Effects of NMDAR2B-mediated Hippocampal Neuron Protection on Cognitive Function in Rats with Depression

Effects of NMDAR2B-mediated Hippocampal Neuron Protection on Cognitive Function in Rats with Depression | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of NMDAR2B-mediated Hippocampal Neuron Protection on Cognitive Function in Rats with Depression Longfei Liu, Peifan Li, Yongxue Hu, Qing Shan, Hongping Li, Yuhan Wei, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5371457/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background To observe the changes in cognitive function of depressive model rats after fluoxetine intervention, and further explore the correlation between fluoxetine's influence on cognitive function in depressive model rats and the N-methyl-D-aspartate receptor 2B subunit (NMDAR2B) in the hippocampus, as well as its impact on hippocampal neurons. Methods The depression model was established using Chronic Unpredictable Mild Stress (CUMS) combined with solitary confinement, followed by fluoxetine intervention upon successful establishment. Neurobehavioral assessments were conducted to evaluate the rats' emotions, cognition, and learning abilities. Molecular docking technology was employed to observe the affinity between fluoxetine and the NMDAR2B subunit. Proteomic analysis was performed to detect changes in NMDAR2B protein, and histopathological staining was used to observe pathological alterations in neurons in the rat hippocampus. Finally, statistical analysis of the data was conducted. Results After modeling, the rats exhibited depressive-like behaviors, impaired cognitive learning and memory abilities, significantly reduced expression and concentration of NMDAR2B protein, pathological damage to neurons in the hippocampus, decreased number of Nissl bodies, markedly reduced dendritic spine density, damaged synaptic structures with decreased synaptic vesicles. Following fluoxetine intervention, these conditions showed varying degrees of recovery. Correlation analysis revealed that the cognitive and learning abilities of rats were impaired, accompanied by a significant decrease in dendritic spine density and a decline in the expression of the NMDAR2B protein. Conclusions Fluoxetine may exert neuroprotective effects by regulating the expression of NMDAR2B protein in the hippocampus, thereby improving the cognitive function of depressed rats. Depression Cognitive Dysfunction in Depression NMDAR2B CUMS Hippocampal Neurons Learning and Memory Rats Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Cognitive impairment is one of the core symptoms of major depressive disorder (MDD), manifesting across different stages of the illness and significantly impacting the prognosis and functional recovery of patients [ 1 ]. A major obstacle to the full recovery of MDD patients lies in the improvement of cognitive dysfunction symptoms [ 2 ]. In 2016, the US Food and Drug Administration (FDA) Drug Evaluation and Research Expert Working Group recommended targeting cognitive symptoms as an intervention point in the treatment of MDD [ 3 ]. Currently, there is no specific drug for treating cognitive dysfunction in MDD. Studies have shown that existing selective serotonin reuptake inhibitors (SSRIs) can improve cognitive symptoms in depressed patients [ 4 – 6 ], but the underlying mechanisms remain unclear and require further investigation. Decreased cortical volume in brain regions associated with cognitive function, such as the hippocampus and prefrontal cortex, is a characteristic brain structural feature in MDD patients [ 7 ]. Among these, the hippocampus, an essential component of the limbic system, is closely associated with learning, memory, emotion, and visceral regulation [ 8 ]. NMDA receptor subunit 2B (NMDAR2B) is a subtype of the NMDA (N-methyl-D-aspartate) receptor family within the ionotropic glutamate receptors. NMDAR2B plays a crucial role in neurons and is a key molecule involved in physiological processes such as learning, memory, and pain perception within the central nervous system [ 9 , 10 ]. Some studies have reported abnormally elevated NMDAR2B levels in depressed mice, and modulating NMDA receptors can exert anxiolytic and antidepressant effects [ 11 ]. However, other studies have yielded contrasting results, with chronic stress leading to a significant decrease in NMDAR2B protein levels, and increasing NMDAR2B subunit levels able to regulate depressive-like behaviors [ 12 ]. In this study, a rat model of depression was established using chronic unpredictable mild stress (CUMS) combined with solitary rearing, and the rats were intervened with the classic antidepressant fluoxetine through intragastric administration. Neurobehavioral manifestations, histopathological changes in the hippocampus, and alterations in NMDAR2B protein were observed and analyzed for their correlations. The aim was to explore the potential mechanisms underlying depressive cognitive dysfunction, providing a more solid theoretical foundation and insights for clinical treatment. Materials and Methods Animals Forty-five six-week-old, Specific Pathogen Free (SPF), adult male, healthy Sprague Dawley (SD) rats with a body weight of 250 ± 20g were obtained from the Experimental Animal Center of Zunyi Medical University. The experimental animal use license number is: SCXK (Qian) 2021-0002. During the experimental period, the rats were housed in the Animal Experimental Center of Guizhou Medical University. The animal experimental research protocol has been approved by the Animal Ethics Committee of Guizhou Medical University (Approval Number: 2305201). Major Reagents and Instruments Fluoxetine Hydrochloride, Specification: 20mg*28 tablets (Lilly Suzhou Pharmaceutical Company); Mouse Anti-N-Methyl-D-Aspartate Receptor 2B (NMDAR-2b) ELISA Kit, purchased from Jingmei Biotechnology Co., Ltd.; Anti-NMDAR2B Antibody (Catalog No.: ab254356), sourced from Abcam; Hematoxylin-Eosin (HE) Staining Kit (Catalog No.: G1120), acquired from Solarbio Science & Technology Co., Ltd.; HRP-Labeled Goat Anti-Rabbit IgG (Catalog No.: LF102), purchased from Yamei Biomedical Technology Co., Ltd. Neurobehavioral apparatus was obtained from Shanghai Xinruan Information Technology Co., Ltd. All major instruments used in the experiment were provided by the Clinical Research Center of the Affiliated Hospital of Guizhou Medical University. Animal Grouping and Model Establishment Forty-five rats were purchased and subjected to adaptive feeding for 7 days before being randomly assigned to three groups using a random number table method, with n = 15 rats per group: normal control group (CON), depression model group (MDD), and fluoxetine treatment group (MDD + F). The CON group was maintained under standard conditions with 5 rats per cage. The remaining two groups underwent depression model preparation [ 13 – 15 ] through a 28-day Chronic Unpredictable Mild Stress (CUMS) protocol combined with solitary housing. The stressors applied were as follows: (1) food deprivation for 24 hours; (2) water deprivation for 24 hours; (3) exposure to damp bedding (dirty cage) for 24 hours; (4) restraint for 6–8 hours; (5) noise exposure for 24 hours; (6) tilting the cage at 45° for 24 hours; (7) forced swimming in 4°C ice water for 5 minutes; (8) intermittent flashing light stimulation (90Hz) for 12 hours; (9) horizontal shaking of the cage for 5 minutes; (10) reversal of light-dark cycle for 24 hours. Each day, one of these stressors was randomly administered to the rats, with each stressor being used 2–3 times to ensure unpredictability of the stress, and rats were housed individually. Following the 28-day model establishment period, drug intervention commenced, with the CON and MDD groups receiving intragastric administration of saline (10ml/kg), while the MDD + F group received fluoxetine (10mg/kg) via intragastric administration for 14 consecutive days(Fig. 1 A). Neurobehavioral Assessment To accurately and effectively evaluate depressive-like behaviors and cognitive abilities in rats, we employed several neurobehavioral tests. The sucrose preference test was used to assess the rats' ability to experience pleasure and maintain interest. The open field test was conducted to evaluate the rats' locomotor activity, exploratory behavior, and anxiety-like behaviors. The forced swim test was administered to determine the presence of despair-like behaviors in the rats. The Morris water maze test was utilized to evaluate the rats' cognitive abilities, particularly their spatial learning and memory capabilities. The three groups of rats were further randomly divided into three subgroups of 5 rats each. The first subgroup from each group underwent neurobehavioral assessment before modeling, the second subgroup after modeling, and the third subgroup following drug intervention. Sucrose Preference Test [ 16 – 19 ] Depressed rats exhibit a decreased or absent response to rewarding stimuli, corresponding to one of the core symptoms of depression known as "anhedonia." The sucrose preference test comprises two parts: an adaptation training phase and a formal testing phase. During the formal test, the consumption of both sucrose solution and drinking water is measured, and the sucrose preference index is calculated using the following formula: $$\:\mathbf{S}\mathbf{u}\mathbf{c}\mathbf{r}\mathbf{o}\mathbf{s}\mathbf{e}\:\mathbf{P}\mathbf{r}\mathbf{e}\mathbf{f}\mathbf{e}\mathbf{r}\mathbf{e}\mathbf{n}\mathbf{c}\mathbf{e}\:\mathbf{R}\mathbf{a}\mathbf{t}\mathbf{e}\:\left(\mathbf{\%}\right)=\frac{\mathbf{S}\mathbf{u}\mathbf{c}\mathbf{r}\mathbf{o}\mathbf{s}\mathbf{e}\:\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{m}\mathbf{p}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\:}{(\mathbf{S}\mathbf{u}\mathbf{c}\mathbf{r}\mathbf{o}\mathbf{s}\mathbf{e}\:\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{m}\mathbf{p}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\:+\:\mathbf{P}\mathbf{u}\mathbf{r}\mathbf{e}\:\mathbf{W}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{r}\:\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{m}\mathbf{p}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n})\:}\times\:\:100\varvec{\%}$$ Open Field Test The rat is placed in the open field apparatus with its back facing the experimenter and allowed to freely move for 5 minutes. During this period, the software records various indicators such as the total distance traveled horizontally, the number of horizontal crossings, the duration of immobility, the ratio of time spent in the peripheral area to the total time, and the ratio of distance traveled in the central area to the total distance traveled. Forced Swim Test Rats are placed in a circular, transparent glass cylinder and forced to swim for 5 minutes. During this period, the software is used to observe the rats' immobility time, which refers to the period when the rats cease struggling and enter a floating state, with their trunks and limbs remaining motionless. This metric is used to assess the level of despair exhibited by the rats. Morris Water Maze Test This test is divided into two parts. The first part is the Place Navigation Test, which spans four days and involves training rats to find a submerged platform within 60 seconds. The second part is the Probe Trail Test, conducted on the fifth day when the platform is removed. The quadrant where the platform was previously located is defined as the target quadrant. The rat is placed in the pool at the point farthest from the target quadrant, and the software records the rat's movement trajectory for 60 seconds. The observed indicators include: total distance traveled while searching for the platform, time spent in the target quadrant, ratio of time spent in the target quadrant to total time, average swimming speed, number of crossings over the previous platform location, and latency to first locate the area where the platform was previously positioned. These metrics are used to further evaluate the rat's spatial cognition and memory abilities. Molecular Docking Technique [ 20 , 21 ] This technique predicts the binding mode and binding affinity between small molecules and target proteins, thereby evaluating the affinity of drug molecules. The steps involved are: Acquisition and Processing of Drug Small Molecule Receptor Structure: Access the PubChem database, search for "Fluoxetine Hydrochloride", download the SDF format, and convert it to mol2 format. Open AutoDock Vina software, import the mol2 format of the small molecule, add all hydrogens, set it as the ligand, assign electron charges, detect and set torsion angles, and save as a PDBQT format file. Acquisition of Target Protein Data: Utilize the RCSB PDB database to search for information on the NMDAR2B protein and download it in pdb format. Import the file into PyMOL 2.6 software, perform water and ligand removal, and save in pdb format. Then, open AutoDock Vina software, import the processed protein molecule, add all hydrogens to the molecular protein, and finally save as a PDBQT format file. Molecular Docking: Using Fluoxetine Hydrochloride as the ligand and the NMDAR2B protein as the target protein receptor, perform docking in the AutoDock Vina software. Record the docking binding energy and conduct visual analysis on PyMOL 2.6 software. Western Blotting Western Blotting To detect the relative expression level of NMDAR2B protein, rats were euthanized under anesthesia after the final neurobehavioral assessment. The bilateral hippocampi were rapidly dissected on ice, placed in liquid nitrogen, and then