120 resultados para Adhesion of cells


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Dried plant food products are increasing in demand in the consumer market, leading to continuing research to develop better products and processing techniques. Plant materials are porous structures, which undergo large deformations during drying. For any given food material, porosity and other cellular parameters have a direct influence on the level of shrinkage and deformation characteristics during drying, which involve complex mechanisms. In order to better understand such mechanisms and their interrelationships, numerical modelling can be used as a tool. In contrast to conventional grid-based modelling techniques, it is considered that meshfree methods may have a higher potential for modelling large deformations of multiphase problem domains. This work uses a meshfree based microscale plant tissue drying model, which was recently developed by the authors. Here, the effects of porosity have been newly accounted for in the model with the objective of studying porosity development during drying and its influence on shrinkage at the cellular level. For simplicity, only open pores are modelled and in order to investigate the influence of different cellular parameters, both apple and grape tissues were used in the study. The simulation results indicated that the porosity negatively influences shrinkage during drying and the porosity decreases as the moisture content reduces (when open pores are considered). Also, there is a clear difference in the deformations of cells, tissues and pores, which is mainly influenced by the cell wall contraction effects during drying.

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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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A silk protein, fibroin, was isolated from the cocoons of the domesticated silkworm (Bombyx mori) and cast into membranes to serve as freestanding templates for tissue-engineered corneal cell constructs to be used in ocular surface reconstruction. In this study, we sought to enhance the attachment and proliferation of corneal epithelial cells by increasing the permeability of the fibroin membranes and the topographic roughness of their surface. By mixing the fibroin solution with poly(ethylene glycol) (PEG) of molecular weight 300 Da, membranes were produced with increased permeability and with topographic patterns generated on their surface. In order to enhance their mechanical stability, some PEG-treated membranes were also crosslinked with genipin. The resulting membranes were thoroughly characterized and compared to the non-treated membranes. The PEG-treated membranes were similar in tensile strength to the non-treated ones, but their elastic modulus was higher and elongation lower, indicating enhanced rigidity. The crosslinking with genipin did not induce a significant improvement in mechanical properties. In cultures of a human-derived corneal epithelial cell line (HCE-T), the PEG treatment of the substratum did not improve the attachment of cells and it enhanced only slightly the cell proliferation in the longer term. Likewise, primary cultures of human limbal epithelial cells grew equally well on both non-treated and PEG-treated membranes, and the stratification of cultures was consistently improved in the presence of an underlying culture of irradiated 3T3 feeder cells, irrespectively of PEG-treatment. Nevertheless, the cultures grown on the PEG-treated membranes in the presence of feeder cells did display a higher nuclear-to-cytoplasmic ratio suggesting a more proliferative phenotype. We concluded that while the treatment with PEG had a significant effect on some structural properties of the B. mori silk fibroin (BMSF) membranes, there were minimal gains in the performance of these materials as a substratum for corneal epithelial cell growth. The reduced mechanical stability of freestanding PEG-treated membranes makes them a less viable choice than the non-treated membranes.

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Cisplatin (cis-diamminedichloroplatinum (II)), is a platinum based chemotherapeutic employed in the clinic to treat patients with lung, ovarian, colorectal or head and neck cancers. Cisplatin acts to induce tumor cell death via multiple mechanisms. The best characterized mode of action is through irreversible DNA cross-links which activate DNA damage signals leading to cell death via the intrinsic mitochondrial apoptosis pathway. However, the primary issue with cisplatin is that while patients initially respond favorably, sustained cisplatin therapy often yields chemoresistance resulting in therapeutic failure. In this chapter, we review the DNA damage and repair pathways that contribute to cisplatin resistance. We also examine the cellular implications of cisplatin resistance that may lead to selection of subpopulations of cells within a tumor. In better understanding the mechanisms conferring cisplatin resistance, novel targets may be identified to restore drug sensitivity.

