Next Article in Journal
Metatranscriptomic Reanalysis of Alzheimer’s Brains Identifies Low-Biomass Microbial Signals Including Enrichment of Acinetobacter radioresistens
Previous Article in Journal
The Role of MNX1–AS1 in Ovarian Cancer Resistance and Tumor Progression via RNA–RNA Interactions
Previous Article in Special Issue
Glycated Albumin and Cardiovascular Mortality in CKD Stage V Patients with Diabetes Mellitus: A Five-Year Follow-Up Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 27
Issue 8
10.3390/ijms27083427
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Experimental Diabetic Retinopathy in Wistar Rats Induced by Streptozotocin: A Window into Retinal Disease Progression

by
Luis Fernando Barba-Gallardo
1,
Manuel Enrique Ávila-Blanco
1,2,
Javier Ventura-Juárez
2,
Martín Humberto Muñoz-Ortega
3,
Ruth Clarisa Murillo-Ruíz
3,
Marcela Rivera-Delgadillo
3,
José Luis Díaz-Rubio
4,
Elizabeth Casillas-Casillas
1,
Luis Héctor Salas-Hernández
1 and
Paloma Lucía Guerra-Ávila
1,*
1
Departamento de Optometría, Centro de Ciencias de la Salud, Universidad Autónoma de Aguascalientes, Av. Universidad 940, Aguascalientes 20100, Mexico
2
Departamento de Morfología, Centro de Ciencias Básicas, Universidad Autónoma de Aguascalientes, Av. Universidad 940, Aguascalientes 20100, Mexico
3
Departamento de Química, Centro de Ciencias Básicas, Universidad Autónoma de Aguascalientes, Av. Universidad 940, Aguascalientes 20100, Mexico
4
Patronato de Banco de Ojos y Tejidos de Aguascalientes, Av. Lic. Adolfo López M. Ote 1808, La Hacienda, Aguascalientes 20190, Mexico
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2026, 27(8), 3427; https://doi.org/10.3390/ijms27083427
Submission received: 5 March 2026 / Revised: 2 April 2026 / Accepted: 7 April 2026 / Published: 11 April 2026
(This article belongs to the Special Issue Biomarkers in Diabetes Mellitus: From Discovery to Clinical Application)
Browse Figures
Versions Notes

Abstract

Diabetic retinopathy (DR), recognized as a progressive neurovascular and microvascular complication of diabetes, remains one of the leading causes of visual disability worldwide, within the context of a sustained increase in ophthalmic diseases and retinal vascular disorders that compromise vision. This study aimed to characterize the progression of diabetic retinopathy in a streptozotocin (STZ)-induced Wistar rat model. A single dose of 65 mg/kg body weight was administered, with follow-up periods at 2, 4, 8, and 10 weeks, compared to healthy controls. STZ-induced rats exhibited reduced weight gain compared to the control group. They also showed markedly variable hyperglycemia, with glucose concentrations ranging from 250 to 530 mg/dL. Histological analysis of retinal tissue at week 4 revealed early signs of vascular compromise, including early indications of a microenvironment conducive to neovascularization and edema. By week 8, retinal damage had progressed to hemorrhage, persistent edema, and layer-specific vascular disruption. At week 10, intensified neovascularization and exacerbated edema indicated advanced microvascular deterioration. Immunofluorescence analysis demonstrated a temporal accumulation of CD8+ T cells in the retina, correlating with photoreceptor degeneration. The coordinated dynamics of CD4+ and CD8+ T cells suggested transient immune activation during STZ-induced retinal degeneration. Gene expression profiling revealed a proinflammatory and pro-oxidative retinal microenvironment, characterized by the overexpression of angiogenic pathways and proliferative signals. Simultaneously, the antioxidant response appeared partially impaired. Collectively, these findings provide mechanistic perspective on the multifactorial nature of diabetic retinopathy. Oxidative stress, inflammation, and angiogenesis converge to disrupt retinal homeostasis. This experimental model may serve as a reliable platform for future studies aimed at elucidating disease pathophysiology, identifying novel therapeutic targets, and evaluating emerging ophthalmic antidiabetic interventions.

1. Introduction

Diabetic retinopathy (DR) is a microvascular and neurodegenerative complication of diabetes mellitus (DM), affecting approximately 35% of people with diabetes worldwide, with significant variation across ethnic and geographic populations [1,2,3,4,5,6,7]. Within 25 years of diagnosis, over 95% of type 1 diabetic patients and around 60% of those with type 2 diabetes will develop some degree of DR [1,2,3,4,5,6,7,8,9,10,11]. DR remains the leading cause of preventable vision loss and blindness among adults aged 20 to 74, especially in middle- and high-income countries [1,2,3,4,5,6,7,9,10,11,12]. The onset and progression of DR are driven by chronic hyperglycemia and the accumulation of advanced glycation end products (AGEs), which disrupt normal metabolic pathways and trigger oxidative stress and early neurodegenerative changes in the retina [13,14,15,16]. In its initial stages, retinal swelling and the deposition of extracellular material occur, yet most patients remain asymptomatic. As the disease advances, damaged blood vessels leak fluid and blood into the retinal tissue, leading to significant visual impairment and, ultimately, blindness [7,10,11,12,13,14,15,16,17]. Common clinical manifestations include fluctuating vision, floaters and scotomas, corneal abnormalities and abrasions, diplopia, ocular pain, nystagmus, cataract formation, and distorted or blurred vision [3,7,17].
Global epidemiological data underscore the growing public health impact of DR. The Global Burden of Disease study identified DR as the fifth leading cause of both blindness and moderate-to-severe visual impairment in adults aged 50 and older [18,19]. Between 1990 and 2020, the age-standardized prevalence of blindness due to diabetic eye disease rose by 14.9% to 18.5%, and forecasts predict that nearly 191 million people worldwide will be living with DR by 2030 [20,21]. These trends highlight an urgent need for enhanced screening, early detection, and effective therapeutic strategies.
The pathogenesis of DR is multifactorial, involving molecular, biochemical, structural, and functional abnormalities that converge to damage both retinal neurons and vascular cells [22,23,24]. Central to this process is oxidative stress, a state in which reactive oxygen species (ROS) such as superoxide anion (O2·−), hydrogen peroxide (H2O2), peroxyl radicals (ROO·), and hydroxyl radicals (·OH) accumulate beyond the cell’s antioxidant capacity [25,26,27]. Hyperglycemia amplifies intracellular ROS production, and excessive ROS in turn injures the retinal microvasculature, leading to capillary basement membrane thickening through altered extracellular matrix turnover, breakdown of the blood retinal barrier (BRB), and formation of acellular, occluded capillaries, hallmarks of progressive DR [27,28,29].
DR is classified based on the presence or absence of neovascularization (NV). Pathological angiogenesis is the hallmark of proliferative diabetic retinopathy (PDR) [30], whereas its absence characterizes non-proliferative diabetic retinopathy (NPDR) [1,2,3,4,5,6,7,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40].
Mild NPDR represents the earliest and most prevalent stage of DR. It is defined by the presence of microaneurysms (MAs), venous occlusions, intraretinal microvascular abnormalities, and subtle dilation of retinal vessels. These are early indicators of retinal damage [41,42]. NPDR encompasses a spectrum of changes triggered by chronic hyperglycemia. It begins with microangiopathy marked by pericyte loss and endothelial cell injury. These alterations lead to disrupted retinal blood flow, thickening of the retinal basement membrane (BM), direct macular damage (diabetic macular edema, DME), formation of acellular capillaries, MA development, venous beading, and dot-blot intraretinal hemorrhages. The release of vasoactive substances promotes NV [43,44,45,46]. Increased permeability of the BRB allows leakage of inflammatory cytokines and plasma proteins, resulting in hard exudates visible on fundus examination. As the disease progresses, vasoconstriction and capillary occlusion induce tortuous capillaries and retinal ischemia. This is often accompanied by cotton-wool spots [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,47].
PDR constitutes the most advanced stage of DR and is associated with severe vision loss. As DR progresses, new blood vessels begin to form on the retinal surface. These vessels are structurally unstable and prone to leakage of blood and extracellular fluids. In the final stages of PDR, profound hypoxia drives NV, vitreous hemorrhage, and retinal detachment [48,49]. Extensive ischemia, NV, and subsequent complications such as vitreous hemorrhage and tractional retinal detachment are characteristic of advanced PDR. These conditions often require surgical intervention [1,2,3,4,5,6,7,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47]. Interestingly, PDR progression stabilizes in about 60% of patients, even among those with DM for over 50 years [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50]. This suggests the existence of endogenous protective mechanisms that may delay or prevent transition to PDR [51].
Mitochondrial quality control in the diabetic retina is critically dependent on balanced mitophagy, which selectively removes depolarized or damaged mitochondria through the accumulation of PTEN-induced putative kinase protein 1 (PINK1) on the outer mitochondrial membrane and the recruitment of Parkin. Parkin-mediated ubiquitination of mitochondrial proteins enables recognition by autophagy receptors binding to light chain 3 (LC3) protein, thereby directing them toward lysosomal degradation [52]. Dysregulation of PINK1/Parkin-dependent pathways, as well as receptor-mediated mechanisms such as BNIP3/NIX and fun 14 domain-containing protein 1 (FUNDC1), under hyperglycemic conditions disrupts mitochondrial fusion-fission dynamics [53]. This imbalance leads to mitochondrial fragmentation, mtDNA damage, and excessive mtROS generation in retinal endothelial cells (REC), retinal pigment epithelium (RPE), Müller cells, and ganglion cells [52,53]. Alterations in the PINK1/Parkin pathway within retinal microvascular endothelial cells and RPE promote the accumulation of dysfunctional mitochondria, sustaining oxidative stress, activating the NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) inflammasome [52], and driving the release of proinflammatory cytokines IL-β and IL-18 [53]. These mediators increase vascular permeability, compromise tight junction proteins, and impair BRB integrity, thereby contributing to diabetic neurovascular injury [52,53]. Conversely, excessive mitophagy has been documented in REC and Müller cells under hyperglycemic states. This process, characterized by dynamin-related protein 1 (Drp1) driven fragmentation and thioredoxin-interacting protein (TXNIP) activation, induces hyperactive Parkin-dependent mitophagy, leading to mitochondrial depletion, apoptosis, and gliosis, ultimately weakening the BRB structure [53]. Collectively, both insufficient and excessive mitophagy compromise mitochondrial quality control. In either scenario, damaged mitochondria persist or cellular bioenergetics collapse, resulting in the overproduction of ROS, NLRP3 activation, cytokine release, and the BRB breakdown [52,53].
Current therapeutic strategies aim to counteract vascular endothelial changes in DR, including excessive angiogenesis, increased permeability, retinal inflammation, and elevated intraocular pressure (IOP) [54]. Clinical success has increasingly focused on targeting the molecular drivers of microvascular abnormalities. A pivotal breakthrough was the identification of vascular endothelial growth factor (VEGF) as a key mediator in DR. Elevated VEGF levels promote aberrant NV by signaling retinal endothelial cells, altering vascular permeability, and driving angiogenesis. Moreover, VEGF serves as a biomarker of microangiopathy in PDR [55,56]. Multiple multicenter clinical trials have demonstrated that anti-vascular endothelial growth factor (anti-VEGF) antibodies effectively reduce DME, prevent further vision loss, and in some cases, improve visual acuity [56,57,58].
Additional therapeutic approaches include intravitreal corticosteroids, laser photocoagulation, which has long been an effective method for controlling proliferation and edema, and vitrectomy, tailored to disease stage and pathology [59]. The treatment of many DR complications continues to be grounded in the use of Anti-VEGF agents and corticosteroids. However, a significant proportion of patients (approximately 40%) exhibit DME that is resistant to monotherapy, and a smaller subset (approximately 8%) remains refractory to dual therapy, resulting in suboptimal visual outcomes [60].
Therefore, the objective of this study is to investigate the molecular mechanisms associated with tissue damage and protection in diabetic retinopathy using a murine model. The objective is to establish the foundation for future therapeutic studies that will enable patients to adopt the most effective treatments and enhance their quality of life.

