Presence of Acanthamoeba and diversified bacterial flora in poorly maintained contact lens cases

Isolation, characterization, and pathogenicity assay of Acanthamoeba and its endosymbionts in respiratory disorders and COVID-19 hospitalized patients, northern Iran

Acanthamoeba spp., are common free-living amoebae found in nature that can serve as reservoirs for certain microorganisms. The SARS-CoV-2 virus is a newly emerged respiratory infection, and the investigation of parasitic infections remains an area of limited research. Given that Acanthamoeba can act as a host for various endosymbiotic microbial pathogens and its pathogenicity assay is not fully understood, this study aimed to identify Acanthamoeba and its bacterial and fungal endosymbionts in patients with chronic respiratory disorders and hospitalized COVID-19 patients in northern Iran. Additionally, a pathogenicity assay was conducted on Acanthamoeba isolates. Urine, nasopharyngeal swab, and respiratory specimens were collected from two groups, and each sample was cultured on 1.5% non-nutrient agar medium. The cultures were then incubated at room temperature and monitored daily for a period of two weeks. Eight Acanthamoeba isolates were identified, and PCR was performed to confirm the presence of amoebae and identify their endosymbionts. Four isolates were found to have bacterial endosymbionts, including Stenotrophomonas maltophilia and Achromobacter sp., while two isolates harbored fungal endosymbionts, including an uncultured fungus and Gloeotinia sp. In the pathogenicity assay, five isolates exhibited a higher degree of pathogenicity compared to the other three. This study provides significant insights into the comorbidity of acanthamoebiasis and COVID-19 on a global scale, and presents the first evidence of Gloeotinia sp. as a fungal endosymbiont. Nevertheless, further research is required to fully comprehend the symbiotic patterns and establish effective treatment protocols.

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images

Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophthalmologists. To characterize the “face” of an infected cornea, we have adapted a deep learning architecture used for facial recognition and applied it to determine a probability score for a specific pathogen causing keratitis. To record the diverse features and mitigate the uncertainty, batches of probability scores of 4 serial images taken from many angles or fluorescence staining were learned for score and decision level fusion using a gradient boosting decision tree. A total of 4306 slit-lamp images including 312 images obtained by internet publications on keratitis by bacteria, fungi, acanthamoeba, and herpes simplex virus (HSV) were studied. The created algorithm had a high overall accuracy of diagnosis, e.g., the accuracy/area under the curve for acanthamoeba was 97.9%/0.995, bacteria was 90.7%/0.963, fungi was 95.0%/0.975, and HSV was 92.3%/0.946, by group K-fold validation, and it was robust to even the low resolution web images. We suggest that our hybrid deep learning-based algorithm be used as a simple and accurate method for computer-assisted diagnosis of infectious keratitis.

Microbiota and Ocular Diseases

Recent advances have identified significant associations between the composition and function of the gut microbiota and various disorders in organ systems other than the digestive tract. Utilizing next-generation sequencing and multiomics approaches, the microbial community that possibly impacts ocular disease has been identified. This review provides an overview of the literature on approaches to microbiota analysis and the roles of commensal microbes in ophthalmic diseases, including autoimmune uveitis, age-related macular degeneration, glaucoma, and other ocular disorders. In addition, this review discusses the hypothesis of the "gut-eye axis" and evaluates the therapeutic potential of targeting commensal microbiota to alleviate ocular inflammation.