935 resultados para Mercury concentrations


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AIM: Total imatinib concentrations are currently measured for the therapeutic drug monitoring of imatinib, whereas only free drug equilibrates with cells for pharmacological action. Due to technical and cost limitations, routine measurement of free concentrations is generally not performed. In this study, free and total imatinib concentrations were measured to establish a model allowing the confident prediction of imatinib free concentrations based on total concentrations and plasma proteins measurements. METHODS: One hundred and fifty total and free plasma concentrations of imatinib were measured in 49 patients with gastrointestinal stromal tumours. A population pharmacokinetic model was built up to characterize mean total and free concentrations with inter-patient and intrapatient variability, while taking into account α1 -acid glycoprotein (AGP) and human serum albumin (HSA) concentrations, in addition to other demographic and environmental covariates. RESULTS: A one compartment model with first order absorption was used to characterize total and free imatinib concentrations. Only AGP influenced imatinib total clearance. Imatinib free concentrations were best predicted using a non-linear binding model to AGP, with a dissociation constant Kd of 319 ng ml(-1) , assuming a 1:1 molar binding ratio. The addition of HSA in the equation did not improve the prediction of imatinib unbound concentrations. CONCLUSION: Although free concentration monitoring is probably more appropriate than total concentrations, it requires an additional ultrafiltration step and sensitive analytical technology, not always available in clinical laboratories. The model proposed might represent a convenient approach to estimate imatinib free concentrations. However, therapeutic ranges for free imatinib concentrations remain to be established before it enters into routine practice.

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BACKGROUND: PCSK9 (Proprotein Convertase Subtilisin Kexin type 9) is a circulating protein that promotes hypercholesterolemia by decreasing hepatic LDL receptor protein. Under non interventional conditions, its expression is driven by sterol response element binding protein 2 (SREBP2) and follows a diurnal rhythm synchronous with cholesterol synthesis. Plasma PCSK9 is associated to LDL-C and to a lesser extent plasma triglycerides and insulin resistance. We aimed to verify the effect on plasma PCSK9 concentrations of dietary interventions that affect these parameters. METHODS: We performed nutritional interventions in young healthy male volunteers and offspring of type 2 diabetic (OffT2D) patients that are more prone to develop insulin resistance, including: i) acute post-prandial hyperlipidemic challenge (n=10), ii) 4 days of high-fat (HF) or high-fat/high-protein (HFHP) (n=10), iii) 7 (HFruc1, n=16) or 6 (HFruc2, n=9) days of hypercaloric high-fructose diets. An acute oral fat load was also performed in two patients bearing the R104C-V114A loss-of-function (LOF) PCSK9 mutation. Plasma PCSK9 concentrations were measured by ELISA. For the HFruc1 study, intrahepatocellular (IHCL) and intramyocellular lipids were measured by 1H magnetic resonance spectroscopy. Hepatic and whole-body insulin sensitivity was assessed with a two-step hyperinsulinemic-euglycemic clamp (0.3 and 1.0 mU.kg-1.min-1). FINDINGS: HF and HFHP short-term diets, as well as an acute hyperlipidemic oral load, did not significantly change PCSK9 concentrations. In addition, post-prandial plasma triglyceride excursion was not altered in two carriers of PCSK9 LOF mutation compared with non carriers. In contrast, hypercaloric 7-day HFruc1 diet increased plasma PCSK9 concentrations by 28% (p=0.05) in healthy volunteers and by 34% (p=0.001) in OffT2D patients. In another independent study, 6-day HFruc2 diet increased plasma PCSK9 levels by 93% (p<0.0001) in young healthy male volunteers. Spearman's correlations revealed that plasma PCSK9 concentrations upon 7-day HFruc1 diet were positively associated with plasma triglycerides (r=0.54, p=0.01) and IHCL (r=0.56, p=0.001), and inversely correlated with hepatic (r=0.54, p=0.014) and whole-body (r=-0.59, p=0.0065) insulin sensitivity. CONCLUSIONS: Plasma PCSK9 concentrations vary minimally in response to a short term high-fat diet and they are not accompanied with changes in cholesterolemia upon high-fructose diet. Short-term high-fructose intake increased plasma PCSK9 levels, independent on cholesterol synthesis, suggesting a regulation independent of SREBP-2. Upon this diet, PCSK9 is associated with insulin resistance, hepatic steatosis and plasma triglycerides.

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BACKGROUND: Metals are known endocrine disruptors and have been linked to cardiometabolic diseases via multiple potential mechanisms, yet few human studies have both the exposure variability and biologically-relevant phenotype data available. We sought to examine the distribution of metals exposure and potential associations with cardiometabolic risk factors in the "Modeling the Epidemiologic Transition Study" (METS), a prospective cohort study designed to assess energy balance and change in body weight, diabetes and cardiovascular disease risk in five countries at different stages of social and economic development. METHODS: Young adults (25-45 years) of African descent were enrolled (N = 500 from each site) in: Ghana, South Africa, Seychelles, Jamaica and the U.S.A. We randomly selected 150 blood samples (N = 30 from each site) to determine concentrations of selected metals (arsenic, cadmium, lead, mercury) in a subset of participants at baseline and to examine associations with cardiometabolic risk factors. RESULTS: Median (interquartile range) metal concentrations (μg/L) were: arsenic 8.5 (7.7); cadmium 0.01 (0.8); lead 16.6 (16.1); and mercury 1.5 (5.0). There were significant differences in metals concentrations by: site location, paid employment status, education, marital status, smoking, alcohol use, and fish intake. After adjusting for these covariates plus age and sex, arsenic (OR 4.1, 95% C.I. 1.2, 14.6) and lead (OR 4.0, 95% C.I. 1.6, 9.6) above the median values were significantly associated with elevated fasting glucose. These associations increased when models were further adjusted for percent body fat: arsenic (OR 5.6, 95% C.I. 1.5, 21.2) and lead (OR 5.0, 95% C.I. 2.0, 12.7). Cadmium and mercury were also related with increased odds of elevated fasting glucose, but the associations were not statistically significant. Arsenic was significantly associated with increased odds of low HDL cholesterol both with (OR 8.0, 95% C.I. 1.8, 35.0) and without (OR 5.9, 95% C.I. 1.5, 23.1) adjustment for percent body fat. CONCLUSIONS: While not consistent for all cardiometabolic disease markers, these results are suggestive of potentially important associations between metals exposure and cardiometabolic risk. Future studies will examine these associations in the larger cohort over time.

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Since it is established that human chorionic gonadotropin (hCG) affects testosterone production and release in the human body, the use of this hormone as a performance enhancing drug has been prohibited by the World Anti-Doping Agency. Nowadays, the only validated biomarker of a hCG doping is its direct quantification in urine. However, this specific parameter is subjected to large inter-individual variability and its determination is directly dependent on the reliability of hCG immunoassays used. In order to counteract these weaknesses, new biomarkers need to be evidenced. To address this issue, a pilot clinical study was performed on 10 volunteers submitted to 3 subsequent hCG injections. Blood and urine samples were collected during two weeks in order to follow the physiological effects on related compounds such as the steroid profile or hormones involved in the hypothalamo-pituitary axis. The hCG pharmacokinetic observed in all subjects was, as expected, prone to important inter-individual variations. Using ROC plots, level of testosterone and testosterone on luteinizing hormone ratio in both blood and urine were found to be the most relevant biomarker of a hCG abuse, regardless of inter-individual variations. In conclusion, this study showed the crucial importance of reliable quantification methods to assess low differences in hormonal patterns. In regard to these results and to anti-doping requirements and constraints, blood together with urine matrix should be included in the anti-doping testing program. Together with a longitudinal follow-up approach it could constitute a new strategy to detect a hCG abuse, applicable to further forms of steroid or other forbidden drug manipulation.

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On three occasions, unusually high trough plasma concentrations of venlafaxine were measured in a patient phenotyped and genotyped as being an extensive CYP2D6 metabolizer and receiving 450 mg/day of venlafaxine and multiple comedications. Values of 1.54 and of 0.60 mg/l of venlafaxine and O-desmethylvenlafaxine, respectively, were determined in the first blood sample, giving an unusually high venlafaxine to O-desmethylvenlafaxine ratio. This suggests an impaired metabolism of venlafaxine to O-desmethylvenlafaxine, and is most likely due to metabolic interactions with mianserin (240 mg/day) and propranolol (40 mg/day). Concentration of (S)-venlafaxine measured in this blood sample was almost twice as high as (R)-venlafaxine ((S)/(R) ratio: 1.94). At the second blood sampling, after addition of thioridazine (260 mg/day), which is a strong CYP2D6 inhibitor, concentrations of venlafaxine were further increased (2.76 mg/l), and concentrations of O-desmethylvenlafaxine decreased (0.22 mg/l). A decrease of the (S)/(R)-venlafaxine ratio (-20%) suggests a possible stereoselectivity towards the (R)-enantiomer of the enzyme(s) involved in venlafaxine O-demethylation at these high venlafaxine concentrations. At the third blood sampling, after interruption of thioridazine, concentrations of venlafaxine and O-desmethylvenlafaxine were similar to those measured in the first blood sample. This case report shows the importance of performing studies on the effects of either genetically determined or acquired deficiency of metabolism on the kinetics of venlafaxine.

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Methadone is a 50:50 mixture of two enantiomers and (R)-methadone accounts for the majority of its opioid effect. The aim of this study was to determine whether a blood concentration of (R)-methadone can be associated with therapeutic response in addict patients in methadone maintenance treatment. Trough plasma concentrations of (R)-, (S)- and (R,S)-methadone were measured in 180 patients in maintenance treatment. Therapeutic response was defined by the absence of illicit opiate or cocaine in urine samples collected during a 2-month period prior to blood sampling. A large interindividual variability of (R)-methadone concentration-to-dose-to-weight ratios was found (mean, S.D., median, range: 112, 54, 100, 19-316 ng x kg/ml x mg). With regard to the consumption of illicit opiate (but not of cocaine), a therapeutic response was associated with (R)- (at 250 ng/ml) and (R,S)-methadone (at 400 ng/ml) but not with (S)-methadone concentrations. A higher specificity was calculated for (R)- than for (R,S)-methadone, as the number of non-responders above this threshold divided by the total number of non-responders was higher for (R,S)-methadone (19%) than for (R)-methadone (7%). The results support the use of therapeutic drug monitoring of (R)-methadone in cases of continued intake of illicit opiates. Due to the variability of methadone concentration-to-dose-to-weight ratios, theoretical doses of racemic methadone could be as small as 55 mg/day and as large as 921 mg/day to produce a plasma (R)-methadone concentration of 250 ng/ml in a 70-kg patient. This demonstrates the importance of individualizing methadone treatment.

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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

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AB Summary: Steady state concentrations of (S)- and (R)-mianserin and desmethylmianserin were measured in 21 homozygous extensive metabolizers (as determined by genotyping for mutations 3 [or A] and 4 [or B]), in seven heterozygous extensive metabolizers and in one poor metabolizer of debrisoquine, as well as in one patient receiving very high doses of mianserin (360 mg/day) and fluoxetine (160 mg/day), a strong cytochrome P450IID6 inhibitor. The mean dose of mianserin was (mean +/- SD, range: 67 +/- 63, 10 to 360 mg/day). High dispersions of the (S)/(R)-mianserin and desmethylmianserin ratios were observed (mean +/- SD, range: 2.10+/- 1.01, 0.64 to 4.76, and 0.29 +/- 0.14, 0.08 to 0.57, respectively). The highest (S)/(R)-mianserin ratio was calculated for the poor metabolizer (4.76) agreeing with those results of a single-dose study with poor and extensive metabolizers of debrisoquine, in that the cytochrome P450IID6 is probably involved in the metabolism of mianserin with an enantioselectivity for the (S)-enantiomer. Nevertheless, the mean concentration-to-dose ratios for (S)- or (R)-mianserin or desmethylmianserin were not significantly different between homozygous and heterozygous extensive metabolizers, and no particular values were measured in the poor metabolizer nor in the patient receiving fluoxetine. Furthermore, the(S)/(R)-mianserin ratio measured in the PM was only slightly higher than the second highest ratio (3.85) of an homozygous extensive metabolizer, whereas no particular value (2.92) was calculated for the patient taking fluoxetine. Finally, no significant differences in (S)/(R)-mianserin or(S)/(R)-desmethylmianserin were calculated between homozygous and heterozygous extensive metabolizers. Although the number of patients included in this study is too low to allow definite conclusions, the results suggest that the debrisoquine genotype has only a moderate influence on the steady state concentrations of the enantiomers of mianserin and desmethylmianserin. (C) Lippincott-Raven Publishers

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Plasma imipenem concentrations were measured in 19 critically ill children (median age, 0.8 year; range, 0.02 to 12.9 years). Wide interindividual variations (2 to 4x at peak and >10x at trough concentrations) resulted in unpredictable plasma levels in several children. To avoid subtherapeutic drug levels, we recommend treatment with at least 100 mg/kg of body weight/day of imipenem-cilastatin for critically ill children requiring such therapy.

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AIM: Genetic polymorphisms of the human angiotensinogen gene are frequent and may induce up to 30% increase of plasma angiotensinogen concentrations with a blood pressure increase of up to 5mmHg. Their role for the pathogenesis of human arterial hypertension remains unclear. High plasma angiotensinogen levels could increase the sensitivity to other blood pressure stressors. METHODS: Male transgenic rats with a 9-fold increase of plasma angiotensinogen concentrations and male non-transgenic rats aged 10 weeks were treated or not with NG-Nitro-L-arginine-methyl ester for 3 weeks in their drinking water (n=3/group). Systolic blood pressure and body weight were measured at baseline and at the end of the study when left ventricular weight and ventricular expression of angiotensin I-converting enzyme and procollagen Iα1 were determined (polymerase chain reaction). RESULTS: At baseline, transgenic rats had +18mmHg higher bood pressure and -8% lower body weight compared to non-transgenic rats (P<0.05) without significant changes for the vehicle groups throughout the study (P>0.05). NG-Nitro-L-arginine-methyl ester increased blood pressure, left ventricular weight and left ventricular weight indexed for body weight by +41%, +17.6% and +18.6% (P<0.05) in transgenic and +25%, +5.3% and +6.7% (P>0.05) in non-transgenic rats compared to untreated animals, respectively. Cardiac gene expression showed no differences between groups (P>0.05). CONCLUSION: Increased plasma angiotensinogen levels may sensitize to additional blood pressure stressors. Our preliminary results point towards an independent role of angiotensinogen in the pathogenesis of human hypertension and associated end-organ damage.

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BACKGROUND: The strong observational association between total homocysteine (tHcy) concentrations and risk of coronary artery disease (CAD) and the null associations in the homocysteine-lowering trials have prompted the need to identify genetic variants associated with homocysteine concentrations and risk of CAD. OBJECTIVE: We tested whether common genetic polymorphisms associated with variation in tHcy are also associated with CAD. DESIGN: We conducted a meta-analysis of genome-wide association studies (GWAS) on tHcy concentrations in 44,147 individuals of European descent. Polymorphisms associated with tHcy (P < 10(-8)) were tested for association with CAD in 31,400 cases and 92,927 controls. RESULTS: Common variants at 13 loci, explaining 5.9% of the variation in tHcy, were associated with tHcy concentrations, including 6 novel loci in or near MMACHC (2.1 Ã- 10(-9)), SLC17A3 (1.0 Ã- 10(-8)), GTPB10 (1.7 Ã- 10(-8)), CUBN (7.5 Ã- 10(-10)), HNF1A (1.2 Ã- 10(-12)), and FUT2 (6.6 Ã- 10(-9)), and variants previously reported at or near the MTHFR, MTR, CPS1, MUT, NOX4, DPEP1, and CBS genes. Individuals within the highest 10% of the genotype risk score (GRS) had 3-μmol/L higher mean tHcy concentrations than did those within the lowest 10% of the GRS (P = 1 Ã- 10(-36)). The GRS was not associated with risk of CAD (OR: 1.01; 95% CI: 0.98, 1.04; P = 0.49). CONCLUSIONS: We identified several novel loci that influence plasma tHcy concentrations. Overall, common genetic variants that influence plasma tHcy concentrations are not associated with risk of CAD in white populations, which further refutes the causal relevance of moderately elevated tHcy concentrations and tHcy-related pathways for CAD.