IgE binding to linear epitopes of Ara h 2 in peanut allergic preschool children undergoing oral Immunotherapy.

BACKGROUND: For patients with peanut allergy, there are currently no methods to predict who will develop sustained unresponsiveness (SU) after oral immunotherapy (OIT). OBJECTIVE: Assess IgE binding to peanut (PN), Ara h 2, and specific linear epitopes of Ara h 2 as predictors of the important clinical parameters: eliciting dose threshold and attainment of SU following OIT. METHODS: Samples and clinical data were collected from children undergoing OIT. PN- and Ara h 2-sIgE were quantified by ImmunoCAP® . IgE binding to linear peptides of Ara h 2 and Ara h 6 was measured with peptide microarrays. RESULTS: Values of PN-sIgE correlated with eliciting dose (P = .001) and with a higher likelihood of achieving SU (P < .0001), but these relationships were lost at higher values for PN-sIgE (≥14 kIU for eliciting dose and ≥35 kIU/L for SU). In subjects with PN-sIgE ≥ 14 kIU/L, binding of IgE to epitopes 5 and 6 of Ara h 2 was associated with a lower eliciting dose at baseline challenge (P < .001; Pc  < .02). In subjects with PN-sIgE ≥ 35 kIU/L, a combined model of IgE binding to epitopes 1, 5 and 6 with PN-sIgE was highly predictive of attainment of SU (AUC of 0.86; P = .0067). CONCLUSION: In young patients with peanut allergy, measurement of PN-sIgE and IgE binding to specific linear epitopes of Ara h 2 in baseline samples may allow stratification of patients regarding sensitivity to challenge and outcome of OIT.

Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data.

Metabolomics is the science of characterizing and quantifying small molecule metabolites in biological systems. These metabolites give organisms their biochemical characteristics, providing a link between genotype, environment, and phenotype. With these opportunities also come data challenges, such as compound annotation, missing values, and batch effects. We present the steps of a general pipeline to process untargeted mass spectrometry data to alleviate the latter two challenges. We assume to have a matrix with metabolite abundances, with metabolites in rows and samples in columns. The steps in the pipeline include summarizing technical replicates (if available), filtering, imputing, transforming, and normalizing the data. In each of these steps, a method and parameters should be chosen based on assumptions one is willing to make, the question of interest, and diagnostic tools. Besides giving a general pipeline that can be adapted by the reader, our goal is to review diagnostic tools and criteria that are helpful when making decisions in each step of the pipeline and assessing the effectiveness of normalization and batch correction. We conclude by giving a list of useful packages and discuss some alternative approaches that might be more appropriate for the reader's data.

Early Mechanistic Events Induced by Low Molecular Weight Polycyclic Aromatic Hydrocarbons in Mouse Lung Epithelial Cells: A Role for Eicosanoid Signaling.

Low molecular weight polycyclic aromatic hydrocarbons (LMW PAHs; < 206.3 g/mol) are under regulated environmental contaminants (eg, secondhand smoke) that lead to gap junction dysregulation, p38 MAPK activation, and increased mRNA production of inflammatory mediators, such as cytokines and cyclooxygenase (COX2), in lung epithelial cells. However, the early mechanisms involving lipid signaling through the arachidonic acid pathway and subsequent eicosanoid production leading to these downstream events are not known. Common human exposures are to mixtures of LMW PAHs, thus C10 cells (a mouse lung epithelial cell line) were exposed to a representative binary PAH mixture, 1-methylanthracene (1-MeA) and fluoranthene (Flthn), for 30 min-24 h with and without p38 and cytosolic phospholipase A2 (cPLA2) inhibitors. Cytosolic phospholipase A2 inhibition reversed PAH-induced phospho-p38 MAPK activation and gap junction dysregulation at 30 min. A significant biphasic increase in cPLA2 protein was observed at 30 min, 2, and 4 h, as well as COX2 protein at 2 and 8 h. Untargeted metabolomics demonstrated a similar trend with significantly changing metabolites at 30 min and 4 h of exposure relative to 1 h; a "cPLA2-like" subset of metabolites within the biphasic response were predominately phospholipids. Targeted metabolomics showed several eicosanoids (eg, prostaglandin D2 (PGD2), PGE2α) were significantly increased at 4, 8, and 12 h following exposure to the binary PAH mixture and this effect was p38-dependent. Finally, PAH metabolism was not observed until after 8 h. These results indicate an early lipid signaling mechanism of LMW PAH toxicity in lung epithelial cells due to parent PAH compounds.