transferred to a -80°C freezer for storage. Subsequent procedures included total protein extraction from the tissue, measurement of protein concentration using the BCA method, normalization of protein concentration, and protein denaturation in a metal bath (since it is an ion channel protein, the sample cannot be boiled as this may lead to protein aggregation; instead, denaturation was performed at 37°C for 15 minutes). Following these steps, the Western blotting experiment was conducted, involving gel preparation, sample loading, electrophoresis, membrane transfer, blocking, incubation with primary antibodies (anti-NMDAR2 antibody at 1:2000 and Beta-Actin at 1:5000) overnight at 4°C, incubation with secondary antibody (goat anti-rabbit IgG(H + L) at 1:4000) for 2 hours, exposure using a chemiluminescence imager, and analysis with Image J software to obtain the relative grayscale values of the target protein bands and internal reference bands. The standardized relative expression level of the target protein was then calculated by dividing the grayscale value of the target band by that of the internal reference band. ELISA The ELISA method was employed to detect the concentration of NMDAR2B protein. The procedures for sample collection and preservation were identical to those used in the Western blot experiment. Operations were strictly carried out according to the instructions provided in the ELISA kit manual. The OD values of each well were measured at a wavelength of 450 nm. A standard curve was plotted based on the OD values of the standards, from which a linear regression equation was derived. By substituting the OD values of the samples into this equation, the concentrations of the samples were calculated. Hematoxylin-Eosin Staining [ 22 ] To observe the pathological changes in neurons within the hippocampus, anesthetized rats underwent in vivo brain fixation and perfusion using 4% paraformaldehyde for sample collection. The brains were then processed through fixation, washing, dehydration, xylene clearing, wax immersion, embedding, trimming, and slicing (3-8um) to prepare paraffin-embedded brain tissue sections. The sections were dried and stored at room temperature for short-term preservation. Prepared paraffin sections underwent dewaxing, rehydration, and hydration, followed by nuclear staining with hematoxylin, differentiation, bluing, cytoplasmic staining with eosin, dehydration, and mounting. Images were captured and analyzed under an optical microscope. Nissl Staining [ 23 , 24 ] Observation of Changes in Nissl Bodies in Hippocampal Neurons: Sample collection and paraffin section preparation were performed similarly to the HE staining method. After staining the sections for 4 minutes in Nissl staining solution (primarily containing toluidine blue), differentiation, dehydration, and mounting were performed. Images were captured and analyzed under a light microscope. Golgi Staining [ 25 – 27 ] Observation of Morphological Changes in Dendritic Spines in the Hippocampus: Following euthanasia of the anesthetized rats, samples were collected directly without perfusion. Golgi staining was performed using the FD Neuro Technologies Rapid Golgi Stain Kit, following the instructions provided in the kit. After staining, the samples underwent routine gradient dehydration, xylene clearing, and mounting with neutral resin. Images were captured using an optical microscope, and the density of dendritic spines was analyzed using ImageJ software. Transmission Electron Microscopy Observation of Microstructural Changes in Hippocampal Synapses: Tissue samples were obtained from anesthetized rats and underwent processing steps including sectioning and staining. Finally, transmission electron microscopy was employed to observe the pre-synaptic membrane, post-synaptic membrane, synaptic cleft, and vesicles within the hippocampal region of the brain tissue. Images were captured and analyzed. Statistical Analysis Data processing and analysis were performed using SPSS 26 software. Data were presented as mean ± SEM. Assuming that the data followed a normal distribution and had homogeneity of variance, repeated measures ANOVA was used for neurobehavioral assessments, while one-way ANOVA was applied for other comparisons. For further post hoc pairwise comparisons, LSD/Bonferroni tests were conducted. For data that did not meet the criteria of normal distribution or homogeneity of variance, non-parametric tests with rank transformation were utilized. In correlation analysis, Pearson's linear correlation analysis was applied to continuous variables that followed a normal distribution. A P-value of < 0.05 was considered statistically significant, indicating a difference that was unlikely to have occurred by chance. Results Neurobehavioral assessment of rats in three groups Before modeling: At baseline, there were no statistically significant differences in the neurobehavioral assessment indices across the sugar preference test (F 2,12 =0.11, P > 0.05), forced swimming test (F 2,12 =0.65, P > 0.05), open-field test ( P > 0.05), and Morris water maze test ( P > 0.05) (Fig. 2A-K; Fig. 3 A-H). Post-modeling: (1) Emotional alterations: Compared to the CON group, the MDD and MDD + F groups exhibited decreased sucrose preference ratio (F 2,12 =93.78, P < 0.001) (Fig. 2D). In the open field test, there was a reduction in total horizontal movement distance (F 2,12 =40.90, P < 0.05), decreased horizontal crossing frequency (F 2,12 =18.49, P < 0.01), prolonged immobility duration (F 2,12 =18.49, P < 0.01), increased time spent in the peripheral zone relative to total time (F 2,12 =6.26, P < 0.01), and decreased central zone movement distance relative to total distance (F 2,12 =18.32, P < 0.001) (Fig. 2E-K). In the forced swim test, the MDD and MDD + F groups displayed extended immobility time (F 2,12 =116.99, P < 0.001) (Fig. 2A-C). (2) Cognitive learning and memory capabilities: When compared to the CON group, during the spatial exploration phase of the Morris water maze, the MDD and MDD + F groups demonstrated increased total path length to explore the platform (F 2,12 =17.63, P < 0.001), shortened time spent in the target quadrant (F 2,12 =191.53, P < 0.001), reduced target quadrant time relative to total time (F 2,12 =191.53, P < 0.001), decreased average swimming speed (F 2,12 =26.14, P < 0.001), increased platform crossings (F 2,12 =8.26, P < 0.05), and prolonged latency to first find the target platform (F 2,12 =22.29, P 0.05). Post-Fluoxetine Intervention: (1) Emotional Aspects: Compared to the MDD group, the CON and MDD + F groups showed significant increases in sucrose preference ratio (F 2,12 =70.57, P < 0.001) (Fig. 2D), total horizontal movement distance (F 2,12 =19.88, P < 0.001), horizontal crossing frequency (F 2,12 =113.00, P < 0.001), shortened immobility duration (F 2,12 =54.06, P < 0.001), decreased time spent in the peripheral zone relative to total time (F 2,12 =13.81, P < 0.01), and altered (though still decreased) central zone movement distance relative to total distance (F 2,12 =27.68, P < 0.001, indicating a normalization trend towards CON levels) (Fig. 2E-K). Additionally, there was a reduction in immobility time during the forced swim test (F 2,12 =93.77, P < 0.001) (Fig. 2A-C). (2) Cognitive Abilities: In comparison to the MDD group, during the Morris water maze spatial exploration task, the CON and MDD + F groups exhibited increased total path length to explore the platform (F 2,12 =14.63, P < 0.01), prolonged time spent in the target quadrant (F 2,12 =15.40, P < 0.01), increased target quadrant time relative to total time (F 2,12 =15.40, P < 0.01), faster average swimming speed (F 2,12 =35.11, P < 0.001), more platform crossings (F 2,12 =15.72, P < 0.01), and shortened latency to first find the target platform (F 2,12 =26.85, P 0.05) (Fig. 3 A-H). Figure 2 Results of neurobehavioral statistical analysis. (A, B) Schematic diagram, trajectory plot, and heatmap of the forced swim test; (C) Statistical results of immobility duration in the forced swim test; (D) Statistical results of sucrose preference ratio. (E, F) Schematic diagram, trajectory plot, and heatmap of the open field test; (G-K) Statistical results of immobility time, horizontal crossing frequency, total horizontal movement distance, central zone movement distance relative to total distance, and peripheral zone time relative to total time in the open field test. (Compared with the CON group, a P <0.05; compared with the MDD group, b P <0.05, n = 5 per group, all data are presented as mean ± SEM.) Molecular Docking Results of Fluoxetine Hydrochloride with Target Protein NMDAR2B Molecular docking was performed using AutoDock Vina software, revealing a binding energy of -6.9kcal·mol-1, which is less than − 5 kcal·mol-1, indicating a robust binding capacity and high affinity between fluoxetine hydrochloride and NMDAR2B (in molecular docking, a binding energy less than − 5 kcal·mol-1 signifies good affinity and binding activity between the ligand and receptor [ 28 ]). Visual inspection of the 2D and 3D diagrams demonstrates that NMDAR2B primarily binds to fluoxetine hydrochloride through hydrogen bonding with HIS-359 and ASP-348, hydrophobic interactions with HIS-359 and ARG-347, and electrostatic interactions with LYS-361. Additionally, van der Waals forces exist between ASP-286, ASP283, TYR-282, LEU-349, GLN-357, and PRO-360. These chemical bonds are spatially arranged in a rational manner, presenting a tight and stable binding state with excellent geometric compatibility. Consequently, the binding of fluoxetine hydrochloride to NMDAR2B protein may potentially exert corresponding pharmacological effects to a certain extent (Fig. 3 A-B). Expression and Concentration of NMDAR2B Protein in the Hippocampal Region of Brain Tissue Western blot analysis revealed that the relative expression levels of NMDAR2B protein were decreased in both MDD and MDD + F groups compared to the CON group (F 2,12 =17.48, P < 0.05). Furthermore, within the MDD + F group, the relative expression of NMDAR2B protein was significantly elevated compared to the MDD group ( P < 0.05) (Fig. 4 A). ELISA assay results indicated a marked reduction in the concentrations of NMDAR2B subunit in both MDD and MDD + F groups, when compared to the CON group (F 2,12 =97.82, P < 0.05). Notably, the protein concentration in the MDD + F group was significantly higher than that in the MDD group ( P < 0.001) (Fig. 4 B). Pathological changes in the hippocampal region HE staining results Under light microscopy, neurons in the CA1, CA3, and DG regions of the hippocampus in the CON group rats were normally distributed, with regular arrangement, full morphology, intact structure, evenly distributed staining, and centrally located and clear nucleoli. In the MDD group, severe pathological damage was observed in the three subregions of the hippocampus, with disordered arrangement of neurons, decreased number, varying sizes and shapes, edema in some cells, uneven cytoplasmic staining, and deeply stained nucleoli. Compared with the MDD group, the MDD + F group showed improved and repaired nerve injury, with increased cell numbers, intact cell membranes, more uniform cytoplasm, clear nuclei, and visible nucleoli (Fig. 6 A-D). Nissl Staining Results Under light microscopy, the neuronal cells in the CA1 region of the hippocampus in the CON group exhibited intact structures, tightly arranged in clear bands, with abundant dark blue granular and patchy structures within the cytoplasm, known as Nissl bodies. In comparison to the CON group, the MDD group showed a significant reduction in neuronal cells, with sparse arrangement, irregular morphology, enlarged intercellular spaces, decreased numbers of Nissl bodies within the cytoplasm, lighter staining, and partial obscuration of Nissl bodies. Compared to the MDD group, the MDD + F group demonstrated an increase in the number of Nissl bodies and neuronal cells, with notable improvement in pathological damage (Fig. 7 A-D). Golgi Staining Results The CON group exhibited high dendrite density, numerous dendrites, and regularly arranged, tight dendrite patterns. In contrast, the MDD group displayed decreased dendrite density, sparsity, and partial dendrite atrophy. Following fluoxetine intervention, the number of dendrites increased, and their arrangement became more compact. Density analysis of individual dendritic spines revealed that compared to the CON group, the density of dendritic spines in hippocampal neurons was reduced in both the MDD and MDD + F groups (F 2,12 =7.95, P < 0.05). Additionally, compared to the MDD group, the MDD + F group showed an increase in dendritic spine density ( P < 0.05) (Fig. 8 A-C). Transmission Electron Microscopy Results The results demonstrated that in the CON group, the synaptic corpuscles had intact membranes, uniform matrix, abundant neurofilaments and microtubules, structurally intact mitochondria with homogeneous intramembrane matrix, and well-preserved axonal terminal membranes featuring uniform matrix, concentrated presynaptic membrane proteins, distinct dense zones, and structurally complete components. Additionally, the number of synaptic vesicles was abundant, and the synaptic cleft was clearly discernible. In contrast, rats from the MDD group exhibited severe synaptic damage characterized by reduced synaptic counts, notably compromised synaptic corpuscles with extensive membrane disruptions and disintegration, markedly decreased cytoplasmic electron density, diminished neurofilaments and microtubules, overtly swollen