Low-threshold monopolar motor mapping for resection of primary motor cortex tumors

Microsurgery within eloquent cortex is a controversial approach because of the high risk of permanent neurological deficit. Few data exist showing the relationship between the mapping stimulation intensity required for eliciting a muscle motor evoked potential and the distance to the motor neurons; furthermore, the motor threshold at which no deficit occurs remains to be defined.

Obesity lowers the threshold of allergic sensitization and augments airway eosinophilia in a mouse model of asthma

Clinical and epidemiological studies show a close association between obesity and the risk of asthma development. The underlying cause-effect relationship between metabolism, innate and adaptive immunity, and inflammation remains to be elucidated.

Enhanced Atlantic subpolar gyre variability through baroclinic threshold in a coarse resolution model

Direct observations, satellite measurements and paleo records reveal strong variability in the Atlantic subpolar gyre on various time scales. Here we show that variations of comparable amplitude can only be simulated in a coupled climate model in the proximity of a dynamical threshold. The threshold and the associated dynamic response is due to a positive feedback involving increased salt transport in the subpolar gyre and enhanced deep convection in its centre. A series of sensitivity experiments is performed with a coarse resolution ocean general circulation model coupled to a statistical-dynamical atmosphere model which in itself does not produce atmospheric variability. To simulate the impact of atmospheric variability, the model system is perturbed with freshwater forcing of varying, but small amplitude and multi-decadal to centennial periodicities and observational variations in wind stress. While both freshwater and wind-stress-forcing have a small direct effect on the strength of the subpolar gyre, the magnitude of the gyre's response is strongly increased in the vicinity of the threshold. Our results indicate that baroclinic self-amplification in the North Atlantic ocean can play an important role in presently observed SPG variability and thereby North Atlantic climate variability on multi-decadal scales.

Predicting spike timing of neocortical pyramidal neurons by simple threshold models

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current--is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating current simulating synaptic bombardment in vivo. The model generates output spikes whenever the membrane voltage (a filtered version of the input current) reaches a dynamic threshold. We find that for input currents with large fluctuation amplitude, up to 75% of the spike times can be predicted with a precision of +/-2 ms. Some of the intrinsic neuronal unreliability can be accounted for by a noisy threshold mechanism. Our results suggest that, under random current injection into the soma, (i) neuronal behavior in the subthreshold regime can be well approximated by a simple linear filter; and (ii) most of the nonlinearities are captured by a simple threshold process.

Increased proximal urethral sensory threshold after radical pelvic surgery in women

AIM: To identify factors that potentially influence urethral sensitivity in women. PATIENTS AND METHODS: The current perception threshold was measured by double ring electrodes in the proximal and distal urethra in 120 women. Univariate analysis using Kaplan-Meier models and multivariate analysis applying Cox regressions were performed to identify factors influencing urethral sensitivity in women. RESULTS: In univariate and multivariate analysis, women who had undergone radical pelvic surgery (radical cystectomy n = 12, radical rectal surgery n = 4) showed a significantly (log rank test P < 0.0001) increased proximal urethral sensory threshold compared to those without prior surgery (hazard ratio (HR) 4.17, 95% confidence interval (CI) 2.04-8.51), following vaginal hysterectomy (HR 4.95, 95% CI 2.07-11.85), abdominal hysterectomy (HR 5.96, 95% CI 2.68-13.23), or other non-pelvic surgery (HR 4.86, 95% CI 2.24-10.52). However, distal urethral sensitivity was unaffected by any form of prior surgery. Also other variables assessed, including age, concomitant diseases, urodynamic diagnoses, functional urethral length, and maximum urethral closure pressure at rest had no influence on urethral sensitivity in univariate as well as in multivariate analysis. CONCLUSIONS: Increased proximal but unaffected distal urethral sensory threshold after radical pelvic surgery in women suggests that the afferent nerve fibers from the proximal urethra mainly pass through the pelvic plexus which is prone to damage during radical pelvic surgery, whereas the afferent innervation of the distal urethra is provided by the pudendal nerve. Better understanding the innervation of the proximal and distal urethra may help to improve surgical procedures, especially nerve sparing techniques. Neurourol. Urodynam. (c) 2006 Wiley-Liss, Inc.

