A5042417846- Electrospun Nanofibers in Biomedical Applications
- Cell Image Analysis Techniques
- Nerve injury and regeneration
- Advanced Sensor and Energy Harvesting Materials
- Tissue Engineering and Regenerative Medicine
- Silk-based biomaterials and applications
- Adversarial Robustness in Machine Learning
- RNA Interference and Gene Delivery
- 3D Printing in Biomedical Research
- Image Processing Techniques and Applications
- Advanced Fluorescence Microscopy Techniques
- Neural Networks and Applications
- Cellular Mechanics and Interactions
- Machine Learning and Data Classification
- Digital Imaging for Blood Diseases
- Single-cell and spatial transcriptomics
- Viral Infectious Diseases and Gene Expression in Insects
- Genetics, Bioinformatics, and Biomedical Research
- Advanced Neural Network Applications
- Explainable Artificial Intelligence (XAI)
- Organoboron and organosilicon chemistry
- Spinal Cord Injury Research
- Nanoparticle-Based Drug Delivery
- Molecular Biology Techniques and Applications
- CRISPR and Genetic Engineering
National Center for Advancing Translational Sciences
2019-2023
National Institutes of Health
2019-2023
American Axle & Manufacturing (United States)
2019-2023
National Institute of Standards and Technology
2016-2022
National Institute of Standards
2020
National Eye Institute
2019
VA Ann Arbor Healthcare System
2018-2019
University of Michigan
2018-2019
Material Measurement Laboratory
2016-2019
Michigan United
2019
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals institutes across diverse modalities facing these have designed specification process (OME-NGFF) address needs. This paper brings together wide range those members describe cloud-optimized itself-OME-Zarr-along with tools data resources available today increase FAIR access remove barriers...
We address the problem of segmenting cell contours from microscopy images human induced pluripotent Retinal Pigment Epithelial stem cells (iRPE) using Convolutional Neural Networks (CNN). Our goal is to compare accuracy gains CNN-based segmentation by (1) un-annotated via Generative Adversarial (GAN), (2) annotated out-of-bio-domain transfer learning, and (3) a priori knowledge about microscope imaging mapped into geometric augmentations small collection images. First, GAN learns an abstract...
Increases in the number of cell therapies preclinical and clinical phases have prompted need for reliable noninvasive assays to validate transplant function biomanufacturing. We developed a robust characterization methodology composed quantitative bright-field absorbance microscopy (QBAM) deep neural networks (DNNs) noninvasively predict tissue cellular donor identity. The was validated using clinical-grade induced pluripotent stem cell–derived retinal pigment epithelial cells (iPSC-RPE)....
Immediately following spinal cord injury, further injury can occur through several secondary cascades. As a consequence of cell lysis, an increase in extracellular Ca(2+) results additional neuronal loss by inducing apoptosis. Thus, hydrogels that reduce concentration may severity. The goal this study was to develop composite consisting alginate, chitosan, and genipin interact with enable situ gelation while maintaining elastic modulus similar native (∼1000 Pa). It hypothesized incorporation...
In this study, we created a new method of electrospinning capable controlling the surface structure individual fibers (fiber nanotopography). The nanotopographical features were by phase separation in as they formed. To control separation, nonsolvent (a chemical insoluble with polymer) was added to an solution containing poly-l-lactic acid (PLLA) and chloroform. nanotopography electrospun PLLA/chloroform smooth. However, adding small weight (<2% total solution) single (water, ethanol, or...
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals institutes across diverse modalities facing these have designed specification process (OME-NGFF) address needs. This paper brings together wide range those members describe cloud-optimized itself -- OME-Zarr along with tools data resources available today increase FAIR access remove...
The surface of aligned, electrospun poly-L-lactic acid (PLLA) fibers was chemically modified to determine if chemistry and hydrophilicity could improve neurite extension from chick dorsal root ganglia. Specifically, diethylenetriamine (DTA, for amine functionalization), 2-(2-aminoethoxy)ethanol (AEO, alcohol or GRGDS (cell adhesion peptide) were covalently attached the fibers. Water contact angle measurements revealed that modification significantly improved fiber compared unmodified (p <...
A promising component of biomaterial constructs for neural tissue engineering are electrospun fibers, which differentiate stem cells and neurons as well direct neurite growth. However, means protecting neurons, glia, seeded on fibers between lab surgical suite have yet to be developed. Here we report an effort accomplish this using cell-encapsulating hydrogel made by interfacial polyelectrolyte complexation (IPC). IPC-hydrogel were created interfacing acid-soluble chitosan (AsC)...
Following central nervous system (CNS) injury, activated astrocytes form a glial scar that inhibits the migration of axons ultimately leading to regeneration failure. Biomaterials developed for CNS repair can provide local delivery therapeutics and/or guidance mechanisms encourage cell into damaged regions brain or spinal cord. Electrospun fibers are promising type biomaterial injury since these direct cellular and axonal while slowly delivering therapy site. In this study, it was...
Cell viability, an essential measurement for cell therapy products, lacks traceability. One of the most common viability tests is trypan blue dye exclusion where blue-stained cells are counted via brightfield imaging. Typically, live and dead classified based on their pixel intensities which may vary arbitrarily making it difficult to compare results. Herein, a traceable absorbance microscopy method determine intracellular uptake demonstrated. The intensity pixels images converted used...
Currently, it is unknown how the mechanical properties of electrospun fibers, and presentation surface nanotopography influence macrophage gene expression protein production. By further elucidating specific fiber (mechanical or properties) alter behavior, may be possible to create scaffolds capable initiating unique cellular tissue responses. In this study, we determined elastic modulus rigidity fibers with varying topographies created by finely controlling humidity including a non-solvent...
SEQUIN is a web-based application (app) that allows fast and intuitive analysis of RNA sequencing data derived for model organisms, tissues, single cells. Integrated app functions enable uploading datasets, quality control, gene set enrichment, visualization, differential expression analysis. We also developed the iPSC Profiler, practical module scoring tool helps measure compare pluripotent differentiated cell types. Benchmarking to other commercial non-commercial products underscored...
Benzoxaboroles are a family of organoboron molecules, which have been finding over the past few years an increasing number biological applications, notably for design new drugs. Given that these molecules still relatively in biomedical context, very investigations regarding their formulation reported to date. Here, complete study on benzoxaboroles biopolymer, poly-l-lactic acid (PLLA), is reported. The incorporation two small benzoxaboroles, namely simplest benzoxaborole molecule (BBzx) and...
Superparamagnetic iron oxide nanoparticles (SPIONs) can generate heat when subjected to an alternating magnetic field (AMF). In the European Union, SPIONs actuated by AMF are used in hyperthermia treatment of glioblastoma multiforme, aggressive form brain cancer. Current data from clinical trials suggest that this therapy improves patient life expectancy, but their effect on healthy cells is virtually unknown. Thus, a viability study involving was carried out cortical rat astrocytes, most...
Cell-scaffold contact measurements are derived from pairs of co-registered volumetric fluorescent confocal laser scanning microscopy (CLSM) images (z-stacks) stained cells and three types scaffolds (i.e., spun coat, large microfiber, medium microfiber). Our analysis the acquired terabyte-sized collection is motivated by need to understand nature shape dimensionality (1D vs 2D 3D) cell-scaffold interactions relevant tissue engineers that grow on biomaterial scaffolds.We designed five...
Predicting Retinal Pigment Epithelium (RPE) cell functions in stem implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of therapies. Such function predictions can be carried out Artificial Intelligence (AI) based models. In this paper we used Traditional Machine Learning (TML) and Deep (DL) AI models prediction tasks. TML depend on feature engineering DL perform automatically but have higher modeling complexity. This work aims at exploring...
The purpose of this work was to develop an assessment technique and subsequent metrics that help in developing understanding the balance between network size task performance simple model networks. Here, exhaustive tests on neural networks datasets are used validate both approach derived from it. concept layer state space is introduced as a mechanism for utilization, where on/off activation all neurons input. Neural efficiency computed measure second metric called artificial intelligence...
The purpose of this work was to develop metrics assess network architectures that balance neural size and task performance. To end, the concept efficiency is introduced measure layer utilization, a second metric called artificial intelligence quotient (aIQ) created performance efficiency. study aIQ efficiency, two simple networks were trained on MNIST: fully connected (LeNet-300-100) convolutional (LeNet-5). LeNet-5 with highest 2.32% less accurate but contained 30,912 times fewer parameters...