Ct3d: tracking microglia motility in 3D using a novel cosegmentation approach

A new method for primary culture of microglia in rats with spinal cord injury

At present, the primary culture method of microglia is complicated, and the culture of spinal cord microglia is rare, so we will explore to establish a new and efficient primary culture method of microglia in rats with spinal cord injury (SCI). The SCI model of SD rats was established by modified A11en's method, and the model of SCI was performed on 1 d, 3 d, 7 d and 14 d respectively. Then the injured spinal cord was removed, mechanically separated and filtered. The morphology of microglia was observed the next day and its purity was identified by CD11b and Iba1 immunofluorescence labeling. According to the above results, the morphological changes of microglia after 3 d of SCI were observed at 1 d, 2 d and 4 d. The results showed that the purity of microglia was 98%. The number of microglia after 3 d of SCI was the most. After SCI, the migration ability of microglia was enhanced, the number of microglia in the injured area increased, and the number was the highest at 3 d, then gradually decreased. In addition, the microglia after SCI would gradually change from active state to resting state with the passage of time. Therefore, we can use a simple and efficient mechanical separation method to extract primary microglia, which provides the basis for the study of microglia.

Correction of uneven illumination in color microscopic image based on fully convolutional network

The correction of uneven illumination in microscopic image is a basic task in medical imaging. Most of the existing methods are designed for monochrome images. An effective fully convolutional network (FCN) is proposed to directly process color microscopic image in this paper. The proposed method estimates the distribution of illumination information in input image, and then carry out the correction of the corresponding uneven illumination through a feature encoder module, a feature decoder module, and a detail supplement module. In this process, overlapping residual blocks are designed to better transfer the illumination information, and in particular a well-designed weighted loss function ensures that the network can not only correct the illumination but also preserve image details. The proposed method is compared with some related methods on real pathological cell images qualitatively and quantitatively. Experimental results show that our method achieves the excellent performance. The proposed method is also applied to the preprocessing of whole slide imaging (WSI) tiles, which greatly improves the effect of image mosaicking.

Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast

Image segmentation is a key process in analyzing biological images. However, it is difficult to detect the differences between foreground and background when the image is unevenly illuminated. The unambiguous segmenting of multi-well plate microscopy images with various uneven illuminations is a challenging problem. Currently, no publicly available method adequately solves these various problems in bright-field multi-well plate images. Here, we propose a new method based on contrast values which removes the need for illumination correction. The presented method is effective enough to distinguish foreground and therefore a model organism (Caenorhabditis elegans) from an unevenly illuminated microscope image. In addition, the method also can solve a variety of problems caused by different uneven illumination scenarios. By applying this methodology across a wide range of multi-well plate microscopy images, we show that our approach can consistently analyze images with uneven illuminations with unparalleled accuracy and successfully solve various problems associated with uneven illumination. It can be used to process the microscopy images captured from multi-well plates and detect experimental subjects from an unevenly illuminated background.

β-Arrestin1 regulates the morphology and dynamics of microglia in zebrafish in vivo

Microglia are the primary immune cells in the central nervous system. Microglia typically exist in a 'resting' state in the healthy brain, with ramified processes dynamically exploring the surrounding microenvironment. They become 'activated' under pathological conditions with marked changes in morphology. However, the regulation of their morphology dynamics remains poorly understood. Here, using in vivo time-lapse imaging and three-dimensional morphology analysis of microglia in intact zebrafish larvae, we found that β-arrestin1, a multifunctional protein involved in various signal transductions, cell-autonomously regulated the microglial morphology. Knockdown of β-arrestin1 increased the volume size and process number of microglia but reduced the deformation speed in the resting state. Meanwhile, β-arrestin1 down-regulation led to a high frequency of phagocytic behaviour of microglia. These defects were partially rescued by over-expressing human β-arrestin1 in microglia. Our study indicated that microglial dynamics in the resting state can be regulated cell-autonomously by β-arrestin1 signalling.

Automated adjustment of region-based active contour parameters using local image geometry

A principled method for active contour (AC) parameterization remains a challenging issue in segmentation research, with a potential impact on the quality, objectivity, and robustness of the segmentation results. This paper introduces a novel framework for automated adjustment of region-based AC regularization and data fidelity parameters. Motivated by an isomorphism between the weighting factors of AC energy terms and the eigenvalues of structure tensors, we encode local geometry information by mining the orientation coherence in edge regions. In this light, the AC is repelled from regions of randomly oriented edges and guided toward structured edge regions. Experiments are performed on four state-of-the-art AC models, which are automatically adjusted and applied on benchmark datasets of natural, textured and biomedical images and two image restoration models. The experimental results demonstrate that the obtained segmentation quality is comparable to the one obtained by empirical parameter adjustment, without the cumbersome and time-consuming process of trial and error.

