Kidney disease, the ninth leading cause of death in the United States, suffers from poor diagnostic efficiency (10%). Traditional biopsies use molecular reagents to enhance diagnostic power but are limited by overlapping spatial and chromatic signals, product quality variability, and additional processing. To address these challenges without disrupting routine diagnostics, we implement label-free imaging modalities—stimulated Raman scattering (SRS), second harmonic generation (SHG), and two-photon fluorescence (TPF)—within a single setup. We identify morphological, lipidomic, and metabolic biomarkers in control and diabetic kidney samples at subcellular resolution. Label-free Stimulated Raman Histology (SRH) reveals distinct collagen morphology, mesangial-glomerular volumes, lipid saturation, redox status, and lipid-protein concentrations previously unrecognized in kidney diseases. Using the same tissue section enhances diagnostic value without compromising limited tissue. These multimodal biomarkers broadly deepen the understanding of kidney disease progression by integrating lipidomic, fibrotic, and metabolic data.

Significance: This article demonstrates a high-throughput technique to map cell images to cell positions. The technology uses a three-dimensional (3D) imaging flow cytometer to record multiparameter 3D cell images at a throughput of 1,000 cells/s and a cell placement robot to place the exiting cells from the imaging system on a filter plate in a first-in–first-out manner so the cells on the plate have the same order as the cells that are imaged. Innovative algorithms were developed to match the cell sequences from the imaging and placement modules to detect and eliminate errors to ensure high accuracy. The technology forms an unprecedented bridge between single-cell molecular analysis and single-cell image analysis to connect phenotype and genotype analysis with single-cell resolution.

Enhanced intestinal permeability is a pervasive issue in modern medicine, with implications demonstrably associated with significant health consequences such as sepsis, multiorgan failure, and death. Key issues involve the trigger mechanisms that could compromise intestinal integrity and increase local permeability allowing the passage of larger, potentially dangerous molecules. Heat stress, whether exertional or environmental, may modulate intestinal permeability and begs interesting questions in the context of global climate change, increasing population vulnerabilities, and public health. Emerging evidence indicates that intestinal leakage of digestive enzymes and associated cell dysfunctions––a process referred to as autodigestion––may play a critical role in systemic physiological damage within the body. This increased permeability is exacerbated in the presence of elevated core temperatures. We employed Latent Dirichlet Allocation (LDA) topic modeling methods to analyze the relationship between heat stress and the nascent theory of autodigestion in a systematic, quantifiable, and unbiased manner. From a corpus of 11,233 scientific articles across four relevant scientific journals (Gut, Shock, Temperature, Gastroenterology), it was found that over 1,000 documents expressed a relationship between intestine, enhanced permeability, core temperature, and heat stress. The association has grown stronger in recent years, as heat stress and potential autodigestion are investigated in tandem, yet still by a limited number of specific research studies. Such findings justify the design of future studies to critically test novel interventions against digestive enzymes permeating the intestinal tract, especially the small intestine.

Stimulated Raman Scattering (SRS) nanoscopy imaging offers unprecedented insights into tissue molecular architecture but often requires stitching multiple high-resolution tiles to capture large fields of view. This process is time-consuming and frequently introduces vignetting artifacts—grid-like intensity fluctuations that degrade image quality and hinder downstream quantitative analyses and processing such as super-resolution deconvolution. We present VIgnetted Stitched-Tile Adjustment using Morphological Adaptive Processing (VISTAmap), a simple tool that corrects these shading artifacts directly on the final stitched image. VISTAmap automatically detects the tile grid configuration by analyzing intensity frequency variations and then applies sequential morphological operations to homogenize the image. In contrast to conventional approaches that require increased tile overlap or pre-acquisition background sampling, VISTAmap offers a pragmatic, post-processing solution without the need for separate individual tile images. This work addresses pressing concerns by delivering a robust, efficient strategy for enhancing mosaic image uniformity in modern nanoscopy, where the smallest details make tremendous impacts.