Sensorimotor Function in Progressive Multiple Sclerosis

Background: A sensitive test reflecting subtle sensorimotor changes throughout disease progression independent of mobility impairment is currently lacking in progressive multiple sclerosis. Objectives: We examined non-ambulatory measures of upper and lower extremity sensorimotor function that may reveal differences between relapsing–remitting and progressive forms of multiple sclerosis. Methods: Cutaneous sensitivity, proprioception, central motor function and mobility were assessed in 32 relapsing–remitting and 31 progressive multiple sclerosis patients and 30 non-multiple sclerosis controls. Results: Cutaneous sensation differed between relapsing–remitting and progressive multiple sclerosis at the foot and to a lesser extent the hand. Proprioception function in the upper but not the lower extremity differed between relapsing–remitting and progressive multiple sclerosis, but was different for both upper and lower extremities between multiple sclerosis patients and non-multiple sclerosis controls. Foot-tap but not hand-tap speed was slower in progressive compared to relapsing–remitting multiple sclerosis, suggestive of greater central motor function impairment in the lower extremity in progressive multiple sclerosis. In addition, the non-ambulatory sensorimotor measures were more sensitive in detecting differences between relapsing–remitting and progressive multiple sclerosis than mobility assessed with the 25-foot walk test. Conclusion: This study provides novel information about changes in sensorimotor function in progressive compared with relapsing–remitting forms of multiple sclerosis, and in particular the importance of assessing both upper and lower extremity function. Importantly, our findings showed loss of proprioceptive function in multiple sclerosis but also in progressive compared to relapsing–remitting multiple sclerosis

Further empirical evidence for the non-linearity of the period-luminosity relations as seen in the Large Magellanic Cloud Cepheids

(abridged) Recent studies, using OGLE data for LMC Cepheids in the optical, strongly suggest that the period-luminosity (PL) relation for the Large Magellanic Cloud (LMC) Cepheids shows a break or non-linearity at a period of 10 days. In this paper we apply statistical tests, the chi-square test and the F-test, to the Cepheid data from the MACHO project to test for a non-linearity of the V- and R-band PL relations at 10 days, and extend these tests to the near infrared (JHK-band) PL relations with 2MASS data. We correct the extinction for these data by applying an extinction map towards the LMC. The statistical test we use, the F-test, is able to take account of small numbers of data points and the nature of that data on either side of the period cut at 10 days. With our data, the results we obtained imply that the VRJH-band PL relations are non-linear around a period of 10 days, while the K-band PL relation is (marginally) consistent with a single-line regression. The choice of a period of 10 days, around which this non-linearity occurs, is consistent with the results obtained when this "break" period is estimated from the data. Long period Cepheids are supplemented from the literature to increase our sample size. The photometry of these long period Cepheids is compared with our data and no trend with period is found. Our main results remain unchanged when we supplement our dataset with these long period Cepheids. By examining our data at maximum light, we also suggest arguments why errors in reddening are unlikely to be responsible for our results. The non-linearity of the mean V-band PL relation as seen in both of the OGLE and MACHO data, using different extinction maps, suggests that this non-linearity is real.Comment: 18 pages, 10 tables, 7 figures. MNRAS accepte

Regression analysis with categorized regression calibrated exposure: some interesting findings

BACKGROUND: Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile) scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. METHODS: We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC). RESULTS: In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. CONCLUSION: Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a percentile scale. Relating back to the original scale of the exposure solves the problem. The conclusion regards all regression models

Mathematical Manipulative Models: In Defense of Beanbag Biology

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education

On the Polynomial Measurement Error Model

This paper discusses point estimation of the coefficients of polynomial measurement error (errors-in-variables) models. This includes functional and structural models. The connection between these models and total least squares (TLS) is also examined. A compendium of existing as well as new results is presented

A Secure Semi-Field System for the Study of Aedes aegypti

Novel vector control strategies require validation in the field before they can be widely accepted. Semi-field system (SFS) containment facilities are an intermediate step between laboratory and field trials that offer a safe, controlled environment that replicates field conditions. We developed a SFS laboratory and cage complex that simulates an urban house and yard, which is the primary habitat for Aedes aegypti, the mosquito vector of dengue in Cairns Australia. The SFS consists of a Quarantine Insectary Level-2 (QIC-2) laboratory, containing 3 constant temperature rooms, that is connected to two QIS-2 cages for housing released mosquitoes. Each cage contains the understory of a “Queenslander” timber house and associated yard. An automated air conditioning system keeps temperature and humidity to within 1°C and 5% RH of ambient conditions, respectively. Survival of released A. aegypti was high, especially for females. We are currently using the SFS to investigate the invasion of strains of Wolbachia within populations of A. aegypti

Multilocus Bayesian Estimates of Intra-Oceanic Genetic Differentiation, Connectivity, and Admixture in Atlantic Swordfish (Xiphias gladius L.)

Versión del editor