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Biology subjects

Webster, D.

Publications and source records attributed to Webster, D..

3 recordsLinked to original sources

Swine reporter model for preclinical evaluation and characterization of gene delivery vectors

Delivery of gene therapy vectors targeted to any somatic cell remains a key barrier for the development of genetic medicines. While rodent models provide insights into vector biodistribution and cellular tropism, their anatomical and physiological differences from humans limit their translational potential and studies in large animal models are often required. In this study, we developed a swine reporter model (SRM-1) to evaluate both viral and nonviral vector delivery in a large animal system. The SRM-1 model harbors a Cre- and CRISPR-activated tdTomato reporter at the Rosa26 locus that allows for tracing of cell-specific delivery and expression of gene therapy vectors in vivo. To evaluate this model, we administered adeno-associated virus serotype 9 (AAV9) and lipid nanoparticles (LNPs) carrying mRNA systemically and found successful in vivo reporter activation across a variety of tissues. Intracerebroventricular (ICV) administration of LNP-Cre mRNA was also performed and demonstrated localized activation in cortical brain cells. In addition to biodistribution studies, this model has utility for testing safety and clinically relevant administration methods, surgical and non-surgical, of delivery vectors. Our findings support the SRM-1 model as a valuable tool for advancing gene therapies from preclinical testing to clinical application.

genetics↗

taxmyPHAGE: Automated taxonomy of dsDNA phage genomes at the genus and species

BackgroundBacteriophages are now classified into genera and species based on genomic similarity. To identify new species and genera requires comparison against all phage genomes currently defined by the International Committee on the Taxonomy of Viruses. With increasing amounts of phage genomic data there is a clear need to fully automate the classification of phages into existing and new genera and species. Materials and MethodsWe created a MASH database for rapid searching of closely related phages, to then be compared with BLASTn to compute intergenomic similarity between bacteriophages (https://github.com/amillard/tax_myPHAGE/tree/main). ResultsTaxmyphage is provided as a conda repository and via a user-friendly website, that allows rapid classification of phages into existing taxa at the genus and species level. ConclusionsTaxmyphage allows the rapid and accurate classification of phage genomes into existing genera and species, at a scale that is compatible with existing sequencing output.

microbiology↗

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↗