Cloning of cDNAs and molecular characterisation of C-type lectin-like proteins from snake venoms

C-type lectin-like proteins (CTLPs) isolated from snake venoms are the largest and most complex non-mammalian vertebrate C-type lectin-like domain family. In the present study, we simultaneously amplified four cDNAs encoding different types of CTLP subunits from the venoms of two different species of snakes by RT-PCR with a single sense primer and a nested universal primer - two CTLP subunit-encoding cDNAs were cloned from Deinagkistrodon acutus venom and two from Agkistrodon halys Pallas venom. All four cloned CTLP subunits exhibited typical motifs in their corresponding domain regions but with relatively-low sequence similarities to each other. Compared with previously-published CTLPs, the four cloned CTLPs subunits showed slight variations in the calcium-binding sites and the disulphide bonding patterns. To our knowledge, these data constitute the first example of co-expression of CTLP platelet glycoprotein Ib-binding subunits and coagulation factors in Agkistrodon halys Pallas venom.

A universal measure of chaotropicity and kosmotropicity

Diverse parameters, including chaotropicity, can limit the function of cellular systems and thereby determine the extent of Earth's biosphere. Whereas parameters such as temperature, hydrophobicity, pressure, pH, Hofmeister effects, and water activity can be quantified via standard scales of measurement, the chao-/kosmotropic activities of environmentally ubiquitous substances have no widely accepted, universal scale. We developed an assay to determine and quantify chao-/kosmotropicity for 97 chemically diverse substances that can be universally applied to all solutes. This scale is numerically continuous for the solutes assayed (from +361kJkg^-1mol^-1 for chaotropes to -659kJkg^-1mol^-1 for kosmotropes) but there are key points that delineate (i) chaotropic from kosmotropic substances (i.e. chaotropes =+4; kosmotropes =-4kJkg^-1mol^-1); and (ii) chaotropic solutes that are readily water-soluble (log P<1.9) from hydrophobic substances that exert their chaotropic activity, by proxy, from within the hydrophobic domains of macromolecular systems (log P>1.9). Examples of chao-/kosmotropicity values are, for chaotropes: phenol +143, CaCl₂ +92.2, MgCl₂ +54.0, butanol +37.4, guanidine hydrochloride +31.9, urea +16.6, glycerol [>6.5M] +6.34, ethanol +5.93, fructose +4.56; for kosmotropes: proline -5.76, sucrose -6.92, dimethylsulphoxide (DMSO) -9.72, mannitol -6.69, trehalose -10.6, NaCl -11.0, glycine -14.2, ammonium sulfate -66.9, polyethylene glycol- (PEG-)1000 -126; and for relatively neutral solutes: methanol, +3.12, ethylene glycol +1.66, glucose +1.19, glycerol [<5M] +1.06, maltose -1.43 (kJkg^-1mol^-1). The data obtained correlate with solute interactions with, and structure-function changes in, enzymes and membranes. We discuss the implications for diverse fields including microbial ecology, biotechnology and astrobiology.

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

When examining complex problems, such as the folding of proteins, coarse grained descriptions of the system drive our investigation and help us to rationalize the results. Oftentimes collective variables (CVs), derived through some chemical intuition about the process of interest, serve this purpose. Because finding these CVs is the most difficult part of any investigation, we recently developed a dimensionality reduction algorithm, sketch-map, that can be used to build a low-dimensional map of a phase space of high-dimensionality. In this paper we discuss how these machine-generated CVs can be used to accelerate the exploration of phase space and to reconstruct free-energy landscapes. To do so, we develop a formalism in which high-dimensional configurations are no longer represented by low-dimensional position vectors. Instead, for each configuration we calculate a probability distribution, which has a domain that encompasses the entirety of the low-dimensional space. To construct a biasing potential, we exploit an analogy with metadynamics and use the trajectory to adaptively construct a repulsive, history-dependent bias from the distributions that correspond to the previously visited configurations. This potential forces the system to explore more of phase space by making it desirable to adopt configurations whose distributions do not overlap with the bias. We apply this algorithm to a small model protein and succeed in reproducing the free-energy surface that we obtain from a parallel tempering calculation.

