Chitosan derivatives alter release profiles of model compounds from calcium phosphate implants

The aim of the current study was to evaluate the impact of chitosan derivatives, namely N-octyl-chitosan and N-octyl-O-sulfate chitosan, incorporated in calcium phosphate implants to the release profiles of model drugs. The rate and extent of calcein (on M.W. 650 Da) ED, and FITC-dextran (M.W. 40 kDa) on in vitro release were monitored by fluorescence spectroscopy. Results show that calcein release is affected by the type of chitosan derivative used. A higher percentage of model drug was released when the hydrophilic polymer N-octyl-sulfated chitosan was present in the tablets compared with the tablets containing the hydrophobic polymer N-octyl-chitosan. The release profiles of calcein or FD from tablets containing N-octyl-O-sulfate revealed a complete release for FD after 120 h compared with calcein where 20% of the drug was released over the same time period. These results suggest that the difference in the release profiles observed from the implants is dependent on the molecular weight of the model drugs. These data indicate the potential of chitosan derivatives in controlling the release profile of active compounds from calcium phosphate implants. (C) 2009 Elsevier Ltd. All rights reserved.

Molecular orbital calculation for the model compounds of kainoid amino acids, agonists of excitatory amino acid receptors. Does the kainoid C4-substituent directly interact with the receptors?

Kainoid amino acids are agonists of the AMPA/kainate receptors and exhibit highly potent neuroexcitatory activity. From the results of extensive structure-activity relationship studies, we previously postulated that the C4-substituent of the kainoid amino acids interacts with an allosteric site of the glutamate receptor with electron-donating character. In order to investigate the mode of action in more detail, molecular orbital calculation for model compounds of the kainoid were performed. The results indicated that the HOMO energy level of the C4-substituent is involved in the potent neuroexcitatory activity, thus supporting our hypothesis. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Macrophages and dendritic cells express tight junction proteins and exchange particles in an in vitro model of the human airway wall

The human airway epithelium serves as structural and functional barrier against inhaled particulate antigen. Previously, we demonstrated in an in vitro epithelial barrier model that monocyte derived dendritic cells (MDDC) and monocyte derived macrophages (MDM) take up particulate antigen by building a trans-epithelial interacting network. Although the epithelial tight junction (TJ) belt was penetrated by processes of MDDC and MDM, the integrity of the epithelium was not affected. These results brought up two main questions: (1) Do MDM and MDDC exchange particles? (2) Are those cells expressing TJ proteins, which are believed to interact with the TJ belt of the epithelium to preserve the epithelial integrity? The expression of TJ and adherens junction (AJ) mRNA and proteins in MDM and MDDC monocultures was determined by RT-PCR, and immunofluorescence, respectively. Particle uptake and exchange was quantified by flow cytometry and laser scanning microscopy in co-cultures of MDM and MDDC exposed to polystyrene particles (1 μm in diameter). MDM and MDDC constantly expressed TJ and AJ mRNA and proteins. Flow cytometry analysis of MDM and MDDC co-cultures showed increased particle uptake in MDDC while MDM lost particles over time. Quantitative analysis revealed significantly higher particle uptake by MDDC in co-cultures of epithelial cells with MDM and MDDC present, compared to co-cultures containing only epithelial cells and MDDC. We conclude from these findings that MDM and MDDC express TJ and AJ proteins which could help to preserve the epithelial integrity during particle uptake and exchange across the lung epithelium.

IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

Mapping Hydrophobicity on the Protein Molecular Surface at Atom-Level Resolution

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 A˚, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced "leopard skin"-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism.

A model for the interaction of trifluoroethanol with peptides and proteins

The structural stabilizing property of 2,2,2-trifluoroethanol (TFE) in peptides has been widely demonstrated, More recently, TFE has been shown to enhance secondary structure content in globular proteins, and to influence quaternary interactions in protein multimers. The molecular mechanisms by which TFE exerts its Influence on peptide and protein structures remain poorly understood. The present analysis integrates the known physical properties of TFE with a variety of experimental observations on the interaction of TFE with peptides and proteins and on the properties of fluorocarbons. Two features of TFE, namely the hydrophobicity of the trifluoromethyl group and the hydrogen bonding character (strong donor and poor acceptor), emerge as the most important factors for rationalising the observed effects of TFE. A model is proposed for TFE interaction with peptides which involves an initial replacement of the hydration shell by fluoroalcohol molecules, a process driven by apolar interactions and favourable entropy of dehydration. Subsequent bifurcated hydrogen-bond formation with peptide carbonyl groups, which leave intramolecular interactions unaffected, promotes secondary structure formation.

