119 research outputs found

    Total 18F-dopa PET tumour uptake reflects metabolic endocrine tumour activity in patients with a carcinoid tumour

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    Positron emission tomography (PET) using 6-[(18)F]fluoro-L-dihydroxyphenylalanine ((18)F-dopa) has an excellent sensitivity to detect carcinoid tumour lesions. (18)F-dopa tumour uptake and the levels of biochemical tumour markers are mediated by tumour endocrine metabolic activity. We evaluated whether total (18)F-dopa tumour uptake on PET, defined as whole-body metabolic tumour burden (WBMTB), reflects tumour load per patient, as measured with tumour markers. Seventy-seven consecutive carcinoid patients who underwent an (18)F-dopa PET scan in two previously published studies were analysed. For all tumour lesions mean standardised uptake values (SUVs) at 40% of the maximal SUV and tumour volume on (18)F-dopa PET were determined and multiplied to calculate a metabolic burden per lesion. WBMTB was the sum of the metabolic burden of all individual lesions per patient. The 24-h urinary serotonin, urine and plasma 5-hydroxindoleacetic acid (5-HIAA), catecholamines (nor)epinephrine, dopamine and their metabolites, measured in urine and plasma, and serum chromogranin A served as tumour markers. All but 1 were evaluable for WBMTB; 74 patients had metastatic disease. (18)F-dopa PET detected 979 lesions. SUV(max) on (18)F-dopa PET varied up to 29-fold between individual lesions within the same patients. WBMTB correlated with urinary serotonin (r = 0.51) and urinary and plasma 5-HIAA (r = 0.78 and 0.66). WBMTB also correlated with urinary norepinephrine, epinephrine, dopamine and plasma dopamine, but not with serum chromogranin A. Tumour load per patient measured with (18)F-dopa PET correlates with tumour markers of the serotonin and catecholamine pathway in urine and plasma in carcinoid patients, reflecting metabolic tumour activity

    Inferring the dynamics of rising radical right-wing party support using Gaussian processes

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    The use of classical regression techniques in social science can prevent the discovery of complex, nonlinear mechanisms, and often relies too heavily on both the expertise and prior expectations of the data analyst. In this paper, we present a regression methodology that combines the interpretability of traditional, well used, statistical methods with the full predictability and flexibility of Bayesian statistics techniques. Our modelling approach allow us to find and explain the mechanisms behind the rise of Radical Right-wing Populist parties (RRPs), that we would have been unable to find using traditional methods. Using Swedish municipality level data (2002-2018) we find no evidence that the proportion of foreignborn residents is predictive of increases in RRP support. Instead, education levels and population density are the significant variables that impact the change in support for the RRP, in addition to spatial and temporal control variables. We argue that our methodology, which produces models with considerably better fit of the complexity and nonlinearities often found in social systems, provides a better tool for hypothesis testing and exploration of theories about RRPs and other social movements

    Transmission of Novel Influenza A(H1N1) in Households with Post-Exposure Antiviral Prophylaxis

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    BACKGROUND: Despite impressive advances in our understanding of the biology of novel influenza A(H1N1) virus, little is as yet known about its transmission efficiency in close contact places such as households, schools, and workplaces. These are widely believed to be key in supporting propagating spread, and it is therefore of importance to assess the transmission levels of the virus in such settings. METHODOLOGY/PRINCIPAL FINDINGS: We estimate the transmissibility of novel influenza A(H1N1) in 47 households in the Netherlands using stochastic epidemic models. All households contained a laboratory confirmed index case, and antiviral drugs (oseltamivir) were given to both the index case and other households members within 24 hours after detection of the index case. Among the 109 household contacts there were 9 secondary infections in 7 households. The overall estimated secondary attack rate is low (0.075, 95%CI: 0.037-0.13). There is statistical evidence indicating that older persons are less susceptible to infection than younger persons (relative susceptibility of older persons: 0.11, 95%CI: 0.024-0.43. Notably, the secondary attack rate from an older to a younger person is 0.35 (95%CI: 0.14-0.61) when using an age classification of <or=12 versus >12 years, and 0.28 (95%CI: 0.12-0.50) when using an age classification of <or=18 versus >18 years. CONCLUSIONS/SIGNIFICANCE: Our results indicate that the overall household transmission levels of novel influenza A(H1N1) in antiviral-treated households were low in the early stage of the epidemic. The relatively high rate of adult-to-child transmission indicates that control measures focused on this transmission route will be most effective in minimizing the total number of infections

    Multishot versus Single-Shot Pulse Sequences in Very High Field fMRI: A Comparison Using Retinotopic Mapping

