1,897 research outputs found

    The acute phase protein, haptoglobin : a potential parameter in welfare assessment?

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    Physiological parameters are important measures in animal welfare assessment. To assess the amount of stress an animal experiences, stress hormones like cortisol are frequently used. However, measuring cortisol has major disadvantages due to its rapid reactivity and decline and many influencing factors. Other potential alternative markers are acute phase proteins, since stress is known to affect the immune system. A pilot study was conducted to investigate the response of the acute phase protein, plasma haptoglobine (HP), in pigs subjected to a stressor (food deprivation) and to examine the correlation between HP levels and average daily growth (ADG). Forty grower pigs (25.1 ± 4.4 kg, mean ± SD) (sex and former pen mates balanced), were allocated to 4 conventional pens, 2 treatment (T) and 2 control (C) groups (10 pigs per pen). After 10 days of adaptation the experiment started and ran for 3 weeks. In the 2nd week, T groups were repeatedly subjected to an 8-hour food deprivation (day 1, 3, 5 and 7 of week 2), C groups had normal, unrestricted, access to food. Pigs were weighed twice a week and blood was collected once a week (every 5th day). Mean levels of plasma HP of C and T groups showed large variation between individuals (C groups, week 2: 1.84 ± 3.11 mg/ml; T groups, week 2: 1.40 ± 1.16 mg/ml). No significant differences (Kruskal-Wallis test) in HP levels or growth were found between the C and T groups or between the different weeks within the T groups. Significant negative weak to moderate correlations were found between ADG and HP levels (HP week 1 and ADG week 1: rs = -0.47, p=0.005; HP week 2 and ADG total; rs= -0.60, p=0.015; HP week 3 and ADG total: rs = -0.43, p=0.025; average HP total and ADG total: rs= -0.41, p=0.017). Large variations in HP levels between individuals were shown and no effect of treatment on HP levels or growth was found. Possibly, food deprivation had no apparent stress eliciting effect. Despite these results, interesting correlations between the level of HP and ADG were found, corroborating the inverse relationship between the acute phase response and growth. To further investigate the relation of the acute phase response and stress a successive experiment will be conducted in which we apply a stronger stressor (mixing pigs) and combine the physiological data with behavior

    Quantitative influence of non-hormonal blood factors on the control of sodium excretion by the isolated dog kidney

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    Quantitative influence of non-hormonal blood factors on the control of sodium excretion by the isolated dog kidney.On the basis of experiments performed on isolated dog kidneys, thus eliminating extrarenal hormonal controls, an attempt has been made to evaluate the influence of arterial blood pressure and several non-hormonal blood parameters on fractional sodium excretion.The roles of plasma protein concentration as modulated by filtration fraction, total renal plasma flow, hematocrit, arterial pressure and plasma potassium concentration on overall fractional sodium reabsorption have been evidenced and quantitatively evaluated.Although the control of sodium reabsorption by renal plasma flow and by hematocrit can be ascribed partly to changes in filtration fraction and post-glomerular plasma protein concentration, other mechanisms appear to be involved as well.Variations in filtration fraction and postglomerular plasma protein concentration play little, if any, role in the induction of pressure natriuresis.The autonomous and quantitative response of the kidney to blood dilution during saline diuresis represents the cumulative results, not only of the dilution of pre- and postglomerular plasma proteins, but also of the simultaneous decrease of hematocrit and increase of renal plasma flow.The implications of these results for the understanding of the adjustment of sodium balance in acute and chronic conditions are discussed

    Impact of provision of cardiovascular disease risk estimates to healthcare professionals and patients: a systematic review.

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    OBJECTIVE: To systematically review whether the provision of information on cardiovascular disease (CVD) risk to healthcare professionals and patients impacts their decision-making, behaviour and ultimately patient health. DESIGN: A systematic review. DATA SOURCES: An electronic literature search of MEDLINE and PubMed from 01/01/2004 to 01/06/2013 with no language restriction and manual screening of reference lists of systematic reviews on similar topics and all included papers. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: (1) Primary research published in a peer-reviewed journal; (2) inclusion of participants with no history of CVD; (3) intervention strategy consisted of provision of a CVD risk model estimate to either professionals or patients; and (4) the only difference between the intervention group and control group (or the only intervention in the case of before-after studies) was the provision of a CVD risk model estimate. RESULTS: After duplicates were removed, the initial electronic search identified 9671 papers. We screened 196 papers at title and abstract level and included 17 studies. The heterogeneity of the studies limited the analysis, but together they showed that provision of risk information to patients improved the accuracy of risk perception without decreasing quality of life or increasing anxiety, but had little effect on lifestyle. Providing risk information to physicians increased prescribing of lipid-lowering and blood pressure medication, with greatest effects in those with CVD risk >20% (relative risk for change in prescribing 2.13 (1.02 to 4.63) and 2.38 (1.11 to 5.10) respectively). Overall, there was a trend towards reductions in cholesterol and blood pressure and a statistically significant reduction in modelled CVD risk (-0.39% (-0.71 to -0.07)) after, on average, 12 months. CONCLUSIONS: There seems evidence that providing CVD risk model estimates to professionals and patients improves perceived CVD risk and medical prescribing, with little evidence of harm on psychological well-being.BS was supported by the European Commission Framework 7, EPIC-CVD: Individualised CVD risk assessment: tailoring targeted and cost-effective approaches to Europe's diverse populations, Grant agreement no: 279233. JUS was supported by a National Institute of Health Research (NIHR) Clinical Lectureship.This is the final version of the article. It first appeared from BMJ via http://dx.doi.org/10.1136/bmjopen-2015-00871

