Autonomous and self-sustained circadian oscillators displayed in human islet cells.

AIMS/HYPOTHESIS: Following on from the emerging importance of the pancreas circadian clock on islet function and the development of type 2 diabetes in rodent models, we aimed to examine circadian gene expression in human islets. The oscillator properties were assessed in intact islets as well as in beta cells. METHODS: We established a system for long-term bioluminescence recording in cultured human islets, employing lentivector gene delivery of the core clock gene Bmal1 (also known as Arntl)-luciferase reporter. Beta cells were stably labelled using a rat insulin2 promoter fluorescent construct. Single-islet/cell oscillation profiles were measured by combined bioluminescence-fluorescence time-lapse microscopy. RESULTS: Human islets synchronised in vitro exhibited self-sustained circadian oscillations of Bmal1-luciferase expression at both the population and single-islet levels, with period lengths of 23.6 and 23.9 h, respectively. Endogenous BMAL1 and CRY1 transcript expression was circadian in synchronised islets over 48 h, and antiphasic to REV-ERBα (also known as NR1D1), PER1, PER2, PER3 and DBP transcript circadian profiles. HNF1A and PDX1 exhibited weak circadian oscillations, in phase with the REV-ERBα transcript. Dispersed islet cells were strongly oscillating as well, at population and single-cell levels. Importantly, beta and non-beta cells revealed oscillatory profiles that were well synchronised with each other. CONCLUSIONS/INTERPRETATION: We provide for the first time compelling evidence for high-amplitude cell-autonomous circadian oscillators displayed in human pancreatic islets and in dispersed human islet cells. Moreover, these clocks are synchronised between beta and non-beta cells in primary human islet cell cultures.

3-D PSF fitting for fluorescence microscopy: implementation and localization application.

Localization microscopy relies on computationally efficient Gaussian approximations of the point spread function for the calculation of fluorophore positions. Theoretical predictions show that under specific experimental conditions, localization accuracy is significantly improved when the localization is performed using a more realistic model. Here, we show how this can be achieved by considering three-dimensional (3-D) point spread function models for the wide field microscope. We introduce a least-squares point spread function fitting framework that utilizes the Gibson and Lanni model and propose a computationally efficient way for evaluating its derivative functions. We demonstrate the usefulness of the proposed approach with algorithms for particle localization and defocus estimation, both implemented as plugins for ImageJ.

Laser Doppler imaging for intraoperative human brain mapping.

The identification and accurate location of centers of brain activity are vital both in neuro-surgery and brain research. This study aimed to provide a non-invasive, non-contact, accurate, rapid and user-friendly means of producing functional images intraoperatively. To this end a full field Laser Doppler imager was developed and integrated within the surgical microscope and perfusion images of the cortical surface were acquired during awake surgery whilst the patient performed a predetermined task. The regions of brain activity showed a clear signal (10-20% with respect to the baseline) related to the stimulation protocol which lead to intraoperative functional brain maps of strong statistical significance and which correlate well with the preoperative fMRI and intraoperative cortical electro-stimulation. These initial results achieved with a prototype device and wavelet based regressor analysis (the hemodynamic response function being derived from MRI applications) demonstrate the feasibility of LDI as an appropriate technique for intraoperative functional brain imaging.

Intracellular nanomanipulation by a photonic-force microscope with real-time acquisition of a 3D stiffness matrix.

A traditional photonic-force microscope (PFM) results in huge sets of data, which requires tedious numerical analysis. In this paper, we propose instead an analog signal processor to attain real-time capabilities while retaining the richness of the traditional PFM data. Our system is devoted to intracellular measurements and is fully interactive through the use of a haptic joystick. Using our specialized analog hardware along with a dedicated algorithm, we can extract the full 3D stiffness matrix of the optical trap in real time, including the off-diagonal cross-terms. Our system is also capable of simultaneously recording data for subsequent offline analysis. This allows us to check that a good correlation exists between the classical analysis of stiffness and our real-time measurements. We monitor the PFM beads using an optical microscope. The force-feedback mechanism of the haptic joystick helps us in interactively guiding the bead inside living cells and collecting information from its (possibly anisotropic) environment. The instantaneous stiffness measurements are also displayed in real time on a graphical user interface. The whole system has been built and is operational; here we present early results that confirm the consistency of the real-time measurements with offline computations.

Quantitative morphometrical characterization of human pronuclear zygotes.

