311 resultados para Fibroblast viability


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In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (DT), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a DT-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes. Copyright © 2009, American Society for Microbiology. All Rights Reserved.

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The exact phenotype of human periodontal ligament cells (hPDLCs) remains a controversial area. Basic fibroblast growth factor (FGF‑2) exhibits various functions and its effect on hPDLCs is also controversial. Therefore, the present study examined the effect of FGF‑2 on the growth and osteoblastic phenotype of hPDLCs with or without osteogenic inducers (dexamethasone and β‑glycerophosphate). FGF‑2 was added to defined growth culture medium and osteogenic inductive culture medium. Cell proliferation, osteogenic differentiation and mineralization were measured. The selected differentiation markers, Runx2, collagen type Ⅰ, α1 (Col1a1), osteocalcin (OCN) and epidermal growth factor receptor (EGFR), were investigated by reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). Runx2 and OCN protein expression was measured by western blotting. FGF‑2 significantly increased the proliferation of hPDLCs, but did not affect alkaline phosphatase activity. RT‑qPCR analysis revealed enhanced mRNA expression of Runx2, OCN and EGFR, but suppressed Col1a1 gene expression in the absence of osteogenic inducers, whereas all these gene levels had no clear trend in their presence. The Runx2 protein expression was clearly increased, but the OCN protein level showed no evident trend. The mineralization assay demonstrated that FGF‑2 inhibited mineralized matrix deposition with osteogenic inducers. These results suggested that FGF‑2 induces the growth of immature hPDLCs, which is a competitive inhibitor of epithelial downgrowth, and suppresses their differentiation into mineralized tissue by affecting Runx2 expression. Therefore, this may lead to the acceleration of periodontal regeneration.

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The hippocampus is an anatomically distinct region of the medial temporal lobe that plays a critical role in the formation of declarative memories. Here we show that a computer simulation of simple compartmental cells organized with basic hippocampal connectivity is capable of producing stimulus intensity sensitive wide-band fluctuations of spectral power similar to that seen in real EEG. While previous computational models have been designed to assess the viability of the putative mechanisms of memory storage and retrieval, they have generally been too abstract to allow comparison with empirical data. Furthermore, while the anatomical connectivity and organization of the hippocampus is well defined, many questions regarding the mechanisms that mediate large-scale synaptic integration remain unanswered. For this reason we focus less on the specifics of changing synaptic weights and more on the population dynamics. Spectral power in four distinct frequency bands were derived from simulated field potentials of the computational model and found to depend on the intensity of a random input. The majority of power occurred in the lowest frequency band (3-6 Hz) and was greatest to the lowest intensity stimulus condition (1% maximal stimulus). In contrast, higher frequency bands ranging from 7-45 Hz show an increase in power directly related with an increase in stimulus intensity. This trend continues up to a stimulus level of 15% to 20% of the maximal input, above which power falls dramatically. These results suggest that the relative power of intrinsic network oscillations are dependent upon the level of activation and that above threshold levels all frequencies are damped, perhaps due to over activation of inhibitory interneurons.

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A hippocampal-CA3 memory model was constructed with PGENESIS, a recently developed version of GENESIS that allows for distributed processing of a neural network simulation. A number of neural models of the human memory system have identified the CA3 region of the hippocampus as storing the declarative memory trace. However, computational models designed to assess the viability of the putative mechanisms of storage and retrieval have generally been too abstract to allow comparison with empirical data. Recent experimental evidence has shown that selective knock-out of NMDA receptors in the CA1 of mice leads to reduced stability of firing specificity in place cells. Here a similar reduction of stability of input specificity is demonstrated in a biologically plausible neural network model of the CA3 region, under conditions of Hebbian synaptic plasticity versus an absence of plasticity. The CA3 region is also commonly associated with seizure activity. Further simulations of the same model tested the response to continuously repeating versus randomized nonrepeating input patterns. Each paradigm delivered input of equal intensity and duration. Non-repeating input patterns elicited a greater pyramidal cell spike count. This suggests that repetitive versus non-repeating neocortical inpus has a quantitatively different effect on the hippocampus. This may be relevant to the production of independent epileptogenic zones and the process of encoding new memories.

