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Dive into the research topics where Rebecca L Pfeiffer is active.

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Featured researches published by Rebecca L Pfeiffer.


Experimental Eye Research | 2016

Retinal remodeling in human retinitis pigmentosa.

Bryan W. Jones; Rebecca L Pfeiffer; William D. Ferrell; Carl B. Watt; Michael F. Marmor; Robert E. Marc

Retinitis Pigmentosa (RP) in the human is a progressive, currently irreversible neural degenerative disease usually caused by gene defects that disrupt the function or architecture of the photoreceptors. While RP can initially be a disease of photoreceptors, there is increasing evidence that the inner retina becomes progressively disorganized as the outer retina degenerates. These alterations have been extensively described in animal models, but remodeling in humans has not been as well characterized. This study, using computational molecular phenotyping (CMP) seeks to advance our understanding of the retinal remodeling process in humans. We describe cone mediated preservation of overall topology, retinal reprogramming in the earliest stages of the disease in retinal bipolar cells, and alterations in both small molecule and protein signatures of neurons and glia. Furthermore, while Müller glia appear to be some of the last cells left in the degenerate retina, they are also one of the first cell classes in the neural retina to respond to stress which may reveal mechanisms related to remodeling and cell death in other retinal cell classes. Also fundamentally important is the finding that retinal network topologies are altered. Our results suggest interventions that presume substantial preservation of the neural retina will likely fail in late stages of the disease. Even early intervention offers no guarantee that the interventions will be immune to progressive remodeling. Fundamental work in the biology and mechanisms of disease progression are needed to support vision rescue strategies.


ACS Chemical Neuroscience | 2014

Retinal Prosthetics, Optogenetics, and Chemical Photoswitches

Robert E. Marc; Rebecca L Pfeiffer; Bryan W. Jones

Three technologies have emerged as therapies to restore light sensing to profoundly blind patients suffering from late-stage retinal degenerations: (1) retinal prosthetics, (2) optogenetics, and (3) chemical photoswitches. Prosthetics are the most mature and the only approach in clinical practice. Prosthetic implants require complex surgical intervention and provide only limited visual resolution but can potentially restore navigational ability to many blind patients. Optogenetics uses viral delivery of type 1 opsin genes from prokaryotes or eukaryote algae to restore light responses in survivor neurons. Targeting and expression remain major problems, but are potentially soluble. Importantly, optogenetics could provide the ultimate in high-resolution vision due to the long persistence of gene expression achieved in animal models. Nevertheless, optogenetics remains challenging to implement in human eyes with large volumes, complex disease progression, and physical barriers to viral penetration. Now, a new generation of photochromic ligands or chemical photoswitches (azobenzene-quaternary ammonium derivatives) can be injected into a degenerated mouse eye and, in minutes to hours, activate light responses in neurons. These photoswitches offer the potential for rapidly and reversibly screening the vision restoration expected in an individual patient. Chemical photoswitch variants that persist in the cell membrane could make them a simple therapy of choice, with resolution and sensitivity equivalent to optogenetics approaches. A major complexity in treating retinal degenerations is retinal remodeling: pathologic network rewiring, molecular reprogramming, and cell death that compromise signaling in the surviving retina. Remodeling forces a choice between upstream and downstream targeting, each engaging different benefits and defects. Prosthetics and optogenetics can be implemented in either mode, but the use of chemical photoswitches is currently limited to downstream implementations. Even so, given the high density of human foveal ganglion cells, the ultimate chemical photoswitch treatment could deliver cost-effective, high-resolution vision for the blind.


Frontiers in Cellular Neuroscience | 2016

Retinal remodeling and metabolic alterations in human AMD

Bryan W. Jones; Rebecca L Pfeiffer; William D. Ferrell; Carl B. Watt; James Tucker; Robert E. Marc

Age-related macular degeneration (AMD) is a progressive retinal degeneration resulting in central visual field loss, ultimately causing debilitating blindness. AMD affects 18% of Americans from 65 to 74, 30% older than 74 years of age and is the leading cause of severe vision loss and blindness in Western populations. While many genetic and environmental risk factors are known for AMD, we currently know less about the mechanisms mediating disease progression. The pathways and mechanisms through which genetic and non-genetic risk factors modulate development of AMD pathogenesis remain largely unexplored. Moreover, current treatment for AMD is palliative and limited to wet/exudative forms. Retina is a complex, heterocellular tissue and most retinal cell classes are impacted or altered in AMD. Defining disease and stage-specific cytoarchitectural and metabolic responses in AMD is critical for highlighting targets for intervention. The goal of this article is to illustrate cell types impacted in AMD and demonstrate the implications of those changes, likely beginning in the retinal pigment epithelium (RPE), for remodeling of the the neural retina. Tracking heterocellular responses in disease progression is best achieved with computational molecular phenotyping (CMP), a tool that enables acquisition of a small molecule fingerprint for every cell in the retina. CMP uncovered critical cellular and molecular pathologies (remodeling and reprogramming) in progressive retinal degenerations such as retinitis pigmentosa (RP). We now applied these approaches to normal human and AMD tissues mapping progression of cellular and molecular changes in AMD retinas, including late-stage forms of the disease.


