Biofeedback control of migraine headaches: A comparison of two approaches

In order to assess the relative effectiveness of finger warming and temporal blood volume pulse reduction biofeedback in the treatment of migraine, 22 female migraine patients were assigned to one of three experimental conditions: temporal artery constriction feedback, finger temperature feedback, or waiting list. Biofeedback training consisted of 12 sessions over a 6-week period. All patients completed 5 weeks of daily self-monitoring of headache activity (frequency, duration, and intensity) and medication before and after treatment. Treatment credibility was assessed at the end of Sessions 1, 6, and 12. Results showed that temporal constriction and finger temperature biofeedback were equally effective in controlling migraine headaches and produced greater benefits than the waiting list condition. Power analyses indicated that very large sample sizes would have been required to detect any significant differences between the two treatment groups. No significant relationships were found between levels of therapeutic gains and levels of thermal or blood volume pulse self-regulation skills. Likewise, treatment outcome was not found to be related to treatment credibility. Further analyses revealed that changes in headache activity and medication were associated with changes in vasomotor variability. Because blood volume pulse variability was not significantly affected by biofeedback training, questions about its role in the therapeutic mechanism are raised.This research was supported in part by grants from the Quebec Ministry of Education and the Quebec Ministery of Social Affairs to the first author, and an award from the Medical Research Council of Canada to the second author. The authors are indebted to Drs. Frank Andrasik, Howard Barbaree, Edward Blanchard, Martin Ford, and Patrick McGrath, as well as to two anonymous reviewers, for their helpful comments on an earlier draft of this paper.     

Combinatorial approaches to functional models for galactose oxidase

The copper enzyme galactose oxidase (GOase, EC 1.1.3.9) catalyses the oxidation of D-galactose and other primary alcohols in air to the corresponding aldehydes and hydrogen peroxide. The current mechanistic hypothesis for this two-electron redox reaction involves a Cu(I)/Cu(II) couple and the reversible oxidation of a ligating phenolate (tyrosine residue of the Tyr272-Cys228 conjugate) to a phenoxyl radical. Our approaches to functional models for galactose oxidase comprise both the use of low-molecular-weight copper complexes of a Schiff-base and sulfonamide ligands, and the synthesis/screening of combinatorial libraries. With regard to the latter, we have synthesized (by the IRORI-directed synthesis approach) peptide libraries carrying either His or the redox-active amino acids Tyr, mod-Cys (a model for the Tyr272-Cys228 conjugate) or TOAC (a TEMPO-derived alpha-amino acid) at four variable positions. After incubation with copper ions, the catalytically active library members were identified by specially designed screening methods.     

Transgenic nonhuman primate models for human diseases: approaches and contributing factors

Nonhuman primates (NHPs) provide powerful experimental models to study human development,cognitive functions and disturbances as well as complex behavior,because of their genetic and physiological simi...     

A two-phase procedure for QTL mapping with regression models

It is typical in QTL mapping experiments that the number of markers under investigation is large. This poses a challenge to commonly used regression models since the number of feature variables is usually much larger than the sample size, especially, when epistasis effects are to be considered. The greedy nature of the conventional stepwise procedures is well known and is even more conspicuous in such cases. In this article, we propose a two-phase procedure based on penalized likelihood techniques and extended Bayes information criterion (EBIC) for QTL mapping. The procedure consists of a screening phase and a selection phase. In the screening phase, the main and interaction features are alternatively screened by a penalized likelihood mechanism. In the selection phase, a low-dimensional approach using EBIC is applied to the features retained in the screening phase to identify QTL. The two-phase procedure has the asymptotic property that its positive detection rate (PDR) and false discovery rate (FDR) converge to 1 and 0, respectively, as sample size goes to infinity. The two-phase procedure is compared with both traditional and recently developed approaches by simulation studies. A real data analysis is presented to demonstrate the application of the two-phase procedure.     

Random regression models for detection of gene by environment interaction

Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.     

A comparison of ovariectomy models for estrogen studies

Many estrogen-replacement studies use ovariectomized animals as controls. However, ovariectomy greatly increases body weight and can enhance the peripheral synthesis of estrogen. Tamoxifen is commonly used as an antiestrogen, but it may elicit mixed agonist or antagonist actions. The aim of our study was to compare vascular function in mesenteric arteries among groups of rats with low estradiol levels. The groups (n = 5, each) of Sprague-Dawley rats were cycling (diestrus), ovariectomized (OVX), OVX + tamoxifen (OVX-T), OVX + 4-hydroxyandrostene-3,17-dione, an aromatase inhibitor (OVX-A) to prevent peripheral synthesis of estrogen, and control-fed OVX to prevent excess weight gain. Body weight was significantly elevated in only the non-control-fed OVX group. Estrogen levels were significantly greater in the cycling rats compared with the other groups, whereas uterine weights were significantly reduced in only the OVX-A and control-fed OVX groups. Methacholine relaxation was blunted only in the OVX-A and control-fed OVX groups, suggesting a possible estrogenic influence in the non-control-fed OVX and OVX-T groups. These data indicate the potential for confounding factors to decrease the efficacy of OVX controls.     

A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep

Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep.