Sinensetin attenuates post-stroke depression via dual modulation of TLR4/NF-κB–NRF2/GPX4 pathways

Abstract

Post-stroke depression (PSD) is a complex neuropsychiatric complication driven by neuroinflammation and ferroptosis, yet effective therapies remain limited. Sinensetin (SIN), a polymethoxylated flavone derived from citrus fruits, possesses potent anti-inflammatory and antioxidant properties. However, its therapeutic efficacy and underlying mechanisms in PSD have not been explored. To investigate this, a mouse model of PSD was established by combining photothrombotic stroke with low-dose lipopolysaccharide (LPS) administration. Mice were treated with SIN (25 and 50 mg/kg) for 14 days. Depressive-like behaviors were assessed using the sucrose preference test (SPT), tail suspension test (TST), and forced swimming test (FST). Crucially, protein-level validation was performed using quantitative immunofluorescence (for glial activation) and ELISA (for serum cytokines and pathway markers), complemented by qPCR and molecular docking/dynamics (MD) simulations. SIN treatment significantly alleviated depressive-like behaviors and restored cerebral blood flow in PSD mice. Quantitative immunofluorescence and ELISA analyses revealed that SIN effectively suppressed the hyperactivation of microglia (IBA1) and astrocytes (GFAP) in the hippocampus and reduced serum concentrations of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β). Mechanistically, SIN inhibited the TLR4/NF-κB signaling pathway by suppressing NF-κB nuclear translocation and concurrently activated the NRF2/GPX4 antioxidant axis, thereby mitigating lipid peroxidation and neuronal ferroptosis. Additionally, molecular docking and MD simulations predicted energetically favorable interactions between SIN and key targets (e.g., TLR4, KEAP1), providing supportive evidence for its multi-target mechanism. Our findings demonstrate that SIN exerts neuroprotective effects in PSD by dually modulating TLR4/NF-κB-mediated neuroinflammation and NRF2/GPX4-dependent ferroptosis. These results highlight SIN as a promising natural therapeutic candidate for the treatment of depression following stroke.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-41351-3.

Introduction

Neuroinflammation is a shared pathological hallmark of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and stroke^1,2. Post-stroke depression (PSD), a debilitating neuropsychiatric complication affecting 30–40% of stroke survivors, is increasingly recognized for its association with neuroinflammation and oxidative stress^3,4. Following ischemic insult, microglia—the primary immune cells of the central nervous system—undergo rapid activation through pattern recognition receptors such as Toll-like receptor 4 (TLR4), initiating a cascade of pro-inflammatory cytokines via the nuclear factor kappa B (NF-κB) pathway^5,6. Previous studies have demonstrated elevated TLR4 expression and NF-κB activation in PSD animals⁷, correlating with increased levels of TNF-α, IL-1β, and IL-6 in the hippocampus and prefrontal cortex⁸. This neuroinflammatory milieu disrupts synaptic plasticity, exacerbates neuronal apoptosis, and contributes to depressive-like behaviors⁹.

The cerebral cortex, particularly the prefrontal and sensorimotor regions, plays a critical role in executive function, mood regulation, and motor control. The hippocampus is essential for memory consolidation and emotional processing. Both structures are vulnerable to ischemic injury during stroke, and damage to these areas is strongly implicated in the pathogenesis of PSD. Lesions in the prefrontal cortex disrupt fronto-limbic circuits that regulate mood and cognition¹⁰, while hippocampal injury impairs neurogenesis and synaptic plasticity, contributing to the development of depressive symptoms post-stroke¹¹.

Concurrently, Stroke-induced oxidative stress is a key trigger for ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation and glutathione peroxidase 4 (GPX4) inactivation^12,13. The nuclear factor erythroid 2-related factor 2 (NRF2)/GPX4 axis serves as a critical endogenous defense system, where NRF2 activation promotes GPX4 transcription to mitigate oxidative damage^14,15. Several studies confirm that PSD is associated with impaired NRF2 signaling and reduced GPX4 expression in the hippocampus, which diminishes antioxidant capacity and contributes to worsened neurological and depressive outcomes^16–18. This dual pathology of inflammation and ferroptosis creates a vicious cycle in PSD progression, as NF-κB activation further inhibits NRF2 by upregulating Kelch-like ECH-associated protein 1 (KEAP1)^19,20.

Natural compounds like polymethoxylated flavones (PMFs) with both anti-inflammatory²¹ and antioxidant properties²² have garnered increasing interest as potential therapeutic agents for PSD. Notably, Sinensetin (SIN), a PMF primarily isolated from Citrus reticulata and other citrus species, has emerged as a promising neuroprotective agent for PSD. Owing to its high lipophilicity, SIN readily crosses the blood-brain barrier and exerts multifaceted pharmacological effects, including anti-inflammatory²³, antioxidative²⁴, and neurotrophic actions²⁵.

Preclinical studies have shown that orally administered SIN at 12.5–50 mg/kg/day for 4 days significantly reduced LPS-induced inflammation in mice by inhibiting NF-κB activation and enhancing SIRT1–NRF2 signaling²³. Moreover, another study demonstrated that SIN at 50 mg/kg (i.p.) markedly alleviated carrageenan-induced paw inflammation in mice by suppressing iNOS and COX-2 expression²⁶. These findings provide a pharmacological basis for selecting 25 mg/kg and 50 mg/kg as the low and high doses in the current PSD mouse model.

Recent studies indicate that SIN exerts neuroprotective effects by simultaneously targeting neuroinflammation and oxidative stress pathways. Specifically, SIN reduces TLR4 expression, NF-κB nuclear translocation, and pro-inflammatory cytokines (e.g., IL-6, TNF-α) in SH-SY5Y cells exposed to amyloid-beta²⁷. Similarly, SIN suppresses TLR4, MyD88, phospho-NF-κB, along with multiple inflammatory mediators’ expression in lung inflammation models in vitro, supporting its broader role in NF-κB pathway inhibition and immunomodulation²⁴. Furthermore, SIN suppresses pyroptosis and reduces ROS levels in LPS-induced lung injury in vivo by targeting inflammasome activation pathways (e.g., NLRP3/Caspase-1/GSDMD)²⁵.

Given the pathological relevance of both the TLR4/NF-κB and KEAP1/NRF2/GPX4 pathways in PSD, SIN’s dual regulatory action may offer a promising therapeutic strategy to break the vicious cycle of neuroinflammation by inhibiting the TLR4/NF-κB pathway and ferroptotic neuronal death by activating the KEAP1/NRF2/GPX4 pathway in PSD model. Building upon the hypothesis above, the study aims to investigate whether SIN improves depressive-like behaviors in a mouse model of PSD and explore the underlying molecular mechanisms in the hippocampus, focusing on microglial activation, inflammatory cytokine expression, and ferroptosis-related signaling.

Materials and methods

Experimental animals

Male Balb/c mice (n = 50; age: 6–8 weeks; weight: 20 ± 2 g) were purchased from Beijing Vital River Laboratory Animal Technology (license: SCXK (Guangzhou) 2022-0063). All animal procedures were approved by the Jinan University Laboratory Animal Welfare and Ethics Committee (approval number: 20240313-0023). The study was conducted in strict accordance with the ARRIVE guidelines 2.0 (Animal Research: Reporting of In Vivo Experiments). A completed ARRIVE checklist is provided as Supplementary Material.

Mice were housed in a specific pathogen-free (SPF) facility at the Experimental Animal Center of Jinan University under controlled environmental conditions (temperature: 23 ± 2 ℃, humidity: 40–60%, 12 h light/dark cycle) with free access to food and water. Mice were randomly assigned to five experimental groups (n = 10/group): Blank, PSD model, Fluoxetine (10 mg/kg), SIN-low dose (25 mg/kg), and SIN-high dose (50 mg/kg). The doses of SIN were selected based on prior rodent pharmacological studies demonstrating anti-inflammatory efficacy within this range²³. All treatments were administered orally once daily for 14 days.

Behavioral assessments were performed after the 14-day SIN or fluoxetine treatment, including the Sucrose Preference Test (SPT) on day 15, Open Field Test (OFT) on day 16, Tail Suspension Test (TST) on day 17, and Forced Swimming Test (FST) on day 18. Testing was carried out between 9:00–12:00 a.m. by blinded investigators, and all experimental procedures were conducted following standardized protocols. Behavioral and histological analyses were also performed by experimenters blinded to group allocation. All animals demonstrated normal neurological function, and no evidence of infection or inflammation was observed throughout the study.

At the study’s conclusion, mice were humanely euthanized by intraperitoneal injection of euthasol (pentobarbital sodium, 100 mg/kg) in accordance with the American Veterinary Medical Association (AVMA) Guidelines for the Euthanasia of Animals (2020). All euthanasia procedures were performed in compliance with ethical standards to minimize animal suffering. Group housing and care were implemented according to standardized laboratory conditions to minimize stress and discomfort.

