M. C. Skala

This study quantifies collagen reorganization in murine melanoma during immunotherapy using second harmonic generation imaging, finding treatment-induced changes in collagen fiber morphology and density.

This study investigates the dual role of naive primary neutrophils in the tumor microenvironment, showing they both restrict tumor invasion and hinder NK cell penetration through ROS and NETs.

This study examines how Toxoplasma gondii infection alters host cell metabolism using multiple techniques, finding similar metabolic changes during infection and the pre-invasion 'kiss and spit' process.

This study uses optical coherence tomography to analyze the mechanical properties of human fetal membranes under dynamic loading, identifying the amnion as the load-bearing layer and location-dependent thickness variations.

The paper introduces an open-source library to streamline single-cell analysis of multi-dimensional microscopy images, providing tools for quality checking, automation, and visualization of trends.

This paper introduces a light sheet FLIM system using SPAD arrays for fast, label-free single-cell NAD(P)H autofluorescence imaging in live cells and organisms.

This paper uses optical metabolic imaging to classify human lymphocyte activation and subtype with high accuracy using autofluorescence lifetime parameters.

The paper investigates metabolic adaptations in winner and loser oncogenic mutant stem cells in skin epidermis, revealing distinct metabolic strategies that drive cell competition outcomes.

This study identifies CD4+/CD8+ double positive T cells as mediators of xenogeneic GVHD but with limited GVL activity.

This study uses label-free live-cell imaging and machine learning to track reprogramming of human somatic cells and identify high-quality iPSCs with ~95% accuracy.

The paper evaluates individual patient-derived cancer organoids using optical metabolic imaging to predict therapeutic response and identify subclonal populations and resistance mechanisms.

This study evaluates how baseline culture conditions affect therapeutic response and heterogeneity in mouse-derived cancer organoids, finding that initial size is the key factor influencing growth and response.

This study uses redox imaging to track individual cancer organoids and assess treatment response by measuring metabolic and morphological changes.

The paper investigates how interactions with pancreatic stromal cells affect the redox state of cancer cells, finding that these interactions promote a more oxidized redox state in cancer cells.

This study introduces an adaptable pump system to generate pulsatile flows from cardiac spheroids, enabling modeling of endothelial cell behavior under different mechanical stresses.

This study shows graphene nanoflakes manipulate membrane cholesterol, altering cell signaling in fibroblasts and neurons.

This study uses optical metabolic imaging to predict pancreatic cancer patient treatment response by analyzing cellular heterogeneity in organoids.

This paper develops a label-free method using NAD(P)H and FAD autofluorescence imaging and machine learning to classify T cell activation states and subtypes with high accuracy.