Approximation methods for analyzing multiscale stochastic vector-borne epidemic models.

Stochastic epidemic models, generally more realistic than deterministic counterparts, have often been seen too complex for rigorous mathematical analysis because of level of details it requires to comprehensively capture the dynamics of diseases. This problem further becomes intense when complexity of diseases increases as in the case of vector-borne diseases (VBD). The VBDs are human illnesses caused by pathogens transmitted among humans by intermediate species, which are primarily arthropods. In this study, a stochastic VBD model is developed and novel mathematical methods are described and evaluated to systematically analyze the model and understand its complex dynamics. The VBD model incorporates some relevant features of the VBD transmission process including demographical, ecological and social mechanisms, and different host and vector dynamic scales. The analysis is based on dimensional reductions and model simplifications via scaling limit theorems. The results suggest that the dynamics of the stochastic VBD depends on a threshold quantity R0, the initial size of infectives, and the type of scaling in terms of host population size. The quantity R0 for deterministic counterpart of the model is interpreted as a threshold condition for infection persistence as is mentioned in the literature for many infectious disease models. Different scalings yield different approximations of the model, and in particular, if vectors have much faster dynamics, the effect of the vector dynamics on the host population averages out, which largely reduces the dimension of the model. Specific scenarios are also studied using simulations for some fixed sets of parameters to draw conclusions on dynamics.

The human placental proteome secreted into the maternal and fetal circulations in normal pregnancy based on 4-vessel sampling.

We sought to identify proteins secreted by the human placenta into the maternal and fetal circulations. Blood samples from the maternal radial artery and uterine vein and umbilical artery and vein were obtained during cesarean section in 35 healthy women with term pregnancy. Slow off-rate modified aptamer (SOMA) protein-binding technology was used to quantify 1310 known proteins. The uteroplacental and umbilical venoarterial concentration differences were calculated. Thirty-four proteins were significantly secreted by the placenta into the maternal circulation, including placental growth factor, growth/differentiation factor 15, and matrix metalloproteinase 12. There were 341 proteins significantly secreted by the placenta into the fetal circulation. Only 7 proteins were secreted into both the fetal and maternal circulations, suggesting a distinct directionality in placental protein release. We examined changes across gestation in the proteins found to be significantly secreted by the placenta into the maternal circulation using serial blood samples from healthy women. Among the 34 proteins secreted into the maternal circulation, 8 changed significantly across gestation. The identified profiles of secreted placental proteins will allow us to identify novel minimally invasive biomarkers for human placental function across gestation and discover previously unknown proteins secreted by the human placenta that regulate maternal physiology and fetal development.-Michelsen, T. M., Henriksen, T., Reinhold, D., Powell, T. L., Jansson, T. The human placental proteome secreted into the maternal and fetal circulations in normal pregnancy based on 4-vessel sampling.

Inhibition of Amino Acid Metabolism Selectively Targets Human Leukemia Stem Cells.

In this study we interrogated the metabolome of human acute myeloid leukemia (AML) stem cells to elucidate properties relevant to therapeutic intervention. We demonstrate that amino acid uptake, steady-state levels, and catabolism are all elevated in the leukemia stem cell (LSC) population. Furthermore, LSCs isolated from de novo AML patients are uniquely reliant on amino acid metabolism for oxidative phosphorylation and survival. Pharmacological inhibition of amino acid metabolism reduces oxidative phosphorylation and induces cell death. In contrast, LSCs obtained from relapsed AML patients are not reliant on amino acid metabolism due to their ability to compensate through increased fatty acid metabolism. These findings indicate that clinically relevant eradication of LSCs can be achieved with drugs that target LSC metabolic vulnerabilities.

Comparative Immune Responses to Licensed Herpes Zoster Vaccines.

