957 resultados para Molecular Modeling
Resumo:
Infection with certain types of HPV is a necessary event in the development of cervical carcinoma; however, not all women who become infected will progress. While much is known about the molecular influence of HPV E6 and E7 proteins on the malignant transformation, little is known about the additional factors needed to drive the process. Currently, conventional cervical screening is insufficient at identifying women who are likely to progress from premalignant lesions to carcinoma. Aneuploidy and chromatin texture from image cytometry have been suggested as quantitative measures of nuclear damage in premalignant lesions and cancer, and traditional epidemiologic studies have identified potential factors to aid in the discrimination of those lesions likely to progress. ^ In the current study, real-time PCR was used to quantitate mRNA expression of the E7 gene in women exhibiting normal epithelium, LSIL, and HSIL. Quantitative cytometry was used to gather information about the DNA index and chromatin features of cells from the same women. Logistic regression modeling was used to establish predictor variables for histologic grade based on the traditional epidemiologic risk factors and molecular markers. ^ Prevalence of mRNA transcripts was lower among women with normal histology (27%) than for women with LSIL (40%) and HSIL (37%) with mean levels ranging from 2.0 to 4.2. The transcriptional activity of HPV 18 was higher than that of HPV 16 and increased with increasing level of dysplasia, reinforcing the more aggressive nature of HPV 18. DNA index and mRNA level increased with increasing histological grade. Chromatin score was not correlated with histology but was higher for HPV 18 samples and those with both HPV 18 and HPV 16. However, chromatin score and DNA index were not correlated with mRNA levels. The most predictive variables in the regression modeling were mRNA level, DNA index, parity, and age, and the ROC curves for LSIL and HSIL indicated excellent discrimination. ^ Real-time PCR of viral transcripts could provide a more efficient method to analyze the oncogenic potential within cells from cervical swabs. Epidemiological modeling of malignant progression in the cervix should include molecular markers, as well as the traditional epidemiological risk factors. ^
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Colorectal cancer is the forth most common diagnosed cancer in the United States. Every year about a hundred forty-seven thousand people will be diagnosed with colorectal cancer and fifty-six thousand people lose their lives due to this disease. Most of the hereditary nonpolyposis colorectal cancer (HNPCC) and 12% of the sporadic colorectal cancer show microsatellite instability. Colorectal cancer is a multistep progressive disease. It starts from a mutation in a normal colorectal cell and grows into a clone of cells that further accumulates mutations and finally develops into a malignant tumor. In terms of molecular evolution, the process of colorectal tumor progression represents the acquisition of sequential mutations. ^ Clinical studies use biomarkers such as microsatellite or single nucleotide polymorphisms (SNPs) to study mutation frequencies in colorectal cancer. Microsatellite data obtained from single genome equivalent PCR or small pool PCR can be used to infer tumor progression. Since tumor progression is similar to population evolution, we used an approach known as coalescent, which is well established in population genetics, to analyze this type of data. Coalescent theory has been known to infer the sample's evolutionary path through the analysis of microsatellite data. ^ The simulation results indicate that the constant population size pattern and the rapid tumor growth pattern have different genetic polymorphic patterns. The simulation results were compared with experimental data collected from HNPCC patients. The preliminary result shows the mutation rate in 6 HNPCC patients range from 0.001 to 0.01. The patients' polymorphic patterns are similar to the constant population size pattern which implies the tumor progression is through multilineage persistence instead of clonal sequential evolution. The results should be further verified using a larger dataset. ^
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The cytochromes P450 comprise a superfamily of heme-containing mono-oxygenases. These enzymes metabolize numerous xenobiotics, but also play a role in metabolism of endogenous compounds. The P450 1A1 enzyme generally metabolizes polycyclic aromatic hydrocarbons, and its expression can be induced by aryl hydrocarbon receptor (AhR) activation. CYP1A1 is an exception to the generality that the majority of CYPs demonstrate highest expression in liver; CYP1Al is present in numerous extrahepatic tissues, including brain. This P450 has been observed in two forms, wildtype (WT) and brain variant (BV), arising from alternatively spliced mRNA transcripts. The CYP1A1 BV mRNA presented an exon deletion and was detected in human brain but not liver tissue of the same individuals. ^ Quantitative PCR analyses were performed to determine CYP1A1 WT and BV transcript expression levels in normal, bipolar disorder or schizophrenic groups. In our samples, we show that CYP1A1 BV mRNA, when present, is found alongside the full-length form. Furthermore, we demonstrate a significant decrease in expression of CYP1A1 in patients with bipolar disorder or schizophrenia. The expression level was not influenced by post-mortem interval, tissue pH, age, tobacco use, or lifetime antipsychotic medication load. ^ There is no indication of increased brain CYP1A1 expression in normal smokers versus non-smokers in these samples. We observed slightly increased CYP1A1 expression only in bipolar and schizophrenic smokers versus non-smokers. This may be indicative of complex interactions between neuronal chemical environments and AhR-mediated CYP1A1 induction in brain. ^ Structural homology modeling demonstrated that P450 1A1 BV has several alterations to positions/orientations of substrate recognition site residues compared to the WT isoform. Automated substrate docking was employed to investigate the potential binding of neurological signaling molecules and neurotropic drugs, as well as to differentiate specificities of the two P450 1A1 isoforms. We consistently observed that the BV isoform produced energetically favorable substrate dockings in orientations not observed for the same substrate in the WT isoform. These results demonstrated that structural differences, namely an expanded substrate access channel and active site, confer greater capacity for unique compound docking positions suggesting a metabolic profile distinct from the wildtype form for these test compounds. ^
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Pb17Li is today a reference breeder material in diverse fusion R&D programs worldwide. Extracting dynamic and structural properties of liquid LiPb mixtures via molecular dynamics simulations, represent a crucial step for multiscale modeling efforts in order to understand the suitability of this compound for future Nuclear Fusion technologies. At present a Li-Pb cross potential is not available in the literature. Here we present our first results on the validation of two semi-empirical potentials for Li and Pb in liquid phase. Our results represent the establishment of a solid base as a previous but crucial step to implement a LiPb cross potential. Structural and thermodynamical analyses confirm that the implemented potentials for Li and Pb are realistic to simulate both elements in the liquid phase.
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Pb17Li is today a reference breeder material in diverse fusion R&D programs worldwide. Extracting dynamic and structural properties of liquid LiPb mixtures via molecular dynamics simulations, represent a crucial step for multiscale modeling efforts in order to understand the suitability of this compound for future Nuclear Fusion technologies. At present a Li-Pb cross potential is not available in the literature. Here we present our first results on the validation of two semi-empirical potentials for Li and Pb in liquid phase. Our results represent the establishment of a solid base as a previous but crucial step to implement a LiPb cross potential. Structural and thermodynamical analyses confirm that the implemented potentials for Li and Pb are realistic to simulate both elements in the liquid phase.
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BACKGROUND: Knowledge of pesticide selectivity to natural enemies is necessary for a successful implementation of biological and chemical control methods in integrated pest management (IPM) programs. Diacylhydrazine (DAH)-based ecdysone agonists also known as molting-accelerating compounds (MACs) are considered a selective group of insecticides, and their compatibility with predatory Heteroptera, which are used as biological control agents, is known. However, their molecular mode of action has not been explored in beneficial insects such as Orius laevigatus (Fieber) (Hemiptera: Anthocoridae). RESULTS: In this project in vivo toxicity assays demonstrated that the DAH-based RH-5849, tebufenozide and methoxyfenozide have no toxic effect against O. laevigatus. The ligand-binding domain (LBD) of the ecdysone receptor (EcR) of O. laevigatus was sequenced and a homology protein model was constructed which confirmed a cavity structure with 12 ?-helixes, harboring the natural insect molting hormone 20-hydroxyecdysone. However, docking studies showed that a steric clash occurred for the DAH-based insecticides due to a restricted extent of the ligand-binding cavity of the EcR of O. laevigatus. CONCLUSIONS: The insect toxicity assays demonstrated that MACs are selective for O. laevigatus. The modeling/docking experiments are indications that these pesticides do not bind with the LBD-EcR of O. laevigatus and support that they show no biological effects in the predatory bug. These data help in explaining the compatible use of MACs together with predatory bugs in IPM programs. Keywords: Orius laevigatus, selectivity, diacylhydrazine insecticides, ecdysone receptor, homology modelling, docking studies.
