Search Results (407)

Background: The retina plays a vital role in vision, and its impairment can cause significant visual deficits. Current retinal disease treatments range from conventional anti-inflammatory drugs to advanced anti-VEGF therapies and monoclonal antibodies. TnP, a novel synthetic peptide in preclinical development, has demonstrated therapeutic potential in chronic inflammatory conditions such as multiple sclerosis and asthma due to its immunomodulatory properties. Using zebrafish—which share significant genetic homology with humans—we investigated TnP’s effects on retinopathy models mimicking diabetic retinopathy (DR) through either cobalt chloride (CoCl₂)-induced hypoxia or light-induced retinal damage (LIRD). Methods: We employed two retinal injury models (CoCl₂-induced hypoxia and LIRD) and subjected them to TnP treatment, assessing the outcomes through visual–motor response testing and histological examination. Results: CoCl₂ exposure impaired swimming activity, while light damage reduced the movement distance. Both models induced distinct retinal morphological changes. Although TnP failed to reverse most injury effects, it specifically restored the inner plexiform layer (IPL)’s thickness. Conclusions: Our findings suggest that TnP may enhance neuronal plasticity by promoting cell proliferation and synaptic connectivity. While showing promise as a therapeutic candidate for retinal and neurodegenerative disorders, TnP might achieve optimal efficacy when combined with complementary treatments. Full article

Until now, the ultimate solution for blind people has not been achieved, because challenges still exist. Retinal implants have emerged as a promising solution for restoring vision in individuals suffering from retinal degenerative diseases such as retinitis pigmentosa and age-related macular degeneration. Central to the efficacy of these implants is the design and functionality of the electrode arrays responsible for stimulating retinal neurons. This review evaluates the evolution of retinal implants, with particular emphasis on electrode specifications, physiological considerations for electrical stimulation, and recent advancements in electrode design. A comprehensive analysis of state-of-the-art published studies provides a detailed cross-comparison of electrode characteristics, offering insights into current state-of-the-art technologies and future directions. Full article

Low-light image enhancement remains a challenging task in computer vision due to the complex interplay of noise, asymmetrical artifacts, illumination non-uniformity, and detail preservation. Existing methods such as traditional histogram equalization, gamma correction, and Retinex-based approaches often struggle to balance contrast improvement and naturalness preservation. Deep learning methods such as CNNs and transformers have shown promise, but face limitations in modeling multi-scale illumination and long-range dependencies. To address these issues, we propose WIGformer, a novel wavelet-based illumination-guided transformer framework for low-light image enhancement. The proposed method extends the single-stage Retinex theory to explicitly model noise in both reflectance and illumination components. It introduces a wavelet illumination estimator with a Wavelet Feature Enhancement Convolution (WFEConv) module to capture multi-scale illumination features and an illumination feature-guided corruption restorer with an Illumination-Guided Enhanced Multihead Self-Attention (IGEMSA) mechanism. WIGformer leverages the symmetry properties of wavelet transforms to achieve multi-scale illumination estimation, ensuring balanced feature extraction across different frequency bands. The IGEMSA mechanism integrates adaptive feature refinement and illumination guidance to suppress noise and artifacts while preserving fine details. The same mechanism allows us to further exploit symmetrical dependencies between illumination and reflectance components, enabling robust and natural enhancement of low-light images. Extensive experiments on the LOL-V1, LOL-V2-Real, and LOL-V2-Synthetic datasets demonstrate that WIGformer achieves state-of-the-art performance and outperforms existing methods, with PSNR improvements of up to 26.12 dB and an SSIM score of 0.935. The qualitative results demonstrate WIGformer’s superior capability to not only restore natural illumination but also maintain structural symmetry in challenging conditions, preserving balanced luminance distributions and geometric regularities that are characteristic of properly exposed natural scenes. Full article

Energy healing refers to a globalising market of healing rituals that aim to stimulate the clients’ self-healing process. In the context of healing, the term ‘energy’ has multi-layered meanings and may denote physical, psychological, social, as well as spiritual principles of restoring well-being. This article demonstrates how the idea of energy as a healing agent was embedded within the occult cosmology and anthropology of the British-American post-Theosophist Alice A. Bailey (1880–1949). Applying historical discourse analysis, Bailey’s impact on the emergence of energy healing is examined. Her theory of energy is explored against the backdrop of her esoteric grand narrative. It is demonstrated how Bailey’s principles of energy formed the basis for her vision of a “medicine of the future”. A concluding discussion proves the global influence of Bailey’s ‘energetic turn’ and how it modelled the approach of major holistic actors of the later twentieth century. Full article

Phase wrapping is a common phenomenon in optical full-field imaging or measurement systems. It arises from large phase retardations and results in wrapped-phase maps that contain essential information about surface roughness and topology. However, these maps are often degraded by noise, such as speckle and Gaussian, which reduces the measurement accuracy and complicates phase reconstruction. Denoising such data is a fundamental problem in computer vision and plays a critical role in biomedical imaging modalities like Full-Field Optical Interferometry. In this paper, we propose WPD-Net (Wrapped-Phase Denoising Network), a lightweight deep learning-based neural network specifically designed to restore phase images corrupted by high noise levels. The network architecture integrates a shallow feature extraction module, a series of Residual Dense Attention Blocks (RDABs), and a dense feature fusion module. The RDABs incorporate attention mechanisms that help the network focus on critical features and suppress irrelevant noise, especially in high-frequency or complex regions. Additionally, WPD-Net employs a growth-rate-based feature expansion strategy to enhance multi-scale feature representation and improve phase continuity. We evaluate the model’s performance on both synthetic and experimentally acquired datasets and compare it with other state-of-the-art deep learning-based denoising methods. The results demonstrate that WPD-Net achieves superior noise suppression while preserving fine structural details even with mixed speckle and Gaussian noises. The proposed method is expected to enable fast image processing, allowing unwrapped biomedical images to be retrieved in real time. Full article

The properties of light propagation underwater typically cause color distortion and reduced contrast in underwater images. In addition, complex underwater lighting conditions can result in issues such as non-uniform illumination, spotting, and noise. To address these challenges, we propose an innovative underwater-image enhancement (UIE) approach based on maximum information-channel compensation and edge-preserving filtering techniques. Specifically, we first develop a channel information transmission strategy grounded in maximum information preservation principles, utilizing the maximum information channel to improve the color fidelity of the input image. Next, we locally enhance the color-corrected image using guided filtering and generate a series of globally contrast-enhanced images by applying gamma transformations with varying parameter values. In the final stage, the enhanced image sequence is decomposed into low-frequency (LF) and high-frequency (HF) components via side-window filtering. For the HF component, a weight map is constructed by calculating the difference between the current exposedness and the optimum exposure. For the LF component, we derive a comprehensive feature map by integrating the brightness map, saturation map, and saliency map, thereby accurately assessing the quality of degraded regions in a manner that aligns with the symmetry principle inherent in human vision. Ultimately, we combine the LF and HF components through a weighted summation process, resulting in a high-quality underwater image. Experimental results demonstrate that our method effectively achieves both color restoration and contrast enhancement, outperforming several State-of-the-Art UIE techniques across multiple datasets. Full article

The accurate detection of small ships based on images or vision is critical for many scenarios, like maritime surveillance, port security, and navigation safety. However, achieving accurate detection for small ships is a challenge for cost-efficiency models; while the models could meet this requirement, they have unacceptable computation costs for real-time surveillance. We propose YOLO-LPSS, a novel model designed to significantly improve small ship detection accuracy with low computation cost. The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. The experimental results show that YOLO-LPSS outperforms the known YOLOv8 nano baseline and other works, and the number of parameters increases by only 0.33 M compared to the original YOLOv8n while achieving 0.796 and 0.831 AP^50:95 in classes consisting mainly of small ship targets (the bounding box of the target area is less than 5% of the image resolution), which is 3–5% higher than the vanilla model and recent SOTA models. Full article

Image dehazing is a critical task in image restoration, aiming to retrieve clear images from hazy scenes. This process is vital for various applications, including machine recognition, security monitoring, and aerial photography. Current dehazing algorithms often encounter challenges in multi-scale feature extraction, detail preservation, effective haze removal, and maintaining color fidelity. To address these limitations, this paper introduces a novel Parallel Image-Dehazing Network (PID-Net). PID-Net uniquely combines a Convolutional Neural Network (CNN) for precise local feature extraction and a Vision Transformer (ViT) to capture global contextual information, overcoming the shortcomings of methods relying solely on either local or global features. A multi-scale CNN branch effectively extracts diverse local details through varying receptive fields, thereby enhancing the restoration of fine textures and details. To optimize the ViT component, a lightweight attention mechanism with CNN compensation is integrated, maintaining performance while minimizing the parameter count. Furthermore, a Redundant Feature Filtering Module is incorporated to filter out noise and haze-related artifacts, promoting the learning of subtle details. Our extensive experiments on public datasets demonstrated PID-Net’s significant superiority over state-of-the-art dehazing algorithms in both quantitative metrics and visual quality. Full article

Aortic dissection (AD) is a life-threatening vascular condition with limited pharmacological options, and shared risk factors with cardiac disease include hypertension, atherosclerosis, smoking, and dyslipidemia. This study investigated Ferrostatin-1 (Fer-1), a ferroptosis inhibitor, in a BAPN/Ang-II-induced mouse model of AD, revealing significant therapeutic potential. Fer-1 significantly reduced AD incidence and mortality by preserving aortic wall integrity. RNA sequencing identified 922 differentially expressed genes, with 416 upregulated and 506 downregulated. Bioinformatics analysis revealed that Fer-1 modulates key regulators, such as MEF2C and KDM5A, impacting immune responses, oxidative stress, apoptosis, and lipid metabolism. Additionally, Fer-1 alters miRNA expression, with the upregulation of miR-361-5p and downregulation of miR-3151-5p, targeting pathways involved in inflammation, oxidative stress, and smooth muscle cell (SMC) phenotypic stability. Functional pathway analysis highlighted the inhibition of actin cytoskeleton, ILK, and IL-17 signaling, essential for SMC differentiation and extracellular matrix remodeling. Gene interaction network analysis identified 21 central molecules, including CXCR3, ACACA, and BPGM, associated with lipid metabolism, inflammation, and vascular remodeling. This research elucidates the mechanism of ferroptosis in AD pathogenesis and establishes Fer-1 as a promising therapeutic intervention. AD and cardiac diseases share molecular mechanisms, risk factors, and pathological processes, positioning AD within the broader scope of cardiovascular pathology. By attenuating lipid peroxidation, oxidative stress, and inflammation, Fer-1 may have cardioprotective effects beyond AD, providing a foundation for future translational research in cardiovascular medicine. Full article

Retinal degeneration, characterized by the progressive loss of photoreceptors, retinal pigment epithelium cells, and/or ganglion cells, is a leading cause of vision impairment. These diseases are generally classified as inherited (e.g., retinitis pigmentosa, Stargardt disease) or acquired (e.g., age-related macular degeneration, diabetic retinopathy, glaucoma) ocular disorders that can lead to blindness. Available treatment options focus on managing symptoms or slowing disease progression and do not address the underlying causes of these diseases. However, recent advancements in regenerative medicine offer alternative solutions for repairing or protecting degenerated retinal tissue. Stem and progenitor cell therapies have shown great potential to differentiate into various retinal cell types and can be combined with gene editing, extracellular vesicles and exosomes, and bioactive molecules to modulate degenerative cellular pathways. Additionally, gene therapy and neuroprotective molecules play a crucial role in enhancing the efficacy of regenerative approaches. These innovative strategies hold the potential to halt the progression of retinal degenerative disorders, repair or replace damaged cells, and improve visual function, ultimately leading to a better quality of life for those affected. Full article

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in the elderly, and it is characterized by oxidative stress, lipid dysregulation, and dysfunction of the retinal pigment epithelium (RPE). A hallmark of AMD is the presence of drusen, extracellular deposits rich in lipids, proteins, and cellular debris, which are secreted by the RPE. These deposits impair RPE function, promote chronic inflammation, and accelerate disease progression. Despite advancements in understanding AMD pathogenesis, therapeutic strategies targeting lipid dysregulation and oxidative damage in RPE cells remain limited. This study evaluated the effects of liraglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), on free fatty acid (FFA)-induced damage in ARPE-19 cells, a widely used in vitro model of RPE dysfunction. FFA treatment induced lipid droplet accumulation, oxidative stress, and epithelial–mesenchymal transition (EMT), which are processes implicated in AMD progression. Liraglutide significantly reduced lipid droplet accumulation, mitigated oxidative stress, and suppressed EMT, as demonstrated by high-content imaging, immunocytochemistry, and molecular assays. Mechanistic analyses revealed that liraglutide activates AMP-activated protein kinase (AMPK), enhancing lipophagy and restoring lipid homeostasis. Furthermore, liraglutide influenced exosome secretion, altering paracrine signaling and reducing EMT markers in neighboring cells. These findings underscore liraglutide’s potential to address critical mechanisms underlying AMD pathogenesis, including lipid dysregulation, oxidative stress, and EMT. This study provides foundational evidence supporting the development of GLP-1 receptor agonists as targeted therapies for AMD. Full article

Neurotrophic keratopathy (NK) is a rare degenerative disease caused by impairment of the trigeminal nerve, leading to corneal anesthesia, epithelial breakdown, and progressive vision loss. Conventional treatments primarily focus on symptom management and the prevention of complications, but they do not address the underlying nerve dysfunction. Corneal neurotization (NT) has emerged as a promising surgical intervention aimed at restoring corneal sensation and improving ocular surface homeostasis. This review evaluates the outcomes of corneal neurotization in patients with NK and compares the effectiveness of direct (DNT) and indirect (INT) techniques. Studies have reported significant improvements in corneal sensitivity, with success rates ranging from 60.7% to 100% (mean: 90%). Most patients experienced recovery of corneal sensation, as measured by the Cochet–Bonnet aesthesiometer, with no significant differences in outcomes between DNT and INT. Indirect neurotization using a sural nerve graft was the most commonly employed technique (63% of cases), while the use of acellular allografts demonstrated comparable efficacy and simplified the procedure. Postoperative corneal sensitivity increased significantly, from a preoperative average of 2.717 mm to 36.01 mm, with reinnervation typically occurring within 4–6 months and peaking at 12 months. In vivo confocal microscopy confirmed the presence of nerve regeneration. Neurotization was found to be safe, with minimal donor-site complications, which generally resolved within one year. Although the procedure improves corneal sensation and tear film stability, visual acuity outcomes remain variable due to pre-existing corneal damage. Early intervention is, therefore, recommended to prevent irreversible scarring. However, the number of patients undergoing the procedure remains limited, making it difficult to draw definitive conclusions. Most available studies consist of small case series. Further research with larger sample sizes is needed to refine surgical techniques and optimize patient selection, thereby improving outcomes in the management of NK. Full article

This article examines Rabbi Moshe Avigdor Amiel’s concept of “Torah and Work” (Torah va’avoda) as a central tenet of Religious Zionism. Rabbi Amiel, a prominent ideologue of the Mizrahi movement who served as Chief Rabbi of Tel Aviv (1936–1945), viewed the integration of spirituality and materiality as representing complete Judaism. Using Hegelian dialectics, Amiel explained his approach: the thesis (spirit) and antithesis (matter) unite to form a synthesis (complete Judaism). He argued that exile transformed Jewish identity from a multidimensional biblical identity to a one-dimensional rabbinical identity focused solely on spirituality. Religious Zionism aimed to restore Judaism to its original completeness. Amiel criticized both ultraorthodox Jews who embraced only the spiritual aspect (Torah) and secular Jews who embraced only the material aspect (work), asserting that only “the complete matter, not half the matter” represents authentic Judaism. He boldly claimed that partial perspectives constitute idolatry. The article explores Amiel’s position on “Hebrew labor”, which he viewed as a national commandment without limitation, contrary to the ultraorthodox view that restricted it to charity considerations. His relationship with labor movements and socialism is also examined—he identified commonalities between Judaism and socialism while highlighting fundamental differences. In 1938, Rabbi Amiel established “Hayishuv Hahadash”, Israel’s first yeshiva high school combining religious and secular studies, as a practical manifestation of his vision of complete Judaism integrating Torah and work. Amiel’s critical stance toward various groups—including Religious Zionism, ultraorthodoxy, and secular Zionism—stemmed from his commitment to revitalizing biblical Jewish identity that harmoniously combines Torah study and productive labor. Full article

Human space exploration presents an unparalleled opportunity to study life in extreme environments—but it also exposes astronauts to physiological stressors that jeopardize key systems like vision. Corneal health, essential for maintaining precise visual acuity, is threatened by microgravity-induced fluid shifts, cosmic radiation, and the confined nature of spacecraft living environments. These conditions elevate the risk of corneal abrasions, infections, and structural damage. In addition, Spaceflight-Associated Neuro-Ocular Syndrome (SANS)—while primarily affecting the posterior segment—has also been potentially linked to anterior segment alterations such as corneal edema and tear film instability. This review examines these ocular challenges and assesses current mitigation strategies. Traditional approaches, such as terrestrial eye banking and corneal transplantation, are impractical for spaceflight due to the limited viability of preserved tissues, surgical complexities, anesthetic risks, infection potential, and logistical constraints. The paper explores emerging technologies like 3D bioprinting and stem cell-based tissue engineering, which offer promising solutions by enabling the on-demand production of personalized corneal constructs. Complementary advancements, including adaptive protective eyewear, bioengineered tear substitutes, telemedicine, and AI-driven diagnostic tools, also show potential in autonomously managing ocular health during long-duration missions. By addressing the complex interplay of environmental stressors and biological vulnerabilities, these innovations not only safeguard astronaut vision and mission performance but also catalyze new pathways for regenerative medicine on Earth. The evolution of space-based ophthalmic care underscores the dual impact of space medicine investments across planetary exploration and terrestrial health systems. Full article

Recent advances in micro-retinal implant technologies have shown promise in vision restoration, yet challenges remain regarding pixel resolution, reliability, power leakage, cost-effectiveness, and device lifespan. Existing devices often face difficulties meeting the long-term safety and reliability requirements set by regulatory bodies such as the FDA and the European Union, making them impractical for widespread use. This research introduces a 256-pixel hexagonal subretinal device with an advanced digital controller designed to overcome these limitations. The proposed system offers solutions to issues of resolution, compactness, economic constraints, and control over biphasic pulse parameters. It was specifically designed to deliver flicker-free vision while increasing resolution and light sensitivity. A prototype was developed using field-programmable gate arrays (FPGAs) and amplitude-shift keying (ASK) modulators for wireless data transmission. The system was fabricated on a microchip and tested against various performance parameters, demonstrating its potential for future commercial viability. Full article