2,557 research outputs found

    Estimating the contribution of Helicobacter pylori to gastric cancer

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    Passive Energy Recapture in Jellyfish Contributes to Propulsive Advantage over other Metazoans

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    Gelatinous zooplankton populations are well known for their ability to take over perturbed ecosystems. The ability of these animals to outcompete and functionally replace fish that exhibit an effective visual predatory mode is counterintuitive because jellyfish are described as inefficient swimmers that must rely on direct contact with prey to feed. We show that jellyfish exhibit a unique mechanism of passive energy recapture, which is exploited to allow them to travel 30% further each swimming cycle, thereby reducing metabolic energy demand by swimming muscles. By accounting for large interspecific differences in net metabolic rates, we demonstrate, contrary to prevailing views, that the jellyfish (Aurelia aurita) is one of the most energetically efficient propulsors on the planet, exhibiting a cost of transport (joules per kilogram per meter) lower than other metazoans. We estimate that reduced metabolic demand by passive energy recapture improves the cost of transport by 48%, allowing jellyfish to achieve the large sizes required for sufficient prey encounters. Pressure calculations, using both computational fluid dynamics and a newly developed method from empirical velocity field measurements, demonstrate that this extra thrust results from positive pressure created by a vortex ring underneath the bell during the refilling phase of swimming. These results demonstrate a physical basis for the ecological success of medusan swimmers despite their simple body plan. Results from this study also have implications for bioinspired design, where low-energy propulsion is required

    Population structure of multidrug resistant Klebsiella oxytoca within hospitals across the UK and Ireland identifies sharing of virulence and resistance genes with K. pneumoniae.

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    Klebsiella oxytoca, a member of the Enterobacteriaceae, is a gram-negative pathogenic bacterium of environmental origin, which can cause infection in healthcare settings. Outbreaks of multidrug-resistant K. oxytoca infection have been increasingly reported in hospitalized patients. Despite the growing importance of this pathogen, there is limited knowledge about the population structure and epidemiology of antimicrobial resistant K. oxytoca. We investigated the population structure and genomic basis of antimicrobial resistance of 41 multidrug resistant K. oxytoca isolates recovered from bloodstream infections across the UK and Ireland. Our results show that K. oxytoca has a highly diverse population, which is composed of several distinct clades, and we identified one recent expansion of a clone within our dataset. Although the K. oxytoca genomes are clearly distinct from the genomes of a global collection of Klebsiella pneumoniae complex, pre-dominantly composed of K. pneumoniae, we found evidence for sharing of core genes through recombination, as well as the exchange of accessory antimicrobial resistance and virulence factor genes between the species. Our findings also suggest that the different K. oxytoca clades have acquired antimicrobial resistance and virulence factor genes independently. This highlights the clinical and therapeutic importance of genetic flexibility in K. oxytoca and the relevance of this in its role as an opportunistic pathogen

    Implementation of Deep CNN Model for the Detection of Plant Leaf Disease

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    The potato is the most important tuber crop in the world, and it is grown in about 125 different nations. Potato is the crop that is most commonly consumed by a billion people worldwide, virtually every day, behind rice and wheat. However, a number of bacterial and fungal diseases are causing the potato crop's quality and yield to decline. Potato Leaf diseases must be promptly identified and prevented to increase production. Various researchers look for solutions to protect plants instead of   traditional processes which take more time. Recent technological developments have thrown up many alternates to traditional methods which are labour intensive. The application of AlexNet model Deep Convolutional Neural Network(CNN) to recognise diseases in potato plants avoids the disadvantages of selecting disease spot features artificially and makes more objective the plant disease feature extraction. It improves research efficiency and speeds up technology transformation. Accuracies ranging from 85% - to 95% were obtained using AlexNet model Deep

    Subgoal- and goal-related reward prediction errors in medial prefrontal cortex

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    A longstanding view of the organization of human and animal behavior holds that behavior is hierarchically organizedin other words, directed toward achieving superordinate goals through the achievement of subordinate goals or subgoals. However, most research in neuroscience has focused on tasks without hierarchical structure. In past work, we have shown that negative reward prediction error (RPE) signals in medial prefrontal cortex (mPFC) can be linked not only to superordinate goals but also to subgoals. This suggests that mPFC tracks impediments in the progression toward subgoals. Using fMRI of human participants engaged in a hierarchical navigation task, here we found that mPFC also processes positive prediction errors at the level of subgoals, indicating that this brain region is sensitive to advances in subgoal completion. However, when subgoal RPEs were elicited alongside with goal-related RPEs, mPFC responses reflected only the goal-related RPEs. These findings suggest that information from different levels of hierarchy is processed selectively, depending on the task context

    Long-term interleukin-6 levels and subsequent risk of coronary heart disease: Two new prospective studies and a systematic review

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    Background The relevance to coronary heart disease (CHD) of cytokines that govern inflammatory cascades, such as interleukin-6 (IL-6), may be underestimated because such mediators are short acting and prone to fluctuations. We evaluated associations of long-term circulating IL-6 levels with CHD risk (defined as nonfatal myocardial infarction [MI] or fatal CHD) in two population-based cohorts, involving serial measurements to enable correction for within-person variability. We updated a systematic review to put the new findings in context. Methods and Findings Measurements were made in samples obtained at baseline from 2,138 patients who had a first-ever nonfatal MI or died of CHD during follow-up, and from 4,267 controls in two cohorts comprising 24,230 participants. Correction for within-person variability was made using data from repeat measurements taken several years apart in several hundred participants. The year-to-year variability of IL-6 values within individuals was relatively high (regression dilution ratios of 0.41, 95% confidence interval [CI] 0.28-0.53, over 4 y, and 0.35, 95% CI 0.23-0.48, over 12 y). Ignoring this variability, we found an odds ratio for CHD, adjusted for several established risk factors, of 1.46 (95% CI 1.29-1.65) per 2 standard deviation (SD) increase of baseline IL-6 values, similar to that for baseline C-reactive protein. After correction for within-person variability, the odds ratio for CHD was 2.14 (95% CI 1.45-3.15) with long-term average ("usual'') IL-6, similar to those for some established risk factors. Increasing IL-6 levels were associated with progressively increasing CHD risk. An updated systematic review of electronic databases and other sources identified 15 relevant previous population-based prospective studies of IL-6 and clinical coronary outcomes (i.e., MI or coronary death). Including the two current studies, the 17 available prospective studies gave a combined odds ratio of 1.61 (95% CI 1.42-1.83) per 2 SD increase in baseline IL-6 (corresponding to an odds ratio of 3.34 [95% CI 2.45-4.56] per 2 SD increase in usual [long-term average] IL-6 levels). Conclusions Long-term IL-6 levels are associated with CHD risk about as strongly as are some major established risk factors, but causality remains uncertain. These findings highlight the potential relevance of IL-6-mediated pathways to CH

    Defining the substrate for ventricular tachycardia ablation: The impact of rhythm at the time of mapping

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    BACKGROUND: Voltage mapping is critical to define substrate during ablation. In ventricular tachycardia, abnormal potentials may be targets. However, wavefront of activation could impact local signal characteristics. This may be particularly true when comparing sinus rhythm versus paced rhythms. We sought to determine how activation wavefront impacts electrogram characteristics. METHODS: Patients with ischemic cardiomyopathy, ventricular tachycardia, and without fascicular or bundle branch block were included. Point by point mapping was done and at each point, one was obtained during an atrial paced rhythm and one during a right ventricular paced rhythm. Signals were adjudicated after ablation to define late potentials, fractionated potentials, and quantify local voltage. Areas of abnormal voltage (defined as \u3c1.5 mV) were also determined. RESULTS: 9 patients were included (age 61.3 ± 9.2 years, 56% male, mean LVEF 34.9 ± 8.6%). LV endocardium was mapped with an average 375 ± 53 points/rhythm. Late potentials were more frequent during right ventricular pacing (51 ± 21 versus 32 ± 15, p \u3c 0.01) while overall scar area was higher during atrial pacing (22 ± 11% vs 13 ± 7%, p \u3c 0.05). In 1/9 patients, abnormal potentials were seen during a right ventricular paced rhythm that were not apparent in an atrial paced rhythm, ablation of which resulted in non-inducibility. CONCLUSION: Rhythm in which mapping is performed has an impact on electrogram characteristics. Whether one rhythm is preferable to map in remains to be determined. However, it is possible defining local signals during normal conduction as well as variable paced rhythms may impart a greater likelihood of elucidating arrhythmogenic substrate

    A CD4+ T cell antagonist epitope down-regulates activating signaling proteins, up-regulates inhibitory signaling proteins and abrogates HIV-specific T cell function

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    BACKGROUND: CD4(+) T cells are critically important in HIV infection, being both the primary cells infected by HIV and likely playing a direct or indirect role in helping control virus replication. Key areas of interest in HIV vaccine research are mechanisms of viral escape from the immune response. Interestingly, in HIV infection it has been shown that peptide sequence variation can reduce CD4(+) T cell responses to the virus, and small changes to peptide sequences can transform agonist peptides into antagonist peptides. RESULTS: We describe, at a molecular level, the consequences of antagonism of HIV p24-specific CD4(+) T cells. Antagonist peptide exposure in the presence of agonist peptide caused a global suppression of agonist-induced gene expression and signaling molecule phosphorylation. In addition to down-regulation of factors associated with T cell activation, a smaller subset of genes associated with negative regulation of cell activation was up-regulated, including KFL-2, SOCS-1, and SPDEY9P. Finally, antagonist peptide in the absence of agonist peptide also delivered a negative signal to T cells. CONCLUSIONS: Small changes in p24-specific peptides can result in T cell antagonism and reductions of both T cell receptor signaling and activation. These changes are at least in part mediated by a dominant negative signal delivered by antagonist peptide, as evidenced by up-regulation of negative regulatory genes in the presence of agonist plus antagonist stimulation. Antagonism can have dramatic effects on CD4(+) T cell function and presents a potential obstacle to HIV vaccine development
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