Faculty Bibliography

Increasing evidence suggests that oxidative injury is involved in the pathogenesis of many age-related neurodegenerative disorders, including Alzheimer's disease (AD). Identifying the protein targets of oxidative stress is critical to determine which proteins may be responsible for the neuronal impairments and subsequent cell death that occurs in AD. In this study, we have applied a high-throughput shotgun proteomic approach to identify the targets of protein carbonylation in both aged and PS1 + AbetaPP transgenic mice. However, because of the inherent difficulties associated with proteomic database searching algorithms, several newly developed bioinformatic tools were implemented to ascertain a probability-based discernment between correct protein assignments and false identifications to improve the accuracy of protein identification. Assigning a probability to each identified peptide/protein allows one to objectively monitor the expression and relative abundance of particular proteins from diverse samples, including tissue from transgenic mice of mixed genetic backgrounds. This robust bioinformatic approach also permits the comparison of proteomic data generated by different laboratories since it is instrument- and database-independent. Applying these statistical models to our initial studies, we detected a total of 117 oxidatively modified (carbonylated) proteins, 59 of which were specifically associated with PS1 + AbetaPP mice. Pathways and network component analyses suggest that there are three major protein networks that could be potentially altered in PS1 + AbetaPP mice as a result of oxidative modifications. These pathways are 1) iNOS-integrin signaling pathway, 2) CRE/CBP transcription regulation and 3) rab-lyst vesicular trafficking. We believe the results of these studies will help establish an initial AD database of oxidatively modified proteins and provide a foundation for the design of future hypothesis driven research in the areas of aging and neurodegeneration

The visual system evolved to process natural images, and the goal of visual neuroscience is to understand the computations it uses to do this. Indeed the goal of any theory of visual function is a model that will predict responses to any stimulus, including natural scenes. It has, however, recently become common to take this fundamental principle one step further: trying to use photographic or cinematographic representations of natural scenes (natural stimuli) as primary probes to explore visual computations. This approach is both challenging and controversial, and we argue that this use of natural images is so fraught with difficulty that it is not useful. Traditional methods for exploring visual computations that use artificial stimuli with carefully selected properties have been and continue to be the most effective tools for visual neuroscience. The proper use of natural stimuli is to test models based on responses to these synthetic stimuli, not to replace them

The tilt aftereffect (TAE) is a visual illusion in which prolonged adaptation to an oriented stimulus causes shifts in subsequent perceived orientations. Historically, neural models of the TAE have explained it as the outcome of response suppression of neurons tuned to the adapting orientation. Recent physiological studies of neurons in primary visual cortex (V1) have confirmed that such response suppression exists. However, it was also found that the preferred orientations of neurons shift away from the adapting orientation. Here we show that adding this second factor to a population coding model of V1 improves the correspondence between neurophysiological data and TAE measurements. According to our model, the shifts in preferred orientation have the opposite effect as response suppression, reducing the magnitude of the TAE.

Granule cell (GC) neurogenesis increases following seizures, and some newborn GCs develop in abnormal locations within the hilus. These ectopic GCs (EGCs) display robust spontaneous and evoked excitatory activity. However, the pattern of afferent input they receive has not been fully defined. This study used electron microscopic immunolabeling to quantitatively evaluate mossy fiber (MF) input to EGCs since MFs densely innervate the hilus normally and undergo sprouting in many animal models of epilepsy. EGC dendrites were examined in tissue from epileptic rats that had initially been treated with pilocarpine to induce status epilepticus and subsequently had spontaneous seizures. MF terminals were labeled with a zinc transporter-3 antibody, and calbindin immunoreactivity was used to label hilar EGCs and GC layer GCs. The pattern of input provided by sprouted MF terminals to EGC dendrites was then compared to the pattern of MF input to GC dendrites in the inner molecular layer (IML), where most sprouted fibers are thought to project. Analysis of EGC dendrites demonstrated that MF terminals represented their predominant source of afferent input: they comprised 63% of all terminals and, on average, occupied 40% and 29% of the dendritic surface in the dorsal and ventral dentate gyrus, respectively, forming frequent synapses. These measures of connectivity were significantly greater than comparable values for MF innervation of GC dendrites located in the IML of the same tissue sections. Thus, EGCs develop a pattern of synaptic connections that could help explain their previously identified predisposition to discharge in epileptiform bursts and suggest that they play an important role in the generation of seizure activity in the dentate gyrus

A ubiquitous feature of the vertebrate anatomy is the segregation of the brain into white and gray matter. Assuming that evolution maximized brain functionality, what is the reason for such segregation? To answer this question, we posit that brain functionality requires high interconnectivity and short conduction delays. Based on this assumption we searched for the optimal brain architecture by comparing different candidate designs. We found that the optimal design depends on the number of neurons, interneuronal connectivity, and axon diameter. In particular, the requirement to connect neurons with many fast axons drives the segregation of the brain into white and gray matter. These results provide a possible explanation for the structure of various regions of the vertebrate brain, such as the mammalian neocortex and neostriatum, the avian telencephalon, and the spinal cord.

The pericardium, although seldom the primary cause of systemic illness, can be involved in almost every type of disease. Pericardial involvement may be subtle and escape detection unless specifically sought, or it can overshadow features of the underlying systemic disease. Suspected pericardial disease is usually initially evaluated with echocardiography. However, magnetic resonance imaging can offer additional valuable information. In addition to the excellent resolution and unlimited imaging planes available for visualization of the entire pericardial sac, the wide field of view allows for evaluation of involvement of adjacent cardiac structures. Dynamic functional imaging and tissue characterization with and without contrast can further characterize disease and provide information regarding concomitant myocardial disease and effects on cardiac motion. The treatment of specific pericardial conditions ultimately depends on the underlying disease process. Magnetic resonance imaging can provide useful information to aid in diagnosis, management, and guidance of therapy for pericardial disease

Various strategies have been developed recently for imparting light sensitivity onto normally insensitive cells. These include expression of natural photosensitive proteins, photolysis of caged agonists of native cell surface receptors and photoswitching of isomerizable tethered ligands that act on specially engineered ion channels and receptor targets. The development of chemical tools for optically stimulating or inhibiting signaling proteins has particular relevance for the nervous system, where precise, noninvasive control is an experimental and medical necessity.

Quantitative determination of cerebral blood volume (CBV) is important for understanding brain physiology and pathophysiology. In this work, a novel approach is presented for accurate measurement of absolute CBV (aCBV) using vascular-space-occupancy (VASO) MRI, a blood-nulling pulse sequence, in combination with the T(1) shortening property of Gd-DTPA. Two VASO images with identical imaging parameters are acquired before and after contrast agent injection, resulting in a subtracted image that reflects the amount of blood present in the brain, i.e., CBV. With an additional normalizing factor, aCBV in units of milliliters of blood per 100 mL of brain can be estimated. Experimental results at 1.5 and 3 T systems showed that aCBV maps with high spatial resolution can be obtained with high reproducibility. The averaged aCBV values in gray and white matter were 5.5 +/- 0.2 and 1.4 +/- 0.1 mL of blood/100 mL of brain, respectively. Compared to dynamic susceptibility contrast techniques, VASO MRI is based upon a relatively straightforward theory and the calculation of CBV does not require measurement of an arterial input function. In comparison with previous pre/postcontrast difference approaches, VASO MRI provides maximal signal difference between pre- and postcontrast situation and does not require the use of whole blood for signal normalization