Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection.

BACKGROUND: Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. METHODOLOGY/PRINCIPAL FINDINGS: Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to select the final algorithm for each model. After eliminating those with missing data, the SISA dataset had 534 subjects, and the SISAL dataset had 98 subjects. For SISA, the best prediction algorithm was the generalized boosting model, with an AUC of 0.91. For SISAL, the best prediction algorithm was the elastic net with an AUC of 0.94. A sensitivity analysis revealed that SISA and SISAL are not directly comparable to one another. CONCLUSIONS/SIGNIFICANCE: Both SISA and SISAL were able to predict arbovirus hospitalization with a high degree of accuracy in our dataset. These algorithms will need to be tested and validated on new data from future patients. Machine learning is a powerful prediction tool and provides an excellent option for new management tools and clinical assessment of arboviral infection.

Nipah Virus-Like Particle Egress Is Modulated by Cytoskeletal and Vesicular Trafficking Pathways: a Validated Particle Proteomics Analysis.

Classified as a biosafety level 4 (BSL4) select agent, Nipah virus (NiV) is a deadly henipavirus in the Paramyxoviridae family, with a nearly 75% mortality rate in humans, underscoring its global and animal health importance. Elucidating the process of viral particle production in host cells is imperative both for targeted drug design and viral particle-based vaccine development. However, little is understood concerning the functions of cellular machinery in paramyxoviral and henipaviral assembly and budding. Recent studies showed evidence for the involvement of multiple NiV proteins in viral particle formation, in contrast to the mechanisms understood for several paramyxoviruses as being reliant on the matrix (M) protein alone. Further, the levels and purposes of cellular factor incorporation into viral particles are largely unexplored for the paramyxoviruses. To better understand the involvement of cellular machinery and the major structural viral fusion (F), attachment (G), and matrix (M) proteins, we performed proteomics analyses on virus-like particles (VLPs) produced from several combinations of these NiV proteins. Our findings indicate that NiV VLPs incorporate vesicular trafficking and actin cytoskeletal factors. The involvement of these biological processes was validated by experiments indicating that the perturbation of key factors in these cellular processes substantially modulated viral particle formation. These effects were most impacted for NiV-F-modulated viral particle formation either autonomously or in combination with other NiV proteins, indicating that NiV-F budding relies heavily on these cellular processes. These findings indicate a significant involvement of the NiV fusion protein, vesicular trafficking, and actin cytoskeletal processes in efficient viral particle formation.IMPORTANCE Nipah virus is a zoonotic biosafety level 4 agent with high mortality rates in humans. The genus to which Nipah virus belongs, Henipavirus, includes five officially recognized pathogens; however, over 20 species have been identified in multiple continents within the last several years. As there are still no vaccines or treatments for NiV infection, elucidating its process of viral particle production is imperative both for targeted drug design as well as for particle-based vaccine development. Developments in high-throughput technologies make proteomic analysis of isolated viral particles a highly insightful approach to understanding the life cycle of pathogens such as Nipah virus.

Association of BCG Vaccination in Childhood With Subsequent Cancer Diagnoses: A 60-Year Follow-up of a Clinical Trial.

Importance: The BCG vaccine is currently the only approved tuberculosis vaccine and is widely administered worldwide, usually during infancy. Previous studies found increased rates of lymphoma and leukemia in BCG-vaccinated populations. Objective: To determine whether BCG vaccination was associated with cancer rates in a secondary analysis of a BCG vaccine trial. Design, Setting, and Participants: Retrospective review (60-year follow-up) of a clinical trial in which participants were assigned to the vaccine group by systematic stratification by school district, age, and sex, then randomized by alternation. The original study was conducted at 9 sites in 5 US states between December 1935 and December 1998. Participants were 2963 American Indian and Alaska Native schoolchildren younger than 20 years with no evidence of previous tuberculosis infection. Statistical analysis was conducted between August 2018 and July 2019. Interventions: Single intradermal injection of either BCG vaccine or saline placebo. Main Outcomes and Measures: The primary outcome was diagnosis of cancer after BCG vaccination. Data on participant interval health and risk factors, including smoking, tuberculosis infection, isoniazid use, and other basic demographic information, were also collected. Results: A total of 2963 participants, including 1540 in the BCG vaccine group and 1423 in the placebo group, remained after exclusions. Vaccination occurred at a median (interquartile range) age of 8 (5-11) years; 805 participants (52%) in the BCG group and 710 (50%) in the placebo group were female. At the time of follow-up, 97 participants (7%) in the placebo group and 106 participants (7%) in the BCG vaccine group could not be located; total mortality was 633 participants (44%) in the placebo group and 632 participants (41%) in the BCG group. The overall rate of cancer diagnosis was not significantly different in BCG vaccine vs placebo recipients (hazard ratio, 0.82; 95% CI, 0.66-1.02), including for lymphoma and leukemia. The rate of lung cancer was significantly lower in BCG vs placebo recipients (18.2 vs 45.4 cases per 100 000 person-years; hazard ratio, 0.38; 95% CI, 0.20-0.74; P = .005), controlling for sex, region, alcohol overuse, smoking, and tuberculosis. Conclusions and Relevance: Childhood BCG vaccination was associated with a lower risk of lung cancer development in American Indian and Alaska Native populations. This finding has potentially important health implications given the high mortality rate associated with lung cancer and the availability of low-cost BCG vaccines.

S1P-dependent interorgan trafficking of group 2 innate lymphoid cells supports host defense.

Innate lymphoid cells (ILCs) are innate counterparts of adaptive T lymphocytes, contributing to host defense, tissue repair, metabolic homeostasis, and inflammatory diseases. ILCs have been considered to be tissue-resident cells, but whether ILCs move between tissue sites during infection has been unclear. We show here that interleukin-25- or helminth-induced inflammatory ILC2s are circulating cells that arise from resting ILC2s residing in intestinal lamina propria. They migrate to diverse tissues based on sphingosine 1-phosphate (S1P)-mediated chemotaxis that promotes lymphatic entry, blood circulation, and accumulation in peripheral sites, including the lung, where they contribute to anti-helminth defense and tissue repair. This ILC2 expansion and migration is a behavioral parallel to the antigen-driven proliferation and migration of adaptive lymphocytes to effector sites and indicates that ILCs complement adaptive immunity by providing both local and distant tissue protection during infection.