scholarly journals Photoreceptor Cell Rescue at Early and Late RPE-Cell Transplantation Periods During Retinal Disease in RCS Dystrophic Rats

1991 ◽  
Vol 2 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Harold J. Sheedlo ◽  
Linxi Li ◽  
James E. Turner
Keyword(s):  
Cell Transplantation ◽  
Photoreceptor Cell ◽  
Retinal Disease ◽  
Late Time ◽  
Early Stages ◽  
Time Periods

Maximal PRC rescue was affected by RPE-cell transplantation in retinas of RCS dystrophic rats at early stages of the retinal disease, while little or no rescue was detected when transplantation was performed at late time periods.

scholarly journals Quantifiable In Vivo Imaging Biomarkers of Retinal Regeneration by Photoreceptor Cell Transplantation

2019 ◽  
Author(s):  
Ying V. Liu ◽  
Simrat Sodhi ◽  
Gilbert Xue ◽  
Derek Teng ◽  
Dzhalal Agakishiev ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
Photoreceptor Cell ◽  
Retinal Cell ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Multiple Imaging ◽  
Green Fluorescent ◽  
Serial Evaluation

AbstractPurposeShort-term improvements in retinal anatomy are known to occur in preclinical models of photoreceptor transplantation. However, correlative changes over the long term are poorly understood. We aimed to develop a quantifiable imaging biomarker grading scheme, using non-invasive multimodal confocal scanning laser ophthalmoscopy (cSLO) imaging, to enable serial evaluation of photoreceptor transplantation over the long term.MethodsYellow-green fluorescent microspheres were transplanted into the vitreous cavity and/or subretinal space of C57/BL6J mice. Photoreceptor cell suspensions or sheets from rhodopsin-green fluorescent protein mice were transplanted subretinally, into either NOD.CB17-Prkdcscid/J or C3H/HeJ-Pde6brd1 mice. Multimodal cSLO imaging was performed serially for up to three months after transplantation. Imaging biomarkers were scored, and a grade was defined for each eye by integrating the scores. Image grades were correlated with immunohistochemistry (IHC) data.ResultsMultimodal imaging enabled the extraction of quantitative imaging biomarkers including graft size, GFP intensity, graft length, on-target graft placement, intra-graft lamination, hemorrhage, retinal atrophy, and peri-retinal proliferation. Migration of transplanted material was observed. Changes in biomarker scores and grades were detected in 13/16 and 7/16 eyes, respectively. A high correlation was found between image grades and IHC parameters.ConclusionsSerial evaluation of multiple imaging biomarkers, when integrated into a per-eye grading scheme, enabled comprehensive tracking of longitudinal changes in photoreceptor cell grafts over time. The application of systematic multimodal in vivo imaging could be useful in increasing the efficiency of preclinical retinal cell transplantation studies in rodents and other animal models.

scholarly journals Quantifiable In Vivo Imaging Biomarkers of Retinal Regeneration by Photoreceptor Cell Transplantation

2020 ◽  
Vol 9 (7) ◽  
pp. 5
Author(s):  
Ying V. Liu ◽  
Simrat K. Sodhi ◽  
Gilbert Xue ◽  
Derek Teng ◽  
Dzhalal Agakishiev ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
In Vivo Imaging ◽  
Photoreceptor Cell ◽  
Imaging Biomarkers ◽  
Retinal Regeneration

scholarly journals Gene Therapy and Stem Cell Transplantation in Retinal Disease: The New Frontier

Ophthalmology ◽  
2016 ◽  
Vol 123 (10) ◽  
pp. S98-S106 ◽  
Author(s):  
Robert E. MacLaren ◽  
Jean Bennett ◽  
Steven D. Schwartz
Keyword(s):  
Gene Therapy ◽  
Stem Cell ◽  
Stem Cell Transplantation ◽  
Cell Transplantation ◽  
Retinal Disease ◽  
New Frontier

A New Deconvolution Technique Based on Pressure-Derivative Data for Pressure-Transient-Test Interpretation

SPE Journal ◽  
2011 ◽  
Vol 17 (01) ◽  
pp. 307-320 ◽  
Author(s):  
Mustafa Onur ◽  
Fikri J. Kuchuk
Keyword(s):  
Small Error ◽  
New Method ◽  
Late Time ◽  
Reservoir Pressure ◽  
Test Interpretation ◽  
Pressure Derivative ◽  
Pressure Transient ◽  
Significant Difference ◽  
Time Periods ◽  
Pressure Transient Test

Summary In this paper, we present a new deconvolution method that removes the dependency of the deconvolved constant-rate drawdown responses on the initial reservoir pressure. It is well known that the late-time periods in particular of the deconvolved responses from the recent pressure-rate deconvolution methods are dependent on the initial reservoir pressure. A small error in the initial reservoir pressure could make a significant difference in the late-time periods of the deconvolved responses that can lead to an incorrect interpretation model, particularly misinterpretation of the boundaries. The new method presented is based on pressure-derivative data rather than pressure data that are used in all published deconvolution algorithms. Using pressure-derivative data in deconvolution leads to a nonlinear least-squares objective function that is different from those used in the earlier deconvolution methods and eliminates the dependency of the deconvolved responses on the initial reservoir pressure. Therefore, the new method minimizes incorrect interpretation because of an error or uncertainty in the initial reservoir pressure. We apply the new method to both simulated and field pressure-transient data sets. The results show that the new method offers a significant advantage over the earlier deconvolution methods for pressure-transient-test interpretation in cases where the initial reservoir pressure is unknown or uncertain.

Cell Transplantation as a Treatment for Retinal Disease

2001 ◽  
Vol 20 (4) ◽  
pp. 415-449 ◽  
Author(s):  
R.D Lund ◽  
A.S.L Kwan ◽  
D.J Keegan ◽  
Y Sauvé ◽  
P.J Coffey ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
Retinal Disease

scholarly journals Modelling and rescue of RP2 Retinitis Pigmentosa using iPSC Derived Retinal Organoids

2020 ◽  
Author(s):  
Amelia Lane ◽  
Katarina Jovanovic ◽  
Ciara Shortall ◽  
Daniele Ottaviani ◽  
Anna Brugulat Panes ◽  
...  
Keyword(s):  
Cell Death ◽  
Retinitis Pigmentosa ◽  
Photoreceptor Cell ◽  
Outer Nuclear Layer ◽  
Disease Model ◽  
Retinal Disease ◽  
Severe Form ◽  
Rod Photoreceptor ◽  
Knock Out ◽  
Induced Pluripotent

SummaryRP2 mutations cause a severe form of X-linked retinitis pigmentosa (XLRP). The mechanism of RP2 associated retinal degeneration in humans is unclear, and animal models of RP2 XLRP do not recapitulate this severe phenotype. Here, we developed gene edited isogenic RP2 knock-out (RP2 KO) induced pluripotent stem cells (iPSC) and RP2 patient derived iPSC to produce 3D retinal organoids as a human retinal disease model. Strikingly, the RP2 KO and RP2 patient derived organoids showed a peak in rod photoreceptor cell death at day 150 (D150) with subsequent thinning of the organoid outer nuclear layer (ONL) by D180 of culture. AAV mediated gene augmentation with human RP2 rescued the degeneration phenotype of the RP2 KO organoids, to prevent ONL thinning and restore rhodopsin expression. Notably, these data show that 3D retinal organoids can be used to model photoreceptor degeneration and test potential therapies to prevent photoreceptor cell death.

scholarly journals Dynamical Simulation of Effective Stem Cell Transplantation for Modulation of Microglia Responses in Stroke Treatment

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 404
Author(s):  
Awatif Jahman Alqarni ◽  
Azmin Sham Rambely ◽  
Ishak Hashim
Keyword(s):  
Mathematical Model ◽  
Stem Cells ◽  
Stem Cell ◽  
Stem Cell Transplantation ◽  
Cell Transplantation ◽  
Biological Information ◽  
Stroke Treatment ◽  
Early Stages ◽  
The Brain

Stem cell transplantation therapy may inhibit inflammation during stroke and increase the presence of healthy cells in the brain. The novelty of this work, is to introduce a new mathematical model of stem cells transplanted to treat stroke. This manuscript studies the stability of the mathematical model by using the current biological information on stem cell therapy as a possible treatment for inflammation from microglia during stroke. The model is proposed to represent the dynamics of various immune brain cells (resting microglia, pro-inflammation microglia, and anti-inflammation microglia), brain tissue damage and stem cells transplanted. This model is based on a set of five ordinary differential equations and explores the beneficial effects of stem cells transplanted at early stages of inflammation during stroke. The Runge–Kutta method is used to discuss the model analytically and solve it numerically. The results of our simulations are qualitatively consistent with those observed in experiments in vivo, suggesting that the transplanted stem cells could contribute to the increase in the rate of ant-inflammatory microglia and decrease the damage from pro-inflammatory microglia. It is found from the analysis and simulation results that stem cell transplantation can help stroke patients by modulation of the immune response during a stroke and decrease the damage on the brain. In conclusion, this approach may increase the contributions of stem cells transplanted during inflammation therapy in stroke and help to study various therapeutic strategies for stem cells to reduce stroke damage at the early stages.

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