824 resultados para Limited dependent variable regression


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In this paper, we introduce the method of leaps and bounds regression which can be used to select variables quickly and obtain the best regression models. These models contain one variable, two variables, three variables and so on. The results obtained by using leaps and bounds regression were compared with those achieved by using stepwise regression to lead to the conclusion that leaps and bounds regression is an effective method.

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Five new chiral liquid crystal systems induced by intermolecular hydrogen bonding between 4-[(S)-2-chloro-3-methyl]butyroyloxy-4'-stilbazole (MBSB, proton acceptor) and 4-alkoxybenzoic acids (nBA, proton donors) were prepared. Their liquid crystalline properties were investigated by DSC and polarized optical microscopy. Chiral nematic and chiral smectic phases were observed, and the thermal stability of one complex was studied through temperature dependent infrared spectroscopy.

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Effects of stocking density on seston dynamics and filtering and biodeposition by the suspension-cultured Zhikong scallop Chlamys farreri Jones et Preston in a eutrophic bay (Sishili Bay, northern China), were determined in a 3-month semi-field experiment with continuous flow-through seawater from the bay. Results showed that the presence of the scallops could strongly decrease seston and chlorophyll a concentrations in the water column. Moreover, in a limited water column, increasing scallop density could cause seston depletion due to scallop's filtering and biodeposition process, and impair scallop growth. Both filtration rate and biodeposition rate of C. farreri showed significant negative correlation with their density and positive relationship with seston concentration. Calculation predicts that the daily removal of suspended matter from water column by the scallops in Sishili Bay ecosystem can be as high as 45% of the total suspended matter; and the daily production of biodeposits by the scallops in early summer in farming zone may amount to 7.78 g m(-2), with daily C, N and P biodeposition rates of 3.06 x 10(-1), 3.86 x 10(-2) and 9.80 x 10(-3) g m(-2), respectively. The filtering and biodeposition by suspension-cultured scallops could substantially enhance the deposition of total suspended particulate material, suppress accumulation of particulate organic matter in water column, and increase the flux of C, N and P to benthos, strongly enhancing pelagic-benthic coupling. It was suggested that the filtering-biodeposition process by intensively suspension-cultured bivalve filter-feeders could exert strong top-down control on phytoplankton biomass and other suspended particulate material in coastal ecosystems. This study also indicated that commercially suspension-cultured bivalves may simultaneously and potentially aid in mitigating eutrophication pressures on coastal ecosystems subject to anthropogenic N and P loadings, serving as a eutrophic-environment bioremediator. The ecological services (e.g. filtering capacity, top-down control, and benthic-pelagic coupling) functioned by extractive bivalve aquaculture should be emphasized in coastal ecosystems. (c) 2005 Elsevier B.V. All rights reserved.

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Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites (including temperate meadow steppe,temperate steppe, temperate desert steppe and alpine meadow) were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity (ANPP) and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation (MAP) was the main factor determining spatial distribution of grassland ANPP (r~2 = 0.61,P < 0.01); while temporally, no significant relationship was found between the variance of AN PP and inter-annual precipitation for the four types of grassland. However, after dividing annual precipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow steppe, the key variable determining inter-annual change of ANPP was last August-May precipitation (r~2= 0.47, P = 0.01); for the temperate steppe, the key variable was July precipitation (r~2 = 0.36, P = 0.02); for the temperate desert steppe, the key variable was April-June precipitation (r~2 = 0.51, P <0.01); for the alpine meadow, the key variable was last September-May precipitation (r~2 = 0.29, P < 0.05). In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.

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A new continuous configuration time-dependent self-consistent field method has been developed to study polyatomic dynamical problems by using the discrete variable representation for the reaction system, and applied to a reaction system coupled to a bath. The method is very efficient because the equations involved are as simple as those in the traditional single configuration approach, and can account for the correlations between the reaction system and bath modes rather well. (C) American Institute of Physics.

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Background: Obesity is the most important health challenge faced at a global level and represents a rapidly growing problem to the health of populations. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. The normalisation of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation. Recognition of the problem is a key component of obesity management and it remains especially crucial to address this issue. A large amount of research has been undertaken on obesity however, limited research has been undertaken using the Health Belief Model. Aim: The aim of the research was to determine factors relating to motivation to change behaviour in individuals who perceive themselves to be overweight and investigate whether the constructs of the Health Belief Model help to explain motivation to change behaviour. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data Collection: Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Sample: A sample of 202 men and women who perceived themselves to be overweight participated in the research. Results: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p =<0.019) and environmental barriers to physical activity (p=<0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p<0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. The current study demonstrated the limited applicability of the Health Belief Model constructs to motivation to change behaviour, as not all core dimensions proved significant predictors of the dependant variable.

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We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process. We approach this problem through the Bayesian variable selection framework, where we assume that the covariates lie on an undirected graph and formulate an Ising prior on the model space for incorporating structural information. Certain computational and statistical problems arise that are unique to such high-dimensional, structured settings, the most interesting being the phenomenon of phase transitions. We propose theoretical and computational schemes to mitigate these problems. We illustrate our methods on two different graph structures: the linear chain and the regular graph of degree k. Finally, we use our methods to study a specific application in genomics: the modeling of transcription factor binding sites in DNA sequences. © 2010 American Statistical Association.

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This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

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Quantitative optical spectroscopy has the potential to provide an effective low cost, and portable solution for cervical pre-cancer screening in resource-limited communities. However, clinical studies to validate the use of this technology in resource-limited settings require low power consumption and good quality control that is minimally influenced by the operator or variable environmental conditions in the field. The goal of this study was to evaluate the effects of two sources of potential error: calibration and pressure on the extraction of absorption and scattering properties of normal cervical tissues in a resource-limited setting in Leogane, Haiti. Our results show that self-calibrated measurements improved scattering measurements through real-time correction of system drift, in addition to minimizing the time required for post-calibration. Variations in pressure (tested without the potential confounding effects of calibration error) caused local changes in vasculature and scatterer density that significantly impacted the tissue absorption and scattering properties Future spectroscopic systems intended for clinical use, particularly where operator training is not viable and environmental conditions unpredictable, should incorporate a real-time self-calibration channel and collect diffuse reflectance spectra at a consistent pressure to maximize data integrity.

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Antigenically variable RNA viruses are significant contributors to the burden of infectious disease worldwide. One reason for their ubiquity is their ability to escape herd immunity through rapid antigenic evolution and thereby to reinfect previously infected hosts. However, the ways in which these viruses evolve antigenically are highly diverse. Some have only limited diversity in the long-run, with every emergence of a new antigenic variant coupled with a replacement of the older variant. Other viruses rapidly accumulate antigenic diversity over time. Others still exhibit dynamics that can be considered evolutionary intermediates between these two extremes. Here, we present a theoretical framework that aims to understand these differences in evolutionary patterns by considering a virus's epidemiological dynamics in a given host population. Our framework, based on a dimensionless number, probabilistically anticipates patterns of viral antigenic diversification and thereby quantifies a virus's evolutionary potential. It is therefore similar in spirit to the basic reproduction number, the well-known dimensionless number which quantifies a pathogen's reproductive potential. We further outline how our theoretical framework can be applied to empirical viral systems, using influenza A/H3N2 as a case study. We end with predictions of our framework and work that remains to be done to further integrate viral evolutionary dynamics with disease ecology.

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Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

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Calanus helgolandicus is a key copepod of the NE Atlantic and fringing shelves, with a distribution that is expanding northwards with oceanic warming. The Plymouth L4 site has warmed over the past 25-years, and experiences large variations in the timing and availability of food for C. helgolandicus. Here we examine the degree to which these changes translate into variation in reproductive output and subsequently C. helgolandicus population size. Egg production rates (eggs female−1 day−1) were maximal in the spring to early-summer period of diatom blooms and high ciliate abundance, rather than during the equally large autumn blooms of autotrophic dinoflagellates. Egg hatch success was lower in spring however, with a greater proportion of naupliar deformities then also. Both the timing and the mean summer abundance of C. helgolandicus (CI–CVI) reflected those of spring total reproductive output. However this relationship was driven by inter-annual variability in female abundance and not that of egg production per female, which ranged only two-fold. Winter abundance of C. helgolandicus at L4 was much more variable than abundance in other seasons, and reflected conditions from the previous growing season. However, these low winter abundances had no clear carry-over signal to the following season’s population size. Overall, the C. helgolandicus population appears to be surprisingly resilient at this dynamic, inshore site, showing no long-term phenology shift and only a four-fold variation in mean abundance between years. This dampening effect may reflect a series of mortality sources, associated with the timing of stratification in the early part of the season, likely affecting egg sinking and loss, plus intense, density-dependent mortality of early stages in mid-summer likely through predation.

