1,135 research outputs found
Moraxella catarrhalis acquisition, airway inflammation and protease-antiprotease balance in chronic obstructive pulmonary disease
<p>Abstract</p> <p>Background</p> <p><it>Moraxella catarrhalis </it>causes approximately 10% of exacerbations in chronic obstructive pulmonary disease (COPD) and also colonizes the lower airway in stable patients. Little is known about the effects of colonization by <it>M. catarrhalis </it>on airway inflammation and protease-antiprotease balance, and how these changes compare to those seen during exacerbations. Since COPD is a progressive inflammatory disease, elucidating the effects of bacterial colonization and exacerbation on airway inflammation is relevant to understanding disease progression in COPD. Our aims were (1) Analyze changes in airway inflammation in colonization and exacerbation of COPD due to <it>M. catarrhalis</it>; (2) Explore protease-antiprotease balance in colonization and exacerbation due to <it>M. catarrhalis</it>. Our hypothesis were (1) Acquisition of a new strain of M. catarrhalis in COPD increases airway inflammation from baseline and alters the protease-antiprotease balance towards a more proteolytic environment; (2) These changes are greater during exacerbations associated with <it>M. catarrhalis </it>as compared to colonization.</p> <p>Methods</p> <p>Thirty-nine consecutive COPD patients with 76 acquisitions of a new strain of <it>M. catarrhalis </it>over a 6-year period were identified in a prospective study. Seventy-six pre-acquisition sputum supernatant samples, obtained just before acquisition of <it>M catarrhalis</it>, and 76 acquisition samples (34 were associated with exacerbation, 42 with colonization) were analyzed for IL-8, TNF-α, Neutrophil Elastase (NE) and Secretory leukocyte protease inhibitor (SLPI). Changes were compared in paired samples from each patient.</p> <p>Results</p> <p>IL-8, TNF-α and NE were significantly elevated after acquisition of <it>M. catarrhalis</it>, compared to pre-acquisition samples (p =< 0.001 for all three). These changes were present in colonization (p = 0.015 for IL-8; p =< 0.001 for TNF-α and NE) as well as in exacerbation (p =< 0.001 for all three), compared to pre-acquisition levels. SLPI was significantly lower after acquisition (p =< 0.001), in colonization (p =< 0.001) as well as in exacerbation (p = 0.004), compared to pre-acquisition levels. SLPI levels correlated negatively with NE levels (R<sup>2 </sup>= 0.07; p = 0.001).</p> <p>Conclusion</p> <p>Acquisition of <it>M. catarrhalis </it>in COPD causes increased airway inflammation and worsening protease-antiprotease imbalance during exacerbations and also in colonization, even in the absence of increased symptoms. These effects could contribute to progression of airway disease in COPD.</p
Outbreak of a beta-lactam resistant non-typeable Haemophilus influenzae sequence type 14 associated with severe clinical outcomes
Activation of Epidermal Growth Factor Receptor Is Required for NTHi-Induced NF-κB-Dependent Inflammation
Inflammation is a hallmark of many serious human diseases. Nontypeable Haemophilus influenzae (NTHi) is an important human pathogen causing respiratory tract infections in both adults and children. NTHi infections are characterized by inflammation, which is mainly mediated by nuclear transcription factor-kappa B (NF-κB)-dependent production of proinflammatory mediators. Epidermal growth factor receptor (EGFR) has been shown to play important roles in regulating diverse biological processes, including cell growth, differentiation, apoptosis, adhesion, and migration. Its role in regulating NF-κB activation and inflammation, however, remains largely unknown.In the present study, we demonstrate that EGFR plays a vital role in NTHi-induced NF-κB activation and the subsequent induction of proinflammatory mediators in human middle ear epithelial cells and other cell types. Importantly, we found that AG1478, a specific tyrosine kinase inhibitor of EGFR potently inhibited NTHi-induced inflammatory responses in the middle ears and lungs of mice in vivo. Moreover, we found that MKK3/6-p38 and PI3K/Akt signaling pathways are required for mediating EGFR-dependent NF-κB activation and inflammatory responses by NTHi.Here, we provide direct evidence that EGFR plays a critical role in mediating NTHi-induced NF-κB activation and inflammation in vitro and in vivo. Given that EGFR inhibitors have been approved in clinical use for the treatment of cancers, current studies will not only provide novel insights into the molecular mechanisms underlying the regulation of inflammation, but may also lead to the development of novel therapeutic strategies for the treatment of respiratory inflammatory diseases and other inflammatory diseases
Determinants of subject visit participation in a prospective cohort study of HTLV infection