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Irradiation with swift heavy ions (SHI), roughly defined as those having atomic masses larger than 15 and energies exceeding 1 MeV/amu, may lead to significant modification of the irradiated material in a nanometric region around the (straight) ion trajectory (latent tracks). In the case of amorphous silica, SHI irradiation originates nano-tracks of higher density than the virgin material (densification). As a result, the refractive index is increased with respect to that of the surroundings. Moreover, track overlapping leads to continuous amorphous layers that present a significant contrast with respect to the pristine substrate. We have recently demonstrated that SHI irradiation produces a large number of point defects, easily detectable by a number of experimental techniques (work presented in the parallel conference ICDIM). The mechanisms of energy transfer from SHI to the target material have their origin in the high electronic excitation induced in the solid. A number of phenomenological approaches have been employed to describe these mechanisms: coulomb explosion, thermal spike, non-radiative exciton decay, bond weakening. However, a detailed microscopic description is missing due to the difficulty of modeling the time evolution of the electronic excitation. In this work we have employed molecular dynamics (MD) calculations to determine whether the irradiation effects are related to the thermal phenomena described by MD (in the ps domain) or to electronic phenomena (sub-ps domain), e.g., exciton localization. We have carried out simulations of up to 100 ps with large boxes (30x30x8 nm3) using a home-modified version of MDCASK that allows us to define a central hot cylinder (ion track) from which heat flows to the surrounding cold bath (unirradiated sample). We observed that once the cylinder has cooled down, the Si and O coordination numbers are 4 and 2, respectively, as in virgin silica. On the other hand, the density of the (cold) cylinder increases with respect to that of silica and, furthermore, the silica network ring size decreases. Both effects are in agreement with the observed densification. In conclusion, purely thermal effects do not explain the generation of point defects upon irradiation, but they do account for the silica densification.
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Neutrophil gelatinase associated lipocalin (NGAL) protein is attracting a great interest because of its antibacterial properties played upon modulating iron content in competition against iron acquisition processes developed by pathogenic bacteria that bind selective ferric iron chelators (siderophores). Besides its known high affinity to enterobactin, the most important siderophore, it has been recently shown that NGAL is able to bind Fe(III) coordinated by catechols. The selective binding of Fe(III)-catechol ligands to NGAL is here studied by using iron coordination structures with one, two, and three catecholate ligands. By means of a computational approach that consists of B3LYP/6-311G(d,p) quantum calculations for geometries, electron properties and electrostatic potentials of ligands, protein–ligand flexible docking calculations, analyses of protein–ligand interfaces, and Poisson–Boltzmann electrostatic potentials for proteins, we study the binding of iron catecholate ligands to NGAL as a central member of the lipocalin family of proteins. This approach provides a modeling basis for exploring in silico the selective binding of iron catecholates ligands giving a detailed picture of their interactions in terms of electrostatic effects and a network of hydrogen bonds in the protein binding pocket.
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Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD.
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En una planta de fusión, los materiales en contacto con el plasma así como los materiales de primera pared experimentan condiciones particularmente hostiles al estar expuestos a altos flujos de partículas, neutrones y grandes cargas térmicas. Como consecuencia de estas diferentes y complejas condiciones de trabajo, el estudio, desarrollo y diseño de estos materiales es uno de los más importantes retos que ha surgido en los últimos años para la comunidad científica en el campo de los materiales y la energía. Debido a su baja tasa de erosión, alta resistencia al sputtering, alta conductividad térmica, muy alto punto de fusión y baja retención de tritio, el tungsteno (wolframio) es un importante candidato como material de primera pared y como posible material estructural avanzado en fusión por confinamiento magnético e inercial. Sin embargo, el tiempo de vida del tungsteno viene controlado por diversos factores como son su respuesta termo-mecánica en la superficie, la posibilidad de fusión y el fallo por acumulación de helio. Es por ello que el tiempo de vida limitado por la respuesta mecánica del tungsteno (W), y en particular su fragilidad, sean dos importantes aspectos que tienes que ser investigados. El comportamiento plástico en materiales refractarios con estructura cristalina cúbica centrada en las caras (bcc) como el tungsteno está gobernado por las dislocaciones de tipo tornillo a escala atómica y por conjuntos e interacciones de dislocaciones a escalas más grandes. El modelado de este complejo