Missing pieces in the puzzle of plant microRNAs

Plant microRNAs (miRNAs) are important regulatory switches. Recent advances have revealed many regulatory layers between the two essential processes, miRNA biogenesis and function. However, how these multilayered regulatory processes ultimately control miRNA gene regulation and connects miRNAs and plant responses with the surrounding environment is still largely unknown. In this opinion article, we propose that the miRNA pathway is highly dynamic and plastic. The apparent flexibility of the miRNA pathway in plants appears to be controlled by a number recently identified proteins and poorly characterized signaling cascades. We further propose that altered miRNA accumulation can be a direct consequence of the rewiring of interactions between proteins that function in the miRNA pathway, an avenue that remains largely unexplored.

Can tissue engineering concepts advance tumor biology research?

Advances in tissue engineering have traditionally led to the design of scaffold- or matrix-based culture systems that better reflect the biological, physical and biochemical environment of the natural extracellular matrix. Although their clinical applications in regenerative medicine tend to receive most of the attention, it is obvious that other areas of biomedical research could be well served by the powerful tools that have already been developed in tissue engineering. In this article, we review the recent literature to demonstrate how tissue engineering platforms can enhance in vitro and in vivo models of tumorigenesis and thus hold great promise to contribute to future cancer research.

Novel analytical and numerical methods for solving fractional dynamical systems

During the past three decades, the subject of fractional calculus (that is, calculus of integrals and derivatives of arbitrary order) has gained considerable popularity and importance, mainly due to its demonstrated applications in numerous diverse and widespread fields in science and engineering. For example, fractional calculus has been successfully applied to problems in system biology, physics, chemistry and biochemistry, hydrology, medicine, and finance. In many cases these new fractional-order models are more adequate than the previously used integer-order models, because fractional derivatives and integrals enable the description of the memory and hereditary properties inherent in various materials and processes that are governed by anomalous diffusion. Hence, there is a growing need to find the solution behaviour of these fractional differential equations. However, the analytic solutions of most fractional differential equations generally cannot be obtained. As a consequence, approximate and numerical techniques are playing an important role in identifying the solution behaviour of such fractional equations and exploring their applications. The main objective of this thesis is to develop new effective numerical methods and supporting analysis, based on the finite difference and finite element methods, for solving time, space and time-space fractional dynamical systems involving fractional derivatives in one and two spatial dimensions. A series of five published papers and one manuscript in preparation will be presented on the solution of the space fractional diffusion equation, space fractional advectiondispersion equation, time and space fractional diffusion equation, time and space fractional Fokker-Planck equation with a linear or non-linear source term, and fractional cable equation involving two time fractional derivatives, respectively. One important contribution of this thesis is the demonstration of how to choose different approximation techniques for different fractional derivatives. Special attention has been paid to the Riesz space fractional derivative, due to its important application in the field of groundwater flow, system biology and finance. We present three numerical methods to approximate the Riesz space fractional derivative, namely the L1/ L2-approximation method, the standard/shifted Gr¨unwald method, and the matrix transform method (MTM). The first two methods are based on the finite difference method, while the MTM allows discretisation in space using either the finite difference or finite element methods. Furthermore, we prove the equivalence of the Riesz fractional derivative and the fractional Laplacian operator under homogeneous Dirichlet boundary conditions – a result that had not previously been established. This result justifies the aforementioned use of the MTM to approximate the Riesz fractional derivative. After spatial discretisation, the time-space fractional partial differential equation is transformed into a system of fractional-in-time differential equations. We then investigate numerical methods to handle time fractional derivatives, be they Caputo type or Riemann-Liouville type. This leads to new methods utilising either finite difference strategies or the Laplace transform method for advancing the solution in time. The stability and convergence of our proposed numerical methods are also investigated. Numerical experiments are carried out in support of our theoretical analysis. We also emphasise that the numerical methods we develop are applicable for many other types of fractional partial differential equations.

Biology or behavior : which is the strongest contributor to weight gain?

