A simple method for using silicone elastomer masks for quantitative analysis of cell migration without cellular damage or substrate disruption

Cell migration is fundamental to many biological processes, including development, normal tissue remodeling, wound healing, and many pathologies. However, cell migration is a complex process, and understanding its regulation in health and disease requires the ability to manipulate and measure this process quantitatively under controlled conditions. This report describes a simple in vitro assay for quantitative analysis of cell migration in two-dimensional cultures that is an inexpensive alternative to the classic “scratch” assay. The method described utilizes flexible silicone masks fabricated in the lab according to the research demands of the specific experiment to create a cell-free area for cells to invade, followed by quantitative analysis based on widely available microscopic imaging tools. This experimental approach has the important advantage of visualizing cell migration in the absence of the cellular damage and disruption of the substrate that occurs when the “wound” is created in the scratch assay. This approach allows the researcher to study the intrinsic migratory characteristics of cells in the absence of potentially confounding contributions from cellular responses to injury and disruption of cell–substrate interactions. This assay has been used with vascular smooth muscle cells, fibroblasts, and epithelial cell types, but should be applicable to the study of practically any type of cultured cell. Furthermore, this method can be easily adapted for use with fluorescence microscopy, molecular biological, or pharmacological manipulations to explore the molecular mechanisms of cell migration, live cell imaging, fluorescence microscopy, and correlative immunolabeling.     

Storage and reproductive strategy of the carpet-shell clam,Ruditapes decussatus in the Gulf of Gabès (Tunisia)

In this study, the variations of glycogen concentrations in Ruditapes decussatus from Sfax coasts (Tunisia) were described in relation to the reproductive cycle. Separate analyses were made of gonad, adductor muscle and ‘remainder’. The timing of gametogenic development and spawning was evaluated using qualitative histology associated with image analysis including (1) the estimation of the gonadal occupation index (GOI), (2) surface area occupied by reserve tissues and (3) variation in oocyte diameter. The reproductive cycle of R. decussatus exhibited partial asynchronization between sexes, the major difference being observed in the duration of the spawning period. Contrary to previous studies, we observed continuous partial spawning (e.g. 50% of ripe oocytes still subsisted at the partial spawning stage). During the gametogenic cycle, GOI varied significantly in males and in females. Most oocytes were ripe and ready to spawn when their diameter reached or exceeded 45?µm. The expansion of gonad was inversely proportional to the development of the foot tissue. Glycogen concentration showed significant temporal variations between tissues, indicating the clear differentiation in energy storage between the clam organs.     

In situ quantification of fish‐cage fouling by underwater photography and image analysis

Close‐up underwater photography and image analysis were used to quantify mesh occlusion by biofouling of salmon‐cage netting. This technique allows fast, non‐destructive sampling of cages in situ for the determination of temporal and spatial changes in fouling. The area of net blockage can be easily determined, allowing rapid evaluation of cleaning or antifouling performance.     

Nutrients determine the spatial architecture of Paracoccus sp. biofilm

Bacterial biofilms adapt and shape their structure in response to varied environmental conditions. A statistical methodology was adopted in this study to empirically investigate the influence of nutrients on biofilm structural parameters deduced from confocal scanning laser microscope images of Paracoccus sp.W1b, a denitrifying bacterium. High concentrations of succinate, Mg⁺⁺, Ca⁺⁺, and Mn⁺⁺ were shown to enhance biofilm formation whereas higher concentration of iron decreased biofilm formation. Biofilm formed at high succinate was uneven with high surface to biovolume ratio. Higher Mg⁺⁺ or Ca⁺⁺ concentrations induced cohesion of biofilm cells, but contrasting biofilm architectures were detected. Biofilm with subpopulation of pillar-like protruding cells was distributed on a mosaic form of monolayer cells in medium with 10 mM Mg⁺⁺. 10 mM Ca⁺⁺ induced a dense confluent biofilm. Denitrification activity was significantly increased in the Mg⁺⁺- and Ca⁺⁺-induced biofilms. Chelator treatment of various biofilm ages indicated that divalent cations are important in the initial stages of biofilm formation.     

