Implications of Neural Plasticity in Retinal Prosthesis

Unveiling the role of CaMKII in retinal degeneration: from biological mechanism to therapeutic strategies

Ca2+/calmodulin-dependent protein kinase II (CaMKII) is a family of broad substrate specificity serine (Ser)/threonine (Thr) protein kinases that play a crucial role in the Ca2+-dependent signaling pathways. Its significance as an intracellular Ca2+ sensor has garnered abundant research interest in the domain of neurodegeneration. Accumulating evidences suggest that CaMKII is implicated in the pathology of degenerative retinopathies such as diabetic retinopathy (DR), age-related macular degeneration (AMD), retinitis pigmentosa (RP) and glaucoma optic neuropathy. CaMKII can induce the aberrant proliferation of retinal blood vessels, influence the synaptic signaling, and exert dual effects on the survival of retinal ganglion cells and pigment epithelial cells. Researchers have put forth multiple therapeutic agents, encompassing small molecules, peptides, and nucleotides that possess the capability to modulate CaMKII activity. Due to its broad range isoforms and splice variants therapeutic strategies seek to inhibit specifically the CaMKII are confronted with considerable challenges. Therefore, it becomes crucial to discern the detrimental and advantageous aspects of CaMKII, thereby facilitating the development of efficacious treatment. In this review, we summarize recent research findings on the cellular and molecular biology of CaMKII, with special emphasis on its metabolic and regulatory mechanisms. We delve into the involvement of CaMKII in the retinal signal transduction pathways and discuss the correlation between CaMKII and calcium overload. Furthermore, we elaborate the therapeutic trials targeting CaMKII, and introduce recent developments in the zone of CaMKII inhibitors. These findings would enrich our knowledge of CaMKII, and shed light on the development of a therapeutic target for degenerative retinopathy.

The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

BACKGROUND

Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP.

METHODS

By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa.

RESULTS

A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa.

CONCLUSIONS

The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.

Patient-specific computational models of retinal prostheses

Retinal prostheses stimulate inner retinal neurons to create visual perception for blind patients. Implanted arrays have many small electrodes. Not all electrodes induce perception at the same stimulus amplitude, requiring clinicians to manually establish a visual perception threshold for each one. Phosphenes created by single-electrode stimuli can also vary in shape, size, and brightness. Computational models provide a tool to predict inter-electrode variability and automate device programming. In this study, we created statistical and patient-specific field-cable models to investigate inter-electrode variability across seven epiretinal prosthesis users. Our statistical analysis revealed that retinal thickness beneath the electrode correlated with perceptual threshold, with a significant fixed effect across participants. Electrode-retina distance and electrode impedance also correlated with perceptual threshold for some participants, but these effects varied by individual. We developed a novel method to construct patient-specific field-cable models from optical coherence tomography images. Predictions with these models significantly correlated with perceptual threshold for 80% of participants. Additionally, we demonstrated that patient-specific field-cable models could predict retinal activity and phosphene size. These computational models could be beneficial for determining optimal stimulation settings in silico, circumventing the trial-and-error testing of a large parameter space in clinic.

Electrophysiological properties of layer 2/3 pyramidal neurons in the primary visual cortex of a retinitis pigmentosa mouse model (rd10)

Retinal degeneration is one of the main causes of visual impairment and blindness. One group of retinal degenerative diseases, leading to the loss of photoreceptors, is collectively termed retinitis pigmentosa. In this group of diseases, the remaining retina is largely spared from initial cell death making retinal ganglion cells an interesting target for vision restoration methods. However, it is unknown how downstream brain areas, in particular the visual cortex, are affected by the progression of blindness. Visual deprivation studies have shown dramatic changes in the electrophysiological properties of visual cortex neurons, but changes on a cellular level in retinitis pigmentosa have not been investigated yet. Therefore, we used the rd10 mouse model to perform patch-clamp recordings of pyramidal neurons in layer 2/3 of the primary visual cortex to screen for potential changes in electrophysiological properties resulting from retinal degeneration. Compared to wild-type C57BL/6 mice, we only found an increase in intrinsic excitability around the time point of maximal retinal degeneration. In addition, we saw an increase in the current amplitude of spontaneous putative inhibitory events after a longer progression of retinal degeneration. However, we did not observe a long-lasting shift in excitability after prolonged retinal degeneration. Together, our results provide evidence of an intact visual cortex with promising potential for future therapeutic strategies to restore vision.

Suppressing Retinal Remodeling to Mitigate Vision Loss in Photoreceptor Degenerative Disorders

Rod and cone photoreceptors degenerate in retinitis pigmentosa and age-related macular degeneration, robbing the visual system of light-triggered signals necessary for sight. However, changes in the retina do not stop with the photoreceptors. A stereotypical set of morphological and physiological changes, known as remodeling, occur in downstream retinal neurons. Some aspects of remodeling are homeostatic, with structural or functional changes compensating for partial loss of visual inputs. However, other aspects are nonhomeostatic, corrupting retinal information processing to obscure vision mediated naturally by surviving photoreceptors or artificially by vision-restoration technologies. In this review, I consider the mechanism of remodeling and its consequences for residual and restored visual function; discuss the role of retinoic acid, a critical molecular trigger of detrimental remodeling; and discuss strategies for suppressing retinoic acid biosynthesis or signaling as therapeutic possibilities for mitigating vision loss.

Retinal Prostheses: Engineering and Clinical Perspectives for Vision Restoration

A retinal prosthesis, also known as a bionic eye, is a device that can be implanted to partially restore vision in patients with retinal diseases that have resulted in the loss of photoreceptors (e.g., age-related macular degeneration and retinitis pigmentosa). Recently, there have been major breakthroughs in retinal prosthesis technology, with the creation of numerous types of implants, including epiretinal, subretinal, and suprachoroidal sensors. These devices can stimulate the remaining cells in the retina with electric signals to create a visual sensation. A literature review of the pre-clinical and clinical studies published between 2017 and 2023 is conducted. This narrative review delves into the retinal anatomy, physiology, pathology, and principles underlying electronic retinal prostheses. Engineering aspects are explored, including electrode-retina alignment, electrode size and material, charge density, resolution limits, spatial selectivity, and bidirectional closed-loop systems. This article also discusses clinical aspects, focusing on safety, adverse events, visual function, outcomes, and the importance of rehabilitation programs. Moreover, there is ongoing debate over whether implantable retinal devices still offer a promising approach for the treatment of retinal diseases, considering the recent emergence of cell-based and gene-based therapies as well as optogenetics. This review compares retinal prostheses with these alternative therapies, providing a balanced perspective on their advantages and limitations. The recent advancements in retinal prosthesis technology are also outlined, emphasizing progress in engineering and the outlook of retinal prostheses. While acknowledging the challenges and complexities of the technology, this article highlights the significant potential of retinal prostheses for vision restoration in individuals with retinal diseases and calls for continued research and development to refine and enhance their performance, ultimately improving patient outcomes and quality of life.

Artificial Olfactory Signal Modulation for Detection in Changing Environments

Animals have evolved to sense in complex environments through both modulation behavior including sniffing as well as sophisticated neural processing including memory and neuromodulation. Here, we explore thermal modulation of chemically diverse sensor arrays, where response patterns are based on partitioning of odorants across the array. The differential response patterns contain information about the chemical nature of the odorant for identification. By transitioning away from well-defined concentration modulation, traditionally used in the field, to thermal modulation, it is possible to capture both diagnostic patterns as well as intensity information in complex environments. This performance is demonstrated with carbon-black based, chemically diverse sensor arrays, that are thermally modulated with light at 25 mHz exposed to different analytes of varying concentrations.

Altered whole-brain gray matter volume in form-deprivation myopia rats based on voxel-based morphometry: A pilot study

Background

Myopia is one of the major public health problems worldwide. However, the exact pathogenesis of myopia remains unclear. This study proposes using voxel-based morphometry (VBM) to investigate potential morphological alterations in gray matter volume (GMV) in form-deprivation myopia (FDM) rats.

Methods

A total of 14 rats with FDM (FDM group) and 15 normal controls (NC group) underwent high-resolution magnetic resonance imaging (MRI). Original T2 brain images were analyzed using VBM method to identify group differences in GMV. Following MRI examination, all rats were perfused with formalin, and immunohistochemical analysis of NeuN and c-fos levels was performed on the visual cortex.

Results

In the FDM group, compared to the NC group, significantly decreased GMVs were found in the left primary visual cortex, left secondary visual cortex, right subiculum, right cornu ammonis, right entorhinal cortex and bilateral molecular layer of the cerebellum. Additionally, significantly increased GMVs were found in the right dentate gyrus, parasubiculum, and olfactory bulb.

Conclusions

Our study revealed a positive correlation between mGMV and the expression of c-fos and NeuN in the visual cortex, suggesting a molecular relationship between cortical activity and macroscopic measurement of visual cortex structural plasticity. These findings may help elucidate the potential neural pathogenesis of FDM and its relationship to changes in specific brain regions.