Factor H's Control of Complement Activation Emerges as a Significant and Promising Therapeutic Target for Alzheimer's Disease Treatment.

The complement is a component of the innate immune system designed to fight infections and tissue- or age-related damages. Complement activation creates an inflammatory microenvironment, which enhances cell death. Excessive complement inflammatory activity has been linked to alterations in the structure and functions of the blood-brain barrier, contributing to a poor prognosis for Alzheimer's disease (AD). In the AD preclinical phase, individuals are often clinically asymptomatic despite evidence of AD neuropathology coupled with heightened inflammation. Considering the involvement of the complement system in the risk of developing AD, we hypothesize that inhibiting complement activation could reduce this inflammatory period observed even before clinical signs, thereby slowing down the onset/progression of AD. To validate our hypothesis, we injected complement inhibitor factor H into the brain of APP/PS1 AD mice at early or late stages of this pathology. Our results showed that the injection of factor H had effects on both the onset and progression of AD by reducing proinflammatory IL6, TNF-α, IL1ß, MAC and amyloid beta levels. This reduction was associated with an increase in VGLUT1 and Psd95 synaptic transmission in the hippocampal region, leading to an improvement in cognitive functions. This study invites a reconsideration of factor H's therapeutic potential for AD treatment.

3D imaging and morphometric descriptors of vascular networks on optically cleared organs.

The vascular system is a multi-scale network whose functionality depends on its structure, and for which structural alterations can be linked to pathological shifts. Though biologists use multiple 3D imaging techniques to visualize vascular networks, the 3D image processing methodologies remain sources of biases, and the extraction of quantitative morphometric descriptors remains flawed. The article, first, reviews the current 3D image processing methodologies, and morphometric descriptors of vascular network images mainly obtained by light-sheet microscopy on optically cleared organs, found in the literature. Second, it proposes operator-independent segmentation and skeletonization methodologies using the freeware ImageJ. Third, it gives more extractable network-level (density, connectivity, fractal dimension) and segment-level (length, diameter, tortuosity) 3D morphometric descriptors and how to statistically analyze them. Thus, it can serve as a guideline for biologists using 3D imaging techniques of vascular networks, allowing the production of more comparable studies in the future.

Computational Identification and 3D Morphological Characterization of Renal Glomeruli in Optically Cleared Murine Kidneys.

The aim of this study was to establish an accessible methodology for the objective identification and 3D morphological characterization of renal glomeruli in mice. 3D imaging of the renal cortex was performed by light sheet microscopy on iDISCO+ optical cleared kidneys of six C57BL/6J mice after labelling of the capillary endothelium by lectin injection. 3D images were processed with the open source software ImageJ, and statistical analysis done with GraphPad Prism. Non-visual delimitation of the external surface of the glomeruli was ensured by greyscale-based thresholding, the value of which was determined from the statistical analysis of the voxel frequency distribution. Exclusion of false-positive identification was done by successive volume- and shape-based segmentation. Renal glomeruli were characterized by their number, surface area, volume, and compactness. Average data were expressed as mean ± SD. The number of glomeruli was equal to 283 ± 35 per mm3 of renal tissue, representing 1.78 ± 0.49% of the tissue volume. The surface area, volume and compactness were equal to 20,830 ± 6200 µm², 62,280 ± 14,000 µm3 and 0.068 ± 0.026, respectively. The proposed standardized methodology allows the identification of the renal glomeruli and their 3D morphological characterization, and is easily accessible for biologists.

3D Imaging and Quantitative Characterization of Mouse Capillary Coronary Network Architecture.

Characterization of the cardiac capillary network structure is of critical importance to understand the normal coronary functional properties and coronary microvascular diseases. The aim of our study was to establish an accessible methodology for 3D imaging and 3D processing to quantitatively characterize the capillary coronary network architecture in mice. Experiments were done on C57BL/6J mice. 3D imaging was performed by light sheet microscopy and confocal microscopy on iDISCO+ optical cleared hearts after labelling of the capillary endothelium by lectin injection. 3D images were processed with the open source software ImageJ. Non-visual image segmentation was based of the frequency distribution of the voxel greyscale values, followed by skeletonization and distance mapping. Capillary networks in left and right ventricles and septum were characterized by the volume network density, the fractal dimension, the number of segments and nodes and their ratio, the total network length, and the average length, diameter, and tortuosity of the segments. Scale-dependent parameter values can be impacted by the resolution limit of the 3D imaging technique. The proposed standardized methodology for 3D image processing is easily accessible for a biologist in terms of investment and difficulty level, and allows the quantification of the 3D capillary architecture and its statistical comparison in different conditions.