2. Results

2.1. Biological Parameters

2.1.1. Streptozotocin-Induced Attenuation of Weight Gain in Wistar Rats in Early-Onset and Temporally Stable

The impact of streptozotocin (STZ) administration on the body weight (BW) of Wistar rats was systematically evaluated. Body weight was recorded at baseline and at the conclusion of the experimental period, and weight gain was calculated as the difference between these two measurements. A one-way analysis of variance (ANOVA) was performed to compare weight gain across groups, using a significance p ≤ 0.05.
Figure 1 illustrates the weekly progression of BW and cumulative weight gain for each group. Rats in the control group exhibited a significantly greater increase in BW compared to those in the STZ-treated groups. Among the experimental groups, no statistically significant differences in weight gain were observed across the various follow-up durations (2, 4, 8, and 10 weeks).
These findings indicate that STZ administration markedly attenuates weight gain in rats relative to the untreated control group, consistent with the metabolic disturbances typically associated with STZ-induced diabetes. The absence of temporal variation in weight gain among STZ-treated groups suggests that the effect of STZ on body mass stabilizes early in the disease course and remains relatively constant thereafter.
Ijms 27 03427 g001
Figure 1. (a) Weekly body weight of control rats (citrate-buffered saline, n = 5), monitored up to 8 weeks. (b) Weekly body weights of streptozotocin-induced rats (STZ in citrate-buffered saline, n = 5), monitored up to 10 weeks. (ANOVA; * p ≤ 0.05, ** p ≤ 0.01).
Figure 1. (a) Weekly body weight of control rats (citrate-buffered saline, n = 5), monitored up to 8 weeks. (b) Weekly body weights of streptozotocin-induced rats (STZ in citrate-buffered saline, n = 5), monitored up to 10 weeks. (ANOVA; * p ≤ 0.05, ** p ≤ 0.01).
Ijms 27 03427 g001

2.1.2. Streptozotocin-Induced β-Cell Cytotoxicity Triggers Sustained Hyperglycemia in Wistar Rats

Blood glucose concentrations were measured in both control and STZ-induced rats to assess the metabolic impact of streptozotocin administration. Control animals maintained stable glycemic levels throughout the study, consistently below the basal threshold of 100 mg/dL, indicating normal glucose homeostasis.
In contrast, rats injected with STZ exhibited a statistically significant elevation in blood glucose compared to their pre-treatment baseline values. Post-induction glycemia exceeded 250 mg/dL in all STZ-induced animals, with peak values reaching approximately 530 mg/dL, as illustrated in Figure 2.
These results confirm the successful induction of hyperglycemia and validate the STZ model for mimicking diabetic conditions. The marked increase in glucose levels reflects the cytotoxic effect of STZ on pancreatic β-cells, leading to impaired insulin production and sustained glycemic dysregulation.
Ijms 27 03427 g002
Figure 2. Blood glucose monitoring in experimental groups. (a) Weekly blood glucose in control rats given one dose of citrate buffer, tracked for 10 weeks. (b) Weekly blood glucose in streptozotocin-induced rats, monitoring over 10-week post injection (ANOVA; * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001).
Figure 2. Blood glucose monitoring in experimental groups. (a) Weekly blood glucose in control rats given one dose of citrate buffer, tracked for 10 weeks. (b) Weekly blood glucose in streptozotocin-induced rats, monitoring over 10-week post injection (ANOVA; * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001).
Ijms 27 03427 g002

2.2. Histology

2.2.1. Preserved Retinal Architecture in Control Rats Confirms Baseline Histological Integrity

Figure 3 illustrates the retinal architecture of five control rats: (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, and (E) rat 5. The following retinal layers were clearly identified in all specimens: (1) photoreceptor layer (rods and cones), (2) inner limiting membrane, (3) outer nuclear layer, (4) outer plexiform layer, (5) inner nuclear layer, (6) inner plexiform layer, (7) ganglion cell layer, and (8) optic nerve fiber layer.
No structural alteration or signs of damage were observed in any of the retinal layers across the control groups, indicating preserved histological integrity and normal retinal morphology under baseline conditions. These findings establish a reliable reference for comparative analysis with STZ-induced animals and support the validity of the control model.
Ijms 27 03427 g003
Figure 3. Histological evaluation of retinal tissue in control rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, and (E) rat 5. Representative photomicrographs of retinal sections stained with hematoxylin and eosin (H&E, 20× objective lens), obtained two weeks after administration of a single dose of citrate-buffered saline.
Figure 3. Histological evaluation of retinal tissue in control rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, and (E) rat 5. Representative photomicrographs of retinal sections stained with hematoxylin and eosin (H&E, 20× objective lens), obtained two weeks after administration of a single dose of citrate-buffered saline.
Ijms 27 03427 g003

2.2.2. Week 4 Post-Streptozotocin: Retinal Early Indications of a Microenvironment Conducive to Neovascularization and Edema Reveal Early Vascular Disruption

Figure 4 highlights pathological changes in retinal sections from STZ-induced rats at week 4. Blue arrows indicate early signs of a microenvironment conducive to neovascularization and the presence of erythrocytes. Yellow arrows mark regions of edema. These features appear in panels (A) through (E), corresponding to rats 1 through 5, respectively, alongside a control image for comparative reference.
A direct comparison between STZ-induced animals and the control group reveals distinct retinal damage induced by streptozotocin. Notably, panels (B) and (C) exhibit abnormal vascular proliferation: in panel (B), blood vessels are evident within the outer plexiform layer, whereas in panel (C), they appear in the inner plexiform layer, both with relatively preserved structural integrity.
Panel (D) demonstrates more pronounced pathological alterations, including marked edema in the ganglion cell layer and the presence of erythrocytes. These changes extend into adjacent layers, compromising their histological integrity. The widespread distribution of erythrocytes across multiple retinal layers, coupled with localized edema, underscores the severity of vascular disruption and tissue remodeling following STZ administration.
Ijms 27 03427 g004
Figure 4. Histopathological alterations in retinal tissue from the streptozotocin-induced group. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative transverse sections of rat retina stained with hematoxylin and eosin (H&E, 20× objective lens), obtained four weeks after a single intraperitoneal dose of streptozotocin.
Figure 4. Histopathological alterations in retinal tissue from the streptozotocin-induced group. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative transverse sections of rat retina stained with hematoxylin and eosin (H&E, 20× objective lens), obtained four weeks after a single intraperitoneal dose of streptozotocin.
Ijms 27 03427 g004

2.2.3. Progressive Retinal Damage at Week 8: STZ-Induced Hemorrhage, Edema, and Layer-Specific Vascular Disruption

Figure 5 presents a comparative analysis of retinal alteration induced by STZ at 8 weeks post-injection, alongside a control image for reference. Blue arrows indicate regions of neovascularization and the presence of erythrocytes associated with hemorrhagic events, as observed in panels (A) through (E), corresponding to rats 1 through 5. Yellow arrows highlight areas of edema in panel (A), which were most prominent in panels (B), (C), and (D).
Panel (B) exhibited the highest concentration of erythrocytes within the ganglion cell layer, suggesting localized vascular disruption and hemorrhage. In contrast, panel (E) showed a greater accumulation of erythrocytes within the plexiform layer, although no edema was detected in that region.
Quantitative analysis revealed a 35% increase in edema within the ganglion cell layer and a 28% rise in erythrocyte presence across the nuclear and ganglion layers, relative to control values. These findings underscore the progressive nature of STZ-induced retinal damage, characterized by vascular leakage, tissue swelling, and compromised structural integrity, particularly in layers critical for visual signal transmission.
Ijms 27 03427 g005
Figure 5. Histopathological changes in retinal tissue from the streptozotocin-induced rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative photomicrographs of transverse retinal sections stained with hematoxylin and eosin (H&E) 20× and 40× objective lenses, collected eight weeks after a single intraperitoneal administration of streptozotocin.
Figure 5. Histopathological changes in retinal tissue from the streptozotocin-induced rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative photomicrographs of transverse retinal sections stained with hematoxylin and eosin (H&E) 20× and 40× objective lenses, collected eight weeks after a single intraperitoneal administration of streptozotocin.
Ijms 27 03427 g005

