Automated MRI Volumetric Analysis in Patients with Rasmussen Syndrome.

BACKGROUND AND PURPOSE: Rasmussen syndrome, also known as Rasmussen encephalitis, is typically associated with volume loss of the affected hemisphere of the brain. Our aim was to apply automated quantitative volumetric MR imaging analyses to patients diagnosed with Rasmussen encephalitis, to determine the predictive value of lobar volumetric measures and to assess regional atrophy differences as well as monitor disease progression by using these measures. MATERIALS AND METHODS: Nineteen patients (42 scans) with diagnosed Rasmussen encephalitis were studied. We used 2 control groups: one with 42 age- and sex-matched healthy subjects and the other with 42 epileptic patients without Rasmussen encephalitis with the same disease duration as patients with Rasmussen encephalitis. Volumetric analysis was performed on T1-weighted images by using BrainSuite. Ratios of volumes from the affected hemisphere divided by those from the unaffected hemisphere were used as input to a logistic regression classifier, which was trained to discriminate patients from controls. Using the classifier, we compared the predictive accuracy of all the volumetric measures. These ratios were used to further assess regional atrophy differences and correlate with epilepsy duration. RESULTS: Interhemispheric and frontal lobe ratios had the best prediction accuracy for separating patients with Rasmussen encephalitis from healthy controls and patient controls without Rasmussen encephalitis. The insula showed significantly more atrophy compared with all the other cortical regions. Patients with longitudinal scans showed progressive volume loss in the affected hemisphere. Atrophy of the frontal lobe and insula correlated significantly with epilepsy duration. CONCLUSIONS: Automated quantitative volumetric analysis provides accurate separation of patients with Rasmussen encephalitis from healthy controls and epileptic patients without Rasmussen encephalitis, and thus may assist the diagnosis of Rasmussen encephalitis. Volumetric analysis could also be included as part of follow-up for patients with Rasmussen encephalitis to assess disease progression.

Ictal infraslow activity in stereoelectroencephalography: Beyond the "DC shift".

OBJECTIVES: The significance of infraslow activity (ISA) in focal epilepsies is largely unknown. Recent work has demonstrated ictal ISA to be more widespread in expression than originally understood. Analysis of ISA by stereoelectroencephalography (SEEG) may help to clarify its localizing value, namely the focal versus widespread expression of ISA. METHODS: The ictal SEEG records for fifteen consecutive adult patients were retrospectively analyzed, using both conventional (1.6-70 Hz) and infraslow (0.01-0.1 Hz) bandpass filters. When justified, seizures were averaged in the infraslow band to clarify their stereotypy. Wavelets were used to quantify the time-frequency characteristics of ISA. RESULTS: All clinical seizures were found to possess ISA, and this was markedly invariant across seizures in a given patient. ISA showed biphasic peaks in power, both at ictal onset and offset, with this most prominent in the anatomical structures implicated by conventional analysis. In addition, ISA demonstrated an association with low voltage fast activity, and possessed a more restricted field than conventional activity. CONCLUSIONS: ISA is both widespread (anatomically distributed) and focal (closed electric field). Seizures possess an infraslow spatiotemporal signature. SIGNIFICANCE: Beyond representing a "focus" of paroxysmal activity, ISA must arise from a network process as a component of wideband ictal dynamics. How this relates to clinical definition of the epileptogenic zone requires further study.

Changes in northern Gulf of Mexico sediment bacterial and archaeal communities exposed to hypoxia.

