Keenan, J. | Search bioRxiv

bioRxiv2018

A smartphone-based tool for rapid, portable, and automated wide-field retinal imaging

PurposeHigh-quality, wide-field retinal imaging is a valuable method to screen preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging.\n\nMethodsThe system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multi-colored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by non-ophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity.\n\nResultsThe system automatically generated 100-degree retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for DR screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%.\n\nConclusionsAutomation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening.\n\nTranslational RelevanceEnhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.

bioengineering↗

bioRxiv2018

Biophysical Principles of Lineage Factor PU.1 Binding Revealed by NextPBMs

Determining the biophysical principles that shape transcription factor (TF) binding in a cell-specific manner is key to quantitative models of gene expression. High-throughput (HT) in vitro methods measuring protein-DNA binding are invaluable for relating TF binding affinity to genome-wide binding; however, the impact of cell-specific post-translational modifications (PTMs) and cofactors are not routinely assessed. To address these limitations, we describe a new HT approach, called nextPBMs (nuclear extract protein-binding microarrays), to characterize TF binding that accounts for PTMs and endogenous cofactors. We use nextPBMs to examine the DNA binding of the lineage factor PU.1/Spi1 and IRF8 in human monocytes. We identify two binding modes for PU.1 in monocytes - autonomous binding unaffected by PTMs and cooperative binding with IRF8, and identify a single cooperative mode for IRF8. We characterize the DNA binding of PU.1:IRF8 complexes, and show how nextPBMs can be used to discover cell-specific cofactors and characterize TF cooperativity at single-nucleotide resolution. We show that chromatin state and cofactors both influence the affinity requirements for PU.1 binding sites. Furthermore, we find that the influences of cooperative (IRF8) and collaborative (C/EBP) cofactors on PU.1-binding-site affinity are independent and additive.

molecular biology↗