3D refraction correction and extraction of clinical parameters from spectral domain optical coherence tomography of the cornea.

Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.

Inter-Species Microbial Sharing in Rural Madagascar: A Study of Environmental Influences on the Skin Microbiome

The skin is home to trillions of microbes, many of which are recently implicated in immune system regulation and various health conditions (33). The skin is continuously exposed to the outside environment, inviting microbial transfer between human skin and the people, animals, and surfaces with which an individual comes into contact. Thus, the aim of this study is to assess how different environmental exposures influence skin microbe communities, as this can strengthen our understanding of how microbial variation relates to health outcomes. This study investigated the skin microbial communities of humans and domesticated cattle living in rural Madagascar. The V3 region of the 16S rRNA gene was sequenced from samples of zebu (the domesticated cattle of Madagascar), zebu owners, and non-zebu owners. Overall, human armpits were the least diverse sample site, while ankles were the most diverse. The diversity of zebu samples was significantly different from armpits, irrespective of zebu ownership (one-way ANOVA and Tukey’s HSD, p<0.05). However, zebu owner samples (from the armpit, ankle forearm, and hand) were more similar to other zebu owner samples than they were to zebu, yet no more similar to other zebu owner samples than they were to non-zebu owner samples (unweighted UniFrac distances, p<0.05). These data suggest a lack of a microbial signature shared by zebu owners and zebu, though further taxonomic analysis is required to explain the role of additional environmental variables in dictating the microbial communities of various samples sites. Understanding the magnitude and directionality of microbial sharing has implications for a breadth of microbe-related health outcomes, with the potential to explain mosquito host preference and mitigate the threats of vector-borne diseases.