Major instruments and reagents

Major instruments used in this study included a digital stereotaxic apparatus (68016, RWD Life Science, Shenzhen, China), tail vein injection restrainer (GEGD-Q9G, Chuangbo Global Biotech, Beijing, China), isoflurane anesthesia system (R550IE, RWD Life Science), surgical heating pad (BR3050, Chuangbo Global Biotech), and a laser speckle contrast imaging system (PSI HR, Perimed, Sweden). Behavioral experiments were conducted using standard equipment for sucrose preference test (SPT; standard drinking bottles and electronic balance), open field test (OFT; black box 50 × 50 × 40 cm with tracking system, Xinruan Information Technology, China), tail suspension test (TST), and forced swimming test (FST) using video monitoring systems (Xinruan). Histological and molecular instruments included a fluorescence inverted microscope (DMi8, Leica, Germany), microtome (RM2235, Leica, Germany), ELISA reader (Multiskan FC, Thermo Fisher Scientific, USA), high-speed refrigerated microcentrifuge (D3024R, Cence/Scilogex), electric thermostatic oven (Shanghai YUEJIN, China), and a real-time PCR system (7300, Applied Biosystems, USA). Additional laboratory tools included an ultrasonic homogenizer (SCILOGEX), ultrasonic extractor (KQ-500DE, Kunshan Shumei), electronic balance (Shimadzu, Japan), vortex mixer (XHD, Lepu Instruments), and micropipettes (Eppendorf, Germany). Major reagents included SIN (purity: 98%, CAS Number: 2306-27-6, Shanghai Tauto Biotech Co., Ltd, Shanghai, China), Rose Bengal (15 mg/mL, Coolaber, Beijing, China), isoflurane (R510-22, RWD Life Science), LPS (L2880, Sigma-Aldrich, USA), normal saline and erythromycin ointment (Guangdong Hengjian Pharmaceutical Co., Ltd.), iodophor and 75% ethanol (Lierkang, Shandong), and Veet depilatory cream (France). Histological and immunofluorescence reagents included HE staining kit (C0105M, Beyotime), 4% paraformaldehyde and PBS buffer (BASMEDTSCI), blocking buffer (10% goat serum, Beyotime), primary antibodies against TLR4 (MA5-16288, Proteintech), NF-κB p65 (8242, CST), NRF2 (ab137550, Abcam), and GPX4 (67763-1-Ig, Proteintech), fluorescent secondary antibody (Goat Anti-Rabbit IgG (H + L), Fluor 488, S0018, Affinity), DAPI (C1002, Beyotime), and antifade mounting medium (P0126, Beyotime). qPCR reagents included TRIzol (15596026, Invitrogen), cDNA synthesis kit (RR047A, Takara), SYBR Green Mix (AG11701, Accurate Biology), DNase/RNase-free water (Thermo Fisher), and gene-specific primers (Sangon Biotech, Shanghai).

PSD model construction

A photochemical-induced thrombosis model was used to induce focal cerebral ischemia, combined with intraperitoneal LPS injection (2 mg/kg) to induce systemic inflammation and depression²⁸. Briefly, Rose Bengal (15 mg/mL, 10 µL/g) was injected via the tail vein. After induction of anesthesia with isoflurane, photothrombosis was targeted to the right anterior/sensorimotor cortex using a 560 nm cold light source for 20 min, with the illumination center positioned at AP + 1.5 mm and ML + 2.0 mm relative to bregma according to the Paxinos & Franklin mouse brain atlas. This cortical region was selected because frontal lesions have been strongly implicated in the pathogenesis of post-stroke depression and permit reliable behavioral evaluation without severe motor deficits^29,30. Following surgery, the incision was sutured, and erythromycin ointment was applied daily to prevent infection.

Neurological function assessment

Neurological deficits were evaluated 24 h after photothrombotic surgery using the modified Longa scoring system. Mice were observed for forelimb retraction, circling behavior, and spontaneous mobility. Scoring criteria were as follows: 0, no observable deficits; 1, mild forelimb flexion; 2, circling to the contralateral side; 3, severe circling and imbalance; and 4, no spontaneous motor activity with possible loss of consciousness. Only mice scoring ≥ 1 were included for subsequent experiments, ensuring successful induction of cerebral ischemia.

Laser Speckle Contrast Imaging (LSCI)

Cerebral blood flow (CBF) in the ischemic and contralateral regions was monitored using a high-resolution LSCI system (PSI HR, Perimed, Sweden). Mice were anesthetized with 5% isoflurane for induction and maintained under 2% isoflurane. Following scalp incision and skull exposure at the bregma area, the cortical surface was moistened with saline. The imaging setup was calibrated with a working distance of 13 cm, zoom level of 80–100×, frame rate of 21 fps, and region-of-interest (ROI) focused on the infarct site. Perfusion images were recorded continuously for 5 min, and stable 1-minute sequences were selected for analysis. Data were processed using PeriCam PSI software, and relative cerebral blood flow (rCBF) was calculated as the ischemic/non-ischemic ROI ratio.

Sucrose Preference Test (SPT)

To assess anhedonia, a core symptom of depression, the SPT was performed following a 48-hour adaptation. During this period, mice were given access to two identical bottles for 24 h containing 1% sucrose solution, followed by 24 h with one bottle replaced with water. Bottle positions were randomized to avoid place preference. On test day, water was withheld for 4 h prior to the 12-h test. Each mouse was housed individually with access to one bottle of water and one of 1% sucrose solution. Bottle weight was measured before and after testing, and sucrose preference was calculated as:

Sucrose Preference (%) = Sucrose Intake / (Sucrose Intake + Water Intake) × 100%, where “Sucrose Intake” and “Water Intake” represent the volume of sucrose solution and water consumed during the test period. Reduced sucrose preference indicates anhedonia.

Open Field Test (OFT)

The OFT was used to evaluate general locomotor activity and anxiety-like behavior. Mice were placed in the center of a black Plexiglas open field (50 × 50 × 40 cm) under ambient lighting conditions. After 1 h of acclimation, each mouse was tested for 6 min, with the first minute excluded from analysis. A video tracking system (Xinruan Information Technology, China) recorded total distance traveled, time spent in the center zone (central 9 of 25 squares), and number of center entries. Reduced central activity was interpreted as anxiety-related behavior. The apparatus was cleaned with 75% ethanol between tests.

Tail Suspension Test (TST)

The TST was used to assess behavioral despair. Mice were suspended by the tail with adhesive tape approximately 5 cm from the tail tip, attached to a horizontal bar 50 cm above the bench surface. Each mouse was tested for 6 min in a quiet environment. The first minute served as acclimation. Immobility duration, defined as the time during which the mouse remained completely motionless except for respiration, was recorded for the final 5 min via video. Increased immobility duration was interpreted as a depressive-like phenotype.

Forced Swimming Test (FST)

The FST was conducted in a cylindrical container (11 cm diameter, 30 cm height) filled with 25 ± 1℃ water to a depth of 20 cm. After 1 h of acclimation to the testing environment, mice were individually placed in the water and monitored for 6 min. The first minute served as habituation, and floating immobility was recorded during the final 5 min. Immobility time, defined as minimal movement necessary to keep the head above water, was used as an index of behavioral despair. After testing, mice were dried with paper towels and returned to a 37℃ incubator to prevent hypothermia.

Nissl staining

Brain tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned at 5 μm thickness. Sections were deparaffinized with xylene and rehydrated through a graded ethanol series (100%, 95%, 80%, 70%). After rinsing in distilled water, sections were stained with 0.1% cresyl violet solution at 37℃ for 10 min. Excess stain was removed by brief differentiation in 95% ethanol containing a few drops of glacial acetic acid. Sections were then dehydrated through graded ethanol solutions, cleared in xylene, and mounted with neutral resin. Neuronal morphology and Nissl body distribution were specifically analyzed in the ipsilateral frontal/sensorimotor cortex and the CA1 region of the hippocampus using a Leica DMi8 microscope.

Quantitative real-time PCR (qPCR)

Total RNA was extracted from ~ 50 mg brain tissue using TRIzol reagent (15596026, Invitrogen, USA), and concentration and purity were assessed by Nanodrop. RNA samples with A260/A280 ratios between 1.8 and 2.1 were reverse-transcribed using the PrimeScript RT Reagent Kit (RR047A, Takara, Japan). qPCR was conducted on an Applied Biosystems 7300 system with TB Green Premix Ex Taq II (AG11701, Accurate Biology, China). Reactions (10 µL) included 5 µL SYBR mix, 0.4 µL each primer, 0.2 µL ROX, 2 µL cDNA, and 2 µL RNase-free water. The cycling conditions were: 95℃ for 30 s, followed by 40 cycles of 95℃ for 5 s and 60℃ for 30 s. Relative mRNA expression was calculated using the 2^−ΔΔCt method with GAPDH as an internal control. Primer sequences for inflammatory and chemotactic genes are provided in Supplementary Table S1.

