Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with a number of popular R packages for single-cell expression, such as Seurat. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.

Obesity is a risk factor for breast cancer and also predicts poor clinical outcomes regardless of menopausal status. Contributing to the poor clinical outcomes is the suboptimal efficacy of standard therapies due to dose limiting toxicities and obesity related complications, highlighting the need to develop novel therapeutic approaches for treating obese patients. We recently found that obesity leads to an increase in tumor-infiltrating macrophages with activated NLRC4 inflammasome and increased interleukin (IL)-1β production. IL-1β, in turn, leads to increased angiogenesis and cancer progression. Using Next Generation RNA sequencing, we identified an NLRC4/IL-1β-dependent upregulation of angiopoietin-like 4 (ANGPTL4), a known angiogenic factor in cancer, in tumors from obese mice. ANGPTL4-deficiency by genetic knockout or treatment with a neutralizing antibody led to a significant reduction in obesity-induced angiogenesis and tumor growth. At a mechanistic level, ANGPTL4 expression is induced by IL-1β from primary adipocytes in a manner dependent on NF-κB- and MAP kinase-activation, which is further enhanced by hypoxia. This report shows that adipocyte-derived ANGPTL4 drives disease progression under obese conditions and is a potential therapeutic target for treating obese breast cancer patients.

Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with the popular Seurat R package. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.

Background: Delirium is common and dangerous, yet underdetected and undertreated. Current screening questionnaires are subjective and ineffectively implemented in busy hospital workflows. Electroencephalography (EEG) can objectively detect the diffuse slowing characteristic of delirium, but it is not suitable for high-throughput screening due to size, cost, and the expertise required for lead placement and interpretation. This study hypothesized that an efficient and reliable point-of-care EEG device for high-throughput screening could be developed. Methods: This prospective study, which measured bispectral EEG (BSEEG) from elderly inpatients to assess their outcomes, was conducted at the University of Iowa Hospitals and Clinics from January 2016 to October 2017. A BSEEG score was defined based on the distribution of 2,938 EEG recordings from the 428 subjects who were assessed for delirium; primary outcomes measured were hospital length of stay, discharge disposition, and mortality. Results: A total of 274 patients had BSEEG score data available for analysis. Delirium and BSEEG score had a significant association (P < .001). Higher BSEEG scores were significantly correlated with length of stay (P < .001 unadjusted, P = .001 adjusted for age, sex, and Charlson Comorbidity Index [CCI] score) as well as with discharge not to home (P < .01). Hazard ratio for survival controlling for age, sex, CCI score, and delirium status was 1.35 (95% CI,1.04 to 1.76; P = .025). Conclusions: In BSEEG, an efficient and reliable device that provides an objective measurement of delirium status was developed. The BSEEG score is significantly associated with pertinent clinical outcomes of mortality, hospital length of stay, and discharge disposition. The BSEEG score better predicts mortality than does clinical delirium status. This study identified a previously unrecognized subpopulation of patients without clinical features of delirium who are at increased mortality risk.

The AFFIRM Study enrolled 4060 predominantly elderly patients with atrial fibrillation to compare ventricular rate control with rhythm control. The patients in the AFFIRM Study were representative of patients at high risk for complications from atrial fibrillation, which indicates that the results of this large clinical trial will be relevant to patient care.