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Interleukin-10 (IL-10) is an important immunoregulatory cytokine produced by various types of cells. Researchers describe here the isolation and characterization of olive flounder IL-10 (ofIL-10) cDNA and genomic organization. The ofIL-10 gene encodes a 187 amino acid protein and is composed of a five exon/four intron structure, similar to other known IL-10 genes. The ofIL-10 promoter sequence analysis shows a high level of homology in putative binding sites for transcription factors which are sufficient for transcriptional regulation ofIL-10. Important structural residues are maintained in the ofIL-10 protein including the four cysteines responsible for the two intra-chain disulfide bridges reported for human IL-10 and two extra cysteine residues that exist only in fish species. The phylogenetic analysis clustered ofIL-10 with other fish IL-10s and apart from mammalian IL-10 molecules. Quantitative real-time Polymerase Chain Reaction (PCR) analysis demonstrated ubiquitous ofIL-10 gene expression in the 13 tissues examined. Additionally, the induction of ofIL-10 gene expression was observed in the kidney tissue from olive flounder infected with bacteria (Edawardsiella tarda) or virus (Viral Hemorrhagic Septicemia Virus; VHSV). These data indicate that IL-10 is an important immune regulator that is conserved strictly genomic organization and function during the evolution of vertebrate immunity.

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Ross River virus (RRV) is the predominant cause of epidemic polyarthritis in Australia, yet the antigenic determinants are not well defined. We aimed to characterize epitope(s) on RRV-E2 for a panel of monoclonal antibodies (MAbs) that recognize overlapping conformational epitopes on the E2 envelope protein of RRV and that neutralize virus infection of cells in vitro. Phage-displayed random peptide libraries were probed with the MAbs T1E7, NB3C4, and T10C9 using solution-phase and solid-phase biopanning methods. The peptides VSIFPPA and KTAISPT were selected 15 and 6 times, respectively, by all three of the MAbs using solution-phase biopanning. The peptide LRLPPAP was selected 8 times by NB3C4 using solid-phase biopanning; this peptide shares a trio of amino acids with the peptide VSIFPPA. Phage that expressed the peptides VSIFPPA and LRLPPAP were reactive with T1E7 and/or NB3C4, and phage that expressed the peptides VSIFPPA, LRLPPAP, and KTAISPT partially inhibited the reactivity of T1E7 with RRV. The selected peptides resemble regions of RRV-E2 adjacent to sites mutated in neutralization escape variants of RRV derived by culture in the presence of these MAbs (E2 210-219 and 238-245) and an additional region of E2 172-182. Together these sites represent a conformational epitope of E2 that is informative of cellular contact sites on RRV.

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Anti-cancer drug loaded-nanoparticles (NPs) or encapsulation of NPs in colon-targeted delivery systems shows potential for increasing the local drug concentration in the colon leading to improved treatment of colorectal cancer. To investigate the potential of the NP-based strategies for colon-specific delivery, two formulations, free Eudragit® NPs and enteric-coated NP-loaded chitosan–hypromellose microcapsules (MCs) were fluorescently-labelled and their tissue distribution in mice after oral administration was monitored by multispectral small animal imaging. The free NPs showed a shorter transit time throughout the mouse digestive tract than the MCs, with extensive excretion of NPs in faeces at 5 h. Conversely, the MCs showed complete NP release in the lower region of the mouse small intestine at 8 h post-administration. Overall, the encapsulation of NPs in MCs resulted in a higher colonic NP intensity from 8 h to 24 h post-administration compared to the free NPs, due to a NP ‘guarding’ effect of MCs during their transit along mouse gastrointestinal tract which decreased NP excretion in faeces. These imaging data revealed that this widely-utilised colon-targeting MC formulation lacked site-precision for releasing its NP load in the colon, but the increased residence time of the NPs in the lower gastrointestinal tract suggests that it is still useful for localised release of chemotherapeutics, compared to NP administration alone. In addition, both formulations resided in the stomach of mice at considerable concentrations over 24 h. Thus, adhesion of NP- or MC-based oral delivery systems to gastric mucosa may be problematic for colon-specific delivery of the cargo to the colon and should be carefully investigated for a full evaluation of particulate delivery systems.