Immunofluorescence Staining (IF)

Frozen brain sections were incubated with 0.5% Triton X-100 for 20 min and blocked with 10% goat serum (Beyotime, China) for 30 min. Sections were then incubated with primary antibodies at 4℃ for 48 h: anti-TLR4 (MA5-16288, Proteintech), anti-NF-κB p65 (8242, CST), anti-NRF2 (ab137550, Abcam), and anti-GPX4 (67763-1-Ig, Proteintech). After PBS washing, sections were incubated with fluorescent-conjugated secondary antibodies (Fluor 488, S0018, Affinity) at room temperature for 2 h in the dark. Nuclei were counterstained with DAPI (C1002, Beyotime) for 10 min. Slides were sealed with antifade mounting medium (P0126, Beyotime) and imaged using a Leica DMi8 fluorescence microscope. Image processing and quantitative analysis were performed using ImageJ software (NIH, Bethesda, MD, USA). To evaluate the protein expression levels of TLR4, NF-κB, NRF2, and GPX4, as well as the activation of microglia (IBA1) and astrocytes (GFAP), the mean fluorescence intensity (MFI) of the positively stained areas was calculated in the hippocampus/cortex. Background signals were subtracted to ensure accuracy.

Enzyme-Linked Immunosorbent Assay (ELISA)

Blood samples were collected from the retro-orbital sinus and allowed to clot at room temperature for 30 min. Serum was separated by centrifugation at 3,000 rpm for 15 min at 4℃. The levels of TNF-α, IL-1β, IL-6, CCL2, IBA1, GFAP, NF-κB, NRF2, GPX4, and TLR4 in the serum were measured using specific ELISA kits (Yeasen Biotechnology (Shanghai) Co., Ltd.) strictly according to the manufacturer’s instructions. The optical density (OD) values were measured at 450 nm using a microplate reader.

Molecular docking analysis

Molecular docking was performed using AutoDock Vina (version 1.1.2) to evaluate the binding affinity between Sinensetin (SIN) and four key target proteins involved in neuroinflammation and oxidative stress: NF-κB, NRF2, GPX4, and TLR4. The 3D structure of SIN was obtained from the PubChem database (CID: 5281647), energy-minimized using the MMFF94 force field, and converted to PDBQT format via Open Babel. Protein crystal structures were retrieved from the RCSB Protein Data Bank (PDB IDs: pdb 00001u36, pdb 00002z64, pdb 00005171, pdb 00001 × 2r), with water molecules and ligands removed. Polar hydrogens and Gasteiger charges were added using AutoDockTools (version 1.5.6). Docking grids were defined to cover the active binding pockets of each target protein, and docking calculations were performed with default Vina settings. The conformation with the lowest binding energy (vina score) was selected for each target. Docked complexes were visualized using PyMOL (version 2.5.4) and Discovery Studio Visualizer to analyze hydrogen bonding, hydrophobic interactions, and π-π stacking. Binding affinities were interpreted based on vina scores, with lower values indicating stronger predicted interactions.

It should be noted that the PDB structures used in this study do not represent full-length proteins in all cases. The selected crystal structures were chosen based on the availability of experimentally resolved domains that encompass key functional or ligand-binding regions, as well as their high structural resolution and suitability for docking analysis. For intrinsically disordered or partially resolved proteins, docking was performed on structurally defined domains to explore the feasibility of potential interactions rather than to claim definitive biological binding.

Molecular Dynamics (MD) simulation

MD simulations were performed using Amber 24 (San Francisco, CA, USA)³¹ with the ff19SB force field³² to calculate system force field parameters. The system was solvated with the TIP3P water model, and counterions were added to neutralize the system. After energy minimization, the system was heated from 0 K to 310.15 K (37℃) over 500 ps. Equilibration was performed in the NVT ensemble, followed by a pre-equilibration at 310.15 K (37℃). Finally, a 100 ns production run was conducted in the NPT ensemble under periodic boundary conditions. All covalent bonds involving hydrogen were constrained using the SHAKE method. The dynamic results were analyzed using AmberTools³³. This simulation involved only a single run, so the results may exhibit some random variability. In the NVT ensemble, the number of particles (N), volume (V), and temperature (T) were maintained constant during the pre-production steps (energy minimization, heating, and equilibration). The production run utilized the NPT ensemble, where the number of particles (N), pressure (P), and temperature (T) were kept constant, which is suitable for simulating biological macromolecules under conditions mimicking real-life experiments. Each production step had a time step of 0.002 ps (2 fs), with trajectory data saved every 5000 steps, or every 10 ps (0.01 ns). Pressure was set to 1.0 bar (100,000 Pa = 100 kPa), equivalent to one standard atmosphere. Counterions (Na⁺ and Cl⁻) were added using the Monte Carlo method to neutralize the system, with a concentration of 0.15 M. Distances in the analysis were measured in Ångströms (Å), with the conversion of 1 nm = 10 Å.

Statistical analysis

Statistical analyses were performed using GraphPad Prism 8 software (GraphPad Software, San Diego, CA). All data are expressed as the mean ± standard deviation (SD). For behavioral tests and serum ELISA assays, a sample size of n = 6 was utilized to ensure statistical robustness. For qPCR, tissue biochemical assays, and immunofluorescence staining, randomly selected samples (n = 3) from each group were analyzed due to constraints on tissue allocation from individual animals. The specific sample size for each experiment is explicitly stated in the corresponding figure legends. For comparisons among multiple groups, one-way analysis of variance (ANOVA) was used. Prior to ANOVA, the homogeneity of variances was assessed using Brown–Forsythe and Bartlett’s tests. When significant differences were detected, Dunnett’s multiple comparison test was applied to compare the treatment groups with the model group (e.g., Model vs. Fluoxetine, Model vs. SIN-low dose, Model vs. SIN-high dose). For pairwise comparisons between two groups, an unpaired two-tailed Student’s T-test was used. A p-value < 0.05 was considered statistically significant.

Results

High-dose SIN restores cerebral perfusion and alleviates depression-like behavior

To assess the effects of SIN on cerebral perfusion and depression-like behavior, laser speckle contrast imaging and behavioral tests were performed in PSD mice. As shown in Fig. 1A, the Blank group displayed normal cortical blood flow, while the Model group exhibited a distinct area of hypoperfusion. Treatment with Fluoxetine, SIN-low dose partially restored blood flow compared to the Model group, but not as effectively as Fluoxetine or SIN-high dose. SIN-high dose partially restored blood flow, improving cerebral perfusion to levels comparable to the Blank group. Quantification of relative cerebral blood flow (rCBF) confirmed a significant reduction in the Model group compared to Blank (p < 0.001), while all treatment groups showed improved perfusion, particularly the SIN-high dose group (p < 0.01; Fig. 1C). The comparison between Fluoxetine and the low-dose group show no significant effect (p = 0.288). The comparison between Fluoxetine and the high-dose group showed significant effect (p < 0.05). The comparison between the high-dose group and low-dose group showed significant effect (p < 0.01). Quantification of rCBF differed significantly among groups (p < 0.001). In the SPT (Fig. 1D), Model mice exhibited significant anhedonia (p < 0.001), which was ameliorated by Fluoxetine and SIN-high dose (p < 0.01, p < 0.05). SIN-low dose had a modest, non-significant effect (p = 0.14). Sucrose preference differed significantly among groups (p < 0.001). In the TST (Fig. 1E), Model mice showed reduced struggling time (p < 0.001), indicative of behavioral despair. Both Fluoxetine and SIN-high dose significantly prolonged struggling time (p < 0.01), while SIN-low dose produced a mild but significant improvement (p < 0.05). The comparison between Fluoxetine and the low-dose group showed significant effect (p < 0.001). The comparison between Fluoxetine and the high-dose group showed significant effect (p < 0.05). The comparison between the high-dose group and low-dose group showed significant effect (p < 0.001). Struggling time differed significantly among groups (p < 0.001). In the FST (Fig. 1I), the PSD model mice spent far more time floating than the blank controls (p < 0.001). Both fluoxetine and SIN treatments significantly reduced immobility versus model (p < 0.001 for fluoxetine, SIN‑low and SIN‑high). Notably, SIN‑low produced a greater reduction in immobility than fluoxetine (p < 0.01), and fluoxetine produced a greater reduction in immobility than SIN‑high (p < 0.001).

Fig. 1.

