N-Benzoyl amino acids as ICAM/LFA-1 inhibitors. Part 2: structure-activity relationship of the benzoyl moiety

o-Bromobenzoyl l-tryptophan 1 inhibits the association of LFA-1 with ICAM-1 with an IC(50) of 1.7microM. Evaluation of the structure-activity relationship of the benzoyl moiety shows that 2,6-di-substitutions greatly enhance potency of this class of inhibitors. Electronegative substitutions that favor a 90 degrees angle between the benzoyl ring and the amide bond yield the most potent compounds. There is a strong correlation between the potency of the compounds and the difference between the ab initio energy at 90 degrees and the global minima energy for given compounds. Combining the favored benzoyl substitutions with l-histidine and l-asparagine resulted in a 15-fold increase in potency over compound 1.     

Nonlinear optical imaging to evaluate the impact of obesity on mammary gland and tumor stroma

Obesity is an established risk factor for breast cancer incidence and mortality. However, the mechanism that links obesity to tumorigenesis is not well understood. Here we combined nonlinear optical imaging technologies with an early-onset diet-induced obesity breast cancer animal model to evaluate the impact of obesity on the composition of mammary gland and tumor stroma. Using coherent anti-Stokes Raman scattering and second harmonic generation on the same platform, we simultaneously imaged mammary adipocytes, blood capillaries, collagen fibrils, and tumor cells without any labeling. We observed that obesity increases the size of lipid droplets of adipocytes in mammary gland and collagen content in mammary tumor stroma, respectively. Such impacts of obesity on mammary gland and tumor stroma could not be analyzed using standard two-dimensional histologic evaluation. Given the importance of mammary stroma to the growth and migration of tumor cells, our observation provides the first imaging evidence that supports the relationship between obesity and breast cancer risk.     

Proteasome-Related HslU and HslV Genes Typical of Eubacteria Are Widespread in Eukaryotes

Many eubacteria contain an ATP-dependent protease complex, which is built by multiple copies of the HslV and HslU proteins and is therefore called HslVU. HslU proteins are AAA + ATPases, while HslV proteins are proteases that show highly significant similarity to β subunits of proteasomes. Therefore, the HslVU complex has been envisaged as a precursor or ancestral type of proteasome. Here we show that species of most of the main eukaryotic lineages have HslU and HslV genes very similar to those found in proteobacteria. We have detected them in amoebozoa, plantae, chromoalveolata, rhizaria, and excavata species. Phylogenetic analyses suggest that these genes have been obtained by endosymbiosis from the proteobacterial ancestor that gave rise to eukaryotic mitochondria. The products encoded by these eukaryotic genes adopt, according to modeling based on the known crystal structures of prokaryotic HslU and HslV proteins, conformations that are compatible with their being fully active, suggesting that functional HslVU complexes may be present in many eukaryotic species. [Reviewing Editor: Dr. Yves Van de Peer]     

Atlas of Iberian water beetles (ESACIB database)

The ESACIB (‘EScarabajos ACuáticos IBéricos’) database is provided, including all available distributional data of Iberian and Balearic water beetles from the literature up to 2013, as well as from museum and private collections, PhD theses, and other unpublished sources. The database contains 62,015 records with associated geographic data (10×10 km UTM squares) for 488 species and subspecies of water beetles, 120 of them endemic to the Iberian Peninsula and eight to the Balearic Islands. This database was used for the elaboration of the “Atlas de los Coleópteros Acuáticos de España Peninsular”. In this dataset data of 15 additional species has been added: 11 that occur in the Balearic Islands or mainland Portugal but not in peninsular Spain and an other four with mainly terrestrial habits within the genus Helophorus (for taxonomic coherence). The complete dataset is provided in Darwin Core Archive format.     

Progesterone induces mucosal immunity in a rodent model of human taeniosis by Taenia solium

More than one quarter of human world's population is exposed to intestinal helminth parasites. The Taenia solium tapeworm carrier is the main risk factor in the transmission of both human neurocysticercosis and porcine cysticercosis. Sex steroids play an important role during T. solium infection, particularly progesterone has been proposed as a key immunomodulatory hormone involved in susceptibility to human taeniosis in woman and cysticercosis in pregnant pigs. Thus, we evaluated the effect of progesterone administration upon the experimental taeniosis in golden hamsters (Mesocricetus auratus). Intact female adult hamsters were randomly divided into 3 groups: progesterone-subcutaneously treated; olive oil-treated as the vehicle group; and untreated controls. Animals were treated every other day during 4 weeks. After 2 weeks of treatment, all hamsters were orally infected with 4 viable T. solium cysticerci. After 2 weeks post infection, progesterone-treated hamsters showed reduction in adult worm recovery by 80%, compared to both vehicle-treated and non-manipulated infected animals. In contrast to control and vehicle groups, progesterone treatment diminished tapeworm length by 75% and increased proliferation rate of leukocytes from spleen and mesenteric lymph nodes of infected hamsters by 5-fold. The latter exhibited high expression levels of IL-4, IL-6 and TNF-α at the duodenal mucosa, accompanied with polymorphonuclear leukocytes infiltration. These results support that progesterone protects hamsters from the T. solium adult tapeworm establishment by improving the intestinal mucosal immunity, suggesting a potential use of analogues of this hormone as novel inductors of the gut immune response against intestinal helminth infections and probably other bowel-related disorders.     

The Relative Expression of Mig6 and EGFR Is Associated with Resistance to EGFR Kinase Inhibitors

The sensitivity of only a few tumors to anti-epidermal growth factor receptor EGFR tyrosine kinase inhibitors (TKIs) can be explained by the presence of EGFR tyrosine kinase (TK) domain mutations. In addition, such mutations were rarely found in tumor types other than lung, such as pancreatic and head and neck cancer. In this study we sought to elucidate mechanisms of resistance to EGFR-targeted therapies in tumors that do not harbor TK sensitizing mutations in order to identify markers capable of guiding the decision to incorporate these drugs into chemotherapeutic regimens. Here we show that EGFR activity was markedly decreased during the evolution of resistance to the EGFR tyrosine kinase inhibitor (TKI) erlotinib, with a concomitant increase of mitogen-inducible gene 6 (Mig6), a negative regulator of EGFR through the upregulation of the PI3K-AKT pathway. EGFR activity, which was more accurately predicted by the ratio of Mig6/EGFR, highly correlated with erlotinib sensitivity in panels of cancer cell lines of different tissue origins. Blinded testing and analysis in a prospectively followed cohort of lung cancer patients treated with gefitinib alone demonstrated higher response rates and a marked increased in progression free survival for patients with a low Mig6/EGFR ratio (approximately 100 days, P = 0.01).     

An Adaptive Complex Network Model for Brain Functional Networks

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.