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Particulates with specific sizes and characteristics can induce potent immune responses by promoting antigen uptake of appropriate immuno-stimulatory cell types. Magnetite (Fe3O4) nanoparticles have shown many potential bioapplications due to their biocompatibility and special characteristics. Here, superparamagnetic Fe3O4 nanoparticles (SPIONs) with high magnetization value (70emug-1) were stabilized with trisodium citrate and successfully conjugated with a model antigen (ovalbumin, OVA) via N,N'-carbonyldiimidazole (CDI) mediated reaction, to achieve a maximum conjugation capacity at approximately 13μgμm-2. It was shown that different mechanisms governed the interactions between the OVA molecules and magnetite nanoparticles at different pH conditions. We evaluated as-synthesized SPION against commercially available magnetite nanoparticles. The cytotoxicity of these nanoparticles was investigated using mammalian cells. The reported CDI-mediated reaction can be considered as a potential approach in conjugating biomolecules onto magnetite or other biodegradable nanoparticles for vaccine delivery.

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Background: Conventional biodiesel production relies on trans-esterification of lipids extracted from vegetable crops. However, the use of valuable vegetable food stocks as raw material for biodiesel production makes it an unfeasibly expensive process. Used cooking oil is a finite resource and requires extra downstream processing, which affects the amount of biodiesel that can be produced and the economics of the process. Lipids extracted from microalgae are considered an alternative raw material for biodiesel production. This is primarily due to the fast growth rate of these species in a simple aquaculture environment. However, the dilute nature of microalgae culture puts a huge economic burden on the dewatering process especially on an industrial scale. This current study explores the performance and economic viability of chemical flocculation and tangential flow filtration (TFF) for the dewatering of Tetraselmis suecicamicroalgae culture. Results: Results show that TFF concentrates the microalgae feedstock up to 148 times by consuming 2.06 kWh m-3 of energy while flocculation consumes 14.81 kWhm-3 to concentrate the microalgae up to 357 times. Economic evaluation demonstrates that even though TFF has higher initial capital investment than polymer flocculation, the payback period for TFF at the upper extreme ofmicroalgae revenue is ∼1.5 years while that of flocculation is ∼3 years. Conclusion: These results illustrate that improved dewatering levels can be achieved more economically by employing TFF. The performances of these two techniques are also compared with other dewatering techniques.

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Background The adsorption of bovine serum albumin (BSA) onto mesoporous silica spheres (MPS) synthesized from silica colloids was studied employing real time in situ measurements. The stabilities of the BSA at different pH values, their isoelectric points and zeta potentials were determined in order to probe the interactions between the protein and the mesoporous silica. Results The pore size of MPS was designed for protein, and this, coupled with an in depth understanding of the physico-chemical characteristics of the protein and MPS has yielded a better binding capacity and delivery profile. The adsorption isotherm at pH 4.2 fitted the Langmuir model and displayed the highest adsorption capacity (71.43 mg mL-1 MPS). Furthermore, the delivery rates of BSA from the MPS under physiological conditions were shown to be dependent on the ionic strength of the buffer and protein loading concentration. Conclusion Economics and scale-up considerations of mesoporous material synthesized via destabilization of colloids by electrolyte indicate the scaleability and commercial viability of this technology as a delivery platform for biopharmaceutical applications.

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The aim of this project was to develop a general theory of stigmergy and a software design pattern to build collaborative websites. Stigmergy is a biological term used when describing some insect swarm-behaviour where 'food gathering' and 'nest building' activities demonstrate the emergence of self-organised societies achieved without an apparent management structure. The results of the project are an abstract model of stigmergy and a software design pattern for building Web 2.0 components exploiting this self-organizing phenomenon. A proof-of-concept implementation was also created demonstrating potential commercial viability for future website projects.

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The purpose of this article is to assess the viability of blanket sustainability policies, such as Building Rating Systems in achieving energy efficiency in university campus buildings. We analyzed the energy consumption trends of 10 LEED-certified buildings and 14 non-LEED certified buildings at a major university in the US. Energy Use Intensity (EUI) of the LEED buildings was significantly higher (EUILEED= 331.20 kBtu/sf/yr) than non-LEED buildings (EUInon-LEED=222.70 kBtu/sf/yr); however, the median EUI values were comparable (EUILEED= 172.64 and EUInon-LEED= 178.16). Because the distributions of EUI values were non-symmetrical in this dataset, both measures can be used for energy comparisons—this was also evident when EUI computations exclude outliers, EUILEED=171.82 and EUInon-LEED=195.41. Additional analyses were conducted to further explore the impact of LEED certification on university campus buildings energy performance. No statistically significant differences were observed between certified and non-certified buildings through a range of robust comparison criteria. These findings were then leveraged to devise strategies to achieve sustainable energy policies for university campus buildings and to identify potential issues with portfolio level building energy performance comparisons.

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In parts of the Indo-Pacific, large-scale exploitation of the green turtle Chelonia mydas continues to pose a serious threat to the persistence of this species; yet very few studies have assessed the pattern and extent of the impact of such harvests. We used demographic and genetic data in an age-based model to investigate the viability of an exploited green turtle stock from Aru, south-east Indonesia. We found that populations are decreasing under current exploitation pressures. The effects of increasingly severe exploitation activities at foraging and nesting habitat varied depending on the migratory patterns of the stock. Our model predicted a rapid decline of the Aru stock in Indonesia under local exploitation pressure and a shift in the genetic composition of the stock. We used the model to investigate the influence of different types of conservation actions on the persistence of the Aru stock. The results show that local management actions such as nest protection and reducing harvests of adult nesting and foraging turtles can have considerable conservation outcomes and result in the long-term persistence of genetically distinct management units. © 2010 The Authors. Animal Conservation © 2010 The Zoological Society of London.

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Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

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Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

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Scarring is a significant medical burden; financially to the health care system and physically and psychologically for patients. Importantly, there have been numerous case reports describing the occurrence of cancer in burn scars. Currently available therapies are not satisfactory due to their undesirable side-effects, complex delivery routes, requirements for long-term use and/or expense. Radix Arnebiae (Zi Cao), a perennial herb, has been clinically applied to treat burns and manage scars for thousands of years in Asia. Shikonin, an active component extracted from Radix Arnebiae, has been demonstrated to induce apoptosis in cancer cells. Apoptosis is an essential process during scar tissue remodelling. It was therefore hypothesized that Shikonin may induce apoptosis in scar-associated cells. This investigation presents the first detailed in vitro study examining the functional responses of scar-associated cells to Shikonin, and investigates the mechanisms underlying these responses. The data obtained suggests that Shikonin inhibits cell viability and proliferation and reduces detectable collagen in scar-derived fibroblasts. Further investigation revealed that Shikonin induces apoptosis in scar fibroblasts by differentially regulating the expression of caspase 3, Bcl-2, phospho-Erk1/2 and phospho-p38. In addition, Shikonin down-regulates the expression of collagen I, collagen III and alpha-smooth muscle actin genes hence attenuating collagen synthesis in scar-derived fibroblasts. In summary, it is demonstrated that Shikonin induces apoptosis and decreases collagen production in scar-associated fibroblasts and may therefore hold potential as a novel scar remediation therapy.

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A simple modular strategy for the synthesis of profluorescent nitroxide containing polymers is described. The incorporation of an epoxide as a pendant functionality on a polymer backbone synthesized using ATRP and subsequent nucleophilic ring-opening with sodium azide gave hydroxyl and azide functionality within a 3-bond radius. Orthogonal coupling chemistry then allowed the independent attachment of fluorophore and nitroxide groups in close proximity, giving rise to a profluorescent polymer. Validation of the viability of these materials as fluorescent sensors is demonstrated through efficient fluorescence switch-on observed when the materials are exposed to a model reductant or carbon-centred radical source.

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This thesis provides the first comprehensive assessment of the economic viability of Australia's Sydney rock oyster industry and forms the bases for future policy and industry management recommendations. In the four separate studies of the thesis, the socio-economic profile of the industry, the market price formation dynamics within Australia's oyster market, efficiency and productivity levels and the potential impact of climate change and market dynamics on the industry's future revenue were investigated. Findings of this project suggest, for example, that market dynamics may pose a greater thread to the future development of this industry than direct effect from climate change.