Spectral image scanning microscopy

Fluorescence spectroscopic profiling of urine samples for predicting kidney transplant rejection

Rejection is the primary factor affecting the functionality of a kidney post-transplant, where its prompt prediction of risk significantly influences therapeutic strategies and clinical outcomes. Current graft health assessment methods, including serum creatinine measurements and transplant kidney puncture biopsies, possess considerable limitations. In contrast, urine serves as a direct indicator of the graft's degenerative stage and provides a more accurate measure than peripheral blood analysis, given its non-invasive collection of kidney-specific metabolite. This research entailed collecting fluorescent fingerprint data from 120 urine samples of post-renal transplant patients using hyperspectral imaging, followed by the development of a learning model to detect various forms of immunological rejection. The model successfully identified multiple rejection types with an average diagnostic accuracy of 95.56 %.Beyond proposing an innovative approach for predicting the risk of complications post-kidney transplantation, this study heralds the potential introduction of a non-invasive, rapid, and accurate supplementary method for risk assessment in clinical practice.

The Development of Microscopy for Super-Resolution: Confocal Microscopy, and Image Scanning Microscopy

Optical methods of super-resolution microscopy, such as confocal microscopy, structured illumination, nonlinear microscopy, and image scanning microscopy are reviewed. These methods avoid strong invasive interaction with a sample, allowing the observation of delicate biological samples. The meaning of resolution and the basic principles and different approaches to superresolution are discussed.

cSPARCOM: Multi-detector reconstruction by confocal super-resolution correlation microscopy

Image scanning microscopy (ISM), an upgraded successor of the ubiquitous confocal microscope, facilitates up to two-fold improvement in lateral resolution, and has become an indispensable element in the toolbox of the bio-imaging community. Recently, super-resolution optical fluctuation image scanning microscopy (SOFISM) integrated the analysis of intensity-fluctuations information into the basic ISM architecture, to enhance its resolving power. Both of these techniques typically rely on pixel-reassignment as a fundamental processing step, in which the parallax of different detector elements to the sample is compensated by laterally shifting the point spread function (PSF). Here, we propose an alternative analysis approach, based on the recent high-performing sparsity-based super-resolution correlation microscopy (SPARCOM) method. Through measurements of DNA origami nano-rulers and fixed cells labeled with organic dye, we experimentally show that confocal SPARCOM (cSPARCOM), which circumvents pixel-reassignment altogether, provides enhanced resolution compared to pixel-reassigned based analysis. Thus, cSPARCOM further promotes the effectiveness of ISM, and particularly that of correlation based ISM implementations such as SOFISM, where the PSF deviates significantly from spatial invariance.

Advances in imaging and analysis of 4 fluorescent components through the rat cortical column

BACKGROUND

Immunofluorescent staining coupled with axial optical sectioning allows for assessment of native three-dimensional structure of brain tissue. Typical challenges of analyzing network structure include limitations driven by magnification/field of view, spatial resolution, tissue thickness, staining quality of dense cell types, data quantifiability and the quantity of simultaneous staining targets.

NEW METHOD

This manuscript demonstrates many methodological advancements. Software-aided alignment of the cortical slice and stereotaxic atlas maximizes ROI-identification accuracy. Tissue compression during antigen retrieval enhances epitope availability without damaging tissue. A thorough factorial experiment focusing on Smi-311 staining highlights the enhancements in image quality from our extended staining protocol. Mosaic scanning techniques and subsequent four-channel alignment ensures high data quality.

RESULTS

Cortical column datasets [800μm x 3000μm x 70μm] utilizing sequential optical sectioning were successfully generated from three rats. Each rat provided three coronal sections in each of two regions, M1 and S1BF, from which data cubes were generated per hemisphere, totaling 36 high-magnification four-color datasets.

COMPARISON WITH EXISTING METHOD(S)

Typical confocal assessments of brain tissue do not utilize such thick tissue slices nor collect entire cortical columns from the cortical surface to the grey/white interface at a resolution that can map fine filamentous processes. The simultaneous collection of our four specific structural markers - neuronal, astrocytic, vascular and nuclear - is novel and the quantitative optimization of staining protocols through a factorial design rare.

CONCLUSIONS

Building upon this preliminary success in protocol development, future work will encompass volumetric modeling and quantitative analysis of regional network architecture.