940 resultados para genotypic variance


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OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

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In Malani and Neilsen (1992) we have proposed alternative estimates of survival function (for time to disease) using a simple marker that describes time to some intermediate stage in a disease process. In this paper we derive the asymptotic variance of one such proposed estimator using two different methods and compare terms of order 1/n when there is no censoring. In the absence of censoring the asymptotic variance obtained using the Greenwood type approach converges to exact variance up to terms involving 1/n. But the asymptotic variance obtained using the theory of the counting process and results from Voelkel and Crowley (1984) on semi-Markov processes has a different term of order 1/n. It is not clear to us at this point why the variance formulae using the latter approach give different results.

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Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

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Resistance of trypanosomes to melarsoprol is ascribed to reduced uptake of the drug via the P2 nucleoside transporter. The aim of this study was to look for evidence of drug resistance in Trypanosoma brucei gambiense isolates from sleeping sickness patients in Ibba, South Sudan, an area of high melarsoprol failure rate. Eighteen T. b. gambiense stocks were phenotypically and only 10 strains genotypically characterized. In vitro, all isolates were sensitive to melarsoprol, melarsen oxide, and diminazene. Infected mice were cured with a 4 day treatment of 2.5mg/kg bwt melarsoprol, confirming that the isolates were sensitive. The gene that codes for the P2 transporter, TbATI, was amplified by PCR and sequenced. The sequences were almost identical to the TbAT1(sensitive) reference, except for one point mutation, C1384T resulting in the amino acid change proline-462 to serine. None of the described TbAT1(resistant)-type mutations were detected. In a T. b. gambiense sleeping sickness focus where melarsoprol had to be abandoned due to the high incidence of treatment failures, no evidence for drug resistant trypanosomes or for TbAT1(resistant)-type alleles of the P2 transporter could be found. These findings indicate that factors other than drug resistance contribute to melarsoprol treatment failures.

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BACKGROUND: The development of arsenical and diamidine resistance in Trypanosoma brucei is associated with loss of drug uptake by the P2 purine transporter as a result of alterations in the corresponding T. brucei adenosine transporter 1 gene (TbAT1). Previously, specific TbAT1 mutant type alleles linked to melarsoprol treatment failure were significantly more prevalent in T. b. gambiense from relapse patients at Omugo health centre in Arua district. Relapse rates of up to 30% prompted a shift from melarsoprol to eflornithine (alpha-difluoromethylornithine, DFMO) as first-line treatment at this centre. The aim of this study was to determine the status of TbAT1 in recent isolates collected from T. b. gambiense sleeping sickness patients from Arua and Moyo districts in Northwestern Uganda after this shift in first-line drug choice. METHODOLOGY AND RESULTS: Blood and cerebrospinal fluids of consenting patients were collected for DNA preparation and subsequent amplification. All of the 105 isolates from Omugo that we successfully analysed by PCR-RFLP possessed the TbAT1 wild type allele. In addition, PCR/RFLP analysis was performed for 74 samples from Moyo, where melarsoprol is still the first line drug; 61 samples displayed the wild genotype while six were mutant and seven had a mixed pattern of both mutant and wild-type TbAT1. The melarsoprol treatment failure rate at Moyo over the same period was nine out of 101 stage II cases that were followed up at least once. Five of the relapse cases harboured mutant TbAT1, one had the wild type, while no amplification was achieved from the remaining three samples. CONCLUSIONS/SIGNIFICANCE: The apparent disappearance of mutant alleles at Omugo may correlate with melarsoprol withdrawal as first-line treatment. Our results suggest that melarsoprol could successfully be reintroduced following a time lag subsequent to its replacement. A field-applicable test to predict melarsoprol treatment outcome and identify patients for whom the drug can still be beneficial is clearly required. This will facilitate cost-effective management of HAT in rural resource-poor settings, given that eflornithine has a much higher logistical requirement for its application.