Background: Live attenuated (ZV) and recombinant adjuvanted (HZ/su) zoster vaccines differ with respect to efficacy, effect of age, and persistence of protection. We compared cell-mediated immunity (CMI responses to ZV and HZ/su. Methods: This was a randomized, double-blind, placebo-controlled trial stratified by age (50-59 and 70-85 years) and by HZ vaccination status (received ZV ≥5 years before entry or not). Varicella zoster virus (VZV)- and glycoprotein E (gE)-specific CMI were analyzed by interleukin 2 (IL-2) and interferon gamma (IFN-γ) FluoroSpot and flow cytometry at study days 0, 30, 90, and 365. Results: Responses to ZV peaked on day 30 and to HZ/su (administered in 2 doses separated by 60 days) peaked on day 90. Age and vaccination status did not affect peak responses, but higher baseline CMI correlated with higher peak responses. HZ/su generated significantly higher VZV-specific IL-2+ and gE-specific IL-2+, IFN-γ+, and IL-2+/IFN-γ+ peak and 1-year baseline-adjusted responses compared with ZV. VZV-specific IFN-γ+ and IL-2+/IFN-γ+ did not differ between vaccines. HZ/su generated higher memory and effector-memory CD4+ peak responses and ZV generated higher effector CD4+ responses . Conclusions: The higher IL-2 and other memory responses generated by HZ/su compared with ZV may contribute to its superior efficacy. Clinical Trials Registration: NCT02114333.

Th1 memory differentiates recombinant from live herpes zoster vaccines.

The adjuvanted varicella-zoster virus (VZV) glycoprotein E (gE) subunit herpes zoster vaccine (HZ/su) confers higher protection against HZ than the live attenuated zoster vaccine (ZV). To understand the immunologic basis for the different efficacies of the vaccines, we compared immune responses to the vaccines in adults 50 to 85 years old. gE-specific T cells were very low/undetectable before vaccination when analyzed by FluoroSpot and flow cytometry. Both ZV and HZ/su increased gE-specific responses, but at peak memory response (PMR) after vaccination (30 days after ZV or after the second dose of HZ/su), gE-specific CD4+ and CD8+ T cell responses were 10-fold or more higher in HZ/su compared with ZV recipients. Comparing the vaccines, T cell memory responses, including gE-IL-2+ and VZV-IL-2+ spot-forming cells (SFCs), were higher in HZ/su recipients and cytotoxic and effector responses were lower. At 1 year after vaccination, all gE-Th1 and VZV-IL-2+ SFCs remained higher in HZ/su compared with ZV recipients. Mediation analyses showed that IL-2+ PMR were necessary for the persistence of Th1 responses to either vaccine and VZV-IL-2+ PMR explained 73% of the total effect of HZ/su on persistence. This emphasizes the biological importance of the memory responses, which were clearly superior in HZ/su compared with ZV participants.

Meta-analysis of peripheral blood gene expression modules for COPD phenotypes.

Chronic obstructive pulmonary disease (COPD) occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules) that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA) and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002), and two had some association with emphysema (meta p ≤ 0.06); some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included "immune response" and "defense response." The cell types whose type-specific genes were overrepresented in modules (p < 0.05) included natural killer cells, dendritic cells, and neutrophils. Together, this is the largest investigation of gene blood expression in COPD with 469 cases in COPDGene, ECLIPSE and TESRA combined, with 6267 genes common to all data sets. Additional, we have 42 and 83 controls in COPDGene and ECLIPSE, respectively.

A Functionally Conserved Gene Regulatory Network Module Governing Olfactory Neuron Diversity.