BACKGROUND: Identification of embryos with high implantation potential remains a challenge in in vitro fertilization (IVF). Subjective pronuclear (PN) zygote scoring systems have been developed for that purpose. The aim of this work was to provide a software tool that enables objective measuring of morphological characteristics of the human PN zygote. METHODS: A computer program was created to analyse zygote images semi-automatically, providing precise morphological measurements. The accuracy of this approach was first validated by comparing zygotes from two different IVF centres with computer-assisted measurements or subjective scoring. Computer-assisted measurement and subjective scoring were then compared for their ability to classify zygotes with high and low implantation probability by using a linear discriminant analysis. RESULTS: Zygote images coming from the two IVF centres were analysed with the software, resulting in a series of precise measurements of 24 variables. Using subjective scoring, the cytoplasmic halo was the only feature which was significantly different between the two IVF centres. Computer-assisted measurements revealed significant differences between centres in PN centring, PN proximity, cytoplasmic halo and features related to nucleolar precursor bodies distribution. The zygote classification error achieved with the computer-assisted measurements (0.363) was slightly inferior to that of the subjective ones (0.393). CONCLUSIONS: A precise and objective characterization of the morphology of human PN zygotes can be achieved by the use of an advanced image analysis tool. This computer-assisted analysis allows for a better morphological characterization of human zygotes and can be used for classification.

Coupled tomography and distinct-element-method approach to exploring the granular media microstructure in a jamming hourglass.

We describe an approach for exploring microscopic properties of granular media that couples x-ray microtomography and distinct-element-method (DEM) simulations through image analysis. We illustrate it via the study of the intriguing phenomenon of instant arching in an hourglass (in our case a cylinder filled with a polydisperse mixture of glass beads that has a small circular shutter in the bottom). X-ray tomography provides three-dimensional snapshots of the microscopic conditions of the system both prior to opening the shutter, and thereafter, once jamming is completed. The process time in between is bridged using DEM simulation, which settles to positions in remarkably good agreement with the x-ray images. Specifically designed image analysis procedures accurately extract the geometrical information, i.e., the positions and sizes of the beads, from the raw x-ray tomographs, and compress the data representation from initially 5 gigabytes to a few tens of kilobytes per tomograph. The scope of the approach is explored through a sensitivity analysis to input data perturbations in both bead sizes and positions. We establish that accuracy of size--much more than position--estimates is critical, thus explaining the difficulty in considering a mixture of beads of different sizes. We further point to limits in the replication ability of granular flows away from equilibrium; i.e., the difficulty of numerically reproducing chaotic motion.

A fast thresholded landweber algorithm for wavelet-regularized multidimensional deconvolution.

We present a fast variational deconvolution algorithm that minimizes a quadratic data term subject to a regularization on the l(1)-norm of the wavelet coefficients of the solution. Previously available methods have essentially consisted in alternating between a Landweber iteration and a wavelet-domain soft-thresholding operation. While having the advantage of simplicity, they are known to converge slowly. By expressing the cost functional in a Shannon wavelet basis, we are able to decompose the problem into a series of subband-dependent minimizations. In particular, this allows for larger (subband-dependent) step sizes and threshold levels than the previous method. This improves the convergence properties of the algorithm significantly. We demonstrate a speed-up of one order of magnitude in practical situations. This makes wavelet-regularized deconvolution more widely accessible, even for applications with a strong limitation on computational complexity. We present promising results in 3-D deconvolution microscopy, where the size of typical data sets does not permit more than a few tens of iterations.

Snakuscules.

A snakuscule (a minuscule snake) is the simplest active contour that we were able to design while keeping the quintessence of traditional snakes: an energy term governed by the data, and a regularization term. Our construction is an area-based snake, as opposed to curve-based snakes. It is parameterized by just two points, thus further easing requirements on the optimizer. Despite their ultimate simplicity, snakuscules retain enough versatility to be employed for solving various problems such as cell counting and segmentation of approximately circular features. In this paper, we detail the design process of a snakuscule and illustrate its usefulness through practical examples. We claim that our didactic intentions are well served by the simplicity of snakuscules.

Molecular substructure of a viral receptor-recognition protein. The gp17 tail-fiber of bacteriophage T7.