Biogeochemical changes in marine sediments during coastal water hypoxia are well described, but less is known about underlying changes in microbial communities. Bacterial and archaeal communities in Louisiana continental shelf (LCS) hypoxic zone sediments were characterized by pyrosequencing 16S rRNA V4-region gene fragments obtained by PCR amplification of community genomic DNA with bacterial- or archaeal-specific primers. Duplicate LCS sediment cores collected during hypoxia had higher concentrations of Fe(II), and dissolved inorganic carbon, phosphate, and ammonium than cores collected when overlying water oxygen concentrations were normal. Pyrosequencing yielded 158,686 bacterial and 225,591 archaeal sequences from 20 sediment samples, representing five 2-cm depth intervals in the duplicate cores. Bacterial communities grouped by sampling date and sediment depth in a neighbor-joining analysis using Chao-Jaccard shared species values. Redundancy analysis indicated that variance in bacterial communities was mainly associated with differences in sediment chemistry between oxic and hypoxic water column conditions. Gammaproteobacteria (26.5%) were most prominent among bacterial sequences, followed by Firmicutes (9.6%), and Alphaproteobacteria (5.6%). Crenarchaeotal, thaumarchaeotal, and euryarchaeotal lineages accounted for 57%, 27%, and 16% of archaeal sequences, respectively. In Thaumarchaeota Marine Group I, sequences were 96-99% identical to the Nitrosopumilus maritimus SCM1 sequence, were highest in surficial sediments, and accounted for 31% of archaeal sequences when waters were normoxic vs. 13% of archaeal sequences when waters were hypoxic. Redundancy analysis showed Nitrosopumilus-related sequence abundance was correlated with high solid-phase Fe(III) concentrations, whereas most of the remaining archaeal clusters were not. In contrast, crenarchaeotal sequences were from phylogenetically diverse lineages, differed little in relative abundance between sampling times, and increased to high relative abundance with sediment depth. These results provide further evidence that marine sediment microbial community composition can be structured according to sediment chemistry and suggest the expansion of hypoxia in coastal waters may alter sediment microbial communities involved in carbon and nitrogen cycling.

Epileptic focus localization based on resting state interictal MEG recordings is feasible irrespective of the presence or absence of spikes.

OBJECTIVE: To investigate whether epileptogenic focus localization is possible based on resting state connectivity analysis of magnetoencephalographic (MEG) data. METHODS: A multivariate autoregressive (MVAR) model was constructed using the sensor space data and was projected to the source space using lead field and inverse matrix. The generalized partial directed coherence was estimated from the MVAR model in the source space. The dipole with the maximum information inflow was hypothesized to be within the epileptogenic focus. RESULTS: Applying the focus localization algorithm (FLA) to the interictal MEG recordings from five patients with neocortical epilepsy, who underwent presurgical evaluation for the identification of epileptogenic focus, we were able to correctly localize the focus, on the basis of maximum interictal information inflow in the presence or absence of interictal epileptic spikes in the data, with three out of five patients undergoing resective surgery and being seizure free since. CONCLUSION: Our preliminary results suggest that accurate localization of the epileptogenic focus may be accomplished using noninvasive spontaneous "resting-state" recordings of relatively brief duration and without the need to capture definite interictal and/or ictal abnormalities. SIGNIFICANCE: Epileptogenic focus localization is possible through connectivity analysis of resting state MEG data irrespective of the presence/absence of spikes.

Voxel-based morphometric MRI post-processing in MRI-negative focal cortical dysplasia followed by simultaneously recorded MEG and stereo-EEG.

We aim to report on the usefulness of a voxel-based morphometric MRI post-processing technique in detecting subtle epileptogenic structural lesions. The MRI post-processing technique was implemented in a morphometric analysis program (MAP), in a 30-year-old male with pharmacoresistant focal epilepsy and negative MRI. MAP gray-white matter junction file facilitated the identification of a suspicious structural lesion in the right frontal opercular area. The electrophysiological data by simultaneously recorded stereo-EEG and MEG confirmed the epileptogenicity of the underlying subtle structural abnormality. The patient underwent a limited right frontal opercular resection, which completely included the area detected by MAP. Surgical pathology revealed focal cortical dysplasia (FCD) type IIb. Postoperatively the patient has been seizure-free for 2 years. This study demonstrates that MAP has promise in increasing the diagnostic yield of MRI reading in challenging patients with "non-lesional" MRIs. The clinical relevance and epileptogenicity of MAP abnormalities in patients with epilepsy have not been investigated systematically; therefore it is important to confirm their pertinence by performing electrophysiological recordings. When confirmed to be epileptogenic, such MAP abnormalities may reflect an underlying subtle cortical dysplasia whose complete resection can lead to seizure-free outcome.

Cytokine dermatitis and febrile seizure from imiquimod.

Cytokine dermatitis is a well-known and common clinical adverse effect of imiquimod 5% cream (Aldara, 3M). Data from initial Phase III clinical trials reveal a minority of study drug patients experience systemic adverse effects, including fever, arthralgia, headache, myalgia, and lymphadenopathy. These adverse effects are caused, presumably, from increased absorption of study drug over the area of dermatitis, leading to systemic cytokine release. Furthermore, the incidence of systemic reactions was rarely statistically increased above control patients. We describe herein a case of severe cytokine dermatitis in a 2-year-old female patient treated with daily imiquimod for molluscum contagiosum who subsequently developed febrile seizure. We believe this to be the first reported case of seizure associated with imiquimod 5% cream (Aldara, 3M) in a pediatric setting.

Hidden Markov modelling of spike propagation from interictal MEG data.

For patients with partial epilepsy, automatic spike detection techniques applied to interictal MEG data often discover several potentially epileptogenic brain regions. An important determination in treatment planning is which of these detected regions are most likely to be the primary sources of epileptogenic activity. Analysis of the patterns of propagation activity between the detected regions may allow for detection of these primary epileptic foci. We describe the use of hidden Markov models (HMM) for estimation of the propagation patterns between several spiking regions from interictal MEG data. Analysis of the estimated transition probability matrix allows us to make inferences regarding the propagation pattern of the abnormal activity and determine the most likely region of its origin. The proposed HMM paradigm allows for a simple incorporation of the spike detector specificity and sensitivity characteristics. We develop bounds on performance for the case of perfect detection. We also apply the technique to simulated data sets in order to study the robustness of the method to the non-ideal specificity-sensitivity characteristics of the event detectors and compare results with the lower bounds. Our study demonstrates robustness of the proposed technique to event detection errors. We conclude with an example of the application of this method to a single patient.

On concomitant gradients in low-field MRI.

Growing interest in magnetic resonance imaging (MRI) at ultra-low magnetic fields (ULF, approximately muT fields) has been motivated by several advantages over its counterparts at higher magnetic fields. These include narrow line widths, the possibility of novel imaging schemes, reduced imaging artifacts from susceptibility variations within a sample, and reduced system cost and complexity. In addition, ULF NMR/MRI with superconducting quantum interference devices is compatible with simultaneous measurements of biomagnetic signals, a capability conventional systems cannot offer. Acquisition of MRI at ULF must, however, account for concomitant gradients that would otherwise result in severe image distortions. In this paper, we introduce the general theoretical framework that describes concomitant gradients, explain why such gradients are more problematic at low field, and present possible approaches to correct for these unavoidable gradients in the context of a non-slice-selective MRI protocol.

Investigations of dipole localization accuracy in MEG using the bootstrap.

We describe the use of the nonparametric bootstrap to investigate the accuracy of current dipole localization from magnetoencephalography (MEG) studies of event-related neural activity. The bootstrap is well suited to the analysis of event-related MEG data since the experiments are repeated tens or even hundreds of times and averaged to achieve acceptable signal-to-noise ratios (SNRs). The set of repetitions or epochs can be viewed as a set of independent realizations of the brain's response to the experiment. Bootstrap resamples can be generated by sampling with replacement from these epochs and averaging. In this study, we applied the bootstrap resampling technique to MEG data from somatotopic experimental and simulated data. Four fingers of the right and left hand of a healthy subject were electrically stimulated, and about 400 trials per stimulation were recorded and averaged in order to measure the somatotopic mapping of the fingers in the S1 area of the brain. Based on single-trial recordings for each finger we performed 5000 bootstrap resamples. We reconstructed dipoles from these resampled averages using the Recursively Applied and Projected (RAP)-MUSIC source localization algorithm. We also performed a simulation for two dipolar sources with overlapping time courses embedded in realistic background brain activity generated using the prestimulus segments of the somatotopic data. To find correspondences between multiple sources in each bootstrap, sample dipoles with similar time series and forward fields were assumed to represent the same source. These dipoles were then clustered by a Gaussian Mixture Model (GMM) clustering algorithm using their combined normalized time series and topographies as feature vectors. The mean and standard deviation of the dipole position and the dipole time series in each cluster were computed to provide estimates of the accuracy of the reconstructed source locations and time series.

Noise-free magnetoencephalography recordings of brain function.

Perhaps the greatest impediment to acquiring high-quality magnetoencephalography (MEG) recordings is the ubiquitous ambient magnetic field noise. We have designed and built a whole-head MEG system using a helmet-like superconducting imaging surface (SIS) surrounding the array of superconducting quantum interference device (SQUID) magnetometers used to measure the MEG signal. We previously demonstrated that the SIS passively shields the SQUID array from ambient magnetic field noise, independent of frequency, by 25-60 dB depending on sensor location. SQUID 'reference sensors' located on the outside of the SIS helmet measure ambient magnetic fields in very close proximity to the MEG magnetometers while being nearly perfectly shielded from all sources in the brain. The fact that the reference sensors measure no brain signal yet are located in close proximity to the MEG sensors enables very accurate estimation and subtraction of the ambient field noise contribution to the MEG sensors using an adaptive algorithm. We have demonstrated total ambient noise reduction factors in excess of 10(6) (> 120 dB). The residual noise for most MEG SQUID channels is at or near the intrinsic SQUID noise floor, typically 2-3 fT Hz-1/2. We are recording MEG signals with greater signal-to-noise than equivalent EEG measurements.

Localization of realistic cortical activity in MEG using current multipoles.

We present a novel approach to MEG source estimation based on a regularized first-order multipole solution. The Gaussian regularizing prior is obtained by calculation of the sample mean and covariance matrix for the equivalent moments of realistic simulated cortical activity. We compare the regularized multipole localization framework to the classical dipole and general multipole source estimation methods by evaluating the ability of all three solutions to localize the centroids of physiologically plausible patches of activity simulated on the surface of a human cerebral cortex. The results, obtained with a realistic sensor configuration, a spherical head model, and given in terms of field and localization error, depict the performance of the dipolar and multipolar models as a function of variable source surface area (50-500 mm(2)), noise conditions (20, 10, and 5 dB SNR), source orientation (0-90 degrees ), and source depth (3-11 cm). We show that as the sources increase in size, they become less accurately modeled as current dipoles. The regularized multipole systematically outperforms the single dipole model, increasingly so as the spatial extent of the sources increases. In addition, our simulations demonstrate that as the orientation of the sources becomes more radial, dipole localization accuracy decreases substantially, while the performance of the regularized multipole model is far less sensitive to orientation and even succeeds in localizing quasi-radial source configurations. Furthermore, our results show that the multipole model is able to localize superficial sources with higher accuracy than the current dipole. These results indicate that the regularized multipole solution may be an attractive alternative to current-dipole-based source estimation methods in MEG.

Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering.

OBJECTIVE: Magnetoencephalography (MEG) dipole localization of epileptic spikes is useful in epilepsy surgery for mapping the extent of abnormal cortex and to focus intracranial electrodes. Visually analyzing large amounts of data produces fatigue and error. Most automated techniques are based on matching of interictal spike templates or predictive filtering of the data and do not explicitly include source localization as part of the analysis. This leads to poor sensitivity versus specificity characteristics. We describe a fully automated method that combines time-series analysis with source localization to detect clusters of focal neuronal current generators within the brain that produce interictal spike activity. METHODS: We first use an ICA (independent components analysis) method to decompose the multichannel MEG data and identify those components that exhibit spike-like characteristics. From these detected spikes we then find those whose spatial topographies across the array are consistent with focal neural sources, and determine the foci of equivalent current dipoles and their associated time courses. We then perform a clustering of the localized dipoles based on distance metrics that takes into consideration both their locations and time courses. The final step of refinement consists of retaining only those clusters that are statistically significant. The average locations and time series from significant clusters comprise the final output of our method. RESULTS AND SIGNIFICANCE: Data were processed from 4 patients with partial focal epilepsy. In all three subjects for whom surgical resection was performed, clusters were found in the vicinity of the resectioned area. CONCLUSIONS: The presented procedure is promising and likely to be useful to the physician as a more sensitive, automated and objective method to help in the localization of the interictal spike zone of intractable partial seizures. The final output can be visually verified by neurologists in terms of both the location and distribution of the dipole clusters and their associated time series. Due to the clinical relevance and demonstrated promise of this method, further investigation of this approach is warranted.

On MEG forward modelling using multipolar expansions.

Magnetoencephalography (MEG) is a non-invasive functional imaging modality based on the measurement of the external magnetic field produced by neural current sources within the brain. The reconstruction of the underlying sources is a severely ill-posed inverse problem typically tackled using either low-dimensional parametric source models, such as an equivalent current dipole (ECD), or high-dimensional minimum-norm imaging techniques. The inability of the ECD to properly represent non-focal sources and the over-smoothed solutions obtained by minimum-norm methods underline the need for an alternative approach. Multipole expansion methods have the advantages of the parametric approach while at the same time adequately describing sources with significant spatial extent and arbitrary activation patterns. In this paper we first present a comparative review of spherical harmonic and Cartesian multipole expansion methods that can be used in MEG. The equations are given for the general case of arbitrary conductors and realistic sensor configurations and also for the special cases of spherically symmetric conductors and radially oriented sensors. We then report the results of computer simulations used to investigate the ability of a first-order multipole model (dipole and quadrupole) to represent spatially extended sources, which are simulated by 2D and 3D clusters of elemental dipoles. The overall field of a cluster is analysed using singular value decomposition and compared to the unit fields of a multipole, centred in the middle of the cluster, using subspace correlation metrics. Our results demonstrate the superior utility of the multipolar source model over ECD models in providing source representations of extended regions of activity.

Rapidly recomputable EEG forward models for realistic head shapes.

With the increasing availability of surface extraction techniques for magnetic resonance and x-ray computed tomography images, realistic head models can be readily generated as forward models in the analysis of electroencephalography (EEG) and magnetoencephalography (MEG) data. Inverse analysis of this data, however, requires that the forward model be computationally efficient. We propose two methods for approximating the EEG forward model using realistic head shapes. The 'sensor-fitted sphere' approach fits a multilayer sphere individually to each sensor, and the 'three-dimensional interpolation' scheme interpolates using a grid on which a numerical boundary element method (BEM) solution has been precomputed. We have characterized the performance of each method in terms of magnitude and subspace error metrics, as well as computational and memory requirements. We have also made direct performance comparisons with traditional spherical models. The approximation provided by the interpolative scheme had an accuracy nearly identical to full BEM, even within 3 mm of the inner skull surface. Forward model computation during inverse procedures was approximately 30 times faster than for a traditional three-shell spherical model. Cast in this framework, high-fidelity numerical solutions currently viewed as computationally prohibitive for solving the inverse problem (e.g. linear Galerkin BEM) can be rapidly recomputed in a highly efficient manner. The sensor-fitting method has a similar one-time cost to the BEM method, and while it produces some improvement over a standard three-shell sphere, its performance does not approach that of the interpolation method. In both methods, there is a one-time cost associated with precomputing the forward solution over a set of grid points.

Drosophila single-minded represses gene transcription by activating the expression of repressive factors.

The Drosophila single-minded gene controls CNS midline cell development by both activating midline gene expression and repressing lateral CNS gene expression in the midline cells. The mechanism by which Single-minded represses transcription was examined using the ventral nervous system defective gene as a target gene. Transgenic-lacZ analysis of constructs containing fragments of the ventral nervous system defective regulatory region identified sequences required for lateral CNS transcription and midline repression. Elimination of Single-minded:Tango binding sites within the ventral nervous system defective gene did not affect midline repression. Mutants of Single-minded that removed the DNA binding and transcriptional activation regions abolished ventral nervous system defective repression, as well as transcriptional activation of other genes. The replacement of the Single-minded transcriptional activation region with a heterologous VP16 transcriptional activation region restored the ability of Single-minded to both activate and repress transcription. These results indicate that Single-minded indirectly represses transcription by activating the expression of repressive factors. Single-minded provides a model system for how regulatory proteins that act only as transcriptional activators can control lineage-specific transcription in both positive and negative modes.

Dipole localization of human induced focal afterdischarge seizure in simultaneous magnetoencephalography and electrocorticography.

Localizations were compared for the same human seizure between simultaneously measured MEG and iEEG, which were both co-registered to MRI. The whole-cortex neuromagnetometer localized a dipole in a sphere phantom, co-registered to the MEG sensor array, with an error of 1.4 mm. A focal afterdischarge seizure was induced in a patient with partial epilepsy, by stimulation at a subdural electrocorticography (ECoG) electrode with a known location, which was co-registered to the MRI and to the MEG sensor array. The simultaneous MEG and ECoG during the 30-second seizure was measured and analyzed using the single, moving dipole model, which is the localization model used clinically. The dipole localizations from simultaneous whole cortex 68-channel MEG and 64-channel ECoG were then compared for the repetitive spiking at six different times during the seizure. There were two main regions of MEG and ECoG activity. The locations of these regions were confirmed by determining the location clusters of 8,000 dipoles on ECoG at consecutive time points during the seizure. The mean distances between the stimulated electrode location versus the dipole location of the MEG and versus the dipole location of the ECoG were each about one (1) centimeter. The mean distance between the dipole locations of the MEG versus the dipole locations of the ECoG was about 2 cm. These errors were compared to errors of MEG and ECoG reported previously for phantoms and for somatosensory evoked responses (SER) in patients. Comparing the findings from the present study to those from prior studies, there appeared to be the expected stepwise increase in mean localization error progressing from the phantom, to the SER, to the seizure.

Paired MEG data set source localization using recursively applied and projected (RAP) MUSIC.

An important class of experiments in functional brain mapping involves collecting pairs of data corresponding to separate "Task" and "Control" conditions. The data are then analyzed to determine what activity occurs during the Task experiment but not in the Control. Here we describe a new method for processing paired magnetoencephalographic (MEG) data sets using our recursively applied and projected multiple signal classification (RAP-MUSIC) algorithm. In this method the signal subspace of the Task data is projected against the orthogonal complement of the Control data signal subspace to obtain a subspace which describes spatial activity unique to the Task. A RAP-MUSIC localization search is then performed on this projected data to localize the sources which are active in the Task but not in the Control data. In addition to dipolar sources, effective blocking of more complex sources, e.g., multiple synchronously activated dipoles or synchronously activated distributed source activity, is possible since these topographies are well-described by the Control data signal subspace. Unlike previously published methods, the proposed method is shown to be effective in situations where the time series associated with Control and Task activity possess significant cross correlation. The method also allows for straightforward determination of the estimated time series of the localized target sources. A multiepoch MEG simulation and a phantom experiment are presented to demonstrate the ability of this method to successfully identify sources and their time series in the Task data.

Functional interactions between Drosophila bHLH/PAS, Sox, and POU transcription factors regulate CNS midline expression of the slit gene.

During Drosophila embryogenesis the CNS midline cells have organizing activities that are required for proper elaboration of the axon scaffold and differentiation of neighboring neuroectodermal and mesodermal cells. CNS midline development is dependent on Single-minded (Sim), a basic-helix-loop-helix (bHLH)-PAS transcription factor. We show here that Fish-hook (Fish), a Sox HMG domain protein, and Drifter (Dfr), a POU domain protein, act in concert with Single-minded to control midline gene expression. single-minded, fish-hook, and drifter are all expressed in developing midline cells, and both loss- and gain-of-function assays revealed genetic interactions between these genes. The corresponding proteins bind to DNA sites present in a 1 kb midline enhancer from the slit gene and regulate the activity of this enhancer in cultured Drosophila Schneider line 2 cells. Fish-hook directly associates with the PAS domain of Single-minded and the POU domain of Drifter; the three proteins can together form a ternary complex in yeast. In addition, Fish can form homodimers and also associates with other bHLH-PAS and POU proteins. These results indicate that midline gene regulation involves the coordinate functions of three distinct types of transcription factors. Functional interactions between members of these protein families may be important for numerous developmental and physiological processes.

Alcohol policy and the young adult: establishing priorities, building partnerships, overcoming barriers.

Young adults (defined here as those 18-29 years of age) in the United States and Canada constitute a demographic group most likely to suffer serious alcohol problems, yet the alcohol policy field has made little effort to develop prevention strategies that respond specifically to their circumstances and needs. This paper briefly reviews relevant research, analyzes prevention policy priorities, presents the barriers to implementation and outlines strategies for overcoming them. Its main conclusions are: (1) Strategies to reduce alcohol availability and increase alcohol prices will significantly reduce alcohol problems among young adults. (2) A high priority should be given to harm reduction strategies and strategies that target the physical environments where young adults are likely to congregate. (3) The alcohol industries and the industries' allies will vigorously oppose these policy reforms, and their resistance constitutes a formidable barrier to implementation. (4) Resistance from other community institutions, which may benefit from the status quo, is an additional barrier that must be addressed. (5) There is a tendency to compromise with the alcohol industries and others and substitute individual-based prevention strategies for public policy reforms. Individual-based strategies complement public policy reforms but should not replace them. (6) Overcoming barriers will require community organizing, coalition building, media advocacy and policy advocacy and an expanded research effort. The field needs to develop new messages and themes in both media and policy advocacy that address the specific concerns and interests of young adults, thereby encouraging their active leadership in prevention policy development.