Photo-cross-linked poly(D,L-lactide)-based networks. Structural characterization by HR-MAS NMR spectroscopy and hydrolytic degradation behavior

To date, biodegradable networks and particularly their kinetic chain lengths have been characterized by analysis of their degradation products in solution. We characterize the network itself by NMR analysis in the solvent-swollen state under magic angle spinning conditions. The networks were prepared by photoinitiated cross-linking of poly(dl-lactide)−dimethacrylate macromers (5 kg/mol) in the presence of an unreactive diluent. Using diffusion filtering and 2D correlation spectroscopy techniques, all network components are identified. By quantification of network-bound photoinitiator fragments, an average kinetic chain length of 9 ± 2 methacrylate units is determined. The PDLLA macromer solution was also used with a dye to prepare computer-designed structures by stereolithography. For these networks structures, the average kinetic chain length is 24 ± 4 methacrylate units. In all cases the calculated molecular weights of the polymethacrylate chains after degradation are maximally 8.8 kg/mol, which is far below the threshold for renal clearance. Upon incubation in phosphate buffered saline at 37 °C, the networks show a similar mass loss profile in time as linear high-molecular-weight PDLLA (HMW PDLLA). The mechanical properties are preserved longer for the PDLLA networks than for HMW PDLLA. The initial tensile strength of 47 ± 2 MPa does not decrease significantly for the first 15 weeks, while HMW PDLLA lost 85 ± 5% of its strength within 5 weeks. The physical properties, kinetic chain length, and degradation profile of these photo-cross-linked PDLLA networks make them most suited materials for orthopedic applications and use in (bone) tissue engineering.

Differential roles of the pRb and Arf/p53 pathways in murine naevus and melanoma genesis

We report on a systematic analysis of genotype-specific melanocyte (MC) UVR responses in transgenic mouse melanoma models along with tumour penetrance and comparative histopathology. pRb or p53 pathway mutations cooperated with NrasQ61K to transform MCs. We previously reported that MCs migrate from the follicular outer root sheath into the epidermis after neonatal UVR. Here, we found that Arf or p53 loss markedly diminished this response. Despite this, mice carrying these mutations developed melanoma with very early age of onset after neonatal UVR. Cdk4R24C did not affect the MC migration. Instead, independent of UVR exposure, interfollicular dermal MCs were more prevalent in Cdk4R24C mice. Subsequently, in adulthood, these mutants developed dermal MC proliferations reminiscent of superficial congenital naevi. Two types of melanoma were observed in this model. The location and growth pattern of the first was consistent with derivation from the naevi, while the second appeared to be of deep dermal origin. In animals carrying the Arf or p53 defects, no naevi were detected, with all tumours ostensibly skipping the benign precursor stage in progression.

Discrimination or Differential Involvement? A Review of the Research Exploring the Impact of Indigenous Status on Sentencing

Existing court data suggest that adult Indigenous offenders are more likely than non-Indigenous defendants to be sentenced to prison but once imprisoned generally receive shorter terms. Using findings from international and Australian multivariate statistical analyses, this paper reviews the three key hypotheses advanced as plausible explanations for these differences: 1) differential involvement, 2) negative discrimination, 3) positive discrimination. Overall, prior research shows strong support for the differential involvement thesis, some support for positive discrimination and little foundation for negative discrimination in the sentencing of Indigenous defendants. Where discrimination is found, we argue that this may be explained by the lack of a more complete set of control variables in researchers’ multivariate models.

