Testing abnormality in the spatial arrangement of cells in the corneal endothelium using spatial point processes

Spatial Pattern Analysis using Closest Events (SPACE)-A Nearest Neighbor Point Pattern Analysis Framework for Assessing Spatial Relationships from Digital Images

The quantitative description of biological structures is a valuable yet difficult task in the life sciences. This is commonly accomplished by imaging samples using fluorescence microscopy and analyzing resulting images using Pearson's correlation or Manders' co-occurrence intensity-based colocalization paradigms. Though conceptually and computationally simple, these approaches are critically flawed due to their reliance on signal overlap, sensitivity to cursory signal qualities, and inability to differentiate true and incidental colocalization. Point pattern analysis provides a framework for quantitative characterization of spatial relationships between spatial patterns using the distances between observations rather than their overlap, thus overcoming these issues. Here we introduce an image analysis tool called Spatial Pattern Analysis using Closest Events (SPACE) that leverages nearest neighbor-based point pattern analysis to characterize the spatial relationship of fluorescence microscopy signals from image data. The utility of SPACE is demonstrated by assessing the spatial association between mRNA and cell nuclei from confocal images of cardiac myocytes. Additionally, we use synthetic and empirical images to characterize the sensitivity of SPACE to image segmentation parameters and cursory image qualities such as signal abundance and image resolution. Ultimately, SPACE delivers performance superior to traditional colocalization methods and offers a valuable addition to the microscopist's toolbox.

Th1 polarization of T cells injected into the cerebrospinal fluid induces brain immunosurveillance

Although CD4 T cells reside within the cerebrospinal fluid, it is yet unclear whether and how they enter the brain parenchyma and migrate to target specific Ags. We examined the ability of Th1, Th2, and Th17 CD4 T cells injected intracerebroventricularly to migrate from the lateral ventricles into the brain parenchyma in mice. We show that primarily Th1 cells cross the ependymal layer of the ventricle and migrate within the brain parenchyma by stimulating an IFN-γ-dependent dialogue with neural cells, which maintains the effector function of the T cells. When injected into a mouse model of Alzheimer's disease, amyloid-β (Aβ)-specific Th1 cells target Aβ plaques, increase Aβ uptake, and promote neurogenesis with no evidence of pathogenic autoimmunity or neuronal loss. Overall, we provide a mechanistic insight to the migration of cerebrospinal fluid CD4 T cells into the brain parenchyma and highlight implications on brain immunity and repair.

MORPHOMETRIC ANALYSIS OF HUMAN CORNEAL ENDOTHELIUM BY MEANS OF SPATIAL POINT PATTERNS

This paper presents a method for detecting abnormalities in spatial arrangements of cells within any tissue that can be described by different sets of relevant points. The method has been applied to the detection of subtle abnormalities in corneal endothelia. Images of this type of tissue can be characterized by two types of points: cell centroids and triple points associated with the apical intersections as it was proposed by Díaz.7 Both types of points jointly considered are modeled using a bivariate spatial point process; then a statistical analysis based on certain distributional descriptors proposed by Doguwa4,9 is carried out to discriminate severe and subtle abnormalities from controls. According to the results, the method constitutes a valid alternative to currently used techniques, which involve statistical descriptions of cell density, cell area and hexagonality, that fail in the detection of these subtle abnormalities.

Inferring biological mechanisms from spatial analysis: prediction of a local inhibitor in the ovary

Female mammals are born with a lifetime's supply of oocytes individually enveloped in flattened epithelial cells to form primordial follicles. It is not clear how sufficient primordial follicles are maintained to sustain the reproductive lifespan, while providing an adequate supply of mature oocytes for ovulation. Locally produced growth factors are thought to be critical regulators of early follicle growth, but knowledge of their identity and source remains incomplete. Here, we have used a simple approach of spatial analysis of structures in histological tissue sections to identify likely sources of such regulatory molecules, narrowing the field for future screening for candidate growth factors or antagonists. We have quantified the relative spatial positions of primordial (resting) follicles and growing follicles in mice on days 4, 8, and 12 after birth, and calculated interfollicular distances. Follicles were significantly less likely to have started growing if they had 1 or more primordial follicles close by (within 10 mum), predicting that primordial follicles inhibit each other. This approach allows us to hypothesize that primordial follicles produce a diffusible inhibitor that prevents neighboring primordial follicles from growing. Such an approach has wide applicability within many branches of developmental and cell biology for studying spatial signaling within tissues and cells.

Spatial clustering analysis in neuroanatomy: applications of different approaches to motor nerve fiber distribution

Spatial organization of the nerve fibers in the peripheral nerves may be important for the studies of axonal regeneration, the degenerative nerve diseases and the construction of interfaces with peripheral nerves, such as nerve prostheses. Functional topography of motor axons related to the gastrocnemius muscle was revealed in the ventral spinal roots by retrograde tracing. Gastrocnemius muscles of adult rats were injected with the tracer Fluoro-Gold. After 3 days of survival the animals were sacrificed and their ventral roots were harvested, sectioned, and imaged on a fluorescence microscope. Maps of the traced fibers were automatically analyzed using a novel approach, local spatial clustering statistics, that tested for occurrences of clusters of motor fibers and visualized them. Thresholds indicating the presence of clustering at various scales of observation were computed based on series of Monte Carlo simulations of random spatial point patterns. Clusters were visualized by kernel interpolation. The approach was tested on simulated data and subsequently applied to the motor fiber maps in the ventral roots. Results revealed clustering of the motor fibers innervating the gastrocnemius muscle at the level of the L6 ventral spinal root. The analysis was validated using Voronoi tessellation and nearest neighbor analysis.

Granulometric analysis of corneal endothelium specular images by using a germ-grain model

Specular microscopy is widely used to study the human corneal endothelium status in vivo. In this paper, the corneal endothelium is represented as a binary image composed of the cell inscribed circles. The granulometric distribution function of the complement of this image is used as a functional descriptor, which provides information about the shape, size and spatial arrangement of cells. Experimental evaluation using bootstrap techniques shows its ability to discriminate between controls and pathological cases. It represents a reliable and graphical alternative to the classical indices (cell density, hexagonality and coefficient of variation of cell areas), which behave poorly when detecting subtle abnormalities.