Cell interactions of osteoarthritic subchondral bone osteoblasts and articular chondrocytes aggravate MMP-2 and MMP-9 production through the mediation of ERK1/2 and JNK phosphorylation

Matrix Metalloproteinases (MMP) play a key role in osteoarthritis (OA) development. The aim of the present study was to investigate whether, the cross-talk between subchondral bone osteoblasts (SBOs) and articular cartilage chondrocytes (ACCs) in OA alters the expression and regulation of MMPs, and also to test the potential involvement of mitogen activated protein kinase (MAPK) signalling pathway during this process.

Exploring retinal and functional markers of diabetic neuropathy

Diabetic peripheral neuropathy (DPN) is one of the most debilitating complications of diabetes. DPN is a major cause of foot ulceration and lower limb amputation. Early diagnosis and management is a key factor in reducing morbidity and mortality. Current techniques for clinical assessment of DPN are relatively insensitive for detecting early disease or involve invasive procedures such as skin biopsies. There is a need for less painful, non-invasive and safe evaluation methods. Eye care professionals already play an important role in the management of diabetic retinopathy; however recent studies have indicated that the eye may also be an important site for the diagnosis and monitoring of neuropathy. Corneal nerve morphology has been shown to be a promising marker of diabetic neuropathy occurring elsewhere in the body, and emerging evidence tentatively suggests that retinal anatomical markers and a range of functional visual indicators could similarly provide useful information regarding neural damage in diabetes – although this line of research is, as yet, less well established. This review outlines the growing body of evidence supporting a potential diagnostic role for retinal structure and visual functional markers in the diagnosis and monitoring of peripheral neuropathy in diabetes.

Persons with age-related maculopathy risk genotypes and clinically normal eyes have reduced mesopic vision

PURPOSE: To determine if participants with normal visual acuity, no ophthalmoscopically signs of age-related maculopathy (ARM) in both eyes and who are carriers of the CFH, LOC387715 and HRTA1 high-risk genotypes (“gene-positive”) have impaired rod- and cone-mediated mesopic visual function compared to persons who do not carry the risk genotypes (“gene-negative”).---------- METHODS: Fifty-three Caucasian study participants (mean 55.8 ± 6.1) were genotyped for CFH, LOC387715/ARMS2 and HRTA1 polymorphisms. We genotyped single nucleotide polymorphisms (SNPs) in the CFH (rs380390), LOC387715/ARMS2 (rs10490924) and HTRA1 (rs11200638) genes using Applied Biosystems optimised TaqMan assays. We determined the critical fusion frequency (CFF) mediated by cones alone (Long, Middle and Short wavelength sensitive cones; LMS) and by the combined activities of cones and rods (LMSR). The stimuli were generated using a 4-primary photostimulator that provides independent control of the photoreceptor excitation under mesopic light levels. Visual function was further assessed using standard clinical tests, flicker perimetry and microperimetry.---------- RESULTS: The mesopic CFF mediated by rods and cones (LMSR) was significantly reduced in gene-positive compared to gene-negative participants after correction for age (p=0.03). Cone-mediated CFF (LMS) was not significantly different between gene-positive and -negative participants. There were no significant associations between flicker perimetry and microperimetry and genotype.---------- CONCLUSIONS: This is the first study to relate ARM risk genotypes with mesopic visual function in clinically normal persons. These preliminary results could become of clinical importance as mesopic vision may be used to document sub-clinical retinal changes in persons with risk genotypes and to determine whether those persons progress into manifest disease.

Magnocellular and parvocellular pathway mediated luminance contrast discrimination in amblyopia

To evaluate whether luminance contrast discrimination losses in amblyopia on putative magnocellular (MC) and parvocellular (PC) pathway tasks reflect deficits at retinogeniculate or cortical sites. Fifteen amblyopes including six anisometropes, seven strabismics, two mixed and 12 age-matched controls were investigated. Contrast discrimination was measured using established psychophysical procedures that differentiate MC and PC processing. Data were described with a model of the contrast response of primate retinal ganglion cells. All amblyopes and controls displayed the same contrast signatures on the MC and PC tasks, with three strabismics having reduced sensitivity. Amblyopic PC contrast gain was similar to electrophysiological estimates from visually normal, non-human primates. Sensitivity losses evident in a subset of the amblyopes reflect cortical summation deficits, with no change in retinogeniculate contrast responses. The data do not support the proposal that amblyopic contrast sensitivity losses on MC and PC tasks reflect retinogeniculate deficits, but rather are due to anomalous post-retinogeniculate cortical processing of retinal signals.

