68 research outputs found

    The relation between anger coping strategies, anger mood and somatic complaints in children and adolescents

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    Attempts to explain the experience of somatic complaints among children and adolescents suggest that they may in part result from the influence of particular strategies for coping with anger on the longevity of negative emotions. To explore these relationships British (n = 393) and Dutch (n = 299) children completed a modified version of the Behavioral Anger Response Questionnaire (BARQ), and two additional questionnaires assessing anger mood and somatic complaints. A hierarchical regression analysis showed that for both the UK and Dutch samples two coping styles, Social support-seeking and Rumination, made a significant contribution to somatic complaints, over and above the variance explained by anger mood. A tendency to repeatedly think or talk about an angering event as a way of coping seems to underlie the observed negative health effects. In addition, tentative support is given for a broader range of strategies to cope with anger than just the traditionally studied anger-out and anger-in styles. © 2007 Springer Science+Business Media, LLC

    Mathematical Modelling as a Proof of Concept for MPNs as a Human Inflammation Model for Cancer Development

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    <p><b>Left:</b> Typical development in stem cells (top panel A) and mature cells (bottom panel B). Healthy hematopoietic cells (full blue curves) dominate in the early phase where the number of malignant cells (stipulated red curves) are few. The total number of cells is also shown (dotted green curves). When a stem cell mutates without repairing mechanisms, a slowly increasing exponential growth starts. At a certain stage, the malignant cells become dominant, and the healthy hematopoietic cells begin to show a visible decline. Finally, the composition between the cell types results in a takeover by the malignant cells, leading to an exponential decline in hematopoietic cells and ultimately their extinction. The development is driven by an approximately exponential increase in the MPN stem cells, and the development is closely followed by the mature MPN cells. <b>Right:</b> B)The corresponding allele burden (7%, 33% and 67% corresponding to ET, PV, and PMF, respectively) defined as the ratio of MPN mature cells to the total number of mature cells.</p

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

    Identifying the RNA Kinetic Traps in Ribosome Assembly

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    Dbpa Is A Region-Specific Rna Helicase

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    DbpA is a DEAD-box RNA helicase implicated in RNA structural rearrangements in the peptidyl transferase center. DbpA contains an RNA binding domain, responsible for tight binding of DbpA to hairpin 92 of 23S ribosomal RNA, and a RecA-like catalytic core responsible for double-helix unwinding. It is not known if DbpA unwinds only the RNA helices that are part of a specific RNA structure, or if DbpA unwinds any RNA helices within the catalytic core\u27s grasp. In other words, it is not known if DbpA is a site-specific enzyme or region-specific enzyme. In this study, we used protein and RNA engineering to investigate if DbpA is a region-specific or a site-specific enzyme. Our data suggest that DbpA is a region-specific enzyme. This conclusion has an important implication for the physiological role of DbpA. It suggests that during ribosome assembly, DbpA could bind with its C-terminal RNA binding domain to hairpin 92, while its catalytic core may unwind any double-helices in its vicinity. The only requirement for a double-helix to serve as a DbpA substrate is for the double-helix to be positioned within the catalytic core\u27s grasp

    The Dbpa Catalytic Core Unwinds Double-Helix Substrates By Directly Loading On Them

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    DbpA is a DEAD-box RNA helicase implicated in the assembly of the large ribosomal subunit. Similar to all the members of the DEAD-box family, the DbpA protein has two N-terminal RecA-like domains, which perform the RNA unwinding. However, unlike other members of this family, the DbpA protein also possesses a structured C-terminal RNA-binding domain that mediates specific tethering of DbpA to hairpin 92 of the Escherichia coli 23S ribosomal RNA. Previous studies using model RNA molecules containing hairpin 92 show that the RNA molecules support the DbpA protein\u27s double-helix unwinding activity, provided that the double helix has a 3\u27 single-stranded region. The 3\u27 single-stranded region was suggested to be the start site of the DbpA protein\u27s catalytic unwinding activity. The data presented here demonstrate that the single-stranded region 3\u27 of the doublehelix substrate is not required for the DbpA protein\u27s unwinding activity and the DbpA protein unwinds the double-helix substrates by directly loading on them

    The DbpA catalytic core unwinds double-helix substrates by directly loading on them

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    DbpA is a DEAD-box RNA helicase implicated in the assembly of the large ribosomal subunit. Similar to all the members of the DEAD-box family, the DbpA protein has two N-terminal RecA-like domains, which perform the RNA unwinding. However, unlike other members of this family, the DbpA protein also possesses a structured C-terminal RNA-binding domain that mediates specific tethering of DbpA to hairpin 92 of the Escherichia coli 23S ribosomal RNA. Previous studies using model RNA molecules containing hairpin 92 show that the RNA molecules support the DbpA protein's double-helix unwinding activity, provided that the double helix has a 3′ single-stranded region. The 3′ single-stranded region was suggested to be the start site of the DbpA protein's catalytic unwinding activity. The data presented here demonstrate that the single-stranded region 3′ of the double-helix substrate is not required for the DbpA protein's unwinding activity and the DbpA protein unwinds the double-helix substrates by directly loading on them

    Time Course Of Large Ribosomal Subunit Assembly In E. Coli Cells Overexpressing A Helicase Inactive Dbpa Protein

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    DbpA is a DEAD-box RNA helicase implicated in Escherichia coli large ribosomal subunit assembly. Previous studies have shown that when the ATPase and helicase inactive DbpA construct, R331A, is expressed in E. coli cells, a large ribosomal subunit intermediate accumulates. The large subunit intermediate migrates as a 45S particle in a sucrose gradient. Here, using a number of structural and fluorescent assays, we investigate the ribosome profiles of cells lacking wild-type DbpA and overexpressing the R331A DbpA construct. Our data show that in addition to the 45S particle previously described, 27S and 35S particles are also present in the ribosome profiles of cells overexpressing R331A DbpA. The 27S, 35S, and 45S independently convert to the 50S subunit, suggesting that ribosome assembly in the presence of R331A and the absence of wild-type DbpA occurs via multiple pathways

    The blending strategy for the plutonium immobilization program

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    The Department of Energy (DOE) has declared approximately 38.2 tonnes of weapons-grade plutonium to be excess to the needs of national security, 14.3 tonnes of fuel- and reactor-grade plutonium excess to DOE needs, and anticipates an additional 7 tonnes to be declared excess to national security needs. Of this 59.5 tonnes, DOE anticipates that {approximately} 7.5 tonnes will be dispositioned as spent fuel at the Geologic Repository and {approximately} 2 tonnes will be declared below the safeguards termination limit and be discard3ed as TRU waste at WIPP. The remaining 50 tonnes of excess plutonium exists in many forms and locations around the country, and is under the control of several DOE offices. In addition to the plutonium, the feed stock also contains about 17 tonnes of depleted uranium, about 600 kg of highly enriched uranium, and many kilograms of neptunium and thorium and about 8 to 10 tonnes of tramp impurities. The Materials Disposition Program (MD) will be received materials packaged by these other Programs to disposition in a manor that meets the spent fuel standard. To minimize the cost of characterization of the feedstock and to minimize purification processes, a blending strategy will be followed. The levelization of the impurities, the plutonium isotopics, and the actinide impurities will also provide some benefits in the area of proliferation resistance. The overall strategy will be outlined and the benefits of following a blending instead of a purification program will be discussed

    Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families

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    Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH− cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction.<br/
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