Movement correction method for laser speckle contrast imaging of cerebral blood flow in cranial windows in rodents

Laser speckle contrast imaging (LSCI) is used in clinical research to dynamically image blood flow. One drawback is its susceptibility to movement artifacts. We demonstrate a new, simple method to correct motion artifacts in LSCI signals measured in awake mice with cranial windows during sensory stimulation. The principle is to identify a region in the image in which speckle contrast (SC) is independent of blood flow and only varies with animal movement, then to regress out this signal from the data. We show that (1) the regressed signal correlates well with mouse head movement, (2) the corrected signal correlates better with independently measured blood volume and (3) it has a (59 ± 6)% higher signal-to-noise ratio. Compared to three alternative correction methods, ours has the best performance. Regressing out flow-independent global variations in SC is a simple and accessible way to improve the quality of LSCI measurements.     

Dosimetric study of Hounsfield number correction effect in areas influenced by contrast product in lungs case

BackgroundThe aim of the study was dosimetric effect quantification of exclusive computed tomography (CT) use with an intravenous (IV) contrast agent (CA ), on dose distribution of 3D-CRT treatment plans for lung cancer. Furthermore, dosimetric advantage investigation of manually contrast-enhanced region overriding, especially the heart.Materials and methodsTen patients with lung cancer were considered. For each patient two planning CT sets were initially taken with and without CA. Treatment planning were optimized based on CT scans without CA. All plans were copied and recomputed on scans with CA. In addition, scans with IV contrast were copied and density correction was performed for heart contrast enhanced. Same plans were copied and replaced to undo dose calculation errors that may be caused by CA. Eventually, dosimetric evaluations based on dose volume histograms (DVHs) of planning target volumes (PTV) and organs at-risk were studied and analyzed using the Wilcoxon’s signed rank test.ResultsThere is no statistically significant difference in dose calculation for the PTV maximum, mean, minimum doses, spinal cord maximum doses and lung volumes that received 20 and 30 Gy, between planes calculated with and without contrast scans (p > 0.05) and also for contrast scan, with manual regions overriding.ConclusionsDose difference caused by the contrast agent is negligible and not significant. Therefore, there is no justification to perform two scans, and using an IV contrast enhanced scan for dose calculation is sufficient.     

Improving joint torque calculations: optimization-based inverse dynamics to reduce the effect of motion errors

The accuracy of joint torques calculated from inverse dynamics methods is strongly dependent upon errors in body segment motion profiles, which arise from two sources of noise: the motion capture system and movement artifacts of skin-mounted markers. The current study presents a method to increase the accuracy of estimated joint torques through the optimization of the angular position data used to describe these segment motions. To compute these angular data, we formulated a constrained nonlinear optimization problem with a cost function that minimizes the difference between the known ground reaction forces (GRFs) and the GRF calculated via a top-down inverse dynamics solution. To evaluate this approach, we constructed idealized error-free reference movements (of squatting and lifting) that produced a set of known “true” motions and associated true joint torques and GRF. To simulate real-world inaccuracies in motion data, these true motions were perturbed by artificial noise. We then applied our approach to these noise-induced data to determine optimized motions and related joint torques. To evaluate the efficacy of the optimization approach compared to traditional (bottom-up or top-down) inverse dynamics approaches, we computed the root mean square error (RMSE) values of joint torques derived from each approach relative to the expected true joint torques. Compared to traditional approaches, the optimization approach reduced the RMSE by 54% to 79%. Average reduction due to our method was 65%; previous methods only achieved an overall reduction of 30%. These results suggest that significant improvement in the accuracy of joint torque calculations can be achieved using this approach.     

On the possibility for computing the transmembrane potential in the heart with a one shot method: an inverse problem

We analyze the possibility for using body surface potential maps (BSPMs), a priori information about the voltage distribution in the heart and the bidomain equations to compute the transmembrane potential throughout the myocardium. Our approach is defined in terms of an inverse problem for elliptic partial differential equations (PDEs). More precisely, we formulate it in terms of an output least squares framework in which a goal functional is minimized subject to suitable PDE constraints. The problem is highly unstable and, even under optimal recording conditions, it does not have a unique solution. We propose a methodology for stabilizing and enforcing uniqueness for this inverse problem. Moreover, a fully implicit method for solving the involved minimization problem is presented. In other words, we show how one may solve it in terms of a system consisting of three linear elliptic PDEs, i.e. we derive a so-called one shot method (also commonly referred to as an all-at-once method). Finally, our theoretical findings are illuminated by a series of numerical experiments. These examples indicate that, in the presence of regional ischemia, it might be possible to approximately recover the transmembrane potential during the resting and plateau phases of the heart cycle. This is probably due to the fact that rather accurate a priori information is available during these time intervals. The problem of computing the transmembrane potential at an arbitrary time instance during a heart beat is still an open problem.     

