New Method to Prepare Mitomycin C Loaded PLA-Nanoparticles with High Drug Entrapment Efficiency

The classical utilized double emulsion solvent diffusion technique for encapsulating water soluble Mitomycin C (MMC) in PLA nanoparticles suffers from low encapsulation efficiency because of the drug rapid partitioning to the external aqueous phase. In this paper, MMC loaded PLA nanoparticles were prepared by a new single emulsion solvent evaporation method, in which soybean phosphatidylcholine (SPC) was employed to improve the liposolubility of MMC by formation of MMC–SPC complex. Four main influential factors based on the results of a single-factor test, namely, PLA molecular weight, ratio of PLA to SPC (wt/wt) and MMC to SPC (wt/wt), volume ratio of oil phase to water phase, were evaluated using an orthogonal design with respect to drug entrapment efficiency. The drug release study was performed in pH 7.2 PBS at 37 °C with drug analysis using UV/vis spectrometer at 365 nm. MMC–PLA particles prepared by classical method were used as comparison. The formulated MMC–SPC–PLA nanoparticles under optimized condition are found to be relatively uniform in size (594 nm) with up to 94.8% of drug entrapment efficiency compared to 6.44 μm of PLA–MMC microparticles with 34.5% of drug entrapment efficiency. The release of MMC shows biphasic with an initial burst effect, followed by a cumulated drug release over 30 days is 50.17% for PLA–MMC–SPC nanoparticles, and 74.1% for PLA–MMC particles. The IR analysis of MMC–SPC complex shows that their high liposolubility may be attributed to some weak physical interaction between MMC and SPC during the formation of the complex. It is concluded that the new method is advantageous in terms of smaller size, lower size distribution, higher encapsulation yield, and longer sustained drug release in comparison to classical method

Canine respiratory coronavirus employs caveolin-1-mediated pathway for internalization to HRT-18G cells

Canine respiratory coronavirus (CRCoV), identified in 2003, is a member of the Coronaviridae family. The virus is a betacoronavirus and a close relative of human coronavirus OC43 and bovine coronavirus. Here, we examined entry of CRCoV into human rectal tumor cells (HRT-18G cell line) by analyzing co-localization of single virus particles with cellular markers in the presence or absence of chemical inhibitors of pathways potentially involved in virus entry. We also targeted these pathways using siRNA. The results show that the virus hijacks caveolin-dependent endocytosis to enter cells via endocytic internalization

Inflammatory cytokines and biofilm production sustain Staphylococcus aureus outgrowth and persistence: A pivotal interplay in the pathogenesis of Atopic Dermatitis

Individuals with Atopic dermatitis (AD) are highly susceptible to Staphylococcus aureus colonization. However, the mechanisms driving this process as well as the impact of S. aureus in AD pathogenesis are still incompletely understood. In this study, we analysed the role of biofilm in sustaining S. aureus chronic persistence and its impact on AD severity. Further we explored whether key inflammatory cytokines overexpressed in AD might provide a selective advantage to S. aureus. Results show that the strength of biofilm production by S. aureus correlated with the severity of the skin lesion, being significantly higher (P < 0.01) in patients with a more severe form of the disease as compared to those individuals with mild AD. Additionally, interleukin (IL)-β and interferon γ (IFN-γ), but not interleukin (IL)-6, induced a concentration-dependent increase of S. aureus growth. This effect was not observed with coagulase-negative staphylococci isolated from the skin of AD patients. These findings indicate that inflammatory cytokines such as IL1-β and IFN-γ, can selectively promote S. aureus outgrowth, thus subverting the composition of the healthy skin microbiome. Moreover, biofilm production by S. aureus plays a relevant role in further supporting chronic colonization and disease severity, while providing an increased tolerance to antimicrobials

Genome-Scale Reconstruction of Escherichia coli's Transcriptional and Translational Machinery: A Knowledge Base, Its Mathematical Formulation, and Its Functional Characterization

Metabolic network reconstructions represent valuable scaffolds for ‘-omics’ data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron–sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of ‘-omics’ datasets and thus the study of the mechanistic principles underlying the genotype–phenotype relationship

Composite GUTs: models and expectations at the LHC

We investigate grand unified theories (GUTs) in scenarios where electroweak (EW) symmetry breaking is triggered by a light composite Higgs, arising as a Nambu-Goldstone boson from a strongly interacting sector. The evolution of the standard model (SM) gauge couplings can be predicted at leading order, if the global symmetry of the composite sector is a simple group G that contains the SM gauge group. It was noticed that, if the right-handed top quark is also composite, precision gauge unification can be achieved. We build minimal consistent models for a composite sector with these properties, thus demonstrating how composite GUTs may represent an alternative to supersymmetric GUTs. Taking into account the new contributions to the EW precision parameters, we compute the Higgs effective potential and prove that it realizes consistently EW symmetry breaking with little fine-tuning. The G group structure and the requirement of proton stability determine the nature of the light composite states accompanying the Higgs and the top quark: a coloured triplet scalar and several vector-like fermions with exotic quantum numbers. We analyse the signatures of these composite partners at hadron colliders: distinctive final states contain multiple top and bottom quarks, either alone or accompanied by a heavy stable charged particle, or by missing transverse energy.Comment: 55 pages, 13 figures, final version to be published in JHE

Category label and response location shifts in category learning

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed

Interaction of Aspirin (Acetylsalicylic Acid) with Lipid Membranes

We studied the interaction of Aspirin (acetylsalicylic acid) with lipid membranes using x-ray diffraction for bilayers containing up to 50 mol% of aspirin. From 2D x-ray intensity maps that cover large areas of reciprocal space we determined the position of the ASA molecules in the phospholipid bilayers and the molecular arrangement of the molecules in the plane of the membranes. We present direct experimental evidence that ASA molecules participate in saturated lipid bilayers of DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) and preferably reside in the head group region of the membrane. Up to 50 mol% ASA molecules can be dissolved in this type of bilayer before the lateral membrane organization is disturbed and the membranes are found to form an ordered, 2D crystal-like structure. Furthermore, ASA and cholesterol were found to co-exist in saturated lipid bilayers, with the ASA molecules residing in the head group region and the cholesterol molecules participating in the hydrophobic membrane core