Mechanisms and molecular regulation of mammalian tooth replacement

In most non-mammalian vertebrates, such as fish and reptiles, teeth are replaced continuously. However, tooth replacement in most mammals, including human, takes place only once and further renewal is apparently inhibited. It is not known how tooth replacement is genetically regulated, and little is known on the physiological mechanism and evolutionary reduction of tooth replacement in mammals. In this study I have attempted to address these questions. In a rare human condition cleidocranial dysplasia, caused by a mutation in a Runt domain transcription factor Runx2, tooth replacement is continued. Runx2 mutant mice were used to investigate the molecular mechanisms of Runx2 function. Microarray analysis from dissected embryonic day 14 Runx2 mutant and wild type dental mesenchymes revealed many downstream targets of Runx2, which were validated using in situ hybridization and tissue culture methods. Wnt signaling inhibitor Dkk1 was identified as a candidate target, and in tissue culture conditions it was shown that Dkk1 is induced by FGF4 and this induction is Runx2 dependent. These experiments demonstrated a connection between Runx2, FGF and Wnt signaling in tooth development and possibly also in tooth replacement. The role of Wnt signaling in tooth replacement was further investigated by using a transgenic mouse model where Wnt signaling mediator β-catenin is continuously stabilized in dental epithelium. This stabilization led to activated Wnt signaling and to the formation of multiple enamel knots. In vitro and transplantation experiments were performed to examine the process of extra tooth formation. We showed that new teeth were continuously generated and that new teeth form from pre-existing teeth. A morphodynamic activator-inhibitor model was used to simulate enamel knot formation. By increasing the intrinsic production rate of the activator (β-catenin), the multiple enamel knot phenotype was reproduced by computer simulations. It was thus concluded that β-catenin acts as an upstream activator of enamel knots, closely linking Wnt signaling to the regulation of tooth renewal. As mice do not normally replace teeth, we used other model animals to investigate the physiological and genetic mechanisms of tooth replacement. Sorex araneus, the common shrew was earlier reported to have non-functional tooth replacement in all antemolar tooth positions. We showed by histological and gene expression studies that there is tooth replacement only in one position, the premolar 4 and that the deciduous tooth is diminished in size and disappears during embryogenesis without becoming functional. The growth rates of deciduous and permanent premolar 4 were measured and it was shown by competence inference that the early initiation of the replacement tooth in relation to the developmental stage of the deciduous tooth led to the inhibition of deciduous tooth morphogenesis. It was concluded that the evolutionary loss of deciduous teeth may involve the early activation of replacement teeth, which in turn suppress their predecessors. Mustela putorius furo, the ferret, has a dentition that resembles that of the human as ferrets have teeth that belong to all four tooth families, and all the antemolar teeth are replaced once. To investigate the replacement mechanism, histological serial sections from different embryonic stages were analyzed. It was noticed that tooth replacement is a process which involves the growth and detachment of the dental lamina from the lingual cervical loop of the deciduous tooth. Detachment of the deciduous tooth leads to a free successional dental lamina, which grows deeper into the mesenchyme, and later buds the replacement tooth. A careful 3D analysis of serial histological sections was performed and it was shown that replacement teeth are initiated from the successional dental lamina and not from the epithelium of the deciduous tooth. The molecular regulation of tooth replacement was studied and it was shown by examination of expression patterns of candidate regulatory genes that BMP/Wnt inhibitor Sostdc1 was strongly expressed in the buccal aspect of the dental lamina, and in the intersection between the detaching deciduous tooth and the successional dental lamina, suggesting a role for Sostdc1 in the process of detachment. Shh was expressed in the enamel knot and in the inner enamel epithelium in both generations of teeth supporting the view that the morphogenesis of both generations of teeth is regulated by similar mechanisms. In summary, histological and molecular studies on different model animals and transgenic mouse models were used to investigate tooth replacement. This thesis work has significantly contributed to the knowledge on the physiological mechanisms and molecular regulation of tooth replacement and its evolutionary suppression in mammals.

Studies on orographic effects in a numerical weather prediction model

Numerical models, used for atmospheric research, weather prediction and climate simulation, describe the state of the atmosphere over the heterogeneous surface of the Earth. Several fundamental properties of atmospheric models depend on orography, i.e. on the average elevation of land over a model area. The higher is the models' resolution, the more the details of orography directly influence the simulated atmospheric processes. This sets new requirements for the accuracy of the model formulations with respect to the spatially varying orography. Orography is always averaged, representing the surface elevation within the horizontal resolution of the model. In order to remove the smallest scales and steepest slopes, the continuous spectrum of orography is normally filtered (truncated) even more, typically beyond a few gridlengths of the model. This means, that in the numerical weather prediction (NWP) models, there will always be subgridscale orography effects, which cannot be explicitly resolved by numerical integration of the basic equations, but require parametrization. In the subgrid-scale, different physical processes contribute in different scales. The parametrized processes interact with the resolved-scale processes and with each other. This study contributes to building of a consistent, scale-dependent system of orography-related parametrizations for the High Resolution Limited Area Model (HIRLAM). The system comprises schemes for handling the effects of mesoscale (MSO) and small-scale (SSO) orographic effects on the simulated flow and a scheme of orographic effects on the surface-level radiation fluxes. Representation of orography, scale-dependencies of the simulated processes and interactions between the parametrized and resolved processes are discussed. From the high-resolution digital elevation data, orographic parameters are derived for both momentum and radiation flux parametrizations. Tools for diagnostics and validation are developed and presented. The parametrization schemes applied, developed and validated in this study, are currently being implemented into the reference version of HIRLAM.

Molecular assemblies for solar energy conversion - Biomimetic approach

Excitation energy migration followed by electron transfer forms the main components of natural photosynthesis. An understanding of these aspects is essential to reenact the primary processes in laboratory under conditions that are precisely repeatable. Here we describe the state of understanding of the natural process and several model systems designed to harvest solar energy and conversion to useful form of chemical energy. The molecular assemblies constituting the model systems offer a great advantage in terms of better comprehension of the mechanistic aspects and yield valuable information on the design of molecular photonic devices.

Lattice model for rapidly folding protein-like heteropolymers

Protein folding is a relatively fast process considering the astronomical number of conformations in which a protein could find itself. Within the framework of a lattice model, we show that one can design rapidly folding sequences by assigning the strongest attractive couplings to the contacts present in a target native state, Our protein design can be extended to situations with both attractive and repulsive contacts. Frustration is minimized by ensuring that all the native contacts are again strongly attractive. Strikingly, this ensures the inevitability of folding and accelerates the folding process by an order of magnitude, The evolutionary implications of our findings are discussed.

Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of similar to 1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (Rank Score), which correlated with the residue depth, and identify active-site residues. Using these correlations, similar to 98% of correct models of CcdB (RMSD <= 4 angstrom) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout.

Modeling the effect of transmission errors on TCP controlled transfers over infrastructure 802.11 wireless LANs

There have been several studies on the performance of TCP controlled transfers over an infrastructure IEEE 802.11 WLAN, assuming perfect channel conditions. In this paper, we develop an analytical model for the throughput of TCP controlled file transfers over the IEEE 802.11 DCF with different packet error probabilities for the stations, accounting for the effect of packet drops on the TCP window. Our analysis proceeds by combining two models: one is an extension of the usual TCP-over-DCF model for an infrastructure WLAN, where the throughput of a station depends on the probability that the head-of-the-line packet at the Access Point belongs to that station; the second is a model for the TCP window process for connections with different drop probabilities. Iterative calculations between these models yields the head-of-the-line probabilities, and then, performance measures such as the throughputs and packet failure probabilities can be derived. We find that, due to MAC layer retransmissions, packet losses are rare even with high channel error probabilities and the stations obtain fair throughputs even when some of them have packet error probabilities as high as 0.1 or 0.2. For some restricted settings we are also able to model tail-drop loss at the AP. Although involving many approximations, the model captures the system behavior quite accurately, as compared with simulations.

Improving LVCSR system combination using neural network language model cross adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.

Model based control for closed loop testing of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts and prediction of the resulting engine transient response. The latter often requires closed loop control over the model to ensure operation within physical limits and tracking of reference signals. For this purpose, a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). As an example this study is focused on the transient response of a light-duty car Diesel engine. For the cases examined the proposed controller implementation gives a more systematic procedure than other ad-hoc approaches that require considerable tuning effort. © 2012 IFAC.

低能Ar~(3+)+Ar碰撞反应过程实验研究

测量了入射离子能量为27 keV、45 keV和66 keV时Ar3++Ar碰撞反应各子过程的分截面,通过将其归一化到Bliman,Dousson等人所测量的截面值,获得了绝对截面.结果表明,该能区电子俘获过程仍占主导地位,但转移电离过程已不能忽略.结果还表明,各子过程反应截面基本不随能量变化.与考虑自电离的MCBM(Molecular Coulombic overBarrier Model)模型比较发现,模型所给截面普遍高于实验测量值,这在一定程度上是由于归一化时带来的系统误差.在误差允许的范围内,单电子和双电子俘获截面符合的比较好,但三电子俘获截面却相差一个数量级.对于实验观测到的转移电离过程,模型却预言并没有此过程发生.