Investigative Ophthalmology & Visual Science | 2017

Pattern recognition analysis reveals unique contrast sensitivity isocontours using static perimetry thresholds across the visual field

Jack Phu; Sieu K. Khuu; Lisa Nivison-Smith; Barbara Zangerl; Agnes Yiu Jeung Choi; Bryan W. Jones; Rebecca L Pfeiffer; Robert E. Marc; Michael Kalloniatis

Purpose To determine the locus of test locations that exhibit statistically similar age-related decline in sensitivity to light increments and age-corrected contrast sensitivity isocontours (CSIs) across the central visual field (VF). We compared these CSIs with test point clusters used by the Glaucoma Hemifield Test (GHT). Methods Sixty healthy observers underwent testing on the Humphrey Field Analyzer 30-2 test grid using Goldmann (G) stimulus sizes I-V. Age-correction factors for GI-V were determined using linear regression analysis. Pattern recognition analysis was used to cluster test locations across the VF exhibiting equal age-related sensitivity decline (age-related CSIs), and points of equal age-corrected sensitivity (age-corrected CSIs) for GI-V. Results There was a small but significant test size–dependent sensitivity decline with age, with smaller stimuli declining more rapidly. Age-related decline in sensitivity was more rapid in the periphery. A greater number of unique age-related CSIs was revealed when using smaller stimuli, particularly in the mid-periphery. Cluster analysis of age-corrected sensitivity thresholds revealed unique CSIs for GI-V, with smaller stimuli having a greater number of unique clusters. Zones examined by the GHT consisted of test locations that did not necessarily belong to the same CSI, particularly in the periphery. Conclusions Cluster analysis reveals statistically significant groups of test locations within the 30-2 test grid exhibiting the same age-related decline. CSIs facilitate pooling of sensitivities to reduce the variability of individual test locations. These CSIs could guide future structure-function and alternate hemifield asymmetry analyses by comparing matched areas of similar sensitivity signatures.


Investigative Ophthalmology & Visual Science | 2017

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye.

Nayuta Yoshioka; Barbara Zangerl; Lisa Nivison-Smith; Sieu K. Khuu; Bryan W. Jones; Rebecca L Pfeiffer; Robert E. Marc; Michael Kalloniatis

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease.


Experimental Eye Research | 2016

Müller cell metabolic chaos during retinal degeneration

Rebecca L Pfeiffer; Robert E. Marc; Mineo Kondo; Hiroko Terasaki; Bryan W. Jones

Müller cells play a critical role in retinal metabolism and are among the first cells to demonstrate metabolic changes in retinal stress or disease. The timing, extent, regulation, and impacts of these changes are not yet known. We evaluated metabolic phenotypes of Müller cells in the degenerating retina. Retinas harvested from wild-type (WT) and rhodopsin Tg P347L rabbits were fixed in mixed aldehydes and resin embedded for computational molecular phenotyping (CMP). CMP facilitates small molecule fingerprinting of every cell in the retina, allowing evaluation of metabolite levels in single cells. CMP revealed signature variations in metabolite levels across Müller cells from TgP347L retina. In brief, neighboring Müller cells demonstrated variability in taurine, glutamate, glutamine, glutathione, glutamine synthetase (GS), and CRALBP. This variability showed no correlation across metabolites, implying the changes are functionally chaotic rather than simply heterogeneous. The inability of any clustering algorithm to classify Müller cell as a single class in the TgP347L retina is a formal proof of metabolic variability in the present in degenerating retina. Although retinal degeneration is certainly the trigger, Müller cell metabolic alterations are not a coherent response to the microenvironment. And while GS is believed to be the primary enzyme responsible for the conversion of glutamate to glutamine in the retina, alternative pathways appear to be unmasked in degenerating retina. Somehow, long term remodeling involves loss of Müller cell coordination and identity, which has negative implications for therapeutic interventions that target neurons alone.


Journal of Neuroscience Methods | 2012

Serial section registration of axonal confocal microscopy datasets for long-range neural circuit reconstruction

Luke Hogrebe; António R. C. Paiva; Elizabeth Jurrus; Cameron Christensen; Michael J. Bridge; Li Dai; Rebecca L Pfeiffer; Patrick R. Hof; Badrinath Roysam; Julie R. Korenberg; Tolga Tasdizen

In the context of long-range digital neural circuit reconstruction, this paper investigates an approach for registering axons across histological serial sections. Tracing distinctly labeled axons over large distances allows neuroscientists to study very explicit relationships between the brains complex interconnects and, for example, diseases or aberrant development. Large scale histological analysis requires, however, that the tissue be cut into sections. In immunohistochemical studies thin sections are easily distorted due to the cutting, preparation, and slide mounting processes. In this work we target the registration of thin serial sections containing axons. Sections are first traced to extract axon centerlines, and these traces are used to define registration landmarks where they intersect section boundaries. The trace data also provides distinguishing information regarding an axons size and orientation within a section. We propose the use of these features when pairing axons across sections in addition to utilizing the spatial relationships among the landmarks. The global rotation and translation of an unregistered section are accounted for using a random sample consensus (RANSAC) based technique. An iterative nonrigid refinement process using B-spline warping is then used to reconnect axons and produce the sought after connectivity information.


bioRxiv | 2018

Neural crest cells regulate optic cup morphogenesis by promoting extracellular matrix assembly

Chase Dallas Bryan; Rebecca L Pfeiffer; Bryan W. Jones; Kristen M. Kwan

The interactions between an organ and its surrounding environment are critical in regulating its development. In vertebrates, neural crest and mesodermal mesenchymal cells have been observed close to the eye during development, and mutations affecting this periocular mesenchyme can cause defects in early eye development, yet the underlying mechanism has been unknown. Here, using timelapse microscopy and four-dimensional cell tracking in zebrafish, we establish that genetic loss of neural crest impairs cell movements within the optic vesicle. At the ultrastructural level, neural crest cells are required for basement membrane formation specifically around the retinal pigment epithelium. Neural crest cells express the extracellular matrix crosslinking protein nidogen and, strikingly, ectopically expressing nidogen in the absence of neural crest partially restores optic cup morphogenesis. These results demonstrate that the neural crest is required for local establishment of ocular extracellular matrix superstructure, which in turn drives optic cup morphogenesis.


bioRxiv | 2018

Heterocellular coupling between amacrine cell and ganglion cells

Robert E. Marc; Crystal Sigulinsky; Rebecca L Pfeiffer; Daniel Emrich; James R. Anderson; Bryan W. Jones

All superclasses of retinal neurons display some form of electrical coupling including the key neurons of the inner plexiform layer: bipolar cells (BCs), amacrine or axonal cells (ACs) and ganglion cells (GCs). However, coupling varies extensively by class. For example, mammalian rod bipolar cells form no gap junctions at all, while all cone bipolar cells form class-specific coupling arrays, many of them homocellular in-superclass arrays. Ganglion cells are unique in that classes with coupling predominantly form heterocellular cross-class arrays of ganglion cell::amacrine cell (GC::AC) coupling in the mammalian retina. Ganglion cells are the least frequent superclass in the inner plexiform layer and GC::AC gap junctions are sparsely arrayed amidst massive cohorts of AC::AC, bipolar cell BC::BC, and AC::BC gap junctions. Many of these gap junctions and most ganglion cell gap junctions are suboptical, complicating analysis of specific ganglion cells. High resolution 2 nm TEM analysis of rabbit retinal connectome RC1 allows quantitative GC::AC coupling maps of identified ganglion cells. Ganglion cells classes apparently avoid direct cross-class homocellular coupling altogether even though they have opportunities via direct membrane touches, while transient OFF alpha ganglion cells and transient ON directionally selective (DS) ganglion cells are strongly coupled to distinct amacrine / axonal cell cohorts. A key feature of coupled ganglion cells is intercellular metabolite flux. Most GC::AC coupling involves GABAergic cells (γ+ amacrine cells), which results in significant GABA flux into ganglion cells. Surveying GABA coupling signatures in the ganglion cell layer across species suggests that the majority of vertebrate retinas engage in GC::AC coupling. Multi-hop synaptic queries of the entire RC1 connectome clearly profiles the coupled amacrine and axonal cells. Photic drive polarities and source bipolar cell class selec-tivities are tightly matched across coupled cells. OFF alpha ganglion cells are coupled to OFF γ+ amacrine cells and transient ON DS ganglion cells are coupled to ON γ+ amacrine cells including a large interstitial axonal cell (IAC). Synaptic tabulations show close matches between the classes of bipolar cells sampled by the coupled amacrine and ganglion cells. Further, both ON and OFF coupling ganglion networks show a common theme: synaptic asymmetry whereby the coupled γ+ neurons are also presynaptic to ganglion cell dendrites from different classes of ganglion cells outside the coupled set. In effect, these heterocellular coupling patterns enable an excited ganglion cell to directly inhibit nearby ganglion cells of different classes. Similarly, coupled γ+ amacrine cells engaged in feedback networks can leverage the additional gain of bipolar cell synapses in shaping the signaling of a spectrum of downstream targets based on their own selective coupling with ganglion cells.


Investigative Ophthalmology & Visual Science | 2017

Predicting Age-related Changes with High Accuracy using a Pattern Recognition Derived Retinal Ganglion Cell Regression Model

Nayuta Yoshioka; Barbara Zangerl; Lisa Nivison-Smith; Sieu K. Khuu; Bryan W. Jones; Rebecca L Pfeiffer; Robert E. Marc; Michael Kalloniatis

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Barbara Zangerl

University of New South Wales

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Lisa Nivison-Smith

University of New South Wales

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Michael Kalloniatis

University of New South Wales

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Sieu K. Khuu

University of New South Wales

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