mitochondria accompanied by sparse and dissolved local matrix, reduced cristae, and vacuolation. Furthermore, the axonal terminal membranes were obscure with dissolved matrix and indistinct presynaptic membrane structures. While synaptic vesicles were abundant, most were damaged or disintegrated. Dendritic spines exhibited sparse matrix and localized membrane disruptions, and the synaptic cleft was obscure. Following fluoxetine intervention, a degree of recovery from the damage observed in the MDD group was noted, with mildly edematous mitochondria, abundant synaptic vesicles of varying sizes but structurally intact, and a reasonably discernible synaptic cleft (Fig. 8 D-E). Correlation Analysis between Pathological Damage, NMDAR2B Subunit Expression, and Cognition-Related Behavioral Indicators Through correlation analysis, it was found that there was a significant correlation between the density of dendritic spines in the hippocampus, the relative expression of the NMDAR2B subunit, and cognition-related behavioral indicators in rats. The expression of NMDAR2B subunit showed a significant positive correlation with the total distance traveled in the exploration platform (R = 0.580, P < 0.05), the time spent in the target quadrant (R = 0.676, P < 0.01), the ratio of time spent in the target quadrant to total time (R = 0.557, P < 0.05), the average swimming speed (R = 0.678, P < 0.01), and the number of platform crossings (R = 0.568, P < 0.05). Conversely, it exhibited a significant negative correlation with the latency to first find the target platform (R=-0.552, P < 0.05) (Fig. 9 A). The dendritic spine density in the hippocampus demonstrated a significant positive correlation with the time spent in the target quadrant (R = 0.603, P < 0.05), the ratio of time spent in the target quadrant to total time (R = 0.529, P < 0.05), and the number of platform crossings (R = 0.524, P < 0.05). Conversely, it showed a significant negative correlation with the latency to first find the target platform (R=-0.621, P 0.05) or the average swimming speed (R = 0.434, P > 0.05) (Fig. 9 C). The relative expression level of the NMDAR2B subunit in the hippocampus displayed a significant positive correlation with dendritic spine density (R = 0.542, P < 0.05) (Fig. 9 B). Discussion The pathological mechanisms underlying depression are intricate, with clinical manifestations encompassing emotional disturbances, somatization symptoms, and cognitive decline across multiple dimensions[ 1 , 29 , 30 ]. Among these, cognitive dysfunction is a prevalent comorbid symptom in patients with depression. The chronic unpredictable mild stress (CUMS) model is considered the most suitable animal model for simulating depression induced by long-term exposure to stress and frustration in humans [ 31 ]. The solitary housing paradigm simulates social isolation, further enhancing the similarity between the CUMS model and the complex etiology of human depression [ 32 ].The hippocampus, a crucial component of the limbic system, is anatomically organized into three layers: the molecular layer, the pyramidal cell layer, and the polymorphic layer. Moreover, it is subdivided into four regions in the transverse plane: Cornu Ammon 1 to 4 (CA1-CA4). From an anatomical and functional perspective, the CA1, CA3, and dentate gyrus (DG) regions are particularly vulnerable to various adverse stimuli[ 33 ], playing pivotal roles in emotional regulation, behavioral inhibition, and the execution of advanced cognitive functions such as learning and memory [ 34 ]. Dysfunction in these regions is closely associated with cognitive impairments in depression [ 34 , 35 ]. N-Methyl-D-aspartate (NMDA) ionotropic glutamate receptors (NMDARs), a significant class of ionotropic glutamate receptors, have a subtype, NMDAR2B, which is central to neural development, synaptogenesis, synaptic plasticity modulation, neural network homeostasis, and cognitive function. Abnormalities in NMDAR-mediated signaling, particularly those involving NMDAR2B dysfunction, have been implicated in numerous neurodegenerative diseases and mental health disorders, highlighting their extensive and profound influence on maintaining normal neural function [ 36 ]. Therefore, a profound investigation into the mechanisms of NMDAR2B in cognitive dysfunction associated with depression is crucial for elucidating the pathophysiological processes of depression and developing novel therapeutic strategies. In this study, after 4 weeks of CUMS modeling, rats exhibited depressive-like behaviors and cognitive dysfunction, aligning with the criteria for a cognitive dysfunction model of depression. Upon successful modeling, a decrease in the expression level and concentration of the NMDAR2B subunit was observed, accompanied by pathological damage and reduced neural plasticity and complexity in the three subregions of the hippocampus. The high absolute value of the molecular docking binding energy between fluoxetine hydrochloride and NMDAR2B indicates that fluoxetine can bind to the NMDAR2B subunit to exert its pharmacological effects. Following fluoxetine hydrochloride intervention, neurobehavioral results revealed improvements in depressive-like behaviors and varying degrees of recovery of cognitive function in the depression model rats. Additionally, there was an increase in the expression level and concentration of NMDAR2B protein, accompanied by varying degrees of repair of pathological damage and neural plasticity. Correlation analysis revealed that more severe pathological damage and lower expression of NMDAR2B protein were associated with more impaired cognitive function, while decreased dendritic spine density correlated with lower expression of NMDAR2B protein. In summary, fluoxetine, a selective serotonin reuptake inhibitor (SSRI), exhibits significant affinity for the NMDAR2B subunit. Fluoxetine improves cognitive symptoms in depression model rats by regulating the expression of the NMDAR2B subunit, thereby exerting neuroprotective effects, aiding in the repair of pathological damage in the hippocampus, and promoting neural plasticity. This provides new theoretical and research insights for the treatment of cognitive dysfunction in depression in clinical settings. The present study possesses certain limitations. Firstly, the experimental subjects were limited to adult male rats, thus not exploring potential gender differences in the recovery of cognitive function. Furthermore, the selection of antidepressants in this study was relatively narrow, with the classic SSRI antidepressant fluoxetine being the sole agent used. Future research should further observe and investigate the impact of other first-line antidepressants on cognitive dysfunction in depression, in order to more comprehensively reveal the interventional effects and underlying mechanisms of antidepressants on cognitive dysfunction associated with depression. Conclusions Rats with depression-related cognitive dysfunction exhibit neuronal damage in the hippocampus, reduced neural plasticity and complexity, and decreased expression of the NMDAR2B subunit. Fluoxetine, with its strong affinity for the NMDAR2B subunit, exerts neuroprotective effects by regulating the expression of NMDAR2B, thereby improving cognitive function in depressed rats. This provides new theoretical insights and approaches for the clinical treatment of cognitive impairment in depression. Declarations Author contributions LL : Contributed to the conception and design of the study, data curation, formal analysis, funding acquisition, investigation, methodology development, project administration, resource allocation, software application, research supervision, result validation, data visualization, drafting the original manuscript, and subsequent review and editing. PL, YH, QS: Participated in data curation, formal analysis, funding acquisition, methodology development, project administration, research supervision, result validation, as well as the review and editing of the manuscript. HL, YW : Were responsible for project administration, research supervision, and the review and editing of the manuscript. YW: Contributed to funding acquisition, resource allocation, and the review and editing of the manuscript. All authors have reviewed the final content of this manuscript and agree to its publication. Funding This work was supported by the National Natural Science Foundation of China, No: 8226140969, Guizhou Provincial Science and Technology Department Qiankehe Platform Talent [2018]5802, [2016]5679. Data availability No datasets were generated or analysed during the current study. Ethics statement The animal study was approved by Guizhou Medical University Attitude of the Animal Care Welfare Committee (Approval Number: 2305201). The study was conducted in accordance with the local legislation and institutional requirements. Competing interests The authors declare no competing interests. References Chinese Society of Psychiatry Chinese Academy of Depressive Disorders, Li LJ, Wang G. Expert consensus on assessment and intervention of cognitive symptoms in major depressive disorder. Chinese Journal of Psychiatry. 2020;53:369-76. doi:10.3760/cma.j.cn113661-20200410-00177. Shilyansky C, Williams LM, Gyurak A, Harris A, Usherwood T, Etkin A. Effect of antidepressant treatment on cognitive impairments associated with depression: a randomised longitudinal study. Lancet Psychiatry. 2016;3:425-35. doi:10.1016/S2215-0366(16)00012-2. Wise T, Radua J, Via E, Cardoner N, Abe O, Adams TM, Amico F, Cheng Y, Cole JH, de Azevedo Marques Périco C, Dickstein DP, Farrow T, Frodl T, Wagner G, Gotlib IH, Gruber O, Ham BJ, Job DE, Kempton MJ, Kim MJ, Koolschijn P, Malhi GS, Mataix-Cols D, McIntosh AM, Nugent AC, O'Brien JT, Pezzoli S, Phillips ML, Sachdev PS, Salvadore G, Selvaraj S, Stanfield AC, Thomas AJ, van Tol MJ, van der Wee N, Veltman DJ, Young AH, Fu CH, Cleare AJ, Arnone D. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis. Mol Psychiatry. 2017;22:1455-63. doi:10.1038/mp.2016.72. Atique-Ur-Rehman H, Neill JC. Cognitive dysfunction in major depression: From assessment to novel therapies. Pharmacol Ther. 2019;202:53-71. doi:10.1016/j.pharmthera.2019.05.013. Rosenblat JD, Kakar R, McIntyre RS. The Cognitive Effects of Antidepressants in Major Depressive Disorder: A Systematic Review and Meta-Analysis of Randomized Clinical Trials. Int J Neuropsychopharmacol. 2015;19:pyv082 [pii]. doi:10.1093/ijnp/pyv082. Baune BT, Renger L. Pharmacological and non-pharmacological interventions to improve cognitive dysfunction and functional ability in clinical depression--a systematic review. Psychiatry Res. 2014;219:25-50. doi:10.1016/j.psychres.2014.05.013. Sheline YI, Liston C, McEwen BS. Parsing the Hippocampus in Depression: Chronic Stress, Hippocampal Volume, and Major Depressive Disorder. Biol Psychiatry. 2019;85:436-8. doi:10.1016/j.biopsych.2019.01.011. LeDoux JE. Emotion circuits in the brain. Annu Rev Neurosci. 2000;23:155-84. doi:10.1146/annurev.neuro.23.1.155. Li QQ, Chen J, Hu P, Jia M, Sun JH, Feng HY, Qiao FC, Zang YY, Shi YY, Chen G, Sheng N, Xu Y, Yang JJ, Xu Z, Shi YS. Enhancing GluN2A-type NMDA receptors impairs long-term synaptic plasticity and learning and memory. Mol Psychiatry. 2022;27:3468-78. doi:10.1038/s41380-022-01579-7. Wang X, Xie J, Tan L, Lu Y, Shen N, Li J, Hu H, Li H, Li X, Cheng L. N6-methyladenosine-modified circRIMS2 mediates synaptic and memory impairments by activating GluN2B ubiquitination in Alzheimer's disease. Transl Neurodegener. 2023;12:53. doi:10.1186/s40035-023-00386-6. Wang C, Zhu MH, Sun N, Shen W, Jiang N, Zhao QS, Zhang YX, Huang Y, Zhou WX. Isorhynchophylline ameliorates stress-induced emotional disorder and cognitive impairment with modulation of NMDA receptors. Front Neurosci. 2022;16:1071068. doi:10.3389/fnins.2022.1071068. Wu HJ, Wu WN, Fan H, Liu LE, Zhan JQ, Li YH, Chen CN, Jiang SZ, Xiong JW, Yu ZM, Wei B, Wang W, Yang YJ. Life extension factor klotho regulates behavioral responses to stress via modulation of GluN2B function in the nucleus accumbens. Neuropsychopharmacology. 2022;47:1710-20. doi:10.1038/s41386-022-01323-3. Willner P. Animal models as simulations of depression. Trends Pharmacol Sci. 1991;12:131-6. doi:10.1016/0165-6147(91)90529-2. Duman CH. Models of depression. Vitam Horm. 2010;82:1-21. doi:10.1016/S0083-6729(10)82001-1. Fernando AB, Robbins TW. Animal models of neuropsychiatric disorders. Annu Rev Clin Psychol. 2011;7:39-61. doi:10.1146/annurev-clinpsy-032210-104454. 中华医学会精神医学分会抑郁障碍研究协作组. 抑郁症认知症状评估与干预专家共识. 中华精神科杂志. 2020;53:369-76. doi:10.3760/cma.j.cn113661-20200410-00177. Liu MY, Yin CY, Zhu LJ, Zhu XH, Xu C, Luo CX, Chen H, Zhu DY, Zhou QG. Sucrose preference test for measurement of stress-induced anhedonia in mice. Nat Protoc. 2018;13:1686-98. doi:10.1038/s41596-018-0011-z. Schalla MA, Kühne SG, Friedrich T, Hanel V, Kobelt P, Goebel-Stengel M, Rose M, Stengel A. Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System. J Vis Exp. 2020. doi:10.3791/60953. Huang HJ, Zhu XC, Han QQ, Wang YL, Yue N, Wang J, Yu R, Li B, Wu GC, Liu Q, Yu J. Ghrelin alleviates anxiety- and depression-like behaviors induced by chronic unpredictable mild stress in rodents. Behav Brain Res. 2017;326:33-43. doi:10.1016/j.bbr.2017.02.040. Paggi JM, Pandit A, Dror RO. The Art and Science of Molecular Docking. Annu Rev Biochem. 