John Hughes

d-Amphetamine unmasks postnatal consequences of exposure to methylmercury in utero: methods for studying behavioral teratogenesis.

Pregnant rats were given various doses of methylmercury (MM) at three different stages of gestation (Days 0, 7 or 14). Administration of 56% or 27% of the dose given on the first day (Day 0) of pregnancy to 7 or 14 day pregnant rats, respectively, resulted in equivalent concentrations of MM ni 19 day old feti and 1 day and 1 week old neonates. A single, 5 mg MM/kg, oral dose on Day 0, or its equivalent on Days 7 or 14 of gestation did not produce any signs of toxicity in pregnant dams or their offspring. Weight gain of pregnant dams, litter size, litter weights at birth or at weaning and gross physical appearance were not different amongst the various treated groups and their respective controls. Operant level of bar pressing and acquisition of a discrete trial autoshape task indicated no differences with respect to operant levels, rate of acquisition or asymptotic performance resulting from exposure to MM in utero. The operant (autoshaped) behavior showed sex related differences to the disrupting influence of d-amphetamine (d-A); females were significantly more sensitive than males. Moreover, both males and females whose dams were treated with MM on Day 0 or 7 of pregnancy were significantly less affected by the d-A when compared with controls. Offspring born to dams given MM on Day 14 of pregnancy did not show a differential effect of d-A. It is concluded that early prenatal exposure to low doses of MM can result in behavioral consequences subtle enough to require unmasking of the effects with psychotropic drugs. Additionally, periods may exist during development when the embryo or fetus is most susceptible to behavioral or functional teratogenic effects of exposure to chemical insult. The testing procedures used in these experiments were objective, automatic and amenable for use with relatively large sample sizes compared with other operant behavior analytical methods. They also lend themselves to appropriate parametric statistical analyses, a staunch requirement for behavioral toxicological and teratological studies.

Acetabular Cartilage Assessment in Patients with Femoroacetabular Impingement by Using T2* Mapping with Arthroscopic Verification

PURPOSEnTo evaluate the ability of T2* mapping to help differentiate damaged from normal acetabular cartilage in patients with femoroacetabular impingement (FAI).nnnMATERIALS AND METHODSnThe institutional review board approved this retrospective study, and the requirement to obtain informed consent was waived. The study complied with HIPAA guidelines. The authors reviewed T2* relaxation time maps of 28 hips from 26 consecutive patients (mean patient age, 28.2 years; range, 12-53 years; eight male patients (nine hips) with a mean age of 26.7 years [range, 16-53 years]; 18 female patients (19 hips) with a mean age of 28.9 years [range, 12-46 years]). Conventional diagnostic 3.0-T magnetic resonance (MR) arthrography was augmented by including a multiecho gradient-recalled echo sequence for T2* mapping. After imaging, acetabular and femoral data were separated and acetabular regions of interest were identified. Arthroscopic cartilage assessment with use of a modified Beck scale for acetabular cartilage damage was performed by an orthopedic surgeon who was blinded to the results of T2* mapping. A patient-specific acetabular projection with a T2* overlay was developed to anatomically correlate imaging data with those from surgery (the standard of reference). Results were analyzed by using receiver operating characteristic (ROC) curves.nnnRESULTSnThe patient-specific acetabular projection enabled co-localization between the MR imaging and arthroscopic findings. T2* relaxation times for normal cartilage (Beck score 1, 35.3 msec ± 7.0) were significantly higher than those for cartilage with early changes (Beck score 2, 20.7 msec ± 6.0) and cartilage with more advanced degeneration (Beck scores 3-6, ≤19.8 msec ± 5.6) (P < .001). At ROC curve analysis, a T2* value of 28 msec was identified as the threshold for damaged cartilage, with a 91% true-positive and 13% false-positive rate for differentiating Beck score 1 cartilage (normal) from all other cartilages.nnnCONCLUSIONnThe patient-specific acetabular projection with a T2* mapping overlay enabled good anatomic localization of cartilage damage defined with a T2* threshold of 28 msec and less.

Delayed teratogenic effect of methylmercury on hepatic cytochrome P-450-dependent monooxygenase systems of rats.

Hepatic cytochrome P-450-dependent monooxygenase systems were depressed in adult male rats which had been exposed prenatally to methylmercury. The effect was not seen in immature male or female rats or in adult female rats. This latent teratogenic effect of methylmercury appeared only when exposure occurred during early fetal development. These studies demonstrate that the expression of a chemically induced teratogenic effect may be considerably delayed in the rat and that the stage of development of the fetus at the time of exposure to the chemical agent may be a determining factor.

Time dependent effects produced in chicks after prenatal injection of methylmercury.

Methylmercury dicyandiamide (0.05 to 10 mg/kg eff) injected into the volk sac of fertilized chicken eggs prior to incubation produced a dose related decrease in the percentage of chicks hatched (90-57% of control). With dosage fixed at 0.5 or 5.0 mg/kg egg and injections made on Days 0, 7 or 14 of incubation, hatches were 90, 68 and 75%, respectively, for the low dose and 63, 13 and 18% for the high dose. In contrast to results obtained from chicks hatched from eggs injected on Day 0 of incubation, chicks hatched from eggs injected with 0.5 or 5.0 mg MMD/kg on Day 7 or 14 were not different from controls in a detour learning situation. Administration of 14-C methylmercury revealed maximal brain radiolabel in embryos injected on Day 0 to be 10% that seen with eggs injected on Day 7 but twice that seen with eggs injected on Day 14. We tentatively conclude that a period of maximal sensitivity to the behavior effects exists prior to Day 7 and that the mechanisms of embryolethality is different from that producing the functional deficits.

