362 research outputs found

    Changes in anti-viral effectiveness of interferon after dose reduction in chronic hepatitis c patients: a case control study

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    BACKGROUND: High dose interferon induction treatment of hepatitis C viral infection blocks viral production over 95%. Since dose reduction is often performed due to clinical considerations, the effect of dose reduction on hepatitis C virus kinetics was studied. METHODS: A new model that allowed longitudinal changes in the parameters of viral dynamics was used in a group of genotype-1 patients (N = 15) with dose reduction from 10 to 3 million units of interferon daily in combination with ribavirin, in comparison to a control group (N = 9) with no dose reduction. RESULTS: Dose reduction gave rise to a complex viral kinetic pattern, which could be only explained by a decrease in interferon effectiveness in blocking virion production. The benefit of the rapid initial viral decline following the high induction dose is lost after dose reduction. In addition, in some patients also the second phase viral decline slope, which is highly predictive of success of treatment, was impaired by the dose reduction resulting in smaller percentage of viral clearance in the dose reduction group. CONCLUSIONS: These findings, while explaining the failure of many induction schedules, suggest that for genotype-1 patients induction therapy should be continued till HCVRNA negativity in serum in order to increase the sustained response rate for chronic hepatitis C

    Globally, plant-soil feedbacks are weak predictors of plant abundance

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    Plant-soil feedbacks (PSFs) have been shown to strongly affect plant performance under controlled conditions, and PSFs are thought to have far reaching consequences for plant population dynamics and the structuring of plant communities. However, thus far the relationship between PSF and plant species abundance in the field is not consistent. Here, we synthesize PSF experiments from tropical forests to semiarid grasslands, and test for a positive relationship between plant abundance in the field and PSFs estimated from controlled bioassays. We meta-analyzed results from 22 PSF experiments and found an overall positive correlation (0.12 <= r over bar <= 0.32) between plant abundance in the field and PSFs across plant functional types (herbaceous and woody plants) but also variation by plant functional type. Thus, our analysis provides quantitative support that plant abundance has a general albeit weak positive relationship with PSFs across ecosystems. Overall, our results suggest that harmful soil biota tend to accumulate around and disproportionately impact species that are rare. However, data for the herbaceous species, which are most common in the literature, had no significant abundance-PSFs relationship. Therefore, we conclude that further work is needed within and across biomes, succession stages and plant types, both under controlled and field conditions, while separating PSF effects from other drivers (e.g., herbivory, competition, disturbance) of plant abundance to tease apart the role of soil biota in causing patterns of plant rarity versus commonness

    Performance of the ESC 0/1-h and 0/3-h Algorithm for the Rapid Identification of Myocardial Infarction Without ST-Elevation in Patients With Diabetes

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    Patients with diabetes mellitus (DM) have elevated levels of high-sensitivity cardiac troponin (hs-cTn). We investigated the diagnostic performance of the European Society of Cardiology (ESC) algorithms to rule out or rule in acute myocardial infarction (AMI) without ST-elevation in patients with DM.; We prospectively enrolled 3,681 patients with suspected AMI and stratified those by the presence of DM. The ESC 0/1-h and 0/3-h algorithms were used to calculate negative and positive predictive values (NPV, PPV). In addition, alternative cutoffs were calculated and externally validated in 2,895 patients.; In total, 563 patients (15.3%) had DM, and 137 (24.3%) of these had AMI. When the ESC 0/1-h algorithm was used, the NPV was comparable in patients with and without DM (absolute difference [AD] -1.50 [95% CI -5.95, 2.96]). In contrast, the ESC 0/3-h algorithm resulted in a significantly lower NPV in patients with DM (AD -2.27 [95% CI -4.47, -0.07]). The diagnostic performance for rule-in of AMI (PPV) was comparable in both groups: 0/1-h (AD 6.59 [95% CI -19.53, 6.35]) and 0/3-h (AD 1.03 [95% CI -7.63, 9.7]). Alternative cutoffs increased the PPV in both algorithms significantly, while improvements in NPV were only subtle.; Application of the ESC 0/1-h algorithm revealed comparable safety to rule out AMI comparing patients with and without DM, while this was not observed with the ESC 0/3-h algorithm. Although alternative cutoffs might be helpful, patients with DM remain a high-risk population in whom identification of AMI is challenging and who require careful clinical evaluation