Combating unhealthy weight gain is a major public health and clinical management issue. The extent of research into the etiology and pathophysiology of obesity has produced a wealth of evidence regarding the contributing factors. While aspects of the environment are ‘obesogenic’, weight gain is not inevitable for every individual. What then explains potentially unhealthy weight gain in individuals living within an environment where others remain lean? In this paper we explore the biological compensation that acts in response to a reduced energy intake by reducing energy needs, in order to defend against weight loss. We then examine the evidence that there is only a weak biological compensation to surplus energy supply, and that this allows behavior to drive weight gain. The extent to which biology impacts behavior is also considered.

Gene transfer vectors targeted to human prostate cancer : do we need better preclinical testing systems?

Destruction of cancer cells by genetically modified viral and nonviral vectors has been the aim of many research programs. The ability to target cytotoxic gene therapies to the cells of interest is an essential prerequisite, and the treatment has always had the potential to provide better and more long-lasting therapy than existing chemotherapies. However, the potency of these infectious agents requires effective testing systems, in which hypotheses can be explored both in vitro and in vivo before the establishment of clinical trials in humans. The real prospect of off-target effects should be eliminated in the preclinical stage, if current prejudices against such therapies are to be overcome. In this review we have set out, using adenoviral vectors as a commonly used example, to discuss some of the key parameters required to develop more effective testing, and to critically assess the current cellular models for the development and testing of prostate cancer biotherapy. Only by developing models that more closely mirror human tissues will we be able to translate literature publications into clinical trials and hence into acceptable alternative treatments for the most commonly diagnosed cancer in humans.

Cellular model systems to study the tumor biological role of kallikrein-related peptidases in ovarian and prostate cancer

Since the identification of the gene family of kallikrein related peptidases (KLKs), their function has been robustly studied at the biochemical level. In vitro biochemical studies have shown that KLK proteases are involved in a number of extracellular processes that initiate intracellular signaling pathways by hydrolysis, as reviewed in Chapters 8, 9, and 15, Volume 1. These events have been associated with more invasive phenotypes of ovarian, prostate, and other cancers. Concomitantly, aberrant expression of KLKs has been associated with poor prognosis of patients with ovarian and prostate cancer (Borgoño and Diamandis, 2004; Clements et al., 2004; Yousef and Diamandis, 2009), with prostate-specific antigen (PSA, KLK3) being a long standing, clinically employed biomarker for prostate cancer (Lilja et al., 2008). Data generated from patient samples in clinical studies, alongwith biochemical activity, suggests that KLKs function in the development and progression of these diseases. To bridge the gap between their function at the molecular level and the clinical need for efficacious treatment and prognostic biomarkers, functional assessment at the in vitro cellular level, using various culture models, is increasing, particularly in a three-dimensional (3D) context (Abbott, 2003; Bissell and Radisky, 2001; Pampaloni et al., 2007; Yamada and Cukierman, 2007).

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.

The biology of the glutamatergic system and potential role in migraine

Migraine is a common genetically linked neurovascular disorder. Approximately ~12% of the Caucasian population are affected including 18% of adult women and 6% of adult men (1, 2). A notable female bias is observed in migraine prevalence studies with females affected ~3 times more than males and is credited to differences in hormone levels arising from reproductive achievements. Migraine is extremely debilitating with wide-ranging socioeconomic impact significantly affecting people's health and quality of life. A number of neurotransmitter systems have been implicated in migraine, the most studied include the serotonergic and dopaminergic systems. Extensive genetic research has been carried out to identify genetic variants that may alter the activity of a number of genes involved in synthesis and transport of neurotransmitters of these systems. The biology of the Glutamatergic system in migraine is the least studied however there is mounting evidence that its constituents could contribute to migraine. The discovery of antagonists that selectively block glutamate receptors has enabled studies on the physiologic role of glutamate, on one hand, and opened new perspectives pertaining to the potential therapeutic applications of glutamate receptor antagonists in diverse neurologic diseases. In this brief review, we discuss the biology of the Glutamatergic system in migraine outlining recent findings that support a role for altered Glutamatergic neurotransmission from biochemical and genetic studies in the manifestation of migraine and the implications of this on migraine treatment.

