Nathan Hotaling

Dataset for the validation and use of DiameterJ an open source nanofiber diameter measurement tool

DiameterJ is an open source image analysis plugin for ImageJ. DiameterJ produces ten files for every image that it analyzes. These files include the images that were analyzed, the data to create histograms of fiber radius, pore size, fiber orientation, and summary statistics, as well as images to check the output of DiameterJ. DiameterJ was validated with 130 in silico-derived, digital, synthetic images and 24 scanning electron microscope (SEM) images of steel wire samples with a known diameter distribution. Once validated, DiameterJ was used to analyze SEM images of electrospun polymeric nanofibers, including a comparison of different segmentation algorithms. In this article, all digital synthetic images, SEM images, and their segmentations are included. Additionally, DiameterJ’s raw output files, and processed data is included for the reader. The data provided herein was used to generate the figures in DiameterJ: A Validated Open Source Nanofiber Diameter Measurement Tool[1], where more discussion can be found.

Rapid fabrication of poly(DL-lactide) nanofiber scaffolds with tunable degradation for tissue engineering applications by air-brushing

Polymer nanofiber based materials have been widely investigated for use as tissue engineering scaffolds. While promising, these materials are typically fabricated through techniques that require significant time or cost. Here we report a rapid and cost effective air-brushing method for fabricating nanofiber scaffolds using a simple handheld apparatus, compressed air, and a polymer solution. Air-brushing also facilities control over the scaffold degradation rate without adversely impacting architecture. This was accomplished through a one step blending process of high (M w  ≈  100 000 g mol(-1)) and low (M w  ≈  25 000 g mol(-1)) molecular weight poly(DL-lactide) (PDLLA) polymers at various ratios (100:0, 70:30 and 50:50). Through this approach, we were able to control fiber scaffold degradation rate while maintaining similar fiber morphology, scaffold porosity, and bulk mechanical properties across all of the tested compositions. The impact of altered degradation rates was biologically evaluated in human bone marrow stromal cell (hBMSC) cultures for up to 16 days and demonstrated degradation rate dependence of both total DNA concentration and gene regulation.

Primary Cilium-Mediated Retinal Pigment Epithelium Maturation Is Disrupted in Ciliopathy Patient Cells

SUMMARY Primary cilia are sensory organelles that protrude from the cell membrane. Defects in the primary cilium cause ciliopathy disorders, with retinal degeneration as a prominent phenotype. Here, we demonstrate that the retinal pigment epithelium (RPE), essential for photoreceptor development and function, requires a functional primary cilium for complete maturation and that RPE maturation defects in ciliopathies precede photoreceptor degeneration. Pharmacologically enhanced ciliogenesis in wild-type induced pluripotent stem cells (iPSC)-RPE leads to fully mature and functional cells. In contrast, ciliopathy patient-derived iPSC-RPE and iPSC-RPE with a knockdown of ciliary-trafficking protein remain immature, with defective apical processes, reduced functionality, and reduced adult-specific gene expression. Proteins of the primary cilium regulate RPE maturation by simultaneously suppressing canonical WNT and activating PKCδ pathways. A similar cilium-dependent maturation pathway exists in lung epithelium. Our results provide insights into ciliopathy-induced retinal degeneration, demonstrate a developmental role for primary cilia in epithelial maturation, and provide a method to mature iPSC epithelial cells for clinical applications.

Modeling, validation and verification of cell-scaffold contact measurements over terabyte-sized 3D image collection

This poster presents the problem of 3D contact measurements from two co-registered volumetric images (z-stacks). The 3D contact measurement consists of (a) segmenting an object of interest in each z-stack, (b) computing the relative spatial positions of the detected objects to detect contacts, (c) validating the accuracy of segmentation, and (d) visually verifying correct contact detection. The 3D measurement has to overcome challenges related to (1) intensity bleed-through across co-registered volumes, (2) insufficient knowledge about statistics and geometry of objects, (3) large RAM requirements (∼3GB just to load the input data) and data volume (>1TB), and (4) complexity of 3D visual inspection.

Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology

An estimated

DiameterJ: A validated open source nanofiber diameter measurement tool

7.1 billion dollars a year is spent due to irreproducibility in pre-clinical data from errors in data analysis and reporting. Therefore, developing tools to improve measurement comparability is paramount. Recently, an open source tool, DiameterJ, has been deployed for the automated analysis of scanning electron micrographs of fibrous scaffolds designed for tissue engineering applications. DiameterJ performs hundreds to thousands of scaffold fiber diameter measurements from a single micrograph within a few seconds, along with a variety of other scaffold morphological features, which enables a more rigorous and thorough assessment of scaffold properties. Herein, an online, publicly available training module is introduced for educating DiameterJ users on how to effectively analyze scanning electron micrographs of fibers and the large volume of data that a DiameterJ analysis yields. The end goal of this training was to improve user data analysis and reporting to enhance reproducibility of analysis of nanofiber scaffolds. User performance was assessed before and after training to evaluate the effectiveness of the training modules. Users were asked to use DiameterJ to analyze reference micrographs of fibers that had known diameters. The results showed that training improved the accuracy and precision of measurements of fiber diameter in scanning electron micrographs. Training also improved the precision of measurements of pore area, porosity, intersection density, and characteristic fiber length between fiber intersections. These results demonstrate that the DiameterJ training module improves precision and accuracy in fiber morphology measurements, which will lead to enhanced data comparability.