Evaluation of behavioral performance and cerebral perfusion in a photochemical thrombosis combined with LPS-induced PSD mouse model.A Representative laser speckle contrast images showing cerebral perfusion patterns across groups. B Representative locomotor trajectory tracks recorded in the open field test (OFT). C Quantitative analysis of the reduction rate of perfusion in the ischemic region relative to the normal area. D Analysis of sucrose preference (%) from the sucrose preference test (SPT). E Quantitative assessment of struggling time in the tail suspension test (TST). F Total distance traveled as measured during the OFT. G Time spent in the peripheral zone during the OFT. H Number of center entries recorded in the OFT. I Duration of floating in FST (s). Data are presented as mean ± SD, n = 6. ##p < 0.01, ###p < 0.001 vs. Blank; *p < 0.05, **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &&p < 0.01, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

SIN improves locomotor activity and reduces anxiety-like behavior in PSD mice

The open field test was used to evaluate spontaneous locomotor activity and anxiety-like behavior. Model mice exhibited reduced total distance traveled compared to the Blank group (p < 0.001), which was partially restored by Fluoxetine and SIN treatments. The comparison between Fluoxetine and the low-dose group showed significant effect (p < 0.05). The comparison between Fluoxetine and the high-dose group showed no significant effect (p = 0.343). The comparison between the high-dose group and low-dose group showed significant effect (p < 0.01). (Fig. 1B, F) (p < 0.001). Anxiety-like behavior was assessed by peripheral zone preference and center entries. Model mice spent significantly more time in the periphery (p < 0.001; Fig. 1G) and made fewer center entries (p < 0.001; Fig. 1H), consistent with anxiety. While SIN-low dose did not show any significant effect on the time spent in surrounding areas (p = 0.613), consistent with previous findings. Both Fluoxetine and SIN-high dose significantly reversed these effects (p < 0.05, p < 0.01). SIN-low dose showed a trend towards improvement but did not reach statistical significance (p = 0.059). Travel time in surrounding areas differed significantly among groups (p < 0.001). Similarly, number of entries into the central region differed significantly among groups (p < 0.001). Overall, these findings demonstrate that PSD mice exhibit marked perfusion deficits and depression/anxiety-like behaviors, which can be alleviated by SIN in a dose-dependent manner, with high-dose SIN exerting superior antidepressant and anxiolytic effects.

SIN attenuates neuronal loss in the hippocampal CA1 region of PSD mice

Nissl staining was performed to assess neuronal integrity in the hippocampal CA1 region (Fig. 2A). In the Blank group, neurons exhibited normal morphology with clear nuclei and neatly arranged layers. PSD model mice displayed pronounced histopathological changes, including decreased neuronal density, nuclear pyknosis, and disorganized cellular arrangement, indicating significant neuronal injury. Treatment with fluoxetine and SIN, especially at high doses, visibly improved these pathological features (p < 0.001). Quantification of neuronal density per area (Fig. 2B and Supplementary Figure S1) revealed that the number of surviving neurons in the Model group was significantly lower than in the Blank group (p < 0.001). Fluoxetine and SIN treatments significantly increased the neuronal count in the CA1 region, with the high-dose SIN group showing the greatest effect (p < 0.001). No significant differences were found between Fluoxetine and the low-dose group (p = 0.086), Fluoxetine and the high-dose group (p = 0.672), or between the high-dose and low-dose groups (p = 0.09). These results suggest that SIN treatment is associated with reduced hippocampal neuronal loss in PSD mice in a dose-dependent manner.

Fig. 2.

Histopathological, oxidative stress, and ferroptosis-related markers evaluations in PSD mice.A Representative Nissl staining images (400× magnification) of the hippocampal CA1 region in each group. B Semi-quantitative analysis of Nissl staining scores indicating neuronal damage. C Quantitative analysis of GSH-Px levels in brain tissues. D Quantification of iron ion (Fe) levels in brain tissues. E Measurement of MDA content reflecting lipid peroxidation. F Assessment of SOD activity. G Relative mRNA level of SLC7A11. H Relative mRNA level of ACSL4. Data are presented as mean ± SD, n = 3. ###p < 0.001 vs. Blank; *p < 0.05, **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &p < 0.05, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

SIN mitigates oxidative stress and ferroptosis-related changes

To further investigate the protective mechanisms of SIN, oxidative stress markers and ferroptosis-associated indicators were evaluated. As shown in Fig. 2C, glutathione peroxidase (GSH-Px) activity was significantly decreased in the Model group compared to Blank group (p < 0.001), indicating impaired antioxidant defense. This reduction was significantly reversed by Fluoxetine (p < 0.01) and SIN-high dose (p < 0.05), with the SIN-low dose group showing a mild but non-significant increase. No significant differences were found between Fluoxetine and the low-dose group (p = 0.446), Fluoxetine and the high-dose group (p = 0.155), or between the high-dose and low-dose groups (p = 0.747). Iron accumulation, a hallmark of ferroptosis, was markedly elevated in the Model group (p < 0.001; Fig. 2D) and significantly reduced in all treatment groups, especially in the SIN-high dose group (p < 0.001), suggesting its anti-ferroptotic potential. No significant differences were found between Fluoxetine and the low-dose group (p = 0.083), and between the high-dose and low-dose groups (p = 0.074). The comparison between Fluoxetine and the high-dose group showed significant effect (p < 0.05). Malondialdehyde (MDA), a lipid peroxidation product, was also significantly elevated in the Model group (p < 0.001; Fig. 2E), while Fluoxetine and both SIN doses reduced MDA levels (p < 0.05, p < 0.01, p < 0.001), with the most pronounced effect in the SIN-high dose group. No significant differences were found between Fluoxetine and the low-dose group (p = 0.06), Fluoxetine and the high-dose group (p = 0.058), or between the high-dose and low-dose groups (p = 0.524). Additionally, superoxide dismutase (SOD) activity was significantly decreased in the Model group (p < 0.001; Fig. 2F), indicating weakened free radical scavenging. SOD activity was significantly increased in the SIN-low (p < 0.01) and SIN-high dose (p < 0.001) groups, whereas Fluoxetine showed no significant effect. The comparison between Fluoxetine and the low-dose group showed significant effect (p < 0.05). The comparison between Fluoxetine and the high-dose group showed significant effect (p < 0.05). The comparison between the high-dose group and low-dose group showed significant effect (p < 0.05). The restoration of GSH-Px and the SOD activity, along with the reduction in MDA levels in SIN-treated groups, both suggesting that SIN treatment is associated with ferroptosis attenuation and upregulation of antioxidant defense systems and reducing lipid peroxidation, thereby protecting neurons from ferroptotic damage. To further confirm the regulation of ferroptosis, qPCR analysis showed that SIN significantly upregulated SLC7A11 and downregulated ACSL4 expression, further supporting its role in enhancing ferroptosis resistance. The mRNA levels of SLC7A11 and ACSL4 were significantly altered in the Model group (p < 0.001; Fig. 2G-H), with SLC7A11 expression reduced and ACSL4 expression increased. The SIN-treated group significantly reversed the gene expression altered by the Model, with SLC7A11 and ACSL4 expression levels returning closer to baseline, highlighting the potential of SIN to modulate the ferroptosis pathway effectively. The comparison between Fluoxetine and the low-dose group showed significant effect (p < 0.001 in SLC7A11; p < 0.05 in ACSL4). The comparison between Fluoxetine and the high-dose group showed significant effect (p < 0.001 in SLC7A11; p < 0.01 in ACSL4). The comparison between the high-dose group and low-dose group showed significant effect (p < 0.001 in SLC7A11; p < 0.05 in ACSL4). These findings suggest that SIN improves antioxidant enzyme activity, reduces lipid peroxidation, and attenuates iron overload, thereby protecting against PSD-induced oxidative and ferroptotic damage in the hippocampus.

