Data-driven simulations for training AI-based segmentation of neutron images.

Neutron interferometry uniquely combines neutron imaging and scattering methods to enable characterization of multiple length scales from 1 nm to 10 µm. However, building, operating, and using such neutron imaging instruments poses constraints on the acquisition time and on the number of measured images per sample. Experiment time-constraints yield small quantities of measured images that are insufficient for automating image analyses using supervised artificial intelligence (AI) models. One approach alleviates this problem by supplementing annotated measured images with synthetic images. To this end, we create a data-driven simulation framework that supplements training data beyond typical data-driven augmentations by leveraging statistical intensity models, such as the Johnson family of probability density functions (PDFs). We follow the simulation framework steps for an image segmentation task including Estimate PDFs → Validate PDFs → Design Image Masks → Generate Intensities → Train AI Model for Segmentation. Our goal is to minimize the manual labor needed to execute the steps and maximize our confidence in simulations and segmentation accuracy. We report results for a set of nine known materials (calibration phantoms) that were imaged using a neutron interferometer acquiring four-dimensional images and segmented by AI models trained with synthetic and measured images and their masks.

Ligand-Based Stability Changes in Duplex DNA Measured with a Microscale Electrochemical Platform.

Development of technologies for rapid screening of DNA secondary structure thermal stability and the effects on stability for binding of small molecule drugs is important to the drug discovery process. In this report, we describe the capabilities of an electrochemical, microdevice-based approach for determining the melting temperatures (Tm) of electrode-bound duplex DNA structures. We also highlight new features of the technology that are compatible with array development and adaptation for high-throughput screening. As a foundational study to exhibit device performance and capabilities, melting-curve analyses were performed on 12-mer DNA duplexes in the presence/absence of two binding ligands: diminazene aceturate (DMZ) and proflavine. By measuring electrochemical current as a function of temperature, our measurement platform has the ability to determine the effect of binding ligands on Tm values with high signal-to-noise ratios and good reproducibility. We also demonstrate that heating our three-electrode cell with either an embedded microheater or a thermoelectric module produces similar results. The ΔTm values we report show the stabilizing ability of DMZ and proflavine when bound to duplex DNA structures. These initial proof-of-concept studies highlight the operating characteristics of the microdevice platform and the potential for future application toward other immobilized samples.