An advanced implicit meshless approach for fractional partial differential equation in computational mechanics

Recently, the numerical modelling and simulation for fractional partial differential equations (FPDE), which have been found with widely applications in modern engineering and sciences, are attracting increased attentions. The current dominant numerical method for modelling of FPDE is the explicit Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings. This paper aims to develop an implicit meshless approach based on the radial basis functions (RBF) for numerical simulation of time fractional diffusion equations. The discrete system of equations is obtained by using the RBF meshless shape functions and the strong-forms. The stability and convergence of this meshless approach are then discussed and theoretically proven. Several numerical examples with different problem domains are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. The results obtained by the meshless formations are also compared with those obtained by FDM in terms of their accuracy and efficiency. It is concluded that the present meshless formulation is very effective for the modelling and simulation for FPDE.

Identification of novel markers for uncomplicated lower genital tract infections and upper genital tract pathology due to Chlamydia trachomatis.

Background: Untreated Chlamydia trachomatis infections in women can result in disease sequelae such as salpingitis and pelvic inflammatory disease (PID), ultimately culminating in tubal occlusion and infertility. Whilst nucleic acid amplification tests can effectively diagnose uncomplicated lower genital tract (LGT) infections, they are not suitable for diagnosing upper genital tract (UGT) pathological sequelae. As a consequence, this study aimed to identify serological markers that can, with a high degree of sensitivity and specificity, discriminate between LGT infections and UGT pathology. Methods: Plasma was collected from 73 women with a history of LGT infection, UGT pathology due to C. trachomatis or no serological evidence of C. trachomatis infection. Western blotting was used to analyse antibody reactivity against extracted chlamydial proteins. Sensitivity and specificity of differential markers were also calculated. Results: Four antigens (CT157, CT423, CT727 and CT396) were identified and found to be capable of discriminating between the infection and disease sequelae state. Sensitivity and specificity calculations showed that our assay for diagnosing LGT infection had a sensitivity and specificity of 75% and 76% respectively, whilst the assay for identifying UGT pathology demonstrated 80% sensitivity and 86% specificity. Conclusions: The use of these assays could potentially facilitate earlier diagnoses in women suffering UGT pathology due to C. trachomatis.

Insulin-like growth factor-i : vitronectin complex-induced changes in gene expression effect breast cell survival and migration

Recent studies have demonstrated that IGF-I associates with VN through IGF-binding proteins (IGFBP) which in turn modulate IGF-stimulated biological functions such as cell proliferation, attachment and migration. Since IGFs play important roles in transformation and progression of breast tumours, we aimed to describe the effects of IGF-I:IGFBP:VN complexes on breast cell function and to dissect mechanisms underlying these responses. In this study we demonstrate that substrate-bound IGF-I:IGFBP:VN complexes are potent stimulators of MCF-7 breast cell survival, which is mediated by a transient activation of ERK/MAPK and sustained activation of PI3-K/AKT pathways. Furthermore, use of pharmacological inhibitors of the MAPK and PI3-K pathways confirms that both pathways are involved in IGF-I:IGFBP:VN complex-mediated increased cell survival. Microarray analysis of cells stimulated to migrate in response to IGF-I:IGFBP:VN complexes identified differential expression of genes with previously reported roles in migration, invasion and survival (Ephrin-B2, Sharp-2, Tissue-factor, Stratifin, PAI-1, IRS-1). These changes were not detected when the IGF-I analogue (\[L24]\[A31]-IGF-I), which fails to bind to the IGF-I receptor, was substituted; confirming the IGF-I-dependent differential expression of genes associated with enhanced cell migration. Taken together, these studies have established that IGF-I:IGFBP:VN complexes enhance breast cell migration and survival, processes central to facilitating metastasis. This study highlights the interdependence of ECM and growth factor interactions in biological functions critical for metastasis and identifies potential novel therapeutic targets directed at preventing breast cancer progression.