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Identifying and comparing different steady states is an important task for clinical decision making. Data from unequal sources, comprising diverse patient status information, have to be interpreted. In order to compare results an expressive representation is the key. In this contribution we suggest a criterion to calculate a context-sensitive value based on variance analysis and discuss its advantages and limitations referring to a clinical data example obtained during anesthesia. Different drug plasma target levels of the anesthetic propofol were preset to reach and maintain clinically desirable steady state conditions with target controlled infusion (TCI). At the same time systolic blood pressure was monitored, depth of anesthesia was recorded using the bispectral index (BIS) and propofol plasma concentrations were determined in venous blood samples. The presented analysis of variance (ANOVA) is used to quantify how accurately steady states can be monitored and compared using the three methods of measurement.

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Localized Magnetic Resonance Spectroscopy (MRS) is in widespread use for clinical brain research. Standard acquisition sequences to obtain one-dimensional spectra suffer from substantial overlap of spectral contributions from many metabolites. Therefore, specially tuned editing sequences or two-dimensional acquisition schemes are applied to extend the information content. Tuning specific acquisition parameters allows to make the sequences more efficient or more specific for certain target metabolites. Cramér-Rao bounds have been used in other fields for optimization of experiments and are now shown to be very useful as design criteria for localized MRS sequence optimization. The principle is illustrated for one- and two-dimensional MRS, in particular the 2D separation experiment, where the usual restriction to equidistant echo time spacings and equal acquisition times per echo time can be abolished. Particular emphasis is placed on optimizing experiments for quantification of GABA and glutamate. The basic principles are verified by Monte Carlo simulations and in vivo for repeated acquisitions of generalized two-dimensional separation brain spectra obtained from healthy subjects and expanded by bootstrapping for better definition of the quantification uncertainties.

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Previous research suggests that the personality of a relationship partner predicts not only the individual’s own satisfaction with the relationship but also the partner’s satisfaction. Based on the actor–partner interdependence model, the present research tested whether actor and partner effects of personality are biased when the same method (e.g., self-report) is used for the assessment of personality and relationship satisfaction and, consequently, shared method variance is not controlled for. Data came from 186 couples, of whom both partners provided self- and partner reports on the Big Five personality traits. Depending on the research design, actor effects were larger than partner effects (when using only self-reports), smaller than partner effects (when using only partner reports), or of about the same size as partner effects (when using self- and partner reports). The findings attest to the importance of controlling for shared method variance in dyadic data analysis.

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BACKGROUND Streptococcus spp. and other Gram-positive, catalase-negative cocci (PNC) form a large group of microorganisms which can be found in the milk of cows with intramammary infection. The most frequently observed PNC mastitis pathogens (major pathogens) are Streptococcus uberis, Strep. dysgalactiae, and Strep. agalactiae. The remaining PNC include a few minor pathogens and a large nonpathogenic group. Improved methods are needed for the accurate identification and differentiation of PNC. A total of 151 PNC were collected from cows with intramammary infection and conclusively identified by 16S rRNA sequencing as reference method. Nine phenotypic microbiological tests (alpha-hemolysis, CAMP reaction, esculin hydrolysis, growth on kanamycin esculin azide agar and on sodium chloride agar, inulin fermentation, hippurate hydrolysis, leucine aminopeptidase and pyrrolidonyl peptidase activity), multiplex PCR for the three major pathogens (target genes for Strep. uberis, Strep. dysgalactiae and Strep. agalactiae: pauA, 16S rRNA, and sklA3, respectively), and mass spectroscopy using the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF MS) were evaluated for the diagnosis and discrimination of the three clinically most relevant PNC. RESULTS The probability that a strain of Strep. uberis, Strep. dysgalactiae and Strep. agalactiae was correctly identified by combining the results of the 9 phenotypic tests was 92%, 90%, and 100%, respectively. Applying the multiplex PCR, all strains of the three major pathogens were correctly identified and no false positive results occurred. Correct identification was observed for all strains of Strep. uberis and Strep. agalactiae using MALDI-TOF MS. In the case of Strep. dysgalactiae, some variability was observed at the subspecies level, but all strains were allocated to one single cluster. CONCLUSIONS The results of the present study show that reliable identification of the clinically most relevant PNC (Strep. uberis, Strep. agalactiae and Strep. dysgalactiae) can be obtained by use of a combination of colony morphology, hemolysis type and catalase reaction, and a multiplex PCR with specific primers restricted to these 3 pathogens. The MALDI-TOF MS is a fast method that shows promising results, although identification of Strep. dysgalactiae at the subspecies level is not yet satisfactory.

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Temperature sensitive (ts) mutant viruses have helped elucidate replication processes in many viral systems. Several panels of replication-defective ts mutants in which viral RNA synthesis is abolished at the nonpermissive temperature (RNA$\sp{-})$ have been isolated for Mouse Hepatitis Virus, MHV (Robb et al., 1979; Koolen et al., 1983; Martin et al., 1988; Schaad et al., 1990). However, no one had investigated genetic or phenotypic relationships between these different mutant panels. In order to determine how the panel of MHV-JHM RNA$\sp{-}$ ts mutants (Robb et al., 1979) were genetically related to other described MHV RNA$\sp{-}$ ts mutants, the MHV-JHM mutants were tested for complementation with representatives from two different sets of MHV-A59 ts mutants (Koolen et al., 1983; Schaad et al., 1990). The three ts mutant panels together were found to comprise eight genetically distinct complementation groups. Of these eight complementation groups, three complementation classes are unique to their particular mutant panel; genetically equivalent mutants were not observed within the other two mutant panels. Two complementation groups were common to all three mutant panels. The three remaining complementation groups overlapped two of the three mutant sets. Mutants MHV-JHM tsA204 and MHV-A59 ts261 were shown to be within one of these overlapping complementation groups. The phenotype of the MHV-JHM mutants within this complementation class has been previously characterized (Leibowitz et al., 1982; Leibowitz et al, 1990). When these mutants were grown at the permissive temperature, then shifted up to the nonpermissive temperature at the start of RNA synthesis, genome-length RNA and leader RNA fragments accumulated, but no subgenomic mRNA was synthesized. MHV-A59 ts261 produced leader RNA fragments identical to those observed with MHV-JHM tsA204. Thus, these two MHV RNA$\sp{-}$ ts mutants that were genetically equivalent by complementation testing were phenotypically similar as well. Recombination frequencies obtained from crosses of MHV-A59 ts261 with several of the gene 1 MHV-A59 mutants indicated that the causal mutation(s) of MHV-A59 ts261 was located near the overlapping junction of ORF1a and ORF1b, in the 3$\sp\prime$ end of ORF1a, or the 5$\sp\prime$ end of ORF1b. Sequence analysis of this junction and 1400 nucleotides into the 5$\sp\prime$ end of ORF1b of MHV-A59 ts261 revealed one nucleotide change from the wildtype MHV-A59. This substitution at nucleotide 13,598 (A to G) was a silent mutation in the ORF1a reading frame, but resulted in an amino acid change in ORF1b gene product (I to V). This amino acid change would be expressed only in the readthrough translation product produced upon successful ribosome frameshifting. A revertant of MHV-A59 ts261 (R2) also retained this guanidine residue, but had a second substitution at nucleotide 14,475 in ORF1b. This mutation results in the substitution of valine for an isoleucine.^ The data presented here suggest that the mutation in MHV-A59 ts261 (nucleotide 13,598) would be responsible for the MHV-JHM complementation group A phenotype. A second-site reversion at nucleotide 14,475 may correct this defect in the revertant. Sequencing of gene 1 immediately upstream of nucleotide 13,296 and downstream of nucleotide 15,010 must be conducted to test this hypothesis. ^