    S100A9 is indispensable for survival of pneumococcal pneumonia in mice

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    S100A8/A9 has important immunomodulatory roles in antibacterial defense, but its relevance in focal pneumonia caused by Streptococcus pneumoniae (S. pneumoniae) is understudied. We show that S100A9 was significantly increased in BAL fluids of patients with bacterial but not viral pneumonia and correlated with procalcitonin and sequential organ failure assessment scores. Mice deficient in S100A9 exhibited drastically elevated Zn2+^{2+} levels in lungs, which led to bacterial outgrowth and significantly reduced survival. In addition, reduced survival of S100A9 KO mice was characterized by excessive release of neutrophil elastase, which resulted in degradation of opsonophagocytically important collectins surfactant proteins A and D. All of these features were attenuated in S. pneumoniae-challenged chimeric WT→S100A9 KO mice. Similarly, therapy of S. pneumoniae-infected S100A9 KO mice with a mutant S100A8/A9 protein showing increased half-life significantly decreased lung bacterial loads and lung injury. Collectively, S100A9 controls central antibacterial immune mechanisms of the lung with essential relevance to survival of pneumococcal pneumonia. Moreover, S100A9 appears to be a promising biomarker to distinguish patients with bacterial from those with viral pneumonia. Trial registration: Clinical Trials register (DRKS00000620)

    Genomic history of Neolithic to Bronze Age Anatolia, Northern Levant, and Southern Caucasus

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    Here, we report genome-wide data analyses from 110 ancient Near Eastern individuals spanning the Late Neolithic to Late Bronze Age, a period characterized by intense interregional interactions for the Near East. We find that 6th millennium BCE populations of North/Central Anatolia and the Southern Caucasus shared mixed ancestry on a genetic cline that formed during the Neolithic between Western Anatolia and regions in today’s Southern Caucasus/Zagros. During the Late Chalcolithic and/or the Early Bronze Age, more than half of the Northern Levantine gene pool was replaced, while in the rest of Anatolia and the Southern Caucasus, we document genetic continuity with only transient gene flow. Additionally, we reveal a genetically distinct individual within the Late Bronze Age Northern Levant. Overall, our study uncovers multiple scales of population dynamics through time, from extensive admixture during the Neolithic period to long-distance mobility within the globalized societies of the Late Bronze Age. Video Abstrac

    The ALMOND Survey: Molecular cloud properties and gas density tracers across 25 nearby spiral galaxies with ALMA

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    We use new HCN(1-0) data from the ALMOND (ACA Large-sample Mapping Of Nearby galaxies in Dense gas) survey to trace the kpc-scale molecular gas density structure and CO(2-1) data from PHANGS-ALMA to trace the bulk molecular gas across 25 nearby, star-forming galaxies. At 2.1 kpc scale, we measure the density-sensitive HCN/CO line ratio and the SFR/HCN ratio to trace the star formation efficiency in the denser molecular medium. At 150 pc scale, we measure structural and dynamical properties of the molecular gas via CO(2-1) line emission, which is linked to the lower resolution data using an intensity-weighted averaging method. We find positive correlations (negative) of HCN/CO (SFR/HCN) with the surface density, the velocity dispersion and the internal turbulent pressure of the molecular gas. These observed correlations agree with expected trends from turbulent models of star formation, which consider a single free-fall time gravitational collapse. Our results show that the kpc-scale HCN/CO line ratio is a powerful tool to trace the 150 pc scale average density distribution of the molecular clouds. Lastly, we find systematic variations of the SFR/HCN ratio with cloud-scale molecular gas properties, which are incompatible with a universal star formation efficiency. Overall, these findings show that mean molecular gas density, molecular cloud properties and star formation are closely linked in a coherent way, and observations of density-sensitive molecular gas tracers are a useful tool to analyse these variations, linking molecular gas physics to stellar output across galaxy discs.Comment: 48 pages, 40 figure

    Large-scale differences in microbial biodiversity discovery between 16S amplicon and shotgun sequencing

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    Modern metagenomic environmental DNA studies are almost completely reliant on next-generation sequencing, making evaluations of these methods critical. We compare two next-generation sequencing techniques – amplicon and shotgun – on water samples across four of Brazil’s major river floodplain systems (Amazon, Araguaia, Paraná, and Pantanal). Less than 50% of phyla identified via amplicon sequencing were recovered from shotgun sequencing, clearly challenging the dogma that mid-depth shotgun recovers more diversity than amplicon-based approaches. Amplicon sequencing also revealed ~27% more families. Overall the amplicon data were more robust across both biodiversity and community ecology analyses at different taxonomic scales. Our work doubles the sampling size in similar environmental studies, and novelly integrates environmental data (e.g., pH, temperature, nutrients) from each site, revealing divergent correlations depending on which data are used. While myriad variants on NGS techniques and bioinformatic pipelines are available, our results point to core differences that have not been highlighted in any studies to date. Given the low number of taxa identified when coupling shotgun data with clade-based taxonomic algorithms, previous studies that quantified biodiversity using such bioinformatic tools should be viewed cautiously or re-analyzed. Nonetheless, shotgun has complementary advantages that should be weighed when designing projects
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