The bacteriophage T7 tail complex consists of a conical tail-tube surrounded by six kinked tail-fibers, which are oligomers of the viral protein gp17 (Mr 61,400). We have derived a molecular model for the tail-fiber by integrating secondary structure predictions with ultrastructural information obtained by correlation averaging of electron micrographs of negatively stained tail complexes. This model has been further refined by high-resolution scanning transmission electron microscopy of purified fibers, both negatively stained and unstained. Mass measurements made from the latter images establish that the fiber is a trimer of gp17. The proximal half-fiber is a uniform rod, about 2.0 nm in diameter and 16.4 nm long, which we infer to be a triple-stranded coiled-coil, containing three copies of an alpha-helical domain of about 117 residues, starting at Phe151. The distal half-fiber is 15.5 nm long, and is made up of four globules, 3.1 to 4.8 nm in diameter, in rigid linear array: it contains the carboxy-terminal halves (residues approximately 268 to 553) of the constituent gp17 chains, arranged with 3-fold symmetry around its long axis. The amino-terminal domains (residues 1 to 149) link the fiber to the tail-tube. We conclude that the three gp17 chains are quasi-equivalent in the proximal half-fiber, equivalent in the distal half-fiber, and non-equivalent in the kink region that separates the two half-fibers: such localized non-equivalence may represent a general mechanism for the formation of kinked joints in segmented homo-oligomeric proteins.

Spline-based image-to-volume registration for three-dimensional electron microscopy.

This paper presents an algorithm based on a continuous framework for a posteriori angular and translational assignment in three-dimensional electron microscopy (3DEM) of single particles. Our algorithm can be used advantageously to refine the assignment of standard quantized-parameter methods by registering the images to a reference 3D particle model. We achieve the registration by employing a gradient-based iterative minimization of a least-squares measure of dissimilarity between an image and a projection of the volume in the Fourier transform (FT) domain. We compute the FT of the projection using the central-slice theorem (CST). To compute the gradient accurately, we take advantage of a cubic B-spline model of the data in the frequency domain. To improve the robustness of the algorithm, we weight the cost function in the FT domain and apply a "mixed" strategy for the assignment based on the minimum value of the cost function at registration for several different initializations. We validate our algorithm in a fully controlled simulation environment. We show that the mixed strategy improves the assignment accuracy; on our data, the quality of the angular and translational assignment was better than 2 voxel (i.e., 6.54 angstroms). We also test the performance of our algorithm on real EM data. We conclude that our algorithm outperforms a standard projection-matching refinement in terms of both consistency of 3D reconstructions and speed.

Aging studies on normal lens using the Scheimpflug slit-lamp camera.

PURPOSE: To study the changes in density and thickness in normal lenses related to aging, and to study changes in anterior chamber depth related to aging. METHODS: Eighty nine normal volunteers (ages 9-80 yr) were examined and their eyes were photographed to obtain Scheimpflug photographs. The images were digitized and linear densitometry was performed, dividing the lens into five areas: posterior capsular (area 1), posterior cortical (area 2), nuclear (area 3), anterior cortical (area 4), and anterior capsular (area 5). Total lens thickness and anterior chamber depth were similarly measured for 90 normal eyes from the densitometry profiles. These were correlated with age. RESULTS: There was a strong positive correlation between increasing age and the density in all lens areas (area 2: r = 0.805; P < 0.0001; area 3: r = 0.836, P < 0.0001; area 4: r = 0.767, P < 0.0001; and area 5: r = 0.319, P < 0.0023), except the posterior capsular area, where correlation was negative (area 1: r = -0.426; P < 0.0001). In addition, there was a significant correlation between age and overall lens thickness (r = 0.756; P < 0.0001), thickness of nucleus (r = 0.543; P < 0.0001), and cortex (r = 0.632; P < 0.0001), and a negative correlation with anterior chamber depth (r = -0.513, P < 0.0001). CONCLUSION: This report shows human lens changes in density and thickness correlated with aging using Scheimpflug photography and image analysis techniques. The results will aid future development of systems for automated detection, classification, and monitoring of human cataracts, as well as other anterior segment disorders.

Effect of phorbol esters on rat lacrimal gland protein secretion.

