Maxence Bigerelle

Qualitative and quantitative study of human osteoblast adhesion on materials with various surface roughnesses

We quantitatively evaluated the adhesion of human osteoblasts on orthopedic metallic substrates (Ti6Al4V alloy) with various surface roughnesses at several times after inoculation and studied its correlation with qualitative changes in the expression of adhesion proteins and with parameters extensively describing the surface topographies. Cells were orientated in a parallel order on polished surfaces. This orientation was not affected by residual grooves after polishing. On sandblasted surfaces the cells never attained confluence and had a stellate shape, and the cell layer had no particular organization. Extracellular matrix (fibronectin, type I collagen, osteopontin) and cytoskeletal protein (actin, vinculin) orientation reflected the cell layer organization. In our experiment human osteoblasts expressed alpha3beta1 integrin but not alpha2beta1 integrin. In addition to currently analyzed roughness magnitude parameters, we calculated roughness organization parameters (fractal dimension parameters) of the substrates. We observed lower adhesion and proliferation on less organized surfaces (i.e., sandblasted ones). The significant statistical correlation observed between fractal dimension parameters (describing surface roughness organization) and cell parameters adds a new concept to the studies of substratum roughness influence on cell behavior. An attempt at modelization of the cell-surface interaction was made that includes the influence of fractal dimensions parameters.

The relative influence of the topography and chemistry of TiAl6V4 surfaces on osteoblastic cell behaviour

Proliferation and adhesion of mouse (MC3T3-E1) osteoblastic cells and primary human osteoblastic cells were carried out on Ti6Al4V titanium alloy samples with varied surface roughnesses. Mechanically or manually polished surfaces were prepared to produce respectively non-oriented or oriented residual polishing grooves. Sand-blasted surfaces were prepared using 500 microm or 3 mm alumina particles. Surface roughness parameters showed a negative correlation in comparison to proliferation and adhesion parameters. X-ray microprobe chemical surface microanalysis showed complete disturbance of the surface element composition of the Ti6Al4V alloy following sand-blasting treatment. An AlOx-enriched layer was observed on sample surfaces. This may lead to the suspicion that the concomittant effect of surface roughness amplitude and AlOx surface concentration has an effect on osteoblastic cell proliferation and adhesion. These findings show the significance of chemical surface analysis after any surface treatment of titanium-based implants before any biological use.

In vitro MC3T3 osteoblast adhesion with respect to surface roughness of Ti6Al4V substrates.

This work investigates the role of the surface roughness of Ti6Al4V on the cell morphology, proliferation and adhesion, and in particular on the variation of the expression of cell adhesion proteins. Standardised test samples with five different surface preparations are used: sandblasted, 80, 1200, and 4000 grade polished, mirror polished. Surface roughness is analysed by Scanning Electron Microscopy and LASER Confocal Microscopy. Cell culture experiments are performed with MC3T3-E1 mouse osteoblasts after 3 days culture: proliferation rate, morphology and adhesion are assessed. The variations of expression of cell adhesion proteins are evidenced by indirect immune fluorescence method: actin from the cytoskeleton, vinculin from the focal adhesion complex, fibronectin and collagen I from the extracellular matrix. The results reveal a clear influence of surface roughness of Ti6Al4V on cell proliferation, morphology and adhesion. A significant correlation is established between surface roughness and cell growth. More the surface is smooth more the osteoblasts proliferate and appear spread out on the test samples. In addition, the expression of adhesion proteins varies with respect to the surface roughness. These results indicate a direct relationship between the decrease of cell adhesion and the increase of cell proliferation on mirror polished materials.

Fractals and fracture

The relation between quantities resulting from fracture energetics and those describing the geometrical structure of a surface is of fundamental importance in investigating the physical nature of a fracture. Since the Mandelbrot’s works, fractal geometry has been extensively applied to characterize the roughness of fracture surfaces and to correlate it with mechanical properties. We will first make a survey of several experimental methods to determine the fractal dimension, Df, according to the roughness of fracture surfaces. Then we will discuss the experimental results reported in the bibliography and the relations inferred to correlate the fractal dimension of fracture surfaces with mechanical properties. These results show that a general conclusion cannot easily be drawn. Some works report a positive variation of fracture toughness along with Df and others a negative one. To other researchers, there is no correlation and the fractal dimension of the fracture surface is a universal constant. The discrepancy between these results is related to the methods used to calculate the fractal dimension. Theoretical and experimental problems exist and have to be solved before correlating the fractal dimension to mechanical behaviour. # 1998 Elsevier Science Ltd. All rights reserved.

Fractal dimension and classification of music

Abstract The fractal aspect of different kinds of music was analyzed in keeping with the time domain. The fractal dimension of a great number of different musics (180 scores) is calculated by the Variation method. By using an analysis of variance, it is shown that fractal dimension helps discriminate different categories of music. Then, we used an original statistical technique based on the Bootstrap assumption to find a time window in which fractal dimension reaches a high power of music discrimination. The best discrimination is obtained between 1/44100 and 16/44100 Hertz. We admit that to distinguish some different aspects of music well, the high information quantity is obtained in the high frequency domain. By calculating fractal dimension with the ANAM method, it was statistically proven that fractal dimension could distinguish different kinds of music very well: musics could be classified by their fractal dimensions.

Estimating the parameters of a generalized lambda distribution

The method of moments is a popular technique for estimating the parameters of a generalized lambda distribution (GLD), but published results suggest that the percentile method gives superior results. However, the percentile method cannot be implemented in an automatic fashion, and automatic methods, like the starship method, can lead to prohibitive execution time with large sample sizes. A new estimation method is proposed that is automatic (it does not require the use of special tables or graphs), and it reduces the computational time. Based partly on the usual percentile method, this new method also requires choosing which quantile u to use when fitting a GLD to data. The choice for u is studied and it is found that the best choice depends on the final goal of the modeling process. The sampling distribution of the new estimator is studied and compared to the sampling distribution of estimators that have been proposed. Naturally, all estimators are biased and here it is found that the bias becomes negligible with sample sizes n>=2x10^3. The .025 and .975 quantiles of the sampling distribution are investigated, and the difference between these quantiles is found to decrease proportionally to 1/n. The same results hold for the moment and percentile estimates. Finally, the influence of the sample size is studied when a normal distribution is modeled by a GLD. Both bounded and unbounded GLDs are used and the bounded GLD turns out to be the most accurate. Indeed it is shown that, up to n=10^6, bounded GLD modeling cannot be rejected by usual goodness-of-fit tests.

Relevance of roughness parameters for describing and modelling machined surfaces

Describing and modelling a machined surface require the selection of relevant roughness parameters. However, this selection is difficult since a machined surface morphology can be described by a large number of roughness parameters.This investigation focuses on the roughness of metallic surfaces taking for two applications: a) the description of machined surface morphologies produced by grinding b) the relationships between machined surface morphologies (grinding or cold-rolling) and their brightness level when irradiated by the white light beam of an optical glossmeter used for industrial surface quality control. For each application, the aim is to determine, from an objective quantitative point of view, the relevance of one hundred or so surface roughness parameters. To reach this objective, a specific software program has been developed to determine a ranking of relevance thanks to the calculation of a computed statistical index of performance.The statistical results of this study show that the fractal dimension estimated by an original method is the most relevant roughness parameter to describe the surface morphology after grinding or rolling. Because of this relevance, this roughness parameter has also to be taken into consideration in models showing the interactions between machined surfaces and an optical wave. The methodology presented in this study can be a useful tool in the quality control phase to keep under control the fabrication process parameters of manufactured objects in industrial environments.

The computer-based bootstrap method as a tool to select a relevant surface roughness parameter

The aim of this paper is to present how to make the most of the recent and powerful statistical computer-based bootstrap method (CBBM) in roughness studies. This work shows that this statistical method can help to determine quantitatively, and without preconception, the most relevant roughness parameter that characterises the surface morphology of a manufactured product as far as a correlation with a particular function, property or application is concerned. The efficiency of this statistical method is illustrated in this paper describing the relationships between the brightness level and the surface roughness of cold-rolled low carbon steel strips; the relevance of 100 or so roughness parameters was studied via a computer software we have been upgrading for a few years.

Bootstrap analysis of FCGR, application to the Paris relationship and to lifetime prediction

Dealing with fatigue crack propagation, this paper aims to report on a statistical method to determine the coefficients C and n of the Paris relationship and the range along which the equation holds. The Probability Density Function (PDF) of those coefficients was calculated using a bootstrap technique. Then a 3-segment piece-wise linear regression FCGR was used to modelize the whole fatigue crack growth data. The statistical results are finally applied on a classical fracture mechanic problem to obtain the PDF lifetime prevision. The PDF lifetime obeys a Gaussian or lognormal PDF which depends on the variance of the initial cracks length.

Existence of a typical threshold in the response of human mesenchymal stem cells to a peak and valley topography.

Our objective in this study was to determine whether a threshold in sensitivity of human mesenchymal stem cells (hMSC) to isotropic roughness exists. Using electrical discharge machining a very wide range of roughnesses (1.2μm<R(a)<21μm) with a perfectly isotropic, fractal and self-affine topography can be produced on titanium, with a range of roughness overlapping the hMSC length dimensions. The curve of the number of adherent hMSC after 2days culture as a function of roughness showed a U-shape with a minimum number of attached cells for a roughness amplitude R(a)=4.5μm and a distance between surface features (width of peaks and valleys) S(m)=110μm. The maximum cell number was observed at the lowest and highest roughnesses. Due to this very wide range of roughness it was possible to demonstrate that the response of hMSC to roughness varies with the dimensions of the surface features relative to the cell size. Above or below their own size hMSC essentially adhere to the nano and submicron features. When the surface displays features about the same size as hMSC the curvature of these surface features will decrease the number of attached cells by a factor of two. A modelling approach is proposed to help the interpretation of these results. It is hypothesized that this minimal adhesion is a consequence of an unfavourable stress imposed on the cell cytoskeleton.