On‐the‐Spot Immobilization of Quantum Dots,Graphene Oxide,and Proteins via Hydrophobins

Class I hydrophobin Vmh2, a peculiar surface active and versatile fungal protein, is known to self‐assemble into chemically stable amphiphilic films, to be able to change wettability of surfaces, and to strongly adsorb other proteins. Herein, a fast, highly homogeneous and efficient glass functionalization by spontaneous self‐assembling of Vmh2 at liquid–solid interfaces is achieved (in 2 min). The Vmh2‐coated glass slides are proven to immobilize not only proteins but also nanomaterials such as graphene oxide (GO) and quantum dots (QDs). As models, bovine serum albumin labeled with Alexa 555 fluorophore, anti‐immunoglobulin G antibodies, and cadmium telluride QDs are patterned in a microarray fashion in order to demonstrate functionality, reproducibility, and versatility of the proposed substrate. Additionally, a GO layer is effectively and homogeneously self‐assembled onto the studied functionalized surface. This approach offers a quick and simple alternative to immobilize nanomaterials and proteins, which is appealing for new bioanalytical and nanobioenabled applications.     

Growth condition of iodine-doped n+-CdTe layers in metal-organic vapor phase epitaxy

Iodine doping of CdTe layers grown on (100) GaAs by metal-organic vapor phase epitaxy (MOVPE) was studied using diethyltelluride (DETe) and diisopropyltelluride (DiPTe) as tellurium precursors and ethyliodine (EI) as a dopant. Electron densities of doped layers increased gradually with decreasing the growth temperature from 425°C to 325°C. Doped layers grown with DETe had higher electron densities than those grown with DiPTe. When the hot-wall temperature was increased from 200°C to 250°C at the growth temperature of 325°C, doped layers grown with DETe showed an increase of the electron density from 3.7×10¹⁶ cm⁻³ to 2.6×10¹⁸ cm⁻³. On the other hand, such an increase of the electron density was not observed for layers grown with DiPTe. The mechanisms for different doping properties for DETe and DiPTe were studied on the basis of the growth characteristics for these precursors. Higher thermal stability of DETe than that of DiPTe was considered to cause the difference of doping properties. With increasing the hot-wall temperature from 200°C to 250°C, the effective ratio of Cd to Te species on the growth surface became larger for layers grown with DETe than those grown with DiPTe. This was considered to decrease the compensation of doped iodine and to increase the electron density of layers grown with DETe. The effective ratio of Cd to Te species on the growth surface also increased with decreasing growth temperature. This was considered to increase the electron density with decreasing growth temperature.     

Effects of cytogenin on spontaneous arthritis in MRL/1 mice and on pristane-induced arthritis (PIA) in DBA/1J mice

Cytogenin, 8-hydroxy-3-hydroxymethyl-6-methoxyisocoumarin, has low cytotoxicity on murine and human tumour cells in vitro. It augments or suppresses phagocytosis of macrophages and lymphocyte proliferation. It has been reported that cytogenin has a potent inhibitory effect clinically on adjuvant arthritis in Lewis rats and on type II collagen-induced arthritis in DBA/1J mice. Our experimental findings provide evidence that cytogenin has beneficial effects on spontaneous polyarthritis in MRL/1 mice and pristane-induced arthritis in DBA/1J mice. The results suggest that the mode of the anti-arthritic action of cytogenin is different from those of NSAIDs; although the precise mode of action remains unclear, cytogenin may become an excellent therapeutic agent for rheumatoid arthritis.     

Thermodynamics of inositol hexakisphosphate interaction with human oxyhemoglobin

The interaction of inositol hexakisphosphate (IHP) with oxygenated human adult hemoglobin (Hb) was investigated at 25 degreesC. The affinity of IHP for oxygenated Hb is strongly pH-dependent, and potentiometric measurements of proton uptake and release upon IHP addition have shown that over the range between pH 8.0 and pH 6.0 in oxygenated Hb there are three groups of residues that change their pKa values after IHP addition, likely because of their interaction with negative charges of the heterotropic effector. On the basis of previous calculations on the electrostatic properties of human Hb (Matthew, J. B., Hanania, G. I. H., and Gurd, F. R. N. (1979) Biochemistry 18, 1919-1928; Lee, A. W.-m., Karplus, M., Poyart, C., and Bursaux, E. (1988) Biochemistry 27, 1285-1301), two of these groups might be Val1beta and His143beta, which are located in the beta1beta2 dyad axis, where they have been also proposed to interact with 2,3-diphosphoglycerate, whereas the third group does not appear easily identifiable. Calorimetric measurements of the heat associated with IHP binding at different pH values over the same range indicate that IHP binding is mostly enthalpy-driven at pH < 7 and mostly entropy-driven at pH > 7.     