SIN suppresses neuroinflammatory and chemotactic gene expression in PSD mice

To investigate the anti-inflammatory effects of SIN in PSD, quantitative real-time PCR was used to assess the mRNA expression of key pro-inflammatory cytokines (IL-1β, IL1A, IL-6, IL-18, TNF-α) and chemokines (CCL2, CCL5, CCL7, CXCL10) in brain tissues. As shown in Fig. 3A–E, PSD induction significantly elevated the expression of IL-1β and IL1A (p < 0.01), IL-6 (p < 0.01), IL-18 (p < 0.001), and TNF-α (p < 0.05) compared to the Blank group, indicating a robust neuroinflammatory response. Fluoxetine, SIN-low dose, and SIN-high dose all significantly suppressed IL-1β and IL1A expression (p < 0.001 vs. Model), with SIN treatments exerting stronger inhibitory effects than Fluoxetine. Similarly, IL-6 and IL-18 levels were markedly decreased by both SIN treatments and Fluoxetine, with SIN-high dose showing the greatest suppression (p < 0.001). TNF-α expression was also reduced in all treatment groups (p < 0.01 for both SIN doses), suggesting that SIN may modulate multiple inflammatory pathways. For IL‑1α, IL‑1β, IL‑6, IL‑18 and TNF‑α, the SIN high‑dose group exhibited a significant reduction in IL‑1α mRNA expression compared with the SIN low‑dose group (P < 0.05), whereas IL‑1β (P = 0.859), IL‑6 (P = 0.388), IL‑18 (P = 0.406) and TNF‑α (P = 0.605) showed no statistically significant differences between these two dosage groups. When compared with the fluoxetine group, SIN low‑dose treatment significantly decreased IL‑1α (P < 0.01), IL‑1β (P < 0.01) and IL‑18 (P < 0.01) mRNA levels, while IL‑6 (P = 0.112) and TNF‑α (P = 0.673) remained unchanged; similarly, the SIN high‑dose group did not differ significantly from fluoxetine in any of these five cytokine transcripts (all P > 0.05). And mRNA levels of IL-1β (p < 0.001), IL-6 (p < 0.001), TNF-α(p < 0.001), and IL-18 (p < 0.001) differed significantly among groups.

Fig. 3.

SIN attenuates neuroinflammatory and chemokine gene expression in the brains of PSD mice. A–E mRNA expression levels of pro-inflammatory cytokines including IL-1β, IL1A, IL-6, IL-18, and TNF-α. (F–I) mRNA expression levels of chemokines including CCL2, CCL5, CCL7, and CXCL10. Gene expression was normalized to GAPDH and analyzed using the 2^−ΔΔCt method. Data are presented as mean ± SD, n = 3. #p < 0.05, ##p < 0.01, ###p < 0.001 vs. Blank; *p < 0.05, **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &p < 0.05; &&p < 0.01, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

Regarding chemokine expression (Fig. 3F–I), CCL2 and CCL5 mRNA levels were significantly elevated in the Model group (p < 0.001), and this upregulation was strongly attenuated by SIN-low and SIN-high dose treatments (p < 0.001). CCL7 and CXCL10 levels were also significantly increased following PSD (CCL7: p < 0.01; CXCL10: p < 0.001), and were suppressed more effectively by SIN-high dose than by Fluoxetine. While Fluoxetine showed only a minor, non-significant effect on CCL7 expression (p = 0.17), SIN-low and high dose groups significantly downregulated both CCL7 and CXCL10 expression, especially at high dose (p < 0.001). For the four chemokines, SIN high‑dose treatment produced a significant reduction in CXCL10 mRNA expression relative to SIN low‑dose (P < 0.01), whereas CCL2 (P = 0.301), CCL5 (P = 0.240) and CCL7 (P = 0.581) were not significantly altered. Compared with fluoxetine, SIN low‑dose had no significant effect on CCL2 (P = 0.164), CCL5 (P = 0.325), CCL7 (P = 0.101) or CXCL10 (P = 0.425), and likewise, SIN high‑dose did not differ from fluoxetine in any of these chemokine transcripts (all P > 0.05). And mRNA levels of CCL2 (p < 0.001), CCL5 (p < 0.001), CCL7 (p < 0.001), and CXCL10 (p < 0.001) differed significantly among groups.

SIN modulates NF-κB and NRF2 signaling in PSD brain tissue

Immunofluorescence staining was performed to assess the expression and localization of NF-κB and NRF2, key regulators of neuroinflammation and oxidative stress, respectively. As shown in Fig. 4A, in the Blank group, NF-κB was predominantly localized in the cytoplasm with weak fluorescence intensity, indicating an inactive state. In contrast, PSD Model mice exhibited marked nuclear translocation of NF-κB, consistent with inflammatory activation. Quantitative analysis (Fig. 4B) confirmed a significant increase in nuclear NF-κB signal in the Model group compared to Blank groups (p < 0.001). Treatment with Fluoxetine, SIN-low dose, and SIN-high dose significantly reduced NF-κB nuclear translocation (p < 0.01, p < 0.001 vs. Model), with the SIN-high dose group showing the most potent inhibitory effect (p < 0.001). To further validate these findings at the protein level, serum NF-κB concentrations were measured by ELISA. As shown in Fig. 4D, the Model group exhibited significantly elevated serum NF-κB levels compared to the Blank group, while SIN treatment effectively reversed this increase, aligning with the activation pattern observed in brain tissue.

Fig. 4.

Immunofluorescence analysis of NF-κB and NRF2 signaling in the brains of PSD mice. A Representative immunofluorescence images showing the subcellular localization and expression of NF-κB (green) and NRF2 (green) in hippocampal sections from each group. Nuclei were counterstained with DAPI (blue). Scale bar: 40 μm. B Quantification of NF-κB-positive nuclear area, reflecting the degree of nuclear translocation. C Quantification of nuclear NRF2 fluorescence intensity. D–E ELISA analysis of the serum concentrations of NF-κB and NRF2. Data are presented as mean ± SD, n = 3. ###p < 0.001 vs. Blank; **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &&p < 0.01 SIN-high dose vs. SIN-low dose.

For NRF2, a master regulator of antioxidant defense, the Blank group showed strong nuclear fluorescence signal (Fig. 4A), while the Model group exhibited both diminished intensity and abnormal cytoplasmic redistribution, suggesting impaired nuclear translocation. As shown in Fig. 4C, Fluoxetine, SIN-low dose, and especially SIN-high dose markedly restored NRF2 nuclear localization and fluorescence intensity (p < 0.01, p < 0.001 vs. Model), and fluorescence intensity of NRF2 differed significantly among groups (p < 0.001). Consistent with the tissue-level observations, ELISA analysis of serum samples (Fig. 4E) revealed that the Model group had reduced total NRF2 protein levels, which were significantly upregulated following SIN treatment, thereby corroborating the restoration of antioxidant capacity.

For NF‑κB immunofluorescence area, the SIN low‑dose group showed a significant increase compared to the fluoxetine group (P < 0.05), whereas the SIN high‑dose group exhibited a significant decrease relative to the SIN low‑dose group (P < 0.01), with no significant difference observed between the SIN high‑dose and fluoxetine groups (P > 0.05). For NRF2 immunofluorescence area, the SIN low‑dose group displayed a significant increase compared to the fluoxetine group (P < 0.001), the SIN high‑dose group further increased relative to the SIN low‑dose group (P < 0.01), and no significant difference was detected between the SIN high‑dose and fluoxetine groups (P > 0.05).

These results demonstrate that PSD is associated with a dual imbalance in NF-κB/NRF2 signaling—namely, the activation of pro-inflammatory NF-κB and suppression of antioxidative NRF2 pathways. SIN reversed both abnormalities in a dose-dependent manner: high-dose SIN not only significantly inhibited NF-κB activation (p < 0.001), but also robustly restored NRF2 nuclear translocation (p < 0.001). This dual regulation suggests that SIN treatment is associated with coordinated modulation of inflammatory and oxidative stress pathways, which may contribute to its observed neuroprotective effects in PSD.

SIN restores GPX4 expression and inhibits TLR4-mediated inflammation in PSD brain tissue

Immunofluorescence staining was conducted to investigate the expression patterns of GPX4, a key marker of ferroptosis, and TLR4, a central mediator of neuroinflammation, in the hippocampal CA1 region of PSD mice. As shown in Fig. 5A, GPX4 was abundantly expressed in the nuclei and cytoplasm of neurons in the Blank group, consistent with a robust antioxidative capacity under physiological conditions. In contrast, the Model group exhibited markedly diminished GPX4 fluorescence, indicating impaired ferroptosis resistance. Meanwhile, TLR4 expression was significantly elevated in the Model group, showing enhanced immunofluorescence intensity and abnormal upregulation, while remaining minimal in the Blank group.

Fig. 5.

Immunofluorescence analysis of GPX4 and TLR4 expression in the hippocampus of PSD mice. A Representative images showing GPX4 (top two rows, green) and TLR4 (bottom two rows, green) immunofluorescence in the hippocampal CA2 region of each group. Nuclei were counterstained with DAPI (blue). Scale bar: 40 μm. B Quantification of GPX4 fluorescence area, reflecting ferroptosis resistance. C Quantification of TLR4 fluorescence area, indicating the extent of neuroinflammatory activation. D, E ELISA analysis of the serum concentrations of GPX4 and TLR4. Data are presented as mean ± SD, n = 3. ##p < 0.01, ###p < 0.001 vs. Blank; **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &&p < 0.01, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

Quantitative analysis (Fig. 5B) demonstrated a significant reduction in GPX4-positive area in the Model group compared to the Blank group (p < 0.01), which was significantly reversed by Fluoxetine and both low- and high-dose Sinensetin treatment (p < 0.01, p < 0.001 vs. Model). The high-dose SIN group showed the most pronounced restorative effect (p < 0.001). To corroborate these tissue-level findings, serum GPX4 levels were measured by ELISA. As shown in Fig. 5D, SIN treatment effectively restored the depleted serum GPX4 protein levels in PSD mice, aligning with the ferroptosis-inhibiting effect observed in the hippocampus. Similarly, TLR4 expression was significantly increased in the Model group (p < 0.001; Fig. 5C), but this upregulation was markedly attenuated by Fluoxetine (p < 0.01), SIN-low dose (p < 0.001), and especially SIN-high dose treatment (p < 0.001), suggesting a dose-dependent anti-inflammatory effect (p < 0.001). This systemic anti-inflammatory efficacy was further confirmed by ELISA analysis (Fig. 5E), which demonstrated that SIN treatment significantly downregulated the elevated serum TLR4 concentrations induced by PSD.

