Ashley L. Kiemen

Quantitative Donor Histology and Transcriptomics Link Pancreatic Composition and Precancers Across the Adult Lifespan

The paper quantifies PanIN burden and pancreatic composition across age to identify high-risk demographics associated with increased precancer burden.

TiSAM: fusing spatial and histopathology foundation models for whole-slide image segmentation

TiSAM improves whole-slide image segmentation by fusing spatial and histopathology features, achieving high accuracy across diverse datasets and scanners.

CODAvision: best practices and a user-friendly interface for rapid, customizable segmentation of medical images

CODAvision provides a user-friendly interface for rapid, customizable medical image segmentation using deep learning, enabling non-experts to train and evaluate models across diverse imaging modalities.

Muscle Loss as a Foundational Step in the Development and Evolution of the Turtle Shell

The paper investigates muscle loss as a key evolutionary step in turtle shell development using multi-modal imaging and histology-based deep learning to analyze turtle embryos.

Virtual multiplex staining of the pancreatic islets across type 1 diabetes progression using a Schroedinger bridge

This paper introduces SMILE, a diffusion model for converting H&E stains to multiplex IHC images, showing superior performance in pancreatic islet analysis and breast cancer stain conversion.

Whole organism 3D mapping reveals universal branching topology and biophysical optimization governs vascular and nervous system development

The paper uses 3D imaging to analyze vascular and nervous systems in embryos, finding shared structural principles but distinct architectures shaped by biophysical constraints.

STAPLE: automating spatial transcriptomics analysis and AI interpretation

STAPLE automates spatial transcriptomics analysis by integrating multiple tools into a modular framework and provides AI-driven interpretation of results.

Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer

The paper develops a 3D multi-omic pipeline using deep learning to analyze chemotherapy response in pancreatic cancer, identifying molecular signatures of resistance and fibroblast-cancer interactions.

3D, multi-omic imaging reveals molecular biomarkers of the pre-metastatic niche in lung cancer

This study uses 3D multi-omic imaging to identify biomarkers of the pre-metastatic niche in lung cancer, revealing myeloid and senescent cell signatures associated with metastasis risk.

A disrupted compartment boundary underlies abnormal cardiac patterning and congenital heart defects

The paper identifies Tbx5 as a gene critical for forming a compartment boundary in the interventricular septum, and shows its disruption leads to congenital heart defects.

3D multi-omic mapping of whole nondiseased human fallopian tubes at cellular resolution reveals a large incidence of ovarian cancer precursors

The paper presents a 3D multi-omic framework to detect and characterize ovarian cancer precursors in fallopian tubes, identifying TP53 mutations in microscopic lesions.

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

The paper introduces a framework for mathematical modeling of multicellular systems using interpretable cell behavior rules derived from biological knowledge and multi-omics data.

Myc and Kras cooperate in adult acinar cells to drive phenotypic heterogeneity, metastasis, and therapeutic resistance in a novel pancreatic cancer mouse model

This study develops a novel pancreatic cancer mouse model by expressing Myc and mutant Kras in adult acinar cells, showing metastasis and therapeutic resistance similar to human PDAc.

PIVOT: an open-source tool for multi-omic spatial data registration

PIVOT is an open-source tool for nonlinear registration of multi-omic spatial data, demonstrating improved throughput compared to existing workflows.

Integration of nuclear morphology and 3D imaging to profile cellular neighborhoods

The paper integrates 3D imaging with nuclear segmentation to analyze nuclear morphology in human tissue, revealing spatial patterns and interactions in disease progression.

Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic responders

This study uses spatial multi-omics to identify TLS-associated immune niches in PDAC that correlate with improved survival in immunotherapy responders.

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

The paper profiles the immune microenvironment of PanINs in 3D at single-cell resolution to understand inflammation's role in cancer progression and finds immune heterogeneity and correlations with PanIN grade.

High-motility pro-tumorigenic monocytes drive macrophage enrichment in the tumor microenvironment

This study identifies high-motility tumor-associated monocytes (TAMos) that drive macrophage infiltration and cancer cell proliferation via IL-6 and MAPK pathways, suggesting IL-6 as a therapeutic target.

qMAP Enabled Microanatomical Mapping of Human Skin Aging

This study introduces qMAP, a deep learning-based workflow for microanatomical mapping of human skin, identifying 10 core processes strongly associated with aging and achieving age prediction accuracy comparable to epigenetic clocks.

Skin keratinocyte-derived SIRT1 and BDNF modulate mechanical allodynia in mouse models of diabetic neuropathy

This study shows that SIRT1 and BDNF in skin keratinocytes reduce mechanical allodynia in diabetic neuropathy by maintaining Meissner corpuscle innervation.

Generative interpolation and restoration of images using deep learning for improved 3D tissue mapping

This paper uses a generative AI model to improve 3D tissue imaging by interpolating and restoring images, enhancing resolution and reducing artifacts across multiple modalities and species.

Three-dimensional reconstruction of fetal rhesus macaque kidneys at single-cell resolution reveals complex inter-relation of structures

This paper uses deep learning to label 17 kidney microstructures in 3D fetal rhesus macaque kidneys, revealing spatial relationships between glomeruli, arteries, and nephrons.

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

This paper introduces SpaceMarkers, a method to infer molecular changes from cell-cell interactions in spatial transcriptomics data, applied to tumor-immune interactions in metastasis and immunotherapy.