Molecular dynamics simulation model for the quantitative assessment of tool wear during single point diamond turning of cubic silicon carbide

Silicon carbide (SiC) is a material of great technological interest for engineering applications concerning hostile environments where silicon-based components cannot work (beyond 623 K). Single point diamond turning (SPDT) has remained a superior and viable method to harness process efficiency and freeform shapes on this harder material. However, it is extremely difficult to machine this ceramic consistently in the ductile regime due to sudden and rapid tool wear. It thus becomes non trivial to develop an accurate understanding of tool wear mechanism during SPDT of SiC in order to identify measures to suppress wear to minimize operational cost.

In this paper, molecular dynamics (MD) simulation has been deployed with a realistic analytical bond order potential (ABOP) formalism based potential energy function to understand tool wear mechanism during single point diamond turning of SiC. The most significant result was obtained using the radial distribution function which suggests graphitization of diamond tool during the machining process. This phenomenon occurs due to the abrasive processes between these two ultra hard materials. The abrasive action results in locally high temperature which compounds with the massive cutting forces leading to sp3–sp2 order–disorder transition of diamond tool. This represents the root cause of tool wear during SPDT operation of cubic SiC. Further testing led to the development of a novel method for quantitative assessment of the progression of diamond tool wear from MD simulations.

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

Universal tight binding model for chemical reactions in solution and at surfaces. II. Water

A revised water model intended for use in condensed phase simulations in the framework of the self consistent polarizable ion tight binding theory is constructed. The model is applied to water monomer, dimer, hexamers, ice, and liquid, where it demonstrates good agreement with theoretical results obtained by more accurate methods, such as DFT and CCSD(T), and with experiment. In particular, the temperature dependence of the self diffusion coefficient in liquid water predicted by the model, closely reproduces experimental curves in the temperature interval between 230 K and 350 K. In addition, and in contrast to standard DFT, the model properly orders the relative densities of liquid water and ice. A notable, but inevitable, shortcoming of the model is underestimation of the static dielectric constant by a factor of two. We demonstrate that the description of inter and intramolecular forces embodied in the tight binding approximation in quantum mechanics leads to a number of valuable insights which can be missing from ab initio quantum chemistry and classical force fields. These include a discussion of the origin of the enhanced molecular electric dipole moment in the condensed phases, and a detailed explanation for the increase of coordination number in liquid water as a function of temperature and compared with ice-leading to insights into the anomalous expansion on freezing. The theory holds out the prospect of an understanding of the currently unexplained density maximum of water near the freezing point. 

Universal tight binding model for chemical reactions in solution and at surfaces. III. Stoichiometric and reduced surfaces of titania and the adsorption of water

We demonstrate a model for stoichiometric and reduced titanium dioxide intended for use in molecular dynamics and other atomistic simulations and based in the polarizable ion tight binding theory. This extends the model introduced in two previous papers from molecular and liquid applications into the solid state, thus completing the task of providing a comprehensive and unified scheme for studying chemical reactions, particularly aimed at problems in catalysis and electrochemistry. As before, experimental results are given priority over theoretical ones in selecting targets for model fitting, for which we used crystal parameters and band gaps of titania bulk polymorphs, rutile and anatase. The model is applied to six low index titania surfaces, with and without oxygen vacancies and adsorbed water molecules, both in dissociated and non-dissociated states. Finally, we present the results of molecular dynamics simulation of an anatase cluster with a number of adsorbed water molecules and discuss the role of edge and corner atoms of the cluster. (C) 2014 AIP Publishing LLC.

An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance

Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.