For GPX4 immunofluorescence area, the SIN low‑dose group showed no significant difference compared to the fluoxetine group (P = 0.208); by contrast, the SIN high‑dose group exhibited a significant increase relative to the fluoxetine group (P < 0.01) and was further elevated compared to the SIN low‑dose group (P < 0.01). For TLR4 immunofluorescence area, the SIN low‑dose group demonstrated a significant decrease compared to the fluoxetine group (P < 0.001); similarly, the SIN high‑dose group also showed a significant reduction versus fluoxetine (P < 0.001) and was further diminished relative to the SIN low‑dose group (P < 0.001).

These findings indicate that the progression of PSD involves dual dysregulation—suppression of the antioxidative ferroptosis-regulator GPX4 and overactivation of the TLR4 inflammatory pathway. High-dose Sinensetin intervention was able to simultaneously restore GPX4 expression and suppress excessive TLR4 activation. This coordinated regulation of ferroptosis and inflammation suggests that Sinensetin treatment is associated with a synergistic “antioxidant–anti-inflammatory” profile, which may underlie its neuroprotective effects in PSD, warranting further mechanistic investigation.

SIN inhibits glial activation in the hippocampal DG region and suppresses inflammatory mediators

To further validate the anti-neuroinflammatory efficacy of SIN, we performed immunofluorescence staining to assess the activation levels of microglia and astrocytes in the dentate gyrus (DG) region of the hippocampus (Fig. 6A). As shown in the representative images, the PSD Model group exhibited a robust increase in the immunoreactivity of IBA1 (microglial marker) and GFAP (astrocytic marker) in the DG region compared to the Blank group, indicating significant glial activation. However, SIN treatment effectively suppressed this upregulation. Quantitative analysis confirmed that the immunofluorescence coverage areas of IBA1 and GFAP were significantly elevated in the Model group but were markedly reduced following SIN administration (p < 0.001; Fig. 6B–C). Notably, high-dose SIN demonstrated a superior inhibitory effect on glial activation compared to the low-dose group (p < 0.001).

Fig. 6.

SIN inhibits glial activation in the hippocampal DG region and reduces inflammatory cytokines. A Representative immunofluorescence images of IBA1 (microglia, green) and GFAP (astrocytes, green) showing the expression levels in the dentate gyrus (DG) of the hippocampus. Nuclei were counterstained with DAPI (blue). Scale bar: 40 μm. B, C Quantitative analysis of the immunofluorescence area (reflecting activation levels) of IBA1 (B) and GFAP (C) in the DG region. (D–I) ELISA analysis of the concentrations of IBA1 (D), GFAP (E), TNF-α (F), IL-6 (G), IL-1β (H), and CCL2 (I). Data are presented as mean ± SD (n = 3 for immunofluorescence analysis in B–C; n = 6 for ELISA analysis in D–I), ###p < 0.001 vs. Blank; **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &&p < 0.01, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

Consistent with the immunofluorescence findings, ELISA analysis revealed that the protein levels of IBA1 and GFAP were significantly upregulated in the PSD mice (p < 0.001; Fig. 6D–E). Treatment with SIN, particularly at the high dose, robustly downregulated these markers. Furthermore, we examined the downstream inflammatory mediators driving the “cytokine storm.” The concentrations of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β) and the chemokine CCL2 were drastically increased in the Model group (p < 0.001; Fig. 6F–I). SIN treatment significantly attenuated the secretion of these factors in a dose-dependent manner. Specifically, high-dose SIN reduced the levels of IL-6, IL-1β, and CCL2 (p < 0.001) more effectively than the low dose, with TNF-α and CCL2 levels reaching values comparable to the fluoxetine-treated group (p > 0.05).

Collectively, these data provide compelling evidence that SIN mitigates PSD-induced neuroinflammation by suppressing the overactivation of microglia and astrocytes in the hippocampal DG region and blocking the release of pro-inflammatory cytokines.

Molecular docking reveals multitarget binding potential of SIN

To explore the potential molecular targets underlying the neuroprotective effects of SIN, molecular docking analyses were performed using AutoDock Vina to predict potential binding modes between SIN and four key proteins involved in inflammation and oxidative stress: NF-κB, NRF2, GPX4, and TLR4. As shown in Fig. 7, SIN exhibited favorable binding affinity with all four targets, with vina scores ranging from − 5.8 to − 7.7 kcal/mol, suggesting the feasibility of stable interactions rather than confirming direct binding.

Fig. 7.

Molecular docking of Sinensetin with NF-κB, NRF2, GPX4, and TLR4.

Specifically, SIN bound to NF-κB (vina score: −5.8) at a pocket involving residues K315, G294, D279, and K334, forming multiple hydrogen bonds and hydrophobic interactions, which may be relevant to its observed inhibitory effects on NF-κB activation. For NRF2, SIN showed the strongest binding affinity (vina score: −7.7), occupying a deep hydrophobic cleft lined by residues V420, A465, F514, and S558, suggesting a potential interaction interface related to NRF2 stabilization.

Docking with GPX4 (vina score: −6.4) revealed interactions with critical residues M129, K135, and L157, which may be associated with modulation of GPX4 activity. Similarly, SIN was predicted to interact with TLR4 (vina score: −7.2) at residues Y31, R52, and F121, suggesting a possible structural basis for the observed suppression of TLR4 signaling in vivo.

Overall, these docking results offer supportive, hypothesis-generating evidence that aligns with the in vivo and in vitro findings, suggesting that the antidepressant and neuroprotective effects of SIN in PSD may be associated with its multitarget regulatory capacity, involving coordinated modulation of TLR4/NF-κB-mediated neuroinflammation and NRF2/GPX4-dependent antioxidant defenses, rather than definitive proof of direct molecular binding.

Predicted binding interactions between SIN and four key target proteins related to neuroinflammation and oxidative stress: NF-κB, NRF2, GPX4, and TLR4. Left panels show the surface structure of each protein with highlighted binding pockets (yellow or pink), while right panels show magnified views of the docking poses and interacting residues (labeled).

Molecular dynamics simulations of SIN–TLR4 and SIN–KEAP1 complexes

To evaluate the binding stability and dynamic behavior of SIN with key inflammatory and oxidative stress-related targets, we conducted 100 ns MD simulations for SIN–TLR4 and SIN–KEAP1 complexes. The results are summarized as follows:

SIN–TLR4 Complex: As shown in Fig. 8A–F, SIN formed stable interactions with TLR4 through hydrogen bonds, π-π stacking, and hydrophobic contacts, particularly involving residues Asp209, Glu239, and Tyr292 (Fig. 8A). The 3D free energy surface (Fig. 8B) revealed a relatively broad energy basin, suggesting a moderate conformational flexibility of the complex. The 2D free energy plot (Fig. 8C) indicated a dominant low-energy region centered around RMSD ≈ 5.2 Å and radius of gyration (Rg) ≈ 32.4 Å. The RMSD trajectory (Fig. 8D) showed that the protein backbone stabilized after ~ 20 ns, with fluctuations maintained within 2.0–3.0 Å, while the ligand remained stably bound with lower RMSD values (< 3.5 Å), indicating good overall binding stability. The RMSF analysis (Fig. 8E) revealed that most residues had fluctuations below 3.0 Å, except for a few surface-exposed loop regions, indicating a structurally stable binding interface. Hydrogen bond analysis (Fig. 8F) demonstrated consistent formation of 1–3 hydrogen bonds throughout the simulation, further supporting stable SIN–TLR4 interactions.

Fig. 8.

Molecular Dynamics Simulations of SIN–TLR4 and SIN–KEAP1 Complexes. (A–F) SIN–TLR4 complex: A 2D schematic of SIN binding to TLR4; B 3D free energy surface (RMSD vs. Rg); C 2D free energy contour plot; D RMSD trajectories of protein and ligand; E RMSF of TLR4 residues; F number of hydrogen bonds over time. G–L SIN–KEAP1 complex: G 2D schematic of SIN binding to KEAP1; H 3D free energy landscape; I 2D free energy contour plot; J RMSD trajectories; K RMSF of KEAP1 residues; L hydrogen bond count over time.