comportamiento requiere la aplicación de métodos capaces de resolver de forma rigurosa cada una de las escalas. El trabajo que se presenta en esta tesis propone un modelado multiescala que es capaz de dar respuestas ingenieriles a las solicitudes técnicas del tungsteno, y que a su vez está apoyado por la rigurosa física subyacente a extensas simulaciones atomísticas. En primer lugar, las propiedades estáticas y dinámicas de las dislocaciones de tipo tornillo en cinco potenciales interatómicos de tungsteno son comparadas, determinando cuáles de ellos garantizan una mayor fidelidad física y eficiencia computacional. Las grandes tasas de deformación asociadas a las técnicas de dinámica molecular hacen que las funciones de movilidad de las dislocaciones obtenidas no puedan ser utilizadas en los siguientes pasos del modelado multiescala. En este trabajo, proponemos dos métodos alternativos para obtener las funciones de movilidad de las dislocaciones: un modelo Monte Cario cinético y expresiones analíticas. El conjunto de parámetros necesarios para formular el modelo de Monte Cario cinético y la ley de movilidad analítica son calculados atomísticamente. Estos parámetros incluyen, pero no se limitan a: la determinación de las entalpias y energías de formación de las parejas de escalones que forman las dislocaciones, la parametrización de los efectos de no Schmid característicos en materiales bcc,etc. Conociendo la ley de movilidad de las dislocaciones en función del esfuerzo aplicado y la temperatura, se introduce esta relación como ecuación de flujo dentro de un modelo de plasticidad cristalina. La predicción del modelo sobre la dependencia del límite de fluencia con la temperatura es validada experimentalmente con ensayos uniaxiales en tungsteno monocristalino. A continuación, se calcula el límite de fluencia al aplicar ensayos uniaxiales de tensión para un conjunto de orientaciones cristalográticas dentro del triángulo estándar variando la tasa de deformación y la temperatura de los ensayos. Finalmente, y con el objetivo de ser capaces de predecir una respuesta más dúctil del tungsteno para una variedad de estados de carga, se realizan ensayos biaxiales de tensión sobre algunas de las orientaciones cristalográficas ya estudiadas en función de la temperatura.-------------------------------------------------------------------------ABSTRACT ----------------------------------------------------------Tungsten and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield and low longterm disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, mostly associated with inter-granular failure and bulk plasticity, that limits its applications. As a result of these various and complex conditions of work, the study, development and design of these materials is one of the most important challenges that have emerged in recent years to the scientific community in the field of materials for energy applications. The plastic behavior of body-centered cubic (bcc) refractory metals like tungsten is governed by the kink-pair mediated thermally activated motion of h¿ (\1 11)i screw dislocations on the atomistic scale and by ensembles and interactions of dislocations at larger scales. Modeling this complex behavior requires the application of methods capable of resolving rigorously each relevant scale. The work presented in this thesis proposes a multiscale model approach that gives engineering-level responses to the technical specifications required for the use of tungsten in fusion energy reactors, and it is also supported by the rigorous underlying physics of extensive atomistic simulations. First, the static and dynamic properties of screw dislocations in five interatomic potentials for tungsten are compared, determining which of these ensure greater physical fidelity and computational efficiency. The large strain rates associated with molecular dynamics techniques make the dislocation mobility functions obtained not suitable to be used in the next steps of the multiscale model. Therefore, it is necessary to employ mobility laws obtained from a different method. In this work, we suggest two alternative methods to get the dislocation mobility functions: a kinetic Monte Carlo model and analytical expressions. The set of parameters needed to formulate the kinetic Monte Carlo model and the analytical mobility law are calculated atomistically. These parameters include, but are not limited to: enthalpy and energy barriers of kink-pairs as a function of the stress, width of the kink-pairs, non-Schmid effects ( both twinning-antitwinning asymmetry and non-glide stresses), etc. The function relating dislocation velocity with applied stress and temperature is used as the main source of constitutive information into a dislocation-based crystal plasticity framework. We validate the dependence of the yield strength with the temperature predicted by the model against existing experimental data of tensile tests in singlecrystal tungsten, with excellent agreement between the simulations and the measured data. We then extend the model to a number of crystallographic orientations uniformly distributed in the standard triangle and study the effects of temperature and strain rate. Finally, we perform biaxial tensile tests and provide the yield surface as a function of the temperature for some of the crystallographic orientations explored in the uniaxial tensile tests.