Single- and two-mode quantumness at a beam splitter

In the context of bipartite bosonic systems, two notions of classicality of correlations can be defined: P-classicality, based on the properties of the Glauber-Sudarshan P-function; and C-classicality, based on the entropic quantum discord. It has been shown that these two notions are maximally inequivalent in a static (metric) sense -- as they coincide only on a set of states of zero measure. We extend and reinforce quantitatively this inequivalence by addressing the dynamical relation between these types of non-classicality in a paradigmatic quantum-optical setting: the linear mixing at a beam splitter of a single-mode Gaussian state with a thermal reference state. Specifically, we show that almost all P-classical input states generate outputs that are not C-classical. Indeed, for the case of zero thermal reference photons, the more P-classical resources at the input the less C-classicality at the output. In addition, we show that the P-classicality at the input -- as quantified by the non-classical depth -- does instead determine quantitatively the potential of generating output entanglement. This endows the non-classical depth with a new operational interpretation: it gives the maximum number of thermal reference photons that can be mixed at a beam splitter without destroying the output entanglement.

Performance of a Novel Molecular Method in the Diagnosis of Late-Onset Sepsis in Very Low Birth Weight Infants

OBJECTIVE: To compare the use of a generic molecular assay to 'standard' investigations used to assist the diagnosis of late onset bacterial sepsis in very low birth weight infants (VLBW, <1500g).

METHODS: VLBW infants, greater than 48 hours of age, who were clinically suspected to have sepsis were investigated using standard tests (full blood count, C-reactive protein (at presentation) and blood culture), in addition, blood was taken for a universal molecular assay (16S rRNA reverse transcriptase PCR) for comparison. Clinical data were recorded during the suspected infection episode. A validated sepsis score (NEO-KISS) was used to retrospectively determine the presence of sepsis (independent of blood culture). The performance of each of the tests were compared by sensitivity, specificity, positive/negative likihood ratios (+/-LR) and postive/negative predictive values (PPV/NPV).

RESULTS: Sixty-five babies with suspected clinical sepsis were prospectively included. The performance indicators are presented with 95% confidence limits. For the detection of bacteria, blood culture had sensitivity of 0.57 (0.34-0.78), specificity of 0.45 (0.30-0.61); +LR of 1.05 (0.66-1.66) and-LR of 0.94 (0.52-1.7); PPV of 33.3 (18.56-50.97) and NPV of 68.97 (49.17-87.72). Serum CRP had sensitivity of 0.92 (0.64-1) and specificity of 0.36 (0.17-0.59); +LR of 1.45 (1-2.1) and-LR of 0.21 (0.03-1.5); PPV of 44.46 (26.6-66.6) and NPV of 88.9 (51.8-99.7). The universal molecular assay had sensitivity of 0.76 (0.53-0.92), specificity of 0.95 (0.85-0.99); +LR of 16.8 (4.2-66.3) and-LR of 0.25 (0.1-0.5); PPV of 88.9 (65.3-98.6) and NPV of 89.4 (76.9-96.5).

CONCLUSIONS: In VLBW infants this universal molecular assay performed better in the diagnosis of late onset sepsis (LOS) than blood culture and CRP. Further development is required to explore and improve the performance of the assay in real-time diagnosis.

Molecular dynamics simulation (MDS) to study nanoscale machining processes

Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.

Electron-impact ionization of argon using the R-matrix with a pseudo-states method

Electron-impact ionization cross sections for argon are calculated using both non-perturbative R-matrix with pseudo-states (RMPS) and perturbative distorted-wave methods. At twice the ionization potential, the 3p(61)S ground-term cross section from a distorted-wave calculation is found to be a factor of 4 above crossed-beams experimental measurements, while with the inclusion of term-dependent continuum effects in the distorted-wave method, the perturbative cross section still remains almost a factor of 2 above experiment. In the case of ionization from the metastable 3p(5)4s(3)P term, the distorted-wave ionization cross section is also higher than the experimental cross section. On the other hand, the ground-term cross section determined from a nonperturbative RMPS calculation that includes 27 LS spectroscopic terms and another 282 LS pseudo-state terms to represent the high Rydberg states, and the target continuum is found to be in excellent agreement with experimental measurements, while the RMPS result is below the experimental cross section for ionization from the metastable term. We conclude that both continuum term dependence and interchannel coupling effects, which are included in the RMPS method, are important for ionization from the ground term, and interchannel coupling is also significant for ionization from the metastable term

