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Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Multi-drug resistance is increasing at alarming rates. The efficacy of phage therapy, treating bacterial infections with bacteriophages alone or in combination with traditional antibiotics, has been demonstrated in emergency cases in the United States and in other countries, however remains to be approved for wide-spread use in the US. One limiting factor is a lack of guidelines for assessing the genomic safety of phage candidates. We present the phage characterization workflow used by our team to generate data for submitting phages to the Federal Drug Administration (FDA) for authorized use. Essential analysis checkpoints and warnings are detailed for obtaining high-quality genomes, excluding undesirable candidates, rigorously assessing a phage genome for safety and evaluating sequencing contamination. This workflow has been developed in accordance with community standards for high-throughput sequencing of viral genomes as well as principles for ideal phages used for therapy. The feasibility and utility of the pipeline is demonstrated on two new phage genomes that meet all safety criteria. We propose these guidelines as a minimum standard for phages being submitted to the FDA for review as investigational new drug candidates. [ABSTRACT FROM AUTHOR]

Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Andrew P. Rothstein, Casandra W. Philipson, Birgitte B. Simen, and Robert C. Morfino own Ginkgo Bioworks employee stocks or restricted stock unit grants. Ezra T. Ernst owns XWELL employee stocks or restricted stock unit grants. No other potential conflicts of interest were disclosed.

Histiocytic sarcoma is an uncommon malignancy in both humans and veterinary species. Research exploring the pathogenesis of this disease is scarce; thus, diagnostic and therapeutic options for patients are limited. Recent publications have suggested a role for the NLR, NLRX1, in acting as a tumor suppressor. Based on these prior findings, we hypothesized that NLRX1 would function to inhibit tumorigenesis and thus the development of histiocytic sarcoma. To test this, we utilized Nlrx1-/- mice and a model of urethane-induced tumorigenesis. Nlrx1-/- mice exposed to urethane developed splenic histiocytic sarcoma that was associated with significant up-regulation of the NF-κB signaling pathway. Additionally, development of these tumors was also significantly associated with the increased regulation of genes associated with AKT signaling, cell death and autophagy. Together, these data show that NLRX1 suppresses tumorigenesis and reveals new genetic pathways involved in the pathobiology of histiocytic sarcoma., Competing Interests: The authors have no conflicts of interest to disclose.