Recent advances in cancer therapy targeting proteins involved in DNA double-strand break repair

Damage to genetic material represents a persistent and ubiquitous threat to genomic stability. Once DNA damage is detected, a multifaceted signaling network is activated that halts the cell cycle, initiates repair, and in some instances induces apoptotic cell death. In this article, we will review DNA damage surveillance networks, which maintain the stability of our genome, and discuss the efforts underway to identify chemotherapeutic compounds targeting the core components of DNA double-strand breaks (DSB) response pathway. The majority of tumor cells have defects in maintaining genomic stability owing to the loss of an appropriate response to DNA damage. New anticancer agents are exploiting this vulnerability of cancer cells to enhance therapeutic indexes, with limited normal tissue toxicity. Recently inhibitors of the checkpoint kinases Chk1 and Chk2 have been shown to sensitize tumor cells to DNA damaging agents. In addition, the treatment of BRCA1- or BRCA2-deficient tumor cells with poly(ADP-ribose) polymerase (PARP) inhibitors also leads to specific tumor killing. Due to the numerous roles of p53 in genomic stability and its defects in many human cancers, therapeutic agents that restore p53 activity in tumors are the subject of multiple clinical trials. In this article we highlight the proteins mentioned above and catalog several additional players in the DNA damage response pathway, including ATM, DNA-PK, and the MRN complex, which might be amenable to pharmacological interventions and lead to new approaches to sensitize cancer cells to radio- and chemotherapy. The challenge is how to identify those patients most receptive to these treatments.

Multiple human single-stranded DNA binding proteins function in genome maintenance : structural, biochemical and functional analysis

DNA exists predominantly in a duplex form that is preserved via specific base pairing. This base pairing affords a considerable degree of protection against chemical or physical damage and preserves coding potential. However, there are many situations, e.g. during DNA damage and programmed cellular processes such as DNA replication and transcription, in which the DNA duplex is separated into two singlestranded DNA (ssDNA) strands. This ssDNA is vulnerable to attack by nucleases, binding by inappropriate proteins and chemical attack. It is very important to control the generation of ssDNA and protect it when it forms, and for this reason all cellular organisms and many viruses encode a ssDNA binding protein (SSB). All known SSBs use an oligosaccharide/oligonucleotide binding (OB)-fold domain for DNA binding. SSBs have multiple roles in binding and sequestering ssDNA, detecting DNA damage, stimulating strand-exchange proteins and helicases, and mediation of protein–protein interactions. Recently two additional human SSBs have been identified that are more closely related to bacterial and archaeal SSBs. Prior to this it was believed that replication protein A, RPA, was the only human equivalent of bacterial SSB. RPA is thought to be required for most aspects of DNA metabolism including DNA replication, recombination and repair. This review will discuss in further detail the biological pathways in which human SSBs function.

Exploiting system fluctuations. Differential training in physical prevention and rehabilitation programs for health and exercise

Background: Traditional causal modeling of health interventions tends to be linear in nature and lacks multidisciplinarity. Consequently, strategies for exercise prescription in health maintenance are typically group based and focused on the role of a common optimal health status template toward which all individuals should aspire. ----- ----- Materials and methods: In this paper, we discuss inherent weaknesses of traditional methods and introduce an approach exercise training based on neurobiological system variability. The significance of neurobiological system variability in differential learning and training was highlighted.----- ----- Results: Our theoretical analysis revealed differential training as a method by which neurobiological system variability could be harnessed to facilitate health benefits of exercise training. It was observed that this approach emphasizes the importance of using individualized programs in rehabilitation and exercise, rather than group-based strategies to exercise prescription.----- ----- Conclusion: Research is needed on potential benefits of differential training as an approach to physical rehabilitation and exercise prescription that could counteract psychological and physical effects of disease and illness in subelite populations. For example, enhancing the complexity and variability of movement patterns in exercise prescription programs might alleviate effects of depression in nonathletic populations and physical effects of repetitive strain injuries experienced by athletes in elite and developing sport programs.

TaNF-YB3 is involved in the regulation of photosynthesis genes in Triticum aestivum