2024;93:389-410. doi:10.1146/annurev-biochem-030222-120000. Burley SK, Bhikadiya C, Bi C, Bittrich S, Chen L, Crichlow GV, Christie CH, Dalenberg K, Di Costanzo L, Duarte JM, Dutta S, Feng Z, Ganesan S, Goodsell DS, Ghosh S, Green RK, Guranović V, Guzenko D, Hudson BP, Lawson CL, Liang Y, Lowe R, Namkoong H, Peisach E, Persikova I, Randle C, Rose A, Rose Y, Sali A, Segura J, Sekharan M, Shao C, Tao YP, Voigt M, Westbrook JD, Young JY, Zardecki C, Zhuravleva M. RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. Nucleic Acids Res. 2021;49:D437-437D451. doi:10.1093/nar/gkaa1038. Yang JZ, Zhang KK, Shen HW, Liu Y, Li XW, Chen LJ, Liu JL, Li JH, Zhao D, Wang Q, Zhou CS. Sigma-1 receptor knockout disturbs gut microbiota, remodels serum metabolome, and exacerbates isoprenaline-induced heart failure. Front Microbiol. 2023;14:1255971. doi:10.3389/fmicb.2023.1255971. Carriel V, Campos A, Alaminos M, Raimondo S, Geuna S. Staining Methods for Normal and Regenerative Myelin in the Nervous System. Methods Mol Biol. 2017;1560:207-18. doi:10.1007/978-1-4939-6788-9_15. Krutsay M. [Nissl staining with cresyl violet]. Z Med Labortech. 1970;11:75-6 Zhong F, Liu L, Wei JL, Dai RP. Step by Step Golgi-Cox Staining for Cryosection. Front Neuroanat. 2019;13:62. doi:10.3389/fnana.2019.00062. Zaqout S, Kaindl AM. Golgi-Cox Staining Step by Step. Front Neuroanat. 2016;10:38. doi:10.3389/fnana.2016.00038. Narayanan SN, Bairy LK, Srinivasamurthy SK. Determining factors for optimal neuronal and glial Golgi-Cox staining. Histochem Cell Biol. 2020;154:431-48. doi:10.1007/s00418-020-01891-9. Chen Y, Zhang F, Sun J, Zhang L. Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment. J Transl Med. 2023;21:920. doi:10.1186/s12967-023-04755-7. Malhi GS, Mann JJ. Depression. Lancet. 2018;392:2299-312. doi:10.1016/S0140-6736(18)31948-2. Zuckerman H, Pan Z, Park C, Brietzke E, Musial N, Shariq AS, Iacobucci M, Yim SJ, Lui L, Rong C, McIntyre RS. Recognition and Treatment of Cognitive Dysfunction in Major Depressive Disorder. Front Psychiatry. 2018;9:655. doi:10.3389/fpsyt.2018.00655. Hao Y, Ge H, Sun M, Gao Y. Selecting an Appropriate Animal Model of Depression. Int J Mol Sci. 2019;20:4827. doi:10.3390/ijms20194827. Willner P. The chronic mild stress (CMS) model of depression: History, evaluation and usage. Neurobiol Stress. 2017;6:78-93. doi:10.1016/j.ynstr.2016.08.002. Li Y, Luo Y, Tang J, Liang X, Wang J, Xiao Q, Zhu P, Xiao K, Jiang L, Dou X, Huang C, Xie Y, Tang Y. The positive effects of running exercise on hippocampal astrocytes in a rat model of depression. Transl Psychiatry. 2021;11:83. doi:10.1038/s41398-021-01216-x. Nieh EH, Schottdorf M, Freeman NW, Low RJ, Lewallen S, Koay SA, Pinto L, Gauthier JL, Brody CD, Tank DW. Geometry of abstract learned knowledge in the hippocampus. Nature. 2021;595:80-4. doi:10.1038/s41586-021-03652-7. Park SA, Miller DS, Nili H, Ranganath C, Boorman ED. Map Making: Constructing, Combining, and Inferring on Abstract Cognitive Maps. Neuron. 2020;107:1226-38.e8. doi:10.1016/j.neuron.2020.06.030. Dupuis JP, Nicole O, Groc L. NMDA receptor functions in health and disease: Old actor, new dimensions. Neuron. 2023;111:2312-28. doi:10.1016/j.neuron.2023.05.002. Additional Declarations No competing interests reported. Supplementary Files fulluncroppedGelsandBlotsimages.zip Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5371457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":378330127,"identity":"1ac51c46-5a05-462a-83be-467071397b74","order_by":0,"name":"Longfei Liu","email":"","orcid":"","institution":"College of Clinical Medicine, Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Longfei","middleName":"","lastName":"Liu","suffix":""},{"id":378330128,"identity":"df802502-4d03-4e22-a28f-a6932e129e75","order_by":1,"name":"Peifan Li","email":"","orcid":"","institution":"Department of Psychiatry, Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Peifan","middleName":"","lastName":"Li","suffix":""},{"id":378330129,"identity":"2d4f676f-f7db-41c5-9271-638e0ab12197","order_by":2,"name":"Yongxue Hu","email":"","orcid":"","institution":"Department of Psychiatry, Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yongxue","middleName":"","lastName":"Hu","suffix":""},{"id":378330130,"identity":"90d92a8c-a4ef-4232-a393-b9d5037ee5b3","order_by":3,"name":"Qing Shan","email":"","orcid":"","institution":"College of Clinical Medicine, Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Shan","suffix":""},{"id":378330131,"identity":"94c09dde-354b-4f3a-b4de-f50afd2c0844","order_by":4,"name":"Hongping Li","email":"","orcid":"","institution":"College of Clinical Medicine, Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongping","middleName":"","lastName":"Li","suffix":""},{"id":378330132,"identity":"75c0c9fe-9628-44ad-8cf1-fa266d088e06","order_by":5,"name":"Yuhan Wei","email":"","orcid":"","institution":"College of Clinical Medicine, Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Wei","suffix":""},{"id":378330133,"identity":"ae530336-3315-4a11-96d7-0ea47692028d","order_by":6,"name":"Yiming Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBAC+/sHEh8k/GCrtz/eQKyeGwyPDT728CUwnDlAtBbGZ4Iz2OQSGG4kEKmDcXZzGjMPj1ke48zHG28w1NhEE9TCLHMs7TGPRVoxs3RasQXDsbTcBkJa2Bhy0o15eI4xtknnmEkwNhwmrIWHIf+bNA/bf8YeyTNEapGQSEiTnMHGljhDgodILQY8B5KBgcxmbMAD9EsCMX4xYG8AR6WcAfvhjTc+1NgQ1oKiXSKBFOUQLaTqGAWjYBSMgpEBAKGOPtS4v0KDAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Psychiatry, Affiliated Hospital of Guizhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-11-01 07:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5371457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5371457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69638017,"identity":"2ab6878a-38a2-45de-aa9a-a6adebdc8065","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":665929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Flowchart of the experimental design.\u003c/p\u003e","description":"","filename":"Fig.1Experimentalflowchart.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/0385f1943ff95f6a1b9132e4.png"},{"id":69638016,"identity":"e02250c6-7f0c-4927-bbcd-afeaad0c55fc","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3895747,"visible":true,"origin":"","legend":"\u003cp\u003eResults of neurobehavioral statistical analysis. \u003cstrong\u003e(A, B)\u003c/strong\u003e Schematic diagram, trajectory plot, and heatmap of the forced swim test; \u003cstrong\u003e(C)\u003c/strong\u003e Statistical results of immobility duration in the forced swim test; \u003cstrong\u003e(D)\u003c/strong\u003e Statistical results of sucrose preference ratio.\u003cstrong\u003e (E, F)\u003c/strong\u003e Schematic diagram, trajectory plot, and heatmap of the open field test;\u003cstrong\u003e (G-K)\u003c/strong\u003e Statistical results of immobility time, horizontal crossing frequency, total horizontal movement distance, central zone movement distance relative to total distance, and peripheral zone time relative to total time in the open field test. (Compared with the CON group,\u003csup\u003e a\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; compared with the MDD group, \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, \u003cem\u003en\u003c/em\u003e=5 per group, all data are presented as mean±SEM.)\u003c/p\u003e","description":"","filename":"Fig.2Resultsofneurobehavioralstatisticalanalysis.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/a889cd1fe49627b830524051.png"},{"id":69639148,"identity":"dc5e5494-ce12-43ab-b67c-bf7447f8bf6b","added_by":"auto","created_at":"2024-11-22 13:40:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2989449,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical analysis results of the Morris water maze test.\u003cstrong\u003e (A, B)\u003c/strong\u003e Schematic diagram, trajectory plot, and heatmap of the Morris water maze test; \u003cstrong\u003e(C-H)\u003c/strong\u003e Statistical results of the number of platform crossings, average swimming speed, latency to first find the target platform, total path length explored, ratio of target quadrant time to total time, and target quadrant retention time during the spatial exploration phase of the Morris water maze test. (Compared with the CON group,\u003csup\u003e a\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; compared with the MDD group, \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05,\u003cem\u003e n\u003c/em\u003e=5 per group, all data are presented as mean±SEM.)\u003c/p\u003e","description":"","filename":"Fig.3StatisticalanalysisresultsoftheMorriswatermazetest.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/198375c2d6c303fbf58ebc95.png"},{"id":69638014,"identity":"7a67e491-0d20-4546-afc2-f93f8f9cbb31","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5568643,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular Docking Results. \u003cstrong\u003e(A-B)\u003c/strong\u003e Represent the 3D visualization simulation and 2D flat diagram of the molecular docking, respectively.\u003c/p\u003e","description":"","filename":"Fig.4MolecularDockingResults.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/8970858d96e41ab10dcafdb0.png"},{"id":69638013,"identity":"060ac8c8-26f7-4a2d-a6b9-2067b1d9d845","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":295945,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in NMDAR2B Protein Expression and Concentration in Rats Across Different Groups. \u003cstrong\u003e(A,B)\u003c/strong\u003e Representative bands from Western blot analysis, relative expression levels, and concentrations of NMDAR2B protein are shown respectively. (Compared with the CON group,\u003csup\u003e a\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; compared with the MDD group, \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05,\u003cem\u003e n\u003c/em\u003e=3 per group, all data are presented as mean±SEM.)\u003c/p\u003e","description":"","filename":"Fig.5ChangesinNMDAR2BProteinExpressionandConcentrationinRatsAcrossDifferentGroups..png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/a8632be1c4c461323f838bc4.png"},{"id":69638021,"identity":"c777e613-51f3-4f20-abc9-b5e4bb40d343","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":22868057,"visible":true,"origin":"","legend":"\u003cp\u003eHE staining results. \u003cstrong\u003e(A)\u003c/strong\u003e Panoramic view of HE staining in the hippocampal region.\u003cstrong\u003e(B-D)\u003c/strong\u003eRepresentative images of local HE staining (X100, 100μm) and magnification (X400, 20μm) in the CA1, CA3, and DG regions of the hippocampus of rats in each group. Arrows: Cyan: Normal neuronal cells; Red: Darkly stained neuronal nuclei; Yellow: Neuronal cell edema; Black: Loose and lightly stained neuronal cytoplasm; Dashed rectangles indicate locally magnified areas (\u003cem\u003en\u003c/em\u003e=3 per group).\u003c/p\u003e","description":"","filename":"Fig.6HEstainingresults.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/ddfc909e6a972d9781a44d63.png"},{"id":69639147,"identity":"0eb8bcec-a5e2-4239-9ecb-b4fd3a4fe33f","added_by":"auto","created_at":"2024-11-22 13:40:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4193315,"visible":true,"origin":"","legend":"\u003cp\u003eNissl Staining Results. \u003cstrong\u003e(A)\u003c/strong\u003e Panoramic view of Nissl staining in the hippocampal region. \u003cstrong\u003e(B-D)\u003c/strong\u003e Representative images of local Nissl staining (X100, 100μm) and magnification (X400, 20μm) in the CA1, CA3, and DG regions of the hippocampus from rats in each experimental group. Arrows indicate: Green: Abundant Nissl bodies within neurons; Red: Decreased Nissl bodies within neurons. Dashed rectangular frames designate locally magnified areas(\u003cem\u003en\u003c/em\u003e=3 per group).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/acaf73c5a24b274b0d126485.png"},{"id":69639149,"identity":"b4f3472f-c0c3-471d-8633-b32b8382b53d","added_by":"auto","created_at":"2024-11-22 13:40:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":25339178,"visible":true,"origin":"","legend":"\u003cp\u003eGolgi Staining and Transmission Electron Microscopy Results. \u003cstrong\u003e(A) \u003c/strong\u003eRepresentative qualitative analysis images of Golgi staining in the CA1, CA3, and DG regions of the hippocampus in rats from each experimental group (X100, 100μm); Arrows: Green indicates high density and abundance of dendrites; Red indicates decreased and sparse dendrite density in the region.\u003cstrong\u003e (B) \u003c/strong\u003ePanoramic view of Golgi staining in the hippocampal region.\u003cstrong\u003e (C) \u003c/strong\u003eRepresentative images and quantitative analysis results of dendritic spine density from Golgi staining. \u003cstrong\u003e(D, E)\u003c/strong\u003e Microstructural images of hippocampal synapses in rats from each group under transmission electron microscopy (TEM) (X15000, 2μm) and representative local magnifications (X40000, 500nm). Arrows: Red: Local damage and disintegration of membrane structures; Blue: Sparse matrix with decreased electron density; Purple: Decreased and damaged synaptic vesicles; Yellow: Mitochondrial edema and vacuoles. SJ: Synaptic Junction; M: Mitochondrion; T: Axon Terminal; PrM: Presynaptic Membrane; PoM: Postsynaptic Membrane; SV: Synaptic Vesicle; DS: Dendritic Spine; SC: Synaptic Cleft; MS: Myelin Sheath. (Compared with the CON group,\u003csup\u003e a\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; compared with the MDD group, \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05,\u003cem\u003e n\u003c/em\u003e=3 per group, all data are presented as mean±SEM.)