Differential growth responses to water balance of coexisting deciduous tree species are linked to wood density in a Bolivian tropical dry forest

A seasonal period of water deficit characterizes tropical dry forests (TDFs). There, sympatric tree species exhibit a diversity of growth rates, functional traits, and responses to drought, suggesting that each species may possess different strategies to grow under different conditions of water availability. The evaluation of the long-term growth responses to changes in the soil water balance should provide an understanding of how and when coexisting tree species respond to water deficit in TDFs. Furthermore, such differential growth responses may be linked to functional traits related to water storage and conductance. We used dendrochronology and climate data to retrospectively assess how the radial growth of seven coexisting deciduous tree species responded to the seasonal soil water balance in a Bolivian TDF. Linear mixed-effects models were used to quantify the relationships between basal area increment and seasonal water balance. We related these relationships with wood density and sapwood production to assess if they affect the growth responses to climate. The growth of all species responded positively to water balance during the wet season, but such responses differed among species as a function of their wood density. For instance, species with a strong growth response to water availability averaged a low wood density which may facilitate the storage of water in the stem. By contrast, species with very dense wood were those whose growth was less sensitive to water availability. Coexisting tree species thus show differential growth responses to changes in soil water balance during the wet season. Our findings also provide a link between wood density, a trait related to the ability of trees to store water in the stem, and wood formation in response to water availability.

Lung CD57+ cell density is increased in very severe COPD

Among all inflammatory cells involved in COPD, those with a cytolytic or elastolytic activity are thought to play a key role in the pathogenesis of the disease. However, there is no data about the infiltration of cells expressing the CD57 marker in small airways and parenchyma of COPD patients. In this study, surgical specimens from 43 subjects undergoing lung resection due to lung cancer (9 non-smokers, 18 smokers without COPD and 16 smokers with moderate COPD) and 16 patients undergoing double lung transplantation for very severe COPD were examined. CD57+ cells, neutrophils, macrophages and mast cells infiltrating bronchioles (epithelium, smooth muscle and connective tissue) and parenchymal interstitium were localized and quantified by immunohistochemical analysis. Compared to the other groups, the small airways of very severe COPD patients showed a significantly higher density of CD57+ cells, mainly infiltrated in the connective tissue (p=0.001), and a significantly higher density of neutrophils located characteristically in the epithelium (p=0.037). Also, the density of neutrophils was significantly higher in parenchyma of very severe COPD patients compared with the rest of the groups (p=0.001). Finally, there were significant correlations between the bronchiolar density of CD57+ cells and the FEV1 values (R=-0.43, p=0.022), as well as between the parenchymal density of neutrophils and macroscopic emphysema degree (R=0.43, p=0.048) in COPD groups. These results show that CD57+ cells may be involved in COPD pathogenesis, especially in the most severe stages of the disease.

Tailoring the surface density of silicon nanocrystals embedded in SiOx single layers

In this article, we explore the possibility of modifying the silicon nanocrystal areal density in SiOx single layers, while keeping constant their size. For this purpose, a set of SiOx monolayers with controlled thickness between two thick SiO2 layers has been fabricated, for four different compositions (x=1, 1.25, 1.5, or 1.75). The structural properties of the SiO x single layers have been analyzed by transmission electron microscopy (TEM) in planar view geometry. Energy-filtered TEM images revealed an almost constant Si-cluster size and a slight increase in the cluster areal density as the silicon content increases in the layers, while high resolution TEM images show that the size of the Si crystalline precipitates largely decreases as the SiO x stoichiometry approaches that of SiO2. The crystalline fraction was evaluated by combining the results from both techniques, finding a crystallinity reduction from 75% to 40%, for x = 1 and 1.75, respectively. Complementary photoluminescence measurements corroborate the precipitation of Si-nanocrystals with excellent emission properties for layers with the largest amount of excess silicon. The integrated emission from the nanoaggregates perfectly scales with their crystalline state, with no detectable emission for crystalline fractions below 40%. The combination of the structural and luminescence observations suggests that small Si precipitates are submitted to a higher compressive local stress applied by the SiO2 matrix that could inhibit the phase separation and, in turn, promotes the creation of nonradiative paths.

Changes in the phenolic content of low density lipoprotein after olive oil consumption in men. A randomized crossover controlled trial

Olive oil decreases the risk of CVD. This effect may be due to the fatty acid profile of the oil, but it may also be due to its antioxidant content which differs depending on the type of olive oil. In this study, the concentrations of oleic acid and antioxidants (phenolic compounds and vitamin E) in plasma and LDL were compared after consumption of three similar olive oils, but with differences in their phenolic content. Thirty healthy volunteers participated in a placebo-controlled, double-blind, crossover, randomized supplementation trial. Virgin, common, and refined olive oils were administered during three periods of 3 weeks separated by a 2-week washout period. Participants were requested to ingest a daily dose of 25 ml raw olive oil, distributed over the three meals of the day, during intervention periods. All three olive oils caused an increase in plasma and LDL oleic acid (P,0·05) content. Olive oils rich in phenolic compounds led to an increase in phenolic compounds in LDL (P,0·005). The concentration of phenolic compounds in LDL was directly correlated with the phenolic concentration in the olive oils. The increase in the phenolic content of LDL could account for the increase of the resistance of LDL to oxidation, and the decrease of the in vivo oxidized LDL, observed in the frame of this trial. Our results support the hypothesis that a daily intake of virgin olive oil promotes protective LDL changes ahead of its oxidation.

