larger frequency bandwidths mean that more sound energy spreads to frequencies that are less masked by anthropogenic noise. We reanalysed how passerine song predicts exposure to noise using a more thorough dataset of acoustic song measurements, and showed that it is large frequency bandwidths, rather than diverse syllables, that predict the exposure of species to noise pollution. Given that larger bandwidths often encompass higher maximum frequencies, which are less masked by anthropogenic noise, our result suggests that tolerance to noise pollution might depend mostly on having the high‐frequency parts of song little masked by noise, thus preventing acoustic communication from going entirely unnoticed at long distances.     

Membrane interactions of the anuran antimicrobial peptide HSP1-NH2: Different aspects of the association to anionic and zwitterionic biomimetic systems

Studies have suggested that antimicrobial peptides act by different mechanisms, such as micellisation, self-assembly of nanostructures and pore formation on the membrane surface. This work presents an extensive investigation of the membrane interactions of the 14 amino-acid antimicrobial peptide hylaseptin P1-NH₂ (HSP1-NH₂), derived from the tree-frog Hyla punctata, which has stronger antifungal than antibacterial potential. Biophysical and structural analyses were performed and the correlated results were used to describe in detail the interactions of HSP1-NH₂ with zwitterionic and anionic detergent micelles and phospholipid vesicles. HSP1-NH₂ presents similar well-defined helical conformations in both zwitterionic and anionic micelles, although NMR spectroscopy revealed important structural differences in the peptide N-terminus. ²H exchange experiments of HSP1-NH₂ indicated the insertion of the most N-terminal residues (1–3) in the DPC-d₃₈ micelles. A higher enthalpic contribution was verified for the interaction of the peptide with anionic vesicles in comparison with zwitterionic vesicles. The pore formation ability of HSP1-NH₂ (examined by dye release assays) and its effect on the size and surface charge as well as on the lipid acyl chain ordering (evaluated by Fourier-transform infrared spectroscopy) of anionic phospholipid vesicles showed membrane disruption even at low peptide-to-phospholipid ratios, and the effect increases proportionately to the peptide concentration. On the other hand, these biophysical investigations showed that a critical peptide-to-phospholipid ratio around 0.6 is essential for promoting disruption of zwitterionic membranes. In conclusion, this study demonstrates that the binding process of the antimicrobial HSP1-NH₂ peptide depends on the membrane composition and peptide concentration.     

Fishers’ ecological knowledge on the reproduction of fish and shrimp in a subtropical coastal ecosystem

Hydrobiologia - Fishers’ ecological knowledge (FEK) has contributed to a better understanding about the reproduction of fishery resources, especially where biological data are scarce or...     

Discrimination of red porgy Pagrus pagrus (Sparidae) potential stocks in the south-western Atlantic by otolith shape analysis

Otolith shape analysis is a powerful method for fish stock identification. We compared the otolith shape of Pagrus pagrus (Linnaeus 1758) along with its distribution in four south-western Atlantic regions where it is commercially fished: Rio de Janeiro, Rio Grande do Sul in southern Brazil, the Argentine-Uruguayan Common Fishing Zone (UA) and the Argentinian Exclusive Fishing Zone (AR). Otolith shapes were compared by Elliptical Fourier and Wavelet coefficients among specimens in a size range with similar otoliths, morphometric parameters and ages. Four potential stocks were identified: one in the AR, a second along the UA which included specimens from southern Brazil with well-marked opaque bands in its otoliths (MRS), the third in southern Brazil with faint or absent opaque bands in its otoliths (FRS) and the fourth along Rio de Janeiro. The difference in the otolith shape among regions followed differences reported using other stock identification techniques. The similarity between otoliths from UA and MRS (ANOVA-like, P > 0.01) can be explained by seasonal short-range migrations. Otoliths shape differences between MRS and FRS (ANOVA-like, P < 0.01) suggest that P. pagrus does not form a homogeneous group in southern Brazil.     