SIN–KEAP1 Complex: As illustrated in Fig. 8G–L, SIN exhibited strong and focused binding to the KEAP1 pocket, forming hydrogen bonds and hydrophobic interactions with key residues such as Ser508, Arg415, and Ala556 (Fig. 8G). The 3D free energy landscape (Fig. 8H) showed a sharply localized minimum, indicating a more rigid and energetically favorable conformation. The 2D energy surface (Fig. 8I) also supported this, with a dominant low-energy basin centered around RMSD ≈ 4.6 Å and Rg ≈ 19.0 Å. In the RMSD plot (Fig. 8J), the KEAP1 backbone remained stable over time, and the ligand displayed very low RMSD (< 2.5 Å), indicating excellent conformational stability of the SIN–KEAP1 complex. RMSF values (Fig. 8K) were uniformly low across residues, suggesting minimal local fluctuations. Hydrogen bond analysis (Fig. 8L) revealed persistent interaction patterns with 2–4 hydrogen bonds consistently maintained, supporting a strong binding profile.

Together, these MD simulations indicate that SIN can form energetically favorable and dynamically stable complexes with both TLR4 and KEAP1 under simplified modeling conditions, particularly exhibiting strong interaction stability with KEAP1. These atomistic analyses are consistent with the molecular docking results and provide supportive structural insight into the potential interaction stability of SIN with its putative anti-inflammatory and antioxidant targets, thereby offering a structural context for the downstream biological effects observed in vivo.

SIN modulates downstream genes of the TLR4 and NRF2 pathways in the hippocampus

To further clarify the mechanism of SIN in PSD treatment, we examined the mRNA levels of key downstream targets of TLR4 and NRF2 pathways in the hippocampus using qPCR (Fig. 9). For the TLR4 pathway (Fig. 9A–D), the model group exhibited significantly elevated mRNA levels of MyD88, IL-1β, TNF-α, and iNOS compared to the blank group (p < 0.001), indicating robust neuroinflammation. Fluoxetine and both SIN doses significantly suppressed these inflammatory markers (p < 0.001 vs. model). Notably, SIN-high dose produced a more pronounced downregulation of MyD88, IL-1β, and iNOS than SIN-low dose (p < 0.01 or p < 0.001), and was also more effective than fluoxetine in reducing IL-1β and iNOS levels. Although TNF-α expression was markedly reduced in all treatment groups, there was no significant difference between SIN-high and fluoxetine groups (p = 0.418).

Fig. 9.

Effects of SIN on mRNA expression of TLR4 and NRF2 pathway downstream genes in the hippocampus of PSD mice. A–D Relative mRNA levels of MyD88, IL-1β, TNF-α, and iNOS. E–H Relative mRNA levels of HO-1, NQO1, GCLM, and SOD1. Data are presented as mean ± SD, n = 3. ###p < 0.001 vs. Blank; *p < 0.05, **p < 0.01, ***p < 0.001 vs. Model; +p < 0.05, ++p < 0.01, +++p < 0.001 vs. Fluoxetine; &p < 0.05, &&&p < 0.001 SIN-high dose vs. SIN-low dose.

For the NRF2 pathway (Fig. 9E–H), antioxidant genes HO-1, NQO1, GCLM, and SOD1 were significantly downregulated in the model group relative to blank controls (p < 0.001). SIN treatment, especially at high dose, markedly upregulated the expression of all four antioxidant genes. SIN-high dose significantly increased HO-1 and GCLM levels above fluoxetine (p < 0.05), and restored SOD1 to near-normal expression. While fluoxetine and SIN-low dose also promoted gene expression, their effects were comparatively modest. Notably, NQO1 expression in the SIN-high group exhibited an upward trend compared to fluoxetine (p = 0.061), suggesting potential dose responsiveness. These findings confirm that SIN exerts dual regulatory effects in the hippocampus by suppressing pro-inflammatory responses via TLR4 and enhancing antioxidant defenses through NRF2 activation, supporting its mechanistic role in PSD treatment.

Discussion

This study provides compelling evidence that SIN, a polymethoxylated flavonoid derived from citrus fruits, exerts neuroprotective effects in a mouse model of PSD which are associated with modulation of the TLR4/NF-κB and NRF2/GPX4 signaling pathways. Our findings demonstrate that SIN not only ameliorates depressive-like behaviors but also restores cerebral perfusion, attenuates hippocampal neuronal damage, and mitigates oxidative stress and neuroinflammation.

The validity of our PSD model is essential for interpreting these findings. The right anterior/sensorimotor cortex was photothrombotic infarction. Clinical and experimental evidence shows that lesions in frontal regions, especially prefrontal and anterior motor areas, are linked to post-stroke depression through disruption of front-limbic circuits regulating mood and cognition^29,34. This cortical location induces depressive-like behaviors while preserving motor function, crucial for behavioral tests such as the forced swim and sucrose assays³⁰. Furthermore, the photochemically induced thrombosis (PIT) technique was adopted instead of the middle cerebral artery occlusion (MCAO) model. PIT produces highly reproducible, sharply demarcated cortical infarcts with low mortality, minimal variability in infarct size, and limited damage to deep brain structures, thereby improving the construct and face validity of PSD modeling³⁵.

Recent high-impact studies have firmly established the TLR4/NF‑κB and NRF2 signaling pathways as central to PSD pathology. Activation of NF‑κB, often downstream of TLR4 stimulation by ischemia-induced cytokines, triggers microglial polarization, cytokine release, and synaptic disruption—events intimately linked to depressive-like behaviors^36,37. LPS-induced hypoactivity is transient and distinct from depression-related behaviors. Our findings from TST, FST, and SPT highlight that SIN’s effects were on depressive-like behavior, not merely on locomotor function. Recent studies support the use of LPS combined with stroke to model depression, validating the PSD model employed in this study³⁸. The TLR4/NF-κB signaling pathway plays a pivotal role in mediating neuroinflammatory responses following cerebral ischemia, contributing to the pathogenesis of PSD. Activation of TLR4 leads to the translocation of NF-κB into the nucleus³⁹, promoting the transcription of pro-inflammatory cytokines such as TNF-α, IL-1β, and IL-6^40,41. Our study observed a significant upregulation of TLR4 and nuclear NF-κB in the hippocampus of PSD mice, which was effectively suppressed by SIN treatment. This aligns with previous research indicating that SIN can inhibit the TLR4/NF-κB pathway and reduce neuroinflammation in various models²⁷.

Concurrently, oxidative stress and ferroptosis are critical contributors to neuronal damage in PSD. NRF2 serves as a master regulator of antioxidants and anti-oxidants defenses; its suppression in PSD models leads to GPX4 downregulation, iron overload, lipid peroxidation, and neuronal loss. Pharmacological activation of NRF2 consistently reverses these pathological changes and mitigates depressive behaviors in PSD animals⁴². Multiple studies show that activating the NRF2 pathway enhances the expression of antioxidant enzymes like GPX4 and SLC7A11, which counteract oxidative stress and ferroptosis after stroke^14,43,44. In our PSD model, we observed a marked decrease in nuclear NRF2 and GPX4 expression, indicative of impaired antioxidant defenses and enhanced ferroptotic activity. SIN administration restored NRF2 nuclear localization and upregulated GPX4 expression, suggesting a reactivation of the antioxidant response. These results are consistent with studies demonstrating the role of NRF2/GPX4 in mitigating ferroptosis and oxidative stress in neurological disorders. Activation of the NRF2/GPX4 pathway reduces oxidative damage, neuronal death, and infarct volume in ischemia-reperfusion models. Compounds like Rhein, quercetin, and ozone enhance NRF2 activation, leading to increased GPX4 expression and suppression of lipid peroxidation and ferroptosis^43–45. While not all studies focused on specific diseases, broad evidence shows that NRF2 activation suppresses oxidative stress and protects neuronal integrity by regulating GPX4, iron metabolism, and anti-inflammatory responses^46,47.