The Human Mesenchymal Stromal Cell-Derived Osteocyte Capacity to Modulate Dendritic Cell Functions Is Strictly Dependent on the Culture System.

In vitro differentiation of mesenchymal stromal cells (MSC) into osteocytes (human differentiated osteogenic cells, hDOC) before implantation has been proposed to optimize bone regeneration. However, a deep characterization of the immunological properties of DOC, including their effect on dendritic cell (DC) function, is not available. DOC can be used either as cellular suspension (detached, Det-DOC) or as adherent cells implanted on scaffolds (adherent, Adh-DOC). By mimicking in vitro these two different routes of administration, we show that both Det-DOC and Adh-DOC can modulate DC functions. Specifically, the weak downregulation of CD80 and CD86 caused by Det-DOC on DC surface results in a weak modulation of DC functions, which indeed retain a high capacity to induce T-cell proliferation and to generate CD4(+)CD25(+)Foxp3(+) T cells. Moreover, Det-DOC enhance the DC capacity to differentiate CD4(+)CD161(+)CD196(+) Th17-cells by upregulating IL-6 secretion. Conversely, Adh-DOC strongly suppress DC functions by a profound downregulation of CD80 and CD86 on DC as well as by the inhibition of TGF-β production. In conclusion, we demonstrate that different types of DOC cell preparation may have a different impact on the modulation of the host immune system. This finding may have relevant implications for the design of cell-based tissue-engineering strategies.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Combined CSL and p53 downregulation promotes cancer-associated fibroblast activation.

Stromal fibroblast senescence has been linked to ageing-associated cancer risk. However, density and proliferation of cancer-associated fibroblasts (CAFs) are frequently increased. Loss or downmodulation of the Notch effector CSL (also known as RBP-Jκ) in dermal fibroblasts is sufficient for CAF activation and ensuing keratinocyte-derived tumours. We report that CSL silencing induces senescence of primary fibroblasts from dermis, oral mucosa, breast and lung. CSL functions in these cells as a direct repressor of multiple senescence- and CAF-effector genes. It also physically interacts with p53, repressing its activity. CSL is downmodulated in stromal fibroblasts of premalignant skin actinic keratosis lesions and squamous cell carcinomas, whereas p53 expression and function are downmodulated only in the latter, with paracrine FGF signalling as the probable culprit. Concomitant loss of CSL and p53 overcomes fibroblast senescence, enhances expression of CAF effectors and promotes stromal and cancer cell expansion. The findings support a CAF activation-stromal co-evolution model under convergent CSL-p53 control.

A multistep process of cancer associated fibroblasts determination under CSL-p53 control

Stromal fibroblast senescence has been linked to the aging-associated increase of tumors. However, in epithelial cancer, density and proliferation of cancer associated fibroblasts (CAF) are frequently increased, rather than decreased. We previously showed that genetic deletion or down-modulation of the canonical Notch effector CSL/RBP-JK in dermal fibroblasts is sufficient for CAF activation with consequent development of keratinocyte-derived tumors. We show here that CSL silencing induces senescence of primary fibroblasts from dermis, oral mucosa, breast and lung. CSL functions in these cells as direct repressor of multiple senescence- and CAF-effector genes. It also physically interacts with p53, repressing its activity. CSL is down-modulated in stromal fibroblasts of premalignant skin actinic keratosis lesions and squamous cell carcinomas (SCC), while p53 gene expression and function is down-modulated only in the latter, with paracrine influences of incipient cancer cells as a likely culprit. Concomitant loss of CSL and p53 overcomes fibroblast senescence, enhances CAF effector gene expression and promotes stromal and cancer cell expansion. The findings support a CAF activation/stromal co-evolution model under convergent CSL/p53 control of likely clinical relevance.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

Sidelobe elimination for generalized synthetic discriminant functions by a two-filter correlation and subsequent postprocessing of the intensity distributions

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Biological interpretation of genome-wide association studies using predicted gene functions.

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

Implementing Role Based Access Control into the Enterprise Environment to Support Business and IT Functions

The thesis studies role based access control and its suitability in the enterprise environment. The aim is to research how extensively role based access control can be implemented in the case organization and how it support organization’s business and IT functions. This study points out the enterprise’s needs for access control, factors of access control in the enterprise environment and requirements for implementation and the benefits and challenges it brings along. To find the scope how extensively role based access control can be implemented into the case organization, firstly is examined the actual state of access control. Secondly is defined a rudimentary desired state (how things should be) and thirdly completed it by using the results of the implementation of role based access control application. The study results the role model for case organization unit, and the building blocks and the framework for the organization wide implementation. Ultimate value for organization is delivered by facilitating the normal operations of the organization whilst protecting its information assets.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.