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A central event in the eukaryotic cell cycle is the decision to commence DNA replication (S phase). Strict controls normally operate to prevent repeated rounds of DNA replication without intervening mitoses (“endoreplication”) or initiation of mitosis before DNA is fully replicated (“mitotic catastrophe”). Some of the genetic interactions involved in these controls have recently been identified in yeast. From this evidence we propose a molecular mechanism of “Start” control in Schizosaccharomyces pombe. Using established principles of biochemical kinetics, we compare the properties of this model in detail with the observed behavior of various mutant strains of fission yeast: wee1− (size control at Start), cdc13Δ and rum1OP (endoreplication), and wee1− rum1Δ (rapid division cycles of diminishing cell size). We discuss essential features of the mechanism that are responsible for characteristic properties of Start control in fission yeast, to expose our proposal to crucial experimental tests.
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Catalysis at organophilic silica-rich surfaces of zeolites and feldspars might generate replicating biopolymers from simple chemicals supplied by meteorites, volcanic gases, and other geological sources. Crystal–chemical modeling yielded packings for amino acids neatly encapsulated in 10-ring channels of the molecular sieve silicalite-ZSM-5-(mutinaite). Calculation of binding and activation energies for catalytic assembly into polymers is progressing for a chemical composition with one catalytic Al–OH site per 25 neutral Si tetrahedral sites. Internal channel intersections and external terminations provide special stereochemical features suitable for complex organic species. Polymer migration along nano/micrometer channels of ancient weathered feldspars, plus exploitation of phosphorus and various transition metals in entrapped apatite and other microminerals, might have generated complexes of replicating catalytic biomolecules, leading to primitive cellular organisms. The first cell wall might have been an internal mineral surface, from which the cell developed a protective biological cap emerging into a nutrient-rich “soup.” Ultimately, the biological cap might have expanded into a complete cell wall, allowing mobility and colonization of energy-rich challenging environments. Electron microscopy of honeycomb channels inside weathered feldspars of the Shap granite (northwest England) has revealed modern bacteria, perhaps indicative of Archean ones. All known early rocks were metamorphosed too highly during geologic time to permit simple survival of large-pore zeolites, honeycombed feldspar, and encapsulated species. Possible microscopic clues to the proposed mineral adsorbents/catalysts are discussed for planning of systematic study of black cherts from weakly metamorphosed Archaean sediments.
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This computer simulation is based on a model of the origin of life proposed by H. Kuhn and J. Waser, where the evolution of short molecular strands is assumed to take place in a distinct spatiotemporal structured environment. In their model, the prebiotic situation is strongly simplified to grasp essential features of the evolution of the genetic apparatus without attempts to trace the historic path. With the tool of computer implementation confining to principle aspects and focused on critical features of the model, a deeper understanding of the model's premises is achieved. Each generation consists of three steps: (i) construction of devices (entities exposed to selection) presently available; (ii) selection; and (iii) multiplication of the isolated strands (R oligomers) by complementary copying with occasional variation by copying mismatch. In the beginning, the devices are single strands with random sequences; later, increasingly complex aggregates of strands form devices such as a hairpin-assembler device which develop in favorable cases. A monomers interlink by binding to the hairpin-assembler device, and a translation machinery, called the hairpin-assembler-enzyme device, emerges, which translates the sequence of R1 and R2 monomers in the assembler strand to the sequence of A1 and A2 monomers in the A oligomer, working as an enzyme.
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Population balances of polymer species in terms 'of discrete transforms with respect to counts of groups lead to tractable first order partial differential equations when ali rate constants are independent of chain length and loop formation is negligible [l]. Average molecular weights in the absence ofgelation are long known to be readily found through integration of an initial value problem. The extension to size distribution prediction is also feasible, but its performance is often lower to the one provided by methods based upon real chain length domain [2]. Moreover, the absence ofagood starting procedure and a higher numerical sensitivity hás decisively impaired its application to non-linear reversibly deactivated polymerizations, namely NMRP [3].
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Adsorption of nitrogen in spherical pores of FDU-1 silica at 77 K is considered by means of a nonlocal density functional theory (NLDFT) accounting for a disordered structure of pore walls. Pore size distribution analysis of various FDU-1 samples subject to different temperatures of calcination revealed three distinct groups of pores. The principal group of pores is identified as ordered spherical mesopores connected with each other by smaller interconnecting pores and irregular micropores present in the mesopore walls. To account for the entrances (connecting pores) into spherical mesopores, a concept of solid mass distribution with respect to the apparent density was introduced. It is shown that the introduction of the aforementioned distribution was sufficient to quantitatively describe experimental adsorption isotherms over the entire range of relative pressures spanning six decades.