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    High-resolution functional MRI is a leading application for very high field (7 Tesla) human MR imaging. Though higher field strengths promise improvements in signal-to-noise ratios (SNR) and BOLD contrast relative to fMRI at 3 Tesla, these benefits may be partially offset by accompanying increases in geometric distortion and other off-resonance effects. Such effects may be especially pronounced with the single-shot EPI pulse sequences typically used for fMRI at standard field strengths. As an alternative, one might consider multishot pulse sequences, which may lead to somewhat lower temporal SNR than standard EPI, but which are also often substantially less susceptible to off-resonance effects. Here we consider retinotopic mapping of human visual cortex as a practical test case by which to compare examples of these sequence types for high-resolution fMRI at 7 Tesla. We performed polar angle retinotopic mapping at each of 3 isotropic resolutions (2.0, 1.7, and 1.1 mm) using both accelerated single-shot 2D EPI and accelerated multishot 3D gradient-echo pulse sequences. We found that single-shot EPI indeed led to greater temporal SNR and contrast-to-noise ratios (CNR) than the multishot sequences. However, additional distortion correction in postprocessing was required in order to fully realize these advantages, particularly at higher resolutions. The retinotopic maps produced by both sequence types were qualitatively comparable, and showed equivalent test/retest reliability. Thus, when surface-based analyses are planned, or in other circumstances where geometric distortion is of particular concern, multishot pulse sequences could provide a viable alternative to single-shot EPI

    Large-Scale Phylogenetic Analysis of Emerging Infectious Diseases

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    Microorganisms that cause infectious diseases present critical issues of national security, public health, and economic welfare.  For example, in recent years, highly pathogenic strains of avian influenza have emerged in Asia, spread through Eastern Europe and threaten to become pandemic. As demonstrated by the coordinated response to Severe Acute Respiratory Syndrome (SARS) and influenza, agents of infectious disease are being addressed via large-scale genomic sequencing.  The goal of genomic sequencing projects are to rapidly put large amounts of data in the public domain to accelerate research on disease surveillance, treatment, and prevention. However, our ability to derive information from large comparative genomic datasets lags far behind acquisition.  Here we review the computational challenges of comparative genomic analyses, specifically sequence alignment and reconstruction of phylogenetic trees.  We present novel analytical results on from two important infectious diseases, Severe Acute Respiratory Syndrome (SARS) and influenza.SARS and influenza have similarities and important differences both as biological and comparative genomic analysis problems.  Influenza viruses (Orthymxyoviridae) are RNA based.  Current evidence indicates that influenza viruses originate in aquatic birds from wild populations. Influenza has been studied for decades via well-coordinated international efforts.  These efforts center on surveillance via antibody characterization of the hemagglutinin (HA) and neuraminidase (N) proteins of the circulating strains to inform vaccine design. However we still do not have a clear understanding of: 1) various transmission pathways such as the role of intermediate hosts such as swine and domestic birds and 2) the key mutation and genomic recombination events that underlie periodic pandemics of influenza.  In the past 30 years, sequence data from HA and N loci has become an important data type. In the past year, full genomic data has become prominent.  These data present exciting opportunities to address unanswered questions in influenza pandemics.SARS is caused by a previously unrecognized lineage of coronavirus, SARS-CoV, which like influenza has an RNA based genome.  Although SARS-CoV is widely believed to have originated in animals there remains disagreement over the candidate animal source that lead to the original outbreak of SARS.  In contrast to the long history of the study of influenza, SARS was only recognized in late 2002 and the virus that causes SARS has been documented primarily by genomic sequencing.In the past, most studies of influenza were performed on a limited number of isolates and genes suited to a particular problem.  Major goals in science today are to understand emerging diseases in broad geographic, environmental, societal, biological, and genomic contexts. Synthesizing diverse information brought together by various researchers is important to find out what can be done to prevent future outbreaks {JON03}.  Thus comprehensive means to organize and analyze large amounts of diverse information are critical.  For example, the relationships of isolates and patterns of genomic change observed in large datasets might not be consistent with hypotheses formed on partial data.  Moreover when researchers rely on partial datasets, they restrict the range of possible discoveries.Phylogenetics is well suited to the complex task of understanding emerging infectious disease. Phylogenetic analyses can test many hypotheses by comparing diverse isolates collected from various hosts, environments, and points in time and organizing these data into various evolutionary scenarios.  The products of a phylogenetic analysis are a graphical tree of ancestor-descendent relationships and an inferred summary of mutations, recombination events, host shifts, geographic, and temporal spread of the viruses.  However, this synthesis comes at a price.  The cost of computation of phylogenetic analysis expands combinatorially as the number of isolates considered increases. Thus, large datasets like those currently produced are commonly considered intractable.  We address this problem with synergistic development of heuristics tree search strategies and parallel computing.Fil: Janies, D.. Ohio State University; Estados UnidosFil: Pol, Diego. Ohio State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    Burden of community-acquired and nosocomial rotavirus gastroenteritis in the pediatric population of Western Europe: a scoping review