\u003c/p\u003e","description":"","filename":"Fig.8GolgiStainingandTransmissionElectronMicroscopyResults..png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/07d0e2c5b0d73cae705cc2c0.png"},{"id":69638020,"identity":"7889d4da-87ed-4a8a-9c17-ca3308dd53f2","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":664925,"visible":true,"origin":"","legend":"\u003cp\u003eResults of correlation analysis. \u003cstrong\u003e(A)\u003c/strong\u003e Bar graph showing the correlation analysis between the relative expression of NMDAR2B protein and cognition-related behavioral indicators. \u003cstrong\u003e(C) \u003c/strong\u003eBar graph illustrating the correlation analysis between dendritic spine density and cognition-related indicators.\u003cstrong\u003e(B)\u003c/strong\u003e Scatter plot and heatmap depicting the correlation analysis between the relative expression of NMDAR2B protein and dendritic spine density.\u003c/p\u003e","description":"","filename":"Fig9Resultsofcorrelationanalysis.png","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/00db05cf9f0b6152553a2c36.png"},{"id":73100064,"identity":"f1c4e9e3-c768-42d1-8ca7-769a6d013629","added_by":"auto","created_at":"2025-01-06 17:32:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":65592264,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/c93cbfc0-bff0-4ceb-ad10-7f6c9665454c.pdf"},{"id":69638019,"identity":"044ca174-52b5-4b5d-b94f-186edc8fa364","added_by":"auto","created_at":"2024-11-22 13:32:51","extension":"zip","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":1437140,"visible":true,"origin":"","legend":"","description":"","filename":"fulluncroppedGelsandBlotsimages.zip","url":"https://assets-eu.researchsquare.com/files/rs-5371457/v1/2a417cf4c3999a4e2c9f6113.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of NMDAR2B-mediated Hippocampal Neuron Protection on Cognitive Function in Rats with Depression","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCognitive impairment is one of the core symptoms of major depressive disorder (MDD), manifesting across different stages of the illness and significantly impacting the prognosis and functional recovery of patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A major obstacle to the full recovery of MDD patients lies in the improvement of cognitive dysfunction symptoms [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 2016, the US Food and Drug Administration (FDA) Drug Evaluation and Research Expert Working Group recommended targeting cognitive symptoms as an intervention point in the treatment of MDD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Currently, there is no specific drug for treating cognitive dysfunction in MDD. Studies have shown that existing selective serotonin reuptake inhibitors (SSRIs) can improve cognitive symptoms in depressed patients [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but the underlying mechanisms remain unclear and require further investigation. Decreased cortical volume in brain regions associated with cognitive function, such as the hippocampus and prefrontal cortex, is a characteristic brain structural feature in MDD patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Among these, the hippocampus, an essential component of the limbic system, is closely associated with learning, memory, emotion, and visceral regulation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. NMDA receptor subunit 2B (NMDAR2B) is a subtype of the NMDA (N-methyl-D-aspartate) receptor family within the ionotropic glutamate receptors. NMDAR2B plays a crucial role in neurons and is a key molecule involved in physiological processes such as learning, memory, and pain perception within the central nervous system [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Some studies have reported abnormally elevated NMDAR2B levels in depressed mice, and modulating NMDA receptors can exert anxiolytic and antidepressant effects [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, other studies have yielded contrasting results, with chronic stress leading to a significant decrease in NMDAR2B protein levels, and increasing NMDAR2B subunit levels able to regulate depressive-like behaviors [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, a rat model of depression was established using chronic unpredictable mild stress (CUMS) combined with solitary rearing, and the rats were intervened with the classic antidepressant fluoxetine through intragastric administration. Neurobehavioral manifestations, histopathological changes in the hippocampus, and alterations in NMDAR2B protein were observed and analyzed for their correlations. The aim was to explore the potential mechanisms underlying depressive cognitive dysfunction, providing a more solid theoretical foundation and insights for clinical treatment.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eForty-five six-week-old, Specific Pathogen Free (SPF), adult male, healthy Sprague Dawley (SD) rats with a body weight of 250\u0026thinsp;\u0026plusmn;\u0026thinsp;20g were obtained from the Experimental Animal Center of Zunyi Medical University. The experimental animal use license number is: SCXK (Qian) 2021-0002. During the experimental period, the rats were housed in the Animal Experimental Center of Guizhou Medical University. The animal experimental research protocol has been approved by the Animal Ethics Committee of Guizhou Medical University (Approval Number: 2305201).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMajor Reagents and Instruments\u003c/h3\u003e\n\u003cp\u003eFluoxetine Hydrochloride, Specification: 20mg*28 tablets (Lilly Suzhou Pharmaceutical Company); Mouse Anti-N-Methyl-D-Aspartate Receptor 2B (NMDAR-2b) ELISA Kit, purchased from Jingmei Biotechnology Co., Ltd.; Anti-NMDAR2B Antibody (Catalog No.: ab254356), sourced from Abcam; Hematoxylin-Eosin (HE) Staining Kit (Catalog No.: G1120), acquired from Solarbio Science \u0026amp; Technology Co., Ltd.; HRP-Labeled Goat Anti-Rabbit IgG (Catalog No.: LF102), purchased from Yamei Biomedical Technology Co., Ltd. Neurobehavioral apparatus was obtained from Shanghai Xinruan Information Technology Co., Ltd. All major instruments used in the experiment were provided by the Clinical Research Center of the Affiliated Hospital of Guizhou Medical University.\u003c/p\u003e\n\u003ch3\u003eAnimal Grouping and Model Establishment\u003c/h3\u003e\n\u003cp\u003eForty-five rats were purchased and subjected to adaptive feeding for 7 days before being randomly assigned to three groups using a random number table method, with \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15 rats per group: normal control group (CON), depression model group (MDD), and fluoxetine treatment group (MDD\u0026thinsp;+\u0026thinsp;F). The CON group was maintained under standard conditions with 5 rats per cage. The remaining two groups underwent depression model preparation [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] through a 28-day Chronic Unpredictable Mild Stress (CUMS) protocol combined with solitary housing. The stressors applied were as follows: (1) food deprivation for 24 hours; (2) water deprivation for 24 hours; (3) exposure to damp bedding (dirty cage) for 24 hours; (4) restraint for 6\u0026ndash;8 hours; (5) noise exposure for 24 hours; (6) tilting the cage at 45\u0026deg; for 24 hours; (7) forced swimming in 4\u0026deg;C ice water for 5 minutes; (8) intermittent flashing light stimulation (90Hz) for 12 hours; (9) horizontal shaking of the cage for 5 minutes; (10) reversal of light-dark cycle for 24 hours. Each day, one of these stressors was randomly administered to the rats, with each stressor being used 2\u0026ndash;3 times to ensure unpredictability of the stress, and rats were housed individually. Following the 28-day model establishment period, drug intervention commenced, with the CON and MDD groups receiving intragastric administration of saline (10ml/kg), while the MDD\u0026thinsp;+\u0026thinsp;F group received fluoxetine (10mg/kg) via intragastric administration for 14 consecutive days(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e\n\u003ch3\u003eNeurobehavioral Assessment\u003c/h3\u003e\n\u003cp\u003eTo accurately and effectively evaluate depressive-like behaviors and cognitive abilities in rats, we employed several neurobehavioral tests. The sucrose preference test was used to assess the rats' ability to experience pleasure and maintain interest. The open field test was conducted to evaluate the rats' locomotor activity, exploratory behavior, and anxiety-like behaviors. The forced swim test was administered to determine the presence of despair-like behaviors in the rats. The Morris water maze test was utilized to evaluate the rats' cognitive abilities, particularly their spatial learning and memory capabilities. The three groups of rats were further randomly divided into three subgroups of 5 rats each. The first subgroup from each group underwent neurobehavioral assessment before modeling, the second subgroup after modeling, and the third subgroup following drug intervention.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSucrose Preference Test\u003c/b\u003e [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDepressed rats exhibit a decreased or absent response to rewarding stimuli, corresponding to one of the core symptoms of depression known as \"anhedonia.\" The sucrose preference test comprises two parts: an adaptation training phase and a formal testing phase. During the formal test, the consumption of both sucrose solution and drinking water is measured, and the sucrose preference index is calculated using the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\mathbf{S}\\mathbf{u}\\mathbf{c}\\mathbf{r}\\mathbf{o}\\mathbf{s}\\mathbf{e}\\:\\mathbf{P}\\mathbf{r}\\mathbf{e}\\mathbf{f}\\mathbf{e}\\mathbf{r}\\mathbf{e}\\mathbf{n}\\mathbf{c}\\mathbf{e}\\:\\mathbf{R}\\mathbf{a}\\mathbf{t}\\mathbf{e}\\:\\left(\\mathbf{\\%}\\right)=\\frac{\\mathbf{S}\\mathbf{u}\\mathbf{c}\\mathbf{r}\\mathbf{o}\\mathbf{s}\\mathbf{e}\\:\\mathbf{C}\\mathbf{o}\\mathbf{n}\\mathbf{s}\\mathbf{u}\\mathbf{m}\\mathbf{p}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}\\:}{(\\mathbf{S}\\mathbf{u}\\mathbf{c}\\mathbf{r}\\mathbf{o}\\mathbf{s}\\mathbf{e}\\:\\mathbf{C}\\mathbf{o}\\mathbf{n}\\mathbf{s}\\mathbf{u}\\mathbf{m}\\mathbf{p}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}\\:+\\:\\mathbf{P}\\mathbf{u}\\mathbf{r}\\mathbf{e}\\:\\mathbf{W}\\mathbf{a}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\:\\mathbf{C}\\mathbf{o}\\mathbf{n}\\mathbf{s}\\mathbf{u}\\mathbf{m}\\mathbf{p}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n})\\:}\\times\\:\\:100\\varvec{\\%}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eOpen Field Test\u003c/h3\u003e\n\u003cp\u003eThe rat is placed in the open field apparatus with its back facing the experimenter and allowed to freely move for 5 minutes. During this period, the software records various indicators such as the total distance traveled horizontally, the number of horizontal crossings, the duration of immobility, the ratio of time spent in the peripheral area to the total time, and the ratio of distance traveled in the central area to the total distance traveled.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eForced Swim Test\u003c/h2\u003e \u003cp\u003eRats are placed in a circular, transparent glass cylinder and forced to swim for 5 minutes. During this period, the software is used to observe the rats' immobility time, which refers to the period when the rats cease struggling and enter a floating state, with their trunks and limbs remaining motionless. This metric is used to assess the level of despair exhibited by the rats.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMorris Water Maze Test\u003c/h3\u003e\n\u003cp\u003eThis test is divided into two parts. The first part is the Place Navigation Test, which spans four days and involves training rats to find a submerged platform within 60 seconds. The second part is the Probe Trail Test, conducted on the fifth day when the platform is removed. The quadrant where the platform was previously located is defined as the target quadrant. The rat is placed in the pool at the point farthest from the target quadrant, and the software records the rat's movement trajectory for 60 seconds. The observed indicators include: total distance traveled while searching for the platform, time spent in the target quadrant, ratio of time spent in the target quadrant to total time, average swimming speed, number of crossings over the previous platform location, and latency to first locate the area where the platform was previously positioned. These metrics are used to further evaluate the rat's spatial cognition and memory abilities.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMolecular Docking Technique\u003c/b\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThis technique predicts the binding mode and binding affinity between small molecules and target proteins, thereby evaluating the affinity of drug molecules. The steps involved are: Acquisition and Processing of Drug Small Molecule Receptor Structure: Access the PubChem database, search for \"Fluoxetine Hydrochloride\", download the SDF format, and convert it to mol2 format. Open AutoDock Vina software, import the mol2 format of the small molecule, add all hydrogens, set it as the ligand, assign electron charges, detect and set torsion angles, and save as a PDBQT format file. Acquisition of Target Protein Data: Utilize the RCSB PDB database to search for information on the NMDAR2B protein and download it in pdb format. Import the file into PyMOL 2.6 software, perform water and ligand removal, and save in pdb format. Then, open AutoDock Vina software, import the processed protein molecule, add all hydrogens to the molecular protein, and finally save as a PDBQT format file. Molecular Docking: Using Fluoxetine Hydrochloride as the ligand and the NMDAR2B protein as the target protein receptor, perform docking in the AutoDock Vina software. Record the docking binding energy and conduct visual analysis on PyMOL 2.6 software.