Pathophysiology and Translational Research of Retinal Diseases

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 5449

Special Issue Editors


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Guest Editor
1. Ruth & Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa 3200003, Israel
2. Department of Ophthalmology, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
Interests: retina; phototransduction; clinical electrophysiology of vision; imaging; inherited retinal dystrophy; retinal drug toxicity; retinal light damage

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Guest Editor
Faculty of Life Sciences, School of Optometry and Vision Science, Bar-Ilan University, Ramat-Gan 52900, Israel
Interests: ophthalmology; retinal degeneration; vision science; retinal electrophysiology; retinal prosthesis; vision restoration

Special Issue Information

Dear Colleagues,

The retina is the gate to visual perception. Photoreceptors convert light, entering the eye from the outside world, into neural signals which are then further processed in the inner retina and then transformed into patterns of electrical activity in the ganglion cells. The visual information is then transmitted to the brain for further analysis, eventually leading to the perception of pattern, color, and space localization.

Most cases of severe visual loss originate in the retina, including inherited disorders and acquired diseases. Most inherited visual disorders are caused by mutations in specific genes coding for proteins associated with the phototransduction process that involves the retinal pigment epithelium (RPE) cells and the photoreceptors. Other mutated genes encode for proteins associated with signal transduction from the photoreceptors to bipolar cells. Some of these diseases are degenerative in nature, eventually leading to blindness (e.g., retinitis pigmentosa), and others are associated with a stationary visual deficit (e.g., congenital stationary night blindness (CSNB) and achromatopsia). Acquired diseases are usually multifactorial and caused by genetic predisposition and non-genetic risk factors such as stress, exposure to light, diet, and more. An example of such a visual disorder is age-related macular dystrophy (AMD), the leading cause of blindness in the Western world, which is characterized by loss of central vision with preservation of peripheral vision.

Vision loss is devastating to the patient and is associated with a heavy burden to the family, to society, and to the economy. Therefore, many academic groups and biomedical companies are dedicated to studying the cellular and molecular mechanisms underlying retinal diseases and to developing novel therapeutic approaches.

This Special Issue of Bioengineering is dedicated to manuscripts focused on pathophysiology and translational research of retinal diseases. We accept manuscripts associated with basic, applied, and translational research on all aspects of retinal diseases, including inherited disorders and acquired diseases. Topics of interest include (but are not limited to) retinal pathophysiology, retinal cell biology, biological and non-biological means for vision restoration, and other related topics.

Prof. Dr. Ido Perlman
Prof. Dr. Yossi Mandel
Guest Editors

Manuscript Submission Information

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Keywords

  • retinal diseases
  • pathophysiological mechanisms
  • novel treatments
  • visual restoration

Published Papers (4 papers)

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Research

17 pages, 2058 KiB  
Article
Deep Learning-Assisted Measurements of Photoreceptor Ellipsoid Zone Area and Outer Segment Volume as Biomarkers for Retinitis Pigmentosa
by Yi-Zhong Wang, Katherine Juroch and David Geoffrey Birch
Bioengineering 2023, 10(12), 1394; https://doi.org/10.3390/bioengineering10121394 - 06 Dec 2023
Viewed by 868
Abstract
The manual segmentation of retinal layers from OCT scan images is time-consuming and costly. The deep learning approach has potential for the automatic delineation of retinal layers to significantly reduce the burden of human graders. In this study, we compared deep learning model [...] Read more.
The manual segmentation of retinal layers from OCT scan images is time-consuming and costly. The deep learning approach has potential for the automatic delineation of retinal layers to significantly reduce the burden of human graders. In this study, we compared deep learning model (DLM) segmentation with manual correction (DLM-MC) to conventional manual grading (MG) for the measurements of the photoreceptor ellipsoid zone (EZ) area and outer segment (OS) volume in retinitis pigmentosa (RP) to assess whether DLM-MC can be a new gold standard for retinal layer segmentation and for the measurement of retinal layer metrics. Ninety-six high-speed 9 mm 31-line volume scans obtained from 48 patients with RPGR-associated XLRP were selected based on the following criteria: the presence of an EZ band within the scan limit and a detectable EZ in at least three B-scans in a volume scan. All the B-scan images in each volume scan were manually segmented for the EZ and proximal retinal pigment epithelium (pRPE) by two experienced human graders to serve as the ground truth for comparison. The test volume scans were also segmented by a DLM and then manually corrected for EZ and pRPE by the same two graders to obtain DLM-MC segmentation. The EZ area and OS volume were determined by interpolating the discrete two-dimensional B-scan EZ-pRPE layer over the scan area. Dice similarity, Bland–Altman analysis, correlation, and linear regression analyses were conducted to assess the agreement between DLM-MC and MG for the EZ area and OS volume measurements. For the EZ area, the overall mean dice score (SD) between DLM-MC and MG was 0.8524 (0.0821), which was comparable to 0.8417 (0.1111) between two MGs. For the EZ area > 1 mm2, the average dice score increased to 0.8799 (0.0614). When comparing DLM-MC to MG, the Bland–Altman plots revealed a mean difference (SE) of 0.0132 (0.0953) mm2 and a coefficient of repeatability (CoR) of 1.8303 mm2 for the EZ area and a mean difference (SE) of 0.0080 (0.0020) mm3 and a CoR of 0.0381 mm3 for the OS volume. The correlation coefficients (95% CI) were 0.9928 (0.9892–0.9952) and 0.9938 (0.9906–0.9958) for the EZ area and OS volume, respectively. The linear regression slopes (95% CI) were 0.9598 (0.9399–0.9797) and 1.0104 (0.9909–1.0298), respectively. The results from this study suggest that the manual correction of deep learning model segmentation can generate EZ area and OS volume measurements in excellent agreement with those of conventional manual grading in RP. Because DLM-MC is more efficient for retinal layer segmentation from OCT scan images, it has the potential to reduce the burden of human graders in obtaining quantitative measurements of biomarkers for assessing disease progression and treatment outcomes in RP. Full article
(This article belongs to the Special Issue Pathophysiology and Translational Research of Retinal Diseases)
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19 pages, 2780 KiB  
Article
Artificial Vision: The High-Frequency Electrical Stimulation of the Blind Mouse Retina Decay Spike Generation and Electrogenically Clamped Intracellular Ca2+ at Elevated Levels
by Lucia Peiroten, Eberhart Zrenner and Wadood Haq
Bioengineering 2023, 10(10), 1208; https://doi.org/10.3390/bioengineering10101208 - 16 Oct 2023
Cited by 1 | Viewed by 1229
Abstract
Background: The electrical stimulation (stim) of retinal neurons enables blind patients to experience limited artificial vision. A rapid response outage of the stimulated ganglion cells (GCs) allows for a low visual sensation rate. Hence, to elucidate the underlying mechanism, we investigated different stim [...] Read more.
Background: The electrical stimulation (stim) of retinal neurons enables blind patients to experience limited artificial vision. A rapid response outage of the stimulated ganglion cells (GCs) allows for a low visual sensation rate. Hence, to elucidate the underlying mechanism, we investigated different stim parameters and the role of the neuromodulator calcium (Ca2+). Methods: Subretinal stim was applied on retinal explants (blind rd1 mouse) using multielectrode arrays (MEAs) or single metal electrodes, and the GC activity was recorded using Ca2+ imaging or MEA, respectively. Stim parameters, including voltage, phase polarity, and frequency, were investigated using specific blockers. Results: At lower stim frequencies (<5 Hz), GCs responded synaptically according to the stim pulses (stim: biphasic, cathodic-first, −1.6/+1.5 V). In contrast, higher stim frequencies (≥5 Hz) also activated GCs directly and induced a rapid GC spike response outage (<500 ms, MEA recordings), while in Ca2+ imaging at the same frequencies, increased intracellular Ca2+ levels were observed. Conclusions: Our study elucidated the mechanisms involved in stim-dependent GC spike response outage: sustained high-frequency stim-induced spike outage, accompanied by electrogenically clamped intracellular Ca2+ levels at elevated levels. These findings will guide future studies optimizing stim paradigms for electrical implant applications for interfacing neurons. Full article
(This article belongs to the Special Issue Pathophysiology and Translational Research of Retinal Diseases)
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11 pages, 3787 KiB  
Article
The Variation of Electrical Pulse Duration Elicits Reliable Network-Mediated Responses of Retinal Ganglion Cells in Normal, Not in Degenerate Primate Retinas
by Seongkwang Cha, Jungryul Ahn, Seong-Woo Kim, Kwang-Eon Choi, Yongseok Yoo, Heejong Eom, Donggwan Shin and Yong Sook Goo
Bioengineering 2023, 10(10), 1135; https://doi.org/10.3390/bioengineering10101135 - 27 Sep 2023
Cited by 1 | Viewed by 802
Abstract
This study aims to investigate the efficacy of electrical stimulation by comparing network-mediated RGC responses in normal and degenerate retinas using a N-methyl-N-nitrosourea (MNU)-induced non-human primate (NHPs) retinitis pigmentosa (RP) model. Adult cynomolgus monkeys were used for normal and outer retinal degeneration (RD) [...] Read more.
This study aims to investigate the efficacy of electrical stimulation by comparing network-mediated RGC responses in normal and degenerate retinas using a N-methyl-N-nitrosourea (MNU)-induced non-human primate (NHPs) retinitis pigmentosa (RP) model. Adult cynomolgus monkeys were used for normal and outer retinal degeneration (RD) induced by MNU. The network-mediated RGC responses were recorded from the peripheral retina mounted on an 8 × 8 multielectrode array (MEA). The amplitude and duration of biphasic current pulses were modulated from 1 to 50 μA and 500 to 4000 μs, respectively. The threshold charge density for eliciting a network-mediated RGC response was higher in the RD monkeys than in the normal monkeys (1.47 ± 0.13 mC/cm2 vs. 1.06 ± 0.09 mC/cm2, p < 0.05) at a 500 μs pulse duration. The monkeys required a higher charge density than rodents among the RD models (monkeys; 1.47 ± 0.13 mC/cm2, mouse; 1.04 ± 0.09 mC/cm2, and rat; 1.16 ± 0.16 mC/cm2, p < 0.01). Increasing the pulse amplitude and pulse duration elicited more RGC spikes in the normal primate retinas. However, only pulse amplitude variation elicited more RGC spikes in degenerate primate retinas. Therefore, the pulse strategy for primate RD retinas should be optimized, eventually contributing to retinal prosthetics. Given that RD NHP RGCs are not sensitive to pulse duration, using shorter pulses may potentially be a more charge-effective approach for retinal prosthetics. Full article
(This article belongs to the Special Issue Pathophysiology and Translational Research of Retinal Diseases)
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15 pages, 2100 KiB  
Article
Using Micro-Electrode-Array Recordings and Retinal Disease Models to Elucidate Visual Functions: Simultaneous Recording of Local Electroretinograms and Ganglion Cell Action Potentials Reveals the Origin of Retinal Oscillatory Potentials
by Wadood Haq, Eberhart Zrenner, Marius Ueffing and François Paquet-Durand
Bioengineering 2023, 10(6), 725; https://doi.org/10.3390/bioengineering10060725 - 15 Jun 2023
Cited by 2 | Viewed by 1837
Abstract
Background: The electroretinogram (ERG) is an essential diagnostic tool for visual function, both in clinical and research settings. Here, we establish an advanced in vitro approach to assess cell-type-specific ERG signal components. Methods: Retinal explant cultures, maintained under entirely controlled conditions, were derived [...] Read more.
Background: The electroretinogram (ERG) is an essential diagnostic tool for visual function, both in clinical and research settings. Here, we establish an advanced in vitro approach to assess cell-type-specific ERG signal components. Methods: Retinal explant cultures, maintained under entirely controlled conditions, were derived from wild-type mice and rd10 rod- and cpfl1 cone-degeneration mouse models. Local micro-ERG (µERG) and simultaneous ganglion cell (GC) recordings were obtained from the retinal explants using multi-electrode arrays. Band-pass filtering was employed to distinguish photoreceptor, bipolar cell, amacrine cell (AC), and GC responses. Results: Scotopic and photopic stimulation discriminated between rod and cone responses in wild-type and mutant retina. The 25 kHz sampling rate allowed the visualization of oscillatory potentials (OPs) in extraordinary detail, revealing temporal correlations between OPs and GC responses. Pharmacological isolation of different retinal circuits found that OPs are generated by inner retinal AC electrical synapses. Importantly, this AC activity helped synchronise GC activity. Conclusion: Our µERG protocol simultaneously records the light-dependent activities of the first-, second-, and third-order neurons within the native neuronal circuitry, providing unprecedented insights into retinal physiology and pathophysiology. This method now also enables complete in vitro retinal function testing of therapeutic interventions, providing critical guidance for later in vivo investigations. Full article
(This article belongs to the Special Issue Pathophysiology and Translational Research of Retinal Diseases)
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