Randomized crossover comparison of proportional assist ventilation and patient-triggered ventilation in extremely low birth weight infants with evolving chronic lung disease

Background: Refinement of ventilatory techniques remains a challenge given the persistence of chronic lung disease of preterm infants. Objective: To test the hypothesis that proportional assist ventilation ( PAV) will allow to lower the ventilator pressure at equivalent fractions of inspiratory oxygen (FiO(2)) and arterial hemoglobin oxygen saturation in ventilator-dependent extremely low birth weight infants in comparison with standard patient-triggered ventilation ( PTV). Methods: Design: Randomized crossover design. Setting: Two level-3 university perinatal centers. Patients: 22 infants ( mean (SD): birth weight, 705 g ( 215); gestational age, 25.6 weeks ( 2.0); age at study, 22.9 days ( 15.6)). Interventions: One 4- hour period of PAV was applied on each of 2 consecutive days and compared with epochs of standard PTV. Results: Mean airway pressure was 5.64 ( SD, 0.81) cm H2O during PAV and 6.59 ( SD, 1.26) cm H2O during PTV ( p < 0.0001), the mean peak inspiratory pressure was 10.3 ( SD, 2.48) cm H2O and 15.1 ( SD, 3.64) cm H2O ( p < 0.001), respectively. The FiO(2) ( 0.34 (0.13) vs. 0.34 ( 0.14)) and pulse oximetry readings were not significantly different. The incidence of arterial oxygen desaturations was not different ( 3.48 ( 3.2) vs. 3.34 ( 3.0) episodes/ h) but desaturations lasted longer during PAV ( 2.60 ( 2.8) vs. 1.85 ( 2.2) min of desaturation/ h, p = 0.049). PaCO2 measured transcutaneously in a subgroup of 12 infants was similar. One infant met prespecified PAV failure criteria. No adverse events occurred during the 164 cumulative hours of PAV application. Conclusions: PAV safely maintains gas exchange at lower mean airway pressures compared with PTV without adverse effects in this population. Backup conventional ventilation breaths must be provided to prevent apnea-related desaturations. Copyright (c) 2007 S. Karger AG, Base

Oligomeric Structure of the MALT1 Tandem Ig-Like Domains

Mucosa-associated lymphoid tissue 1 (MALT1) plays an important role in the adaptive immune program. During TCR- or BCR-induced NF-κB activation, MALT1 serves to mediate the activation of the IKK (IκB kinase) complex, which subsequently regulates the activation of NF-κB. Aggregation of MALT1 is important for E3 ligase activation and NF-κB signaling.Unlike the isolated CARD or paracaspase domains, which behave as monomers, the tandem Ig-like domains of MALT1 exists as a mixture of dimer and tetramer in solution. High-resolution structures reveals a protein-protein interface that is stabilized by a buried surface area of 1256 Å(2) and contains numerous hydrogen and salt bonds. In conjunction with a second interface, these interactions may represent the basis of MALT1 oligomerization.The crystal structure of the tandem Ig-like domains reveals the oligomerization potential of MALT1 and a potential intermediate in the activation of the adaptive inflammatory pathway.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1

Development of Mouse Hepatocyte Lines Permissive for Hepatitis C Virus (HCV)

The lack of a suitable small animal model for the analysis of hepatitis C virus (HCV) infection has hampered elucidation of the HCV life cycle and the development of both protective and therapeutic strategies against HCV infection. Human and mouse harbor a comparable system for antiviral type I interferon (IFN) induction and amplification, which regulates viral infection and replication. Using hepatocytes from knockout (ko) mice, we determined the critical step of the IFN-inducing/amplification pathways regulating HCV replication in mouse. The results infer that interferon-beta promoter stimulator (IPS-1) or interferon A receptor (IFNAR) were a crucial barrier to HCV replication in mouse hepatocytes. Although both IFNARko and IPS-1ko hepatocytes showed a reduced induction of type I interferons in response to viral infection, only IPS-1-/- cells circumvented cell death from HCV cytopathic effect and significantly improved J6JFH1 replication, suggesting IPS-1 to be a key player regulating HCV replication in mouse hepatocytes. We then established mouse hepatocyte lines lacking IPS-1 or IFNAR through immortalization with SV40T antigen. Expression of human (h)CD81 on these hepatocyte lines rendered both lines HCVcc-permissive. We also found that the chimeric J6JFH1 construct, having the structure region from J6 isolate enhanced HCV replication in mouse hepatocytes rather than the full length original JFH1 construct, a new finding that suggests the possible role of the HCV structural region in HCV replication. This is the first report on the entry and replication of HCV infectious particles in mouse hepatocytes. These mouse hepatocyte lines will facilitate establishing a mouse HCV infection model with multifarious applications

Design and utilization of epitope-based databases and predictive tools

In the last decade, significant progress has been made in expanding the scope and depth of publicly available immunological databases and online analysis resources, which have become an integral part of the repertoire of tools available to the scientific community for basic and applied research. Herein, we present a general overview of different resources and databases currently available. Because of our association with the Immune Epitope Database and Analysis Resource, this resource is reviewed in more detail. Our review includes aspects such as the development of formal ontologies and the type and breadth of analytical tools available to predict epitopes and analyze immune epitope data. A common feature of immunological databases is the requirement to host large amounts of data extracted from disparate sources. Accordingly, we discuss and review processes to curate the immunological literature, as well as examples of how the curated data can be used to generate a meta-analysis of the epitope knowledge currently available for diseases of worldwide concern, such as influenza and malaria. Finally, we review the impact of immunological databases, by analyzing their usage and citations, and by categorizing the type of citations. Taken together, the results highlight the growing impact and utility of immunological databases for the scientific community

