Nanoparticle–electrode collisions as a dynamic seeding route for the growth of metallic nanostructures

The collisions between colloidal metal nanoparticles and a carbon electrode were explored as a dynamic method for the electrodeposition of a diverse range of electrocatalytically active Ag and Au nanostructures whose morphology is dominated by the electrostatic interaction between the charge of the nanoparticle and metal salt.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Catalytic activity evaluation of industrial Pd/C catalyst via gray-box dynamic modeling and simulation of hydropurification reactor

In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

Computational micromodel for epigenetic mechanisms

Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of histone modifications and DNA methylation. These dynamic elements interact to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing imbalance that can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in gene expression and investigate their intrinsic interdependency. In this paper, we explore the relation between DNA methylation and transcription and characterize in detail the histone modifications for specific DNA methylation levels using a stochastic approach.

Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer

Epigenetic changes correspond to heritable modifications of the chromatin structure, which do not involve any alteration of the DNA sequence but nonetheless affect gene expression. These mechanisms play an important role in cell differentiation, but aberrant occurrences are also associated with a number of diseases, including cancer and neural development disorders. In particular, aberrant DNA methylation induced by H. Pylori has been found to be a significant risk factor in gastric cancer. To investigate the sensitivity of different genes and cell types to this infection, a computational model of methylation in gastric crypts is developed. In this article, we review existing results from physical experiments and outline their limitations, before presenting the computational model and investigating the influence of its parameters.

Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Watermarking capacity control for dynamic payload embedding

Despite significant improvements in capacity-distortion performance, a computationally efficient capacity control is still lacking in the recent watermarking schemes. In this paper, we propose an efficient capacity control framework to substantiate the notion of watermarking capacity control to be the process of maintaining “acceptable” distortion and running time, while attaining the required capacity. The necessary analysis and experimental results on the capacity control are reported to address practical aspects of the watermarking capacity problem, in dynamic (size) payload embedding.

DNA molecules and future blockbuster therapeutics

Deoxyribonucleic acid molecules are heralding a new generation of reverse - engineered biopharmaceuticals. In terms of potential application in gene medicine, plasmid DNA (pDNA) vectors have exceptional therapeutic and immunological profiles as they are free from safety concerns associated with viral vectors, display non-toxicity and are simpler to develop. This presentation will discuss the potential applications of pDNA molecules in vaccine development and gene therapy, pilot-scale production of pDNA-based biopharmaceuticals and the controlled delivery of therapeutic sequences in biodegradable polymers to different target cells via the nasal route.

Dynamic input to determine hip joint moments, power and work on the prosthetic limb of transfemoral amputees: ground reactions vs knee reactions

Study Design: Comparative analysis Background: Calculations of lower limbs kinetics are limited by floor-mounted force-plates. Objectives: Comparison of hip joint moments, power and mechanical work on the prosthetic limb of a transfemoral amputee calculated by inverse dynamics using either the ground reactions (force-plates) or knee reactions (transducer). Methods: Kinematics, ground reactions and knee reactions were collected using a motion analysis system, two force-plates and a multi-axial transducer mounted below the socket, respectively. Results: The inverse dynamics using ground reactions under-estimated the peaks of hip energy generation and absorption occurring at 63 % and 76 % of the gait cycle (GC) by 28 % and 54 %, respectively. This method over-estimated a phase of negative work at the hip (from 37 %GC to 56 %GC) by 24%. It under-estimated the phases of positive (from 57 %GC to 72 %GC) and negative (from 73 %GC to 98 %GC) work at the hip by 11 % and 58%, respectively. Conclusions: A transducer mounted within the prosthesis has the capacity to provide more realistic kinetics of the prosthetic limb because it enables assessment of multiple consecutive steps and a wide range of activities without issues of foot placement on force-plates. CLINICAL RELEVANCE The hip is the only joint that an amputee controls directly to set in motion the prosthesis. Hip joint kinetics are associated with joint degeneration, low back pain, risks of fall, etc. Therefore, realistic assessment of hip kinetics over multiple gait cycles and a wide range of activities is essential.

The molecular structure of kaolinite–potassium acetate intercalation complexes: A combined experimental and molecular dynamic simulation study

The kaolinite (Kaol) intercalated with potassium acetate (Ac) was prepared and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetry. Molecular dynamic simulation was performed to investigate the structure of Kaol–Ac intercalation complex and the hydrogen bonds between Kaol and intercalated Ac andwater using INTERFACE forcefield. The acetate anions andwater arranged in a bilayer structure in the interlayer space of Kaol. The potassium cations distributed in the interlayer space and strongly coordinated with acetate anions aswell aswater rather than keyed into the ditrigonal holes of tetrahedral surface of Kaol. Strong hydrogen bonds formed between the hydrogen atoms of hydroxyl on the octahedral surface and oxygen atoms of both acetate anions and water. The acetate anions andwater also weakly bonded hydrogen to the silica tetrahedral surface through their hydrogen atoms with the oxygen atoms of silica tetrahedral surface.