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Glucose dependent insulinotropic polypeptide (GIP) is a gastrointestinal hormone with therapeutic potential for type 2 diabetes due to its insulin-releasing and antihyperglycaemic actions. However, development of GIP-based therapies is limited by N-terminal degradation by DPP IV resulting in a very short circulating half-life. Numerous GIP analogues have now been generated exhibiting DPP IV resistance and extended bioactivity profiles. In this study, we report a direct comparison of the long-term antidiabetic actions of three such GIP molecules, N-AcGIP, GIP(LyS(37)PAL) and N-AcGIP(LyS(37)PAL) in obese diabetic (ob/ob) mice. An extended duration of action of each GIP analogue was demonstrated prior to examining the effects of once daily injections (25 nmol kg(-1) body weight) over a 14-day period. Administration of either N-AcGIP, GIP(LyS(37)PAL) or N-AcGIP(LyS37PAL) significantly decreased non-fasting plasma glucose and improved glucose tolerance compared to saline treated controls. All three analogues significantly enhanced glucose and nutrient-induced insulin release, and improved insulin sensitivity. The metabolic and insulin secretory responses to native GIP were also enhanced in 14-day analogue treated mice, revealing no evidence of GIP-receptor desensitization. These effects were accompanied by significantly enhanced pancreatic insulin following N-AcGIP(Lys(37)PAL) and increased islet number and islet size in all three groups. Body weight, food intake and circulating glucagon were unchanged. These data demonstrate the therapeutic potential of once daily injection of enzyme resistant GIP analogues and indicate that N-AcGIP is equally as effective as related palmitate derivatised analogues of GIP. (c) 2006 Elsevier Inc. All rights reserved.

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1. Barnacles are a good model organism for the study of open populations with space-limited recruitment. These models are applicable to other species with open supply of new individuals and resource limitation. The inclusion of space in models leads to reductions in recruitment with increasing density, and thus predictions of population size and stability are possible. 2. Despite the potential generality of a demographic theory for open space-limited populations, the models currently have a narrow empirical base. In this study, a model for an open population with space-limited recruitment was extended to include size-specific survival and promotions to any size class. The assumptions of this model were tested using data from a pan-European study of the barnacle Chthamalus montagui Southward. Two models were constructed: a 6-month model and a periodic annual model. Predicted equilibria and their stabilities were compared between shores. 3. Tests of model assumptions supported the extension of the theory to include promotions to any size class. Mortality was found to be size-specific and density independent. Studied populations were open, with recruitment proportional to free space. 4. The 6-month model showed a significant interaction between time and location for equilibrium free space. This may have been due to contrasts in the timing of structuring processes (i.e. creating and filling space) between Mediterranean and Atlantic systems. Integration of the 6-month models into a periodic annual model removed the differences in equilibrium-free space between locations. 5. Model predictions show a remarkable similarity between shores at a European scale. Populations were persistent and all solutions were stable. This reflects the apparent absence of density-dependent mortality and a high adult survivorship in C. montagui. As populations are intrinsically stable, observations of fluctuations in density are directly attributable to variations in the environmental forcing of recruitment or mortality

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In this study, the surface properties of and work required to remove 12 commercially available and developmental catheters from a model biological medium (agar), a measure of catheter lubricity, were characterised and the relationships between these properties were examined using multiple regression and correlation analysis. The work required for removal of catheter sections (7 cm) from a model biological medium (1% w/w agar) were examined using tensile analysis. The water wettability of the catheters were characterised using dynamic contact angle analysis, whereas surface roughness was determined using atomic force microscopy. Significant differences in the ease of removal were observed between the various catheters, with the silicone-based materials generally exhibiting the greatest ease of removal. Similarly, the catheters exhibited a range of advancing and receding contact angles that were dependent on the chemical nature of each catheter. Finally, whilst the microrugosities of the various catheters differed, no specific relationship to the chemical nature of the biomaterial was apparent. Using multiple regression analysis, the relationship between ease of removal, receding contact angle and surface roughness was defined as: Work done (N mm) 17.18 + 0.055 Rugosity (nm)-0.52 Receding contact angle (degrees) (r = 0.49). Interestingly, whilst the relationship between ease of removal and surface roughness was significant (r = 0.48, p = 0.0005), in which catheter lubricity increased as the surface roughness decreased, this was not the case with the relationship between ease of removal and receding contact angle (r = -0.18, p > 0.05). This study has therefore uniquely defined the contributions of each of these surface properties to catheter lubricity. Accordingly, in the design of urethral catheters. it is recommended that due consideration should be directed towards biomaterial surface roughness to ensure maximal ease of catheter removal. Furthermore, using the method described in this study, differences in the lubricity of the various catheters were observed that may be apparent in their clinical use. (C) 2003 Elsevier Ltd. All rights reserved.