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Poor Prediction (poor + prediction)
Selected AbstractsTayloring standard TDDFT approaches for computing UV/Vis transitions in thiocarbonyl chromophoresINTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 4 2008Julien Preat Abstract We report the development of an accurate computational procedure for the calculation of the n , ,* (,max,1) and , , ,* (,max,2) transitions of a set of thiocarbonyl derivatives. To ensure converged results, all calculations are carried out using the 6-311+G(2df,p) basis set for time-dependent calculations, and the 6-311G(2df,p) for the ground-state geometrical optimization. Starting with two hybrids, PBE0 and B3LYP, the Hartree,Fock exchange percentage (,) used is optimized in order to reach excitation energies that fit experimental data. It turns out that BLYP(,) is the more adequate functional for calibration. For the n , ,* excitation, the optimal , value lies in the 0.10,0.20 interval, whereas for the , , ,* process setting , equal to 0.10 provides the most accurate results. The corresponding mean absolute errors (MAE) are limited to 17 nm for ,max,1, and to 10 nm for ,max,2, allowing a consistent and accurate prediction of both transitions. We also assess the merits of the ZINDO//AM1 scheme and it turns out that the semi-empirical method only provides a poor prediction of the ,max of thiocarbonyl derivatives, especially for the n , ,* transition. © 2007 Wiley Periodicals, Inc. Int J Quantum Chem, 2008 [source] Do microsatellites reflect genome-wide genetic diversity in natural populations?MOLECULAR ECOLOGY, Issue 5 2010A comment on Väli et al. (2008) Abstract A recent study by Väli et al. (2008) highlights that microsatellites will often provide a poor prediction of the genome-wide nucleotide diversity of wild populations, but does not fully explain why. To clarify and stress the importance of identity disequilibrium and marker variability for correlations between multilocus heterozygosity and genome-wide genetic variability, we performed a simple simulation with different types of markers, corresponding to microsatellites and SNPs, in populations with different inbreeding history. The importance of identity disequilibrium was apparent for both markers and there was a clear impact of marker variability. [source] QT Interval Variability and Adaptation to Heart Rate Changes in Patients with Long QT SyndromePACING AND CLINICAL ELECTROPHYSIOLOGY, Issue 1 2009JAN N, MEC M.D. Background: Increased QT variability (QTV) has been reported in conditions associated with ventricular arrhythmias. Data on QTV in patients with congenital long QT syndrome (LQTS) are limited. Methods: Ambulatory electrocardiogram recordings were analyzed in 23 genotyped LQTS patients and in 16 healthy subjects (C). Short-term QTV was compared between C and LQTS. The dependence of QT duration on heart rate was evaluated with three different linear models, based either on the RR interval preceding the QT interval (RR0), the RR interval preceding RR0 (RR -1), or the average RR interval in the 60-second period before QT interval (mRR). Results: Short-term QTV was significantly higher in LQTS than in C subjects (14.94 ± 9.33 vs 7.31 ± 1.29 ms; P < 0.001). It was also higher in the non-LQT1 than in LQT1 patients (23.00 ± 9.05 vs 8.74 ± 1.56 ms; P < 0.001) and correlated positively with QTc in LQTS (r = 0.623, P < 0.002). In the C subjects, the linear model based on mRR predicted QT duration significantly better than models based on RR0 and RR -1. It also provided better fit than any nonlinear model based on RR0. This was also true for LQT1 patients. For non-LQT1 patients, all models provided poor prediction of QT interval. Conclusions: QTV is elevated in LQTS patients and is correlated with QTc in LQTS. Significant differences with respect to QTV exist among different genotypes. QT interval duration is strongly affected by noninstantaneous heart rate in both C and LQT1 subjects. These findings could improve formulas for QT interval correction and provide insight on cellular mechanisms of QT adaptation. [source] Paternity and social rank in wild chimpanzees (Pan troglodytes) from the Budongo Forest, UgandaAMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, Issue 3 2010Nicholas E. Newton-Fisher Abstract We analyzed patterns of paternity and male dominance rank in the Sonso community of wild East African chimpanzees (Pan troglodytes schweinfurthii) in the Budongo Forest, Uganda. Our major objective was to determine whether and how social rank influenced paternity success. We successfully genotyped 52 individuals at up to nine microsatellite loci, using DNA extracted from fecal samples. Of 24 offspring analyzed, we identified sires for 21. Paternity success was significantly correlated with social rank, with alpha males siring a disproportionate number of offspring. However, both middle- and low-ranking males also fathered offspring, and the priority-of-access model provided a relatively poor prediction of which males would be successful and under what circumstances. The concentration of paternities among only seven males and the tendency for high-ranking males to sire offspring of multiparous females suggest that both individual variation in male quality and the resource value of particular females may be mediating factors. In comparison with other chimpanzee studies, our results support the hypothesis that larger male cohort size reduces the ability of the alpha male to monopolize females, though within our study, male number did not affect the success of the alpha. Successful sires were not necessarily those who achieved the highest mating success with the females whose offspring they sired, but were those who demonstrated higher investment by spending significantly more time in association with these females. Finally, we estimate extra-group paternity at 0,5%, supporting other evidence that the community serves as the primary reproductive unit in chimpanzees. Am J Phys Anthropol 2010. © 2009 Wiley-Liss, Inc. [source] Nonparametric population modeling of valproate pharmacokinetics in epileptic patients using routine serum monitoring data: implications for dosageJOURNAL OF CLINICAL PHARMACY & THERAPEUTICS, Issue 2 2004I. B. Bondareva Summary Therapeutic drug monitoring (TDM) of valproate (VAL) is important in the optimization of its therapy. The aim of the present work was to evaluate the ability of TDM using model-based, goal-oriented Bayesian adaptive control for help in planning, monitoring, and adjusting individualized VAL dosing regimens. USC*PACK software and routine TDM data were used to estimate population and individual pharmacokinetics of two commercially available VAL formulations in epileptic adult and pediatric patients on chronic VAL monotherapy. The population parameter values found were in agreement with values reported earlier. A statistically significant (P < 0.001) difference in median values of the absorption rate constant was found between enteric-coated and sustained-release VAL formulations. In our patients (aged 0·25,53 years), VAL clearance declined with age until adult values were reached at about age 10. Because of the large interindividual variability in PK behavior, the median population parameter values gave poor predictions of the observed VAL serum concentrations. In contrast, the Bayesian individualized models gave good predictions for all subjects in all populations. The Bayesian posterior individualized PK models were based on the population models described here and where most patients had two (a peak and a trough) measured serum concentrations. Repeated consultations and adjusted dosage regimens with some patients allowed us to evaluate any possible influence of dose-dependent VAL clearance on the precision of total VAL concentration predictions based on TDM data and the proposed population models. These nonparametric expectation maximization (NPEM) population models thus provide a useful tool for planning an initial dosage regimen of VAL to achieve desired target peak and trough serum concentration goals, coupled with TDM soon thereafter, as a peak,trough pair of serum concentrations, and Bayesian fitting to individualize the PK model for each patient. The nonparametric PK parameter distributions in these NPEM population models also permit their use by the new method of ,multiple model' dosage design, which allows the target goals to be achieved specifically with maximum precision. Software for both types of Bayesian adaptive control is now available to employ these population models in clinical practice. [source] Prediction of human pharmacokinetics , renal metabolic and excretion clearanceJOURNAL OF PHARMACY AND PHARMACOLOGY: AN INTERNATI ONAL JOURNAL OF PHARMACEUTICAL SCIENCE, Issue 11 2007Urban Fagerholm The kidneys have the capability to both excrete and metabolise drugs. An understanding of mechanisms that determine these processes is required for the prediction of pharmacokinetics, exposures, doses and interactions of candidate drugs. This is particularly important for compounds predicted to have low or negligible non-renal clearance (CL). Clinically significant interactions in drug transport occur mostly in the kidneys. The main objective was to evaluate methods for prediction of excretion and metabolic renal CL (CLR) in humans. CLR is difficult to predict because of the involvement of bi-directional passive and active tubular transport, differences in uptake capacity, pH and residence time on luminal and blood sides of tubular cells, and limited knowledge about regional tubular residence time, permeability (Pe) and metabolic capacity. Allometry provides poor predictions of excretion CLR because of species differences in unbound fraction, urine pH and active transport. The correlation between fraction excreted unchanged in urine (fe) in humans and animals is also poor, except for compounds with high passive Pe (extensive/complete tubular reabsorption; zero/negligible fe) and/or high non-renal CL. Physiologically based in-vitro/in-vivo methods could potentially be useful for predicting CLR. Filtration could easily be predicted. Prediction of tubular secretion CL requires an in-vitro transport model and establishment of an in-vitro/in-vivo relationship, and does not appear to have been attempted. The relationship between passive Pe and tubular fraction reabsorbed (freabs) for compounds with and without apparent secretion has recently been established and useful equations and limits for prediction were developed. The suggestion that reabsorption has a lipophilicity cut-off does not seem to hold. Instead, compounds with passive Pe that is less than or equal to that of atenolol are expected to have negligible passive freabs. Compounds with passive Pe that is equal to or higher than that of carbamazepine are expected to have complete freabs. For compounds with intermediate Pe the relationship is irregular and freabs is difficult to predict. Tubular cells are comparably impermeable (for passive diffusion), and show regional differences in enzymatic and transporter activities. This limits the usefulness of microsome data and makes microsome-based predictions of metabolic CLR questionable. Renal concentrations and activities of CYP450s are comparably low, suggesting that CYP450 substrates have negligible metabolic CLR. The metabolic CLR of high-Pe UDP-glucuronyltransferase substrates could contribute to the total CL. [source] | |||||||||||||