2.2.4. Week 10 Post-Streptozotocin: Intensified Retinal Edema and Neovascularization Signal Advanced Microvascular Damage

Figure 6 illustrates the retinal effects of STZ at 10 weeks post-induction, compared to a control group. Blue arrows denote areas of neovascularization and erythrocyte accumulation due to hemorrhage, as observed in panels (A) through (E), corresponding to rats 1 through 5. These panels reveal a marked increase in erythrocyte infiltration and vascular proliferation within the inner retinal layers, particularly in the ganglion cell layer, where vessels appeared notably enlarged.
Yellow arrows indicate regions of edema, predominantly visible in panels (A), (B), (C), and (D). Panel (B) exhibited the most pronounced edema, characterized by significant separation within the ganglion cell layer that extended into the nuclear layers, a pattern also evident in panel (E), despite the absence of yellow arrow annotation.
Collectively, these findings confirm a substantial increase in edema affecting multiple retinal layers, accompanied by intensified erythrocyte presence and neovascularization within the ganglion cell layer. This progression underscores the severity of STZ-induced microvascular damage and its impact on retinal architecture, suggesting a sustained inflammatory and angiogenic response beyond the early stages of diabetic retinopathy.
Ijms 27 03427 g006
Figure 6. Histopathological assessment of retinal tissue in streptozotocin-induced rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative photomicrographs of transverse retinal sections stained with hematoxylin and eosin (H&E), captured at 20× objective lens, ten weeks after a single intraperitoneal dose of STZ.
Figure 6. Histopathological assessment of retinal tissue in streptozotocin-induced rats. (A) rat 1, (B) rat 2, (C) rat 3, (D) rat 4, (E) rat 5 and (F) control group. Representative photomicrographs of transverse retinal sections stained with hematoxylin and eosin (H&E), captured at 20× objective lens, ten weeks after a single intraperitoneal dose of STZ.
Ijms 27 03427 g006

2.3. Immunofluorescence

2.3.1. Intrinsic M-Iodopsin Fluorescence and Hoechst Staining Confirm Retinal Integrity in Control Samples

Figure 7 displays the rod photoreceptors in retinal samples from control rats, which contain M-iodopsin, a naturally autofluorescent opsin. The intrinsic fluorescence of M-iodopsin enabled clear visualization of the rod outer segments without the need for additional labeling.
Furthermore, nuclear staining with Hoechst dye confirmed the structural integrity of the retinal layers. The distinct separation and organization of each layer were preserved, allowing for precise identification of nuclear positioning and interlaminar spacing. These findings validate the morphological preservation of the control retina and establish a baseline for comparison with STZ-induced animals’ samples.
Ijms 27 03427 g007
Figure 7. Immunofluorescence photomicrographs of retinal tissue from control rats. Cone photoreceptors exhibiting autofluorescence at 530 nm, corresponding to M-opsin (green), with an approximate emission peak at 554 nm.
Figure 7. Immunofluorescence photomicrographs of retinal tissue from control rats. Cone photoreceptors exhibiting autofluorescence at 530 nm, corresponding to M-opsin (green), with an approximate emission peak at 554 nm.
Ijms 27 03427 g007

2.3.2. CD4+ T Cell Infiltration and Photoreceptor Degeneration Reveal Inflammatory Retinal Remodeling Post-Streptozotocin

As shown in Figure 8, CD4+ helper T cells were detected using a rabbit-derived anti-CD4 primary antibody, followed by Alexa Fluor® 488 as the secondary marker. CD4+ cells are indicated by red arrows in the images.
The intrinsic autofluorescence of M-iodopsin enabled visualization of the photoreceptor layer, allowing assessment of structural damage over time. Progressive deterioration of the rods and cones was evident across experimental weeks, highlighting the cumulative impact of STZ-induced retinal stress.
CD4+ cells were predominantly localized within the nuclear and plexiform layers, suggesting targeted immune infiltration in regions critical for synaptic transmission and cellular organization. These findings support the hypothesis of an inflammatory response contributing to retinal remodeling and functional impairment in diabetic conditions.
Ijms 27 03427 g008
Figure 8. Immunofluorescence analysis of retinal tissue from streptozotocin-induced rats. Representative photomicrographs of transverse retinal sections collected at 4, 8, and 10 weeks following a single intraperitoneal dose of streptozotocin, visualized at 20× objective lens. A rabbit-derived anti-CD4 antibody was used as the primary marker to detect helper T lymphocytes, followed by Alexa Fluor 488-conjugated secondary antibody for fluorescence detection.
Figure 8. Immunofluorescence analysis of retinal tissue from streptozotocin-induced rats. Representative photomicrographs of transverse retinal sections collected at 4, 8, and 10 weeks following a single intraperitoneal dose of streptozotocin, visualized at 20× objective lens. A rabbit-derived anti-CD4 antibody was used as the primary marker to detect helper T lymphocytes, followed by Alexa Fluor 488-conjugated secondary antibody for fluorescence detection.
Ijms 27 03427 g008

2.3.3. Temporal Accumulation of CD8+ T Cells Correlates with Photoreceptor Degeneration in Streptozotocin-Induced Retinopathy

As illustrated in Figure 9, cytotoxic CD8+ T cells were identified using a rabbit-derived anti-CD8 primary antibody, followed by Alexa Fluor® 594-conjugated anti-rabbit secondary antibody. In the merged image, CD8+ cells appear in red.
The autofluorescence of M-iodopsin enabled assessment of the structural integrity of the photoreceptor layer, revealing progressive degeneration of rods and cones throughout the experimental timeline. Notably, CD8+ T lymphocytes were first detected at week 4, with a marked increase in signal intensity by week 8.
These findings suggest a time-dependent infiltration of cytotoxic T cells into the retinal tissue, potentially contributing to the exacerbation of neuroinflammatory damage and photoreceptor loss. The spatial and temporal dynamics of CD8+ cell accumulation underscore their possible role in the pathophysiology of STZ-induced retinal degeneration.
Ijms 27 03427 g009
Figure 9. Immunofluorescence analysis of retinal tissue from streptozotocin-induced rats. Representative photomicrographs of transverse retinal sections collected at 4, 8, and 10 weeks after a single intraperitoneal dose of streptozotocin, visualized at 20× objective lens. A rabbit anti-CD8 antibody was used as the primary marker to detect cytotoxic T lymphocytes, followed by Alexa Fluor 594-conjugated anti-rabbit secondary antibody. CD8+ cells are indicated by red arrows in the merged image.
Figure 9. Immunofluorescence analysis of retinal tissue from streptozotocin-induced rats. Representative photomicrographs of transverse retinal sections collected at 4, 8, and 10 weeks after a single intraperitoneal dose of streptozotocin, visualized at 20× objective lens. A rabbit anti-CD8 antibody was used as the primary marker to detect cytotoxic T lymphocytes, followed by Alexa Fluor 594-conjugated anti-rabbit secondary antibody. CD8+ cells are indicated by red arrows in the merged image.
Ijms 27 03427 g009

2.3.4. Coordinated CD4+ and CD8+ T Cells Dynamics Reveal Transient Immune Activation During Streptozotocin-Induced Retinal Degeneration

Figure 10 illustrates the temporal dynamics of CD4+ and CD8+ T lymphocyte counts over a 10-week period. As shown in Graph 10a, CD4+ T cells exhibited a pronounced peak at week 8, reaching approximately 750 cells/mm2, followed by a sharp decline to 100 cells/mm2 by week 10. In contrast, CD8+ T cells (graph 10b) displayed a more variable pattern, with an initial count of 60 cells/mm2 at week 4, a modest rise to 80 cells/mm2 at week 8, and a subsequent decrease to 30 cells/mm2 at week 10.
A concurrent increase in both T cell subsets was observed at week 8, with the surge being markedly higher in the CD4+ population. This synchronized elevation suggests a coordinated immune activation phase, potentially reflecting a peak in retinal inflammatory response. The subsequent decline in both populations may indicate resolution or exhaustion of the local immune activity, aligning with the progression of retinal degeneration.
Ijms 27 03427 g010
Figure 10. Quantification of T lymphocytes in rat retina. Graph (a) shows CD4+ cell counts and graph (b) shows CD8+ cell counts in retinal tissue from control rats at 10 weeks following a single dose of citrate buffer, and from streptozotocin-induced rats at 4-, 8-, and 10-weeks post-injection. Statistical analysis was performed using one-way ANOVA (* p ≤ 0.05).
Figure 10. Quantification of T lymphocytes in rat retina. Graph (a) shows CD4+ cell counts and graph (b) shows CD8+ cell counts in retinal tissue from control rats at 10 weeks following a single dose of citrate buffer, and from streptozotocin-induced rats at 4-, 8-, and 10-weeks post-injection. Statistical analysis was performed using one-way ANOVA (* p ≤ 0.05).
Ijms 27 03427 g010

2.3.5. Gene Expression Profile in Retinal Tissue of Streptozotocin-Induced Animals

The gene expression profile indicates a proinflammatory and pro-oxidative retinal microenvironment in STZ-induced rats, characterized by the activation of angiogenic pathways (Vegfa) and proliferative signals (Egf). Concurrently, the antioxidant response appears to be partially compromised. The upregulation of Sod2 and Cat suggests compensatory activation of endogenous antioxidant defenses in response to excessive production of reactive oxygen species (ROS). However, the downregulation of Nfe2l2 may imply that Sod2 and Cat are being upregulated through alternative mechanisms such as cytokine-mediated signaling or mitochondrial feedback rather than through coordinated transcriptional control by Nfe2l2.
The overexpression of Nos2 and Hmox1 reflects a cellular response to nitrosative and oxidative stress, while the reduced expression of Il10 may indicate suppression of anti-inflammatory signaling. Finally, the increased expression of Tgfb1 could suggest activation of fibrogenic or immunomodulatory pathways, Figure 11. Collectively, these findings are consistent with the early pathophysiological features of diabetic retinopathy.
Ijms 27 03427 g011
Figure 11. Analysis of oxidative stress and antioxidant gene expression in rat retina following streptozotocin administration. The relative expression of genes associated with oxidative stress (Ifng, Nos2, Vegfa, Egf) and antioxidant defense (Nfe2l2, Hmox1, Sod2, Cat, Il10, and Tgfb1) was evaluated in retinal tissue ten weeks after a single intraperitoneal dose of streptozotocin. Gene expression was quantified by real-time PCR using β-actin mRNA as the internal reference (2ΔCT method). Relative expression levels were calculated using the 2ΔΔCT method, comparing STZ-induced rats to healthy controls. (a) Relative expression of oxidative stress-related genes. Significant differences were observed between the control and STZ groups. (b) Relative expression of antioxidant-related genes. Mean expression levels of each gene were significantly altered in STZ-induced rats compared to healthy controls. Data are presented as mean ± SD. Statistical analysis was performed using one way ANOVA followed by Tukey’s multiple comparison test (* p ≤ 0.05, *** p ≤ 0.001).
Figure 11. Analysis of oxidative stress and antioxidant gene expression in rat retina following streptozotocin administration. The relative expression of genes associated with oxidative stress (Ifng, Nos2, Vegfa, Egf) and antioxidant defense (Nfe2l2, Hmox1, Sod2, Cat, Il10, and Tgfb1) was evaluated in retinal tissue ten weeks after a single intraperitoneal dose of streptozotocin. Gene expression was quantified by real-time PCR using β-actin mRNA as the internal reference (2ΔCT method). Relative expression levels were calculated using the 2ΔΔCT method, comparing STZ-induced rats to healthy controls. (a) Relative expression of oxidative stress-related genes. Significant differences were observed between the control and STZ groups. (b) Relative expression of antioxidant-related genes. Mean expression levels of each gene were significantly altered in STZ-induced rats compared to healthy controls. Data are presented as mean ± SD. Statistical analysis was performed using one way ANOVA followed by Tukey’s multiple comparison test (* p ≤ 0.05, *** p ≤ 0.001).
Ijms 27 03427 g011

3. Discussion

3.1. Pharmacological Induction of Diabetes Mellitus

The pharmacological induction of pancreatic β-cell destruction remains the most widely employed method for modeling type 1-like diabetes mellitus in rodents. Streptozotocin (STZ), administered via a single intraperitoneal injection, reliably induces hyperglycemia at doses ranging from 150 to 200 mg/kg in mice and 30 to 80 mg/kg in rats [61]. In the present study, we administered STZ at a dose of 65 mg/kg body weight, a concentration well tolerated by Wistar rats and effective in inducing diabetes. The diabetic state was confirmed by alterations in glycemic control, vascular integrity, and immunological parameters.
Previous studies using Sprague-Dawley rats reported significant weight loss (28 ± 20 g) within the first 72 h following a 65 mg/kg STZ dose, whereas doses of 40 or 50 mg/kg did not exhibit significant changes in body weight [62]. Consistent with these findings, our STZ-induced Wistar rats maintained stable body weight throughout the experimental period. In contrast, control animals subjected to the same hypercaloric diet exhibited a statistically significant increase in body weight. Notably, STZ-induced rats showed a marked reduction in adipose tissue, with minimal or absent brown fat deposits at euthanasia, while control rats retained visible abdominal brown adipose tissue.

3.2. Pathophysiological Effects of Streptozotocin-Induced Diabetes Mellitus

STZ-induced diabetes leads to persistent hyperglycemia, with blood glucose levels exceeding 200 mg/dL within the first week and surpassing 400 mg/dL thereafter findings consistent with previous reports [62]. In our study, some animals reached glycemic values above 600 mg/dL, exceeding the detection limit of the glucometer (Figure 2).
Beyond systemic metabolic disruption, STZ-induced diabetes caused progressive retinal damage, including hemorrhage, fibrovascular proliferation, and detachment of the photosensitive layer. These findings are consistent with those reported by Moldovan [63]. The alterations observed between weeks 2 and 10 post-induction represent hallmark features of proliferative diabetic retinopathy (Figure 3, Figure 4, Figure 5 and Figure 6) [61].

3.3. CD4+ and CD8+ T Lymphocytes

Immunofluorescence analysis revealed increased infiltration of CD4+ and CD8+ T lymphocytes in the retina (Figure 8 and Figure 9), particularly in the photoreceptor and nuclear layers. Although less evident than histological sections, the presence of retinal injury was discernible and consistent with diabetic retinopathy. Comparative studies have shown a predominance of CD4+ over CD8+ cells in DR models, a pattern replicated in our findings [64]. This adaptive immune-mediated inflammation was especially pronounced in the inner plexiform, nuclear, and photoreceptor layers.
By week 4, erythrocytes were detected in the inner plexiform layer (Figure 4), likely originating from newly formed blood vessels, accompanied by edema in the ganglion cell layer. These features intensified by week 8 (Figure 5), with detachment of the ganglion cell layer. At week 10 (Figure 6), edema extended into deeper retinal layers, and neovascular structures became more prominent. These cumulative changes validate the model as a reliable representation of diabetic glaucoma. Importantly, CD4+ and CD8+ T cells were elevated not only in the retina but also in peripheral blood and lymphoid tissues [65]. CD4+ T cells, crucial for immune homeostasis, are upregulated during diabetes progression [66], while CD8+ cells contribute to retinal neovascularization and vascular leakage, driving pathological angiogenic in DR [65].

3.4. Molecular and Oxidative Mechanisms

Oxidative stress plays a central role in DR pathogenesis, exacerbating hyperglycemia-induced metabolic disturbances and triggering molecular cascades that compromise retinal integrity [67]. Our PCR data revealed proinflammatory and pro-oxidative retinal microenvironment in STZ-induced rats, marked by upregulation of Nos2, a key indicator of nitrosative and oxidative stress. These findings align with reports linking iNOS expression to diabetes duration and early vascular [68,69].
The down regulation of IL-10 suggests impaired anti-inflammatory signaling, potentially favoring activation of M1 macrophages, microglia, and B cells, as observed in DR patient samples [70,71,72,73]. This inflammatory shift may further amplify oxidative damage and vascular dysfunction.
Angiogenic and proliferative pathways were also activated, as evidenced by increased Vegfa and Egf expression. Vegfa, a member of the cystine knot superfamily, promotes angiogenesis and vascular permeability under hypoxic and oxidative conditions [74,75,76]. Its upregulation in serum and ocular fluids correlates with leukocyte adhesion, ICAM-1 expression, and neovascularization in proliferative DR [70,77,78]. Egf similarly enhances retinal cell proliferation and neovascular formation [73,79].
These angiogenic signals may be potentiated by PKC pathway activation, which increases endothelial permeability and Vegfa expression [51,80]. Moreover, hyperglycemia, ROS, cytokines, PKC, and AGEs activate NF-κB, a transcription factor regulating over 500 genes, including VEGF, IL-1, IL-6, TNF-α, MCP-1, VCAM-1, and PDGF [81,82,83].
Interestingly, while Sod2 and Cat were upregulated suggesting a compensatory antioxidant response, the downregulation of Nfe2l2 implies alternative regulatory mechanisms. Although Nfe2l2 nuclear levels increase in STZ-induced diabetic retinas, its binding to the antioxidant response element (ARE4) is impaired under hyperglycemia, reducing Gclc expression and GSH synthesis [84,85,86]. Histone methylation at the Gclc-ARE4 locus may further hinder Nfe2l2 binding, and this repression persists even after glucose normalization.
Hmox1, a stress-inducible enzyme with antioxidant, anti-inflammatory, and anti-apoptotic properties, was also upregulated. Its induction modulates macrophage polarization toward the anti-inflammatory M2 phenotype, inhibits dendritic cell maturation, and promotes Treg responses, thereby mitigating oxidative stress and inflammation [87]. Hmox1 also protects against pyroptosis and ferroptosis, emerging form of programmed cell death implicated in diabetic complications.
Finally, increased Tgfb1 expression may reflect activation of fibrogenic and immunomodulatory pathways, contributing to endothelial proliferation and neovascularization [73,79]. Conversely, Il10 downregulation may impair Vegfa suppression, fostering a proangiogenic environment [88,89].

4. Materials and Methods

4.1. Animals

A total of 30 male Wistar rats (6–8 weeks old; 150–220 g body weight) were obtained from the Bioterium of the Universidad Autónoma de Aguascalientes. Animals were housed under controlled environmental conditions (24 ± 2 °C; 55.5 ± 5% relative humidity) with a 12 h light/dark cycle and had ad libitum access to standard chow and water. Following a 7-day acclimatization period, the rats were randomly assigned into five experimental groups: a healthy control group (n = 5), which received a single intraperitoneal (i.p.) injection of citrate buffer (vehicle), and four streptozotocin (STZ)-induced diabetic groups (n = 5 per group), monitored at 2, 4, 8, and 10 weeks post-induction (total n = 20). To ensure the integrity of longitudinal study and account for potential attrition, we induced diabetes in five additional rats. This precaution allowed us to maintain a complete n = 5 per group throughout the 10- week follow-up, despite the loss of four animals’ post-induction.
All procedures were reviewed and approved by the Research, Bioethics, and Biosecurity Committees of the Universidad Autónoma de Aguascalientes (protocol INV 798/2021) and conducted in accordance with the Mexican Official Standard for the Care and Use of Laboratory Animals (NOM-062-ZOO-1999; revised 2001).

4.2. Induction of Type 1 Diabetes Mellitus (STZ Model)

Type 1 diabetes mellitus was induced following a 12-h fasting period via a single i.p. injection of streptozotocin (STZ; 65 mg/kg body weight; cat. S0130-1G, Sigma-Aldrich, St. Louis, MO, USA) freshly dissolved in 0.1 M citrate buffer (pH 4.5) [90]. Control animals received an equivalent volume (200 µL) of citrate buffer without STZ. Diabetes was confirmed by measuring the fasting glucose concentration (glucose ≥ 200 mg/dL) 1 week after STZ administration.
At the end of each experimental period, animals were euthanized by intraperitoneal administration of sodium pentobarbital (1.5 mL/100 g body weight), using a double dose relative to that required for sedation. Collected tissues were fixed in 4% paraformaldehyde and processed for histological analysis [91].

4.3. Analytical Procedures

4.3.1. Blood Glucose Monitoring

Blood glucose levels were measured using an Accu-Check PerformaTM glucometer (Roche Diabetes Care, Mannheim, Germany). Samples were collected in the morning via tail-tip puncture.

4.3.2. Body Weight

Rats were weighed weekly throughout the experimental period to monitor changes in body mass.

4.3.3. Histological Analysis

Histological evaluations included hematoxylin and eosin staining, as well as indirect immunofluorescence. Primary antibodies were used at a concentration of 1:500, specifically CD4 Monoclonal (cat. 11-0041-82, Invitrogen, Waltham, MA, USA) and CD8 (cat. MCA1576GA, Bio-Rad, Hercules, CA, USA). Secondary antibodies were applied at a concentration of 1:1000, including Alexa Fluor® 488 (cat. A11008, Invitrogen, Waltham, MA, USA) and 596 (cat. A11005, Invitrogen, Waltham, MA, USA). Nuclear staining was performed using Hoechst dye (cat. 33258, Thermo-Fisher, Waltham, MA, USA). Image acquisition and analysis were conducted with Image-pro Plus Software Version 5.4.0.19 (Media Cybernetics, Inc., Rockville, MD, USA), employing a Cool Snap-pro CF camera mounted on a Axioskop 40 microscope (Zeiss, Oberkochen, Germany).

4.3.4. RNA Extraction and Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)

Total RNA was isolated from the retinal tissue of healthy and STZ-induced rats using Trizol Reagent (cat. 15596026, Invitrogen, Waltham, MA, USA), strictly following the manufacturer’s protocol. Next, 5 µg of RNA from each sample were reverse transcribed using the High-Capacity cDNA Archive Kit (cat. 4322171, Applied Biosystems, Foster City, CA, USA). The resulting cDNA was amplified by quantitative real-time PCR on the SDS 7300 system (Applied Biosystems). β-actin served as the endogenous control due to its constitutive expression as a housekeeping gene. All reactions were performed in duplicate. Gene expression levels of Ifng, Nos2, Vegfa, Egf, Nfe2l2, Hmox1, Sod2, Cat, Il10, and Tgfb1 were normalized to β-actin, and relative expression changes were calculated using the 2−ΔΔCT method.

4.3.5. Data Analysis

Image processing and quantification were conducted using Fiji software version 2.16.0/1.5p (Fiji Is Just ImageJ, GNU General Public License) [92], with subsequent deep learning-assisted classification performed via Ilastik. Positive cells were counted per field to estimate cell density (cells/mm2). Comparison of gene expression between experimental and control groups was conducted using Student’s t-test or one-way analysis of variance (ANOVA), as appropriate. A p-value < 0.05 was considered statistically significant. Graphs and statistical analyses were generated using GraphPad Prism 9 for macOS.

5. Conclusions

Our findings underscore the multifactorial nature of diabetic retinopathy, wherein oxidative stress, inflammation, and angiogenesis converge to destabilize retinal homeostasis. The STZ-induced model employed in this study faithfully recapitulates key molecular and histopathological hallmarks of human DR, thereby providing a robust and reproducible platform for mechanistic investigations and therapeutic development.

Future Directions

Critically, future investigations in the fields of metabolic diseases and ophthalmology would be enriched by:
Early confirmation of neovascularization through histological analysis using Isolectin B4 staining.
Characterization of molecular factors preceding mitophagy deregulation, including the PINK1/Parkin signaling pathway, NLRP3 inflammasome activation, TXNIP involvement, Drp1, Mfn1/Mfn2, VDAC1, ZO-1, the LC3-II/LC3-I ratio, Sirt3, as well as BNIP3/Nix and FUNDC1 non-canonical pathways.
Exploration of calcium overload, which may induce mitochondrial permeability transition (mPT) via the mPTP pore, thereby facilitating the release of cytochrome c and other mitochondrial components.
The integration of multi-omics technologies will enable the identification of novel therapeutic targets with greater specificity and reduced adverse effects, supporting the development of more precise treatment for diabetic retinopathy. In parallel, the incorporation of Optical Coherence Tomography (OCT) for structural assessments and of Optical Coherence Tomography Angiography (OCT-A) for vascular function will provide an additional clinical dimension. These non-invasive imaging modalities, by complementing molecular and histological analyses, will allow longitudinal monitoring of retinal alterations, thereby strengthening translational relevance and broadening the scope of potential clinical applications.

Author Contributions

Conceptualization, L.F.B.-G. and M.E.Á.-B.; Methodology, M.H.M.-O., R.C.M.-R. and M.R.-D.; Software, M.E.Á.-B.; Validation, M.E.Á.-B.; Formal analysis, M.E.Á.-B. and E.C.-C.; Investigation, M.E.Á.-B. and L.H.S.-H.; Resources, J.V.-J.; Writing—original draft, L.F.B.-G. and J.V.-J.; Writing—review & editing, P.L.G.-Á.; Supervision, L.F.B.-G.; Project administration, L.F.B.-G.; Funding acquisition, J.L.D.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Universidad Autónoma de Aguascalientes, grant number UAA-DGIP-PIBB22-1.

Institutional Review Board Statement

The animal study protocol was approved by the Institutional Review Board (or Ethics Committee) of Universidad Autónoma de Aguascalientes (protocol code INV 798/2021, approval date on 19 October 2021).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
DRDiabetic retinopathy
STZStreptozotocin
ROSReactive oxygen species
O2⋅−Superoxide anion
H2O2Hydrogen peroxide
ROO⋅Peroxyl radicals
⋅OHHydroxyl radicals
NVNeovascularization
PDRProliferative diabetic retinopathy
NPDRNon-proliferative diabetic retinopathy
MAMicroaneurysms
BMBasement membrane
DMDDirect macular damage
DMEDiabetic macular edema
BRBBlood-retinal barrier
DMDiabetes mellitus
IOPIntraocular pressure
H&EHematoxylin and eosin
RNARibonucleic acid
cDNAComplementary deoxyribonucleic acid
PCRPolymerase chain reaction
ANOVAAnalysis of variance
CD4Cluster of differentiation 4, often called helper T cells
CD8Cluster of differentiation 8, often called cytotoxic T lymphocytes
VegfaVascular endothelial growth factor
EgfEpidermal growth factor
IfngInterferon gamma
Nos2Inducible nitric oxide synthase
Nfe2l2Nuclear factor erythroid 2-related factor 2
Hmox1Heme oxygenase-1
Sod2Mitochondrial superoxide dismutase 2
CatCatalase
Il10Interleukin-10
Tgfb1Transforming Growth Factor-beta
PKCProtein kinase C
AGEsAdvanced Glycation End-products
NF-κBNuclear Factor-kappa B
IL-1Interleukin-1
IL-6Interleukin-6
TNF-αTumor Necrosis Factor-alpha
MCP-1Monocyte chemoattractant protein-1
VCAM-1Vascular cell adhesion molecule-1
PDGFPlatelet-derived growth factor
GCLC-ARE4Glutamate-cysteine ligase catalytic subunit-antioxidant response elements 4
PINK1PTEN-induced putative kinase protein 1
BNIP3Bcl-2 and adenovirus E1B 19-kDa interacting protein 3
NixBNIP3-like protein (BNIP3L, also known as Nix) are homologous of the Bcl-2 family of proteins.
FUNDC1Fun14 domain-containing protein 1
LC3Light chain 3 protein
Drp1Dynamin-related protein 1
NLRP3NOD-, LRR-, and pyrin domain-containing protein 3
TXNIPThioredoxin-interacting protein
mtDNAMitochondrial DNA
mtROSMitochondrial reactive oxygen species
RPERetinal pigment epithelium
RECRetinal endothelial cells

