A robust ex vivo method to evaluate the diffusion properties of agents in biological tissues

A robust method is presented for evaluating the diffusion properties of chemicals in ex vivo biological tissues. Using this method that relies only on thickness and collimated transmittance measurements, the diffusion properties of glycerol, fructose, polypropylene glycol and water in muscle tissues were evaluated. Amongst other results, the diffusion coefficient of glycerol in colorectal muscle was estimated with a value of 3.3 × 10−7 cm2/s. Due to the robustness and simplicity of the method, it can be used in other fields of biomedical engineering, namely in organ cryoprotection and food industry

Cortical Arousal Strategies in Left-Handers during the Aural Perception and Manual Playback of Mono- and Polyphonic Rhythmical Patterns

The actual purpose of this study is to establish the cortical arousal strategies (according to the power of the EEG (electroencephalogram) α-oscillations) during the aural perception as well as manual playback of mono- and polyphonic rhythmical patterns in men with left profile. The study involved 35 men from 19 to 21 years old with the left profile of the manual and aural asymmetries. EEG was recorded in the functional status of rest: during the aural perception and playback of mono- and polyphonic rhythmical patterns with the left and right hand fingers. The monophony in the rhythmical pattern sounding relative to monophonic patterns is followed by more expressed and widespread cortical processes of the EEG α-oscillation depression. Given patterns indicate a greater intensity of ascending nonspecific arousal strategies of data processing by men on conditions of the sound and harmonious complications of the pattern structure. The aural perception and playback of rhythmical patterns with both hands were accompanied by the increased significance of arousal processes in the right hemisphere. This may be due to the dominant role of the hemisphere during the formation of the innervation impacts on the left-hander’s neuro-motor apparatus. More differentiated changes in the cerebral cortex were installed during the left hand activation

Control of glycolytic dynamics by hexose transport in Saccharomyces cerevisiae

AbstractIt is becoming accepted that steady-state fluxes are not necessarily controlled by single rate-limiting steps. This leaves open the issue whether cellular dynamics are controlled by single pacemaker enzymes, as has often been proposed. This paper shows that yeast sugar transport has substantial but not complete control of the frequency of glycolytic oscillations. Addition of maltose, a competitive inhibitor of glucose transport, reduced both average glucose consumption flux and frequency of glycolytic oscillations. Assuming a single kinetic component and a symmetrical carrier, a frequency control coefficient of between 0.4 and 0.6 and an average-flux control coefficient of between 0.6 and 0.9 were calculated for hexose transport activity. In a second approach, mannose was used as the carbon and free-energy source, and the dependencies on the extracellular mannose concentration of the transport activity, of the frequency of oscillations, and of the average flux were compared. In this case the frequency control coefficient and the average-flux control coefficient of hexose transport activity amounted to 0.7 and 0.9, respectively. From these results, we conclude that 1) transport is highly important for the dynamics of glycolysis, 2) most but not all control resides in glucose transport, and 3) there should at least be one step other than transport with substantial control

Morphological segmentation analysis and texture-based support vector machines classification on mice liver fibrosis microscopic images

Background To reduce the intensity of the work of doctors, pre-classification work needs to be issued. In this paper, a novel and related liver microscopic image classification analysis method is proposed. Objective For quantitative analysis, segmentation is carried out to extract the quantitative information of special organisms in the image for further diagnosis, lesion localization, learning and treating anatomical abnormalities and computer-guided surgery. Methods in the current work, entropy based features of microscopic fibrosis mice’ liver images were analyzed using fuzzy c-cluster, k-means and watershed algorithms based on distance transformations and gradient. A morphological segmentation based on a local threshold was deployed to determine the fibrosis areas of images. Results the segmented target region using the proposed method achieved high effective microscopy fibrosis images segmenting of mice liver in terms of the running time, dice ratio and precision. The image classification experiments were conducted using Gray Level Co-occurrence Matrix (GLCM). The best classification model derived from the established characteristics was GLCM which performed the highest accuracy of classification using a developed Support Vector Machine (SVM). The training model using 11 features was found to be as accurate when only trained by 8 GLCMs. Conclusion The research illustrated the proposed method is a new feasible research approach for microscopy mice liver image segmentation and classification using intelligent image analysis techniques. It is also reported that the average computational time of the proposed approach was only 2.335 seconds, which outperformed other segmentation algorithms with 0.8125 dice ratio and 0.5253 precision