20,400 research outputs found
DNA mismatch binding and antiproliferative activity of rhodium metalloinsertors
Deficiencies in mismatch repair (MMR) are associated with carcinogenesis. Rhodium metalloinsertors bind to DNA base mismatches with high specificity and inhibit cellular proliferation preferentially in MMR-deficient cells versus MMR-proficient cells. A family of chrysenequinone diimine complexes of rhodium with varying ancillary ligands that serve as DNA metalloinsertors has been synthesized, and both DNA mismatch binding affinities and antiproliferative activities against the human colorectal carcinoma cell lines HCT116N and HCT116O, an isogenic model system for MMR deficiency, have been determined. DNA photocleavage experiments reveal that all complexes bind to the mismatch sites with high specificities; DNA binding affinities to oligonucleotides containing single base CA and CC mismatches, obtained through photocleavage titration or competition, vary from 10^4 to 10^8 M^−1 for the series of complexes. Significantly, binding affinities are found to be inversely related to ancillary ligand size and directly related to differential inhibition of the HCT116 cell lines. The observed trend in binding affinity is consistent with the metalloinsertion mode where the complex binds from the minor groove with ejection of mismatched base pairs. The correlation between binding affinity and targeting of the MMR-deficient cell line suggests that rhodium metalloinsertors exert their selective biological effects on MMR-deficient cells through mismatch binding in vivo
Design principles of hardware-based phong shading and bump-mapping
The VISA+ hardware architecture is the first of a new generation of graphics accelerators designed primarily to render bump-, texture-, environment- and environment-bump-mapped polygons. This paper presents examples of the main graphical capabilities and discusses methods and simplifications used to create high quality images. One of the key concepts in the VISA+ design, the use of reflectance cubes, is predestined for environment mapping. In combination with bump- and texture-mapping it shows the strength of our new architecture. Furthermore it justifies some of the decisions made during simulation and development of the complex VISA+ architecture
Exploring the cellular accumulation of metal complexes
Transition metal complexes offer great potential as diagnostic and therapeutic agents, and a growing number of biological applications have been explored. To be effective, these complexes must reach their intended target inside the cell. Here we review the cellular accumulation of metal complexes, including their uptake, localization, and efflux. Metal complexes are taken up inside cells through various mechanisms, including passive diffusion and entry through organic and metal transporters. Emphasis is placed on the methods used to examine cellular accumulation, to identify the mechanism(s) of uptake, and to monitor possible efflux. Conjugation strategies that have been employed to improve the cellular uptake characteristics of metal complexes are also described
Selective Cytotoxicity of Rhodium Metalloinsertors in Mismatch Repair-Deficient Cells
Mismatches in DNA occur naturally during replication and as a result of endogenous DNA damaging agents, but the mismatch repair (MMR) pathway acts to correct mismatches before subsequent rounds of replication. Rhodium metalloinsertors bind to DNA mismatches with high affinity and specificity and represent a promising strategy to target mismatches in cells. Here we examine the biological fate of rhodium metalloinsertors bearing dipyridylamine ancillary ligands in cells deficient in MMR versus those that are MMR-proficient. These complexes are shown to exhibit accelerated cellular uptake which permits the observation of various cellular responses, including disruption of the cell cycle, monitored by flow cytometry assays, and induction of necrosis, monitored by dye exclusion and caspase inhibition assays, that occur preferentially in the MMR-deficient cell line. These cellular responses provide insight into the mechanisms underlying the selective activity of this novel class of targeted anticancer agents
Learning Dynamic Boltzmann Distributions as Reduced Models of Spatial Chemical Kinetics
Finding reduced models of spatially-distributed chemical reaction networks
requires an estimation of which effective dynamics are relevant. We propose a
machine learning approach to this coarse graining problem, where a maximum
entropy approximation is constructed that evolves slowly in time. The dynamical
model governing the approximation is expressed as a functional, allowing a
general treatment of spatial interactions. In contrast to typical machine
learning approaches which estimate the interaction parameters of a graphical
model, we derive Boltzmann-machine like learning algorithms to estimate
directly the functionals dictating the time evolution of these parameters. By
incorporating analytic solutions from simple reaction motifs, an efficient
simulation method is demonstrated for systems ranging from toy problems to
basic biologically relevant networks. The broadly applicable nature of our
approach to learning spatial dynamics suggests promising applications to
multiscale methods for spatial networks, as well as to further problems in
machine learning
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