The effect of change of background colour on the ultrastructure of the pars intermedia of the pituitary of the eel (Anguilla anguilla)

Summary Colour change in the eel resulted in marked ultrastructural changes in the pre-dominating (Type II) secretory cells of the pars intermedia of the pituitary. The effects on these cells of transferring eels from white to black backgrounds for periods of up to 56 days were: a) hypertrophy of the rough endoplasmic reticulum, which increased from 12 to 35% of the cytoplasmic volume; b) loss of secretory granules which decreased from 38 to 5% of the cytoplasmic volume; c) development of a system of fine (25–35 nm) tubules located especially at the secretory poles of the cells but also found in the region of the Golgi apparatus. The tubules were seen to connect with the plasma membrane, with the limiting membrane of the secretory granules, and in one instance to connect a granule with the plasma membrane. After glutaraldehyde fixation at pH 5, electron dense material similar to that found in the secretory granules was observed in the lumen of many of the tubules.The changes that occurred in black background eels are taken to indicate that the Type II cells of the pars intermedia are responsible for MSH secretion, particularly since these changes were reversed by returning eels to white backgrounds. The cytoplasmic tubules found in Type II cells may indicate a process for MSH release which does not involve granule extrusion, but rather direct transport of material from the Golgi apparatus to the cell membrane.The electron microscope facilities used in this investigation were funded by the Medical Research Council.     

Investigation on the surface properties of chemically modified natural fibers using inverse gas chromatography

This paper presents the application of inverse gas chromatography (IGC) technique for characterization and comparison of the surface properties of the natural fibers as reinforcement fillers in wood plastic composites. The effects of chemical modification using 1% NaOH were also studied. The fibers used for this work were Iranian cultivated eucalyptus, spruce, bagasse, and wheat straw. Chemical composition of fibers was found to be modified after treatment as characterized by Fourier transform infrared spectroscopy (FTIR). The crystallinity of fibers and the specific interaction was improved by the alkaline treatment, with more relevance to the agro-fibers. The IGC shows also a general increase in the wettability of the modified fiber when compared with the raw (unmodified) samples. Alkaline treatment achieves the best overall improvement in the properties evaluated of the agro-fibers when compared to the wood fibers.     

Estimation of external contact loads using an inverse dynamics and optimization approach: General method and application to sit-to-stand maneuvers

This paper presents a general method to estimate unmeasured external contact loads (ECLs) acting on a system whose kinematics and inertial properties are known. This method is dedicated to underdetermined problems, e.g. when the system has two or more unmeasured external contact wrenches. It is based on inverse dynamics and a quadratic optimization, and is therefore relatively simple, computationally cost effective and robust. Net joint loads (NJLs) are included as variables of the problem, and thus could be estimated in the same procedure as the ECL and be used within the cost function.     

Shape discrimination by wasps (<Emphasis Type="Italic">Paravespula germanica</Emphasis>) at the food source: generalization among various types of contrast

Wasps (Paravespula germanica) were trained and tested at an artificial feeding site, using convex shapes that produced colour contrast, luminance contrast, or motion contrast against the background. With each of the three types of contrast, we tested the wasps capacity to discriminate the learned shape from novel shapes. In addition, in each experiment we tested the wasps capability to recognize the learned shape when it offered a different type of contrast than that it had during the training. With the coloured shapes, a side-glance at the colour discrimination performance of the wasps was possible in addition. Wasps are found to discriminate between a variety of convex shapes regardless of the type of contrast that they produce against the background. Mainly, they discriminate the learned shape from novel shapes even if the colour of the shapes or the type of contrast they produce against the background is altered in the test. Thus, wasps generalize the learned shape from one colour to another, as well as between colour contrast, luminance contrast, and motion contrast.     

Forecasting the effect of feast and famine conditions on biological sulphate reduction in an anaerobic inverse fluidized bed reactor using artificial neural networks

The longevity and robustness of bioreactors used for wastewater treatment is determined by the activity of the microorganisms under steady and transient loading conditions. Two identical continuously operated inverse fluidized bed bioreactors (IFB), IFB R1 and IFB R2, were tested for sulphate removal under the same operating conditions for 140 d (Periods I–IV). Later, IFB R1 was used as the control reactor (Period V), while IFB R2 was operated under feast (Period V-A) and famine (Period V-B) feeding conditions for 66 d. The sulphate removal efficiency was comparable in both IFB, <20% in Period I and ∼70% during Periods II, III and IV. The robustness of the IFB was evident when the sulphate removal efficiency remained comparable during the feast Period (67 ± 15%) applied to IFB R2 compared to continuous feeding Periods (Period IV (71 ± 4%) for IFB R2 and Period V (61 ± 15%) for IFB R1). The IFB performance was modelled using a three-layered artificial neural networks (ANN) model (5-11-3) and a sensitivity analysis, the sulphate removal was found to be dependent on the COD:sulphate ratio. Besides, the robustness, resilience and adaptation time of the IFB were affected by the degree of mixing and the hydraulic retention time.     

Characterization of human passive muscles for impact loads using genetic algorithm and inverse finite element methods

The objective of this study is to identify the dynamic material properties of human passive muscle tissues for the strain rates relevant to automobile crashes. A novel methodology involving genetic algorithm (GA) and finite element method is implemented to estimate the material parameters by inverse mapping the impact test data. Isolated unconfined impact tests for average strain rates ranging from 136 s⁻¹ to 262 s⁻¹ are performed on muscle tissues. Passive muscle tissues are modelled as isotropic, linear and viscoelastic material using three-element Zener model available in PAMCRASH^TM explicit finite element software. In the GA based identification process, fitness values are calculated by comparing the estimated finite element forces with the measured experimental forces. Linear viscoelastic material parameters (bulk modulus, short term shear modulus and long term shear modulus) are thus identified at strain rates 136 s⁻¹, 183 s⁻¹ and 262 s⁻¹ for modelling muscles. Extracted optimal parameters from this study are comparable with reported parameters in literature. Bulk modulus and short term shear modulus are found to be more influential in predicting the stress-strain response than long term shear modulus for the considered strain rates. Variations within the set of parameters identified at different strain rates indicate the need for new or improved material model, which is capable of capturing the strain rate dependency of passive muscle response with single set of material parameters for wide range of strain rates.     

Bias correction for estimated QTL effects using the penalized maximum likelihood method

A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.     

Dynamical properties of model gene networks and implications for the inverse problem

We study the inverse problem, or the "reverse-engineering" problem, for two abstract models of gene expression dynamics, discrete-time Boolean networks and continuous-time switching networks. Formally, the inverse problem is similar for both types of networks. For each gene, its regulators and its Boolean dynamics function must be identified. However, differences in the dynamical properties of these two types of networks affect the amount of data that is necessary for solving the inverse problem. We derive estimates for the average amounts of time series data required to solve the inverse problem for randomly generated Boolean and continuous-time switching networks. We also derive a lower bound on the amount of data needed that holds for both types of networks. We find that the amount of data required is logarithmic in the number of genes for Boolean networks, matching the general lower bound and previous theory, but are superlinear in the number of genes for continuous-time switching networks. We also find that the amount of data needed scales as 2(K), where K is the number of regulators per gene, rather than 2(2K), as previous theory suggests.     

Model-based inverse estimation for active contraction stresses of tongue muscles using 3D surface shape in speech production

This paper presents a novel inverse estimation approach for the active contraction stresses of tongue muscles during speech. The proposed method is based on variational data assimilation using a mechanical tongue model and 3D tongue surface shapes for speech production. The mechanical tongue model considers nonlinear hyperelasticity, finite deformation, actual geometry from computed tomography (CT) images, and anisotropic active contraction by muscle fibers, the orientations of which are ideally determined using anatomical drawings. The tongue deformation is obtained by solving a stationary force-equilibrium equation using a finite element method. An inverse problem is established to find the combination of muscle contraction stresses that minimizes the Euclidean distance of the tongue surfaces between the mechanical analysis and CT results of speech production, where a signed-distance function represents the tongue surface. Our approach is validated through an ideal numerical example and extended to the real-world case of two Japanese vowels, /ʉ/ and /ɯ/. The results capture the target shape completely and provide an excellent estimation of the active contraction stresses in the ideal case, and exhibit similar tendencies as in previous observations and simulations for the actual vowel cases. The present approach can reveal the relative relationship among the muscle contraction stresses in similar utterances with different tongue shapes, and enables the investigation of the coordination of tongue muscles during speech using only the deformed tongue shape obtained from medical images. This will enhance our understanding of speech motor control.     

Analysis of the chromosomal distribution of transposon-carrying T-DNAs in tomato using the inverse polymerase chain reaction

We are developing a system for isolating tomato genes by transposon mutagenesis. In maize and tobacco, the transposon Activator (Ac) transposes preferentially to genetically linked sites. To identify transposons linked to various target genes, we have determined the RFLP map locations of Ac- and Dissociation (Ds)-carrying T-DNAs in a number of transformants. T-DNA flanking sequences were isolated using the inverse polymerase chain reaction (IPCR) and located on the RFLP map of tomato. The authenticity of IPCR reaction products was tested by several criteria including nested primer amplification, DNA sequence analysis and PCR amplification of the corresponding insertion target sequences. We report the RFLP map locations of 37 transposon-carrying T-DNAs. We also report the map locations of nine transposed Ds elements. T-DNAs were identified on all chromosomes except chromosome 6. Our data revealed no apparent chromosomal preference for T-DNA integration events. Lines carrying transposons at known map locations have been established which should prove a useful resource for isolating tomato genes by transposon mutagenesis.