The inhibition of NF-κB nuclear translocation and the restoration of NRF2 nuclear localization affected by the SIN treatment suggest that SIN may contribute to breaking the inflammatory-oxidative cycle in PSD. The activation of NF-κB inhibits NRF2 by upregulating KEAP1⁴⁸, causing oxidative stress⁴⁹ and ferroptosis⁵⁰. SIN counteracts this cycle by inhibiting NF-κB activation and promoting NRF2 nuclear translocation, thereby reducing neuroinflammation and enhancing the antioxidant response. This modulation of NF-κB and NRF2 highlights the dual regulatory effect of SIN on both inflammatory and oxidative pathways, which underscores its potential as a multifaceted therapeutic agent for PSD. Molecular docking analyses further support this, revealing strong binding affinities of SIN to TLR4, NF-κB, NRF2, and GPX4, which may be relevant to its observed modulatory effects. Such multitarget engagement is advantageous in complex disorders like PSD, where multiple pathological processes are intertwined. The parallel improvements observed in both behavioral phenotypes and the expression of inflammation- and oxidative stress-related genes (TLR4 and NRF2 pathways) suggest a mechanistic link. Notably, the superior effects of high-dose SIN at both molecular and behavioral levels support the hypothesis that SIN’s antidepressant and anxiolytic actions may be mediated, at least in part, by its dual regulation of neuroinflammation and antioxidant defense.

In this study, SIN’s multitarget engagement in complex PSD pathology is further supported by our gene expression analyses. These findings demonstrate that SIN ameliorates PSD‑associated neuroinflammation and oxidative imbalance in the hippocampus through coordinated regulation of MyD88‑dependent signaling and endogenous antioxidant defenses. The robust upregulation of MyD88, IL‑1β, TNF‑α and iNOS in PSD mice confirms activation of the TLR4/MyD88-NF‑κB pro‑inflammatory cascade, whereas downregulation of HO‑1, NQO1, GCLM and SOD1 reflects impaired NRF2‑mediated antioxidative capacity. Both fluoxetine and SIN treatments normalized these dysregulated transcripts, but SIN exerted a clear dose‑dependent advantage: SIN‑high produced significantly greater suppression of pro‑inflammatory genes and stronger induction of antioxidant enzymes compared to SIN‑low (all p < 0.05–0.001). Notably, SIN‑low outperformed fluoxetine in upregulating HO‑1, GCLM and SOD1, suggesting that SIN engages endogenous redox machinery more effectively than a classical antidepressant. Together, these data support a dual‑action mechanism whereby SIN not only inhibits MyD88‑driven neuroinflammation but also bolsters NRF2‑target gene expression, thereby restoring hippocampal homeostasis and contributing to its superior neuroprotective and antidepressant efficacy in PSD. Molecular docking analyses further support this, revealing strong binding affinities of SIN to TLR4, NF‑κB, NRF2, and GPX4, suggesting direct interactions that may underlie its modulatory effects. Such multitarget engagement is advantageous in complex disorders like PSD, where multiple pathological processes are intertwined.

Although NRF2 is a key transcription factor in the antioxidant defense system and an important target in this study, we did not perform MD simulations for the SIN–NRF2 complex due to the inherent structural limitations of NRF2. Specifically, the N‑terminal Neh2 domain of NRF2, which contains the critical ETGE and DLG motifs responsible for binding to KEAP1, is classified as a typical intrinsically disordered region (IDR). These regions lack stable secondary or tertiary structure in solutions and exhibit highly dynamic conformational flexibility. As a result, classical MD simulations of such disordered proteins often fail to reach structural convergence and produce unreliable interaction models. Given these challenges, we selected KEAP1-a well‑characterized upstream regulator of NRF2—as the alternative docking and simulation target. KEAP1 functions as the central redox sensor and negative regulator of NRF2, directly determining its stability and activation. Targeting KEAP1 can provide insight into SIN’s potential to modulate NRF2 signaling via the stabilization of NRF2 or disruption of KEAP1–NRF2 interactions. Furthermore, KEAP1 has a well‑defined β‑propeller domain suitable for high‑quality docking and MD analysis, thereby ensuring structural reliability of the simulation data.

Moreover, A recent study identified sinensetin as one of several polymethoxylated flavones (PMFs) with excellent BBB permeability. It demonstrated anti-inflammatory effects in an Alzheimer’s disease mouse model, reducing neuroinflammation and showing brain-targeted activity after in vivo administration⁵¹. Its natural origin and minimal toxicity profile make it an attractive candidate for further development. However, while our findings are promising, clinical studies are necessary to validate the efficacy and safety of SIN in human subjects with PSD.

Despite these strengths, our study has several limitations that warrant attention. First, we relied on pharmacological intervention without genetic manipulation (e.g., knockout mice or specific inhibitors), limiting our findings to mechanistic associations rather than definitive causality. Second, future studies may benefit from the inclusion of separate ischemia-only or inflammation-only control groups to better disentangle the individual contributions of cerebral ischemia and systemic inflammation to PSD pathogenesis. Third, although molecular docking and MD simulations suggested energetically favorable interactions between SIN and key targets, these in silico analyses were conducted under simplified modeling conditions. Specifically, the TLR4 simulation did not fully incorporate the MD-2 co-receptor complex, and the KEAP1–NRF2 interaction is dynamic and structurally complex due to the intrinsically disordered regions of NRF2. Therefore, these computational results should be interpreted as predictive and hypothesis-generating rather than definitive evidence of direct binding, which requires future validation via biophysical assays such as Surface Plasmon Resonance (SPR). Finally, the sample size for molecular assays (qPCR and Western blot) was relatively small (n = 3) due to tissue availability constraints and adherence to the 3Rs principle. However, the high consistency between these molecular data and the behavioral outcomes (n = 6) supports the robustness of our conclusions.

Conclusion

In summary, this study demonstrates that SIN, a polymethoxylated flavonoid derived from citrus, effectively alleviates PSD in mice associated with dual modulation of the TLR4/NF-κB and NRF2/GPX4 signaling pathways. SIN significantly improved cerebral perfusion, attenuated hippocampal neuronal damage, suppressed neuroinflammation, and enhanced antioxidant defense. Molecular docking further confirmed its multitarget binding capacity to key regulators of neuroinflammation and ferroptosis. These findings highlight SIN’s potential as a promising natural therapeutic candidate for PSD, offering a multi-mechanistic regulatory profile associated with both inflammatory and oxidative stress-related pathology. Future investigations should focus on validating these effects in clinical settings and elucidating SIN’s long-term efficacy and safety.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

BBB

Blood–Brain Barrier

CBF

Cerebral Blood Flow

CCL

C–C Motif Chemokine Ligand

CNS

Central Nervous System

CST

Cell Signaling Technology

CXCL

C–X–C Motif Chemokine Ligand

DAPI

4′,6-Diamidino-2-Phenylindole

DG

Dentate gyrus

ELISA

Enzyme-Linked Immunosorbent Assay

FST

Forced Swimming Test

GFAP

Glial fibrillary acidic protein

GPX4

Glutathione Peroxidase 4

GSH-Px

Glutathione Peroxidase

IBA1

Ionized calcium-binding adapter molecule 1

IF

Immunofluorescence

IL

Interleukin

KEAP1

Kelch-like ECH-associated Protein 1

LPS

Lipopolysaccharide

LSCI

Laser Speckle Contrast Imaging

MD

Molecular Dynamics

MDA

Malondialdehyde

NF-κB

Nuclear Factor-kappa B

NRF2

Nuclear Factor Erythroid 2-related Factor 2

OFT

Open Field Test

PBS

Phosphate Buffered Saline

PCR

Polymerase Chain Reaction

PMFs

Polymethoxylated Flavones

PSD

Post-Stroke Depression

qPCR

Quantitative Polymerase Chain Reaction

rCBF

Relative Cerebral Blood Flow

ROS

Reactive Oxygen Species

SIN

Sinensetin

SOD

Superoxide Dismutase

SPT

Sucrose Preference Test

TST

Tail Suspension Test

TLR4

Toll-like Receptor 4

TNF-α

Tumor Necrosis Factor-alpha

Author contributions

Qiqi Fan contributed to resource provision, original draft preparation, formal analysis, and data visualization. Renfeng Huang was involved in original draft writing, formal analysis, and visualization. Kunling Luo participated in original draft writing, data curation, and experimental investigation. Jiaxin Chen and Xuanying Yin contributed to the original draft, experimental investigations, and manuscript review and editing. Erjuan Zhao and Yuanyue Liu contributed to the original draft and conducted experimental investigations. Lei Sheng and Qi Wang were responsible for conceptualization, project administration, supervision, and manuscript review and editing. Weiwu Cai provided resources and contributed to conceptualization, project administration, supervision, and manuscript review and editing.

Funding

This work was supported by the Scientific Research Project of Guangdong Provincial Bureau of Traditional Chinese Medicine (No.20251448), Science and Technology Projects in Guangzhou (No.2023A04J1926), Jiangmen Science and Technology Bureau Project (No.2024YL02001), Jiangsu Association of Chinese Medicine Eaglet Soaring Project (No.CYTF2024015), and Intra-hospital Young and Middle-aged Science and Technology Elites Project (No.SEZ2023001).

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. All data supporting the findings of this study are included in the article and its supplementary information files.

Declarations

Competing interests

The authors declare no competing interests.