Does Doxycycline work in synergy with cisplatin and oxaliplatin in colorectal cancer?

Background: In recent years, apart from antibacterial properties, doxycycline is reported to have cytotoxic and anti-proliferative actions in various cancers including colorectal cancer. Colorectal cancer constitutes one of the most common cancers in the western population. Apart from surgery, chemotherapy plays crucial role in the treatment of colorectal cancer. Cisplatin and oxaliplatin are most commonly used platinum compounds for the cancer chemotherapy. This study has looked for any impact of doxycycline on the cytotoxic effects of platinum compounds in colorectal cancer including its mechanisms of actions.Methods: HT 29 colorectal cancer cells were used for this study. These cells were treated with cisplatin and oxaliplatin with or without doxycycline treatment. The caspase 3 gene expression was quantitated by gel electrophoresis and qualitated by real time polymerase chain reactions. The caspase 3 activity was assessed in HT 29 cells with fluorescence kit.Results: The results revealed increased caspase 3 gene expressions and activities in HT 29 cells treated with cisplatin, oxaliplatin and doxycycline; however the combination of doxycycline with cisplatin and oxaliplatin did not report increased caspase 3 gene expressions and activity compared to cisplatin and oxaliplatin alone.Conclusion: We concluded that doxycycline has role in apoptosis induction in the colorectal cancer. However, it did not show any synergy with platinum compounds in the colorectal cancer cells. This study also pointed towards possible caspase-independent actions of doxycycline with cisplatin and oxaliplatin. However, further work is required to underpin the mechanisms of actions of doxycycline

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Ontogenetic changes in leaf traits of tropical rainforest trees differing in juvenile light requirement

Relationships between leaf traits and the gap dependence for regeneration, and ontogenetic changes therein, were investigated in juvenile and adult tropical rainforest tree species. The juveniles of the 17 species included in the study were grown in high light, similar to the exposed crowns of the adult trees. The traits were structural, biomechanical, chemical and photosynthetic. With increasing species gap dependence, leaf mass per area (LMA) decreased only slightly in juveniles and remained constant in adults, whereas punch strength together with tissue density decreased, and photosynthetic capacity and chlorophyll increased. Contrary to what has been mostly found in evergreen tropical rainforest, the trade-off between investment in longevity and in productivity was evident at an essentially constant LMA. Of the traits pertaining to the chloroplast level, photosynthetic capacity per unit chlorophyll increased with gap dependence, but the chlorophyll a/b ratio showed no relationship. Adults had a twofold higher LMA, but leaf strength was on average only about 50% larger. Leaf tissue density, and chlorophyll and leaf N per area were also higher, whereas chlorophyll and leaf N per unit dry mass were lower. Ranking of the species, relationships between traits and with the gap dependence of the species were similar for juveniles and adults. However, the magnitudes of most ontogenetic changes were not clearly related to a species’ gap dependence. The adaptive value of the leaf traits for juveniles and adults is discussed

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Optimal stomatal behaviour around the world

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordStomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.This research was supported by the Australian Research Council (ARC MIA Discovery Project 1433500-2012-14). A.R. was financially supported in part by The Next-Generation Ecosystem Experiments (NGEE-Arctic) project, which is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science, and through the United States Department of Energy contract No. DE-AC02-98CH10886 to Brookhaven National Laboratory. M.O.d.B. acknowledges that the Brassica data were obtained within a research project financed by the Belgian Science Policy (OFFQ, contract number SD/AF/02) and coordinated by K. Vandermeiren at the Open-Top Chamber research facilities of CODA-CERVA (Tervuren, Belgium)

Optimal stomatal behaviour around the world

© 2015 Macmillan Publishers Limited. All rights reserved. Stomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Limbic-thalamo-cortical projections and reward-related circuitry integrity affects eating behavior: A longitudinal DTI study in adolescents with restrictive eating disorders.

Few studies have used diffusion tensor imaging (DTI) to investigate the micro-structural alterations of WM in patients with restrictive eating disorders (rED), and longitudinal data are lacking. Twelve patients with rED were scanned at diagnosis and after one year of family-based treatment, and compared to twenty-four healthy controls (HCs) through DTI analysis. A tract-based spatial statistics procedure was used to investigate diffusivity parameters: fractional anisotropy (FA) and mean, radial and axial diffusivities (MD, RD and AD, respectively). Reduced FA and increased RD were found in patients at baseline in the corpus callosum, corona radiata and posterior thalamic radiation compared with controls. However, no differences were found between follow-up patients and controls, suggesting a partial normalization of the diffusivity parameters. In patients, trends for a negative correlation were found between the baseline FA of the right anterior corona radiata and the Eating Disorder Examination Questionnaire total score, while a positive trend was found between the baseline FA in the splenium of corpus callosum and the weight loss occurred between maximal documented weight and time of admission. A positive trend for correlation was also found between baseline FA in the right anterior corona radiata and the decrease in the Obsessive-Compulsive Inventory Revised total score over time. Our results suggest that the integrity of the limbic-thalamo-cortical projections and the reward-related circuitry are important for cognitive control processes and reward responsiveness in regulating eating behavior