<p>Abstract</p> <p>Background</p> <p>Understanding participation in a prospective study is crucial to maintaining and improving retention rates. In 1990–92, following attempted blood donation at five blood centers, we enrolled 155 HTLV-I, 387 HTLV-II and 799 HTLV seronegative persons in a long-term prospective cohort.</p> <p>Methods</p> <p>Health questionnaires and physical exams were administered at enrollment and 2-year intervals through 2004. To examine factors influencing attendance at study visits of the cohort participants we calculated odds ratios (ORs) with generalized estimated equations (GEE) to analyze fixed and time-varying predictors of study visit participation.</p> <p>Results</p> <p>There were significant independent associations between better visit attendance and female gender (OR = 1.31), graduate education (OR = 1.86) and income > 25 vs. $10). None of the health related variables (HTLV status, perceived health status and referral to specialty diagnostic exam for potential adverse health outcomes) significantly affected participation after controlling for demographic variables.</p> <p>Conclusion</p> <p>Increasing and maintaining participation by minority and lower socioeconomic status participants is an ongoing challenge in the study of chronic disease outcomes. Future studies should include methods to evaluate attrition and retention, in addition to primary study outcomes, including qualitative analysis of reasons for participation or withdrawal.</p
Regulation of the vapBC-1 Toxin-Antitoxin Locus in Nontypeable Haemophilus influenzae
Nontypeable Haemophilus influenzae (NTHi) are human-adapted commensal bacteria that can cause a number of chronic mucosal infections, including otitis media and bronchitis. One way for these organisms to survive antibiotic therapy and cause recurrent disease is to stop replicating, as most antimicrobials target essential biosynthetic pathways. Toxin-antitoxin (TA) gene pairs have been shown to facilitate entry into a reversible bacteriostatic state. Characteristically, these operons encode a protein toxin and an antitoxin that associate following translation to form a nontoxic complex, which then binds to and regulates the cognate TA promoter. Under stressful conditions, the labile antitoxin is degraded and the complex disintegrates, freeing the stable toxin to facilitate growth arrest. How these events affected the regulation of the TA locus, as well as how the transcription of the operon was subsequently returned to its normal state upon resumption of growth, was not fully understood. Here we show that expression of the NTHi vapBC-1 TA locus is repressed by a complex of VapB-1 and VapC-1 under conditions favorable for growth, and activated by the global transactivator Factor for Inversion Stimulation (Fis) upon nutrient upshift from stationary phase. Further, we demonstrate for the first time that the VapC-1 toxin alone can bind to its cognate TA locus control region and that the presence of VapB-1 directs the binding of the VapBC-1 complex in the transcriptional regulation of vapBC-1
Molecular Surveillance of True Nontypeable Haemophilus influenzae: An Evaluation of PCR Screening Assays
BackgroundUnambiguous identification of nontypeable Haemophilus influenzae (NTHi) is not possible by conventional microbiology. Molecular characterisation of phenotypically defined NTHi isolates suggests that up to 40% are Haemophilus haemolyticus (Hh); however, the genetic similarity of NTHi and Hh limits the power of simple molecular techniques such as PCR for species discrimination.Methodology/Principal FindingsHere we assess the ability of previously published and novel PCR-based assays to identify true NTHi. Sixty phenotypic NTHi isolates, classified by a dual 16S rRNA gene PCR algorithm as NTHi (n = 22), Hh (n = 27) or equivocal (n = 11), were further characterised by sequencing of the 16S rRNA and recA genes then interrogated by PCR-based assays targeting the omp P2, omp P6, lgtC, hpd, 16S rRNA, fucK and iga genes. The sequencing data and PCR results were used to define NTHi for this study. Two hpd real time PCR assays (hpd#1 and hpd#3) and the conventional iga PCR assay were equally efficient at differentiating study-defined NTHi from Hh, each with a receiver operator characteristic curve area of 0.90 [0.83; 0.98]. The hpd#1 and hpd#3 assays were completely specific against a panel of common respiratory bacteria, unlike the iga PCR, and the hpd#3 assay was able to detect below 10 copies per reaction.Conclusions/SignificanceOur data suggest an evolutionary continuum between NTHi and Hh and therefore no single gene target could completely differentiate NTHi from Hh. The hpd#3 real time PCR assay proved to be the superior method for discrimination of NTHi from closely related Haemophilus species with the added potential for quantification of H. influenzae directly from specimens. We suggest the hpd#3 assay would be suitable for routine NTHi surveillance and to assess the impact of antibiotics and vaccines, on H. influenzae carriage rates, carriage density, and disease
Syntenator: Multiple gene order alignments with a gene-specific scoring function