Understanding requirements of novel healthcare information systems for management of advanced prostate cancer

Effective management of chronic diseases is a global health priority. A healthcare information system offers opportunities to address challenges of chronic disease management. However, the requirements of health information systems are often not well understood. The accuracy of requirements has a direct impact on the successful design and implementation of a health information system. Our research describes methods used to understand the requirements of health information systems for advanced prostate cancer management. The research conducted a survey to identify heterogeneous sources of clinical records. Our research showed that the General Practitioner was the common source of patient's clinical records (41%) followed by the Urologist (14%) and other clinicians (14%). Our research describes a method to identify diverse data sources and proposes a novel patient journey browser prototype that integrates disparate data sources.

Methane and nitrous oxide fluxes in annual and perennial land-use systems of the irrigated areas in the Aral Sea Basin

Land use and agricultural practices can result in important contributions to the global source strength of atmospheric nitrous oxide (N2O) and methane (CH4). However, knowledge of gas flux from irrigated agriculture is very limited. From April 2005 to October 2006, a study was conducted in the Aral Sea Basin, Uzbekistan, to quantify and compare emissions of N2O and CH4 in various annual and perennial land-use systems: irrigated cotton, winter wheat and rice crops, a poplar plantation and a natural Tugai (floodplain) forest. In the annual systems, average N2O emissions ranged from 10 to 150 μg N2O-N m−2 h−1 with highest N2O emissions in the cotton fields, covering a similar range of previous studies from irrigated cropping systems. Emission factors (uncorrected for background emission), used to determine the fertilizer-induced N2O emission as a percentage of N fertilizer applied, ranged from 0.2% to 2.6%. Seasonal variations in N2O emissions were principally controlled by fertilization and irrigation management. Pulses of N2O emissions occurred after concomitant N-fertilizer application and irrigation. The unfertilized poplar plantation showed high N2O emissions over the entire study period (30 μg N2O-N m−2 h−1), whereas only negligible fluxes of N2O (<2 μg N2O-N m−2 h−1) occurred in the Tugai. Significant CH4 fluxes only were determined from the flooded rice field: Fluxes were low with mean flux rates of 32 mg CH4 m−2 day−1 and a low seasonal total of 35.2 kg CH4 ha−1. The global warming potential (GWP) of the N2O and CH4 fluxes was highest under rice and cotton, with seasonal changes between 500 and 3000 kg CO2 eq. ha−1. The biennial cotton–wheat–rice crop rotation commonly practiced in the region would average a GWP of 2500 kg CO2 eq. ha−1 yr−1. The analyses point out opportunities for reducing the GWP of these irrigated agricultural systems by (i) optimization of fertilization and irrigation practices and (ii) conversion of annual cropping systems into perennial forest plantations, especially on less profitable, marginal lands.

Biolistic transformation of elite indica rice (Oryza sativa L.) cultivars through semi-solid and liquid medium selection systems

Following microprojectile mediated delivery of a plasmid construct (pAHC-25) encoding bar (bialophos resistance) gene into five-day-old scutellar calli derived from mature embryos, the effectiveness of selection procedure for bar-gene expressing tissue was compared for two indica rice cultivars (IR-64 and Karnal Local). While IR-64 transformants could be selected through the generally used semi-solid selection medium, the same procedure was not effective in the basmati cultivar Karnal Local. In the latter case, while lower concentrations (2–4 mg 1−1) of the selective agent phosphinothricin (PPT) yielded only escapes, higher concentrations (6–8 mg l−1) inhibited proliferation of transformed as well as untransformed sectors. For Karnal Local, a liquid medium based selection system was successfully utilized for recovering transformed sectors and, eventually, regenerants. The study demonstrates the generation of transformants of two elite indica cultivars using the environment-independent system of mature embryos from seeds.

Canards in advection-reaction-diffusion systems in one spatial dimension

This thesis contains a mathematical investigation of the existence of travelling wave solutions to singularly perturbed advection-reaction-diffusion models of biological processes. An enhanced mathematical understanding of these solutions and models is gained via the identification of canards (special solutions of fast/slow dynamical systems) and their role in the existence of the most biologically relevant, shock-like solutions. The analysis focuses on two existing models. A new proof of existence of a whole family of travelling waves is provided for a model describing malignant tumour invasion, while new solutions are identified for a model describing wound healing angiogenesis.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

In silico biology : making the most of parallel computing

Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed.