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BackgroundCOVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. ObjectiveThe aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. MethodsWe used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19–positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. ResultsUpon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. ConclusionsWe externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Topics of diversity, equity, and inclusion (DEI) are an integral component of post-graduate medical education. However, it is currently unclear the extent to which physical medicine and rehabilitation residency programs have incorporated a DEI curriculum into their training programs. Here, a novel, multi-institutional DEI journal club is described. This journal club format can be an important component of the DEI curriculum as it provides non-local perspectives and insights into specific issues and allows for a simple way to introduce DEI training in programs currently without such training. The virtual format also provides further opportunities for discussion and networking. [ABSTRACT FROM AUTHOR]

Many arboviral proteins are phosphorylated in infected mammalian cells, but it is unknown if the same phosphorylation events occur when insects are similarly infected. One of the mammalian kinases responsible for phosphorylation, protein kinase G (PKG), has been implicated in the behavior of multiple nonvector insects, but is unstudied in mosquitoes. PKG from Aedes aegypti was cloned, and phosphorylation of specific viral sites was monitored by mass spectrometry from biochemical and cell culture experiments. PKG from Aedes mosquitoes is able to phosphorylate dengue nonstructural protein 5 (NS5) at specific sites in cell culture and cell-free systems and autophosphorylates its own regulatory domain in a cell-free system. Injecting Aedes aegypti and Anopheles gambiae mosquitoes with a pharmacological PKG activator resulted in increased Aedes wing activity during periods of their natural diurnal/crepuscular activity and increased Anopheles nocturnal locomotor/flight activity. Thus, perturbation of the PKG signaling pathway in mosquitoes alters flight behavior. The demonstrated effect of PKG alterations is consistent with a viral PKG substrate triggering increased PKG activity. This increased PKG activity could be the mechanism by which dengue virus increases flight behavior and possibly facilitates transmission. Whether or not PKG is part of the mechanism by which dengue increases flight behavior, this report is the first to show PKG can modulate behavior in hematophagous disease vectors. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDA) is an aggressive malignancy characterized by a paucity of tumor-proximal CD8 + T cells and resistance to immunotherapeutic interventions. Cancer-associated mechanisms that elicit CD8 + T-cell exclusion and resistance to immunotherapy are not well-known. Here, using a Kras- and p53-driven model of PDA, we describe a mechanism of action for the protumorigenic cytokine IL35 through STAT3 activation in CD8 + T cells. Distinct from its action on CD4 + T cells, IL35 signaling in gp130 + CD8 + T cells activated the transcription factor STAT3, which antagonized intratumoral infiltration and effector function of CD8 + T cells via suppression of CXCR3, CCR5, and IFNγ expression. Inhibition of STAT3 signaling in tumor-educated CD8 + T cells improved PDA growth control upon adoptive transfer to tumor-bearing mice. We showed that activation of STAT3 in CD8 + T cells was driven by B cell- but not regulatory T cell-specific production of IL35. We also demonstrated that B cell-specific deletion of IL35 facilitated CD8 + T-cell activation independently of effector or regulatory CD4 + T cells and was sufficient to phenocopy therapeutic anti-IL35 blockade in overcoming resistance to anti-PD-1 immunotherapy. Finally, we identified a circulating IL35 + B-cell subset in patients with PDA and demonstrated that the presence of IL35 + cells predicted increased occurrence of phosphorylated (p)Stat3 + CXCR3 - CD8 + T cells in tumors and inversely correlated with a cytotoxic T-cell signature in patients. Together, these data identified B cell-mediated IL35/gp130/STAT3 signaling as an important direct link to CD8 + T-cell exclusion and immunotherapy resistance in PDA., (©2020 American Association for Cancer Research.)

Many arboviral proteins are phosphorylated in infected mammalian cells, but it is unknown if the same phosphorylation events occur when insects are similarly infected. One of the mammalian kinases responsible for phosphorylation, protein kinase G (PKG), has been implicated in the behavior of multiple nonvector insects, but is unstudied in mosquitoes. PKG from Aedes aegypti was cloned, and phosphorylation of specific viral sites was monitored by mass spectrometry from biochemical and cell culture experiments. PKG from Aedes mosquitoes is able to phosphorylate dengue nonstructural protein 5 (NS5) at specific sites in cell culture and cell-free systems and autophosphorylates its own regulatory domain in a cell-free system. Injecting Aedes aegypti and Anopheles gambiae mosquitoes with a pharmacological PKG activator resulted in increased Aedes wing activity during periods of their natural diurnal/crepuscular activity and increased Anopheles nocturnal locomotor/flight activity. Thus, perturbation of the PKG signaling pathway in mosquitoes alters flight behavior. The demonstrated effect of PKG alterations is consistent with a viral PKG substrate triggering increased PKG activity. This increased PKG activity could be the mechanism by which dengue virus increases flight behavior and possibly facilitates transmission. Whether or not PKG is part of the mechanism by which dengue increases flight behavior, this report is the first to show PKG can modulate behavior in hematophagous disease vectors.