Recent Update on the Molecular Mechanisms of Gonadal Steroids Action in Adipose Tissue

The gonadal steroids, including androgens, estrogens and progestogens, are involved in the control of body fat distribution in humans. Nevertheless, not only the size and localization of the fat depots depend on the sex steroids levels, but they can also highly affect the functioning of adipose tissue. Namely, the gonadocorticoids can directly influence insulin signaling, lipid metabolism, fatty acid uptake and adipokine production. They may also alter energy balance and glucose homeostasis in adipocytes in an indirect way, e.g., by changing the expression level of aquaglyceroporins. This work presents the recent advances in understanding the molecular mechanism of how the gonadal steroids influence the functioning of adipose tissue leading to a set of detrimental metabolic consequences. Special attention is given here to highlighting the sexual dimorphism of adipocyte functioning in terms of health and disease. Particularly, we discuss the molecular background of metabolic disturbances occurring in consequence of hormonal imbalance which is characteristic of some common endocrinopathies such as the polycystic ovary syndrome. From this perspective, we highlight the potential drug targets and the active substances which can be used in personalized sex-specific management of metabolic diseases, in accord with the patient’s hormonal status.     

PGRP-LB: An Inside View into the Mechanism of the Amidase Reaction

Peptidoglycan recognition proteins (PGRPs) are ubiquitous among animals and play pivotal functions in insect immunity. Non-catalytic PGRPs are involved in the activation of immune pathways by binding to the peptidoglycan (PGN), whereas amidase PGRPs are capable of cleaving the PGN into non-immunogenic compounds. Drosophila PGRP-LB belongs to the amidase PGRPs and downregulates the immune deficiency (IMD) pathway by cleaving meso-2,6-diaminopimelic (meso-DAP or DAP)-type PGN. While the recognition process is well analyzed for the non-catalytic PGRPs, little is known about the enzymatic mechanism for the amidase PGRPs, despite their essential function in immune homeostasis. Here, we analyzed the specific activity of different isoforms of Drosophila PGRP-LB towards various PGN substrates to understand their specificity and role in Drosophila immunity. We show that these isoforms have similar activity towards the different compounds. To analyze the mechanism of the amidase activity, we performed site directed mutagenesis and solved the X-ray structures of wild-type Drosophila PGRP-LB and its mutants, with one of these structures presenting a protein complexed with the tracheal cytotoxin (TCT), a muropeptide derived from the PGN. Only the Y78F mutation abolished the PGN cleavage while other mutations reduced the activity solely. Together, our findings suggest the dynamic role of the residue Y78 in the amidase mechanism by nucleophilic attack through a water molecule to the carbonyl group of the amide function destabilized by Zn²⁺.     

The Co-Culture of Staphylococcal Biofilm and Fibroblast Cell Line: The Correlation of Biological Phenomena with Metabolic NMR1 Footprint

Staphylococcus aureus is one of the most prevalent pathogens associated with several types of biofilm-based infections, including infections of chronic wounds. Mature staphylococcal biofilm is extremely hard to eradicate from a wound and displays a high tendency to induce recurring infections. Therefore, in the present study, we aimed to investigate in vitro the interaction between S. aureus biofilm and fibroblast cells searching for metabolites that could be considered as potential biomarkers of critical colonization and infection. Utilizing advanced microscopy and microbiological methods to examine biofilm formation and the staphylococcal infection process, we were able to distinguish 4 phases of biofilm development. The analysis of staphylococcal biofilm influence on the viability of fibroblasts allowed us to pinpoint the moment of critical colonization—12 h post contamination. Based on the obtained model we performed a metabolomics analysis by ¹H NMR spectroscopy to provide new insights into the pathophysiology of infection. We identified a set of metabolites related to the switch to anaerobic metabolism that was characteristic for staphylococcal biofilm co-cultured with fibroblast cells. The data presented in this study may be thus considered a noteworthy but preliminary step in the direction of developing a new, NMR-based tool for rapid diagnosing of infection in a chronic wound.     

Classification of dissimilarity data with a new flexible Mahalanobis-like metric

Statistical pattern recognition traditionally relies on feature-based representation. For many applications, such vector representation is not available and we only possess proximity data (distance, dissimilarity, similarity, ranks, etc.). In this paper, we consider a particular point of view on discriminant analysis from dissimilarity data. Our approach is inspired by the Gaussian classifier and we defined decision rules to mimic the behavior of a linear or a quadratic classifier. The number of parameters is limited (two per class). Numerical experiments on artificial and real data show interesting behavior compared to Support Vector Machines and to kNN classifier: (a) lower or equivalent error rate, (b) equivalent CPU time, (c) more robustness with sparse dissimilarity data.