Faculty Bibliography

Epidemiological studies indicate that women have a higher risk of Alzheimer's disease (AD) even after adjustment for age. Though transgenic mouse models of AD develop AD-related amyloid beta (Abeta) and/or tau pathology, gender differences have not been well documented in these models. In this study, we found that female 3xTg-AD transgenic mice expressing mutant APP, presenilin-1 and tau have significantly more aggressive Abeta pathology. We also found an increase in beta-secretase activity and a reduction of neprilysin in female mice compared to males; this suggests that a combination of increased Abeta production and decreased Abeta degradation may contribute to higher risk of AD in females. In contrast to significantly more aggressive Abeta pathology in females, gender did not affect the levels of phosphorylated tau in 3xTg-AD mice. These results point to the involvement of Abeta pathways in the higher risk of AD in women. In addition to comparison of pathology between genders at 9, 16 and 23 months of age, we examined the progression of Abeta pathology at additional age points; i.e., brain Abeta load, intraneuronal oligomeric Abeta distribution and plaque load, in male 3xTg-AD mice at 3, 6, 9, 12, 16, 20 and 23 months of age. These findings confirm progressive Abeta pathology in 3xTg-AD transgenic mice, and provide guidance for their use in therapeutic research

Slow (<0.1 Hz), spontaneous fluctuations in the functional magnetic resonance imaging blood oxygen level-dependent (BOLD) signal have been shown to exhibit phase coherence within functionally related areas of the brain. Surprisingly, this phenomenon appears to transcend levels of consciousness. The genesis of coherent BOLD fluctuations remains to be fully explained. We present a resting state functional connectivity study of a 6-year-old child with a radiologically normal brain imaged both before and after complete section of the corpus callosum for the treatment of intractable epilepsy. Postoperatively, there was a striking loss of interhemispheric BOLD correlations with preserved intrahemispheric correlations. These unique data provide important insights into the relationship between connectional anatomy and functional organization of the human brain. Such observations have the potential to increase our understanding of large-scale brain systems in health and disease as well as improve the treatment of neurologic disorders.

The intercellular spaces between neurons and glia contain an amorphous, negatively charged extracellular matrix (ECM) with the potential to shape and regulate the distribution of many diffusing ions, proteins and drugs. However, little evidence exists for direct regulation of extracellular diffusion by the ECM in living tissue. Here, we demonstrate macromolecule sequestration by an ECM component in vivo, using quantitative diffusion measurements from integrative optical imaging. Diffusion measurements in free solution, supported by confocal imaging and binding assays with cultured cells, were used to characterize the properties of a fluorescently labeled protein, lactoferrin (Lf), and its association with heparin and heparan sulfate in vitro. In vivo diffusion measurements were then performed through an open cranial window over rat somatosensory cortex to measure effective diffusion coefficients (D*) under different conditions, revealing that D* for Lf was reduced approximately 60% by binding to heparan sulfate proteoglycans, a prominent component of the ECM and cell surfaces in brain. Finally, we describe a method for quantifying heparan sulfate binding site density from data for Lf and the structurally similar protein transferrin, allowing us to predict a low micromolar concentration of these binding sites in neocortex, the first estimate in living tissue. Our results have significance for many tissues, because heparan sulfate is synthesized by almost every type of cell in the body. Quantifying ECM effects on diffusion will also aid in the modeling and design of drug delivery strategies for growth factors and viral vectors, some of which are likely to interact with heparan sulfate

We previously generated genome-wide expression data (microarray) from children with septic shock having the potential to lead the field into novel areas of investigation. Herein we seek to validate our data through a bioinformatic approach centered on a validation patient cohort. Forty-two children with a clinical diagnosis of septic shock and 15 normal controls served as the training data set, while 30 separate children with septic shock and 14 separate normal controls served as the test data set. Class prediction modeling using the training data set and the previously reported genome-wide expression signature of pediatric septic shock correctly identified 95-100% of controls and septic shock patients in the test data set, depending on the class prediction algorithm and the gene selection method. Subjecting the test data set to an identical filtering strategy as that used for the training data set, demonstrated 75% concordance between the two gene lists. Subjecting the test data set to a purely statistical filtering strategy, with highly stringent correction for multiple comparisons, demonstrated <50% concordance with the previous gene filtering strategy. However, functional analysis of this statistics-based gene list demonstrated similar functional annotations and signaling pathways as that seen in the training data set. In particular, we validated that pediatric septic shock is characterized by large-scale repression of genes related to zinc homeostasis and lymphocyte function. These data demonstrate that the previously reported genome-wide expression signature of pediatric septic shock is applicable to a validation cohort of patients

Both impulsivity and novelty-seeking have been suggested to be behavioral markers of the propensity to take addictive drugs. However, their relevance for the vulnerability to compulsively seek and take drugs, which is a hallmark feature of addiction, is unknown. We report here that, whereas high reactivity to novelty predicts the propensity to initiate cocaine self-administration, high impulsivity predicts the development of addiction-like behavior in rats, including persistent or compulsive drug-taking in the face of aversive outcomes. This study shows experimental evidence that a shift from impulsivity to compulsivity occurs during the development of addictive behavior, which provides insights into the genesis and neural mechanisms of drug addiction.

In addition to its role as a neurotransmitter, dopamine can stimulate neurite outgrowth and morphological effects upon primary neurons. To investigate the signal transduction mechanisms used by dopamine in developing striatal neurons, we focused upon the effects of activating the dopamine D1 receptor. Using the D1 receptor agonist, SKF38393, we found that Trk neurotrophin receptors were activated in embryonic (E) day 18 striatal neurons. K-252a, a Trk tyrosine kinase inhibitor, and a dopamine D1 receptor antagonist could block the effects of SKF38393. The increase in TrkB phosphorylation was not the result of increased neurotrophin production. Induction of TrkB activity by D1 agonist was accompanied by the phosphorylation of several Trk signaling proteins, including PLCgamma, Akt and MAP kinase. Biotinylation experiments followed by immunostaining by phospho-TrkB specific antibodies indicated that the mechanism involved increased TrkB surface expression by dopamine D1 receptor activation. This increase in cell surface TrkB expression was dependent upon an increase in intracellular Ca2+. These results indicate that stimulation of dopamine D1 receptors can be coupled to the neurotrophin receptor signaling to mediate dopamine's effects upon striatal neurons

In rodent hippocampus, neuronal activity is organized by a 6-10 Hz theta oscillation. The spike timing of hippocampal pyramidal cells with respect to the theta rhythm correlates with an animal's position in space. This correlation has been suggested to indicate an explicit temporal code for position. Alternatively, it may be interpreted as a byproduct of theta-dependent dynamics of spatial information flow in hippocampus. Here we show that place cell activity on different phases of theta reflects positions shifted into the future or past along the animal's trajectory in a two-dimensional environment. The phases encoding future and past positions are consistent across recorded CA1 place cells, indicating a coherent representation at the network level. Consistent theta-dependent time offsets are not simply a consequence of phase-position correlation (phase precession), because they are no longer seen after data randomization that preserves the phase-position relationship. The scale of these time offsets, 100-300 ms, is similar to the latencies of hippocampal activity after sensory input and before motor output, suggesting that offset activity may maintain coherent brain activity in the face of information processing delays

Gating the ion-permeation pathway in K(+) channels requires conformational changes in activation and inactivation gates. Here we have investigated the structural alterations associated with pH-dependent inactivation gating of the KcsA-Kv1.3 K(+) channel using solid-state NMR spectroscopy in direct reference to electrophysiological and pharmacological experiments. Transition of the KcsA-Kv1.3 K(+) channel from a closed state at pH 7.5 to an inactivated state at pH 4.0 revealed distinct structural changes within the pore, correlated with activation-gate opening and inactivation-gate closing. In the inactivated K(+) channel, the selectivity filter adopts a nonconductive structure that was also induced by binding of a pore-blocking tetraphenylporphyrin derivative. The results establish a structural link between inactivation and block of a K(+) channel in a membrane setting.

The Ca2+ release channel ryanodine receptor 2 (RyR2) is required for excitation-contraction coupling in the heart and is also present in the brain. Mutations in RyR2 have been linked to exercise-induced sudden cardiac death (catecholaminergic polymorphic ventricular tachycardia [CPVT]). CPVT-associated RyR2 mutations result in "leaky" RyR2 channels due to the decreased binding of the calstabin2 (FKBP12.6) subunit, which stabilizes the closed state of the channel. We found that mice heterozygous for the R2474S mutation in Ryr2 (Ryr2-R2474S mice) exhibited spontaneous generalized tonic-clonic seizures (which occurred in the absence of cardiac arrhythmias), exercise-induced ventricular arrhythmias, and sudden cardiac death. Treatment with a novel RyR2-specific compound (S107) that enhances the binding of calstabin2 to the mutant Ryr2-R2474S channel inhibited the channel leak and prevented cardiac arrhythmias and raised the seizure threshold. Thus, CPVT-associated mutant leaky Ryr2-R2474S channels in the brain can cause seizures in mice, independent of cardiac arrhythmias. Based on these data, we propose that CPVT is a combined neurocardiac disorder in which leaky RyR2 channels in the brain cause epilepsy, and the same leaky channels in the heart cause exercise-induced sudden cardiac death.

PURPOSE: To validate Bridge Burner, a new brain segmentation algorithm based on thresholding, connectivity, surface detection, and a new operator of constrained growing. MATERIALS AND METHODS: T1-weighted MR images were selected at random from three previous neuroimaging studies to represent a spectrum of system manufacturers, pulse sequences, subject ages, genders, and neurological conditions. The ground truth consisted of brain masks generated manually by a consensus of expert observers. All cases were segmented using a common set of parameters. RESULTS: Bridge Burner segmentation errors were 3.4% +/- 1.3% (volume mismatch) and 0.34 +/- 0.17 mm (surface mismatch). The disagreement among experts was 3.8% +/- 2.0% (volume mismatch) and 0.48 +/- 0.49 mm (surface mismatch). The error obtained using the brain extraction tool (BET), a widely used brain segmentation program, was 8.3% +/- 9.1%. Bridge Burner brain masks are visually similar to the masks generated by human experts. Areas affected by signal intensity nonuniformity artifacts were occasionally undersegmented, and meninges and large sinuses were often falsely classified as the brain tissue. Segmentation of one MRI dataset takes seven seconds. CONCLUSION: The new fully automatic algorithm appears to provide accurate brain segmentation from high-resolution T1-weighted MR images