Mechanisms of cisplatin resistance: DNA repair and cellular implications

Cisplatin (cis-diamminedichloroplatinum (II)), is a platinum based chemotherapeutic employed in the clinic to treat patients with lung, ovarian, colorectal or head and neck cancers. Cisplatin acts to induce tumor cell death via multiple mechanisms. The best characterized mode of action is through irreversible DNA cross-links which activate DNA damage signals leading to cell death via the intrinsic mitochondrial apoptosis pathway. However, the primary issue with cisplatin is that while patients initially respond favorably, sustained cisplatin therapy often yields chemoresistance resulting in therapeutic failure. In this chapter, we review the DNA damage and repair pathways that contribute to cisplatin resistance. We also examine the cellular implications of cisplatin resistance that may lead to selection of subpopulations of cells within a tumor. In better understanding the mechanisms conferring cisplatin resistance, novel targets may be identified to restore drug sensitivity.

BRCA1 deficiency exacerbates estrogen-induced DNA damage and genomic instability

Germline mutations in BRCA1 predispose carriers to a high incidence of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through critical roles in DNA repair, cell cycle arrest and transcriptional control. A major question has been why BRCA1 loss or mutation leads to tumors mainly in estrogen-regulated tissues, given that BRCA1 has essential functions in all cell types. Here we report that estrogen and estrogen metabolites can cause DNA double strand breaks (DSB) in estrogen receptor-α negative breast cells and that BRCA1 is required to repair these DSBs to prevent metabolite-induced genomic instability. We found that BRCA1 also regulates estrogen metabolism and metabolite-mediated DNA damage by repressing the transcription of estrogen-metabolising enzymes, such as CYP1A1, in breast cells. Lastly, we used a knock-in human cell model with a heterozygous BRCA1 pathogenic mutation to show how BRCA1 haploinsufficiency affects these processes. Our findings provide pivotal new insights into why BRCA1 mutation drives the formation of tumours in estrogen-regulated tissues, despite the general role of BRCA1 in DNA repair in all cell types.

The role of DNA repair pathways in cisplatin resistant lung cancer

Platinum chemotherapeutic agents such as cisplatin are currently used in the treatment of various malignancies such as lung cancer. However, their efficacy is significantly hindered by the development of resistance during treatment. While a number of factors have been reported that contribute to the onset of this resistance phenotype, alterations in the DNA repair capacity of damaged cells is now recognised as an important factor in mediating this phenomenon. The mode of action of cisplatin has been linked to its ability to crosslink purine bases on the DNA, thereby interfering with DNA repair mechanisms and inducing DNA damage. Following DNA damage, cells respond by activating a DNA-damage response that either leads to repair of the lesion by the cell thereby promoting resistance to the drug, or cell death via activation of the apoptotic response. Therefore, DNA repair is a vital target to improving cancer therapy and reduce the resistance of tumour cells to DNA damaging agents currently used in the treatment of cancer patients. To date, despite the numerous findings that differential expression of components of the various DNA repair pathways correlate with response to cisplatin, translation of such findings in the clinical setting are still warranted. The identification of alterations in specific proteins and pathways that contribute to these unique DNA repair pathways in cisplatin resistant cancer cells may potentially lead to a renewed interest in the development of rational novel therapies for cisplatin resistant cancers, in particular, lung cancer.

Identification of a BRCA1-mRNA splicing complex required for efficient DNA repair and maintenance of genomic stability

Mutations within BRCA1 predispose carriers to a high risk of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through the assembly of multiple protein complexes involved in DNA repair, cell-cycle arrest, and transcriptional regulation. Here, we report the identification of a DNA damage-induced BRCA1 protein complex containing BCLAF1 and other key components of the mRNA-splicing machinery. In response to DNA damage, this complex regulates pre-mRNA splicing of a number of genes involved in DNA damage signaling and repair, thereby promoting the stability of these transcripts/proteins. Further, we show that abrogation of this complex results in sensitivity to DNA damage, defective DNA repair, and genomic instability. Interestingly, mutations in a number of proteins found within this complex have been identified in numerous cancer types. These data suggest that regulation of splicing by the BRCA1-mRNA splicing complex plays an important role in the cellular response to DNA damage.

The structural basis of DNA binding by the single-stranded DNA-binding protein from Sulfolobus solfataricus

Canonical single-stranded DNA-binding proteins (SSBs) from the oligosaccharide/oligonucleotide-binding (OB) domain family are present in all known organisms and are critical for DNA replication, recombination and repair. The SSB from the hyperthermophilic crenarchaeote Sulfolobus solfataricus (SsoSSB) has a ‘simple’ domain organization consisting of a single DNA-binding OB fold coupled to a flexible C-terminal tail, in contrast with other SSBs in this family that incorporate up to four OB domains. Despite the large differences in the domain organization within the SSB family, the structure of the OB domain is remarkably similar all cellular life forms. However, there are significant differences in the molecular mechanism of ssDNA binding. We have determined the structure of the SsoSSB OB domain bound to ssDNA by NMR spectroscopy. We reveal that ssDNA recognition is modulated by base-stacking of three key aromatic residues, in contrast with the OB domains of human RPA and the recently discovered human homologue of SsoSSB, hSSB1. We also demonstrate that SsoSSB binds ssDNA with a footprint of five bases and with a defined binding polarity. These data elucidate the structural basis of DNA binding and shed light on the molecular mechanism by which these ‘simple’ SSBs interact with ssDNA.