    Tailoring the Implementation of New Biomarkers Based on Their Added Predictive Value in Subgroups of Individuals

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    Background\ud The value of new biomarkers or imaging tests, when added to a prediction model, is currently evaluated using reclassification measures, such as the net reclassification improvement (NRI). However, these measures only provide an estimate of improved reclassification at population level. We present a straightforward approach to characterize subgroups of reclassified individuals in order to tailor implementation of a new prediction model to individuals expected to benefit from it.\ud \ud Methods\ud In a large Dutch population cohort (n = 21,992) we classified individuals to low (<5%) and high (≄5%) fatal cardiovascular disease risk by the Framingham risk score (FRS) and reclassified them based on the systematic coronary risk evaluation (SCORE). Subsequently, we characterized the reclassified individuals and, in case of heterogeneity, applied cluster analysis to identify and characterize subgroups. These characterizations were used to select individuals expected to benefit from implementation of SCORE.\ud \ud Results\ud Reclassification after applying SCORE in all individuals resulted in an NRI of 5.00% (95% CI [-0.53%; 11.50%]) within the events, 0.06% (95% CI [-0.08%; 0.22%]) within the nonevents, and a total NRI of 0.051 (95% CI [-0.004; 0.116]). Among the correctly downward reclassified individuals cluster analysis identified three subgroups. Using the characterizations of the typically correctly reclassified individuals, implementing SCORE only in individuals expected to benefit (n = 2,707,12.3%) improved the NRI to 5.32% (95% CI [-0.13%; 12.06%]) within the events, 0.24% (95% CI [0.10%; 0.36%]) within the nonevents, and a total NRI of 0.055 (95% CI [0.001; 0.123]). Overall, the risk levels for individuals reclassified by tailored implementation of SCORE were more accurate.\ud \ud Discussion\ud In our empirical example the presented approach successfully characterized subgroups of reclassified individuals that could be used to improve reclassification and reduce implementation burden. In particular when newly added biomarkers or imaging tests are costly or burdensome such a tailored implementation strategy may save resources and improve (cost-)effectivenes

    Intestinal fibrosis is reduced by early elimination of inflammation in a mouse model of IBD: Impact of a “Top‐Down” approach to intestinal fibrosis in mice

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    Background: The natural history of Crohn's disease follows a path of progression from an inflammatory to a fibrostenosing disease, with most patients requiring surgical resection of fibrotic strictures. Potent antiinflammatory therapies reduce inflammation but do not appear to alter the natural history of intestinal fibrosis. The aim of this study was to determine the relationship between intestinal inflammation and fibrogenesis and the impact of a very early “top‐down” interventional approach on fibrosis in vivo. Methods: In this study we removed the inflammatory stimulus from the Salmonella typhimurium mouse model of intestinal fibrosis by eradicating the S. typhimurium infection with levofloxacin at sequential timepoints during the infection. We evaluated the effect of this elimination of the inflammatory stimulus on the natural history of inflammation and fibrosis as determined by gross pathology, histopathology, mRNA expression, and protein expression. Results: Fibrogenesis is preceded by inflammation. Delayed eradication of the inflammatory stimulus by antibiotic treatment represses inflammation without preventing fibrosis. Early intervention significantly ameliorates but does not completely prevent subsequent fibrosis. Conclusions: This study demonstrates that intestinal fibrosis develops despite removal of an inflammatory stimulus and elimination of inflammation. Early intervention ameliorates but does not abolish subsequent fibrosis, suggesting that fibrosis, once initiated, is self‐propagating, suggesting that a very early top‐down interventional approach may have the most impact on fibrostenosing disease. (Inflamm Bowel Dis 2012;)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90367/1/21812_ftp.pd

    A hydroxypyrone-based inhibitor of metalloproteinase-12 displays neuroprotective properties in both status epilepticus and optic nerve crush animal models

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    Recently, we showed that matrix metalloproteinase-12 (MMP-12) is highly expressed in microglia and myeloid infiltrates, which are presumably involved in blood\u2013brain barrier (BBB) leakage and subsequent neuronal cell death that follows status epilepticus (SE). Here, we assessed the effects of a hydroxypyrone-based inhibitor selective for MMP-12 in the pilocarpine-induced SE rat model to determine hippocampal cell survival. In the hippocampus of rats treated with pilocarpine, intra-hippocampal injections of the MMP-12 inhibitor protected Cornu Ammonis 3 (CA3) and hilus of dentate gyrus neurons against cell death and limited the development of the ischemic-like lesion that typically develops in the CA3 stratum lacunosum-moleculare of the hippocampus. Furthermore, we showed that MMP-12 inhibition limited immunoglobulin G and albumin extravasation after SE, suggesting a reduction in BBB leakage. Finally, to rule out any possible involvement of seizure modulation in the neuroprotective effects of MMP-12 inhibition, neuroprotection was also observed in the retina of treated animals after optic nerve crush. Overall, these results support the hypothesis that MMP-12 inhibition can directly counteract neuronal cell death and that the specific hydroxypyrone-based inhibitor used in this study could be a potential therapeutic agent against neurological diseases/disorders characterized by an important inflammatory response and/or neuronal cell loss

    Prediction models for clustered data: comparison of a random intercept and standard regression model

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    BACKGROUND: When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. METHODS: Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. RESULTS: The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≄15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. CONCLUSION: The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters
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