Crystal structure of nucleotide-free dynamin

Dynamin is a mechanochemical GTPase that oligomerizes around the neck of clathrin-coated pits and catalyses vesicle scission in a GTP-hydrolysis-dependent manner. The molecular details of oligomerization and the mechanism of the mechanochemical coupling are currently unknown. Here we present the crystal structure of human dynamin 1 in the nucleotide-free state with a four-domain architecture comprising the GTPase domain, the bundle signalling element, the stalk and the pleckstrin homology domain. Dynamin 1 oligomerized in the crystals via the stalks, which assemble in a criss-cross fashion. The stalks further interact via conserved surfaces with the pleckstrin homology domain and the bundle signalling element of the neighbouring dynamin molecule. This intricate domain interaction rationalizes a number of disease-related mutations in dynamin 2 and suggests a structural model for the mechanochemical coupling that reconciles previous models of dynamin function

Suppression of Mcl-1 via RNA interference sensitizes human hepatocellular carcinoma cells towards apoptosis induction

BACKGROUND: Hepatocelluar carcinoma (HCC) is one of the most common cancers worldwide and a major cause of cancer-related mortality. HCC is highly resistant to currently available chemotherapeutic drugs. Defects in apoptosis signaling contribute to this resistance. Myeloid cell leukemia-1 (Mcl-1) is an anti-apoptotic member of the Bcl-2 protein family which interferes with mitochondrial activation. In a previous study we have shown that Mcl-1 is highly expressed in tissues of human HCC. In this study, we manipulated expression of the Mcl-1 protein in HCC cells by RNA interference and analyzed its impact on apoptosis sensitivity of HCC cells in vitro. METHODS: RNA interference was performed by transfecting siRNA to specifically knock down Mcl-1 expression in HCC cells. Mcl-1 expression was measured by quantitative real-time PCR and Western blot. Induction of apoptosis and caspase activity after treatment with chemotherapeutic drugs and different targeted therapies were measured by flow cytometry and fluorometric analysis, respectively. RESULTS: Here we demonstrate that Mcl-1 expressing HCC cell lines show low sensitivity towards treatment with a panel of chemotherapeutic drugs. However, treatment with the anthracycline derivative epirubicin resulted in comparatively high apoptosis rates in HCC cells. Inhibition of the kinase PI3K significantly increased apoptosis induction by chemotherapy. RNA interference efficiently downregulated Mcl-1 expression in HCC cells. Mcl-1 downregulation sensitized HCC cells to different chemotherapeutic agents. Sensitization was accompanied by profound activation of caspase-3 and -9. In addition, Mcl-1 downregulation also increased apoptosis rates after treatment with PI3K inhibitors and, to a lower extent, after treatment with mTOR, Raf I and VEGF/PDGF kinase inhibitors. TRAIL-induced apoptosis did not markedly respond to Mcl-1 knockdown. Additionally, knockdown of Mcl-1 efficiently enhanced apoptosis sensitivity towards combined treatment modalities: Mcl-1 knockdown significantly augmented apoptosis sensitivity of HCC cells towards chemotherapy combined with PI3K inhibition. CONCLUSION: Our data suggest that specific downregulation of Mcl-1 by RNA interference is a promising approach to sensitize HCC cells towards chemotherapy and molecularly targeted therapies

PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

Background: CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high

Regulation of the DNA Damage Response and Gene Expression by the Dot1L Histone Methyltransferase and the 53Bp1 Tumour Suppressor

Dot1L, a histone methyltransferase that targets histone H3 lysine 79 (H3K79), has been implicated in gene regulation and the DNA damage response although its functions in these processes remain poorly defined.Using the chicken DT40 model system, we generated cells in which the Dot1L gene is disrupted to examine the function and focal recruitment of the 53Bp1 DNA damage response protein. Detailed kinetic and dose response assays demonstrate that, despite the absence of H3K79 methylation demonstrated by mass spectrometry, 53Bp1 focal recruitment is not compromised in these cells. We also describe, for the first time, the phenotypes of a cell line lacking both Dot1L and 53Bp1. Dot1L⁻/⁻ and wild type cells are equally resistant to ionising radiation, whereas 53Bp1⁻/⁻/Dot1L⁻/⁻ cells display a striking DNA damage resistance phenotype. Dot1L and 53Bp1 also affect the expression of many genes. Loss of Dot1L activity dramatically alters the mRNA levels of over 1200 genes involved in diverse biological functions. These results, combined with the previously reported list of differentially expressed genes in mouse ES cells knocked down for Dot1L, demonstrates surprising cell type and species conservation of Dot1L-dependent gene expression. In 53Bp1⁻/⁻ cells, over 300 genes, many with functions in immune responses and apoptosis, were differentially expressed. To date, this is the first global analysis of gene expression in a 53Bp1-deficient cell line.Taken together, our results uncover a negative role for Dot1L and H3K79 methylation in the DNA damage response in the absence of 53Bp1. They also enlighten the roles of Dot1L and 53Bp1 in gene expression and the control of DNA double-strand repair pathways in the context of chromatin

Metabolite ratios as potential biomarkers for type 2 diabetes:a DIRECT study

Aims/hypothesis Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case–control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p Conclusion/interpretation In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.</p