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Combustion characterization of coal-water slurry fuel
As a result of coal cleaning operations, a substantial amount of coal is disposed as waste into the ponds, effecting and endangering the environment. This study includes a technique to recover and utilize the waste coal fines from the preparation plant effluent streams and tailing ponds. Due to the large moisture content of the recovered coal fines, this investigation is focused on the utilization of coal fines in the coal-water slurry fuel. It is our belief that a blend of plant coal and waste coal fines can be used to produce a coal-water slurry fuel with the desired combustion characteristics required by the industry. The coal blend is composed of 85% clean coal and 15% recovered coal fines. The coal-water slurry is prepared at 60% solids with a viscosity less than 500 centipose and 80-90% of solid particles passing through 200 mesh. This paper contains analysis of clean coal, recovered coal fines, and coal-water slurry fuel as well as combustion characteristics
Analysis on Design and Implementation of 4×10 Gb/s WDM-TDM PON with Disparate Receivers
This article presents a design of wavelength division multiplexing/ Time division Multiplexing (WDM-TDM) in passive optical network with a data rate of 10 Gbps. The implementation has been carried out for varying link distance from 40km to 100km for 4 different wavelengths with a maximum of 32 supporting users with two different receiver photodiodes. The parameters such as BER and the Q-factor for PON network is being analyzed with the link distance. The BER is decreased as the distance of the network is increased when using the APD receivers than PIN receiver. Optimal value of BER is obtained for a distance of 97 Km in APD and 96 Km in pin receiver
Structural phase transitions in yttrium up to 183 GPa
Angle-dispersive x-ray powder diffraction experiments have been performed on yttrium metal up to 183 GPa.We find that the recently discoveredoF16 structure observed in the high-Ztrivalent lanthanides is also adoptedby yttrium above 106 GPa, pressures where it has a superconducting temperature of∼20 K. We have also refinedboth tetragonal and rhombohedral structures against the diffraction data from the preceding “distorted-fcc” phaseand we are unable to state categorically which of these is the true structure of this phase. Finally, analysis ofyttrium’s equation of state reveals a marked change in the compressibility upon adoption of theoF16 structure,after which the compression is that of a “regular” metal. Electronic structure calculations ofoF16-Y confirm itsstability overoF8 structure seen in Nd and Sm, and provide insight into the nature of the shift of orbital characterfromstodunder compression
LoCo: a novel main chain scoring function for protein structure prediction based on local coordinates
From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions
©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein
Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function
Missense mutations in p53 are severely deleterious and occur in over 50% of all human cancers. The majority of these mutations are located in the inherently unstable DNA-binding domain (DBD), many of which destabilize the domain further and expose its aggregation-prone hydrophobic core, prompting self-assembly of mutant p53 into inactive cytosolic amyloid-like aggregates. Screening an oligopyridylamide library, previously shown to inhibit amyloid formation associated with Alzheimer\u2019s disease and type II diabetes, identified a tripyridylamide, ADH-6, that abrogates self-assembly of the aggregation-nucleating subdomain of mutant p53 DBD. Moreover, ADH-6 targets and dissociates mutant p53 aggregates in human cancer cells, which restores p53\u2019s transcriptional activity, leading to cell cycle arrest and apoptosis. Notably, ADH-6 treatment effectively shrinks xenografts harboring mutant p53, while exhibiting no toxicity to healthy tissue, thereby substantially prolonging survival. This study demonstrates the successful application of a bona fide small-molecule amyloid inhibitor as a potent\ua0anticancer agent
Knowledge-based energy functions for computational studies of proteins
This chapter discusses theoretical framework and methods for developing
knowledge-based potential functions essential for protein structure prediction,
protein-protein interaction, and protein sequence design. We discuss in some
details about the Miyazawa-Jernigan contact statistical potential,
distance-dependent statistical potentials, as well as geometric statistical
potentials. We also describe a geometric model for developing both linear and
non-linear potential functions by optimization. Applications of knowledge-based
potential functions in protein-decoy discrimination, in protein-protein
interactions, and in protein design are then described. Several issues of
knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe
Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized
Understanding protein structure is of crucial importance in science, medicine
and biotechnology. For about two decades, knowledge based potentials based on
pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been
center stage in the prediction and design of protein structure and the
simulation of protein folding. However, the validity, scope and limitations of
these potentials are still vigorously debated and disputed, and the optimal
choice of the reference state -- a necessary component of these potentials --
is an unsolved problem. PMFs are loosely justified by analogy to the reversible
work theorem in statistical physics, or by a statistical argument based on a
likelihood function. Both justifications are insightful but leave many
questions unanswered. Here, we show for the first time that PMFs can be seen as
approximations to quantities that do have a rigorous probabilistic
justification: they naturally arise when probability distributions over
different features of proteins need to be combined. We call these quantities
reference ratio distributions deriving from the application of the reference
ratio method. This new view is not only of theoretical relevance, but leads to
many insights that are of direct practical use: the reference state is uniquely
defined and does not require external physical insights; the approach can be
generalized beyond pairwise distances to arbitrary features of protein
structure; and it becomes clear for which purposes the use of these quantities
is justified. We illustrate these insights with two applications, involving the
radius of gyration and hydrogen bonding. In the latter case, we also show how
the reference ratio method can be iteratively applied to sculpt an energy
funnel. Our results considerably increase the understanding and scope of energy
functions derived from known biomolecular structures
Effects of acute cannabidiol on behavior and the endocannabinoid system in HIV-1 Tat transgenic female and male mice
Background: Some evidence suggests that cannabidiol (CBD) has potential to help alleviate HIV symptoms due to its antioxidant and anti-inflammatory properties. Here we examined acute CBD effects on various behaviors and the endocannabinoid system in HIV Tat transgenic mice. Methods: Tat transgenic mice (female/male) were injected with CBD (3, 10, 30 mg/kg) and assessed for antinociception, activity, coordination, anxiety-like behavior, and recognition memory. Brains were taken to quantify endocannabinoids, cannabinoid receptors, and cannabinoid catabolic enzymes. Additionally, CBD and metabolite 7-hydroxy-CBD were quantified in the plasma and cortex. Results: Tat decreased supraspinal-related nociception and locomotion. CBD and sex had little to no effects on any of the behavioral measures. For the endocannabinoid system male sex was associated with elevated concentration of the proinflammatory metabolite arachidonic acid in various CNS regions, including the cerebellum that also showed higher FAAH expression levels for Tat(+) males. GPR55 expression levels in the striatum and cerebellum were higher for females compared to males. CBD metabolism was altered by sex and Tat expression. Conclusion: Findings indicate that acute CBD effects are not altered by HIV Tat, and acute CBD has no to minimal effects on behavior and the endocannabinoid system
On Side-Chain Conformational Entropy of Proteins
The role of side-chain entropy (SCE) in protein folding has long been speculated about but is still not fully understood. Utilizing a newly developed Monte Carlo method, we conducted a systematic investigation of how the SCE relates to the size of the protein and how it differs among a protein's X-ray, NMR, and decoy structures. We estimated the SCE for a set of 675 nonhomologous proteins, and observed that there is a significant SCE for both exposed and buried residues for all these proteins—the contribution of buried residues approaches ∼40% of the overall SCE. Furthermore, the SCE can be quite different for structures with similar compactness or even similar conformations. As a striking example, we found that proteins' X-ray structures appear to pack more “cleverly” than their NMR or decoy counterparts in the sense of retaining higher SCE while achieving comparable compactness, which suggests that the SCE plays an important role in favouring native protein structures. By including a SCE term in a simple free energy function, we can significantly improve the discrimination of native protein structures from decoys
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