Regulated cell death is a major mechanism to eliminate damaged, infected, or superfluous cells. Previously, apoptosis was thought to be the only regulated cell death mechanism; however, new modalities of caspase-independent regulated cell death have been identified, including necroptosis, pyroptosis, and autophagic cell death. As an understanding of the cellular mechanisms that mediate regulated cell death continues to grow, there is increasing evidence that these pathways are implicated in the pathogenesis of many pulmonary disorders. This review summarizes our understanding of regulated cell death as it pertains to the pathogenesis of chronic obstructive pulmonary disease, asthma, idiopathic pulmonary fibrosis, acute respiratory distress syndrome, and pulmonary arterial hypertension.
Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the percapita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ∼390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotypespecific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0-0.33), as did daily basic reproductive numbers (0.49-4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.disease ecology | emerging infections | arthropod-borne virus T he force of infection (FoI) describes the per-capita rate at which susceptible individuals become infected with a pathogen (1, 2). An accurate estimate of the FoI is essential for parameterizing disease models (3). It can be used to calculate key quantities such as the basic reproductive number (R 0 ) (2, 4) and the critical vaccination coverage threshold (p c ) of a pathogen (5), which are frequently used to guide disease control programs and for determining the control effort required to eliminate a disease (6).Dengue, a mosquito-borne disease whose incidence and geographic range have increased considerably in the past 50 y (7, 8), is caused by any of four related but antigenically distinct virus serotypes (DENV-1, DENV-2, DENV-3, and DENV-4). Previous estimates of the FoI for DENV are few and uncertain owing to limitations inherent to most available DENV datasets, including difficulty in specifying when an individual DENV infection occurred. Given the growing public health need for optimal vector management strategies and the growing potential for deployment of a dengue vaccine in the near future (9), there is a pressing need for accurate, serotype-specific estimates of the FoI and p c for DENV. Here, we use a unique, long-term serologi...
BackgroundDengue virus (DENV) infection can range in severity from mild dengue fever (DF) to severe dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS). Changes in host gene expression, temporally through the progression of DENV infection, especially during the early days, remains poorly characterized. Early diagnostic markers for DHF are also lacking.Methodology/Principal FindingsIn this study, we investigated host gene expression in a cohort of DENV-infected subjects clinically diagnosed as DF (n = 51) and DHF (n = 13) from Maracay, Venezuela. Blood specimens were collected daily from these subjects from enrollment to early defervescence and at one convalescent time-point. Using convalescent expression levels as baseline, two distinct groups of genes were identified: the “early” group, which included genes associated with innate immunity, type I interferon, cytokine-mediated signaling, chemotaxis, and complement activity peaked at day 0–1 and declined on day 3–4; the second “late” group, comprised of genes associated with cell cycle, emerged from day 4 and peaked at day 5–6. The up-regulation of innate immune response genes coincided with the down-regulation of genes associated with viral replication during day 0–3. Furthermore, DHF patients had lower expression of genes associated with antigen processing and presentation, MHC class II receptor, NK and T cell activities, compared to that of DF patients. These results suggested that the innate and adaptive immunity during the early days of the disease are vital in suppressing DENV replication and in affecting outcome of disease severity. Gene signatures of DHF were identified as early as day 1.Conclusions/SignificanceOur study reveals a broad and dynamic picture of host responses in DENV infected subjects. Host response to DENV infection can now be understood as two distinct phases with unique transcriptional markers. The DHF signatures identified during day 1–3 may have applications in developing early molecular diagnostics for DHF.
Objectives: To assess parents' liquid medication administration errors by dosing instrument type and to examine the degree to which parents' health literacy influences dosing accuracy.
Abstract. Dengue virus infections are a major cause of morbidity in tropical countries. Early detection of dengue hemorrhagic fever (DHF) may help identify individuals that would benefit from intensive therapy. Predictive modeling was performed using 11 laboratory values of 51 individuals (38 DF and 13 DHF) obtained on initial presentation using logistic regression. We produced a robust model with an area under the curve of 0.9615 that retained IL-10 levels, platelets, and lymphocytes as the major predictive features. A classification and regression tree was developed on these features that were 86% accurate on cross-validation. The IL-10 levels and platelet counts were also identified as the most informative features associated with DHF using a Random Forest classifier. In the presence of polymerase chain reaction-proven acute dengue infections, we suggest a complete blood count and rapid measurement of IL-10 can assist in the triage of potential DHF cases for close follow-up or clinical intervention improving clinical outcome.
Pulmonary hypertension describes a heterogeneous disease defined by increased pulmonary artery pressures, and progressive increase in pulmonary vascular resistance due to pathologic remodeling of the pulmonary vasculature involving pulmonary endothelial cells, pericytes, and smooth muscle cells. This process occurs under various conditions, and although these populations vary, the clinical manifestations are the same: progressive dyspnea, increases in right ventricular (RV) afterload and dysfunction, RV-pulmonary artery uncoupling, and right-sided heart failure with systemic circulatory collapse. The overall estimated 5-yr survival rate is 72% in highly functioning patients, and as low as 28% for those presenting with advanced symptoms. Metabolic theories have been suggested as underlying the pathogenesis of pulmonary hypertension with growing evidence of the role of mitochondrial dysfunction involving the major proteins of the electron transport chain, redox-related enzymes, regulators of the proton gradient and calcium homeostasis, regulators of apoptosis, and mitophagy. There remain more studies needed to characterize mitochondrial dysfunction leading to impaired vascular relaxation, increase proliferation, and failure of regulatory mechanisms. The effects on endothelial cells and resulting interactions with their microenvironment remain uncharted territory for future discovery. Additionally, on the basis of observations that the "plexigenic lesions" of pulmonary hypertension resemble the unregulated proliferation of tumor cells, similarities between cancer pathobiology and pulmonary hypertension have been drawn, suggesting interactions between mitochondria and angiogenesis. Recently, mitochondria targeting has become feasible, which may yield new therapeutic strategies. We present a state-of-the-art review of the role of mitochondria in both the pathobiology of pulmonary hypertension and potential therapeutic targets in pulmonary vascular processes.
Secondary Dengue viral infection can produce capillary leakage associated with increased mortality known as Dengue Hemorrhagic Fever (DHF). Because the mortality of DHF can be reduced by early detection and intensive support, improved methods for its detection are needed. We applied multidimensional protein profiling to predict outcomes in a prospective Dengue surveillance study in South America. Plasma samples taken from initial clinical presentation of acute Dengue infection were subjected to proteomics analyses using ELISA and a recently developed biofluid analysis platform. Demographics, clinical laboratory measurements, 9 cytokines and 419 plasma proteins collected at the time of initial presentation were compared between the DF and DHF outcomes. Here, the subject’s gender, clinical parameters, 2 cytokines and 42 proteins discriminated between the outcomes. These factors were reduced by multivariate adaptive regression splines (MARS) that a highly accurate classification model based on 8 discriminant features with an AUC of 0.999. Model analysis indicated that the feature-outcome relationship were non-linear. Although this DHF risk model will need validation in a larger cohort, we conclude that approaches to develop predictive biomarker models for disease outcome will need to incorporate nonparametric modeling approaches.
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