Biology subjects

Stegmayr, J.

Publications and source records attributed to Stegmayr, J..

4 recordsLinked to original sources

bioRxiv2023

Deep learning for rapid and reproducible histology scoring of lung injury in a porcine model

Acute respiratory distress syndrome (ARDS) is a life-threatening condition with mortality rates between 30-50%. Although in vitro models replicate some aspects of ARDS, small and large animal models remain the primary research tools due to the multifactorial nature of the disease. When using these animal models, histology serves as the gold standard method to confirm lung injury and exclude other diagnoses as high-resolution chest images are often not feasible. Semi-quantitative scoring performed by independent observers is the most common form of histologic analysis in pre-clinical animal models of ARDS. Despite progress in standardizing analysis procedures, objectively comparing histological injuries remains challenging, even for highly-trained pathologists. Standardized scoring simplifies the task and allows better comparisons between research groups and across different injury models, but it is time-consuming, and interobserver variability remains a significant concern. Convolutional neural networks (CNNs), which have emerged as a key tool in image analysis, could automate this process, potentially enabling faster and more reproducible analysis. Here we explored the reproducibility of human standardized scoring for an animal model of ARDS and its suitability for training CNNs for automated scoring at the whole slide level. We found large variations between human scorers, even for pre-clinical experts and board-certified pathologies in evaluating ARDS animal models. We demonstrate that CNNs (VGG16, EfficientNetB4) are suitable for automated scoring and achieve up to 83% F1-score and 78% accuracy. Thus, CNNs for histopathological classification of acute lung injury could help reduce human variability and eliminate a time-consuming manual research task with acceptable performance.

bioinformatics↗

bioRxiv2022

Simultaneous isolation of proximal and distal lung progenitor cells from individual mice using a 3D printed guide reduces proximal cell contamination of distal lung epithelial cell isolations

The respiratory epithelium consists of multiple, functionally distinct cell-types and is maintained by regionally-specific progenitor populations which repair the epithelium following injury. Several in vitro methods exist for studying lung epithelial repair using primary murine lung epithelial cells, but isolation methods are hampered by a lack of surface markers distinguishing epithelial progenitors along the respiratory epithelium. Here, we developed a 3D-printed lobe divider (3DLD) to aid in simultaneous isolation of proximal versus distal lung epithelial progenitors from individual mice which give rise to differentiated epithelia in multiple in vitro assays. In contrast to 3DLD-isolated distal progenitor cells, classic manual tracheal ligation methods followed by lobe removal resulted in co-isolation of rare proximal progenitors with distal cells which altered the transcriptional landscape of distal organoid cultures. Thus, cell isolation with the 3DLD generates reproducible distal versus proximal progenitor populations and minimizes the potential for contaminating populations to confound in vitro assays. HighlightsO_LI3DLD reproducibly separates lung lobes and extrapulmonary airways (bronchi/trachea) C_LIO_LI3DLD cell isolation yields consistent isolation of distal epithelial cells (DECs) C_LIO_LIContamination of proximal cells in classic DEC isolations may alter in vitro results C_LIO_LI3DLD allows for simultaneous isolation of proximal and DECs from single animals C_LI eTOC blurbAlsafadi et al. describes a new method for simultaneous isolation of lung epithelial proximal and distal progenitors using the aid of a 3D printed device (3DLD). Both isolated cell types differentiate in multiple in vitro assays. The 3DLD guide minimized contamination of proximal cells in distal cell isolations whose presence can alter the transcriptional landscape of distal epithelial organoids.

cell biology↗

bioRxiv2020

Isolation of high yield and quality RNA from human precision-cut lung slices for RNA-sequencing and computational integration with larger patient cohorts

Precision-cut lung slices (PCLS) have gained increasing interest as a model to study lung biology and disease, as well as for screening novel therapeutics. In particular, PCLS derived from human tissue can better recapitulate some aspects of lung biology and disease as compared to PCLS derived from animals (e.g. clinical heterogeneity), but access to human tissue is limited. A number of different experimental readouts have been established for use with PCLS, but obtaining high yield and quality RNA for downstream gene expression analysis has remained challenging. This is particularly problematic for utilizing the power of next-generation sequencing techniques, such as RNA-sequencing (RNA-seq), for non-biased and high through-put analysis of PCLS human cohorts. In the current study, we present a novel approach for isolating high quality RNA from a small amount of tissue, including diseased human tissue, such as idiopathic pulmonary fibrosis (IPF). We show that the RNA isolated using this method is of sufficient quality for both RT-qPCR and RNA-seq analysis. Furthermore, the RNA-seq data from human PCLS was comparable to data generated from native tissue and could be used in several established computational pipelines, including deconvolution of bulk RNA-seq data using publicly available single-cell RNA-seq data sets. Deconvolution using Bisque revealed a diversity of cell populations in human PCLS derived from distal lung tissue, including several immune cell populations, which correlated with cell populations known to be present and aberrant in human disease, such as IPF.

molecular biology↗

bioRxiv2018

Galectin-3, A Novel Endogenous Trem2 Ligand, Regulates Inflammatory Response and Aβ Fibrilation in Alzheimer’s Disease

Alzheimers disease (AD) is a progressive neurodegenerative disease in which the formation of extracellular aggregates of amyloid beta (A{beta}) peptide, intraneuronal tau neurofibrillary tangles and microglial activation are major pathological hallmarks. One of the key molecules involved in microglial activation is galectin-3 (gal3), and we demonstrate here for the first time a key role of gal3 in AD pathology. Gal3 was highly upregulated in the brains of AD patients and 5xFAD (familial Alzheimers disease) mice, and found specifically expressed in microglia associated with A{beta} plaques. Single nucleotide polymorphisms in the LGALS3 gene, which encodes gal3, were associated to an increased risk of AD. Gal3 deletion in 5xFAD mice attenuated microglia-associated immune responses, particularly those associated with TLR and TREM2/DAP12 signaling. In vitro data demonstrated the requirement of gal3 to fully activate microglia in response to fibrillar A{beta}. Gal3 deletion decreased the A{beta} burden in 5xFAD mice and improved cognitive behavior. Electron microscopy of gal3 in AD mice demonstrated i) a preferential expression of gal3 by plaque-associated microglia, ii) its presence in the extracellular space and iii) its association to A{beta} plaques. Low concentrations (1 nM) of pure gal3 promoted cross-seeding fibrilization of pure A{beta}. Importantly, a single intrahippocampal injection of gal3 along with A{beta} monomers in WT mice was sufficient to induce the formation of insoluble A{beta} aggregates that were absent when gal3 was lacking. High-resolution microscopy (STORM) demonstrated close co-localization of gal3 and TREM2 in microglial processes, and a direct interaction was shown by a fluorescence anisotropy assay involving the gal3 CRD domain. Furthermore, gal3 stimulated the TREM2-DAP12 signaling pathway. In conclusion, we provide evidence that gal3 is a central regulator of microglial immune response in AD. It drives proinflammatory activation and A{beta} aggregation, as well as acting as an endogenous ligand to TREM2, a key receptor driving microglial response under disease conditions. Gal3 inhibition may, hence, be a potential pharmacological approach to counteract AD.

neuroscience↗