To identify a role for protein kinase C in lacrimal gland protein secretion, we incubated rat exorbital lacrimal gland acini in the ester 4-beta-phorbol 12, 13 dibutyrate (beta-phorbol dibutyrate), its inactive isomer 4-alpha-phorbol 12, 13 dibutyrate (alpha-phorbol dibutyrate), and the diacylglycerol analog 1,2-oleoyl acetylglycerol (OAG). We determined protein secretion by measuring the activity of peroxidase, a protein secreted by lacrimal gland acini. beta-phorbol dibutyrate, but not alpha-phorbol dibutyrate, stimulated peroxidase secretion in a concentration-dependent manner with 3 X 10(-8) M producing maximal secretion. OAG (10(-6) M) also stimulated peroxidase secretion. To determine whether muscarinic and alpha 1-adrenergic agonists activate protein kinase C, we added beta-phorbol dibutyrate (10(-7) M) simultaneously with carbachol (10(-5) M) or phenylephrine (10(-4) M); under both conditions, secretion was less than additive. Protein secretion in the presence of beta-phorbol dibutyrate (10(-7) M) and vasoactive intestinal peptide (VIP) (10(-8) M), the latter that acts through cAMP, was additive, and when the beta-phorbol dibutyrate but not the VIP concentration was decreased to 10(-8) M, secretion was potentiated. We conclude that muscarinic and alpha 1-adrenergic agonists, but not VIP, stimulated lacrimal gland protein secretion by activating protein kinase C.

Role of cyclic AMP and Ca2+ in potentiation of rat lacrimal gland protein secretion.

Addition of a cholinergic agonist carbachol and vasoactive intestinal peptide (VIP) to dispersed rat exorbital lacrimal gland acini produces protein secretion, measured by secretion of the enzyme peroxidase, that was statistically significantly greater than additive (potentiated). To determine where in stimulus-secretion coupling these secretagogues interact to potentiate secretion, rat exorbital gland acini were incubated simultaneously with cyclic AMP- and Ca2+-dependent agonists and protein secretion, cyclic AMP level, or Ca2+ concentration measured. As a measure of protein secretion, the supernatant obtained after centrifugation of acini was analyzed for peroxidase, a protein secreted by rat lacrimal glands. Interaction did not occur at the receptor level, because peroxidase secretion also was potentiated by simultaneous addition of carbachol and forskolin, which activates the catalytic subunit of adenyl cyclase. A potentiated increase in the cyclic AMP level did not potentiate protein secretion, because the level was the same with VIP as with carbachol and VIP added together at concentrations that potentiated peroxidase secretion. A potentiated increase in free intracellular [Ca2+] did not potentiate protein secretion, because [Ca2+] was greater with carbachol than with carbachol and VIP added together at concentrations that potentiated peroxidase secretion. We conclude that cholinergic- and VIP-dependent pathways interact to potentiate lacrimal gland protein secretion after the rise of intracellular cyclic AMP or Ca2+.

Interpolation revisited.

Based on the theory of approximation, this paper presents a unified analysis of interpolation and resampling techniques. An important issue is the choice of adequate basis functions. We show that, contrary to the common belief, those that perform best are not interpolating. By opposition to traditional interpolation, we call their use generalized interpolation; they involve a prefiltering step when correctly applied. We explain why the approximation order inherent in any basis function is important to limit interpolation artifacts. The decomposition theorem states that any basis function endowed with approximation order can be expressed as the convolution of a B-spline of the same order with another function that has none. This motivates the use of splines and spline-based functions as a tunable way to keep artifacts in check without any significant cost penalty. We discuss implementation and performance issues, and we provide experimental evidence to support our claims.

Unwarping of unidirectionally distorted EPI images.

Echo-planar imaging (EPI) is a fast nuclear magnetic resonance imaging (MRI) method. Unfortunately, local magnetic field inhomogeneities induced mainly by the subject's presence cause significant geometrical distortion, predominantly along the phase-encoding direction, which must be undone to allow for meaningful further processing. So far, this aspect has been too often neglected. In this paper, we suggest a new approach using an algorithm specifically developed for the automatic registration of distorted EPI images with corresponding anatomically correct MRI images. We model the deformation field with splines, which gives us a great deal of flexibility, while comprising the affine transform as a special case. The registration criterion is least squares. Interestingly, the complexity of its evaluation does not depend on the resolution of the control grid. The spline model gives us good accuracy thanks to its high approximation order. The short support of splines leads to a fast algorithm. A multiresolution approach yields robustness and additional speedup. The algorithm was tested on real as well as synthetic data, and the results were compared with a manual method. A wavelet-based Sobolev-type random deformation generator was developed for testing purposes. A blind test indicates that the proposed automatic method is faster, more reliable, and more precise than the manual one.

Automated extraction of serial myocardial borders from M-mode echocardiograms.

A method is presented for the automated extraction of myocardial borders in M-mode echocardiograms. The successive steps of processing are: preprocessing for noise reduction, enhancement of border characteristics using a set of suitably chosen matched filters, and final extraction of border points by searching for optimal paths along the time axis. During the last step of processing, the contribution of each elementary border element is characterised by a normalized correlation coefficient. The optimal path, defined as the one that maximizes the sum of all elementary contributions, is determined efficiently using dynamic programming. An alternative approach uses a maximum tracking procedure whose performances are improved by utilizing a local model to predict the position of the next border point. Experimental examples are presented and the performance of both border extraction algorithms are compared.