Phenoscope: an automated large‐scale phenotyping platform offering high spatial homogeneity

Increased phenotyping accuracy and throughput are necessary to improve our understanding of quantitative variation and to be able to deconstruct complex traits such as those involved in growth responses to the environment. Still, only a few facilities are known to handle individual plants of small stature for non‐destructive, real‐time phenotype acquisition from plants grown in precisely adjusted and variable experimental conditions. Here, we describe Phenoscope, a high‐throughput phenotyping platform that has the unique feature of continuously rotating 735 individual pots over a table. It automatically adjusts watering and is equipped with a zenithal imaging system to monitor rosette size and expansion rate during the vegetative stage, with automatic image analysis allowing manual correction. When applied to Arabidopsis thaliana, we show that rotating the pots strongly reduced micro‐environmental disparity: heterogeneity in evaporation was cut by a factor of 2.5 and the number of replicates needed to detect a specific mild genotypic effect was reduced by a factor of 3. In addition, by controlling a large proportion of the micro‐environmental variance, other tangible sources of variance become noticeable. Overall, Phenoscope makes it possible to perform large‐scale experiments that would not be possible or reproducible by hand. When applied to a typical quantitative trait loci (QTL) mapping experiment, we show that mapping power is more limited by genetic complexity than phenotyping accuracy. This will help to draw a more general picture as to how genetic diversity shapes phenotypic variation.     

Mapping the navigational knowledge of individually foraging ants,Myrmecia croslandi

Ants are efficient navigators, guided by path integration and visual landmarks. Path integration is the primary strategy in landmark-poor habitats, but landmarks are readily used when available. The landmark panorama provides reliable information about heading direction, routes and specific location. Visual memories for guidance are often acquired along routes or near to significant places. Over what area can such locally acquired memories provide information for reaching a place? This question is unusually approachable in the solitary foraging Australian jack jumper ant, since individual foragers typically travel to one or two nest-specific foraging trees. We find that within 10 m from the nest, ants both with and without home vector information available from path integration return directly to the nest from all compass directions, after briefly scanning the panorama. By reconstructing panoramic views within the successful homing range, we show that in the open woodland habitat of these ants, snapshot memories acquired close to the nest provide sufficient navigational information to determine nest-directed heading direction over a surprisingly large area, including areas that animals may have not visited previously.     

Using Head Patch Pattern as a Reliable Biometric Character for Noninvasive Individual Recognition of an Endangered Pitviper Protobothrops mangshanensis

Mangshan pitviper, Protobothrops mangshanensis(formerly Zhaoermia mangshanensis) is endemic to China. Unfortunately, due to the decreasing size of its wild populations, this snake has been listed as critically endangered. Research carried out on the Mangshan pitviper's population ecology and captive reproduction has revealed that the unique head patch patterns of different individuals may potentially be used as a noninvasive recognition biometric character. We collected head patch pattern images of 40 individuals of P. mangshanensis between 1994 and 2011. By comparing each pitviper's head patch pattern, we found that the head patch pattern of individual snakes was different and unique. Additionally, we observed and recorded the head patch pattern characters of four adults and five juveniles before and after ecdysis. Our findings confirmed that head patch patterns of Mangshan pitvipers are unique and stable, remaining unchanged after ecdysis. Thus, individuals can be quickly identified by examining the head patch pattern within a specific recognition area on the head. This method may be useful for noninvasive individual recognition in many other species that display color patch pattern variations, especially in studies of endangered species where the use of invasive marking techniques is undesirable.     

Robust algorithm for brain magnetic resonance image (MRI) classification based on GARCH variances series

In this paper, a robust algorithm for disease type determination in brain magnetic resonance image (MRI) is presented. The proposed method classifies MRI into normal or one of the seven different diseases. At first two-level two-dimensional discrete wavelet transform (2D DWT) of input image is calculated. Our analysis show that the wavelet coefficients of detail sub-bands can be modeled by generalized autoregressive conditional heteroscedasticity (GARCH) statistical model. The parameters of GARCH model are considered as the primary feature vector. After feature vector normalization, principal component analysis (PCA) and linear discriminant analysis (LDA) are used to extract the proper features and remove the redundancy from the primary feature vector. Finally, the extracted features are applied to the K-nearest neighbor (KNN) and support vector machine (SVM) classifiers separately to determine the normal image or disease type. Experimental results indicate that the proposed algorithm achieves high classification rate and outperforms recently introduced methods while it needs less number of features for classification.