다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

The thermodynamic properties of 154 mineral end-members, 13 silicate liquid end-members and 22 aqueous fluid species are presented in a revised and updated data set. The use of a temperature-dependent thermal expansion and bulk modulus, and the use of high-pressure equations of state for solids and fluids, allows calculation of mineral–fluid equilibria to 100 kbar pressure or higher. A pressure-dependent Landau model for order–disorder permits extension of disordering transitions to high pressures, and, in particular, allows the alpha–beta quartz transition to be handled more satisfactorily. Several melt end-members have been included to enable calculation of simple phase equilibria and as a first stage in developing melt mixing models in NCKFMASH. The simple aqueous species density model has been extended to enable speciation calculations and mineral solubility determination involving minerals and aqueous species at high temperatures and pressures. The data set has also been improved by incorporation of many new phase equilibrium constraints, calorimetric studies and new measurements of molar volume, thermal expansion and compressibility. This has led to a significant improvement in the level of agreement with the available experimental phase equilibria, and to greater flexibility in calculation of complex mineral equilibria. It is also shown that there is very good agreement between the data set and the most recent available calorimetric data.

An internally consistent thermodynamic data set for phases of petrological interest

The thermodynamic properties of 154 mineral end-members, 13 silicate liquid end-members and 22 aqueous fluid species are presented in a revised and updated data set. The use of a temperature-dependent thermal expansion and bulk modulus, and the use of high-pressure equations of state for solids and fluids, allows calculation of mineral-fluid equilibria to 100 kbar pressure or higher. A pressure-dependent Landau model for order-disorder permits extension of disordering transitions to high pressures, and, in particular, allows the alpha-beta quartz transition to be handled more satisfactorily. Several melt end- members have been included to enable calculation of simple phase equilibria and as a first stage in developing melt mixing models in NCKFMASH. The simple aqueous species density model has been extended to enable speciation calculations and mineral solubility determination involving minerals and aqueous species at high temperatures and pressures. The data set has also been improved by incorporation of many new phase equilibrium constraints, calorimetric studies and new measurements of molar volume, thermal expansion and compressibility. This has led to a significant improvement in the level of agreement with the available experimental phase equilibria, and to greater flexibility in calculation of complex mineral equilibria. It is also shown that there is very good agreement between the data set and the most recent available calorimetric data. kinetics which apply to determining directly the greatest majority of such equilibria in the laboratory, for forming solid solutions, and inclusion of aqueous and silicate melt species), and provides uncertainties especially at lower temperatures, as well as the diYculty of establishing reversals of reactions involving solid allowing the likely uncertainties on the results of thermodynamic calculations to be estimated. This is a solutions. The levels of precision and accuracy required of thermodynamic data in order to be able to forward- critical issue in that calculations using data sets should always involve uncertainty propagation to help evalu- model synthetic and natural mineral assemblages mean that the continuing upgrading and expansion of the ate the results. Because the experimental phase equilib- ria involve overlapping subsets of compositional space, data set by incorporation of new phase equilibrium constraints, calorimetry and new measurements of the derived thermodynamic data are highly correlated, and it is only the inclusion of the correlations which molar volume, thermal expansion and compressibility are more than justified. enables the reliable calculation of uncertainties on mineral reactions to be performed. Earlier work on mineral thermodynamic data sets for rock-forming minerals includes compilations of The thermodynamic data extraction involves using weighted least squares on the diVerent types of data

Escherichia coli is the organism of choice for the production of recombinant proteins. Its use as a cell factory is well-established and it has become the most popular expression platform. For this reason, there are many molecular tools and protocols at hand for the high-level production of recombinant proteins, such as a vast catalog of expression plasmids, a great number of engineered strains and many cultivation strategies. We review the different approaches for the synthesis of recombinant proteins in E. coli and discuss recent progress in this ever-growing field.

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Recombinant protein expression in Escherichia coli: advances and challenges.

The thermodynamic properties of 254 end-members, including 210 mineral end-members, 18 silicate liquid end-members and 26 aqueous fluid species are presented in a revised and updated internally consistent thermodynamic data set. The PVT properties of the data set phases are now based on a modified Tait equation of state (EOS) for the solids and the Pitzer & Sterner (1995) equation for gaseous components. Thermal expansion and compressibility are linked within the modified Tait EOS (TEOS) by a thermal pressure formulation using an Einstein temperature to model the temperature dependence of both the thermal expansion and bulk modulus in a consistent way. The new EOS has led to improved fitting of the phase equilibrium experiments. Many new end-members have been added, including several deep mantle phases and, for the first time, sulphur-bearing minerals. Silicate liquid end-members are in good agreement with both phase equilibrium experiments and measured heat of melting. The new dataset considerably enhances the capabilities for thermodynamic calculation on rocks, melts and aqueous fluids under crustal to deep mantle conditions. Implementations are already available in thermocalc to take advantage of the new data set and its methodologies, as illustrated by example calculations on sapphirine-bearing equilibria, sulphur-bearing equilibria and calculations to 300 kbar and 2000 °C to extend to lower mantle conditions.

An improved and extended internally consistent thermodynamic dataset for phases of petrological interest, involving a new equation of state for solids

A new classification and nomenclature scheme for the amphibole-supergroup minerals is described, based on the general formula AB 2 C 5 T 8 O 22 W 2 , where A = □, Na, K, Ca, Pb, Li; B = Na, Ca, Mn 2+ , Fe 2+ , Mg, Li; C = Mg, Fe 2+ , Mn 2+ , Al, Fe 3+ , Mn 3+ , Ti 4+ , Li; T = Si, Al, Ti 4+ , Be; W = (OH), F, Cl, O 2− . Distinct arrangements of formal charges at the sites (or groups of sites) in the amphibole structure warrant distinct root names , and are, by implication, distinct species; for a specific root name, different homovalent cations (e.g., Mg vs. Fe 2+ ) or anions (e.g., OH vs. F) are indicated by prefixes (e.g., ferro-, fluoro-). The classification is based on the A, B, and C groups of cations and the W group of anions, as these groups show the maximum compositional variability in the amphibole structure. The amphibole supergroup is divided into two groups according to the dominant W species: W (OH,F,Cl)-dominant amphiboles and W O-dominant amphiboles (oxo-amphiboles). Amphiboles with (OH, F, Cl) dominant at W are divided into eight subgroups according to the dominant charge-arrangements and type of B-group cations: magnesium-iron-manganese amphiboles, calcium amphiboles, sodium-calcium amphiboles, sodium amphiboles, lithium amphiboles, sodium-(magnesium-iron-manganese) amphiboles, lithium-(magnesium-iron-manganese) amphiboles and lithium-calcium amphiboles. Within each of these subgroups, the A- and C-group cations are used to assign specific names to specific compositional ranges and root compositions. Root names are assigned to distinct arrangements of formal charges at the sites, and prefixes are assigned to describe homovalent variation in the dominant ion of the root composition. For amphiboles with O dominant at W, distinct root-compositions are currently known for four (calcium and sodium) amphiboles, and homovalent variation in the dominant cation is handled as for the W (OH,F,Cl)-dominant amphiboles. With this classification, we attempt to recognize the concerns of each constituent community interested in amphiboles and incorporate these into this classification scheme. Where such concerns conflict, we have attempted to act in accord with the more important concerns of each community.

Nomenclature of the amphibole supergroup

Background: Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles. Principal Findings: To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well. Conclusion: The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system.

/pdf/design-parameters-to-control-synthetic-gene-expression-in-4mmotanae1.pdf

Design Parameters to Control Synthetic Gene Expression in Escherichia coli

Engineering genes for predictable protein expression.

Methods for sensing test stimuli using arrays of biopolymers are provided. Libraries of biopolymers, such nucleic acid variants, and expression products encoded by nucleic acid variants are provided. Reusable library arrays, and methods for their use are provided.

Biosensors, reagents and diagnostic applications of directed evolution

On the basis of extensive studies of synthetic perovskite-structured compounds it is possible to derive a hierarchy of hettotype structures which are derivatives of the arisotypic cubic perovskite structure ( ABX 3 ), exemplified by SrTiO 3 (tausonite) or KMgF 3 (parascandolaite) by: (1) tilting and distortion of the BX 6 octahedra; (2) ordering of A- and B -site cations; (3) formation of A -, B - or X -site vacancies. This hierarchical scheme can be applied to some naturally-occurring oxides, fluorides, hydroxides, chlorides, arsenides, intermetallic compounds and silicates which adopt such derivative crystal structures. Application of this hierarchical scheme to naturally-occurring minerals results in the recognition of a perovskite supergroup which is divided into stoichiometric and non-stoichiometric perovskite groups, with both groups further divided into single ABX 3 or double A 2 BB ʹ X 6 perovskites. Subgroups, and potential subgroups, of stoichiometric perovskites include: (1) silicate single perovskites of the bridgmanite subgroup; (2) oxide single perovskites of the perovskite subgroup (tausonite, perovskite, loparite, lueshite, isolueshite, lakargiite, megawite); (3) oxide single perovskites of the macedonite subgroup which exhibit second order Jahn-Teller distortions (macedonite, barioperovskite); (4) fluoride single perovskites of the neighborite subgroup (neighborite, parascandolaite); (5) chloride single perovskites of the chlorocalcite subgroup; (6) B- site cation ordered double fluoride perovskites of the cryolite subgroup (cryolite, elpasolite, simmonsite); (7) B- site cation ordered oxide double perovskites of the vapnikite subgroup [vapnikite, (?) latrappite]. Non-stoichiometric perovskites include: (1) A- site vacant double hydroxides, or hydroxide perovskites, belonging to the sohngeite, schoenfliesite and stottite subgroups; (2) Anion-deficient perovskites of the brownmillerite subgroup (srebrodolskite, shulamitite); (3) A- site vacant quadruple perovskites (skutterudite subgroup); (4) B -site vacant single perovskites of the oskarssonite subgroup [oskarssonite]; (5) B -site vacant inverse single perovskites of the cohenite and auricupride subgroups; (6) B -site vacant double perovskites of the diaboleite subgroup; (7) anion-deficient partly-inverse B -site quadruple perovskites of the hematophanite subgroup.

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Mark D. Welch

Papers

Nomenclature of the amphibole supergroup

Design Parameters to Control Synthetic Gene Expression in Escherichia coli

Engineering genes for predictable protein expression.

Biosensors, reagents and diagnostic applications of directed evolution

Nomenclature of the perovskite supergroup: A hierarchical system of classification based on crystal structure and composition