Sensory neuron diversity is required for organisms to decipher complex environmental cues. In Drosophila, the olfactory environment is detected by 50 different olfactory receptor neuron (ORN) classes that are clustered in combinations within distinct sensilla subtypes. Each sensilla subtype houses stereotypically clustered 1-4 ORN identities that arise through asymmetric divisions from a single multipotent sensory organ precursor (SOP). How each class of SOPs acquires a unique differentiation potential that accounts for ORN diversity is unknown. Previously, we reported a critical component of SOP diversification program, Rotund (Rn), increases ORN diversity by generating novel developmental trajectories from existing precursors within each independent sensilla type lineages. Here, we show that Rn, along with BarH1/H2 (Bar), Bric-à-brac (Bab), Apterous (Ap) and Dachshund (Dac), constitutes a transcription factor (TF) network that patterns the developing olfactory tissue. This network was previously shown to pattern the segmentation of the leg, which suggests that this network is functionally conserved. In antennal imaginal discs, precursors with diverse ORN differentiation potentials are selected from concentric rings defined by unique combinations of these TFs along the proximodistal axis of the developing antennal disc. The combinatorial code that demarcates each precursor field is set up by cross-regulatory interactions among different factors within the network. Modifications of this network lead to predictable changes in the diversity of sensilla subtypes and ORN pools. In light of our data, we propose a molecular map that defines each unique SOP fate. Our results highlight the importance of the early prepatterning gene regulatory network as a modulator of SOP and terminally differentiated ORN diversity. Finally, our model illustrates how conserved developmental strategies are used to generate neuronal diversity.

CIB1 depletion impairs cell survival and tumor growth in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with generally poor prognosis and no available targeted therapies, highlighting a critical unmet need to identify and characterize novel therapeutic targets. We previously demonstrated that CIB1 is necessary for cancer cell survival and proliferation via regulation of two oncogenic signaling pathways, RAF-MEK-ERK and PI3K-AKT. Because these pathways are often upregulated in TNBC, we hypothesized that CIB1 may play a broader role in TNBC cell survival and tumor growth. Methods utilized include inducible RNAi depletion of CIB1 in vitro and in vivo, immunoblotting, clonogenic assay, flow cytometry, RNA-sequencing, bioinformatics analysis, and Kaplan-Meier survival analysis. CIB1 depletion resulted in significant cell death in 8 of 11 TNBC cell lines tested. Analysis of components related to PI3K-AKT and RAF-MEK-ERK signaling revealed that elevated AKT activation status and low PTEN expression were key predictors of sensitivity to CIB1 depletion. Furthermore, CIB1 knockdown caused dramatic shrinkage of MDA-MB-468 xenograft tumors in vivo. RNA sequence analysis also showed that CIB1 depletion in TNBC cells activates gene programs associated with decreased proliferation and increased cell death. CIB1 expression levels per se did not predict TNBC susceptibility to CIB1 depletion, and CIB1 mRNA expression levels did not associate with TNBC patient survival. Our data are consistent with the emerging concept of non-oncogene addiction, where a large subset of TNBCs depend on CIB1 for cell survival and tumor growth, independent of CIB1 expression levels. Our data establish CIB1 as a novel therapeutic target for TNBC.

Evaluation of buccal alveolar bone dimension of maxillary anterior and premolar teeth: a cone beam computed tomography investigation.

PURPOSE: Clinical guidelines suggest that a minimal buccal alveolar bone thickness of 1 to 2 mm is required to maintain the tissue architecture following tooth extraction and implant placement. The aim of this study was to evaluate the thickness of buccal alveolar bone at the maxillary first premolars and anterior teeth using cone beam computed tomography (CBCT). MATERIALS AND METHODS: CBCT images of the maxillae of 43 implant patients were obtained. Two examiners manually measured the distance from the cementoenamel junction (CEJ) to the buccal alveolar bone crest and the thickness of the buccal alveolar bone at the crest, midroot, and apex of the maxillary first premolars and anterior teeth. The absence of bone and presence of radiographic artifacts were recorded. Average bone thicknesses were calculated and compared. Both parametric and nonparametric statistics were used to analyze the findings. RESULTS: The median distance from the CEJ to the buccal alveolar bone crest was 2.79 mm, and measurements were similar among tooth positions. The median buccal alveolar bone thickness 1 mm apical to the alveolar bone was 1.13 mm in the premolar area and 0.83 mm for the anterior maxillary teeth. The median buccal alveolar bone thickness at the midroot was 1.03 mm in the premolar area and 0.70 mm for the other anterior maxillary teeth. Measurements of the buccal plate at 1 mm from the tooth apex were similar in all teeth positions, with a median thickness of 0.88 mm. CONCLUSIONS: The presence or absence of buccal alveolar bone can be discerned by CBCT evaluation. Few maxillary anterior teeth displayed buccal alveolar bone thickness greater than 1 mm. The implications for implant therapy must be fully discerned regarding tissue biotypes and dental implant outcomes.