μManager is an open-source, cross-platform desktop application, to control a wide variety of motorized microscopes, scientific cameras, stages, illuminators, and other microscope accessories. Since its inception in 2005, μManager has grown to support a wide range of microscopy hardware and is now used by thousands of researchers around the world. The application provides a mature graphical user interface and offers open programming interfaces to facilitate plugins and scripts. Here, we present a guide to using some of the recently added advanced μManager features, including hardware synchronization, simultaneous use of multiple cameras, projection of patterned light onto a specimen, live slide mapping, imaging with multi-well plates, particle localization and tracking, and high-speed imaging.
SUMMARY
The oral mucosa is one of the most rapidly dividing tissues in the body and serves as a barrier to physical and chemical insults from mastication, food, and microorganisms. Breakdown of this barrier can lead to significant morbidity and potentially life-threatening infections for patients. Determining the identity and organization of oral epithelial progenitor cells (OEPCs) is therefore paramount to understanding their roles in homeostasis and disease. Using lineage tracing and label retention experiments, we show that rapidly-dividing OEPCs are located broadly within the basal layer of the mucosa throughout the oral cavity. Quantitative clonal analysis demonstrated that OEPCs undergo population asymmetrical divisions following neutral drift dynamics and that they respond to chemotherapyinduced damage by altering daughter cell fates. Finally, using single cell RNAseq, we establish the basal layer population structure and propose a model that defines the organization of cells within the basal layer.
Background
Previous analyses of factors influencing footfall timings and gait selection in quadrupeds have focused on the implications for energetic cost or gait mechanics separately. Here we present a model for symmetrical walking gaits in quadrupedal mammals that combines both factors, and aims to predict the substrate contexts in which animals will select certain ranges of footfall timings that (1) minimize energetic cost, (2) minimize rolling and pitching moments, or (3) balance the two. We hypothesize that energy recovery will be a priority on all surfaces, and will be the dominant factor determining footfall timings on flat, ground-like surfaces. The ability to resist pitch and roll, however, will play a larger role in determining footfall choice on narrower and more complex branch-like substrates. As a preliminary test of the expectations of the model, we collected sample data on footfall timings in a primate with relatively high flexibility in footfall timings – the squirrel monkey (
Saimiri sciureus
) – walking on a flat surface, straight pole, and a pole with laterally-projecting branches to simulate simplified ground and branch substrates. We compare limb phase values on these supports to the expectations of the model.
Results
As predicted, walking steps on the flat surface tended towards limb phase values that promote energy exchange. Both pole substrates induced limb phase values predicted to favor reduced pitching and rolling moments.
Conclusions
These data provide novel insight into the ways in which animals may choose to adjust their behavior in response to movement on flat versus complex substrates and the competing selective factors that influence footfall timing in mammals. These data further suggest a pathway for future investigations using this perspective.
Multiphoton microscopy is a powerful technique for deep in vivo imaging in scattering samples. However, it requires precise, sample-dependent increases in excitation power with depth in order to generate contrast in scattering tissue, while minimizing photobleaching and phototoxicity. We show here how adaptive imaging can optimize illumination power at each point in a 3D volume as a function of the sample’s shape, without the need for specialized fluorescent labeling. Our method relies on training a physics-based machine learning model using cells with identical fluorescent labels imaged in situ. We use this technique for in vivo imaging of immune responses in mouse lymph nodes following vaccination. We achieve visualization of physiologically realistic numbers of antigen-specific T cells (~2 orders of magnitude lower than previous studies), and demonstrate changes in the global organization and motility of dendritic cell networks during the early stages of the immune response. We provide a step-by-step tutorial for implementing this technique using exclusively open-source hardware and software.
Myeloid-derived cells such as monocytes, dendritic cells (DCs), and macrophages are at the heart of the immune effector function in an inflammatory response. But because of the lack of an efficient imaging system to trace these cells live during their migration and maturation in their native environment at sub-cellular resolution, our knowledge is limited to data available from specific time-points analyzed by flow cytometry, histology, genomics and other immunological methods. Here, we have developed a ratiometric imaging method for measuring monocyte maturation in inflamed mouse lungs in situ using real-time using 2-photon imaging and complementary methods. We visualized that while undifferentiated monocytes were predominantly found only in the vasculature, a semi-differentiated monocyte/macrophage population could enter the tissue and resembled more mature and differentiated populations by morphology and surface phenotype. As these cells entered and differentiated, they were already selectively localized near inflamed airways and their entry was associated with changes in motility and morphology. We were able to visualize these during the act of differentiation, a process that can be demonstrated in this way to be faster on a per-cell basis under inflammatory conditions. Finally, our in situ analyses demonstrated increases, in the differentiating cells, for both antigen uptake and the ability to mediate interactions with T cells. This work, while largely confirming proposed models for in situ differentiation, provides important in situ data on the coordinated site-specific recruitment and differentiation of these cells and helps elaborate the predominance of immune pathology at the airways. Our novel imaging technology to trace immunogenic cell maturation in situ will complement existing information available on in situ differentiation deduced from other immunological methods, and assist better understanding of the spatio-temporal cellular behavior during an inflammatory response.
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