\u003c/p\u003e\n\u003ch3\u003eWestern Blotting\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eWestern Blotting\u003c/div\u003e \u003cp\u003eTo detect the relative expression level of NMDAR2B protein, rats were euthanized under anesthesia after the final neurobehavioral assessment. The bilateral hippocampi were rapidly dissected on ice, placed in liquid nitrogen, and then transferred to a -80\u0026deg;C freezer for storage. Subsequent procedures included total protein extraction from the tissue, measurement of protein concentration using the BCA method, normalization of protein concentration, and protein denaturation in a metal bath (since it is an ion channel protein, the sample cannot be boiled as this may lead to protein aggregation; instead, denaturation was performed at 37\u0026deg;C for 15 minutes). Following these steps, the Western blotting experiment was conducted, involving gel preparation, sample loading, electrophoresis, membrane transfer, blocking, incubation with primary antibodies (anti-NMDAR2 antibody at 1:2000 and Beta-Actin at 1:5000) overnight at 4\u0026deg;C, incubation with secondary antibody (goat anti-rabbit IgG(H\u0026thinsp;+\u0026thinsp;L) at 1:4000) for 2 hours, exposure using a chemiluminescence imager, and analysis with Image J software to obtain the relative grayscale values of the target protein bands and internal reference bands. The standardized relative expression level of the target protein was then calculated by dividing the grayscale value of the target band by that of the internal reference band.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eELISA\u003c/h2\u003e \u003cp\u003eThe ELISA method was employed to detect the concentration of NMDAR2B protein. The procedures for sample collection and preservation were identical to those used in the Western blot experiment. Operations were strictly carried out according to the instructions provided in the ELISA kit manual. The OD values of each well were measured at a wavelength of 450 nm. A standard curve was plotted based on the OD values of the standards, from which a linear regression equation was derived. By substituting the OD values of the samples into this equation, the concentrations of the samples were calculated.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHematoxylin-Eosin Staining\u003c/b\u003e [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTo observe the pathological changes in neurons within the hippocampus, anesthetized rats underwent in vivo brain fixation and perfusion using 4% paraformaldehyde for sample collection. The brains were then processed through fixation, washing, dehydration, xylene clearing, wax immersion, embedding, trimming, and slicing (3-8um) to prepare paraffin-embedded brain tissue sections. The sections were dried and stored at room temperature for short-term preservation. Prepared paraffin sections underwent dewaxing, rehydration, and hydration, followed by nuclear staining with hematoxylin, differentiation, bluing, cytoplasmic staining with eosin, dehydration, and mounting. Images were captured and analyzed under an optical microscope.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNissl Staining\u003c/b\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eObservation of Changes in Nissl Bodies in Hippocampal Neurons: Sample collection and paraffin section preparation were performed similarly to the HE staining method. After staining the sections for 4 minutes in Nissl staining solution (primarily containing toluidine blue), differentiation, dehydration, and mounting were performed. Images were captured and analyzed under a light microscope.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGolgi Staining\u003c/b\u003e[\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eObservation of Morphological Changes in Dendritic Spines in the Hippocampus: Following euthanasia of the anesthetized rats, samples were collected directly without perfusion. Golgi staining was performed using the FD Neuro Technologies Rapid Golgi Stain Kit, following the instructions provided in the kit. After staining, the samples underwent routine gradient dehydration, xylene clearing, and mounting with neutral resin. Images were captured using an optical microscope, and the density of dendritic spines was analyzed using ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTransmission Electron Microscopy\u003c/h2\u003e \u003cp\u003eObservation of Microstructural Changes in Hippocampal Synapses: Tissue samples were obtained from anesthetized rats and underwent processing steps including sectioning and staining. Finally, transmission electron microscopy was employed to observe the pre-synaptic membrane, post-synaptic membrane, synaptic cleft, and vesicles within the hippocampal region of the brain tissue. Images were captured and analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData processing and analysis were performed using SPSS 26 software. Data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Assuming that the data followed a normal distribution and had homogeneity of variance, repeated measures ANOVA was used for neurobehavioral assessments, while one-way ANOVA was applied for other comparisons. For further post hoc pairwise comparisons, LSD/Bonferroni tests were conducted. For data that did not meet the criteria of normal distribution or homogeneity of variance, non-parametric tests with rank transformation were utilized. In correlation analysis, Pearson's linear correlation analysis was applied to continuous variables that followed a normal distribution. A P-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant, indicating a difference that was unlikely to have occurred by chance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eNeurobehavioral assessment of rats in three groups\u003c/h2\u003e \u003cp\u003eBefore modeling: At baseline, there were no statistically significant differences in the neurobehavioral assessment indices across the sugar preference test (F\u003csub\u003e2,12\u003c/sub\u003e=0.11, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), forced swimming test (F\u003csub\u003e2,12\u003c/sub\u003e=0.65, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), open-field test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and Morris water maze test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;2A-K; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-H).\u003c/p\u003e \u003cp\u003ePost-modeling: (1) Emotional alterations: Compared to the CON group, the MDD and MDD\u0026thinsp;+\u0026thinsp;F groups exhibited decreased sucrose preference ratio (F\u003csub\u003e2,12\u003c/sub\u003e=93.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2D). In the open field test, there was a reduction in total horizontal movement distance (F\u003csub\u003e2,12\u003c/sub\u003e=40.90, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), decreased horizontal crossing frequency (F\u003csub\u003e2,12\u003c/sub\u003e=18.49, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), prolonged immobility duration (F\u003csub\u003e2,12\u003c/sub\u003e=18.49, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), increased time spent in the peripheral zone relative to total time (F\u003csub\u003e2,12\u003c/sub\u003e=6.26, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and decreased central zone movement distance relative to total distance (F\u003csub\u003e2,12\u003c/sub\u003e=18.32, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2E-K). In the forced swim test, the MDD and MDD\u0026thinsp;+\u0026thinsp;F groups displayed extended immobility time (F\u003csub\u003e2,12\u003c/sub\u003e=116.99, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2A-C). (2) Cognitive learning and memory capabilities: When compared to the CON group, during the spatial exploration phase of the Morris water maze, the MDD and MDD\u0026thinsp;+\u0026thinsp;F groups demonstrated increased total path length to explore the platform (F\u003csub\u003e2,12\u003c/sub\u003e=17.63, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), shortened time spent in the target quadrant (F\u003csub\u003e2,12\u003c/sub\u003e=191.53, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), reduced target quadrant time relative to total time (F\u003csub\u003e2,12\u003c/sub\u003e=191.53, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), decreased average swimming speed (F\u003csub\u003e2,12\u003c/sub\u003e=26.14, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), increased platform crossings (F\u003csub\u003e2,12\u003c/sub\u003e=8.26, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and prolonged latency to first find the target platform (F\u003csub\u003e2,12\u003c/sub\u003e=22.29, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-H). No statistically significant differences were observed between the MDD and MDD\u0026thinsp;+\u0026thinsp;F groups in the aforementioned neurobehavioral indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003ePost-Fluoxetine Intervention: (1) Emotional Aspects: Compared to the MDD group, the CON and MDD\u0026thinsp;+\u0026thinsp;F groups showed significant increases in sucrose preference ratio (F\u003csub\u003e2,12\u003c/sub\u003e=70.57, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2D), total horizontal movement distance (F\u003csub\u003e2,12\u003c/sub\u003e=19.88, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), horizontal crossing frequency (F\u003csub\u003e2,12\u003c/sub\u003e=113.00, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), shortened immobility duration (F\u003csub\u003e2,12\u003c/sub\u003e=54.06, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), decreased time spent in the peripheral zone relative to total time (F\u003csub\u003e2,12\u003c/sub\u003e=13.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and altered (though still decreased) central zone movement distance relative to total distance (F\u003csub\u003e2,12\u003c/sub\u003e=27.68, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating a normalization trend towards CON levels) (Fig.\u0026nbsp;2E-K). Additionally, there was a reduction in immobility time during the forced swim test (F\u003csub\u003e2,12\u003c/sub\u003e=93.77, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2A-C). (2) Cognitive Abilities: In comparison to the MDD group, during the Morris water maze spatial exploration task, the CON and MDD\u0026thinsp;+\u0026thinsp;F groups exhibited increased total path length to explore the platform (F\u003csub\u003e2,12\u003c/sub\u003e=14.63, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), prolonged time spent in the target quadrant (F\u003csub\u003e2,12\u003c/sub\u003e=15.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), increased target quadrant time relative to total time (F\u003csub\u003e2,12\u003c/sub\u003e=15.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), faster average swimming speed (F\u003csub\u003e2,12\u003c/sub\u003e=35.11, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), more platform crossings (F\u003csub\u003e2,12\u003c/sub\u003e=15.72, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and shortened latency to first find the target platform (F\u003csub\u003e2,12\u003c/sub\u003e=26.85, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No statistically significant differences were observed between the CON and MDD\u0026thinsp;+\u0026thinsp;F groups in these neurobehavioral indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-H).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e Results of neurobehavioral statistical analysis. \u003cb\u003e(A, B)\u003c/b\u003e Schematic diagram, trajectory plot, and heatmap of the forced swim test; \u003cb\u003e(C)\u003c/b\u003e Statistical results of immobility duration in the forced swim test; \u003cb\u003e(D)\u003c/b\u003e Statistical results of sucrose preference ratio. \u003cb\u003e(E, F)\u003c/b\u003e Schematic diagram, trajectory plot, and heatmap of the open field test; \u003cb\u003e(G-K)\u003c/b\u003e Statistical results of immobility time, horizontal crossing frequency, total horizontal movement distance, central zone movement distance relative to total distance, and peripheral zone time relative to total time in the open field test. (Compared with the CON group, \u003csup\u003ea\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; compared with the MDD group, \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5 per group, all data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM.)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Docking Results of Fluoxetine Hydrochloride with Target Protein NMDAR2B\u003c/h2\u003e \u003cp\u003eMolecular docking was performed using AutoDock Vina software, revealing a binding energy of -6.9kcal\u0026middot;mol-1, which is less than \u0026minus;\u0026thinsp;5 kcal\u0026middot;mol-1, indicating a robust binding capacity and high affinity between fluoxetine hydrochloride and NMDAR2B (in molecular docking, a binding energy less than \u0026minus;\u0026thinsp;5 kcal\u0026middot;mol-1 signifies good affinity and binding activity between the ligand and receptor [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]). Visual inspection of the 2D and 3D diagrams demonstrates that NMDAR2B primarily binds to fluoxetine hydrochloride through hydrogen bonding with HIS-359 and ASP-348, hydrophobic interactions with HIS-359 and ARG-347, and electrostatic interactions with LYS-361. Additionally, van der Waals forces exist between ASP-286, ASP283, TYR-282, LEU-349, GLN-357, and PRO-360. These chemical bonds are spatially arranged in a rational manner, presenting a tight and stable binding state with excellent geometric compatibility. Consequently, the binding of fluoxetine hydrochloride to NMDAR2B protein may potentially exert corresponding pharmacological effects to a certain extent (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eExpression and Concentration of NMDAR2B Protein in the Hippocampal Region of Brain Tissue\u003c/h2\u003e \u003cp\u003eWestern blot analysis revealed that the relative expression levels of NMDAR2B protein were decreased in both MDD and MDD\u0026thinsp;+\u0026thinsp;F groups compared to the CON group (F\u003csub\u003e2,12\u003c/sub\u003e=17.48, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, within the MDD\u0026thinsp;+\u0026thinsp;F group, the relative expression of NMDAR2B protein was significantly elevated compared to the MDD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eELISA assay results indicated a marked reduction in the concentrations of NMDAR2B subunit in both MDD and MDD\u0026thinsp;+\u0026thinsp;F groups, when compared to the CON group (F\u003csub\u003e2,12\u003c/sub\u003e=97.82, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, the protein concentration in the MDD\u0026thinsp;+\u0026thinsp;F group was significantly higher than that in the MDD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePathological changes in the hippocampal region\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003eHE staining results\u003c/h2\u003e \u003cp\u003eUnder light microscopy, neurons in the CA1, CA3, and DG regions of the hippocampus in the CON group rats were normally distributed, with regular arrangement, full morphology, intact structure, evenly distributed staining, and centrally located and clear nucleoli. In the MDD group, severe pathological damage was observed in the three subregions of the hippocampus, with disordered arrangement of neurons, decreased number, varying sizes and shapes, edema in some cells, uneven cytoplasmic staining, and deeply stained nucleoli. Compared with the MDD group, the MDD\u0026thinsp;+\u0026thinsp;F group showed improved and repaired nerve injury, with increased cell numbers, intact cell membranes, more uniform cytoplasm, clear nuclei, and visible nucleoli (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eNissl Staining Results\u003c/h2\u003e \u003cp\u003eUnder light microscopy, the neuronal cells in the CA1 region of the hippocampus in the CON group exhibited intact structures, tightly arranged in clear bands, with abundant dark blue granular and patchy structures within the cytoplasm, known as Nissl bodies. In comparison to the CON group, the MDD group showed a significant reduction in neuronal cells, with sparse arrangement, irregular morphology, enlarged intercellular spaces, decreased numbers of Nissl bodies within the cytoplasm, lighter staining, and partial obscuration of Nissl bodies. Compared to the MDD group, the MDD\u0026thinsp;+\u0026thinsp;F group demonstrated an increase in the number of Nissl bodies and neuronal cells, with notable improvement in pathological damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eGolgi Staining Results\u003c/h2\u003e \u003cp\u003eThe CON group exhibited high dendrite density, numerous dendrites, and regularly arranged, tight dendrite patterns. In contrast, the MDD group displayed decreased dendrite density, sparsity, and partial dendrite atrophy. Following fluoxetine intervention, the number of dendrites increased, and their arrangement became more compact. Density analysis of individual dendritic spines revealed that compared to the CON group, the density of dendritic spines in hippocampal neurons was reduced in both the MDD and MDD\u0026thinsp;+\u0026thinsp;F groups (F\u003csub\u003e2,12\u003c/sub\u003e=7.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, compared to the MDD group, the MDD\u0026thinsp;+\u0026thinsp;F group showed an increase in dendritic spine density (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-C).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTransmission Electron Microscopy Results\u003c/h2\u003e \u003cp\u003eThe results demonstrated that in the CON group, the synaptic corpuscles had intact membranes, uniform matrix, abundant neurofilaments and microtubules, structurally intact mitochondria with homogeneous intramembrane matrix, and well-preserved axonal terminal membranes featuring uniform matrix, concentrated presynaptic membrane proteins, distinct dense zones, and structurally complete components. Additionally, the number of synaptic vesicles was abundant, and the synaptic cleft was clearly discernible. In contrast, rats from the MDD group exhibited severe synaptic damage characterized by reduced synaptic counts, notably compromised synaptic corpuscles with extensive membrane disruptions and disintegration, markedly decreased cytoplasmic electron density, diminished neurofilaments and microtubules, overtly swollen mitochondria accompanied by sparse and dissolved local matrix, reduced cristae, and vacuolation. Furthermore, the axonal terminal membranes were obscure with dissolved matrix and indistinct presynaptic membrane structures. While synaptic vesicles were abundant, most were damaged or disintegrated. Dendritic spines exhibited sparse matrix and localized membrane disruptions, and the synaptic cleft was obscure. Following fluoxetine intervention, a degree of recovery from the damage observed in the MDD group was noted, with mildly edematous mitochondria, abundant synaptic vesicles of varying sizes but structurally intact, and a reasonably discernible synaptic cleft (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCorrelation Analysis between Pathological Damage, NMDAR2B Subunit Expression, and Cognition-Related Behavioral Indicators\u003c/h2\u003e \u003cp\u003eThrough correlation analysis, it was found that there was a significant correlation between the density of dendritic spines in the hippocampus, the relative expression of the NMDAR2B subunit, and cognition-related behavioral indicators in rats.\u003c/p\u003e \u003cp\u003eThe expression of NMDAR2B subunit showed a significant positive correlation with the total distance traveled in the exploration platform (R\u0026thinsp;=\u0026thinsp;0.580, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the time spent in the target quadrant (R\u0026thinsp;=\u0026thinsp;0.676, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), the ratio of time spent in the target quadrant to total time (R\u0026thinsp;=\u0026thinsp;0.557, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the average swimming speed (R\u0026thinsp;=\u0026thinsp;0.678, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and the number of platform crossings (R\u0026thinsp;=\u0026thinsp;0.568, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, it exhibited a significant negative correlation with the latency to first find the target platform (R=-0.552, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eThe dendritic spine density in the hippocampus demonstrated a significant positive correlation with the time spent in the target quadrant (R\u0026thinsp;=\u0026thinsp;0.603, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the ratio of time spent in the target quadrant to total time (R\u0026thinsp;=\u0026thinsp;0.529, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the number of platform crossings (R\u0026thinsp;=\u0026thinsp;0.524, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, it showed a significant negative correlation with the latency to first find the target platform (R=-0.621, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no correlation was observed between the dendritic spine density and the total distance traveled in the exploration platform (R\u0026thinsp;=\u0026thinsp;0.452, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) or the average swimming speed (R\u0026thinsp;=\u0026thinsp;0.434, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThe relative expression level of the NMDAR2B subunit in the hippocampus displayed a significant positive correlation with dendritic spine density (R\u0026thinsp;=\u0026thinsp;0.542, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe pathological mechanisms underlying depression are intricate, with clinical manifestations encompassing emotional disturbances, somatization symptoms, and cognitive decline across multiple dimensions[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Among these, cognitive dysfunction is a prevalent comorbid symptom in patients with depression. The chronic unpredictable mild stress (CUMS) model is considered the most suitable animal model for simulating depression induced by long-term exposure to stress and frustration in humans [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The solitary housing paradigm simulates social isolation, further enhancing the similarity between the CUMS model and the complex etiology of human depression [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].The hippocampus, a crucial component of the limbic system, is anatomically organized into three layers: the molecular layer, the pyramidal cell layer, and the polymorphic layer. Moreover, it is subdivided into four regions in the transverse plane: Cornu Ammon 1 to 4 (CA1-CA4). From an anatomical and functional perspective, the CA1, CA3, and dentate gyrus (DG) regions are particularly vulnerable to various adverse stimuli[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], playing pivotal roles in emotional regulation, behavioral inhibition, and the execution of advanced cognitive functions such as learning and memory [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Dysfunction in these regions is closely associated with cognitive impairments in depression [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eN-Methyl-D-aspartate (NMDA) ionotropic glutamate receptors (NMDARs), a significant class of ionotropic glutamate receptors, have a subtype, NMDAR2B, which is central to neural development, synaptogenesis, synaptic plasticity modulation, neural network homeostasis, and cognitive function. Abnormalities in NMDAR-mediated signaling, particularly those involving NMDAR2B dysfunction, have been implicated in numerous neurodegenerative diseases and mental health disorders, highlighting their extensive and profound influence on maintaining normal neural function [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Therefore, a profound investigation into the mechanisms of NMDAR2B in cognitive dysfunction associated with depression is crucial for elucidating the pathophysiological processes of depression and developing novel therapeutic strategies.\u003c/p\u003e \u003cp\u003eIn this study, after 4 weeks of CUMS modeling, rats exhibited depressive-like behaviors and cognitive dysfunction, aligning with the criteria for a cognitive dysfunction model of depression. Upon successful modeling, a decrease in the expression level and concentration of the NMDAR2B subunit was observed, accompanied by pathological damage and reduced neural plasticity and complexity in the three subregions of the hippocampus. The high absolute value of the molecular docking binding energy between fluoxetine hydrochloride and NMDAR2B indicates that fluoxetine can bind to the NMDAR2B subunit to exert its pharmacological effects. Following fluoxetine hydrochloride intervention, neurobehavioral results revealed improvements in depressive-like behaviors and varying degrees of recovery of cognitive function in the depression model rats. Additionally, there was an increase in the expression level and concentration of NMDAR2B protein, accompanied by varying degrees of repair of pathological damage and neural plasticity. Correlation analysis revealed that more severe pathological damage and lower expression of NMDAR2B protein were associated with more impaired cognitive function, while decreased dendritic spine density correlated with lower expression of NMDAR2B protein. In summary, fluoxetine, a selective serotonin reuptake inhibitor (SSRI), exhibits significant affinity for the NMDAR2B subunit. Fluoxetine improves cognitive symptoms in depression model rats by regulating the expression of the NMDAR2B subunit, thereby exerting neuroprotective effects, aiding in the repair of pathological damage in the hippocampus, and promoting neural plasticity. This provides new theoretical and research insights for the treatment of cognitive dysfunction in depression in clinical settings.\u003c/p\u003e \u003cp\u003eThe present study possesses certain limitations. Firstly, the experimental subjects were limited to adult male rats, thus not exploring potential gender differences in the recovery of cognitive function. Furthermore, the selection of antidepressants in this study was relatively narrow, with the classic SSRI antidepressant fluoxetine being the sole agent used. Future research should further observe and investigate the impact of other first-line antidepressants on cognitive dysfunction in depression, in order to more comprehensively reveal the interventional effects and underlying mechanisms of antidepressants on cognitive dysfunction associated with depression.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eRats with depression-related cognitive dysfunction exhibit neuronal damage in the hippocampus, reduced neural plasticity and complexity, and decreased expression of the NMDAR2B subunit. Fluoxetine, with its strong affinity for the NMDAR2B subunit, exerts neuroprotective effects by regulating the expression of NMDAR2B, thereby improving cognitive function in depressed rats. This provides new theoretical insights and approaches for the clinical treatment of cognitive impairment in depression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLL : Contributed to the conception and design of the study, data curation, formal analysis, funding acquisition, investigation, methodology development, project administration, resource allocation, software application, research supervision, result validation, data visualization, drafting the original manuscript, and subsequent review and editing. PL, YH, QS: Participated in data curation, formal analysis, funding acquisition, methodology development, project administration, research supervision, result validation, as well as the review and editing of the manuscript. HL, YW : Were responsible for project administration, research supervision, and the review and editing of the manuscript. YW: Contributed to funding acquisition, resource allocation, and the review and editing of the manuscript. All authors have reviewed the final content of this manuscript and agree to its publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China, No: 8226140969, Guizhou Provincial Science and Technology Department Qiankehe Platform Talent [2018]5802, [2016]5679.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal study was approved by Guizhou Medical University Attitude of the Animal Care Welfare Committee (Approval Number: 2305201). The study was conducted in accordance with the local legislation and institutional requirements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChinese Society of Psychiatry Chinese Academy of Depressive Disorders, Li LJ, Wang G. Expert consensus on assessment and intervention of cognitive symptoms in major depressive disorder. Chinese Journal of Psychiatry. 2020;53:369-76. doi:10.3760/cma.j.cn113661-20200410-00177.\u003c/li\u003e\n\u003cli\u003eShilyansky C, Williams LM, Gyurak A, Harris A, Usherwood T, Etkin A. Effect of antidepressant treatment on cognitive impairments associated with depression: a randomised longitudinal study. Lancet Psychiatry. 2016;3:425-35. doi:10.1016/S2215-0366(16)00012-2.\u003c/li\u003e\n\u003cli\u003eWise T, Radua J, Via E, Cardoner N, Abe O, Adams TM, Amico F, Cheng Y, Cole JH, de Azevedo Marques P\u0026eacute;rico C, Dickstein DP, Farrow T, Frodl T, Wagner G, Gotlib IH, Gruber O, Ham BJ, Job DE, Kempton MJ, Kim MJ, Koolschijn P, Malhi GS, Mataix-Cols D, McIntosh AM, Nugent AC, O\u0026apos;Brien JT, Pezzoli S, Phillips ML, Sachdev PS, Salvadore G, Selvaraj S, Stanfield AC, Thomas AJ, van Tol MJ, van der Wee N, Veltman DJ, Young AH, Fu CH, Cleare AJ, Arnone D. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis. Mol Psychiatry. 2017;22:1455-63. doi:10.1038/mp.2016.72.\u003c/li\u003e\n\u003cli\u003eAtique-Ur-Rehman H, Neill JC. Cognitive dysfunction in major depression: From assessment to novel therapies. Pharmacol Ther. 2019;202:53-71. doi:10.1016/j.pharmthera.2019.05.013.\u003c/li\u003e\n\u003cli\u003eRosenblat JD, Kakar R, McIntyre RS. The Cognitive Effects of Antidepressants in Major Depressive Disorder: A Systematic Review and Meta-Analysis of Randomized Clinical Trials. Int J Neuropsychopharmacol. 2015;19:pyv082 [pii]. doi:10.1093/ijnp/pyv082.\u003c/li\u003e\n\u003cli\u003eBaune BT, Renger L. Pharmacological and non-pharmacological interventions to improve cognitive dysfunction and functional ability in clinical depression--a systematic review. Psychiatry Res. 2014;219:25-50. doi:10.1016/j.psychres.2014.05.013.\u003c/li\u003e\n\u003cli\u003eSheline YI, Liston C, McEwen BS. Parsing the Hippocampus in Depression: Chronic Stress, Hippocampal Volume, and Major Depressive Disorder. Biol Psychiatry. 2019;85:436-8. doi:10.1016/j.biopsych.2019.01.011.\u003c/li\u003e\n\u003cli\u003eLeDoux JE. Emotion circuits in the brain. Annu Rev Neurosci. 2000;23:155-84. doi:10.1146/annurev.neuro.23.1.155.\u003c/li\u003e\n\u003cli\u003eLi QQ, Chen J, Hu P, Jia M, Sun JH, Feng HY, Qiao FC, Zang YY, Shi YY, Chen G, Sheng N, Xu Y, Yang JJ, Xu Z, Shi YS. Enhancing GluN2A-type NMDA receptors impairs long-term synaptic plasticity and learning and memory. Mol Psychiatry. 2022;27:3468-78. doi:10.1038/s41380-022-01579-7.\u003c/li\u003e\n\u003cli\u003eWang X, Xie J, Tan L, Lu Y, Shen N, Li J, Hu H, Li H, Li X, Cheng L. N6-methyladenosine-modified circRIMS2 mediates synaptic and memory impairments by activating GluN2B ubiquitination in Alzheimer\u0026apos;s disease. Transl Neurodegener. 2023;12:53. doi:10.1186/s40035-023-00386-6.\u003c/li\u003e\n\u003cli\u003eWang C, Zhu MH, Sun N, Shen W, Jiang N, Zhao QS, Zhang YX, Huang Y, Zhou WX. Isorhynchophylline ameliorates stress-induced emotional disorder and cognitive impairment with modulation of NMDA receptors. Front Neurosci. 2022;16:1071068. doi:10.3389/fnins.2022.1071068.\u003c/li\u003e\n\u003cli\u003eWu HJ, Wu WN, Fan H, Liu LE, Zhan JQ, Li YH, Chen CN, Jiang SZ, Xiong JW, Yu ZM, Wei B, Wang W, Yang YJ. Life extension factor klotho regulates behavioral responses to stress via modulation of GluN2B function in the nucleus accumbens. Neuropsychopharmacology. 2022;47:1710-20. doi:10.1038/s41386-022-01323-3.\u003c/li\u003e\n\u003cli\u003eWillner P. Animal models as simulations of depression. Trends Pharmacol Sci. 1991;12:131-6. doi:10.1016/0165-6147(91)90529-2.\u003c/li\u003e\n\u003cli\u003eDuman CH. Models of depression. Vitam Horm. 2010;82:1-21. doi:10.1016/S0083-6729(10)82001-1.\u003c/li\u003e\n\u003cli\u003eFernando AB, Robbins TW. Animal models of neuropsychiatric disorders. Annu Rev Clin Psychol. 2011;7:39-61. doi:10.1146/annurev-clinpsy-032210-104454.\u003c/li\u003e\n\u003cli\u003e中华医学会精神医学分会抑郁障碍研究协作组. 抑郁症认知症状评估与干预专家共识. 中华精神科杂志. 2020;53:369-76. doi:10.3760/cma.j.cn113661-20200410-00177.\u003c/li\u003e\n\u003cli\u003eLiu MY, Yin CY, Zhu LJ, Zhu XH, Xu C, Luo CX, Chen H, Zhu DY, Zhou QG. Sucrose preference test for measurement of stress-induced anhedonia in mice. Nat Protoc. 2018;13:1686-98. doi:10.1038/s41596-018-0011-z.\u003c/li\u003e\n\u003cli\u003eSchalla MA, K\u0026uuml;hne SG, Friedrich T, Hanel V, Kobelt P, Goebel-Stengel M, Rose M, Stengel A. Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System. J Vis Exp. 2020. doi:10.3791/60953.\u003c/li\u003e\n\u003cli\u003eHuang HJ, Zhu XC, Han QQ, Wang YL, Yue N, Wang J, Yu R, Li B, Wu GC, Liu Q, Yu J. Ghrelin alleviates anxiety- and depression-like behaviors induced by chronic unpredictable mild stress in rodents. Behav Brain Res. 2017;326:33-43. doi:10.1016/j.bbr.2017.02.040.\u003c/li\u003e\n\u003cli\u003ePaggi JM, Pandit A, Dror RO. The Art and Science of Molecular Docking. Annu Rev Biochem. 2024;93:389-410. doi:10.1146/annurev-biochem-030222-120000.\u003c/li\u003e\n\u003cli\u003eBurley SK, Bhikadiya C, Bi C, Bittrich S, Chen L, Crichlow GV, Christie CH, Dalenberg K, Di Costanzo L, Duarte JM, Dutta S, Feng Z, Ganesan S, Goodsell DS, Ghosh S, Green RK, Guranović V, Guzenko D, Hudson BP, Lawson CL, Liang Y, Lowe R, Namkoong H, Peisach E, Persikova I, Randle C, Rose A, Rose Y, Sali A, Segura J, Sekharan M, Shao C, Tao YP, Voigt M, Westbrook JD, Young JY, Zardecki C, Zhuravleva M. RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. Nucleic Acids Res. 2021;49:D437-437D451. doi:10.1093/nar/gkaa1038.\u003c/li\u003e\n\u003cli\u003eYang JZ, Zhang KK, Shen HW, Liu Y, Li XW, Chen LJ, Liu JL, Li JH, Zhao D, Wang Q, Zhou CS. Sigma-1 receptor knockout disturbs gut microbiota, remodels serum metabolome, and exacerbates isoprenaline-induced heart failure. Front Microbiol. 2023;14:1255971. doi:10.3389/fmicb.2023.1255971.\u003c/li\u003e\n\u003cli\u003eCarriel V, Campos A, Alaminos M, Raimondo S, Geuna S. Staining Methods for Normal and Regenerative Myelin in the Nervous System. Methods Mol Biol. 2017;1560:207-18. doi:10.1007/978-1-4939-6788-9_15.\u003c/li\u003e\n\u003cli\u003eKrutsay M. [Nissl staining with cresyl violet]. Z Med Labortech. 1970;11:75-6\u003c/li\u003e\n\u003cli\u003eZhong F, Liu L, Wei JL, Dai RP. Step by Step Golgi-Cox Staining for Cryosection. Front Neuroanat. 2019;13:62. doi:10.3389/fnana.2019.00062.\u003c/li\u003e\n\u003cli\u003eZaqout S, Kaindl AM. Golgi-Cox Staining Step by Step. Front Neuroanat. 2016;10:38. doi:10.3389/fnana.2016.00038.\u003c/li\u003e\n\u003cli\u003eNarayanan SN, Bairy LK, Srinivasamurthy SK. Determining factors for optimal neuronal and glial Golgi-Cox staining. Histochem Cell Biol. 2020;154:431-48. doi:10.1007/s00418-020-01891-9.\u003c/li\u003e\n\u003cli\u003eChen Y, Zhang F, Sun J, Zhang L. Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment. J Transl Med. 2023;21:920. doi:10.1186/s12967-023-04755-7.\u003c/li\u003e\n\u003cli\u003eMalhi GS, Mann JJ. Depression. Lancet. 2018;392:2299-312. doi:10.1016/S0140-6736(18)31948-2.\u003c/li\u003e\n\u003cli\u003eZuckerman H, Pan Z, Park C, Brietzke E, Musial N, Shariq AS, Iacobucci M, Yim SJ, Lui L, Rong C, McIntyre RS. Recognition and Treatment of Cognitive Dysfunction in Major Depressive Disorder. Front Psychiatry. 2018;9:655. doi:10.3389/fpsyt.2018.00655.\u003c/li\u003e\n\u003cli\u003eHao Y, Ge H, Sun M, Gao Y. Selecting an Appropriate Animal Model of Depression. Int J Mol Sci. 2019;20:4827. doi:10.3390/ijms20194827.\u003c/li\u003e\n\u003cli\u003eWillner P. The chronic mild stress (CMS) model of depression: History, evaluation and usage. Neurobiol Stress. 2017;6:78-93. doi:10.1016/j.ynstr.2016.08.002.\u003c/li\u003e\n\u003cli\u003eLi Y, Luo Y, Tang J, Liang X, Wang J, Xiao Q, Zhu P, Xiao K, Jiang L, Dou X, Huang C, Xie Y, Tang Y. The positive effects of running exercise on hippocampal astrocytes in a rat model of depression. Transl Psychiatry. 2021;11:83. doi:10.1038/s41398-021-01216-x.\u003c/li\u003e\n\u003cli\u003eNieh EH, Schottdorf M, Freeman NW, Low RJ, Lewallen S, Koay SA, Pinto L, Gauthier JL, Brody CD, Tank DW. Geometry of abstract learned knowledge in the hippocampus. Nature. 2021;595:80-4. doi:10.1038/s41586-021-03652-7.\u003c/li\u003e\n\u003cli\u003ePark SA, Miller DS, Nili H, Ranganath C, Boorman ED. Map Making: Constructing, Combining, and Inferring on Abstract Cognitive Maps. Neuron. 2020;107:1226-38.e8. doi:10.1016/j.neuron.2020.06.030.\u003c/li\u003e\n\u003cli\u003eDupuis JP, Nicole O, Groc L. NMDA receptor functions in health and disease: Old actor, new dimensions. Neuron. 2023;111:2312-28. doi:10.1016/j.neuron.2023.05.002.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Depression, Cognitive Dysfunction in Depression, NMDAR2B, CUMS, Hippocampal Neurons, Learning and Memory, Rats","lastPublishedDoi":"10.21203/rs.3.rs-5371457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5371457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo observe the changes in cognitive function of depressive model rats after fluoxetine intervention, and further explore the correlation between fluoxetine's influence on cognitive function in depressive model rats and the N-methyl-D-aspartate receptor 2B subunit (NMDAR2B) in the hippocampus, as well as its impact on hippocampal neurons.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe depression model was established using Chronic Unpredictable Mild Stress (CUMS) combined with solitary confinement, followed by fluoxetine intervention upon successful establishment. Neurobehavioral assessments were conducted to evaluate the rats' emotions, cognition, and learning abilities. Molecular docking technology was employed to observe the affinity between fluoxetine and the NMDAR2B subunit. Proteomic analysis was performed to detect changes in NMDAR2B protein, and histopathological staining was used to observe pathological alterations in neurons in the rat hippocampus. Finally, statistical analysis of the data was conducted.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter modeling, the rats exhibited depressive-like behaviors, impaired cognitive learning and memory abilities, significantly reduced expression and concentration of NMDAR2B protein, pathological damage to neurons in the hippocampus, decreased number of Nissl bodies, markedly reduced dendritic spine density, damaged synaptic structures with decreased synaptic vesicles. Following fluoxetine intervention, these conditions showed varying degrees of recovery. Correlation analysis revealed that the cognitive and learning abilities of rats were impaired, accompanied by a significant decrease in dendritic spine density and a decline in the expression of the NMDAR2B protein.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFluoxetine may exert neuroprotective effects by regulating the expression of NMDAR2B protein in the hippocampus, thereby improving the cognitive function of depressed rats.\u003c/p\u003e","manuscriptTitle":"Effects of NMDAR2B-mediated Hippocampal Neuron Protection on Cognitive Function in Rats with Depression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-22 13:32:46","doi":"10.21203/rs.3.rs-5371457/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0bf6945a-807e-47d9-bb5f-5bc9c52a1969","owner":[],"postedDate":"November 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-06T17:23:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-22 13:32:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5371457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5371457","identity":"rs-5371457","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}