The synthesis of novel nitroxides and their application as small-molecule antioxidants and profluorescent probes for oxidative stress

The detection and potential treatment of oxidative stress in biological systems has been explored using isoindoline-based nitroxide radicals. A novel tetraethyl-fluorescein nitroxide was synthesised for its use as a profluorescent probe for redox processes in biological systems. This tetraethyl system, as well as a tetramethyl-fluorescein nitroxide, were shown to be sensitive and selective probes for superoxide in vitro. The redox environment of cellular systems was also explored using the tetramethylfluorescein species based on its reduction to the hydroxylamine. Flow cytometry was employed to assess the extent of nitroxide reduction, reflecting the overall cellular redox environment. Treatment of normal fibroblasts with rotenone and 2-deoxyglucose resulted in an oxidising cellular environment as shown by the lack of reduction of the fluorescein-nitroxide system. Assessment of the tetraethyl-fluorescein nitroxide system in the same way demonstrated its enhanced resistance to reduction and offers the potential to detect and image biologically relevant reactive oxygen species directly. Importantly, these profluorescent nitroxide compounds were shown to be more effective than the more widely used and commercially available probes for reactive oxygen species such as 2’,7’-dichlorodihydrofluorescein diacetate. Fluorescence imaging of the tetramethyl-fluorescein nitroxide and a number of other rhodamine-nitroxide derivatives was undertaken, revealing the differential cellular localisation of these systems and thus their potential for the detection of redox changes in specific cellular compartments. As well as developing novel methods for the detection of oxidative stress, a number of novel isoindoline nitroxides were synthesised for their potential application as small-molecule antioxidants. These compounds incorporated known pharmacophores into the isoindoline-nitroxide structure in an attempt to increase their efficacy in biological systems. A primary and a secondary amine nitroxide were synthesised which incorporated the phenethylamine backbone of the sympathomimetic amine class of drugs. Initial assessment of the novel primary amine derivative indicated a protective effect comparable to that of 5-carboxy-1,1,3,3- tetramethylisoindolin-2-yloxyl. Methoxy-substituted nitroxides were also synthesised as potential antioxidants for their structural similarity to some amphetamine type stimulants. A copper-catalysed methodology provided access to both the mono- and di-substituted methoxy-nitroxides. Deprotection of the ethers in these compounds using boron tribromide successfully produced a phenolnitroxide, however the catechol moiety in the disubstituted derivative appeared to undergo reaction with the nitroxide to produce quinone-like degradation products. A novel fluoran-nitroxide was also synthesised from the methoxy-substituted nitroxide, providing a pH-sensitive spin probe. An amino-acid precursor containing a nitroxide moiety was also synthesised for its application as a dual-action antioxidant. N-Acetyl protection of the nitroxide radical was necessary prior to the Erlenmeyer reaction with N-acetyl glycine. Hydrolysis and reduction of the azlactone intermediate produced a novel amino acid precursor with significant potential as an effective antioxidant.

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.

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.

Subchondral bone osteoblasts can induce chondrocyte mineralization during osteoarthritis and this process is relevant to cartilage degradation

Pathological mineralization of articular cartilage is a characteristic feature of osteoarthritis (OA); however, the underlying mechanisms, and their relevance to cartilage degeneration, are not clear. The involvement of subchondral bone changes in OA have been reported previously with the characterization of abnormal subchondral bone mineral density (BMD), osteiod volume, altered bone mechanical parameters and an increase in bone turnover markers. A number of osteoarthritic animal models have demonstrated that subchondral bone changes often precede cartilage degeneration. In this study site specific localization of mineralization markers were detected in the OA cartilage. Chondrocytes and osteoblasts derived from OA cartilage and subchondral bone showed a significant increase in the mRNA expressions of mineralization markers. Interestingly, osteoblasts from OA subchondral bone could significantly decrease cartilage matrix expression; whereas, increase mineralization of chondrocytes (Figure 1). Osteogenic factors, such as CBFA1, ALP, and type X collagen (Col-X), were detected in chondrocytes under mineralization conditions (Figure 2). Furthermore, chondrocyte mineralization was followed by increased mRNA and protein levels of MMP-2, MMP-9 and MMP-13, all of which are detrimental to cartilage integrity in vivo. The data reported here suggests that the upregulation of subchondral bone-mineralization, typical of OA progression, causes cartilage mineralization, and that the mineralization of chondrocytes induce increased MMP levels with a subsequent degradation of the articular cartilage.

Advances in heterogeneous photocatalytic degradation of phenols and dyes in wastewater : a review

The heterogeneous photocatalytic water purification process has gained wide attention due to its effectiveness in degrading and mineralizing the recalcitrant organic compounds as well as the possibility of utilizing the solar UV and visible light spectrum. This paper aims to review and summarize the recently published works in the field of photocatalytic oxidation of toxic organic compounds such as phenols and dyes, predominant in waste water effluent. In this review, the effects of various operating parameters on the photocatalytic degradation of phenols and dyes are presented. Recent findings suggested that different parameters, such as type of photocatalyst and composition, light intensity, initial substrate concentration, amount of catalyst, pH of the reaction medium, ionic components in water, solvent types, oxidizing agents/electron acceptors, mode of catalyst application, and calcinations temperature can play an important role on the photocatlytic degradation of organic compounds in water environment. Extensive research has focused on the enhancement of photocatalysis by modification of TiO2 employing metal, non-metal and ion doping. Recent advances in TiO2 photocatalysis for the degradation of various phenols and dyes are also highlighted in this review.

Influence of parameters on the heterogeneous photocatalytic degradation of pesticides and phenolic contaminants in wastewater : a short review

In recent years, the application of heterogeneous photocatalytic water purification process has gained wide attention due to its effectiveness in degrading and mineralizing the recalcitrant organic compounds as well as the possibility of utilizing the solar UV and visible light spectrum. This paper aims to review and summarize the recently published works on the titanium dioxide (TiO2) photocatalytic oxidation of pesticides and phenolic compounds, predominant in storm and waste water effluents. The effect of various operating parameters on the photocatalytic degradation of pesticides and phenols are discussed. Results reported here suggested that the photocatalytic degradation of organic compounds depends on the type of photocatalyst and composition, light intensity, initial substrate concentration, amount of catalyst, pH of the reaction medium, ionic components in water, solvent types, oxidizing agents/electron acceptors, catalyst application mode, and calcinations temperature in water environment. A substantial amount of research has focused on the enhancement of TiO2 photocatalysis by modification with metal, non-metal and ion doping. Recent developments in TiO2 photocatalysis for the degradation of various pesticides and phenols are also highlighted in this review. It is evident from the literature survey that photocatalysis has shown good potential for the removal of various organic pollutants. However, still there is a need to find out the practical utility of this technique on commercial scale.

Heterogeneous photocatalytic degradation of phenols in wastewater : a review on current status and developments

In recent years, there has been an enormous amount of research and development in the area of heterogeneous photocatalytic water purification process due to its effectiveness in degrading and mineralising the recalcitrant organic compounds as well as the possibility of utilising the solar UV and visible spectrum. One hundred and twenty recently published papers are reviewed and summarised here with the focus being on the photocatalytic oxidation of phenols and their derivatives, predominant in waste water effluent. In this review, the effects of various operating parameters on the photocatalytic degradation of phenols and substituted phenols are presented. Recent findings suggested that different parameters, such as type of photocatalyst and composition, light intensity, initial substrate concentration, amount of catalyst, pH of the reaction medium, ionic components in water, solvent types, oxidising agents/electron acceptors, mode of catalyst application, and calcination temperatures can play an important role on the photocatalytic degradation of phenolic compounds in wastewater. Extensive research has focused on the enhancement of photocatalysis by modification of TiO2 employing metal, non-metal and ion doping. Recent developments in TiO2 photocatalysis for the degradation of various phenols and substituted phenols are also reviewed.

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.

Recent developments in photocatalytic degradation of pesticides and phenols in storm and wastewater effluent

The heterogeneous photocatalytic oxidation process offers a versatile promise in the detoxification and disinfection of wastewater containing hazardous organic compounds such as pesticides and phenolic compounds in storm and wastewater effluent. This process has gained wide attention due to its effectiveness in degrading and mineralizing the organic compounds into harmless and often useful components. To develop an efficient photocatalytic process, titanium dioxide has been actively studied in recent years due to its excellent performance as a photocatalyst under UV light irradiation. This paper aims at critically evaluating and highlighting the recent developments of the heterogeneous photocatalytic systems with a special focus on storm and wastewater treatment applications.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.