Effects of the architecture of tissue engineering scaffolds on cell seeding and culturing

The advance of rapid prototyping techniques has significantly improved control over the pore network architecture of tissue engineering scaffolds. In this work we assessed the influence of scaffold pore architecture on cell seeding and static culturing, by comparing a computer‐designed gyroid architecture fabricated by stereolithography to a random‐pore architecture resulting from salt‐leaching. The scaffold types showed comparable porosity and pore size values, but the gyroid type showed a more than tenfold higher permeability due to the absence of size‐limiting pore interconnections. The higher permeability significantly improved the wetting properties of the hydrophobic scaffolds, and increased the settling speed of cells upon static seeding of immortalised mesenchymal stem cells. After dynamic seeding followed by 5 days of static culture, gyroid scaffolds showed large cell populations in the centre of the scaffold, while salt‐leached scaffolds were covered with a cell‐sheet on the outside and no cells were found in the scaffold centre. It was shown that interconnectivity of the pores and permeability of the scaffold prolongs the time of static culture before overgrowth of cells at the scaffold periphery occurs. Furthermore, novel scaffold designs are proposed to further improve the transport of oxygen and nutrients throughout the scaffolds, and to create tissue engineering grafts with designed, pre‐fabricated vasculature.

Cell invasion with proliferation mechanisms motivated by time-lapse data

Cell invasion involves a population of cells which are motile and proliferative. Traditional discrete models of proliferation involve agents depositing daughter agents on nearest- neighbor lattice sites. Motivated by time-lapse images of cell invasion, we propose and analyze two new discrete proliferation models in the context of an exclusion process with an undirected motility mechanism. These discrete models are related to a family of reaction- diffusion equations and can be used to make predictions over a range of scales appropriate for interpreting experimental data. The new proliferation mechanisms are biologically relevant and mathematically convenient as the continuum-discrete relationship is more robust for the new proliferation mechanisms relative to traditional approaches.

Migration of breast cancer cells : understanding the roles of volume exclusion and cell-to-cell adhesion

We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

Solid freeform fabrication of hydrogel structures and cell encapsulation

We aim to fabricate computer-controlled hydrogel structures containing viable encapsulated cells to overcome the low seeding densities which are inherent to most pre-fabricated scaffold systems.

Selective accumulation of virus-specific CD8+ T cells within the peripheral blood stem cell compartment

The absence of cellular immunity is central to the pathogenesis of herpesvirus-mediated diseases after allogeneic hemopoietic stem cell transplantation (HSCT). For both bone marrow (BM)– and granulocyte-colony stimulating factor–mobilized peripheral blood stem cells (PBSCs) HSCT, donor-derived Epstein-Barr virus (EBV) and cytomegalovirus (CMV) peptide–specific CD8+ T cells clones undergo early expansion and persist long-term, with additional diversification arising from novel antigen-specific clones from donor-derived progenitors. Whether BM or PBSC is the superior source of antiviral CD8+ T cells is unclear. Given that PBSC has largely replaced BM as a source of stem cells for HSCT, it is unlikely that herpesvirus effector T-cell reconstitution will ever be compared prospectively. PBSC grafts contain 10 to 30 times more T cells than BM and a randomized study found proven viral infections were more frequent in BM than PBSC recipients, suggesting viral-specific T-cell immunity is enhanced in PBSC. Recently Moss showed in lung cancer patients that herpesvirus-specific BM-derived CD8+ T cells have unique homing properties relative to herpesvirus-specific CD8+ T cells present in unmobilized peripheral blood (PB). Immunodominant EBV-lytic peptide–specific CD8+ T cells were enriched in BM but were reduced for CMV peptide–specific CD8+ T cells relative to PB. EBV-latent peptide–specific CD8+ T cells were equivalent, which has relevance in the context of posttransplantation lymphoproliferative disorder for which impaired EBV-latent CD8+ T-cell immunity is a risk-factor. A comparison of herpesvirus-specific cellular immunity in PBSC versus PB has yet to be performed.

Modelling cell separation during plant organ abscission

A simple mathematical model is presented to describe the cell separation process that plants undertake in order to deliberately shed organs. The focus here is on modelling the production of the enzyme polygalacturonase, which breaks down pectin that provides natural cell-to-cell adhesion in the localised abscission zone. A coupled system of three ordinary differential equations is given for a single cell, and then extended to hold for a layer of cells in the abscission zone. Simple observations are made based on the results of this preliminary model and, furthermore, a number of opportunities for applied mathematicians to make contributions in this subject area are discussed.

A chimeric vitronectin : IGF-I protein supports feeder-cell-free and serum-free culture of human embryonic stem cells

This paper was retracted by the Journal of Stem Cells and Development on February 15, 2013.

Mechanistic investigations into interactions between IGF-I and IGFBPs and their impact on facilitating cell migration on vitronectin

Numerous studies have reported links between insulin-like growth factors (IGFs) and the extra-cellular matrix protein vitronectin (VN). We ourselves have reported that IGF-I binds to VN via IGF-binding proteins (IGFBPs) to stimulate HaCaT and MCF-7 cell migration. Here, we detail the functional evaluation of IGFBP-1, -2, -3, -4 and -6 in the presence and absence of IGF-I and VN. The data presented here, combined with our prior data on IGFBP-5, suggest that IGFBP-3, -4 and -5 are the most effective at stimulating cell migration in combination with IGF-I and VN. In addition, we demonstrate that different regions within IGFBP-3 and -4 are critical for complex formation. Furthermore, we examine whether multi-protein complexes of IGF-I and IGFBPs associated with fibronectin and collagen IV are also able to enhance functional biological responses.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.