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    <p>Abstract</p> <p>Background</p> <p>Rotavirus affects 95% of children worldwide by age 5 years and is the leading cause of severe dehydrating diarrhea. The objective of this review was to estimate the burden of rotavirus gastroenteritis (RVGE) in the Western European pediatric population.</p> <p>Methods</p> <p>A comprehensive literature search (1999-2010) was conducted in PubMed and other sources (CDC; WHO, others). Data on the epidemiology and burden of RVGE among children < 5 years-old in Western Europe --including hospital-acquired disease--were extracted.</p> <p>Results</p> <p>76 studies from 16 countries were identified. The mean percentage of acute gastroenteritis (AGE) cases caused by rotavirus ranged from 25.3%-63.5% in children < 5 years of age, peaking during winter. Incidence rates of RVGE ranged from 1.33-4.96 cases/100 person- years. Hospitalization rates for RVGE ranged from 7% to 81% among infected children, depending on the country. Nosocomial RVGE accounted for 47%-69% of all hospital-acquired AGE and prolonged hospital stays by 4-12 days. Each year, RVGE incurred 0.540.54- 53.6 million in direct medical costs and 1.71.7-22.4 million in indirect costs in the 16 countries studied. Full serotyping data was available for 8 countries. G1P[8], G2P[4], G9P[8], and G3P[8] were the most prevalent serotypes (cumulative frequency: 57.2%- 98.7%). Serotype distribution in nosocomial RVGE was similar.</p> <p>Conclusions</p> <p>This review confirms that RVGE is a common disease associated with significant morbidity and costs across Western Europe. A vaccine protecting against multiple serotypes may decrease the epidemiological and cost burden of RVGE in Western Europe.</p

    Cost-effectiveness of collaborative care for chronically ill patients with comorbid depressive disorder in the general hospital setting, a randomised controlled trial

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    Background. Depressive disorder is one of the most common disorders, and is highly prevalent in chronically ill patients. The presence of comorbid depression has a negative influence on quality of life, health care costs, self-care, morbidity, and mortality. Early diagnosis and well-organized treatment of depression has a positive influence on these aspects. Earlier research in the USA has reported good results with regard to the treatment of depression with a collaborative care approach and an antidepressant algorithm. In the UK 'Problem Solving Treatment' has proved to be feasible. However, in the general hospital setting this approach has not yet been evaluated. Methods/Design. CC: DIM (Collaborative Care: Depression Initiative in the Medical setting) is a two-armed randomised controlled trial with randomisation at patient level. The aim of the trial is to evaluate the treatment of depressive disorder in general hospitals in the Netherlands based on a collaborative care framework, including contracting, 'Problem Solving Treatment', antidepressant algorithm, and manual-guided self-help. 126 outpatients with diabetes mellitus, chronic obstructive pulmonary disease, or cardiovascular diseases will be randomised to either the intervention group or the control group. Patients will be included if they have been diagnosed with moderate to severe depression, based on the DSM-IV criteria in a two-step screening method. The intervention group will receive treatment based on the collaborative care approach; the control group will receive 'care as usual'. Baseline and follow-up measurements (after 3, 6, 9, and 12 months) will be performed by means of questionnaires. The primary outcome measure is severity of depressive symptoms, as measured with the PHQ-9. The secondary outcome measure is the cost-effectiveness of these treatments according to the TiC-P, the EuroQol and the SF-36. Discussion. Earlier research has indicated that depressive disorder is a chronic, mostly recurrent illness, which tends to cluster with physical comorbidity. Even though the treatment of depressive disorder based on the guidelines for depression is proven effective, these guidelines are often insufficiently adhered to. Collaborative care and 'Problem Solving Treatment' will be specifically tailored to patients with depressive disorders and evaluated in a general hospital setting in the Netherlands

    Measuring serotonin synthesis: from conventional methods to PET tracers and their (pre)clinical implications

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    The serotonergic system of the brain is complex, with an extensive innervation pattern covering all brain regions and endowed with at least 15 different receptors (each with their particular distribution patterns), specific reuptake mechanisms and synthetic processes. Many aspects of the functioning of the serotonergic system are still unclear, partially because of the difficulty of measuring physiological processes in the living brain. In this review we give an overview of the conventional methods of measuring serotonin synthesis and methods using positron emission tomography (PET) tracers, more specifically with respect to serotonergic function in affective disorders. Conventional methods are invasive and do not directly measure synthesis rates. Although they may give insight into turnover rates, a more direct measurement may be preferred. PET is a noninvasive technique which can trace metabolic processes, like serotonin synthesis. Tracers developed for this purpose are α-[11C]methyltryptophan ([11C]AMT) and 5-hydroxy-L-[β-11C]tryptophan ([11C]5-HTP). Both tracers have advantages and disadvantages. [11C]AMT can enter the kynurenine pathway under inflammatory conditions (and thus provide a false signal), but this tracer has been used in many studies leading to novel insights regarding antidepressant action. [11C]5-HTP is difficult to produce, but trapping of this compound may better represent serotonin synthesis. AMT and 5-HTP kinetics are differently affected by tryptophan depletion and changes of mood. This may indicate that both tracers are associated with different enzymatic processes. In conclusion, PET with radiolabelled substrates for the serotonergic pathway is the only direct way to detect changes of serotonin synthesis in the living brain
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