Nuclear Factor Y (NF-Y) transcription factor is a heterotrimer comprised of three subunits: NF-YA, NF-YB and NF-YC. Each of the three subunits in plants is encoded by multiple genes with differential expression profiles, implying the functional specialisation of NF-Y subunit members in plants. In this study, we investigated the roles of NF-YB members in the light-mediated regulation of photosynthesis genes. We identified two NF-YB members from Triticum aestivum (TaNF-YB3 & 7) which were markedly upregulated by light in the leaves and seedling shoots using quantitative RT-PCR. A genome-wide coexpression analysis of multiple Affymetrix Wheat Genome Array datasets revealed that TaNF-YB3-coexpressed transcripts were highly enriched with the Gene Ontology term photosynthesis. Transgenic wheat lines constitutively overexpressing TaNF-YB3 had a significant increase in the leaf chlorophyll content, photosynthesis rate and early growth rate. Quantitative RT-PCR analysis showed that the expression levels of a number of TaNF-YB3-coexpressed transcripts were elevated in the transgenic wheat lines. The mRNA level of TaGluTR encoding glutamyl-tRNA reductase, which catalyses the rate limiting step of the chlorophyll biosynthesis pathway, was significantly increased in the leaves of the transgenic wheat. Significant increases in the expression level in the transgenic plant leaves were also observed for four photosynthetic apparatus genes encoding chlorophyll a/b-binding proteins (Lhca4 and Lhcb4) and photosystem I reaction center subunits (subunit K and subunit N), as well as for a gene coding for chloroplast ATP synthase  subunit. These results indicate that TaNF-YB3 is involved in the positive regulation of a number of photosynthesis genes in wheat.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Communicating assessment criteria is not sufficient for influencing students' approaches to assessment tasks – perspectives from a differential equations class

This report presents the findings of an exploratory study into the perceptions held by students regarding the use of criterion-referenced assessment in an undergraduate differential equations class. Students in the class were largely unaware of the concept of criterion referencing and of the various interpretations that this concept has among mathematics educators. Our primary goal was to investigate whether explicitly presenting assessment criteria to students was useful to them and guided them in responding to assessment tasks. Quantitative data and qualitative feedback from students indicates that while students found the criteria easy to understand and useful in informing them as to how they would be graded, the manner in which they actually approached the assessment activity was not altered as a result of the use of explicitly communicated grading criteria.

Investigation of electrophoretic loading and enhanced mechanical properties of hydrogels for delivery of therapeutic proteins

Hydrogels, which are three-dimensional crosslinked hydrophilic polymers, have been used and studied widely as vehicles for drug delivery due to their good biocompatibility. Traditional methods to load therapeutic proteins into hydrogels have some disadvantages. Biological activity of drugs or proteins can be compromised during polymerization process or the process of loading protein can be really timeconsuming. Therefore, different loading methods have been investigated. Based on the theory of electrophoresis, an electrochemical gradient can be used to transport proteins into hydrogels. Therefore, an electrophoretic method was used to load protein in this study. Chemically and radiation crosslinked polyacrylamide was used to set up the model to load protein electrophoretically into hydrogels. Different methods to prepare the polymers have been studied and have shown the effect of the crosslinker (bisacrylamide) concentration on the protein loading and release behaviour. The mechanism of protein release from the hydrogels was anomalous diffusion (i.e. the process was non-Fickian). The UV-Vis spectra of proteins before and after reduction show that the bioactivities of proteins after release from hydrogel were maintained. Due to the concern of cytotoxicity of residual monomer in polyacrylamide, poly(2-hydroxyethyl- methacrylate) (pHEMA) was used as the second tested material. In order to control the pore size, a polyethylene glycol (PEG) porogen was introduced to the pHEMA. The hydrogel disintegrated after immersion in water indicating that the swelling forces exceeded the strength of the material. In order to understand the cause of the disintegration, several different conditions of crosslinker concentration and preparation method were studied. However, the disintegration of the hydrogel still occurred after immersion in water principally due to osmotic forces. A hydrogel suitable for drug delivery needs to be biocompatible and also robust. Therefore, an approach to improving the mechanical properties of the porogen-containing pHEMA hydrogel by introduction of an inter-penetrating network (IPN) into the hydrogel system has been researched. A double network was formed by the introduction of further HEMA solution into the system by both electrophoresis and slow diffusion. Raman spectroscopy was used to observe the diffusion of HEMA into the hydrogel prior to further crosslinking by ã-irradiation. The protein loading and release behaviour from the hydrogel showing enhanced mechanical property was also studied. Biocompatibility is a very important factor for the biomedical application of hydrogels. Different hydrogels have been studied on both a three-dimensional HSE model and a HSE wound model for their biocompatibilities. They did not show any detrimental effect to the keratinocyte cells. From the results reported above, these hydrogels show good biocompatibility in both models. Due to the advantage of the hydrogels such as the ability to absorb and deliver protein or drugs, they have potential to be used as topical materials for wound healing or other biomedical applications.

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively.