Quantitative estimation of bioturbation based on digital image analysis

Quantitative determination of modification of primary sediment features, by the activity of organisms (i.e., bioturbation) is essential in geosciences. Some methods proposed since the 1960s are mainly based on visual or subjective determinations. The first semiquantitative evaluations of the Bioturbation Index, Ichnofabric Index, or the amount of bioturbation were attempted, in the best cases using a series of flashcards designed in different situations. Recently, more effective methods involve the use of analytical and computational methods such as X-rays, magnetic resonance imaging or computed tomography; these methods are complex and often expensive. This paper presents a compilation of different methods, using Adobe® Photoshop® software CS6, for digital estimation that are a part of the IDIAP (Ichnological Digital Analysis Images Package), which is an inexpensive alternative to recently proposed methods, easy to use, and especially recommended for core samples. The different methods — “Similar Pixel Selection Method (SPSM)”, “Magic Wand Method (MWM)” and the “Color Range Selection Method (CRSM)” — entail advantages and disadvantages depending on the sediment (e.g., composition, color, texture, porosity, etc.) and ichnological features (size of traces, infilling material, burrow wall, etc.). The IDIAP provides an estimation of the amount of trace fossils produced by a particular ichnotaxon, by a whole ichnocoenosis or even for a complete ichnofabric. We recommend the application of the complete IDIAP to a given case study, followed by selection of the most appropriate method. The IDIAP was applied to core material recovered from the IODP Expedition 339, enabling us, for the first time, to arrive at a quantitative estimation of the discrete trace fossil assemblage in core samples.

Cell adhesion molecule uvomorulin expression in human breast cancer cell lines : relationship to morphology and invasive capacities

Loss of cell-cell adhesion in carcinoma cells may be an important step in the acquisition of an invasive, metastatic phenotype. We have examined the expression of the epithelial-specific cell adhesion molecule uvomorulin (E-cadherin, cell-CAM 120/80, L-CAM) in human breast cancer cell lines. We find that fibroblastoid, highly invasive, vimentin-expressing breast cancer cell lines do not express uvomorulin. Of the more epithelial-appearing, less invasive, keratin-expressing breast cancer cell lines, some express uvomorulin, and some do not. We examined the morphologies of the cell lines in the reconstituted basement membrane matrix Matrigel and measured the ability of the cells to traverse a Matrigel-coated filter as in vitro models for detachment of carcinoma cells from neighboring cells and invasion through basement membrane into surrounding tissue. Colonies of uvomorulin-positive cells have a characteristic fused appearance in Matrigel, whereas uvomorulin-negative cells appear detached. Cells which are uvomorulin negative and vimentin positive have a stellate morphology in Matrigel. We show that uvomorulin is responsible for the fused colony morphology in Matrigel since treatment of uvomorulin-positive MCF-7 cells with an antibody to uvomorulin caused the cells to detach from one another but did not induce invasiveness in these cells, as measured by their ability to cross a Matrigel-coated polycarbonate filter in a modified Boyden chamber assay. Two uvomorulin-negative, vimentin-negative cell lines are also not highly invasive as measured by this assay. We suggest that loss of uvomorulin-mediated cell-cell adhesion may be one of many changes involved in the progression of a carcinoma cell to an invasive phenotype.

Tunable “Nano-Shearing” : A physical mechanism to displace nonspecific cell adhesion during rare cell detection

We report a tunable alternating current electrohydrodynamic (ac-EHD) force which drives lateran fluid motion within a few nanometers of an electrode surface. Because the magnitude of this fluid shear force can be tuned externally (e.g., via the application of an ac electric field), it provides a new capability to physically displace weakly (nonspecifically) bound cellular analytes. To demonstrate the utility of the tunable nanoshearing phenomenon, we present data on purpose-built microfluidic devices that employ ac-EHD force to remove nonspecific adsorption of molecular and cellular species. Here, we show that an ac-EHD device containing asymmetric planar and microtip electrode pairs resulted in a 4-fold reduction in nonspecific adsorption of blood cells and also captured breast cancer cells in blood, with high efficiency (approximately 87%) and specificity. We therefore feel that this new capability of externally tuning and manipulating fluid flow could have wide applications as an innovative approach to enhance the specific capture of rare cells such as cancer cells in blood.

Corneal confocal microscopy shown an improvement in small-fibre neuropathy in subjects with type 1 diabetes on continuous subcutaneous insulin infusion compared to multiple daily injection

Improved glycemic control is the only treatment that has been shown to be effective for diabetic peripheral neuropathy in patients with type 1 diabetes (1). Continuous subcutaneous insulin infusion (CSII) is superior to multiple daily insulin injection (MDI) for reducing HbA1c and hypoglycemic events (2). Here, we have compared the benefits of CSII compared withMDI for neuropathy over 24months....

Pre-processing for approximate Bayesian computation in image analysis

Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computational cost of these simulations can be prohibitive for high dimensional data. An important example is the Potts model, which is commonly used in image analysis. Images encountered in real world applications can have millions of pixels, therefore scalability is a major concern. We apply ABC with a synthetic likelihood to the hidden Potts model with additive Gaussian noise. Using a pre-processing step, we fit a binding function to model the relationship between the model parameters and the synthetic likelihood parameters. Our numerical experiments demonstrate that the precomputed binding function dramatically improves the scalability of ABC, reducing the average runtime required for model fitting from 71 hours to only 7 minutes. We also illustrate the method by estimating the smoothing parameter for remotely sensed satellite imagery. Without precomputation, Bayesian inference is impractical for datasets of that scale.

DroplIT, an improved image analysis method for droplet identification in high-throughput crystallization trials

The application of robotics to protein crystallization trials has resulted in the production of millions of images. Manual inspection of these images to find crystals and other interesting outcomes is a major rate-limiting step. As a result there has been intense activity in developing automated algorithms to analyse these images. The very first step for most systems that have been described in the literature is to delineate each droplet. Here, a novel approach that reaches over 97% success rate and subsecond processing times is presented. This will form the seed of a new high-throughput system to scrutinize massive crystallization campaigns automatically. © 2010 International Union of Crystallography Printed in Singapore-all rights reserved.

Scalable Bayesian Computation for intractable likelihoods in image analysis

The inverse temperature hyperparameter of the hidden Potts model governs the strength of spatial cohesion and therefore has a substantial influence over the resulting model fit. The difficulty arises from the dependence of an intractable normalising constant on the value of the inverse temperature, thus there is no closed form solution for sampling from the distribution directly. We review three computational approaches for addressing this issue, namely pseudolikelihood, path sampling, and the approximate exchange algorithm. We compare the accuracy and scalability of these methods using a simulation study.

Corneal confocal microscopy predicts 4-year incident peripheral neuropathy in Type 1 diabetes

OBJECTIVE This study determined if deficits in corneal nerve fiber length (CNFL) assessed using corneal confocal microscopy (CCM) can predict future onset of diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS CNFL and a range of other baseline measures were compared between 90 nonneuropathic patients with type 1 diabetes who did or did not develop DPN after 4 years. The receiver operator characteristic (ROC) curve was used to determine the capability of single and combined measures of neuropathy to predict DPN. RESULTS DPN developed in 16 participants (18%) after 4 years. Factors predictive of 4-year incident DPN were lower CNFL (P = 0.041); longer duration of diabetes (P = 0.002); higher triglycerides (P = 0.023); retinopathy (higher on the Early Treatment of Diabetic Retinopathy Study scale) (P = 0.008); nephropathy (higher albumin-to-creatinine ratio) (P = 0.001); higher neuropathy disability score (P = 0.037); lower cold sensation (P = 0.001) and cold pain (P = 0.027) thresholds; higher warm sensation (P = 0.008), warm pain (P = 0.024), and vibration (P = 0.003) thresholds; impaired monofilament response (P = 0.003); and slower peroneal (P = 0.013) and sural (P = 0.002) nerve conduction velocity. CCM could predict the 4-year incident DPN with 63% sensitivity and 74% specificity for a CNFL threshold cutoff of 14.1 mm/mm2 (area under ROC curve = 0.66, P = 0.041). Combining neuropathy measures did not improve predictive capability. CONCLUSIONS DPN can be predicted by various demographic, metabolic, and conventional neuropathy measures. The ability of CCM to predict DPN broadens the already impressive diagnostic capabilities of this novel ophthalmic marker.

Risk factors associated with corneal nerve alteration in type 1 diabetes in the absence of neuropathy: A longitudinal in vivo corneal confocal microscopy study

Purpose The aim of this study was to determine alterations to the corneal subbasal nerve plexus (SNP) over four years using in vivo corneal confocal microscopy (IVCM) in participants with type 1 diabetes and to identify significant risk factors associated with these alterations. Methods A cohort of 108 individuals with type 1 diabetes and no evidence of peripheral neuropathy at enrollment underwent laser-scanning IVCM, ocular screening, and health and metabolic assessment at baseline and the examinations continued for four subsequent annual visits. At each annual visit, eight central corneal images of the SNP were selected and analyzed to quantify corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL). Linear mixed model approaches were fitted to examine the relationship between risk factors and corneal nerve parameters. Results A total of 96 participants completed the final visit and 91 participants completed all visits. No significant relationships were found between corneal nerve parameters and time, sex, duration of diabetes, smoking, alcohol consumption, blood pressure or BMI. However, CNFD was negatively associated with HbA1c (β=-0.76, P<0.01) and age (β=-0.13, P<0.01) and positively related to high density lipids (HDL) (β=2.01, P=0.03). Higher HbA1c (β=-1.58, P=0.04) and age (β=-0.23, P<0.01) also negatively impacted CNBD. CNFL was only affected by higher age (β=-0.06, P<0.01). Conclusions Glycemic control, HDL and age have significant effects on SNP structure. These findings highlight the importance of diabetic management to prevent corneal nerve damage as well as the capability of IVCM for monitoring subclinical alterations in the corneal SNP in diabetes.

Corneal confocal microscopy detects neuropathy in patients with type 1 diabetes without retinopathy or microalbuminuria

Objective Corneal innervation is increasingly used as a surrogate marker of human diabetic peripheral neuropathy (DPN) however its temporal relationship with the other microvascular complications of diabetes is not fully established. In this cross-sectional, observational study we aimed to assess whether neuropathy occurred in patients with type 1 diabetes, without retinopathy or microalbuminuria. Materials and Methods All participants underwent detailed assessment of peripheral neuropathy [neuropathy disability score (NDS), vibration perception threshold (VPT), peroneal motor nerve conduction velocity (PMNCV), sural sensory nerve conduction velocity (SSNCV) and in vivo corneal confocal microscopy (IVCCM)], retinopathy (digital fundus photography) and albuminuria status [albumin: creatinine ratio (ACR)]. Results 53 patients with Type 1 diabetes with (n=37) and without retinopathy (n=16) were compared to control subjects (n=27). SSNCV, corneal nerve fibre (CNFD) and branch (CNBD) density and length (CNFL) were reduced significantly (p<0.001) in diabetic patients without retinopathy compared to control subjects. Furthermore, CNFD, CNBD and CNFL were also significantly (p<0.001) reduced in diabetic patients without microalbuminuria (n=39), compared to control subjects. Greater neuropathic severity was associated with established retinopathy and microalbuminuria. Conclusions IVCCM detects early small fibre damage in the absence of retinopathy or microalbuminuria in patients with Type 1 diabetes.

The inferior whorl for detecting diabetic peripheral neuropathy using corneal confocal microscopy

PURPOSE: In vivo corneal confocal microscopy (CCM) is increasingly used as a surrogate endpoint in studies of diabetic polyneuropathy (DPN). However, it is not clear whether imaging the central cornea provides optimal diagnostic utility for DPN. Therefore, we compared nerve morphology in the central cornea and the inferior whorl, a more distal and densely innervated area located inferior and nasal to the central cornea. METHODS: A total of 53 subjects with type 1/type 2 diabetes and 15 age-matched control subjects underwent detailed assessment of neuropathic symptoms (NPS), deficits (neuropathy disability score [NDS]), quantitative sensory testing (vibration perception threshold [VPT], cold and warm threshold [CT/WT], and cold- and heat-induced pain [CIP/HIP]), and electrophysiology (sural and peroneal nerve conduction velocity [SSNCV/PMNCV], and sural and peroneal nerve amplitude [SSNA/PMNA]) to diagnose patients with (DPN+) and without (DPN-) neuropathy. Corneal nerve fiber density (CNFD) and length (CNFL) in the central cornea, and inferior whorl length (IWL) were quantified. RESULTS: Comparing control subjects to DPN- and DPN+ patients, there was a significant increase in NDS (0 vs. 2.6 ± 2.3 vs. 3.3 ± 2.7, P < 0.01), VPT (V; 5.4 ± 3.0 vs. 10.6 ± 10.3 vs. 17.7 ± 11.8, P < 0.01), WT (°C; 37.7 ± 3.5 vs. 39.1 ± 5.1 vs. 41.7 ± 4.7, P < 0.05), and a significant decrease in SSNCV (m/s; 50.2 ± 5.4 vs. 48.4 ± 5.0 vs. 39.5 ± 10.6, P < 0.05), CNFD (fibers/mm2; 37.8 ± 4.9 vs. 29.7 ± 7.7 vs. 27.1 ± 9.9, P < 0.01), CNFL (mm/mm2; 27.5 ± 3.6 vs. 24.4 ± 7.8 vs. 20.7 ± 7.1, P < 0.01), and IWL (mm/mm2; 35.1 ± 6.5 vs. 26.2 ± 10.5 vs. 23.6 ± 11.4, P < 0.05). For the diagnosis of DPN, CNFD, CNFL, and IWL achieved an area under the curve (AUC) of 0.75, 0.74, and 0.70, respectively, and a combination of IWL-CNFD achieved an AUC of 0.76. CONCLUSIONS: The parameters of CNFD, CNFL, and IWL have a comparable ability to diagnose patients with DPN. However, IWL detects an abnormality even in patients without DPN. Combining IWL with CNFD may improve the diagnostic performance of CCM.