Neurobiology of microglial action in CNS injuries: receptor-mediated signaling mechanisms and functional roles

Microglia are the first line of immune defense against central nervous system (CNS) injuries and disorders. These highly plastic cells play dualistic roles in neuronal injury and recovery and are known for their ability to assume diverse phenotypes. A broad range of surface receptors are expressed on microglia and mediate microglial 'On' or 'Off' responses to signals from other host cells as well as invading microorganisms. The integrated actions of these receptors result in tightly regulated biological functions, including cell mobility, phagocytosis, the induction of acquired immunity, and trophic factor/inflammatory mediator release. Over the last few years, significant advances have been made toward deciphering the signaling mechanisms related to these receptors and their specific cellular functions. In this review, we describe the current state of knowledge of the surface receptors involved in microglial activation, with an emphasis on their engagement of distinct functional programs and their roles in CNS injuries. It will become evident from this review that microglial homeostasis is carefully maintained by multiple counterbalanced strategies, including, but not limited to, 'On' and 'Off' receptor signaling. Specific regulation of theses microglial receptors may be a promising therapeutic strategy against CNS injuries.

Similarity maps and hierarchical clustering for annotating FT-IR spectral images

Background

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization.

Results

We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy.

Conclusions

We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward’s clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

Evaluation of the effectiveness of simple nuclei-segmentation methods on Caenorhabditis elegans embryogenesis images

BACKGROUND

For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei.

RESULTS

Here, we selected six simple methods from various watershed based and local maxima detection based methods that are frequently used for nuclei segmentation, and evaluated their segmentation accuracy for each developmental stage of the Caenorhabditis elegans. We included a 4D noise filter, in addition to 2D and 3D noise filters, as a pre-processing step to evaluate the potential of simple methods as widely as possible. By applying the methods to image data between the 50- to 500-cell developmental stages at 50-cell intervals, the error rate for nuclei detection could be reduced to ≤ 2.1% at every stage until the 350-cell stage. The fractions of total errors throughout the stages could be reduced to ≤ 2.4%. The error rates improved at most of the stages and the total errors improved when a 4D noise filter was used. The methods with the least errors were two watershed-based methods with 4D noise filters. For all the other methods, the error rate and the fraction of errors could be reduced to ≤ 4.2% and ≤ 4.1%, respectively. The minimum error rate for each stage between the 400- to 500-cell stages ranged from 6.0% to 8.4%. However, similarities between the computational and manual segmentations measured by volume overlap and Hausdorff distance were not good. The methods were also applied to Drosophila and zebrafish embryos and found to be effective.

CONCLUSIONS

The simple segmentation methods were found to be useful for detecting nuclei until the 350-cell stage, but not very useful after the 400-cell stage. The incorporation of a 4D noise filter to the simple methods could improve their performances. Error types and the temporal biases of errors were dependent on the methods used. Combining multiple simple methods could also give good segmentations.

Quantitating the subtleties of microglial morphology with fractal analysis

It is well established that microglial form and function are inextricably linked. In recent years, the traditional view that microglial form ranges between “ramified resting” and “activated amoeboid” has been emphasized through advancing imaging techniques that point to microglial form being highly dynamic even within the currently accepted morphological categories. Moreover, microglia adopt meaningful intermediate forms between categories, with considerable crossover in function and varying morphologies as they cycle, migrate, wave, phagocytose, and extend and retract fine and gross processes. From a quantitative perspective, it is problematic to measure such variability using traditional methods, but one way of quantitating such detail is through fractal analysis. The techniques of fractal analysis have been used for quantitating microglial morphology, to categorize gross differences but also to differentiate subtle differences (e.g., amongst ramified cells). Multifractal analysis in particular is one technique of fractal analysis that may be useful for identifying intermediate forms. Here we review current trends and methods of fractal analysis, focusing on box counting analysis, including lacunarity and multifractal analysis, as applied to microglial morphology.

Immunohistochemistry, histopathology and infrared spectral histopathology of colon cancer tissue sections

During the past years, many studies have shown that infrared spectral histopathology (SHP) can distinguish different tissue types and disease types independently of morphological criteria. In this manuscript, we report a comparison of immunohistochemical (IHC), histopathological and spectral histopathological results for colon cancer tissue sections. A supervised algorithm, based on the "random forest" methodology, was trained using classical histopathology, and used to automatically identify colon tissue types, and areas of colon adenocarcinoma. The SHP images subsequently were compared to IHC-based images. This comparison revealed excellent agreement between the methods, and demonstrated that label-free SHP detects compositional changes in tissue that are the basis of the sensitivity of IHC.

Reciprocal regulation between resting microglial dynamics and neuronal activity in vivo

Microglia are the primary immune cells in the brain. Under physiological conditions, they typically stay in a "resting" state, with ramified processes continuously extending to and retracting from surrounding neural tissues. Whether and how such highly dynamic resting microglia functionally interact with surrounding neurons are still unclear. Using in vivo time-lapse imaging of both microglial morphology and neuronal activity in the optic tectum of larval zebrafish, we found that neuronal activity steers resting microglial processes and facilitates their contact with highly active neurons. This process requires the activation of pannexin-1 hemichannels on neurons. Reciprocally, such resting microglia-neuron contact reduces both spontaneous and visually evoked activities of contacted neurons. Our findings reveal an instructive role for neuronal activity in resting microglial motility and suggest the function for microglia in homeostatic regulation of neuronal activity in the healthy brain.