CYP2E1 genotype and isoniazid-induced hepatotoxicity in patients treated for latent tuberculosis

OBJECTIVE: To determine whether pharmacogenetic tests such as N-acetyltransferase 2 (NAT2) and cytochrome P450 2E1 (CYP2E1) genotyping are useful in identifying patients prone to antituberculosis drug-induced hepatotoxicity in a cosmopolite population. METHODS: In a prospective study we genotyped 89 patients treated with isoniazid (INH) for latent tuberculosis. INH-induced hepatitis (INH-H) or elevated liver enzymes including hepatitis (INH-ELE) was diagnosed based on the clinical diagnostic scale (CDS) designed for routine clinical practice. NAT2 genotypes were assessed by fluorescence resonance energy transfer probe after PCR analysis, and CYP2E1 genotypes were determined by PCR with restriction fragment length polymorphism analysis. RESULTS: Twenty-six patients (29%) had INH-ELE, while eight (9%) presented with INH-H leading to INH treatment interruption. We report no significant influence of NAT2 polymorphism, but we did find a significant association between the CYP2E1 *1A/*1A genotype and INH-ELE (OR: 3.4; 95% CI:1.1-12; p = 0.02) and a non significant trend for INH-H (OR: 5.9; 95% CI: 0.69-270; p = 0.13) compared with other CYP2E1 genotypes. This test for predicting INH-ELE had a positive predictive value (PPV) of 39% (95% CI: 26-54%) and a negative predictive value (NPV) of 84% (95% CI: 69-94%). CONCLUSION: The genotyping of CYP2E1 polymorphisms may be a useful predictive tool in the common setting of a highly heterogeneous population for predicting isoniazid-induced hepatic toxicity. Larger prospective randomized trials are needed to confirm these results.

Ondansetron does not reduce the shivering threshold in healthy volunteers

BACKGROUND: Ondansetron, a serotonin-3 receptor antagonist, reduces postoperative shivering. Drugs that reduce shivering usually impair central thermoregulatory control, and may thus be useful for preventing shivering during induction of therapeutic hypothermia. We determined, therefore, whether ondansetron reduces the major autonomic thermoregulatory response thresholds (triggering core temperatures) in humans. METHODS: Control (placebo) and ondansetron infusions at the target plasma concentration of 250 ng ml(-1) were studied in healthy volunteers on two different days. Each day, skin and core temperatures were increased to provoke sweating; then reduced to elicit peripheral vasoconstriction and shivering. We determined the core-temperature sweating, vasoconstriction and shivering thresholds after compensating for changes in mean-skin temperature. Data were analysed using t-tests and presented as means (sds); P<0.05 was taken as significant. RESULTS: Ondensetron plasma concentrations were 278 (57), 234 (55) and 243 (58) ng ml(-1) at the sweating, vasoconstriction and shivering thresholds, respectively; these corresponded to approximately 50 mg of ondansetron which is approximately 10 times the dose used for postoperative nausea and vomiting. Ondansetron did not change the sweating (control 37.4 (0.4) degrees C, ondansetron 37.6 (0.3) degrees C, P=0.16), vasoconstriction (37.0 (0.5) degrees C vs 37.1 (0.3) degrees C; P=0.70), or shivering threshold (36.3 (0.5) degrees C vs 36.3 (0.6) degrees C; P=0.76). No sedation was observed on either study day. CONCLUSIONS: /b>. Ondansetron appears to have little potential for facilitating induction of therapeutic hypothermia.

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

Additive Hazards Models with Latent Treatment Effectiveness Lag Time

In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied to estimate the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalizing over random effects, so parameters in the models are easy to be estimated and interpreted, while the flexibility without specifying baseline hazard function is kept. Monte Carlo simulation studies demonstrate the appropriateness of the proposed semiparametric estimation procedure. Data collected in the actual randomized clinical trial, which evaluates the effectiveness of biodegradable carmustine polymers for treatment of recurrent brain tumors, are analyzed.

Checking Assumptions in Latent Class Regression Models via a Markov Chain Monte Carlo Estimation Approach: An Application to Depression and Socio-Economic Status

Latent class regression models are useful tools for assessing associations between covariates and latent variables. However, evaluation of key model assumptions cannot be performed using methods from standard regression models due to the unobserved nature of latent outcome variables. This paper presents graphical diagnostic tools to evaluate whether or not latent class regression models adhere to standard assumptions of the model: conditional independence and non-differential measurement. An integral part of these methods is the use of a Markov Chain Monte Carlo estimation procedure. Unlike standard maximum likelihood implementations for latent class regression model estimation, the MCMC approach allows us to calculate posterior distributions and point estimates of any functions of parameters. It is this convenience that allows us to provide the diagnostic methods that we introduce. As a motivating example we present an analysis focusing on the association between depression and socioeconomic status, using data from the Epidemiologic Catchment Area study. We consider a latent class regression analysis investigating the association between depression and socioeconomic status measures, where the latent variable depression is regressed on education and income indicators, in addition to age, gender, and marital status variables. While the fitted latent class regression model yields interesting results, the model parameters are found to be invalid due to the violation of model assumptions. The violation of these assumptions is clearly identified by the presented diagnostic plots. These methods can be applied to standard latent class and latent class regression models, and the general principle can be extended to evaluate model assumptions in other types of models.

A Mechanistic Latent Variable Model for Estimating Drug Concentrations in the Male Genital Tract

The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.