Statistical analysis of functional MRI data in the wavelet domain.

The use of the wavelet transform is explored for the detection of differences between brain functional magnetic resonance images (fMRI's) acquired under two different experimental conditions. The method benefits from the fact that a smooth and spatially localized signal can be represented by a small set of localized wavelet coefficients, while the power of white noise is uniformly spread throughout the wavelet space. Hence, a statistical procedure is developed that uses the imposed decomposition orthogonality to locate wavelet-space partitions with large signal-to-noise ratio (SNR), and subsequently restricts the testing for significant wavelet coefficients to these partitions. This results in a higher SNR and a smaller number of statistical tests, yielding a lower detection threshold compared to spatial-domain testing and, thus, a higher detection sensitivity without increasing type I errors. The multiresolution approach of the wavelet method is particularly suited to applications where the signal bandwidth and/or the characteristics of an imaging modality cannot be well specified. The proposed method was applied to compare two different fMRI acquisition modalities. Differences of the respective useful signal bandwidths could be clearly demonstrated; the estimated signal, due to the smoothness of the wavelet representation, yielded more compact regions of neuroactivity than standard spatial-domain testing.

A new resolution criterion based on spectral signal-to-noise ratios.

A new criterion for the "useful" resolution of electron micrographs of macromolecular particles is introduced. This criterion is based on estimation of the spatial frequency limit beyond which the spectral signal-to-noise ratio (SSNR) falls below an acceptable baseline. Applicable to both periodic and aperiodic specimens, this approach is particularly apposite for sets of correlation-averaged images. It represents a straightforward and intuitively appealing generalization of the traditional method of estimating the resolution of crystalline specimens from the spectral ranges of periodic reflections in their diffraction patterns. This method allows one to assess how closely the resolution of an averaged image based on N individual images approaches the ultimate resolution obtainable from an indefinitely large number of statistically equivalent images. Inter-relationships between the SSNR and two other measures of resolution, the differential phase residual and the Fourier ring correlation coefficient, are discussed, and their properties compared.

Normalization procedures and factorial representations for classification of correlation-aligned images: a comparative study.

We have addressed the problem of optimizing procedures of multivariate statistical analysis (MSA) for identifying homogeneous sets of electron micrographs of biological macromolecules, with a view to averaging over consistent sets of images. Using pre-aligned images of negatively stained protein molecules - known a priori to fall into two subtly different classes - we compared how the capacity to discriminate between them was affected by the normalization procedure used, and by the choice of factorial representation. Specifically, these images were analyzed both after being scaled according to constant minimum and maximum (CMM) values, and after imposing constant values of image mean and variance (CMV). The factorial representations compared were correspondence analysis (CA) and the principal components (PC) formalism. When used with PC, CMM normalization was found to give rise to spurious inter-image fluctuations that were more pronounced than the genuine difference between the two kinds of images; even with CA, CMV proved to be a more satisfactory method of normalization. When CMV was used with CA or PC, both factorial representations yielded qualitatively similar results, although according to a quantitative measure of inter-set discrimination, the performance of PC was slightly superior. Even in the best case, however, the two classes of images - as mapped in factorial space - were not fully resolved. The implications of this observation are discussed with regard to potential ambiguities of image classification in practice.

Odd men out: a quantitative objective procedure for identifying anomalous members of a set of noisy images of ostensibly identical specimens.

Achievement of an optimal improvement in signal-to-noise ratio from image averaging techniques depends crucially on the assumption that all members of the set of images to be averaged are fundamentally alike. In HREM of biological macromolecules, this assumption may be invalid for such reasons as variations in viewing geometry, non-uniformity of staining, or structural perturbations caused by specimen preparation procedures of radiation damage. Inclusion of data that are compromized these or other factors will degrade the information content of the averaged image. Here we present an algorithm which provides an objective quantitative method for the identification and elimination of anomalous members of a set of pre-aligned images. Based on a statistical criterion of mutual consistency, the algorithm forms an ordered list in which the individual images are ranked from most to least reliable. On specification of the noise statistics--in the formulation given here, of stationary white noise--an acceptability threshold in this ordered list is imposed. The derivation and implementation of this algorithm are presented, its properties discussed, and its application illustrated using both real and model electron micrograph data.