Electron-impact ionization and recombination of M -shell atomic ions in the argon isonuclear sequence

Electron-impact ionization and recombination cross sections and rate coefficients are calculated for M-shell Ar atomic ions using a configuration-average distorted-wave method. The electron-impact ionization calcula- tions are for all atomic ions in the Ar isonuclear sequence. Ionization contributions include both direct ioniza- tion and excitation-autoionization processes. Good agreement is found between theory and experimental crossed-beam measurements for moderately charged ion stages. Comparisons are made with previous theoret- ical calculations where possible.We also generate rate coefficients for neutral argon ionization, based on recent R-matrix with pseudostates calculations. Electron-impact dielectronic recombination is calculated for all M-shell ions of argon. For Ar6+ and Ar7+ the current theoretical results agree well with previous level-resolved distorted-wave calculations. In order to compare with published ionization balance results our dielectronic recombination data are combined with literature values for the higher ion stages and with recent radiative recombination data for all the ion stages. We find significant differences in our equilibrium fractional abun- dances for the M-shell ions, compared with literature values. We relate these differences to the underlying atomic data.

Electron-impact ionization of C+ in both ground and metastable states

Electron-impact ionization cross sections are calculated for the ground and metastable states of C+. Com- parisons between perturbative distorted-wave and nonperturbative time-dependent close-coupling calculations find reductions in the peak direct ionization cross sections due to electron coupling effects of approximately 5% for ground state C+ and approximately 15% for metastable state C+. Fairly small excitation-autoionization contributions are found for ground state C+, while larger excitation-autoionization contributions are found for metastable state C+. Comparisons between perturbative distorted-wave and nonperturbative R-matrix with pseudostates calculations find reductions in the peak total ionization cross sections due to electron coupling effects of approximately 15–20 % for ground state C+ and approximately 25–35 % for metastable state C+. Finally, comparisons between theory and experiment find that present and previous C+ crossed-beam measure- ments are in excellent agreement with ground state nonperturbative R-matrix with pseudostates calculations for total ionization cross sections. Combined with previous non-perturbative calculations for C, C2+, and C3+, accurate ionization cross sections and rate coefficients are now available for the ground and metastable states of all carbon ion stages.

Molecular genomics of a genetic code alteration

The genetic code is not universal. Alterations to its standard form have been discovered in both prokaryotes and eukaryotes and demolished the dogma of an immutable code. For instance, several Candida species translate the standard leucine CUG codon as serine. In the case of the human pathogen Candida albicans, a serine tRNA (tRNACAGSer) incorporates in vivo 97% of serine and 3% of leucine in proteins at CUG sites. Such ambiguity is flexible and the level of leucine incorporation increases significantly in response to environmental stress. To elucidate the function of such ambiguity and clarify whether the identity of the CUG codon could be reverted from serine back to leucine, we have developed a forced evolution strategy to increase leucine incorporation at CUGs and a fluorescent reporter system to monitor such incorporation in vivo. Leucine misincorporation increased from 3% up to nearly 100%, reverting CUG identity from serine back to leucine. Growth assays showed that increasing leucine incorporation produced impressive arrays of phenotypes of high adaptive potential. In particular, strains with high levels of leucine misincorporation exhibited novel phenotypes and high level of tolerance to antifungals. Whole genome re-sequencing revealed that increasing levels of leucine incorporation were associated with accumulation of single nucleotide polymorphisms (SNPs) and loss of heterozygozity (LOH) in the higher misincorporating strains. SNPs accumulated preferentially in genes involved in cell adhesion, filamentous growth and biofilm formation, indicating that C. albicans uses its natural CUG ambiguity to increase genetic diversity in pathogenesis and drug resistance related processes. The overall data provided evidence for unantecipated flexibility of the C. albicans genetic code and highlighted new roles of codon ambiguity on the evolution of genetic and phenotypic diversity.