We employed male Wistar rats (Rattus novergicus domestica) aged 6 weeks with an average weight of 250 gr across all experimental protocols. The animals were housed under standardized conditions, maintaining a 12-h light–dark cycle (12:12), and ad libitum access to water and standard rodent chow throughout the procedures. All experimental manipulations adhered rigorously to the animal handling guidelines outlined by the Association for Research in Vision and Ophthalmology (ARVO). Prior to implementation, each procedure was subjected to meticulous review and approval by the Institute of Neurobiology’s Research Ethics Committee at the National Autonomous University of Mexico, ensuring compliance with ethical standards and regulatory requirements (protocol 122A). Experimental interventions were exclusively directed on the left eye of each subject, while maintaining the right eye as an internal control.

Three experimental groups were formed in which animals with ONC, or sham surgery were performed on the left eye. They were anesthetized intraperitoneally using ketamine (80 mg/kg) and xylazine (8 mg/kg). To induce the ONC, an incision was made in the lower conjunctiva of the left eye, allowing access to the optic nerve. The extraocular muscles were separated, and the optic nerve was exposed using fine scissors. The optic nerve was crushed 2 mm behind the optic disc for 10 s, using self-closing forceps (Dumont Tweezers #7; Dumoxel) (Allen et al., 2021), taking care to preserve the ophthalmic artery. In the sham group, the same procedure was replicated, excluding manipulations of the optic nerve. After surgery, animals received subcutaneous injections of bovine recombinant growth hormone (bGH) (Boostin-S, Intervet) every 12 h at dose of 0.5 mg/kg (Figure 1; Aberg et al., 2009). Tissue samples were collected either 24 h or 14 days after ONC, with at least two independent experiments conducted at each time point. Retinas were collected, frozen at −80°C, and later processed for qPCR or protein analysis by Western blot or ELISA. For histological assessments, both eyes and optic nerves were promptly fixed as described below and preserved for further analysis.

At the predetermined time points (24 h or 14 days post-ONC), retinas were individually collected, frozen on dry ice, and stored at −80°C for later processing. Total RNA extraction was performed using the Zymo Direct-zol purification kit in combination with TRIzol reagent (Zymo Research Corp., Irvine, CA, United States), strictly following the manufacturer’s guidelines. RNA was analyzed using a NanoDrop Lite Plus spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States), where it was quantified and its purity assessed (A260/A280). Only samples with a purity ratio within the range of 1.9 and 2.1 were used for downstream applications. For complementary DNA (cDNA) synthesis, 1 μg of RNA was reverse-transcribed using the high-capacity cDNA reverse transcription kit (Applied Biosystems, Waltham, MA, United States) strictly following the manufacturer’s instructions. The resulting cDNA was stored at −20°C until further use. Gene expression of selected targets (detailed in Tables 1, 2) was assessed through qPCR using the QuantStudio system (Applied Biosystems) and SYBR green (Maxima; Thermo Fisher Scientific, Waltham, MA, United States) in a reaction volume of 10 μL. No-template controls were also included to detect contamination and avoid false positives, and each sample was analyzed in technical replicate. The cycling conditions included: 95°C for 5 min, and then 40 cycles of 95°C for 15 s, 60°C for 15 s, and 72°C for 15 s. A dissociation curve was run at the end of each qPCR experiment to confirm primer specificity. Validation curves were generated for all oligonucleotides by constructing standard curves based on serial dilutions. The standard curve was plotted with the logarithm (base 10) of cDNA dilution factor on the x-axis and Ct values on the y-axis. Linear regression was used to derive the equation of the curve (y = mx + b), from which the slope (m) was obtained. The efficiency values (E) were obtained using the formula: E = ((10^−(1/slope))−1)*100. Amplification efficiencies were ranged between 95 and 115%. All primers were designed using Primer-BLAST (NCBI) to span an exon–exon junctions to prevent amplification of genomic DNA. Primer specificity was confirmed by melt curve analysis and agarose gel electrophoresis, which showed a single amplicon of the expected size without primer-dimers. Relative mRNA levels were quantified using the 2^(^−ΔΔCT) method and normalized against ribosomal protein S18 (RPS18) mRNA as reference gene (Livak and Schmittgen, 2001), which was selected as the most stable housekeeping gene in this model based on NormFinder analysis, with a stability value of 0.015.

Retinas were microdissected from enucleated eyes. Protein extraction from retinal tissue was performed by homogenization using a GE 130 PB sonicator (Cole-Parmer, Vernon Hills, IL, United States) at an amplitude setting of 10 for 30 s in RIPA buffer (Abcam, Cambridge, United Kingdom), supplemented with a complete protease inhibitor cocktail (Roche, Basel, Switzerland).Eighty microgram of the extracted total protein from samples were placed in each ELISA plate well. The concentration of proinflammatory cytokines IL1β, IL6 and TNFα were analyzed using specific commercial enzyme-linked immunosorbent assay (ELISA) kits (IL1β, Ref: BMS630, Lot: 337105–009; IL6, Ref: ERA31RB, Lot: 724090623; TNFα, Ref: ERA56RB Lot: 709090623, Invitrogen, Waltham, MA, United States), following the manufacturer’s instructions, and absorbance was measured at 405 nm using an ELISA plate reader (Bio-Rad, Hercules, CA, United States). Cytokines levels were quantified in picograms per milliliter (pg/mL) and were expressed as the relative change compared to the sham group.

Total protein extraction from SIM-A9 cell was performed through homogenization using a GE 130 PB sonicator (Cole-Parmer, Vernon Hills, IL, United States) at amplitude of 10 for 30 s in RIPA buffer (Abcam, Cambridge, United Kingdom), with the addition of a complete protease inhibitor cocktail (Roche, Basel, Switzerland). Proteins (40 μg per sample) were separated using 12% SDS-PAGE gels under reducing conditions, followed by transfer onto nitrocellulose membranes (Bio-Rad). To block non-specific binding, membranes were incubated with 5% non-fat milk (Bio-Rad) in TBS for 1 h at room temperature (RT, RT = 21°C). The membranes were then incubated overnight at RT with NF-kB antibody (Table 3) in TTBS (TBS with 0.05% Tween) containing 1% non-fat milk. After three washes in TTBS (3 × 5 min), the membranes were incubated for 2 h with HRP-conjugated secondary antibody (Table 3). Visualization of protein bands was achieved using the ECL blotting detection reagent (Amersham-Pharmacia, Buckinghamshire, United Kingdom), followed by exposure to autoradiography films (Fujifilm, Tokyo, Japan). Kaleidoscope molecular weight markers (Bio-Rad) were used to determine the approximate molecular weights of the proteins. Images were captured using a Gel Doc EZ Imager (Bio-Rad), and the immunoreactive band intensities were analyzed with Image Lab software (Bio-Rad). All target protein levels of immunoreactivity were normalized against β-actin as a loading control.

The eyes were fixed in a 4% paraformaldehyde solution containing 3% sucrose diluted in PBS at 4°C, for 6 h. To optimize fixation, approximately 30 μL of this solution was injected into the eyes through the cornea using a 31-gauge insulin syringe. After fixation, the tissues underwent cryoprotection in PBS with progressively increasing sucrose concentrations of 10, 20, and 30% with 12 h of incubation in each solution. Subsequently, the tissues were frozen and mounted onto aluminum sectioning blocks using Tissue-Tek O. C. T (Sakura Finetek, Torrance, CA, United States). Retinal sections of 15 μm thickness were prepared using a cryostat (Leica CM3050 S, Buffalo Grove, IL, United States) and placed on glass slides. The eyes were sectioned along the naso-temporal axis at the equator. For immunohistochemical (IHC) analysis, the sections were first blocked with 5% Blotting-Grade Blocker non-fat dry milk (Bio-Rad) in PBS. They were then incubated overnight at 4°C with primary antibodies (as specified in Table 3), diluted in PBS containing 0.05% Triton X-100 and 1% non-fat dry milk. Following primary antibody incubations, sections were incubated for 2 h at RT with secondary fluorescent antibodies (Table 3) at a dilution of 1:1000 in the same solution, along with DAPI (100 ng/mL) (Sigma-Aldrich, St. Louis, MO, United States) to counterstain cell nuclei. Negative controls, in which the primary antibodies were omitted, were included for validation purposes. Image capture was performed using an Olympus BX51 fluorescence microscope (Olympus, Tokyo, Japan), and subsequent data analysis was completed using Image Pro 10 software (Media Cybernetics, Rockville, MD, United States).

The steps for morphological analysis in this study were based on previous research that employed similar techniques to indicate microglial morphological changes (Young and Morrison, 2018; Green et al., 2022). Specifically, Iba1 staining was analyzed using the skeletal analysis and FracLac plugins in ImageJ (free ImageJ Fiji software, NIH, Bethesda, MD).

The Iba1-stained images were converted to black-and-white images, where 100 individual microglial cells were isolated for subsequent analysis. Each image underwent brightness and contrast adjustment to optimize the visualization of microglial branches. The threshold was then adjusted, and the image was converted to binary format, applying the close and remove outliers’ functions to refine the analysis. For single-cell skeletal analysis, the binary images were skeletonized and analyzed using the skeletal analysis plugin in ImageJ. This tool was employed to calculate the number of branches, junctions and end points in each microglia. For fractal analysis, the binary images of the microglial cells were converted to outlines. The FracLac plugin was used to perform box counting analysis with the grid design parameter “Num G” set to four. Several parameters were measured, including the fractal dimension (measure of the complexity of the pattern), lacunarity (measure of how the pattern fills space), density (number of pixels per area), span ratio (the longest length divided by the longest width), circularity (indicator of how circular the cell is), as well as the area and perimeter of each microglial cell.

Fundus imaging was conducted 1 day after the completion of GH treatment. Pupils were dilated using a solution of tropicamide/phenylephrine (8 mg/50 mg/mL), and the corneas were kept hydrated with 5% dexpanthenol. Rats were anesthetized via intraperitoneal injection of ketamine (80 mg/kg) and xylazine (8 mg/kg). Brightfield images of the fundus were captured using a Micron IV fundus camera (Phoenix Research Laboratories, Bend, OR, United States). Following image acquisition, optic nerve diameters were measured using ImageJ software, and the relative diameter was calculated in comparison to the sham group.

The optomotor reflex test was conducted 2 weeks after the completion of GH treatment. This interval was necessary because the animals did not reliably perform the task immediately after treatment, likely due to the handling associated with the experimental procedures. The visual function of conscious, unrestrained rodents was evaluated using a virtual optomotor task, specifically assessing the optomotor kinetic tracking (OKT) response to a visual stimulus. This was performed using the OptoMotry system (Cerebral Mechanics, Inc., Lethbridge, AB, Canada) (Redfern et al., 2011; Bretz et al., 2020).

For the test, rats were placed on an elevated platform inside the chamber. A video camera positioned above the animal provided real-time images, which were monitored by a trained observer on a desktop computer screen. The OptoMotry system projected a virtual rotating cylinder displaying a pattern of white and black lines. The rats were allowed to move freely on the platform. When a grating pattern, perceptible by the rat, was projected, the test commenced. A trained observer assessed whether the rat tracked the pattern by moving its head in the direction of the visual stimuli. The grating frequency (cycles per degree; c/d) was adjusted based on the observer input, if the rat was observed to track the pattern, the frequency was increased, and if not, it was decreased. The software automatically determined the endpoint of the test when changes between successive readings became minimal. The contrast of the stimuli was set at 100%, and the rotation speed at 12 degrees/s. If a rat slipped or jumped off the platform during the test, it was gently returned to the platform and the test resumed. The rats were generally tested during the early hours of their daylight cycle. The primary observer was masked to the treatment conditions, and a second trained observer independently confirmed the tracking assessments to ensure consistency. The optomotor response in rodents is known to be asymmetric. Therefore, the visual capabilities of each eye were assessed separately by rotating the stimulus in different directions: clockwise rotation tested the left eye (with ONC), while counterclockwise rotation tested the right eye (control) (Thomas et al., 2004).

The SIM-A9 microglial cell line (ATCC^® CRL-3265™, Manassas, VA, United States) was derived from a primary glial culture obtained from postnatal murine cerebral cortices. These cells underwent spontaneous immortalization, enabling continuous proliferation without requiring genetic or pharmacological interventions (Nagamoto-Combs et al., 2014; Dave et al., 2020). SIM-A9 cultures were maintained in Petri dishes using Dulbecco’s modified Eagle medium (DMEM) (Gibco, Life Technologies, Carlsbad, CA, United States) supplemented with 10% fetal bovine serum (FBS; Gibco, Thermo Fisher Scientific, United States) and antibiotics 10,000 units/mL of penicillin and streptomycin, and 25 μg/mL antifungal Fungizone (Gibco, Life Technologies). Cells were incubated at 37°C in a humidified 5% CO₂ atmosphere. Before initiating experiments, an equal number of cells were seeded in multi-well plates, incubated overnight, and subjected to serum deprivation for 2 h prior to treatment.

For experimental treatments, SIM-A9 cells were seeded at a density of 3 x 10 5 cells/well in 6-well culture plates. Cells were either untreated (control; ctrl) or treated with lipopolysaccharide (LPS; 10 ng/mL; from Salmonella enterica serotype Minnesota from Sigma-Aldrich) alone or in combination with GH (LPS + GH; 10 ng/mL and 100 nM, respectively; bGH, NHPP AF10325C, Harbor-UCLA Medical Center, Torrance, CA, United States). Treatments were performed for 30 min for WB analysis and 6 h for qPCR.

Gene expression (qPCR), protein levels (ELISA and Western blot), optic cup diameter, optomotor tests, and microglial morphology were analyzed across two independent experiments. These assessments involved 6–10 animals for qPCR, 6–8 animals for protein levels, 8–11 animals for optic cup measurements, 5–6 animals for optomotor tests, and 100 microglial cells from 6 animals for morphological analysis. All data are presented as mean ± SEM. Normality of data distribution was assessed using the Shapiro–Wilk test, and homogeneity of variances was evaluated with the Brown-Forsythe test. Outliers were identified using the ROUT method with Q = 1%. For data that did not meet the assumption of equal variances, Welch’s ANOVA was applied. For data where equal variances were observed, one-way ANOVA followed by Fisher’s LSD post-hoc test was used to determine statistical significance between groups or treatments. All statistical analyses were performed using Prism 10 software (GraphPad, San Diego, CA, United States). Differences were considered statistically significant when p-values were less than 0.05. Statistical significance is indicated as follows: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

The antiinflammatory effects of GH administration were evaluated by the expression levels of cytokines in the retina at 24 h and 14 days post-ONC. At 24 h (Figure 2A), ONC significantly increased Il6 and Tnf expression (p < 0.01) compared to the sham group (dashed line). However, GH treatment significantly reduced Il6 and Tnf expression (p < 0.05) compared to the ONC group. Both, ONC and ONC + GH groups significantly increased Il1b expression (p < 0.05). Similarly, Il18 and Nos2 expression were significantly upregulated (p < 0.05) by ONC compared to the sham group, and GH treatment significantly reduced (p < 0.05) the expression of these proinflammatory cytokines. The ONC group showed no significant effects on Nos3 or Vegfa expression at this time point. Although no significant changes were observed in Ptgs2 expression compared to the sham group, GH treatment resulted in a significant decrease (p < 0.05) compared to the ONC group. The expression of TNFα receptors was analyzed and Tnfrsf1a (proinflammatory) showed a significant increase (p < 0.05) in the ONC group compared to sham group, while Tnfrsf1b (pro-survival) did not show significant differences with the sham group but significantly decreased (p < 0.05) in the ONC + GH group compared to the ONC group. Neither treatment showed significant differences in Tgfb1 expression at his time point.

Similarly, the expression of these cytokines was analyzed 14 days after ONC injury (Figure 2B). ONC injury significantly increased (p < 0.05) Il6 expression compared to the sham group, while GH treatment reduced that effect and did not show any significant changes compared to sham group. Tnf levels in the ONC group were not different from sham, but GH treatment showed a significant decrease (p < 0.05) compared to the sham group. Il1b expression did not show significant changes in either the ONC or ONC + GH groups as compared to the control. In turn, Il18 expression was significantly increased (p < 0.001) in the ONC group compared to sham, whereas GH treatment significantly reduced (p < 0.001) its expression compared to the ONC group. In contrast, Nos2 expression was significantly decreased in the ONC group (p < 0.05) in comparison to sham, and GH treatment caused a further decrease (p < 0.01) compared to sham and was also different than ONC (p < 0.05), while Nos3 expression showed no significant changes in either group. GH treatment significantly decreased Vegfa levels compared to both the ONC and sham groups, whereas the ONC group was no different than sham. Ptgs2 and TNFα receptors (Tnfrsf1a and Tnfrsf1b) did not show significant changes between groups. Lastly, Tgfb1 expression showed a significant increase (p < 0.05) in the GH-treated group compared to the ONC group.

The damage caused by ONC in the retina affected cytokine expression, indicating an association with glial cell activity. Thus, microglial markers like Iba1 (Aif1), CD86 (Cd86; M1 phenotype), and CD206 (Mrc1; M2 phenotype) were analyzed at 24 h and 14 days post-ONC (Figure 3) by qPCR. At 24 h, ONC significantly increased Aif1 and Cd86 expression (p < 0.05), as well as Mrc1 (p < 0.01) as compared to the sham group, whereas GH treatment did not show any significant differences compared to the control group.

On the other hand, after 14 days, no significant changes were observed in Aif1 expression in any of the groups compared to control. However, both ONC and ONC + GH groups showed a significant increase (p < 0.05) in Cd86 expression compared to sham. In contrast, Mrc1 levels showed a significant decrease (p < 0.05) in both groups as compared to the control.

Proinflammatory cytokine levels (IL6, TNFα and IL1β) in the retinas were measured 24 h post-ONC using ELISA (Figures 4A–C). No significant differences in IL6 levels were observed between the experimental groups (Figure 4A), although data showed a tendency to increase with ONC and to decrease with GH treatment. Conversely, TNFα levels were significantly elevated (p < 0.01) in the ONC group compared to the sham group, whereas GH treatment after ONC resulted in a significant decrease (p < 0.05) compared to the ONC group (Figure 4B). In turn, IL1β levels showed no significant differences among groups (Figure 4C).

To evaluate the effects induced by the treatments on microglia, IHC analyses were performed 24 h post-ONC (Figure 5) using a specific antibody against Iba1. Results revealed that, in the sham group, a clear Iba1-immunoreactivity (IR) was observed in the IPL, although some Iba1-IR was also present in the outer plexiform layer (OPL). However, following ONC, an important reduction in Iba1-IR was noticed in the OPL. Morphological changes were quantified using Iba1 IHC analysis (Figures 5A,B,F,G,K,L), where individual microglial cells were isolated from the photomicrographs (Figures 5C,H,M). These cell pictures were then converted into binary images (Figures 5D,I,N), allowing for skeleton and fractal analyses. Representative skeleton test images (Figures 5E,J,O) display branches in red, junctions in blue and endpoints in green. Then, quantification of the morphological changes was performed, and the number of branches, junctions and end points were assessed using a skeleton analysis (Figure 5P). This analysis showed a significant reduction in the number of branches in the ONC group (p < 0.001) in comparison to the control. Similarly, the ONC + GH group exhibited a significant decrease (p < 0.01) against the sham group, although GH treatment significantly increased (p < 0.05) the number of branches compared to the ONC group. In regard to junctions, both the ONC (p < 0.001) and ONC + GH (0.01) groups showed significant reductions as compared to sham but also showed a significant difference between themselves (p < 0.05). In turn, end points analysis also revealed significant reductions in both the ONC and ONC + GH groups (p < 0.001) in comparison to the sham control (Figure 5P).

Figure 5Q shows that cell body area was significantly reduced (p < 0.001) in both the ONC and ONC + GH groups compared to the sham group. This finding was consistent with the significant decrease (p < 0.001) in cell body perimeter of both groups compared to the sham control (Figure 5R). Furthermore, fractal analysis (Figure 5S) demonstrated a significant reduction (p < 0.05) in the complexity of the branching pattern (fractal dimension, Db) in the ONC group compared to the sham. Additionally, lacunarity was significantly decreased in both the ONC and ONC + GH groups (p < 0.001) compared to the sham. Both ONC and ONC + GH groups also exhibited a significant increase in density (p < 0.001) compared to the control. Span ratio analysis showed significant increases in the ONC (p < 0.05) and ONC + GH (p < 0.01) groups, respectively. However, no significant differences were observed between groups in microglia circularity.

Morphological analyses were also performed 14 days after ONC (Figure 6) using a similar approach. Iba1 IHC was used to visualize microglial morphology (Figures 6A,B,F,G,K,L). At this time point, Iba1-IR was observed in IPL and OPL in the sham retinas. Again, following ONC, a clear reduction in Iba1-IR was noted in the OPL; however, GH treatment induced an increased immunoreactivity in the OPL. To analyze the morphological changes that occurred with the treatments, individual microglial cells were isolated from the photomicrographs (Figures 6C,H,M) and converted into binary images (Figures 6D,I,N), as described earlier. Figures 5E,J,O show representative skeleton test images, where branches are displayed in red, junctions in blue and endpoints in green. Skeleton analysis (Figure 6P) exhibited a significant reduction in the number of branches in both ONC (p < 0.001) and ONC + GH (p < 0.05) groups compared to the sham group. Similarly, the number of junctions was significantly decreased in ONC (p < 0.001) and ONC + GH (p < 0.01) compared to the sham. End points were also significantly reduced in both the ONC (p < 0.001) and ONC + GH (p < 0.01) group compared to the sham control.

At this time point, cell body area (Figure 6Q) and cell body perimeter (Figure 6R) were significantly reduced in the ONC (p < 0.001) and ONC + GH (p < 0.001) groups, although GH treatment significantly increased the cell body area compared to the ONC group (p < 0.05). Fractal analysis (Figure 6S) demonstrated that ONC significantly reduced (p < 0.01) the complexity of the branching pattern (fractal dimension, Db) compared to the sham group, with a similar, though less pronounced, reduction observed in the ONC + GH group (p < 0.05). Lacunarity was significantly decreased (p < 0.01) by ONC compared to sham, and GH treatment further decreased this parameter compared to both sham (p < 0.001) and ONC (p < 0.05). Density was significantly reduced in the ONC + GH group (p < 0.001) compared to ONC group, while ONC alone caused a significant increase in density compared to both sham (p < 0.001) and ONC + GH (p < 0.01). Span ratio and circularity did not show significant changes 14 days post-ONC in any of the groups.

Representative fundus images from the Sham, ONC, and ONC + GH groups are shown in Figures 7A–C, respectively. The optic cup diameter was measured and compared between groups (Figure 7D). A significant increase (p < 0.01) in the optic cup diameter was observed in the ONC group compared to the sham group. However, GH treatment significantly reduced (p < 0.05) the optic cup diameter compared to the ONC group, with no significant difference observed between the ONC + GH group and the sham group.

As a measure to determine the effect of treatments on visual function, the optomotor kinetic tracking (OKT) response to a visual stimulus was analyzed using the OptoMotry system (Figure 8A). The ONC group exhibited a significant decrease of the spatial frequency threshold compared to the sham group (p < 0.001) (Figure 8B). In fact, the ONC lesioned rats did not respond to the visual stimuli, and their readings remained at baseline throughout the test. In contrast, the lesioned GH-treated group showed no significant differences from the sham group but exhibited a significant increase in the spatial frequency threshold compared to the ONC group (p < 0.01).

To complement our study, we aimed to analyze the anti-inflammatory effect of GH in response to an LPS challenge using a mouse microglia-derived SIM-A9 cell line. Figures 9A,B show that LPS-treatment significantly activated (p < 0.001) the NF-κB signaling pathway, as evidenced by increased p65 immunoreactivity determined by Western blot, in comparison to the sham group; whereas GH treatment significantly reduced (p < 0.01) p65 phosphorylation levels as compared to the LPS group, although was still different (p < 0.05) than the sham control. Additionally, cytokine expression analysis by PCR showed that LPS stimulation significantly upregulated Il1β (p < 0.001) (Figure 9C), Il6 (p < 0.001) (Figure 9D), Tnf (p < 0.001) (Figure 9E), and Tgfb1 (p < 0.05) (Figure 9F) mRNAs. GH treatment significantly reduced Il6 expression, lowering its significance from p < 0.0001 in the LPS group to p < 0.001 in the LPS + GH group in relation to sham group; the direct comparison between these groups showed no significant difference (p = 0.57). Regarding Tnf expression, a significant reduction was observed following GH treatment (p < 0.01) compared to the LPS group. Conversely, GH further increased the expression of the anti-inflammatory cytokine Tgfb1 (p < 0.05). It is important to note that GH treatment only slightly increased the difference between the LPS and LPS + GH groups; however, both groups remained significantly different from the sham group.