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Random walk models are often used to interpret experimental observations of the motion of biological cells and molecules. A key aim in applying a random walk model to mimic an in vitro experiment is to estimate the Fickian diffusivity (or Fickian diffusion coefficient),D. However, many in vivo experiments are complicated by the fact that the motion of cells and molecules is hindered by the presence of obstacles. Crowded transport processes have been modeled using repeated stochastic simulations in which a motile agent undergoes a random walk on a lattice that is populated by immobile obstacles. Early studies considered the most straightforward case in which the motile agent and the obstacles are the same size. More recent studies considered stochastic random walk simulations describing the motion of an agent through an environment populated by obstacles of different shapes and sizes. Here, we build on previous simulation studies by analyzing a general class of lattice-based random walk models with agents and obstacles of various shapes and sizes. Our analysis provides exact calculations of the Fickian diffusivity, allowing us to draw conclusions about the role of the size, shape and density of the obstacles, as well as examining the role of the size and shape of the motile agent. Since our analysis is exact, we calculateDdirectly without the need for random walk simulations. In summary, we find that the shape, size and density of obstacles has a major influence on the exact Fickian diffusivity. Furthermore, our results indicate that the difference in diffusivity for symmetric and asymmetric obstacles is significant.

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Embryonic development involves diffusion and proliferation of cells, as well as diffusion and reaction of molecules, within growing tissues. Mathematical models of these processes often involve reaction–diffusion equations on growing domains that have been primarily studied using approximate numerical solutions. Recently, we have shown how to obtain an exact solution to a single, uncoupled, linear reaction–diffusion equation on a growing domain, 0 < x < L(t), where L(t) is the domain length. The present work is an extension of our previous study, and we illustrate how to solve a system of coupled reaction–diffusion equations on a growing domain. This system of equations can be used to study the spatial and temporal distributions of different generations of cells within a population that diffuses and proliferates within a growing tissue. The exact solution is obtained by applying an uncoupling transformation, and the uncoupled equations are solved separately before applying the inverse uncoupling transformation to give the coupled solution. We present several example calculations to illustrate different types of behaviour. The first example calculation corresponds to a situation where the initially–confined population diffuses sufficiently slowly that it is unable to reach the moving boundary at x = L(t). In contrast, the second example calculation corresponds to a situation where the initially–confined population is able to overcome the domain growth and reach the moving boundary at x = L(t). In its basic format, the uncoupling transformation at first appears to be restricted to deal only with the case where each generation of cells has a distinct proliferation rate. However, we also demonstrate how the uncoupling transformation can be used when each generation has the same proliferation rate by evaluating the exact solutions as an appropriate limit.

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Many processes during embryonic development involve transport and reaction of molecules, or transport and proliferation of cells, within growing tissues. Mathematical models of such processes usually take the form of a reaction-diffusion partial differential equation (PDE) on a growing domain. Previous analyses of such models have mainly involved solving the PDEs numerically. Here, we present a framework for calculating the exact solution of a linear reaction-diffusion PDE on a growing domain. We derive an exact solution for a general class of one-dimensional linear reaction—diffusion process on 0of the growing domain. Comparing our exact solutions with numerical approximations confirms the veracity of the method. Furthermore, our examples illustrate a delicate interplay between: (i) the rate at which the domain elongates, (ii) the diffusivity associated with the spreading density profile, (iii) the reaction rate, and (iv) the initial condition. Altering the balance between these four features leads to different outcomes in terms of whether an initial profile, located near x = 0, eventually overcomes the domain growth and colonizes the entire length of the domain by reaching the boundary where x = L(t).

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Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

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BACKGROUND Hydrogel-based cell cultures are excellent tools for studying physiological events occurring in the growth and proliferation of cells, including cancer cells. Diffusion magnetic resonance is a physical technique that has been widely used for the characterisation of biological systems as well as hydrogels. In this work, we applied diffusion magnetic resonance imaging (MRI) to hydrogel-based cultures of human ovarian cancer cells. METHODS Diffusion-weighted spin-echo MRI measurements were used to obtain spatially-resolved maps of apparent diffusivities for hydrogel samples with different compositions, cell loads and drug (Taxol) treatment regimes. The samples were then characterised using their diffusivity histograms, mean diffusivities and the respective standard deviations, and pairwise Mann-Whitney tests. The elastic moduli of the samples were determined using mechanical compression testing. RESULTS The mean apparent diffusivity of the hydrogels was sensitive to the polymer content, cell load and Taxol treatment. For a given sample composition, the mean apparent diffusivity and the elastic modulus of the hydrogels exhibited a negative correlation. CONCLUSIONS Diffusivity of hydrogel-based cancer cell culture constructs is sensitive to both cell proliferation and Taxol treatment. This suggests that diffusion-weighted imaging is a promising technique for non-invasive monitoring of cancer cell proliferation in hydrogel-based, cellularly-sparse 3D cell cultures. The negative correlation between mean apparent diffusivity and elastic modulus suggests that the diffusion coefficient is indicative of the average density of the physical microenvironment within the hydrogel construct.

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Cancer stem cells (CSCs) are a vital subpopulation of cells to target for the treatment of cancers. In oesophageal squamous cell carcinoma (ESCC), there are several markers such as CD44, ALDH, Pygo2, MAML1, Twist1, Musashi1, Side population (SP), CD271 and CD90 that have been proposed to identify the cancer stem cells in individual cancer masses. It has also been demonstrated that stem cell markers like ALDH1, HIWI, Oct3/4, ABCG2, SOX2, SALL4, BMI-1, NANOG, CD133 and podoplanin are associated with patient's prognosis, pathological stages, cancer recurrence and therapy resistance. Finding new cancer stem cell targets or designing drugs to manipulate the known molecular targets in CSCs could be useful for improvements in clinical outcomes of the disease. To conclude, data suggest that CSCs in oesophageal squamous cell carcinoma are related to resistance to therapy and poor prognosis of patients with ESCC. Therefore, innovative insights into CSC biology and CSC-targeted therapies will help to achieve more effective management of patients with oesophageal squamous cell carcinoma.

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In this study, we investigated the expression profiles and clinicopathological significance of miR-126 in large cohort of patients with colorectal cancers as well the cellular repercussions of miR-126 in colon cancer cells along with its targets in-vitro. Down regulation of miR-126 expression was associated with histological subtypes, peri-neural tumour infiltration, microsatellite instability and pathological staging of colorectal cancers (p<0.05). Low miR-126 expression was also associated with poorer survival in patients with colorectal cancer. Analysis of matched tissues from the same patient revealed that approximately 70% of the tested patients had similar levels of expression of miR-126 in primary cancer and cancer metastases in both lymph node and distant metastases. In addition, induced overexpression of miR-126 showed reduced cell proliferation, increased apoptosis and decreased accumulation of cells in the G0-G1 phase of the colon cancer cells. Furthermore, SW480(+miR-126) cells showed reduced BCL-2 and increased P53 protein expression. To conclude, deregulation of miR-126 in colorectal cancer at the tissue and cellular levels as well as its correlation with various clinicopathological parameters confirm the cancer suppressive role of miR-126 in colorectal cancer.

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The detailed molecular mechanisms underlying the regulation of sleep duration in mammals are still elusive. To address this challenge, we constructed a simple computational model, which recapitulates the electrophysiological characteristics of the slow-wave sleep and awake states. Comprehensive bifurcation analysis predicted that a Ca2+-dependent hyperpolarization pathway may play a role in slow-wave sleep and hence in the regulation of sleep duration. To experimentally validate the prediction, we generate and analyze 21 KO mice. Here we found that impaired Ca2+-dependent K+ channels (Kcnn2 and Kcnn3), voltage-gated Ca2+ channels (Cacna1g and Cacna1h), or Ca2+/calmodulin-dependent kinases (Camk2a and Camk2b) decrease sleep duration, while impaired plasma membrane Ca2+ ATPase (Atp2b3) increases sleep duration. Pharmacological intervention and whole-brain imaging validated that impaired NMDA receptors reduce sleep duration and directly increase the excitability of cells. Based on these results, we propose a hypothesis that a Ca2+-dependent hyperpolarization pathway underlies the regulation of sleep duration in mammals.