References

  1. Sivaprasad, S.; Gupta, B.; Crosby-Nwaobi, R.; Evans, J. Prevalence of Diabetic Retinopathy in Various Ethnic Groups: A Worldwide Perspective. Surv. Ophthalmol. 2012, 57, 347–370. [Google Scholar] [CrossRef]
  2. Jampol, L.M.; Glassman, A.R.; Sun, J. Evaluation and Care of Patients with Diabetic Retinopathy. N. Engl. J. Med. 2020, 382, 1629–1637. [Google Scholar] [CrossRef]
  3. Gadekallu, T.R.; Khare, N.; Bhattacharya, S.; Singh, S.; Maddikunta, P.K.R.; Srivastava, G. Deep neural networks to predict diabetic retinopathy. J. Ambient. Intell. Humaniz. Comput. 2023, 14, 5407–5420. [Google Scholar] [CrossRef]
  4. Lachin, J.M.; Genuth, S.; Nathan, D.M.; Zinman, B.; Rutledge, B.N. Effect of glycemic exposure on the risk of microvascular complications in the diabetes control and complications trial-revisited. Diabetes 2008, 57, 995–1001. [Google Scholar] [CrossRef]
  5. Chew, E.Y.; Davis, M.D.; Danis, R.P.; Lovato, J.F.; Perdue, L.H.; Greven, C.; Genuth, S.; Goff, D.C.; Leiter, L.A.; Ismail-Beigi, F.; et al. The Effects of Medical Management on the Progression of Diabetic Retinopathy in Persons with Type 2 Diabetes. Ophthalmology 2014, 121, 2443–2451. [Google Scholar] [CrossRef]
  6. Song, K.H.; Jeong, J.S.; Kim, M.K.; Kwon, H.S.; Baek, K.H.; Ko, S.H.; Ahn, Y.B. Discordance in risk factors for the progression of diabetic retinopathy and diabetic nephropathy in patients with type 2 diabetes mellitus. J. Diabetes Investig. 2019, 10, 745–752. [Google Scholar] [CrossRef] [PubMed]
  7. Takao, T.; Takahashi, K.; Yoshida, Y.; Kushiyama, A.; Onishi, Y.; Tahara, T.; Shimmei, A.; Kikuchi, T.; Suka, M.; Yanagisawa, H.; et al. Effect of postprandial hyperglycemia at clinic visits on the incidence of retinopathy in patients with type 2 diabetes: An analysis using real-world long-term follow-up data. J. Diabetes Investig. 2020, 11, 930–937. [Google Scholar] [CrossRef] [PubMed]
  8. Klein, R.; Knudtson, M.D.; Lee, K.E.; Gangnon, R.; Klein, B.E.K. The Wisconsin Epidemiologic Study of Diabetic Retinopathy XXII: The Twenty-Five-Year Progression of Retinopathy in Persons with Type 1 Diabetes. Ophthalmology 2008, 115, 1859–1868. [Google Scholar] [CrossRef]
  9. Cheung, N.; Mitchell, P.; Wong, T.Y. Diabetic retinopathy. Lancet 2010, 376, 124–136. [Google Scholar] [CrossRef] [PubMed]
  10. Lu, J.; Ma, X.; Zhang, L.; Mo, Y.; Ying, L.; Lu, W.; Zhu, W.; Bao, Y.; Zhou, J. Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes. J. Diabetes Investig. 2019, 10, 753–759. [Google Scholar] [CrossRef]
  11. Beli, E.; Yan, Y.; Moldovan, L.; Vieira, C.P.; Gao, R.; Duan, Y.; Prasad, R.; Bhatwadekar, A.; White, F.A.; Townsend, S.D.; et al. Restructuring of the gut microbiome by intermittent fasting prevents retinopathy and prolongs survival in db/db mice. Diabetes 2018, 67, 1867–1879. [Google Scholar] [CrossRef]
  12. Cunha-Vaz, J. Characterization and relevance of different diabetic retinopathy phenotypes. Dev. Ophthalmol. 2007, 39, 13–30. [Google Scholar] [CrossRef]
  13. Nentwich, M.M. Diabetic retinopathy—Ocular complications of diabetes mellitus. World J. Diabetes 2015, 6, 489–499. [Google Scholar] [CrossRef]
  14. Roy, S.; Kim, D. Retinal capillary basement membrane thickening: Role in the pathogenesis of diabetic retinopathy. Prog. Retin. Eye Res. 2021, 82, 100903. [Google Scholar] [CrossRef] [PubMed]
  15. Wong, T.Y.; Cheung, C.M.G.; Larsen, M.; Sharma, S.; Simó, R. Diabetic retinopathy. Nat. Rev. Dis. Primers 2016, 2, 16012, Erratum in Nat. Rev. Dis. Primers 2016, 2, 16030. https://doi.org/10.1038/nrdp.2016.30. [Google Scholar] [CrossRef] [PubMed]
  16. Heng, L.Z.; Comyn, O.; Peto, T.; Tadros, C.; Ng, E.; Sivaprasad, S.; Hykin, P.G. Diabetic retinopathy: Pathogenesis, clinical grading, management and future developments. Diabet. Med. 2013, 30, 640–650. [Google Scholar] [CrossRef] [PubMed]
  17. Flaxman, S.R.; Bourne, R.R.A.; Resnikoff, S.; Ackland, P.; Braithwaite, T.; Cicinelli, M.V.; Das, A.; Jonas, J.B.; Keeffe, J.; Kempen, J.H.; et al. Global causes of blindness and distance vision impairment 1990–2020: A systematic review and meta-analysis. Lancet Glob. Health 2017, 5, e1221–e1234. [Google Scholar] [CrossRef]
  18. Mathews, P.M.; Lindsley, K.; Aldave, A.J.; Akpek, E.K. Etiology of global corneal blindness and current practices of corneal transplantation: A focused review. Cornea 2018, 37, 1198–1203. [Google Scholar] [CrossRef]
  19. Steinmetz, J.D.; Bourne, R.R.A.; Briant, P.S.; Flaxman, S.; Taylor, H.R.; Jonas, J.B.; Abdoli, A.A.; Abrha, W.A.; Abualhasan, A.; Abu-Gharbieh, E.G.; et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: The Right to Sight: An analysis for the Global Burden of Disease Study. Lancet Glob. Health 2021, 9, e144–e160, Correction in Lancet Glob. Health 2021, 2, 144–160. [Google Scholar] [CrossRef]
  20. Zheng, Y.; He, M.; Congdon, N. The worldwide epidemic of diabetic retinopathy. Indian J. Ophthalmol. 2012, 60, 428–431. [Google Scholar] [CrossRef]
  21. Lee, R.; Wong, T.Y.; Sabanayagam, C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis. 2015, 2, 17. [Google Scholar] [CrossRef] [PubMed]
  22. Giacco, F.; Brownlee, M. Oxidative stress and diabetic complications. Circ. Res. 2010, 107, 1058–1070. [Google Scholar] [CrossRef]
  23. Gueven, N.; Nadikudi, M.; Daniel, A.; Chhetri, J. Targeting mitochondrial function to treat optic neuropathy. Mitochondrion 2017, 36, 7–14. [Google Scholar] [CrossRef]
  24. Santos, J.M.; Tewari, S.; Lin, J.Y.; Kowluru, R.A. Interrelationship between activation of matrix metalloproteinases and mitochondrial dysfunction in the development of diabetic retinopathy. Biochem. Biophys. Res. Commun. 2013, 438, 760–764. [Google Scholar] [CrossRef]
  25. Prasad, S.; Gupta, S.C.; Tyagi, A.K. Reactive oxygen species (ROS) and cancer: Role of antioxidative nutraceuticals. Cancer Lett. 2017, 387, 95–105. [Google Scholar] [CrossRef]
  26. Brownlee, M. Biochemistry and molecular cell biology of diabetic complications. Nature 2001, 414, 813–820. [Google Scholar] [CrossRef]
  27. Khan, Z.A.; Chakrabarti, S. Cellular signaling and potential new treatment targets in diabetic retinopathy. Exp. Diabetes Res. 2007, 2007, 031867. [Google Scholar] [CrossRef]
  28. Madsen-Bouterse, S.A.; Kowluru, R.A. Oxidative stress and diabetic retinopathy: Pathophysiological mechanisms and treatment perspectives. Rev. Endocr. Metab. Disord. 2008, 9, 315–327. [Google Scholar] [CrossRef]
  29. Alam, N.M.; Iv, W.C.M.; Wong, A.A.; Douglas, R.M.; Szeto, H.H.; Prusky, G.T. A mitochondrial therapeutic reverses visual decline in mouse models of diabetes. DMM Dis. Models Mech. 2015, 8, 701–710. [Google Scholar] [CrossRef]
  30. Robinson, R.; Barathi, V.A.; Chaurasia, S.S.; Wong, T.Y.; Kern, T.S. Update on animal models of diabetic retinopathy: From molecular approaches to mice and higher mammals. DMM Dis. Models Mech. 2012, 5, 444–456. [Google Scholar] [CrossRef] [PubMed]
  31. Dan Dunn, J.; Alvarez, L.A.J.; Zhang, X.; Soldati, T. Reactive oxygen species and mitochondria: A nexus of cellular homeostasis. Redox Biol. 2015, 6, 472–485. [Google Scholar] [CrossRef]
  32. Kowluru, R.A.; Kowluru, A.; Mishra, M.; Kumar, B. Oxidative stress and epigenetic modifications in the pathogenesis of diabetic retinopathy. Prog. Retin. Eye Res. 2015, 48, 40–61. [Google Scholar] [CrossRef]
  33. Kowluru, R.A. Diabetic retinopathy: Mitochondrial dysfunction and retinal capillary cell death. Antioxid. Redox Signal. 2005, 7, 1581. [Google Scholar] [CrossRef] [PubMed]
  34. Poprac, P.; Jomova, K.; Simunkova, M.; Kollar, V.; Rhodes, C.J.; Valko, M. Targeting Free Radicals in Oxidative Stress-Related Human Diseases. Trends Pharmacol. Sci. 2017, 38, 592–607. [Google Scholar] [CrossRef] [PubMed]
  35. Hammes, H.P. Diabetic retinopathy: Hyperglycaemia, oxidative stress and beyond. Diabetologia 2018, 61, 29–38. [Google Scholar] [CrossRef]
  36. Sachdeva, M.M. Retinal Neurodegeneration in Diabetes: An Emerging Concept in Diabetic Retinopathy. Curr. Diabetes Rep. 2021, 21, 65. [Google Scholar] [CrossRef] [PubMed]
  37. Lee, H.B.; Yu, M.R.; Yang, Y.; Jiang, Z.; Ha, H. Reactive oxygen species-regulated signaling pathways in diabetic nephropathy. J. Am. Soc. Nephrol. 2003, 14, S241–S245. [Google Scholar] [CrossRef]
  38. Bonfiglio, V.; Platania, C.B.M.; Lazzara, F.; Conti, F.; Pizzo, C.; Reibaldi, M.; Russo, A.; Fallico, M.; Ortisi, E.; Pignatelli, F.; et al. Tgf-β serum levels in diabetic retinopathy patients and the role of anti-vegf therapy. Int. J. Mol. Sci. 2020, 21, 9558. [Google Scholar] [CrossRef] [PubMed]
  39. Liu, C.H.; Wang, Z.; Sun, Y.; Chen, J. Animal models of ocular angiogenesis: From development to pathologies. FASEB J. 2017, 31, 4665–4681. [Google Scholar] [CrossRef]
  40. Chu, J.; Ali, Y. Diabetic retinopathy: A review. Drug Dev. Res. 2008, 69, 1–14. [Google Scholar] [CrossRef]
  41. Wang, L.Z.; Cheung, C.Y.; Tapp, R.J.; Hamzah, H.; Tan, G.; Ting, D.; Lamoureux, E.; Wong, T.Y. Availability and variability in guidelines on diabetic retinopathy screening in Asian countries. Br. J. Ophthalmol. 2017, 101, 1352–1360. [Google Scholar] [CrossRef]
  42. Roy, S.; Ha, J.; Trudeau, K.; Beglova, E. Vascular basement membrane thickening in diabetic retinopathy. Curr. Eye Res. 2010, 35, 1045–1056. [Google Scholar] [CrossRef] [PubMed]
  43. Andersen, N.; Hjortdal, J.Ø.; Schielke, K.C.; Bek, T.; Grauslund, J.; Laugesen, C.S.; Andersen, H.L.; Cerqueira, C.; Andresen, J. The Danish registry of diabetic retinopathy. Clin. Epidemiol. 2016, 8, 613–619. [Google Scholar] [CrossRef]
  44. Rodríguez, M.L.; Pérez, S.; Mena-Mollá, S.; Desco, M.C.; Ortega, Á.L. Oxidative Stress and Microvascular Alterations in Diabetic Retinopathy: Future Therapies. Oxidative Med. Cell. Longev. 2019, 2019, 4940825. [Google Scholar] [CrossRef] [PubMed]
  45. Wykoff, C.C.; Khurana, R.N.; Nguyen, Q.D.; Kelly, S.P.; Lum, F.; Hall, R.; Abbass, I.M.; Abolian, A.M.; Stoilov, I.; To, T.M.; et al. Risk of blindness among patients with diabetes and newly diagnosed diabetic retinopathy. Diabetes Care 2021, 44, 748–756. [Google Scholar] [CrossRef]
  46. Kirwin, S.J.; Kanaly, S.T.; Hansen, C.R.; Cairns, B.J.; Ren, M.; Edelman, J.L. Retinal gene expression and visually evoked behavior in diabetic Long Evans rats. Investig. Ophthalmol. Vis. Sci. 2011, 52, 7654–7663. [Google Scholar] [CrossRef][Green Version]
  47. Kowluru, R.A.; Kowluru, A.; Veluthakal, R.; Mohammad, G.; Syed, I.; Santos, J.M.; Mishra, M. TIAM1-RAC1 signalling axis-mediated activation of NADPH oxidase-2 initiates mitochondrial damage in the development of diabetic retinopathy. Diabetologia 2014, 57, 1047–1056. [Google Scholar] [CrossRef] [PubMed]
  48. Rodrigues, E.B.; Urias, M.G.; Penha, F.M.; Badaró, E.; Novais, E.; Meirelles, R.; Farah, M.E. Diabetes induces changes in neuroretina before retinal vessels: A spectral-domain optical coherence tomography study. Int. J. Retin. Vitr. 2015, 1, 4. [Google Scholar] [CrossRef]
  49. Sun, J.K.; Keenan, H.A.; Cavallerano, J.D.; Asztalos, B.F.; Schaefer, E.J.; Sell, D.R.; Strauch, C.M.; Monnier, V.M.; Doria, A.; Aiello, L.P.; et al. Protection from retinopathy and other complications in patients with type 1 diabetes of extreme duration: The Joslin 50-year medalist study. Diabetes Care 2011, 34, 968–974. [Google Scholar] [CrossRef]
  50. Praidou, A.; Androudi, S.; Brazitikos, P.; Karakiulakis, G.; Papakonstantinou, E.; Dimitrakos, S. Angiogenic Growth Factors and their Inhibitors in Diabetic Retinopathy. Curr. Diabetes Rev. 2010, 6, 304–312. [Google Scholar] [CrossRef]
  51. Titchenell, P.M.; Antonetti, D.A. Using the past to inform the future: Anti-VEGF therapy as a road map to develop novel therapies for diabetic retinopathy. Diabetes 2013, 62, 1808–1815. [Google Scholar] [CrossRef]
  52. D’Amico, A.G.; Maugeri, G.; Magrì, B.; Bucolo, C.; D’Agata, V. Targeting the PINK1/Parkin pathway: A new perspective in the prevention and therapy of diabetic retinopathy. In Experimental Eye Research; Academic Press: Cambridge, MA, USA, 2024. [Google Scholar] [CrossRef] [PubMed]
  53. Li, M.; Yang, L.; Zhai, H.; Qiao, L.; Wang, Z.; An, X.; Wang, J. A new perspective on protecting the blood-retinal barrier against injury in diabetic retinopathy: Mitophagy. Front. Endocrinol. 2025, 16, 1617797. [Google Scholar] [CrossRef]
  54. Duh, E.J.; Sun, J.K.; Stitt, A.W. Diabetic retinopathy: Current understanding, mechanisms, and treatment strategies. JCI Insight 2017, 2, e93751. [Google Scholar] [CrossRef] [PubMed]
  55. Simó, R.; Sundstrom, J.M.; Antonetti, D.A. Ocular anti-VEGF therapy for diabetic retinopathy: The role of VEGF in the pathogenesis of diabetic retinopathy. Diabetes Care 2014, 37, 893–899. [Google Scholar] [CrossRef] [PubMed]
  56. Nguyen, Q.D.; Brown, D.M.; Marcus, D.M.; Boyer, D.S.; Patel, S.; Feiner, L.; Gibson, A.; Sy, J.; Rundle, A.C.; Hopkins, J.J.; et al. Ranibizumab for diabetic macular edema: Results from 2 phase iii randomized trials: RISE and RIDE. Ophthalmology 2012, 119, 789–801. [Google Scholar] [CrossRef]
  57. Korobelnik, J.F.; Do, D.V.; Schmidt-Erfurth, U.; Boyer, D.S.; Holz, F.G.; Heier, J.S.; Midena, E.; Kaiser, P.K.; Terasaki, H.; Marcus, D.M.; et al. Intravitreal aflibercept for diabetic macular edema. Ophthalmology 2014, 121, 2247–2254. [Google Scholar] [CrossRef]
  58. Wang, W.; Lo, A.C.Y. Diabetic retinopathy: Pathophysiology and treatments. Int. J. Mol. Sci. 2018, 19, 1816. [Google Scholar] [CrossRef]
  59. Choi, M.Y.; Jee, D.; Kwon, J.W. Characteristics of diabetic macular edema patients refractory to anti-VEGF treatments and a dexamethasone implant. PLoS ONE 2019, 14, e0222364. [Google Scholar] [CrossRef] [PubMed]
  60. Quiroz, J.; Yazdanyar, A. Animal models of diabetic retinopathy. Ann. Transl. Med. 2021, 9, 1272. [Google Scholar] [CrossRef]
  61. Pitale, P.M.; Gorbatyuk, M.S. Diabetic Retinopathy: From Animal Models to Cellular Signaling. Int. J. Mol. Sci. 2022, 23, 1487. [Google Scholar] [CrossRef]
  62. Vélez, S.; Gómez, L.; Tapia, D.; Guerrero, E.; Morán, J. Estandarización del modelo de diabetes experimental inducida por estreptozotocina en ratas sprague-dawley. Rev. Médico Científica 2015, 28, 4–13. [Google Scholar]
  63. Moldovan, M.; Capraș, R.D.; Paşcalău, R.; Filip, G.A. Molecular Findings Before Vision Loss in the Streptozotocin-Induced Rat Model of Diabetic Retinopathy. Curr. Issues Mol. Biol. 2025, 47, 28. [Google Scholar] [CrossRef]
  64. Cantón, A.; Martinez-Cáceres, E.M.; Hernández, C.; Espejo, C.; García-Arumí, J.; Simó, R. CD4-CD8 and CD28 expression in t cells infiltrating the vitreous fluidin patients with proliferative diabetic retinopathy: A flow cytometric analysis. Arch. Ophthalmol. 2004, 122, 743–749. [Google Scholar] [CrossRef]
  65. Bayless, K.J. Direct Involvement of CD8+ T Cells in Retinal Angiogenesis. In Arteriosclerosis, Thrombosis, and Vascular Biology; Lippincott Williams & Wilkins Hagerstown: Hagerstown, MD, USA, 2023; pp. 537–539. [Google Scholar]
  66. Yu, H.; Liu, B.; Wu, G.; Du, Z.; Wu, Q.; Zeng, X.; Xiao, Y.; Fang, F.; Yuan, L.; Ma, S.; et al. Dysregulation of circulating follicular helper T cells in type 2 diabetic patients with diabetic retinopathy. Immunol. Res. 2021, 69, 153–161. [Google Scholar] [CrossRef]
  67. Li, C.; Miao, X.; Li, F.; Wang, S.; Liu, Q.; Wang, Y.; Sun, J. Oxidative stress-related mechanisms and antioxidant therapy in diabetic retinopathy. Oxid. Med. Cell Longev. 2017, 2017, 9702820. [Google Scholar] [CrossRef]
  68. Nagareddy, P.R.; Xia, Z.; McNeill, J.H.; MacLeod, K.M. Increased expression of iNOS is associated with endothelial dysfunction and impaired pressor responsiveness in streptozotocin-induced diabetes. Am. J. Physiol.-Heart Circ. Physiol. 2005, 289, H2144–H2152. [Google Scholar] [CrossRef]
  69. Zheng, L.; Du, Y.; Miller, C.; Gubitosi-Klug, R.A.; Kern, T.S.; Ball, S.; Berkowitz, B.A. Critical role of inducible nitric oxide synthase in degeneration of retinal capillaries in mice with streptozotocin-induced diabetes. Diabetologia 2007, 50, 1987–1996. [Google Scholar] [CrossRef] [PubMed]
  70. Tsai, T.; Kuehn, S.; Tsiampalis, N.; Vu, M.K.; Kakkassery, V.; Stute, G.; Dick, H.B.; Joachim, S.C. Anti-inflammatory cytokine and angiogenic factors levels in vitreous samples of diabetic retinopathy patients. PLoS ONE 2018, 13, e0194603. [Google Scholar] [CrossRef] [PubMed]
  71. Wakabayashi, Y.; Usui, Y.; Okunuki, Y.; Takeuchi, M.; Kezuka, T.; Iwasaki, T.; Goto, H. Increased levels of monokine induced by interferon-γ (Mig) in the vitreous of patients with diabetic retinopathy. Diabet. Med. 2008, 25, 875–877. [Google Scholar] [CrossRef]
  72. Vujosevic, S.; Micera, A.; Bini, S.; Berton, M.; Esposito, G.; Midena, E. Proteome analysis of retinal glia cells-related inflammatory cytokines in the aqueous humour of diabetic patients. Acta Ophthalmol. 2016, 94, 56–64. [Google Scholar] [CrossRef] [PubMed]
  73. Zhu, H.; Li, B.; Huang, T.; Wang, B.; Li, S.; Yu, K.; Cai, L.; Ye, Y.; Chen, S.; Zhu, H.; et al. Update in the molecular mechanism and biomarkers of diabetic retinopathy. Biochim. Biophys. Acta (BBA)-Mol. Basis Dis. 2025, 1871, 167758. [Google Scholar] [CrossRef]
  74. Caldwell, R.B.; Bartoli, M.; Behzadian, M.A.; El-Remessy, A.E.B.; Al-Shabrawey, M.; Platt, D.H.; Liou, G.I.; Caldwell, R.W. Vascular endothelial growth factor and diabetic retinopathy: Role of oxidative stress. Curr. Drug Targets 2005, 6, 511–524. [Google Scholar] [CrossRef] [PubMed]
  75. Ferrara, N. Vascular endothelial growth factor: Basic science and clinical progress. Endocr. Rev. 2004, 25, 581–611. [Google Scholar] [CrossRef] [PubMed]
  76. Arrigo, A.; Aragona, E.; Bandello, F. VEGF-targeting drugs for the treatment of retinal neovascularization in diabetic retinopathy. Ann. Med. 2022, 54, 1089–1111. [Google Scholar] [CrossRef]
  77. Wu, F.; Phone, A.; Lamy, R.; Ma, D.; Laotaweerungsawat, S.; Chen, Y.; Zhao, T.; Ma, W.; Zhang, F.; Psaras, C.; et al. Correlation of aqueous, vitreous, and plasma cytokine levels in patients with proliferative diabetic retinopathy. Investig. Ophthalmol. Vis. Sci. 2020, 61, 26. [Google Scholar] [CrossRef] [PubMed]
  78. Praidou, A.; Papakonstantinou, E.; Androudi, S.; Georgiadis, N.; Karakiulakis, G.; Dimitrakos, S. Vitreous and serum levels of vascular endothelial growth factor and platelet-derived growth factor and their correlation in patients with non-proliferative diabetic retinopathy and clinically significant macula oedema. Acta Ophthalmol. 2011, 89, 248–254. [Google Scholar] [CrossRef]
  79. Boulton, M.; Gregor, Z.; McLeod, D.; Charteris, D.; Jarvis-Evans, J.; Moriarty, P.; Khaliq, A.; Foreman, D.; Allamby, D.; Bardsley, B. Intravitreal growth factors in proliferative diabetic retinopathy: Correlation with neovascular activity and glycaemic management. Br. J. Ophthalmol. 1997, 81, 228–233. [Google Scholar] [CrossRef][Green Version]
  80. Aiello, L.P.; Clermont, A.; Arora, V.; Davis, M.D.; Sheetz, M.J.; Bursell, S.E. Inhibition of PKC β by oral administration of ruboxistaurin is well tolerated and ameliorates diabetes-induced retinal hemodynamic abnormalities in patients. Investig. Ophthalmol. Vis. Sci. 2006, 47, 86–92. [Google Scholar] [CrossRef]
  81. Gray, C.M.; Remouchamps, C.; McCorkell, K.A.; Solt, L.A.; Dejardin, E.; Orange, J.S.; May, M.J. Noncanonical NF-κB signaling is limited by classical NF-κB activity. Sci. Signal 2014, 7, ra13. [Google Scholar] [CrossRef][Green Version]
  82. Gupta, S.C.; Kim, J.H.; Prasad, S.; Aggarwal, B.B. Regulation of survival, proliferation, invasion, angiogenesis, and metastasis of tumor cells through modulation of inflammatory pathways by nutraceuticals. Cancer Metastasis Rev. 2010, 29, 405–434. [Google Scholar] [CrossRef]
  83. Ahn, K.S.; Aggarwal, B.B. Transcription factor NF-κB: A sensor for smoke and stress signals. Ann. N. Y. Acad. Sci. 2005, 1056, 218–233. [Google Scholar] [CrossRef]
  84. Mishra, M.; Zhong, Q.; Kowluru, R.A. Epigenetic modifications of Nrf2-mediated glutamate–cysteine ligase: Implications for the development of diabetic retinopathy and the metabolic memory phenomenon associated with its continued progression. Free Radic. Biol. Med. 2014, 75, 129–139. [Google Scholar] [CrossRef]
  85. Zhong, Q.; Kowluru, R.A. Epigenetic modification of Sod2 in the development of diabetic retinopathy and in the metabolic memory: Role of histone methylation. Investig. Ophthalmol. Vis. Sci. 2013, 54, 244–250. [Google Scholar] [CrossRef]
  86. Xu, Z.; Wei, Y.; Gong, J.; Cho, H.; Park, J.K.; Sung, E.R.; Huang, H.; Wu, L.; Eberhart, C.; Handa, J.T.; et al. NRF2 plays a protective role in diabetic retinopathy in mice. Diabetologia 2014, 57, 204–213. [Google Scholar] [CrossRef] [PubMed]
  87. Zhang, J.J.; Ni, P.; Song, Y.; Gao, M.J.; Guo, X.Y.; Zhao, B.Q. Effective protective mechanisms of HO-1 in diabetic complications: A narrative review. Cell Death Discov. 2024, 10, 433. [Google Scholar] [CrossRef] [PubMed]
  88. Mao, C.; Yan, H. Roles of elevated intravitreal IL-1β and IL-10 levels in proliferative diabetic retinopathy. Indian J. Ophthalmol. 2014, 62, 699–701. [Google Scholar] [CrossRef]
  89. Hernandez, C.; Segura, R.M.; Fonollosa, A.; Carrasco, E.; Francisco, G.; Simo, R. Interleukin-8, monocyte chemoattractant protein-1 and IL-10 in the vitreous fluid of patients with proliferative diabetic retinopathy. Diabet. Med. 2005, 22, 719–722. [Google Scholar] [CrossRef] [PubMed]
  90. Guerra-Ávila, P.L.; Guzmán, T.J.; Vargas-Guerrero, B.; Domínguez-Rosales, J.A.; Cervantes-Garduño, A.B.; Salazar-Montes, A.M.; Sánchez-Orozco, L.V.; Gurrola-Díaz, C.M. Comparative screening of the liver gene expression profiles from type 1 and type 2 diabetes rat models. Int. J. Mol. Sci. 2024, 25, 4151. [Google Scholar] [CrossRef]
  91. Luna, L.G. Manual of histologic staining methods of the Armed Forces Institute of Pathology. In Manual of Histologic Staining Methods of the Armed Forces Institute of Pathology; McGraw-Hill: New York, NY, USA, 1968; pp. 12–258. [Google Scholar]
  92. Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B.; et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 2012, 9, 676–682. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Barba-Gallardo, L.F.; Ávila-Blanco, M.E.; Ventura-Juárez, J.; Muñoz-Ortega, M.H.; Murillo-Ruíz, R.C.; Rivera-Delgadillo, M.; Díaz-Rubio, J.L.; Casillas-Casillas, E.; Salas-Hernández, L.H.; Guerra-Ávila, P.L. Experimental Diabetic Retinopathy in Wistar Rats Induced by Streptozotocin: A Window into Retinal Disease Progression. Int. J. Mol. Sci. 2026, 27, 3427. https://doi.org/10.3390/ijms27083427

AMA Style

Barba-Gallardo LF, Ávila-Blanco ME, Ventura-Juárez J, Muñoz-Ortega MH, Murillo-Ruíz RC, Rivera-Delgadillo M, Díaz-Rubio JL, Casillas-Casillas E, Salas-Hernández LH, Guerra-Ávila PL. Experimental Diabetic Retinopathy in Wistar Rats Induced by Streptozotocin: A Window into Retinal Disease Progression. International Journal of Molecular Sciences. 2026; 27(8):3427. https://doi.org/10.3390/ijms27083427

Chicago/Turabian Style

Barba-Gallardo, Luis Fernando, Manuel Enrique Ávila-Blanco, Javier Ventura-Juárez, Martín Humberto Muñoz-Ortega, Ruth Clarisa Murillo-Ruíz, Marcela Rivera-Delgadillo, José Luis Díaz-Rubio, Elizabeth Casillas-Casillas, Luis Héctor Salas-Hernández, and Paloma Lucía Guerra-Ávila. 2026. "Experimental Diabetic Retinopathy in Wistar Rats Induced by Streptozotocin: A Window into Retinal Disease Progression" International Journal of Molecular Sciences 27, no. 8: 3427. https://doi.org/10.3390/ijms27083427

APA Style

Barba-Gallardo, L. F., Ávila-Blanco, M. E., Ventura-Juárez, J., Muñoz-Ortega, M. H., Murillo-Ruíz, R. C., Rivera-Delgadillo, M., Díaz-Rubio, J. L., Casillas-Casillas, E., Salas-Hernández, L. H., & Guerra-Ávila, P. L. (2026). Experimental Diabetic Retinopathy in Wistar Rats Induced by Streptozotocin: A Window into Retinal Disease Progression. International Journal of Molecular Sciences, 27(8), 3427. https://doi.org/10.3390/ijms27083427

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop