BACKGROUND: Immune checkpoint inhibitors (ICIs) are standard treatments for advanced non-small cell lung cancer and have expanded use in small cell lung cancer. Although generally better tolerated than traditional chemotherapy, immune-related adverse events, such as immune checkpoint inhibitor-related pneumonitis (ICI-P), remain poorly understood toxicities that limit ICI treatment and can result in considerable morbidity. In this retrospective case-control study, we assessed a lung cancer cohort to identify ICI-P risk factors.RESEARCH QUESTION: What are the risk factors, clinical presentations, radiographic findings, and outcomes for ICI-P in a real-world lung cancer cohort? Do chronic pulmonary diseases confer increased risk for ICI-P? STUDY DESIGN AND METHODS: Medical records from lung cancer patients receiving nivolumab, pembrolizumab, or combination ipilimumab and nivolumab at six centers in North Carolina were reviewed (January 2004-July 2017). Patients with ICI-P and control participants were characterized, and logistic regression was used to assess for ICI-P risk factors. FUNDING/SUPPORT: i2b2 software, Electronic Medical Record Search Engine (EMERSE), and the Carolina Data Warehouse for Health (CDW-H) were used in conducting this study. i2b2 is the flagship tool developed by the i2b2 (Informatics for Integrating Biology and the Bedside) Center, a National Institutes of Health-funded National Center for Biomedical Computing based at Partners HealthCare System. EMERSE allows users to search free-text (unstructured) clinical notes from the electronic health record. The CDW-H is a central data repository containing clinical, research, and administrative data sourced from the University of North Carolina Health system. Both current and legacy hospital systems are represented, with the ability to query most data elements. These research tools at the University of

Human T-lymphotropic Virus-1 (HTLV-1) is a retrovirus that persists lifelong by driving clonal proliferation of infected T-cells. HTLV-1 causes a neuroinflammatory disease and adult T-cell leukemia/lymphoma. Strongyloidiasis, a gastrointestinal infection by the helminth Strongyloides stercoralis, and Infective Dermatitis associated with HTLV-1 (IDH), appear to be risk factors for the development of HTLV-1 related diseases. We used high-throughput sequencing to map and quantify the insertion sites of the provirus in order to monitor the clonality of the HTLV-1-infected T-cell population (i.e. the number of distinct clones and abundance of each clone). A newly developed biodiversity estimator called “DivE” was used to estimate the total number of clones in the blood. We found that the major determinant of proviral load in all subjects without leukemia/lymphoma was the total number of HTLV-1-infected clones. Nevertheless, the significantly higher proviral load in patients with strongyloidiasis or IDH was due to an increase in the mean clone abundance, not to an increase in the number of infected clones. These patients appear to be less capable of restricting clone abundance than those with HTLV-1 alone. In patients co-infected with Strongyloides there was an increased degree of oligoclonal expansion and a higher rate of turnover (i.e. appearance and disappearance) of HTLV-1-infected clones. In Strongyloides co-infected patients and those with IDH, proliferation of the most abundant HTLV-1+ T-cell clones is independent of the genomic environment of the provirus, in sharp contrast to patients with HTLV-1 infection alone. This implies that new selection forces are driving oligoclonal proliferation in Strongyloides co-infection and IDH. We conclude that strongyloidiasis and IDH increase the risk of development of HTLV-1-associated diseases by increasing the rate of infection of new clones and the abundance of existing HTLV-1+ clones.

Electroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.

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