Modelling Techniques for the Quantification of Some Electron Beam Induced Phenomena

This paper presents simulation models for quantifying the voltage contrast, cathodoluminescence and indirect specimen charging phenomena in the scanning electron microscope (SEM). The voltage contrast model comprises an electric field computation program using the finite-element approach, and a secondary electron trajectory tracking algorithm employing a linear electric field assumption. This trajectory tracking algorithm is more accurate than the conventional electron trajectory tracking algorithms which make use of a constant electric field assumption within each computation step. Using this model, results of qualitative voltage contrast effects on secondary electron trajectories in the specimen chamber of the SEM are shown. This model can also be used for quantitative voltage studies for designing low error voltage energy analysers. The cathodoluminescence (CL) model consists of programs for simulating the electron beam-specimen interaction via Monte Carlo analysis, excess carrier generation and distribution, and optical losses of the CL emission. This model has been used to simulate the CL intensity as a function of surface recombination velocity, diffusion length, and absorption coefficient. A model has also been developed to simulate indirect charging of specimens in the SEM. This model uses the finite-element method to solve for the self-consistent electric field due to the imposed boundary conditions, trapped and moving charges. Secondary electrons are tracked using the trajectory tracking scheme developed

Crystal structure of a tripartite complex between C3dg, C-terminal domains of factor H and OspE of Borrelia burgdorferi

Complement is an important part of innate immunity. The alternative pathway of complement is activated when the main opsonin, C3b coats non-protected surfaces leading to opsonisation, phagocytosis and cell lysis. The alternative pathway is tightly controlled to prevent autoactivation towards host cells. The main regulator of the alternative pathway is factor H (FH), a soluble glycoprotein that terminates complement activation in multiple ways. FH recognizes host cell surfaces via domains 19–20 (FH19-20). All microbes including Borrelia burgdorferi, the causative agent of Lyme borreliosis, must evade complement activation to allow the infectious agent to survive in its host. One major mechanism that Borrelia uses is to recruit FH from host. Several outer surface proteins (Osp) have been described to bind FH via the C-terminus, and OspE is one of them. Here we report the structure of the tripartite complex formed by OspE, FH19-20 and C3dg at 3.18 Å, showing that OspE and C3dg can bind simultaneously to FH19-20. This verifies that FH19-20 interacts via the “common microbial binding site” on domain 20 with OspE and simultaneously and independently via domain 19 with C3dg. The spatial organization of the tripartite complex explains how OspE on the bacterial surface binds FH19-20, leaving FH fully available to protect the bacteria against complement. Additionally, formation of tripartite complex between FH, microbial protein and C3dg might enable enhanced protection, particularly on those regions on the bacteria where previous complement activation led to deposition of C3d. This might be especially important for slow-growing bacteria that cause chronic disease like Borrelia burgdorferi.Peer reviewe

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Genetic Associations of Type 2 Diabetes with Islet Amyloid Polypeptide Processing and Degrading Pathways in Asian Populations

10.1371/journal.pone.0062378PLoS ONE86

Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study

Increased red cell distribution width (RDW) is associated with poorer outcomes in various patient populations. We investigated the association between preoperative RDW and anaemia on 30-day postoperative mortality among elderly patients undergoing non-cardiac surgery. Medical records of 24,579 patients aged 65 and older who underwent surgery under anaesthesia between 1 January 2012 and 31 October 2016 were retrospectively analysed. Patients who died within 30 days had higher median RDW (15.0%) than those who were alive (13.4%). Based on multivariate logistic regression, in our cohort of elderly patients undergoing non-cardiac surgery, moderate/severe preoperative anaemia (aOR 1.61, p = 0.04) and high preoperative RDW levels in the 3rd quartile (>13.4% and ≤14.3%) and 4th quartile (>14.3%) were significantly associated with increased odds of 30-day mortality - (aOR 2.12, p = 0.02) and (aOR 2.85, p = 0.001) respectively, after adjusting for the effects of transfusion, surgical severity, priority of surgery, and comorbidities. Patients with high RDW, defined as >15.7% (90th centile), and preoperative anaemia have higher odds of 30-day mortality compared to patients with anaemia and normal RDW. Thus, preoperative RDW independently increases risk of 30-day postoperative mortality, and future risk stratification strategies should include RDW as a factor

Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducibility for use in research/quality assurance

<p>Abstract</p> <p>Background</p> <p>Although reproducibility in reading MRI images amongst radiologists and clinicians has been studied previously, no studies have examined the reproducibility of inexperienced clinicians in extracting pathoanatomic information from magnetic resonance imaging (MRI) narrative reports and transforming that information into quantitative data. However, this process is frequently required in research and quality assurance contexts. The purpose of this study was to examine inter-rater reproducibility (agreement and reliability) among an inexperienced group of clinicians in extracting spinal pathoanatomic information from radiologist-generated MRI narrative reports.</p> <p>Methods</p> <p>Twenty MRI narrative reports were randomly extracted from an institutional database. A group of three physiotherapy students independently reviewed the reports and coded the presence of 14 common pathoanatomic findings using a categorical electronic coding matrix. Decision rules were developed after initial coding in an effort to resolve ambiguities in narrative reports. This process was repeated a further three times using separate samples of 20 MRI reports until no further ambiguities were identified (total n = 80). Reproducibility between trainee clinicians and two highly trained raters was examined in an arbitrary coding round, with agreement measured using percentage agreement and reliability measured using unweighted Kappa (<it>k</it>). Reproducibility was then examined in another group of three trainee clinicians who had not participated in the production of the decision rules, using another sample of 20 MRI reports.</p> <p>Results</p> <p>The mean percentage agreement for paired comparisons between the initial trainee clinicians improved over the four coding rounds (97.9-99.4%), although the greatest improvement was observed after the first introduction of coding rules. High inter-rater reproducibility was observed between trainee clinicians across 14 pathoanatomic categories over the four coding rounds (agreement range: 80.8-100%; reliability range <it>k </it>= 0.63-1.00). Concurrent validity was high in paired comparisons between trainee clinicians and highly trained raters (agreement 97.8-98.1%, reliability <it>k </it>= 0.83-0.91). Reproducibility was also high in the second sample of trainee clinicians (inter-rater agreement 96.7-100.0% and reliability <it>k </it>= 0.76-1.00; intra-rater agreement 94.3-100.0% and reliability <it>k </it>= 0.61-1.00).</p> <p>Conclusions</p> <p>A high level of radiological training is not required in order to transform MRI-derived pathoanatomic information from a narrative format to a quantitative format with high reproducibility for research or quality assurance purposes.</p

Identification of neural networks that contribute to motion sickness through principal components analysis of fos labeling induced by galvanic vestibular stimulation

Motion sickness is a complex condition that includes both overt signs (e.g., vomiting) and more covert symptoms (e.g., anxiety and foreboding). The neural pathways that mediate these signs and symptoms are yet to identified. This study mapped the distribution of c-fos protein (Fos)-like immunoreactivity elicited during a galvanic vestibular stimulation paradigm that is known to induce motion sickness in felines. A principal components analysis was used to identify networks of neurons activated during this stimulus paradigm from functional correlations between Fos labeling in different nuclei. This analysis identified five principal components (neural networks) that accounted for greater than 95% of the variance in Fos labeling. Two of the components were correlated with the severity of motion sickness symptoms, and likely participated in generating the overt signs of the condition. One of these networks included neurons in locus coeruleus, medial, inferior and lateral vestibular nuclei, lateral nucleus tractus solitarius, medial parabrachial nucleus and periaqueductal gray. The second included neurons in the superior vestibular nucleus, precerebellar nuclei, periaqueductal gray, and parabrachial nuclei, with weaker associations of raphe nuclei. Three additional components (networks) were also identified that were not correlated with the severity of motion sickness symptoms. These networks likely mediated the covert aspects of motion sickness, such as affective components. The identification of five statistically independent component networks associated with the development of motion sickness provides an opportunity to consider, in network activation dimensions, the complex progression of signs and symptoms that are precipitated in provocative environments. Similar methodology can be used to parse the neural networks that mediate other complex responses to environmental stimuli. © 2014 Balaban et al

The neural substrate of positive bias in spontaneous emotional processing

Even in the presence of negative information, healthy human beings display an optimistic tendency when thinking of past success and future chances, giving a positive bias to everyday's cognition. The tendency to actively select positive thoughts suggests the existence of a mechanism to exclude negative content, raising the issue of its dependence on mechanisms like those of effortful control. Using perfusion imaging, we examined how brain activations differed according to whether participants were left to prefer positive thoughts spontaneously, or followed an explicit instruction to the same effect, finding a widespread dissociation of brain perfusion patterns. Under spontaneous processing of emotional material, recruitment of areas associated with effortful attention, such as the dorsolateral prefrontal cortex, was reduced relative to instructed avoidance of negative material (F(1,58) = 26.24, p = 0.047, corrected). Under spontaneous avoidance perfusion increments were observed in several areas that were deactivated by the task, including the perigenual medial prefrontal cortex. Furthermore, individual differences in executive capacity were not associated with positive bias. These findings suggest that spontaneous positive cognitive emotion regulation in health may result from processes that, while actively suppressing emotionally salient information, differ from those associated with effortful and directed control