Relationship between ventilatory threshold and muscle fiber conduction velocity responses in trained cyclists

The relationship between surface electromyography (SEMG) amplitude and the ventilatory threshold has been extensively studied. However, previous studies of muscle fiber conduction velocity (MFCV) are scarce and present insufficient evidence concerning the relationship between MFCV and metabolic responses during cycling. Based on that fact, the purpose of this study is twofold: (1) to investigate the existence of a MFCV threshold (MFCVT) during cycling and (2) to verify if this possible breakpoint is correlated with the ventilatory threshold (VT) and the SEMG threshold (SEMGT). Eight trained male cyclists (age 36.0 ± 9.7 years) performed an incremental cycling test with initial workload of 150 W gradually incremented by 20 W min^?1 until the exhaustion. Gas analyses were conducted using a breath-by-breath open-circuit spirometry and SEMG were registered from vastus lateralis in each pedaling cycle with a linear array of electrodes. A bi-segmental linear regression computer algorithm was used to estimate VT, MFCVT and SEMGT respectively in the carbon dioxide production (VCO₂), MFCV and electromyography root mean square (EMG RMS) curves. The one way ANOVA for repeated measures did not reveal any significant difference among VT (77.1 ± 7.5% of VO₂max), MFCVT (80.3 ± 10.4% of VO₂max) and SEMGT (81.9 ± 11.7% of VO₂max). The Bland and Altman procedure confirmed a good concordance between SEMGT and VT (Bias = 5.5 of %VO₂max) as well as MFCVT and VT (Bias = 5.2 of %VO₂max). The present findings suggest that muscle fiber conduction velocity threshold is a valid and reliable non-invasive tool to obtain information about ventilatory threshold in trained cyclists.     

Diet supplementation with beta-carotene improves the serum lipid profile in rats fed a cholesterol-enriched diet

The present study investigated the underlying mechanism associated with the hypocholesterolemic activity of beta-carotene by examining its effects on the serum lipid profile, fecal cholesterol excretion, and gene expression of the major receptors, enzymes, and transporters involved in cholesterol metabolism. Female Fischer rats were divided into three groups and were fed either a control or a hypercholesterolemic diet supplemented or not supplemented with 0.2 % beta-carotene. After 6 weeks of feeding, blood, livers, and feces were collected for analysis, and quantitative real-time polymerase chain reaction (qRT-PCR) was performed. Dietary supplementation with 0.2 % beta-carotene decreased serum total cholesterol, non-HDL cholesterol, the atherogenic index, and hepatic total lipid and cholesterol contents. These changes were accompanied by an increase in the total lipid and cholesterol contents excreted in the feces. The qRT-PCR analyses demonstrated that the hypercholesterolemic diet promoted a decrease in the gene expression of sterol regulatory element-binding protein 2, 3-hydroxy-3-methylglutaryl CoA reductase, and low-density lipoprotein receptor and an increase in the gene expression of peroxisome proliferator-activated receptor α and cholesterol-7a-hydroxylase. The expression of these genes and gene expression of ATP-binding cassette subfamily G transporters 5and 8 were unaffected by beta-carotene supplementation. In conclusion, the decrease in serum cholesterol and the elevation of fecal cholesterol obtained following beta-carotene administration indicate that this substance may decrease cholesterol absorption in the intestine and increase cholesterol excretion into the feces without a direct effect on the expression of cholesterol metabolism genes.     

Diet-Sensitive Sources of Reactive Oxygen Species in Liver Mitochondria: Role of Very Long Chain Acyl-CoA Dehydrogenases

High fat diets and accompanying hepatic steatosis are highly prevalent conditions. Previous work has shown that steatosis is accompanied by enhanced generation of reactive oxygen species (ROS), which may mediate further liver damage. Here we investigated mechanisms leading to enhanced ROS generation following high fat diets (HFD). We found that mitochondria from HFD livers present no differences in maximal respiratory rates and coupling, but generate more ROS specifically when fatty acids are used as substrates. Indeed, many acyl-CoA dehydrogenase isoforms were found to be more highly expressed in HFD livers, although only the very long chain acyl-CoA dehydrogenase (VLCAD) was more functionally active. Studies conducted with permeabilized mitochondria and different chain length acyl-CoA derivatives suggest that VLCAD is also a source of ROS production in mitochondria of HFD animals. This production is stimulated by the lack of NAD⁺. Overall, our studies uncover VLCAD as a novel, diet-sensitive, source of mitochondrial ROS.     

Using Manifold Learning for Atlas Selection in Multi-Atlas Segmentation

Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process.