<p>Abstract</p> <p>Background</p> <p>Identification of homologous regions or conserved syntenies across genomes is one crucial step in comparative genomics. This task is usually performed by genome alignment softwares like WABA or blastz. In case of conserved syntenies, such regions are defined as conserved gene orders. On the gene order level, homologous regions can even be found between distantly related genomes, which do not align on the nucleotide sequence level.</p> <p>Results</p> <p>We present a novel approach to identify regions of conserved synteny across multiple genomes. Syntenator represents genomes and alignments thereof as partial order graphs (POGs). These POGs are aligned by a dynamic programming approach employing a gene-specific scoring function. The scoring function reflects the level of protein sequence similarity for each possible gene pair. Our method consistently defines larger homologous regions in pairwise gene order alignments than nucleotide-level comparisons. Our method is superior to methods that work on predefined homology gene sets (as implemented in Blockfinder). Syntenator successfully reproduces 80% of the EnsEMBL man-mouse conserved syntenic blocks. The full potential of our method becomes visible by comparing remotely related genomes and multiple genomes. Gene order alignments potentially resolve up to 75% of the EnsEMBL 1:many orthology relations and 27% of the many:many orthology relations.</p> <p>Conclusion</p> <p>We propose Syntenator as a software solution to reliably infer conserved syntenies among distantly related genomes. The software is available from <url>http://www2.tuebingen.mpg.de/abt4/plone</url>.</p
Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection
BACKGROUND: Gaps in disease surveillance capacity, particularly for emerging infections and bioterrorist attack, highlight a need for efficient, real time identification of diseases. METHODS: We studied automated records from 1996 through 1999 of approximately 250,000 health plan members in greater Boston. RESULTS: We identified 152,435 lower respiratory infection illness visits, comprising 106,670 episodes during 1,143,208 person-years. Three diagnoses, cough (ICD9CM 786.2), pneumonia not otherwise specified (ICD9CM 486) and acute bronchitis (ICD9CM 466.0) accounted for 91% of these visits, with expected age and sex distributions. Variation of weekly occurrences corresponded closely to national pneumonia and influenza mortality data. There was substantial variation in geographic location of the cases. CONCLUSION: This information complements existing surveillance programs by assessing the large majority of episodes of illness for which no etiologic agents are identified. Additional advantages include: a) sensitivity, uniformity and efficiency, since detection of events does not depend on clinicians' to actively report diagnoses, b) timeliness, the data are available within a day of the clinical event; and c) ease of integration into automated surveillance systems. These features facilitate early detection of conditions of public health importance, including regularly occurring events like seasonal respiratory illness, as well as unusual occurrences, such as a bioterrorist attack that first manifests as respiratory symptoms. These methods should also be applicable to other infectious and non-infectious conditions. Knowledge of disease patterns in real time may also help clinicians to manage patients, and assist health plan administrators in allocating resources efficiently
Occlusion-aware 3D Morphable Models and an Illumination Prior for Face Image Analysis
Faces in natural images are often occluded by a variety of objects. We propose a fully automated, probabilistic and occlusion-aware 3D morphable face model adaptation framework following an analysis-by-synthesis setup. The key idea is to segment the image into regions explained by separate models. Our framework includes a 3D morphable face model, a prototype-based beard model and a simple model for occlusions and background regions. The segmentation and all the model parameters have to be inferred from the single target image. Face model adaptation and segmentation are solved jointly using an expectation-maximization-like procedure. During the E-step, we update the segmentation and in the M-step the face model parameters are updated. For face model adaptation we apply a stochastic sampling strategy based on the Metropolis-Hastings algorithm. For segmentation, we apply loopy belief propagation for inference in a Markov random field. Illumination estimation is critical for occlusion handling. Our combined segmentation and model adaptation needs a proper initialization of the illumination parameters. We propose a RANSAC-based robust illumination estimation technique. By applying this method to a large face image database we obtain a first empirical distribution of real-world illumination conditions. The obtained empirical distribution is made publicly available and can be used as prior in probabilistic frameworks, for regularization or to synthesize data for deep learning methods
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