A matrix computational approach to kinesin neck linker extension.

Kinesin stepping requires both tethered diffusion of the free head and conformational changes driven by the chemical state of the motor. We present a numerical method using matrix representations of approximating Markov chains and renewal theory to compute important experimental quantities for models that include both tethered diffusion and chemical transitions. Explicitly modeling the tethered diffusion allows for exploration of the model under perturbation of the neck linker; comparisons are made between the computed models and in vitro assays.

Fast, fully Bayesian spatiotemporal inference for fMRI data

We propose a spatial Bayesian variable selection method for detecting blood oxygenation level dependent activation in functional magnetic resonance imaging (fMRI) data. Typical fMRI experiments generate large datasets that exhibit complex spatial and temporal dependence. Fitting a full statistical model to such data can be so computationally burdensome that many practitioners resort to fitting oversimplified models, which can lead to lower quality inference. We develop a full statistical model that permits efficient computation. Our approach eases the computational burden in two ways. We partition the brain into 3D parcels, and fit our model to the parcels in parallel. Voxel-level activation within each parcel is modeled as regressions located on a lattice. Regressors represent the magnitude of change in blood oxygenation in response to a stimulus, while a latent indicator for each regressor represents whether the change is zero or non-zero. A sparse spatial generalized linear mixed model captures the spatial dependence among indicator variables within a parcel and for a given stimulus. The sparse SGLMM permits considerably more efficient computation than does the spatial model typically employed in fMRI. Through simulation we show that our parcellation scheme performs well in various realistic scenarios. Importantly, indicator variables on the boundary between parcels do not exhibit edge effects. We conclude by applying our methodology to data from a task-based fMRI experiment.

T2 relaxation time of acetabular and femoral cartilage with and without intraarticular gadopentetate dimeglumine in patients with femoroacetabular impingement

OBJECTIVEnThe purpose of this study was to assess whether the presence of intraarticular gadopentetate dimeglumine during clinical MR arthrography significantly alters the T2* relaxation time of hip articular cartilage in patients with femoroacetabular impingement.nnnSUBJECTS AND METHODSnT2* mapping of 10 patient volunteers (seven female patients, three male patients; age range, 14-49 years; mean, 33.0 ± 12.2 [SD] years) with symptomatic femoroacetabular impingement was performed before and after intraarticular administration of gadopentetate dimeglumine. Overall 323 ROIs were defined in each acetabular and femoral cartilage before and after gadolinium injection. Agreement of the T2* relaxation times before and after gadolinium injection was assessed with the Krippendorff alpha coefficient and linear regression through the origin.nnnRESULTSnT2* relaxation times before and after gadolinium injection in both acetabular and femoral cartilage were found to agree strongly. Specifically, estimated Krippendorff alpha values were greater than 0.8 for both acetabular and femoral cartilage, linear regressions through the origin yielded estimated slopes very close to 1, and R(2) values were greater than 0.98.nnnCONCLUSIONnThe results indicate that intraarticular injection of gadopentetate dimeglumine according to the protocol described in this study has little effect on the T2* of femoral and acetabular cartilage. The results suggest that T2* mapping can be safely performed as an addition to a standard clinical hip imaging protocol that includes gadopentetate dimeglumine administration.

Likelihood inference for particle location in fluorescence microscopy

We introduce a procedure to automatically count and locate the fluorescent particles in a microscopy image. Our procedure employs an approximate likelihood estimator derived from a Poisson random field model for photon emission. Estimates of standard errors are generated for each image along with the parameter estimates, and the number of particles in the image is determined using an information criterion and likelihood ratio tests. Realistic simulations show that our procedure is robust and that it leads to accurate estimates, both of parameters and of standard errors. This approach improves on previous ad hoc least squares procedures by giving a more explicit stochastic model for certain fluorescence images and by employing a consistent framework for analysis.

Bayesian Spatiotemporal Modeling for Detecting Neuronal Activation via Functional Magnetic Resonance Imaging

We consider recent developments in Bayesian spatiotemporal models for detecting neuronal activation in fMRI experiment. A Bayesian approach typically results in complicated posterior distributions that can be of enormous dimension for a whole-brain analysis, thus posing a formidable computational challenge. Recently developed Bayesian approaches to detecting local activation have proved computationally efficient while requiring few modeling compromises. We review two such methods and implement them on a data set from the Human Connectome Project in order to show that, contrary to popular opinion, careful implementation of Markov chain Monte Carlo methods can be used to obtain reliable results in a matter of minutes.

Bayesian Spatiotemporal Modeling Using Hierarchical Spatial Priors, with Applications to Functional Magnetic Resonance Imaging

We propose a spatiotemporal Bayesian variable selection model for detecting activation in functional magnetic resonance imaging (fMRI) settings. Following recent research in this area, we use binary indicator variables for classifying active voxels. We assume that the spatial dependence in the images can be accommodated by applying an areal model to parcels of voxels. The use of parcellation and a spatial hierarchical prior (instead of the popular Ising prior) results in a posterior distribution amenable to exploration with an efficient Markov chain Monte Carlo algorithm. We study the properties of our approach by applying it to simulated data and to two fMRI data sets.