A water-dielectric capacitor using hydrated graphene oxide film

Despite the widespread use of paper, plastic or ceramics in dielectric capacitors, water has not been commonly used as a dielectric due to its tendency to become conductive as it easily leaches ions from the environment. We show here that when water is confined between graphene oxide sheets, it can retain its insulating nature and behave as a dielectric. A hydrated graphene oxide film was used as a dielectric spacer to construct a prototype water-dielectric capacitor. The capacitance depends on the water content of the hydrated GO film as well as the voltage applied to the device. Our results show that the capacitance per unit area of the GO film is in the range of 100–800 mF cm �2, which is 5–40 times that of the double layer capacitance per surface area of activated carbon.

Integrated genomic characterization of endometrial carcinoma

We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

Validation of a new tool to measure responsiveness and structure in the feeding context : the Authoritative Feeding Practices Questionnaire

How mothers interact with their toddlers around food lays the foundations for healthy eating and healthy weight gain in later life. This research involving 467 Australian first-time mothers of 2-year-old children resulted in the development of a new self-report tool, the Authoritative Feeding Practices Questionnaire, assessing maternal responsive feeding and mealtime structure. Secondary analysis of the NOURISH randomised controlled trial included theory-driven item selection, confirmatory factor analysis, evaluation of psychometric properties and construct validation. The result is a brief, reliable and valid new tool for evaluating the maternal feeding practices that support children to become healthy, independent eaters.

Association between maternal depressive symptoms in the early postnatal period and responsiveness in feeding at child age 2 years

Maternal depression is a known risk factor for poor outcomes for children. Pathways to these poor outcomes relate to reduced maternal responsiveness or sensitivity to the child. Impaired responsiveness potentially impacts the feeding relationship and thus may be a risk factor for inappropriate feeding practices. The aim of this study was to examine the longitudinal relationships between self-reported maternal post-natal depressive symptoms at child age 4 months and feeding practices at child age 2 years in a community sample. Participants were Australian first-time mothers allocated to the control group of the NOURISH randomized controlled trial when infants were 4 months old. Complete data from 211 mothers (of 346 allocated) followed up when their children were 2 years of age (51% girls) were available for analysis. The relationship between Edinburgh Postnatal Depression Scale (EPDS) score (child age 4 months) and child feeding practices (child age 2 years) was tested using hierarchical linear regression analysis adjusted for maternal and child characteristics. Higher EPDS score was associated with less responsive feeding practices at child age 2 years: greater pressure [β = 0.18, 95% confidence interval (CI): 0.04–0.32, P = 0.01], restriction (β = 0.14, 95% CI: 0.001–0.28, P = 0.05), instrumental (β = 0.14, 95% CI: 0.005–0.27, P = 0.04) and emotional (β = 0.15, 95% CI: 0.01–0.29, P = 0.03) feeding practices (ΔR2 values: 0.02–0.03, P < 0.05). This study provides evidence for the proposed link between maternal post-natal depressive symptoms and lower responsiveness in child feeding. These findings suggest that the provision of support to mothers experiencing some levels of depressive symptomatology in the early post-natal period may improve responsiveness in the child feeding relationship.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

The power of hands-on exercises in SCADA cyber security education

For decades Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems (ICS) have used computers to monitor and control physical processes in many critical industries, including electricity generation, gas pipelines, water distribution, waste treatment, communications and transportation. Increasingly these systems are interconnected with corporate networks via the Internet, making them vulnerable and exposed to the same risks as those experiencing cyber-attacks on a conventional network. Very often SCADA networks services are viewed as a specialty subject, more relevant to engineers than standard IT personnel. Educators from two Australian universities have recognised these cultural issues and highlighted the gap between specialists with SCADA systems engineering skills and the specialists in network security with IT background. This paper describes a learning approach designed to help students to bridge this gap, gain theoretical knowledge of SCADA systems' vulnerabilities to cyber-attacks via experiential learning and acquire practical skills through actively participating in hands-on exercises.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

A novel route in bone tissue engineering : magnetic biomimetic scaffolds

In recent years, interest in tissue engineering and its solutions has increased considerably. In particular, scaffolds have become fundamental tools in bone graft substitution and are used in combination with a variety of bio-agents. However, a long-standing problem in the use of these conventional scaffolds lies in the impossibility of re-loading the scaffold with the bio-agents after implantation. This work introduces the magnetic scaffold as a conceptually new solution. The magnetic scaffold is able, via magnetic driving, to attract and take up in vivo growth factors, stem cells or other bio-agents bound to magnetic particles. The authors succeeded in developing a simple and inexpensive technique able to transform standard commercial scaffolds made of hydroxyapatite and collagen in magnetic scaffolds. This innovative process involves dip-coating of the scaffolds in aqueous ferrofluids containing iron oxide nanoparticles coated with various biopolymers. After dip-coating, the nanoparticles are integrated into the structure of the scaffolds, providing the latter with magnetization values as high as 15 emu g�1 at 10 kOe. These values are suitable for generating magnetic gradients, enabling magnetic guiding in the vicinity and inside the scaffold. The magnetic scaffolds do not suffer from any structural damage during the process, maintaining their specific porosity and shape. Moreover, they do not release magnetic particles under a constant flow of simulated body fluids over a period of 8 days. Finally, preliminary studies indicate the ability of the magnetic scaffolds to support adhesion and proliferation of human bone marrow stem cells in vitro. Hence, this new type of scaffold is a valuable candidate for tissue engineering applications, featuring a novel magnetic guiding option.

Rho GTPases mediate the mechanosensitive lineage commitment of neural stem cells

Adult neural stem cells (NSCs) play important roles in learning and memory and are negatively impacted by neurological disease. It is known that biochemical and genetic factors regulate self-renewal and differentiation, and it has recently been suggested that mechanical and solid-state cues, such as extracellular matrix (ECM) stiffness, can also regulate the functions of NSCs and other stem cell types. However, relatively little is known of the molecular mechanisms through which stem cells transduce mechanical inputs into fate decisions, the extent to which mechanical inputs instruct fate decisions versus select for or against lineage-committed blast populations, or the in vivo relevance of mechanotransductive signaling molecules in native stem cell niches. Here we demonstrate that ECM-derived mechanical signals act through Rho GTPases to activate the cellular contractility machinery in a key early window during differentiation to regulate NSC lineage commitment. Furthermore, culturing NSCs on increasingly stiff ECMs enhances RhoA and Cdc42 activation, increases NSC stiffness, and suppresses neurogenesis. Likewise, inhibiting RhoA and Cdc42 or downstream regulators of cellular contractility rescues NSCs from stiff matrix- and Rho GTPase-induced neurosuppression. Importantly, Rho GTPase expression and ECM stiffness do not alter proliferation or apoptosis rates indicating that an instructive rather than selective mechanism modulates lineage distributions. Finally, in the adult brain, RhoA activation in hippocampal progenitors suppresses neurogenesis, analogous to its effect in vitro. These results establish Rho GTPase-based mechanotransduction and cellular stiffness as biophysical regulators of NSC fate in vitro and RhoA as an important regulatory protein in the hippocampal stem cell niche.

High-throughput indentational elasticity measurements of hydrogel extracellular matrix substrates

Much interest surrounds the effect of extracellular matrix (ECM) elasticity on cell behavior. Here we present a rapid method for measuring the elasticity of synthetic ECM substrates based on indentation of the substrate with a ferromagnetic sphere and optical tracking of the resulting deformation. We find that this method yields order-of-magnitude agreement with atomic force microscopy elasticity measurements, but that the degree of this agreement depends strongly on sphere density and gel elasticity. In its regime of greatest accuracy, we envision that this method may be used for high-throughput characterization of ECM substrates in cell biological studies.

Rational design of artificial cellular niches for tissue engineering

Tissue Engineering is a promising emerging field that studies the intrinsic regenerative potential of the human body and uses it to restore functionality of damaged organs or tissues unable of self-healing due to illness or ageing. In order to achieve regeneration using Tissue Engineering strategies, it is first necessary to study the properties of the native tissue and determine the cause of tissue failure; second, to identify an optimum population of cells capable of restoring its functionality; and third, to design and manufacture a cellular microenvironment in which those specific cells are directed towards the desired cellular functions. The design of the artificial cellular niche has a tremendous importance, because cells will feel and respond to both its biochemical and biophysical properties very differently. In particular, the artificial niche will act as a physical scaffold for the cells, allowing their three-dimensional spatial organization; also, it will provide mechanical stability to the artificial construct; and finally, it will supply biochemical and mechanical cues to control cellular growth, migration, differentiation and synthesis of natural extracellular matrix. During the last decades, many scientists have made great contributions to the field of Tissue Engineering. Even though this research has frequently been accompanied by vast investments during extended periods of time, yet too often these efforts have not been enough to translate the advances into new clinical therapies. More and more scientists in this field are aware of the need of rational experimental designs before carrying out complex, expensive and time-consuming in vitro and in vivo trials. This review highlights the importance of computer modeling and novel biofabrication techniques as critical key players for a rational design of artificial cellular niches in Tissue Engineering.

