Multiphoton microscopy (MPM) provides high-resolution imaging of deep tissue structures while allowing for the visualization of non-labeled biological samples. However, photon generation efficiency of intrinsic biomarkers is low and this, coupled with inherent detection inaccuracies in the photoelectric sensors, leads to an introduction of noise in acquired images. Higher dwelling times can reduce noise but increase the likelihood of photobleaching. To combat this, deep learning methods are being increasingly employed to denoise MPM images, allowing for a more efficient and less invasive process. However, machine learning models can hallucinate information, which is unacceptable for critical scientific microscopy applications. Uncertainty quantification, which has been demonstrated for image-to-image regression tasks, can provide confidence bounds for machine learning-based image reconstruction tasks, adding confidence to predictions. In this work, we discuss incorporating uncertainty quantification into an optimized denoising model to guide adaptive multiphoton microscopy image acquisition. We demonstrate that our method is capable of maintaining fine features in the denoised image, while outperforming other denoising methods by adaptively selecting to reimage the most uncertain pixels in a human endometrium tissue sample.
Label-free nonlinear microscopy allows for high-resolution and three-dimensional imaging of live biological specimens without the need for exogenous labels. The integration of multiple modalities further enhances molecular specificity and visualization diversity for metabolic and structural mapping of heterogeneous tissue architectures. In this work, we introduce high-speed simultaneous label-free autofluorescence-multiharmonic (hSLAM) microscopy, where a high-peak-power adaptive fiber source based on multimode fiber (MMF) is employed with a nonlinear fiber piano. We will also talk about how the higher speed SLAM enables multicellular dynamics in living tissues with higher spectral flexibility and peak power, providing new possibilities for bioimaging.
Engineered tissues offer great promise as engrafted therapies and in vitro models, but these tissues require a vascular network to retain viability at large scales. Significant efforts are focused on optimizing these in vitro vascular constructs, yet current evaluation methods require fixation and immunostaining. These destructive evaluation methods alter vascular network morphology, and cannot non-invasively monitor vascular assembly over time. Here, we demonstrate that autofluorescence multiphoton microscopy (MPM) can quantitatively assess the morphology of living 3D vascular networks without fixation, labels, or dyes. Autofluorescence MPM was used to non-invasively monitor the effect of culture conditions on 3D vascular network formation. Human embryonic stem (ES) cell-derived endothelial cells and primary human pericytes cultured in polyethylene glycol (PEG) hydrogels self-assembled into 3D vascular networks. Autofluorescence MPM of the metabolic co-enzyme NAD(P)H (excitation/emission wavelengths of 750 nm/400-460 nm) was used to quantify morphological parameters at day 6 of culture. Specifically, vessel diameter, vascular density, branch point density, and integration of endothelial cells into the network were quantified. Dynamic culture conditions (flow at 1μL/sec) led to vascular networks with higher mean vessel diameter compared to static culture (p<0.05). Standard immunohistochemistry found that vascular networks were positive for markers of endothelial cells, pericytes, and tight junctions. Scanning electron micrographs confirmed vessel lumen formation with pericytes wrapped around vessels. Dye transit of FITC-dextran through the network confirmed leaky endothelial barrier function. Our results demonstrate that autofluorescence MPM can non-invasively evaluate in vitro 3D vascular networks, and could be used for quality control of engineered tissues.
“Mice are not little people” – a refrain becoming louder as the gaps between animal models and human disease become more apparent. At the same time, three emerging approaches are headed toward integration: powerful systems biology analysis of cell-cell and intracellular signaling networks in patient-derived samples; 3D tissue engineered models of human organ systems, often made from stem cells; and micro-fluidic and meso-fluidic devices that enable living systems to be sustained, perturbed and analyzed for weeks in culture. Integration of these rapidly moving fields has the potential to revolutionize development of therapeutics for complex, chronic diseases, including those that have weak genetic bases and substantial contributions from gene-environment interactions. Technical challenges in modeling complex diseases with “organs on chips” approaches include the need for relatively large tissue masses and organ-organ cross talk to capture systemic effects, such that current microfluidic formats often fail to capture the required scale and complexity for interconnected systems. These constraints drive development of new strategies for designing in vitro models, including perfusing organ models, as well as “mesofluidic” pumping and circulation in platforms connecting several organ systems, to achieve the appropriate physiological relevance.
KEYWORDS: Liver, Microfluidics, Tissues, In vitro testing, In vivo imaging, Toxicology, Tumor growth modeling, Mode conditioning cables, System integration, Drug discovery
A new cell culture analog has been developed. It is based on the standard multiwell cell culture plate format but it provides perfused three-dimensional cell culture capability. The new capability is achieved by integrating microfluidic valves and pumps into the plate. The system provides a means to conduct high throughput assays for target validation and predictive toxicology in the drug discovery and development process. It can be also used for evaluation of long-term
exposure to drugs or environmental agents or as a model to study viral hepatitis, cancer metastasis, and other diseases and pathological conditions.
Biological applications of MEMS technology (bioMEMS) is of increasing interest in the development of miniature and portable instrumentation for cell-based microassays and sensor applications. A major bioMEMS challenge is the physical incorporation of living cells into sensors and diagnostic devices and creation of the environmental conditions conducive for organization of differentiated cells into tissue-like structures. Our work towards these goals is illustrated by a tissue-based bioassay system we are developing based on a miniature cross-flow bioreactor constructed from of an array of cell-filled microchannels integrated into an environmentally-controlled polymer microfluidics manifold. We describe our microchannel array and manifold manufacturing methods and report on the in vitro culture of cell populations in the bioreactor.
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