Optimization approaches for the design of additively manufactured scaffolds

Scaffolds play a pivotal role in tissue engineering, promoting the synthesis of neo extra-cellular matrix (ECM), and providing temporary mechanical support for the cells during tissue regeneration. Advances introduced by additive manufacturing techniques have significantly improved the ability to regulate scaffold architecture, enhancing the control over scaffold shape and porosity. Thus, considerable research efforts have been devoted to the fabrication of 3D porous scaffolds with optimized micro-architectural features. This chapter gives an overview of the methods for the design of additively manufactured scaffolds and their applicability in tissue engineering (TE). Along with a survey of the state of the art, the Authors will also present a recently developed method, called Load-Adaptive Scaffold Architecturing (LASA), which returns scaffold architectures optimized for given applied mechanical loads systems, once the specific stress distribution is evaluated through Finite Element Analysis (FEA).

The feeding practices and structure questionnaire : construction and initial validation in a sample of Australian first-time mothers and their 2-year olds

Background Early feeding practices lay the foundation for children’s eating habits and weight gain. Questionnaires are available to assess parental feeding but overlapping and inconsistent items, subscales and terminology limit conceptual clarity and between study comparisons. Our aim was to consolidate a range of existing items into a parsimonious and conceptually robust questionnaire for assessing feeding practices with very young children (<3 years). Methods Data were from 462 mothers and children (age 21–27 months) from the NOURISH trial. Items from five questionnaires and two study-specific items were submitted to a priori item selection, allocation and verification, before theoretically-derived factors were tested using Confirmatory Factor Analysis. Construct validity of the new factors was examined by correlating these with child eating behaviours and weight. Results Following expert review 10 factors were specified. Of these, 9 factors (40 items) showed acceptable model fit and internal reliability (Cronbach’s α: 0.61-0.89). Four factors reflected non-responsive feeding practices: ‘Distrust in Appetite’, ‘Reward for Behaviour’, ‘Reward for Eating’, and ‘Persuasive Feeding’. Five factors reflected structure of the meal environment and limits: ‘Structured Meal Setting’, ‘Structured Meal Timing’, ‘Family Meal Setting’, ‘Overt Restriction’ and ‘Covert Restriction’. Feeding practices generally showed the expected pattern of associations with child eating behaviours but none with weight. Conclusion The Feeding Practices and Structure Questionnaire (FPSQ) provides a new reliable and valid measure of parental feeding practices, specifically maternal responsiveness to children’s hunger/satiety signals facilitated by routine and structure in feeding. Further validation in more diverse samples is required.

Discrete phase-locked loop systems and spreadsheets

This paper demonstrates the use of a spreadsheet in exploring non-linear difference equations that describe digital control systems used in radio engineering, communication and computer architecture. These systems, being the focus of intensive studies of mathematicians and engineers over the last 40 years, may exhibit extremely complicated behaviour interpreted in contemporary terms as transition from global asymptotic stability to chaos through period-doubling bifurcations. The authors argue that embedding advanced mathematical ideas in the technological tool enables one to introduce fundamentals of discrete control systems in tertiary curricula without learners having to deal with complex machinery that rigorous mathematical methods of investigation require. In particular, in the appropriately designed spreadsheet environment, one can effectively visualize a qualitative difference in the behviour of systems with different types of non-linear characteristic.

Highly NO2 sensitive caesium doped graphene oxide conductometric sensors

Here we report on the synthesis of caesium doped graphene oxide (GO-Cs) and its application to the development of a novel NO2 gas sensor. The GO, synthesized by oxidation of graphite through chemical treatment, was doped with Cs by thermal solid-state reaction. The samples, dispersed in DI water by sonication, have been drop-casted on standard interdigitated Pt electrodes. The response of both pristine and Cs doped GO to NO2 at room temperature is studied by varying the gas concentration. The developed GO-Cs sensor shows a higher response to NO2 than the pristine GO based sensor due to the oxygen functional groups. The detection limit measured with GO-Cs sensor is ≈90 ppb.