Multistage intervention copper death inhibitor for treating cognitive dysfunction in wilson disease and preparation method thereof

Abstract

The application provides a multi-stage intervention copper death inhibitor for treating Wilson disease cognitive dysfunction and a preparation method thereof, and realizes multi-link active intervention of neuron copper death by constructing a Cur-polypeptide conjugate (GFC) with copper response morphology transformation characteristics as a copper death inhibitor, realizes specific recognition of WD brain neurons by the GFC with the aid of an EVs targeted delivery mode, the phospholipid bilayer of the IE can maintain the structural stability of the GFC in the delivery stage in a physiological environment, and after entering the target cell, the intracellular high copper signal drives the GFC to transform from a nanoparticle into a nanofiber structure. The linear structure after the transformation significantly improves the action time of the Cur in inhibiting PrP-mediated copper influx and the GHK in chelating intracellular copper and repairing the function of mitochondria through the high specific surface area characteristics, breaks the vicious cycle of copper influx-mitochondrial damage, and finally realizes comprehensive inhibition of neuron copper death and improvement of WD cognitive impairment.

Description

Technical Field

[0001] This invention belongs to the field of cognitive impairment in Wilson's disease, specifically relating to a multi-level intervention copper death inhibitor for treating cognitive impairment in Wilson's disease and its preparation method. Background Technology

[0002] Wilson's disease (WD) is an autosomal recessive copper metabolism disorder caused by mutations in the ATP7B gene, characterized by abnormal copper accumulation in organs such as the liver and brain. Approximately 30%-40% of WD patients present with neuropsychiatric symptoms as their initial manifestation, with cognitive impairment (CI) being the most common disabling complication. The core pathological basis is neuronal damage induced by copper accumulation. Current clinical treatment for WD primarily relies on copper-lowering drugs. While these can reduce systemic copper load, they have difficulty crossing the blood-brain barrier, resulting in extremely low efficiency in clearing copper accumulated within neurons and failing to reverse neuronal damage. Furthermore, long-term medication leads to significant adverse reactions and poor adherence. Therefore, exploring more effective treatment options that can proactively intervene in neuronal damage is crucial for the treatment of WD cognitive impairment (WDCI).

[0003] Copper death is a novel form of cell death triggered by an abnormal overload of intracellular free copper ions. It closely aligns with the pathological characteristics of Wild West (WD), providing a new perspective on the mechanism by which copper accumulation induces neuronal damage in WD cognitive impairment. The execution mechanism of copper death involves copper ions binding to mitochondrial lipid-acylated proteins, triggering protein aggregation and iron-sulfur cluster degradation, leading to mitochondrial dysfunction and cell death. Existing research reveals two key steps in the progression of copper death: firstly, the upregulation of prion proteins (PrP), involved in cellular copper uptake, leads to a large accumulation of intracellular copper, becoming the initiating factor for copper death. Secondly, mitochondria are the main target of excessive copper ions; their dysfunction induces oxidative stress, leading to a large accumulation of reactive oxygen species, further promoting the copper death process. Current intervention strategies for copper death mostly focus on single steps, using copper chelators to scavenge copper ions or antioxidants to repair mitochondrial function, with limited inhibitory effects, suggesting a possible undiscovered regulatory relationship between copper influx and mitochondrial damage. Based on this, it is hypothesized that PrP-mediated abnormal copper influx and mitochondrial dysfunction do not act independently, but rather form a cascading vicious cycle that continuously exacerbates the copper death process. This may be the core reason why existing intervention strategies are unable to completely inhibit copper death. Therefore, simultaneously blocking copper ion influx and repairing mitochondrial function may break this potential vicious cycle and achieve a comprehensive inhibition of neuronal copper death.

[0004] Based on the above analysis, two bioactive molecules with complementary functions were identified. Curcumin, a natural polyphenolic compound isolated from turmeric, significantly enhances the activation activity of nuclear factor E2-related factor 2 (Nrf2). Studies have confirmed that Nrf2 negatively regulates prion protein (PrP) expression; therefore, curcumin can inhibit PrP-mediated copper influx by activating Nrf2, thus blocking the triggering process of copper death at its source. On the other hand, GHK (glycyl-histidyl-lysine) is a naturally occurring tripeptide with a high-affinity copper chelating domain. Targeting the pathological characteristic of high intracellular copper in neurons of WD cognitive impairment, GHK possesses a multifunctional advantage of "turning toxicity into treasure." Specifically, GHK not only chelates intracellular free copper to reduce cytotoxicity, but also, because the GHK-copper complex it forms is not an inert metabolite, it can repair mitochondrial function and enhance ROS scavenging ability. This process transforms toxic copper ions into "active resources" for mitochondrial repair, effectively blocking the copper death process. Therefore, the combined use of Curl and GHK allows Curl to inhibit PrP-mediated copper influx, preventing copper death; GHK chelates intracellular copper and repairs mitochondrial function, blocking the progression of copper death. The two are complementary and indispensable, working together to break the vicious cycle of copper influx and mitochondrial damage, achieving comprehensive inhibition of neuronal copper death. However, despite the significant synergistic therapeutic potential of the Curl and GHK combination, applying this strategy to the brain still faces two key challenges. First, insufficient drug delivery efficiency makes it difficult to efficiently cross the blood-brain barrier and precisely target damaged neurons. Second, the short duration of drug action makes it difficult to maintain effective concentrations at the lesion site for long-term intervention. Summary of the Invention

[0005] First, this invention targets the characteristic environment of copper overload within neurons of WD lesions, designing a Cur-peptide conjugate (GHKLVFF-Cur, GFC) with copper-responsive morphological transformation properties. Its structure integrates three functional modules: GHK: the response module, constituting the morphological transformation "trigger"; LVFF: the self-assembly module, serving as the structural basis for morphological transformation; and Cur: the drug module. Furthermore, natural extracellular vesicles (EVs), due to their low immunogenicity, long circulation characteristics, and ability to cross the blood-brain barrier (BBB), are ideal carriers for drug delivery to the brain.

[0006] This invention uses extracellular vesicles derived from mesenchymal stem cells as delivery carriers and modifies their surface with neuron-specific IKRG-targeting peptides (IKRG-EVs, IE) to further enhance the BBB penetration efficiency and precise neuronal targeting capability of the delivery system. Finally, GFCs are loaded into IKRG-EVs to construct a precise targeting-morphological transformation integrated nanodelivery system (GFC@IE).

[0007] This system innovatively achieves multi-stage active intervention in neuronal copper death: (1) Precise targeting: With the help of EVs targeted delivery mode, GFCs specifically recognize neurons in the WD brain. (2) Pathological environment response: The phospholipid bilayer of IE can maintain the structural stability of GFCs during delivery in the physiological environment. After entering the target cell, the intracellular high copper signal drives GFCs to transform from nanoparticles into nanofiber structures. (3) Functional integration: The transformed linear structure, through its high specific surface area, significantly enhances the timeliness of Cur inhibiting PrP-mediated copper influx and GHK chelating intracellular copper and repairing mitochondrial function, jointly breaking the vicious cycle of copper influx-mitochondrial damage, and ultimately achieving comprehensive inhibition of neuronal copper death and improvement of WD cognitive impairment.

[0008] The preparation method of this multi-level intervention copper death inhibitor for treating cognitive impairment in Wilson's disease involves the following steps: First, GHKLVFF is prepared using a solid-phase synthesis method, followed by chemical coupling to prepare GHKLVFF-Cur (GFC). Second, extracellular vesicles (EVs) derived from mesenchymal stem cells are isolated and extracted, and IKRG-targeting peptides are modified on their surface via membrane insertion to obtain IKRG-EVs (IE). Finally, GFC and IE are mixed in an optimized ratio, and loaded using ultrasonic treatment and co-extrusion technology to obtain the precise targeting-morphological transformation integrated copper death inhibitor GFC@IE.

[0009] This invention proposes a multi-step copper death inhibitor (GFC@IE) that comprehensively inhibits neuronal copper death through multi-step synergistic action. Unlike traditional single-function agents, this invention innovatively constructs a GFC conjugate through covalent coupling of Cur and GHK peptide, achieving functional complementarity between the two therapeutic modules. On one hand, Cur downregulates PrP-mediated copper ion influx by upregulating Nrf2 expression, blocking the triggering step of copper death at its source. On the other hand, the GHK peptide has the ability to chelate intracellular free copper ions through high-affinity coordination, converting toxic copper into a GHK-copper complex with mitochondrial repair activity. This mechanism further inhibits the progression of copper death. This dual-step synergistic action breaks the vicious cycle of copper overload and mitochondrial dysfunction, fundamentally ending the cascade process of copper death formation.

[0010] To address delivery challenges, mesenchymal stem cell-derived extracellular molecules (EVs) were employed, with a surface-modified IKRG peptide serving as the delivery carrier. Leveraging the natural BBB penetration capability of EVs and the neuronal-specific targeting effect of the IKRG peptide, globulin-free fatty acids (GFCs) were precisely delivered from the systemic circulation to hippocampal neurons. Crucially, the inherent copper-responsive morphotransformation properties of GFCs can be triggered within neurons. Upon entry into hippocampal neurons, the unique high-copper pathological microenvironment drives their self-assembly from spherical nanoparticles into high-aspect-ratio nanofibers. This in-situ morphotransformation in response to endogenous stimuli significantly enhances the efficiency of Cur activation of Nrf2 and the copper-chelating capacity of the GHK peptide.

[0011] This invention first validated, through clinical samples and animal models, that copper death is the core pathological mechanism of WDCI (WDCI). It also clarified the driving role of a self-amplifying vicious cycle between copper overload and mitochondrial dysfunction in this pathological process. Clinical and animal experimental data showed that the expression of copper death biomarkers FDX1, LIAS, and DLAT was significantly upregulated, and their expression levels were closely related to neuronal damage. Proteomics analysis further revealed the existence of this vicious cycle. Copper overload induces mitochondrial dysfunction, which in turn activates oxidative stress and inflammatory responses. These pathological changes promote further copper ion influx, ultimately forming a cascade amplifying loop of copper overload-mitochondrial dysfunction-intensified copper influx. This finding provides a theoretical basis for comprehensively inhibiting neuronal copper death. Based on this, the function of GFC@IE was validated. In vitro experiments showed that this inhibitor can efficiently cross the BBB. Colocalization assays and TrkB receptor competition experiments further validated its high specificity for neurons, with neuronal targeting efficiency increased to 3.40 times that of the control group. Subsequently, the morphological transformation of GFC from nanoparticles to nanofibers was observed in a high-copper intracellular environment using bio-transmission electron microscopy (Bio-TEM). More importantly, molecular dynamics simulations elucidated the intrinsically triggered in-situ morphology transformation mechanism of copper ions. The GHK module and Cu 2+ The coordination rearrangement of the KLVFF domains led to intermolecular interactions. This process lowered the system's free energy, driving the assembly from nanoparticles to β-sheet-rich nanofibers.

[0012] Based on these functions, GFC@IE can completely disrupt the vicious cycle of copper death through a multi-stage synergistic effect, thereby achieving comprehensive inhibition of neuronal copper death. In vitro cell experiments confirmed that using this inhibitor reduced the copper ion level in neurons by 70.05%. Furthermore, mitochondrial membrane potential and energy metabolism function were effectively restored. Western blot and immunofluorescence analyses showed that the expression of copper death-related proteins FDX1 and LIAS was downregulated by 78.45% and 66.36%, respectively. Simultaneously, Nrf2 expression-mediated abnormal PrP activation was effectively inhibited. Notably, the single-morphotype (GLC@IE) only partially reduced copper ion levels, but its effect on restoring mitochondrial function and downregulating copper death proteins was significantly lower than that of GFC@IE. This indicates that the high specific surface area ratio nanofiber structure conferred by copper-responsive morphotransformation is crucial for enhancing Cur-mediated Nrf2 activation and the copper chelation and mitochondrial repair capabilities of GHK peptides. In vivo animal experiments showed that GFC@IE significantly improved cognitive function in WDCI model mice and effectively restored the number of neurons. Copper levels in the hippocampus decreased by 66.25%, with PrP expression also downregulated. Furthermore, levels of key tricarboxylic acid cycle metabolites (including SUCN, AKG, and ATP) in mitochondria increased by 2.03-fold, 3.00-fold, and 3.18-fold, respectively. Transcriptome analysis further revealed that GFC@IE downregulated gene pathways involved in copper death (FDX1, LIAS) and neuroinflammation (NF-κB, IL-1β). Conversely, it upregulated pathways related to mitochondrial energy metabolism (TCA cycle, oxidative phosphorylation) and cognitive function.

[0013] In summary, the GFC@IE constructed in this invention achieves comprehensive inhibition of neuronal copper death across multiple stages. Unlike DMPS, a clinical drug that simply clears copper ions, GFC@IE achieves multi-step intervention by synergistically blocking copper influx and restoring mitochondrial function. This multi-step intervention strategy provides a revolutionary new approach for the effective treatment of WDCI. Attached Figure Description

[0014] Figure 1This diagram illustrates the mechanism by which GFC@IE inhibits neuronal copper death through multi-step intervention to alleviate WDCI. The inhibitor penetrates the BBB and targets specific neurons via IKRG peptide-mediated recognition. Once inside the neuron, the high-copper microenvironment of WD triggers the in-situ morphological transformation of GFCs from nanoparticles to nanofibers, thereby exerting multi-level inhibition on neuronal copper death. (i) Cur prevents the initiation of copper death by activating Nrf2 expression and blocking source PrP-mediated copper influx. (ii) The GHK peptide chelates excess intracellular free copper ions and simultaneously repairs mitochondrial function, further halting the progression of copper death. These actions collectively break the vicious cycle of copper overload and mitochondrial dysfunction, achieving comprehensive inhibition of neuronal copper death and ultimately improving cognitive function in WD.

[0015] Figure 2 The study demonstrates the close association between WDCI and hippocampal neuronal copper death. a) Flowchart of clinical indicator collection and analysis. b) Relative quantitative analysis of CP (n=5). c) Cross-sectional MRI images of the brains of healthy controls and WD patients. d) Comparison of MMSE scores between the healthy control group and the WD group (I: orientation, II: memory, III: attention and calculation, IV: recall, V: language, VI: total MMSE score, n=5). e) Comparison of MoCA scores between the healthy control group and the WD patient group (I: visuospatial and executive function, II: naming, III: attention, IV: language, V: abstract thinking, VI: delayed recall, VII: orientation, VIII: total MoCA score, n=5). f) Voxel placement in hippocampal MRI and corresponding data. 1 H-MRS spectra. Sagittal plots show regions of interest in the hippocampus. Areas under the spectra represent the concentrations of corresponding metabolites in the tissue. g, Comparison of hippocampal metabolite concentration ratios (NAA: N-acetylaspartate, Cr: creatine, n=5). h, i, Relative expression of FDX1 and LIAS in the serum of healthy controls and WD patients (n=5). j, Representative swimming trajectories of WD mice in the Morris water maze, k, Escape latency, l, Duration of different groups of mice in the target quadrant. m, Representative immunofluorescence images of FDX1 and DLAT in the hippocampus of different groups of mice. n, GO functional enrichment analysis, o, KEGG enrichment analysis, and p, PPI (protein-protein interaction) network (n=5). Statistical analysis was performed using one-way ANOVA.

[0016] Figure 3Preparation and characterization of GFCs. a, Schematic diagram of GFC self-assembly and copper ion-induced morphological transformation. b, UV-Vis absorption spectra of GFCs, GF, and Cur. c, Cu cumulative release curve in vitro (n=3). d, XPS spectra of Cu-GFCs and high-resolution XPS spectra of Cu 2p. e, Hydrodynamic diameter of GFCs. f, Transmission electron microscopy images of GFCs and Cu-GFCs, scale bar: 200 nm. g, AFM image of Cu-GFCs, inset showing selected nanofiber height, scale bar: 200 nm. h, CAC, i is Cu. 2+ CD spectra before and after coordination, j, Cu 2+ FTIR spectra before and after coordination. The k, l, and EPR spectra show (k)•OH and (l)•O. 2- The scavenging ability. UV-Vis absorption spectra of (m) oxidized TMB and (n) DPBF in different systems.

[0017] Figure 4 The dynamic process and molecular mechanism of morphology transformation regulated by GFC copper ions. a, Different equivalents of Cu 2+ TEM images of the transformation of GFCs from nanoparticles to nanofibers after processing, scale bar: 200 nm. b, ThT fluorescence spectrum, c, Cu-GFCs exposed to gradient concentrations of Cu. 2+ The UV-Vis absorption spectra are shown below. d, GFC system and e, Cu-GFC system, snapshots of molecular dynamics simulations within 100 ns. fk, intermolecular interaction forces and thermodynamic parameters in different systems.

[0018] Figure 5 Schematic diagram of GFC@IE preparation. a, Schematic diagram of GFC@IE preparation process. b, Fluorescence intensity of FITC-labeled CIKRG peptide and IE. c, CIKRG peptide grafting rate (n=3). d, Particle size change of GFC@IE in PBS and FBS at different time points. e, Fluorescence images of GFC and IE at different mixing ratios (red fluorescence represents GFC, green fluorescence represents IE), scale bar: 1 μm. f, Fusion efficiency of GFC and IE (n=3). g, TEM images of IE and GFC@IE, scale bar: 200 nm. h, Hydrodynamic diameters of EVs, IE, and GFC@IE. i, Western blot analysis of CD63 and CD81 expression in EVs, IE, and GFC@IE. Statistical analysis was performed using one-way ANOVA.

[0019] Figure 6GFC@IE precisely targets hippocampal neurons across the blood-brain barrier (BBB). a) Schematic diagram of in vitro Transwell BBB construction. b) Fluorescence images of the superior and inferior vena cava after incubation with different Cy5-labeled samples. c) BBB penetration efficiency of different samples (n=3). d) Schematic diagram of GFC@IE crossing the blood-brain barrier and precisely targeting neurons. e) Representative CLSM images of GFC@IE uptake by bEnd.3, HT22, and BV2 cells, scale bar: 10 μm. f) Flow cytometry analysis of mean fluorescence intensity (MFI) after GFC@IE uptake by different cells (n=3). g) Cell uptake MFI of GFC@E and GFC@IE at different incubation time points (n=3). h) Representative CLSM images of cell uptake by different samples after 4 h of incubation, scale bar: 10 μm. i) Schematic diagram of neuronal targeting by GFC@IE and flow cytometry analysis of MFI uptake by GFC@IE cells with and without IKRG peptide pretreatment (n=3). j. Flow cytometry analysis of HT22 cell uptake mechanisms under different conditions (n=3). k, l: Bio-TEM images of HT22 cells treated with GLC@IE and GFC@IE. Scale bars: 1 μm and 500 nm. Statistical analysis was performed using one-way ANOVA.

[0020] Figure 7 To alleviate copper overload and restore mitochondrial function using GFC@IE. a) Schematic diagram of GFC@IE reducing copper overload and repairing mitochondrial damage. b) Intracellular copper levels in HT22 cells after different sample treatments. 2+ Representative CLSM images at the horizontal level (DAPI: cell nucleus, Rhodamine B hydrazide (RBH): Cu) 2+ ), Scale bar: 20 μm. c, GFC@IE and HT22 cells were co-incubated for 120 min, intracellular Cu 2+ CLSM images and quantitative analysis, scale bar: 10 μm. d. ROS levels in HT22 cells assessed using the DCFH-DA probe, scale bar: 20 μm. e, f. Mitochondrial membrane potential of HT22 cells after different treatments detected using JC-1 and analyzed by flow cytometry (n=3). g. Representative images of mitochondrial morphology in HT22 cells of the model group and GFC@IE treatment group, scale bar: 10 μm. h. Quantitative analysis of the average branch length of mitochondria (n=3). i. Transmission electron microscopy imaging of HT22 cells of the model group and GFC@IE treatment group, scale bars: 2 μm and 1 μm. j, k. Quantitative analysis of oxygen consumption and basal respiration in HT22 cells after different sample treatments (n=3). l, m. Quantitative analysis of external acidification rate and glycolysis in HT22 cells after different sample treatments (n=3). Statistical analysis was performed using one-way ANOVA.

[0021] Figure 8To demonstrate the effectiveness of GFC@IE in inhibiting neuronal copper death: a) CCK-8 assay to detect the survival rate of HT22 cells after different sample treatments. b) Fluorescence images of live / dead HT22 cells under different treatments (red fluorescence indicates dead cells, green fluorescence indicates live cells), scale bar: 100 μm. c) Immunofluorescence staining image of FDX1 in HT22 cells, scale bar: 20 μm. d) Western blot analysis of copper death-related protein expression in HT22 cells after different treatments. e) Quantitative analysis of FDX1 and LIAS in HT22 cells (n=3). f) Schematic diagram of the comprehensive inhibition of neuronal copper death by GFC@IE. gj) Quantitative analysis of the relative levels of TNF-α, IL-6, IL-4, and IL-10 in HT22 cells (n=3). Statistical analysis was performed using one-way ANOVA.

[0022] Figure 9 To assess the in vivo targeting ability of GFC@IE. a, b, Blood fluorescence images and quantitative analysis collected at different time points after intravenous injection of free Cy5 and Cy5-labeled GFC@IE (n=3). c, e, Brain fluorescence imaging and corresponding quantitative analysis of WDCI mice at different time intervals under different sample treatments (n=3), scale bar: 1 cm. d, f, In vitro fluorescence imaging and corresponding quantitative analysis of the brain and major organs of WDCI mice 24 h after drug administration (n=3), scale bar: 1 cm. gi, Representative colocalization images of different Cy5-labeled samples and hippocampal neurons (blue: cell nucleus, green: neuron MAP2, red: different Cy5-labeled samples), scale bar: 5 μm. j, Flow cytometry analysis of colocalization of mouse hippocampal neurons and different Cy5-labeled samples (n=3). Statistical analysis: Two-way ANOVA (e, f); one-way ANOVA (j).

[0023] Figure 10To improve the learning, memory, and cognitive functions of WDCI mice with GFC@IE. a. Schematic diagram of the treatment program's timeline. b. Representative swimming trajectories of mice in different treatment groups in the Morris water maze. c. Schematic diagram of the Morris water maze test. d. Escape latency. e. Time spent in the target quadrant. f. Number of platform crossings in different treatment groups (n=5). g. Representative trajectory of mice in the Y-maze test. h. Schematic diagram of the Y-maze test. i. Percentage of entry into the novelty arm. j. Percentage of time spent in the novelty arm (n=5). k. Representative movement trajectory of mice in the new object recognition test. l. Schematic diagram of the new object recognition test. m. Exploration time of mice in different treatment groups for old object B and new object C (sample: I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, VIII: DMPS, (n=5). n. Recognition index (n=5). Statistical analysis was performed using one-way ANOVA.

[0024] Figure 11 The therapeutic mechanism of GFC@IE in improving cognitive function in WDCI mice. a, Schematic diagram of the mechanism by which GFC@IE improves cognitive function in WDCI mice. b, ICP-MS detection of copper content in mouse hippocampus (n=5). c, Schematic diagram of the mechanism by which GFC@IE improves mitochondrial function. df, Relative contents of succinic acid (SUCN), α-ketoglutarate (AKG), and ATP in mouse hippocampus (n=5). g, h, FDX1 immunofluorescence staining images and quantitative analysis (n=5), scale bar: 100μm. il, ELISA kit detection of relative expression levels of TNF-α, IL-6, IL-4, and IL-10 (n=5). m, Voxel localization and proton magnetic resonance spectroscopy of the hippocampus in each group of mice. 1 H-MRS (Hyper-MRS) atlas. n, quantitative analysis of NAA / Cr ratio in hippocampal tissue of mice in each group (n=5). o, NeuN immunofluorescence staining image of mouse hippocampal tissue, scale bar: 100μm.

[0025] Figure 12 Results of transcription sequencing and bioanalysis. a, Venn diagram of differentially expressed genes (DEGs) between the model group and the GFC@IE treatment group. b, Heatmap showing expression of selected core genomes related to the study mechanism. c, Volcano plot of differentially expressed genes between the model group and the GFC@IE group (fold change > 1.2, P < 0.05). d, e, GSEA enrichment plot (n=3). f, g, Bubble plot of KEGG pathway enrichment of differentially expressed genes between the model group and the GFC@IE group. hj, Bubble plot of GO function enrichment of differentially expressed genes between the model group and the GFC@IE group.

[0026] Figure 13The number of times the target platform was crossed by mice in the normal control group and the model group (n=3).

[0027] Figure 14 (a) Representative movement trajectories of mice in each group during the new object recognition test. (b) Exploration time (n=3) of mice in the control and model groups for old object B and new object C during the test phase. (c) Discrimination index (n=3). (d) Exploration time (n=3) of mice in the control and model groups for old object A and old object B. (e) Exploration time (n=3) of mice in the control and model groups for old object A and new object C.

[0028] Figure 15 Representative immunofluorescence staining images of FDX1 and DLAT in the hippocampus of mice in the control and model groups. Scale bar: 100 μm.

[0029] Figure 16 (a) Principal component analysis (PCA) based on differentially expressed proteins (DEPs) in the hippocampus of the two groups of mice. (b) Volcano plots of upregulated and downregulated proteins in the model group (fold change > 1.2 and p < 0.05).

[0030] Figure 17 This is the synthesis scheme for GFC.

[0031] Figure 18 Analytical characterization of GFC: (a) high performance liquid chromatography (HPLC), (b) mass spectrometry.

[0032] Figure 19 The zeta potentials of GFC, GF, and Cur are (n=3).

[0033] Figure 20 To determine the Cu content in the solution before and after the addition of GFC 2+ ICP-OES quantitative analysis of the content (n=3).

[0034] Figure 21 For GLC and Cu 2+ Transmission electron microscope images before and after coordination, scale bar: 200 nm.

[0035] Figure 22 To treat different groups of ·OH and O 2- Quantitative analysis of clearance capacity (n=3).

[0036] Figure 23 To compare and analyze (a) RMSD curves and (b) radius of gyration curves using molecular dynamics simulations.

[0037] Figure 24 For DSPE-PEG 2000 Synthesis scheme for CIKRG peptide.

[0038] Figure 25 For (a)DSPE-PEG 2000 -Mal and (b)DSPE-PEG 2000 -CIKRG 1 H NMR spectrum.

[0039] Figure 26 TEM image of EVs, scale bar: 100nm.

[0040] Figure 27 The zeta potentials of different samples (n=3).

[0041] Figure 28 Representative fluorescence images of HT22 cells in the lower chamber after different sample treatments in an in vitro BBB model (blue: cell nuclei; red: different samples), scale bar: 10 μm.

[0042] Figure 29 Representative fluorescence images of HT22 cells after different sample treatments (blue: cell nucleus; red: Cu). 2 + ), Scale: 20μm.

[0043] Figure 30 To quantitatively detect Cu in HT22 cells after different sample treatments using flow cytometry 2+ Levels. (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, VIII: DMPS, n=3).

[0044] Figure 31 Representative fluorescence images of HT22 cells after different sample treatments (blue: cell nucleus; green: ROS fluorescent probe), scale bar: 20 μm.

[0045] Figure 32 To detect ROS levels in HT22 cells after different sample treatments using ROS fluorescent probes by flow cytometry. (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=3).

[0046] Figure 33 Representative fluorescence images of mitochondrial membrane potential in HT22 cells after different sample treatments. JC-1 monomers (green), JC-1 aggregates (red), and DAPI (blue). Scale bar: 20 μm.

[0047] Figure 34To conduct quantitative analysis of the model group and the average morphological factor (a) and average area (b) after GFC@IE treatment (n=3).

[0048] Figure 35 ATP-coupled respiration in HT22 cells after different sample treatments (a) and maximum respiration in (b). (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=3).

[0049] Figure 36 To quantitatively analyze (a) glycolytic capacity and (b) non-glycolytic acidification level of HT22 cells after different sample treatments. (I.: control group, II.: model group, III.: Cur, IV.: GFC, V.: GFC@E, VI.: GLC@IE, VII.: GFC@IE, n=3).

[0050] Figure 37 To detect (a) succinate, (b) α-ketoglutarate, and (c) ATP levels in HT22 cells after different sample treatments using an ELISA kit. (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=3).

[0051] Figure 38 (a) Survival rate of HT22 cells treated with different concentrations of GFC@IE (n=3). (b) Cell survival rate of HT22 cells incubated with GFC@IE for different times (n=3).

[0052] Figure 39 Representative immunofluorescence staining images of DLAT in HT22 cells from different treatment groups. Scale bar: 20 μm.

[0053] Figure 40 To determine the relative content of Nrf2 in HT22 cells after different sample treatments by ELISA. (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=3).

[0054] Figure 41 To determine the relative content of Nrf2 in HT22 cells under different sample treatment conditions by ELISA. (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=3).

[0055] Figure 42The hemolysis rate (n=3) was calculated under different concentrations of GFC@IE treatment.

[0056] Figure 43 To determine the exploration time of mice to (a) old object A and old object B, and (b) old object A and new object C after different sample treatments (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, VIII: DMPS, n=5).

[0057] Figure 44 The images show representative movement trajectories of mice in different treatment groups during the open field experiment.

[0058] Figure 45 (a) total distance to the center, (b) total distance traveled, and (c) average speed of mice in different treatment groups in the open field experiment (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, VIII: DMPS, n=5).

[0059] Figure 46 After different sample treatments, the relative contents of (a) Nrf2 and (b) PrP in mouse hippocampus were detected by ELISA kit (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, n=5).

[0060] Figure 47 Representative immunofluorescence staining images of DLAT in hippocampal tissues of mice in different treatment groups. Scale bar: 20 μm.

[0061] Figure 48 After different sample treatments, the LIAS level in mouse hippocampus was detected by ELISA kit (I: control group, II: model group, III: Cur, IV: GFC, V: GFC@E, VI: GLC@IE, VII: GFC@IE, VIII: DMPS, n=5).

[0062] Figure 49 For mouse hippocampus 1 H-MRS spectroscopy.

[0063] Figure 50 H&E staining images of hippocampal tissue from mice in different treatment groups. Scale bar: 200 μm.

[0064] Figure 51 The weight of mice after different sample treatments (n=3).

[0065] Figure 52 Images of H&E staining of heart, liver, spleen, lung and kidney tissues from mice in different treatment groups. Scale bar: 200 μm. Detailed Implementation

[0066] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings.

[0067] Example 1: Experimental Method

[0068] 1. Ethical Statement:

[0069] All animal experiments were approved by the Laboratory Animal Management Committee of the Institute of Health and Medical Sciences, Hefei Comprehensive National Science Center (License No.: IHM-AP-2024-051). The use of human clinical indicators was approved by the Ethics Committee of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine (License No.: 2023AH-56).

[0070] 2. Materials:

[0071] 2-Chloropropyl resin, 1-hydroxybenzotriazole hydrate (HOBt), N-diisopropylethylamine (DIEA), 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide (EDC), trifluoroacetic acid, triisopropylsilane, and 4-dimethylaminopyridine (DMAP) were purchased from Shanghai Bid Pharmaceutical Technology Co., Ltd., China. 3,3',5,5'-Tetramethylbenzoamine (TMB), 1,3-diphenylisobenzofuran (DPBF), xanthine, flavanine oxidase (XO), chlorpromazine hydrochloride (CPZ), and amiloride hydrochloride were purchased from Aladdin Biochemical Technology (Shanghai, China). Cell counting kit-8 (CCK-8) was purchased from Dojin Chemical Co., Ltd., Kumamoto, Japan. Rabbit anti-microtubule-associated protein 2 (MAP2) polyclonal antibody (bs-1369R) was purchased from Beijing Bio-Sens Biotechnology Co., Ltd. The mouse tumor necrosis factor α (TNF-α), mouse interleukin-4 (IL-4), mouse interleukin-10 (IL-10), mouse interleukin-6 (IL-6), mouse lipoic acid synthase (LIAS), and mouse ferroredoxin 1 (FDX1) ELISA kits were all purchased from Jiangsu Enzyme Immunoassay Co., Ltd., China.

[0072] 3. Synthesis of GFC and GLC:

[0073] First, GHKLVFF, GHKFVLF, and CIKRG peptides were prepared using a standard solid-phase synthesis (SPPS) method. For GFC synthesis, GHKLVFF (10.39 mg, 0.01 mmol), Cur (36.8 mg, 0.1 mmol), EDC (59 mg, 0.3 mmol), and DMAP (37 mg, 0.3 mmol) were dissolved in 5 mL of anhydrous DMF. The reaction mixture was stirred at room temperature for 48 h. After the reaction was complete, cold diethyl ether was added to precipitate the product. The product was collected by centrifugation, washed three times with cold diethyl ether, and dried to obtain the crude GFC. Following the same procedure, GLC was synthesized under the same conditions using the corresponding peptides and curcumin.

[0074] 4. IE Synthesis

[0075] 10 mg CIKRG peptide and 10 mg DSPE-PEG 2000 -Mal was dissolved in 2 mL of anhydrous DMF and stirred for 96 h in the dark under nitrogen protection at room temperature. After the reaction, the mixture was transferred to a dialysis bag (MWCO 2000 Da) and dialyzed under deionized water for 12 h, followed by lyophilization to obtain the final product (DSPE-PEG). 2000 -IKRG). Finally, 10 mg of the product was reacted with 100 μL LEVs (10 9 particles mL -1 The target IE complex was obtained by incubation in the dark at 4°C for 24 h. To evaluate the grafting rate, Cy5-labeled DSPE-PEG was prepared. 2000 -IKRG, and the grafting rate was determined using fluorescence spectroscopy.

[0076] 5. Combining GFC@IE:

[0077] To prepare the GFC@IE complex, take 0.5 mL of IE (10 9 particles mL -1 ) and 0.5mLGFC (10 9 particles mL -1 The mixture was then ultrasonicated at 4°C for 10 min. Subsequently, the resulting mixture was slowly extruded through a small extruder to obtain a uniform GFC@IE.

[0078] To optimize the composite conditions, the effect of different IE to GFC ratios on loading efficiency was investigated. Specifically, DiO-labeled IE and Cy5-labeled GFC were mixed in ratios of 1:6, 1:3, 1:1, 3:1, and 6:1 and incubated at room temperature for 12 h. Subsequently, the mixed samples were dropped onto glass slides, and images of five fields of view were randomly acquired using a fluorescence microscope. Image analysis was used to quantify the total number of particles exhibiting double-label overlap (Ntotal) and the number of yellow particles (Nyellow) in each field. The overlap rate (Noverlapped%) was calculated as (Nyellow / Ntotal × 100%) to evaluate the loading efficiency of GFC and IE at different ratios, thereby determining the optimal ratio.

[0079] 6. Detection of hydroxyl radicals using TMB:

[0080] First, TMB was dissolved in anhydrous ethanol to prepare a 10 mM stock solution. Then, 100 μL of the 10 mM TMB stock solution, 20 μL of 10 mM hydrogen peroxide solution, and 780 μL of PBS buffer (pH 7.4) were added sequentially to the reaction system. An equal volume (100 μL) of GLC, GFC, or Cu-GFC solution (each with a final concentration of 1 mM) was added. After vortex mixing, the absorbance of the reaction system was continuously monitored in the 550–750 nm wavelength range using a micro spectrophotometer to evaluate its catalytic activity for TMB oxidation.

[0081] 7. Detection of peroxide anions using DPBF:

[0082] All operations were performed under light-protected conditions. At a constant temperature of 37°C, phosphate buffer (pH 7.4), nanomaterial dispersions of varying concentrations (uniformly dispersed by sonication), xanthine aqueous solution (final concentration 0.075 mM), and DPBF ethanol stock solution (final concentration 100 µM) were added sequentially to a quartz cuvette. After gentle shaking to mix, XOD solution (final concentration 0.0167 U / mL) was rapidly added to initiate the enzymatic reaction. XOD catalyzes the oxidation of xanthine to uric acid, thereby stably generating superoxide anions. The generated superoxide anions oxidize the DPBF probe, which is sensitive to reactive oxygen species, causing a decrease in the intensity of its characteristic absorption peak at 410 nm.

[0083] 8. In vitro copper ion responsiveness:

[0084] First, the peptide GFC was dissolved in phosphate-buffered saline (PBS, pH 7.4) to prepare a 4 mM stock solution, which was then diluted to a working solution concentration of 1 mM. Different equivalents of Cu were then added to the working solution. 2+(0, 0.2, 0.4, 0.5, 0.6, 0.8, and 1.0 eq). After thorough mixing, the samples were annealed at 80 °C for 30 min, and then slowly cooled to room temperature to complete assembly. The morphology of the resulting assemblies was observed using transmission electron microscopy. Simultaneously, the degree of β-sheet was assessed using thioflavin T (ThT) fluorescence assay. Specifically, 10 μM ThT dye was added to each group of samples, and after overnight incubation at 37 °C, fluorescence intensities from 450 to 600 nm were recorded, with an excitation wavelength of 421 nm, thus systematically evaluating Cu. 2+ How does concentration affect peptide self-assembly?

[0085] 9. All-atom molecular dynamics (MD) simulations:

[0086] Molecular dynamics simulations were performed using GROMACS (version 5.1.5) to investigate the self-assembly process of the coordination compounds. The simulation system was run under closed conditions with a temperature set at 25°C, pH adjusted to 7.4, and pressure fixed at 1 bar. A GROMACS-compatible molecular topology file was generated using the AmberTools suite, the molecular structure was converted to ITP format, and ligand atoms were treated with a GAFF2 force field. The TIP3P water model was used for dissolution. Energy minimization was performed for all atoms using the steepest descent method. Position-constrained simulations were then performed: first, 1000 ps of NVT (number, volume, and temperature) equilibration, followed by 1000 ps of NPT (constant number, pressure, and temperature) equilibration. After the NVT and NPT equilibration steps, a 100 ns production run was performed with a time step of 2 fs.

[0087] 10. Cell lines and animals:

[0088] HT22 cells, MSCs, BV2, and bEnd.3 cell lines were purchased from Shanghai Xinyu Biotechnology Co., Ltd. (Shanghai, China). Cells were cultured in DMEM complete medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin-amphoteric B at 37°C and 5% CO2. TX mice carrying the ATP7B gene mutation (C3He-ATP7B) were also included. tx-j Purchased from Jackson Laboratory Animal Center (Maine, USA). 11. In vitro BBB penetration:

[0089] An in vitro blood-brain barrier (BBB) ​​model was established using Transwell chambers. bEnd.3 cells were cultured at 5 × 10⁶ cells per well. 4Cells were seeded at a density of [number] cells per cell in the upper chamber (0.4 μm pore size) and cultured for 10 days to form a confluent monolayer. HT22 cells were then seeded in the lower chamber and treated with CuSO4 for 24 h. Cy5-labeled test samples (5 μM each) were then added to the upper chamber, and the co-culture system was incubated for another 24 h. After incubation, cells were collected from both the upper and lower chambers, stained with DiO2 (10 μM) for 15 min, and then stained with DAPI (5 μg·mL⁻¹). -1 Stain for 10 minutes. Observe the stained HT22 cells using a fluorescence microscope and IVIS imaging system.

[0090] Penetration rate is calculated using the following formula:

[0091] Transmittance (%) = (Fluorescence intensity of Cy5 in the lower chamber / Sum of fluorescence intensities of Cy5 in the upper and lower chambers) × 100%.

[0092] 12. Cellular uptake:

[0093] HT22 cells were spaced at 5 × 10⁶ cells per well. 4 Cells were seeded at a density of [number] cells / mL in confocal culture dishes and cultured overnight. After treatment with 300 μM CuSO4 for 24 h, the cells were further co-incubated with 5 μM Cy5-labeled test samples for 4 h. Subsequently, the cells were treated with DiO2 (10 μM, 15 min) and DAPI (5 μg / mL). -1 Staining was performed (10 min), and fluorescence images were acquired using a confocal laser scanning microscope (CLSM).

[0094] For the endocytosis inhibition experiment, HT22 cells were spaced at 5 × 10⁶ cells per well. 4 Cells were seeded at a density of [number] cells / well in 6-well plates and treated using the same method. Subsequently, cells were treated with 10 μM chlorpromazine (CPZ), 1 mM amiloride, or 5 mM methyl-β-cyclodextrin (MβCD) to inhibit different endocytic pathways, and then co-incubated with a 5 μM DiO2-labeled sample for 4 h. After cell collection, fluorescence intensity was detected by flow cytometry.

[0095] 13 Cu 2+ Cleared real-time confocal fluorescence imaging

[0096] HT22 cells were seeded at a density of 5 × 10⁶ cells / year. 3 mL of cells -1 In a confocal culture dish, 300 μM CuSO4 was added and incubated for 24 h. The mixture was then rinsed with PBS, followed by the addition of 200 μL Cu. 2+ The fluorescent probe (1 μM) was incubated in the dark at 37°C for 30 min. After recording began, GFC@IE (5 μM) was added to the culture dish, and fluorescence changes were recorded for 120 min to observe intracellular Cu. 2+Changes in fluorescence intensity.

[0097] 14. Mitochondrial morphology analysis:

[0098] HT22 cells were planted at a density of 1 × 10⁶ cells per well. 4 Cells were seeded at a density of 100 μL in 96-well plates and cultured for 24 h to ensure complete adhesion. Subsequently, cells in designated groups were exposed to copper sulfate solution for 24 h, followed by co-incubation with each sample for another 24 h. After treatment, cells were washed three times with PBS to remove uninternalized nanoparticles. Next, cells were incubated with 100 μL of 100 nM Mito-Tracker Green dye at 37 °C in the dark for 30 min. Fluorescence imaging was then performed using a high-content imaging system. Finally, mitochondrial network parameters (including mean branch length, mean shape factor, and mean area) were quantitatively assessed using ImageJ / Fiji software with the MiNA plugin.

[0099] 15. Oxygen Consumption Rate (OCR) Measurement:

[0100] Mitochondrial function was assessed using a Seahorse XF96 Cell Energy Metabolism Analyzer by measuring oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). HT22 cells were cultured at 5 × 10⁶ cells per well. 3 Cells were seeded at a density of 100 μM into XF96 cell culture microplates and cultured at 37°C for 24 h to allow them to adhere. After treatment with 300 μM CuSO4 for 24 h, the cells were co-incubated with different samples for another 24 h. The Seahorse XF calibration plate was equilibrated overnight at 37°C without carbon dioxide the day before the experiment. Before measurement, the culture medium in the cell culture plate was replaced with OCR and ECAR detection reagents, respectively, and incubated at 37°C without carbon dioxide for 60 min. During the experiment, the instrument automatically injected oligomycin (1.5 μM), FCCP (1.0 μM), and rotenone / antimycin A (Rot / AA, 0.5 μM) to measure OCR. For ECAR measurement, 0.5 μM glucose, 50 mM oligomycin, and 2-deoxyglucose (2-DG) were added sequentially. Finally, the OCR and ECAR values ​​were standardized based on cell count.

[0101] 16. Cell viability assay:

[0102] HT22 cells were seeded into 96-well plates at a density of 1 × 10⁶ cells per well. 4Cells were cultured for 24 hours to allow them to adhere. The model group was treated with CuSO4 at a final concentration of 300 μM and incubated for another 24 hours to establish a cell model. The experimental groups were subsequently treated with different concentrations (0.25, 0.5, 1, 2.5, 5, and 10 μM) of GFC@IE for 24 hours. Cell viability was determined using the CCK-8 assay. Furthermore, cell viability assessments at different sample treatments and time points were performed following the same procedures.

[0103] To further investigate cell viability, a live / dead staining assay was performed. HT22 cells were cultured at 5 × 10⁶ cells per dish. 4 Cells were seeded at a density of [number] cells per confocal culture dish. The cell model establishment and drug administration methods were consistent with the CCK-8 experiment described above. After treatment, cells were stained with calcein-AM (2 mM, for live cells) and propidium iodide (PI, 1 mg / mL, for dead cells) for 20 min. Fluorescence images were then acquired using an inverted microscope.

[0104] 17. Enzyme-linked immunosorbent assay (ELISA):

[0105] HT22 cells were treated as described above, and different samples (normal group, model group, Cur group, GFC, GFC@E group, GLC@IE group, GFC@IE group) were collected. Cells were disrupted using an ultrasonic disruptor to release intracellular components, and the supernatant was collected by centrifugation at 2000 rpm and 2-8℃. The levels of FDX1, LIAS, TNF-α, IL-4, IL-6, IL-10, ATP, AKG, SUCN, Nrf2, and PrP were then measured using a specific ELISA kit.

[0106] 18. Internal treatment plan:

[0107] Male homozygous TX mice (6-8 weeks old) were randomly divided into six experimental groups: model group, Cur group, GFC group, GFC@E group, GLC@IE group, and GFC@IE group. Age-matched homologous DL mice were used as the control group (n=5 per group). Mice in the experimental groups received tail vein injections of the corresponding sample twice weekly (200 μL, 10 mg / kg). -1 The control group received the same amount of PBS. The total treatment duration was 28 days. Cognitive function was assessed using the Morris water maze test, mine site test, Y-maze test, and new object recognition test.

[0108] 19. In vivo biodistribution and pharmacokinetic studies:

[0109] To assess the in vivo distribution of nanoparticles, WD mice were administered 200 μL of free Cy5 or Cy5-labeled GFC@IE (10 mg / kg) via tail vein injection. -1Subsequently, imaging was performed using the IVIS system at 0, 1, 5, 9, 12, and 24 hours post-injection. In in vitro imaging, mice were euthanized after in vivo imaging, and brain, heart, liver, spleen, lung, and kidney organs were collected. Cy5 fluorescence signals in each organ were observed using the IVIS system.

[0110] 20. Immunofluorescence staining and brain cytokine measurement:

[0111] After treatment, major organs (heart, liver, spleen, lung, kidney, and brain) of mice in each experimental group were collected and fixed in 4% paraformaldehyde. Brain tissue was then embedded in paraffin and cut into 3 μm thick sections. Immunofluorescence staining was used to detect the expression of FDX1 and DLAT in the hippocampus. Simultaneously, the remaining organs were embedded in paraffin and prepared into 5 μm thick sections for H&E staining. Furthermore, specific detection kits were used to quantify the levels of cytokines (TNF-α, IL-10, IL-6, and IL-4) in the hippocampus of mice in each group.

[0112] 21. In vivo safety assessment:

[0113] Different concentrations of GFC@IE solution (500 μL) were mixed with an equal volume (500 μL) of 2% (v / v) erythrocyte suspension in 1.5 mL centrifuge tubes to form the sample group. Ultrapure water was used as the positive control (PC), and physiological saline was used as the negative control (NC). After incubation at 37°C for 2 h, the mixture was centrifuged at 360 × g for 10 min. Subsequently, 200 μL of the supernatant was transferred to a 96-well plate, and the absorbance was measured at 540 nm using a microplate reader. The hemolysis rate was calculated using the following formula: Hemolysis rate (%) = (A − An) / (Ap − An) × 100%, where A is the absorbance of the sample group, Ap is the absorbance of the positive control, and An is the absorbance of the negative control.

[0114] 22. Statistical Analysis:

[0115] All experiments were repeated at least three times. Statistical significance was assessed using Student's test for pairwise comparisons, and multiple group comparisons were performed using one-way or two-way ANOVA followed by Tukey's post-hoc test. Data analysis was conducted using GraphPadPrism software (version 9.5). A p-value < 0.05 was considered statistically significant.

[0116] Example 2: Experimental Results

[0117] 1. Clinical and animal experiments have confirmed that neuronal copper death is a key pathological mechanism of cognitive impairment in WD.

[0118] To clarify the core pathological features of WDCI, clinically diagnosed WD patients and healthy controls were included. Relevant clinical and imaging indicators were then measured. Figure 2a). Ceruloplasmin (CP) is a core biomarker for the clinical diagnosis of WD, and magnetic resonance imaging (MRI) can directly observe pathological changes related to copper deposition in the brain. The combined use of these two methods assesses systemic copper metabolism abnormalities and brain copper accumulation. Results showed that CP levels in WD patients were significantly lower than in healthy controls ( Figure 2 b). Further cranial MRI showed that the basal ganglia region of WD patients exhibited symmetrical low signal intensity on T1-weighted images (T1WI), while showing high signal intensity on T2-weighted images (T2WI) and fluid attenuation inversion recovery (FLAIR) sequences. Figure 2 c), this imaging feature is highly consistent with the typical characteristics of abnormal copper accumulation in the brain, and the decrease in serum CP further confirms that the subjects conform to the pathological features of WD. Subsequently, cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). The total scores of WD patients on both scales were significantly lower than those of healthy controls ( Figure 2 (d, e) indicates that WD patients have clear cognitive impairment. Previous studies have shown that the hippocampus is a key brain region regulating episodic memory formation, spatial cognition, and learning and memory consolidation, and its dysfunction is a core pathological basis of cognitive impairment (CI) in various neurological diseases. Considering that excessive copper accumulation in the hippocampus of WD patients may induce neurological damage, hippocampal magnetic resonance spectroscopy (MRI) was performed on WDCI patients. 1 H-MRS (Hypertrophic Metabolic Strain Reduction) is used to assess neuronal functional integrity. This technique reflects neuronal survival and functional status by detecting changes in the levels of characteristic neurometabolites in the brain. N-acetylaspartate (NAA) is a neuron-specific biomarker, and its ratio to creatine (Cr) directly reflects the structural integrity and functional status of neurons. Results showed that NAA levels in the hippocampus of WDCI patients were significantly reduced, and the NAA / Cr ratio decreased by 36.26% compared to the control group. Figure 2 (f, g). These findings confirm significant neuronal damage in the hippocampus of patients with WDCI.

[0119] Recent research indicates that copper death, as a novel form of programmed cell death, is closely related to intracellular copper overload in its triggering mechanism. To clarify whether copper death activation exists in patients with WDCI, the expression levels of two key markers of copper death, ferroredoxin 1 (FDX1) and lipoic acid synthase (LIAS), were measured in serum. The results showed that, compared with the control group, the levels of FDX1 and LIAS in WDCI patients increased by 1.68-fold and 1.88-fold, respectively. Figure 2This finding suggests that the copper death pathway may be activated during the progression of WDCI. To further validate the association between copper death and WDCI in vivo, in vivo validation was performed using classic WD model mice. Morris water maze test results showed that WD mice had significantly longer escape latency, spent significantly less time in the target quadrant, and crossed fewer platforms. Figure 2 jl and Figure 13 This indicates that WD mice have impaired spatial learning and memory abilities. The results of the new object recognition experiment validated the CI phenotype of WD mice. Figure 14 Subsequently, the expression of copper death markers in the hippocampus of mice was detected by immunofluorescence staining. The results showed that the fluorescence intensity of FDX1 and DLAT in the hippocampus of WDCI mice was significantly higher than that in the control group. Figure 2 m and Figure 15 These findings directly demonstrate that copper death is a crucial driving mechanism for neuronal damage in WDCI.

[0120] Finally, proteomic sequencing analysis was performed on the hippocampal tissues of WDCI mice and normal control mice. Principal component analysis (PCA) showed significant differences in protein expression between the model group and the normal control group. Figure 16 a). Compared with the control group, the model group showed 737 differentially expressed proteins (DEPs), of which 364 were upregulated and 373 were downregulated. Figure 16 b). Subsequently, gene ontology (GO) functional enrichment analysis was performed on the DEPs. For example... Figure 2 As shown in n, copper ion influx, copper homeostasis imbalance, oxidative stress, and inflammation are the main enrichment pathways. Significant enrichment in the Kyoto Encyclopedia of Genetics and Genomes (KEGG) includes the tricarboxylic acid (TCA) cycle, pyruvate metabolism, and oxidative stress response pathways. Figure 2 Furthermore, protein-protein interaction (PPI) network analysis revealed that proteins involved in mitochondrial energy metabolism (Cox17, Pdha1, Sdhb) and proteins involved in oxidative stress responses (Sod1, Ndufs1, Txnrd1) formed tight interaction clusters. Figure 2 These findings suggest a self-amplifying vicious cycle between copper overload and mitochondrial dysfunction, ultimately driving the initiation and progression of neuronal copper death.

[0121] 2. Preparation and Characterization of GFCs

[0122] This invention constructs a Cur-peptide conjugate GFC with copper-responsive morphological transformation properties, which can self-assemble into nanoparticles. In the high copper environment of WD neurons, the GHK-responsive module triggers a conformational change by chelating copper ions, driving the GFC to transform from a nanoparticle structure into a nanofiber structure. Figure 3a). After peptide synthesis, curcumin molecules are covalently coupled to the C-terminus of the peptide ( Figure 17 Liquid chromatography-mass spectrometry (LC-MS) results confirmed the structural integrity and high purity of GFC. Figure 18 The UV-Vis absorption spectroscopy results show that GFC exhibits a characteristic absorption peak of Cur at approximately 435 nm. Figure 3 b), and the Zeta potential decreased from 16.4 mV before coupling to 7.9 mV (b). Figure 19 The above results confirm the successful coupling of curcumin and peptides. In vitro release experiments showed that GFC exhibited a slow but sustained release behavior within 72 hours, with a cumulative release rate of up to 80%. Figure 3 c). To verify the copper ion binding ability and response characteristics of GFC, X-ray photoelectron spectroscopy (XPS) was used to analyze the chemical valence state and coordination mode of copper ions. Full-spectrum scanning confirmed the presence of C, O, N, and Cu elements, and the Cu 2p spectrum showed characteristic peaks at 932.5 eV and 952.3 eV corresponding to Cu 2p3 / 2 and Cu 2p1 / 2, respectively, indicating that Cu... 2+ They were effectively chelated to form stable chelates. Figure 3 d). Inductively coupled plasma optical emission spectroscopy (ICP-OES) results showed that after co-incubation of GFC with copper chloride solution, the concentration of free copper ions in the solution was significantly reduced ( Figure 20 This further confirms its highly efficient copper ion binding ability.

[0123] Next, the morphological transformation behavior of GFCs under copper ion stimulation was investigated. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) results showed that, without the addition of Cu... 2+ At that time, GFC self-assembles into uniformly dispersed nanoparticles through intermolecular non-covalent interactions (hydrophobic interactions, hydrogen bonds), with an average particle size of approximately 130 nm. Figure 3 e, f), while when Cu is introduced 2+ Subsequently, Cu-GFC assembles to form a nanofiber structure. Figure 3 f). Atomic force microscopy (AFM) results show that the nanofibers are approximately 3 nm in height. Figure 3 g). The critical aggregation concentration (CAC) of copper ions before and after the response was determined by Nile Red fluorescence method. The CAC values ​​of the two groups of samples were 7.8 μM and 11.5 μM, respectively, indicating that GFCs have a strong tendency to aggregate. Figure 3 h). To further analyze Cu 2+ The microstructure of the morphological changes resulting from the stimulus response was characterized using circular dichroism (CD) chromatography. The results showed that GFC, when present alone, exhibited a typical random coil-like negative peak at 198 nm, while when combined with Cu... 2+After co-incubation (Cu-GFC), it exhibits typical β-sheet conformation spectral characteristics, characterized by a positive peak at 199 nm and a negative peak at 212 nm. Figure 3 i). Fourier transform infrared spectroscopy (FTIR) further confirmed this conformational transition, with GFC at 1640 cm⁻¹. -1 The characteristic absorption peak of random curling appears at 1689 cm⁻¹, while Cu-GFC shows a peak at 1689 cm⁻¹. -1 and 1632cm -1 The presence of a characteristic absorption peak for antiparallel β-sheets at this location confirms that the conformation of GFCs under copper ion stimulation changes from random coil to antiparallel β-sheets. Figure 3 (j) Notably, the LVFF polypeptide sequence, a self-assembling module in GFCs, inherently tends to form antiparallel β-sheets. Its ordered arrangement, driven by intermolecular hydrogen bonds and hydrophobic interactions, provides the structural basis for the copper ion-induced conformational change. These results indicate that copper ion stimulation transforms the conformation of GFCs from random coils to antiparallel β-sheets, thereby driving its morphological transformation from nanoparticles to nanofibers.

[0124] GHK tripeptide itself has antioxidant activity, and with Cu 2+ After coordination to form GFC conjugates, their free radical scavenging and oxidative damage inhibition capabilities are enhanced. It is also hypothesized that the high aspect ratio nanofiber structure formed after the response of copper ions can further amplify its antioxidant efficacy. To verify this hypothesis, a morphologically uniform GHKFVLF-Cur (GLC) conjugate was constructed as a control. This conjugate disrupts the structural basis for antiparallel β-sheet formation by altering the amino acid sequence of the LVFF self-assembly module. TEM results show that regardless of the presence of Cu... 2+ GLCs maintained their nanoparticle morphology, confirming that they lost their ability to respond to copper ions in morphological transformation. Figure 21 Based on this, the antioxidant properties of different groups of samples were compared. EPR results showed that GFC and Cu... 2+ After coordination to form nanofibers, the scavenging ability of Cu-GFC for hydroxyl radicals and superoxide anions was significantly enhanced compared to the uncoordinated group. Furthermore, under the same conditions, Cu-GFC forming nanofibers exhibited superior free radical scavenging ability compared to Cu which could only form nanoparticles. 2+ -GLC control group ( Figure 3 k, l). TMB and DPBF were used as trapping probes for hydroxyl radicals and superoxide anions, and the results were verified by UV-Vis spectrophotometry, consistent with EPR. Figure 3 m, n and Figure 22 The above results confirm that copper ion chelation not only enhances the inherent antioxidant activity of GHK peptides, but also further amplifies their ROS scavenging ability by triggering LVFF sequence-mediated morphological transformation to form high specific surface area nanofibers.

[0125] 3. Dynamic processes and molecular mechanisms by which copper ions regulate the morphological transformation of GFCs

[0126] Previous characterization has confirmed that GFCs can undergo a copper-responsive "sphere-to-line" morphological transition, but the underlying regulatory mechanism remains unclear. Literature reports that GHK peptides can react with Cu via the imidazole group of histidine residues and the amino group of lysine residues. 2+ A stable coordination structure with a 1:1 coordination ratio is formed, providing the structural basis for the GHK module to function as a copper ion-responsive "trigger". First, TEM was used to investigate the effects of different Cu concentrations. 2+ The effect on the morphology of the assembly was observed to be related to the change in Cu content. 2+ With increasing concentration, the initially uniformly dispersed nanoparticles gradually dissociate and recombine into nanofiber structures. Figure 4 a). Thioflavin T (ThT) is a specific fluorescent probe for β-sheet structures. The dynamic formation process of β-sheet structures induced by copper ions was verified using ThT fluorescence spectroscopy. The fluorescence intensity increased with increasing Cu content. 2+ The increase in the amount added is gradient-enhanced. Figure 4 (b) This aligns with the morphological evolution trend observed by TEM, confirming the regulation of secondary structure by metal-ligand coordination. UV-vis spectroscopy further reveals the kinetic characteristics of the coordination reaction. GHK and Cu 2+ After coordination, a characteristic absorption peak appears at 600 nm due to electronic transition, and the absorption intensity is similar to that of Cu. 2+ The amount added is positively correlated ( Figure 4 c), confirming the concentration dependence of the chelate.

[0127] To further elucidate the dynamic molecular mechanism of copper ion-driven morphology transformation, molecular dynamics (MD) simulations were conducted to compare the differences in GFC self-assembly behavior before and after copper ion chelation. The results show that without Cu... 2+ In the system, GFC maintained a relatively compact spherical assembly morphology throughout the 100 ns simulation period, without significant conformational stretching or structural rearrangement. Figure 4 d). And in Cu 2+ In the chelated system, Cu-GFC gradually disintegrates from an initial compact spherical structure during the simulation period, and the polypeptide molecules undergo axial extension and orderly arrangement, eventually forming a regular linear layered assembly structure. Figure 4 e). Cu 2+ After chelation, the root mean square deviation (RMSD) of Cu-GFC increases rapidly in the early stages of the simulation, and then enters a stable convergence state after 20 ns, while the Cu-free GFC exhibits a similar pattern. 2+ The RMSD of the system remained stable at a low level throughout the process, indicating that Cu 2+ This caused significant perturbation to the GFC assembly structure. Figure 23 a). Cyclotron radius (Rg) analysis shows that Cu 2+ After binding, the Rg of Cu-GFC stabilizes at 37.46 Å, which is significantly higher than that without Cu. 2+ The system's 34.72 Å density confirms its transformation from a compact spherical structure to an extended fiber structure. Figure 23 b). During the morphological transformation, the intermolecular interactions were also significantly reshaped. Notably, in Cu... 2+ More intermolecular hydrogen bonds were formed in the chelation system, indicating that the formation of the nanofiber structure was accompanied by the enhancement of the hydrogen bond network. Figure 4 f). A key cation-π stacking interaction is formed between the cationic side chain of lysine (Lys) and the benzene ring side chain of phenylalanine (Phe) in the polypeptide sequence. Figure 4 g), and at the same time, the π-π interactions between Phe side chains are also significantly enhanced ( Figure 4 h). This result indicates that Cu 2+ The binding process enhances intermolecular attraction, promoting the formation of an ordered assembly structure. Finally, thermodynamic parameter analysis reveals the energetic basis of the morphological transformation. The results show that the total entropy change (TΔS), Gibbs free energy, and binding free energy of the Cu-GF system are significantly lower than those of the GFC system. Figure 4 (ik), indicating Cu 2+ Coordination leads to a lower energy state in the assembly, significantly improving thermodynamic stability. Based on the above experimental results, the molecular mechanism of copper ion-induced morphological transformation was analyzed. Without copper ion chelation, the Cur module exhibits strong hydrophobic interactions, which may, to some extent, interfere with or weaken the intermolecular interactions of the LVFF self-assembly module, thus preferentially assembling GFC into nanoparticles. However, when the GHK module chelates Cu... 2+ Subsequently, metal coordination reconstructed the intermolecular interaction network of the LVFF assembly core, enhancing multiple non-covalent interactions such as hydrogen bonding, cation-π and π-π stacking, breaking the original thermodynamic equilibrium of the nanoparticles, driving the polypeptide molecules to arrange themselves in an orderly manner along the axis and extend their growth to form a β-sheet structure, ultimately achieving the morphological transformation from nanoparticles to nanofibers.

[0128] 4. Preparation and Characterization of GFC@IE

[0129] The physiological function of the blood-brain barrier (BBB) ​​is a core bottleneck limiting the efficiency of intrabrain delivery of drugs for treating central nervous system diseases. To achieve efficient intrabrain delivery of GFCs and precise targeting of hippocampal neurons, a composite nanodelivery system based on extracellular vesicle (EV) surface modification, GFC@IE, was constructed. Figure 5a) Extracellular vesicles derived from bone marrow mesenchymal stem cells were selected as delivery carriers. Due to their low immunogenicity, biocompatibility, and endogenous ability to cross the BBB, they have been proven to effectively improve the efficiency of central drug delivery. Furthermore, based on the specific binding ability of the brain-derived neurotrophic factor (BDNF)-derived peptide IKRG to the TrkB receptor highly expressed in hippocampal neurons, it was chemically modified to anchor it on the surface of EVs, achieving precise targeted delivery to hippocampal neurons. First, using the Michael addition reaction of maleimide (Mal) with thiol groups, CIKRG was coupled to DSPE-PEG. 2000 -Mal, to obtain DSPE-PEG 2000 -CIKRG conjugates ( Figure 24 ). DSPE-PEG 2000 -Mal 1 The peak at approximately 6.70 ppm in the HNMR results was identified as a characteristic peak of the Mal group. This peak disappeared after coupling with the CIKRG peptide, confirming that the peptide was successfully linked to DSPE-PEG. 2000 -Mal on ( Figure 25 ).

[0130] Based on this, the grafting rate of IKRG peptides on the surface of EVs was evaluated. Cy5-labeled DSPE-PEG was then used. 2000 -After co-incubation of CIKRG with EVs, the grafting rate of IKRG peptide on the surface of EVs was calculated to be 39.58%. Figure 5 (b, c). Based on the above results, GFC was further encapsulated into IE using co-extrusion technology to prepare GFC@IE. The stability of GFC@IE in PBS buffer and containing 10% fetal bovine serum (FBS) was investigated. Dynamic light scattering (DLS) results showed that the particle size distribution of the nanoparticles did not change significantly within 7 days. Figure 5 d), indicating that the nano-formulation possesses excellent stability. To investigate the effect of the quantitative ratio of GFC to IE on the preparation of GFC@IE, Cy5-labeled GFC (red fluorescence) and DiO-labeled IE (green fluorescence) were used in the experiment. Figure 5 e and Figure 5 As shown in f, the fluorescence of Cy5 and DiO overlapped most effectively at a GFC to IE ratio of 1:1, with a fusion efficiency of 80%. Therefore, subsequent studies determined the ideal GFC to IE ratio to be 1. TEM and DLS results showed that unmodified EVs exhibited a typical vesicle-like structure. After modification with IKRG peptide, the IE morphology remained intact, while after loading with GFC, the particles exhibited a more regular spherical shape and a more uniform particle size distribution. Figure 5 g, h and Figure 26Zeta potential results showed that the surface negative charge of EVs (-28.6 mV) increased to -12.9 mV after modification with IKRG peptide, while GFC@IE further increased to -3.94 mV. Figure 27 This difference in potential may be due to the presence of positive charges on the peptide side chain groups. Western blot (WB) analysis confirmed that GFC@IE expresses the EVs' signature membrane proteins CD63 and CD81 (… Figure 5 i) confirms that the entire modification and drug delivery process did not damage the membrane structure integrity of EVs.

[0131] 5 GFC@IE Precision Targeting Neuron Research

[0132] To evaluate the blood-brain barrier (BBB) ​​penetration ability, hippocampal neuronal targeted delivery efficiency, and intracellular behavior of GFC@IE, an in vitro BBB model was constructed. Brain microvascular endothelial cells (bEnd.3 cells) were seeded in the upper chamber of Transwell, and hippocampal neurons (HT22 cells) were seeded in the lower chamber to simulate the in vivo cross-BBB delivery process. Figure 6 a) Different samples (GFC, GFC@E, and GFC@IE) were incubated together with the dense bEnd.3 layer of the upper chamber. Subsequently, fluorescence imaging of the upper and lower chambers was performed using an in vivo imaging system (IVIS). Figure 6 As shown in b and 6c, the BBB penetration efficiencies of GFC@E and GFC@IE reached 70.16% and 72.29%, respectively, representing increases of 1.52-fold and 1.56-fold compared to free GFCs. This finding indicates that mesenchymal stem cell-derived EVs can significantly enhance the BBB penetration ability of GFCs. Subsequent confocal laser microscopy (CLSM) confirmed that GFC@IE can effectively cross the BBB barrier and be taken up by the underlying HT22 hippocampal neurons. Figure 28 ).

[0133] To verify the precise targeting ability of GFC@IE, multiple cell types, including HT22 cells, microglia (BV2 cells), and bEnd.3 cells, were evaluated. CLSM and flow cytometry analyses showed that HT22 cells exhibited the highest uptake efficiency of GFC@IE, with mean fluorescence intensities 3.47 times and 2.40 times higher than those of BV2 and bEnd.3 cells, respectively. Figure 6 e, f). This finding demonstrates that GFC@IE possesses exceptional precision targeting capabilities. Flow cytometry analysis showed that HT22 cells exhibited time-dependent cell uptake of different samples, and were significantly higher than the GLC@IE group after 4 hours of incubation. Figure 6Previous studies have reported that IKRG peptides mimic the active domain of BDNF and specifically bind to the TrkB receptor, which is highly expressed on the surface of hippocampal neurons. Competitive binding experiments were conducted using free IKRG peptides to validate this targeting mechanism. HT22 cells were pretreated with free IKRG peptides to saturate the membrane TrkB receptors. This pretreatment reduced the uptake efficiency of GFC@IE by 70.64% compared to the untreated group. This confirms that the precise neuronal targeting of GFC@IE is mediated by the specific binding interaction between IKRG and the TrkB receptor. Figure 6 i).

[0134] The uptake mechanism of GFC@IE in HT22 cells was then investigated using pretreatment with various endocytosis inhibitors. HT22 cells were pretreated with methyl-β-cyclodextrin (MβCD, a caveolin-mediated endocytosis inhibitor), chlorpromazine (CPZ, a clathrin-mediated endocytosis inhibitor), amiloride (a macropinocytosis pathway inhibitor), and low temperature (4℃). Flow cytometry results showed that 4℃ low temperature treatment significantly inhibited the uptake efficiency of HT22 cells, indicating that the uptake mechanism depends on energy endocytosis. Furthermore, only the MβCD pretreatment group had no significant effect on the uptake efficiency of GFC@IE. Figure 6 (j) indicates that its endocytosis mainly relies on clathrin-mediated endocytosis and macropinocytosis pathways. Finally, biotransmission electron microscopy (Bio-TEM) was used to observe the morphological changes of the nanoparticles after entering the cells. The results showed that GFC@IE self-assembled into nanofibers under the induction of a high copper intracellular environment. Figure 6 k), while GLC@IE, with its uniform morphology, always maintains a nanoparticle structure (k), Figure 6 l). This morphological difference is similar to that of in vitro Cu. 2+ The consistent response characteristics confirm that copper ion-triggered morphological changes can occur in situ within cells. In summary, the GFC@IE nanodelivery system possesses the ability to penetrate the blood-brain barrier and precisely target hippocampal neurons. Upon entering the neurons, it responds to the high-copper intracellular environment to complete morphological changes, providing an efficient delivery system to support its long-term synergistic intervention in the treatment of cognitive impairment in WD disease.

[0135] 6. Regulatory effects of GFC@IE on neuronal copper overload and mitochondrial dysfunction

[0136] The core pathological feature of WDCI is the abnormal accumulation of intracellular copper ions, which ultimately leads to neuronal damage by inducing oxidative stress and mitochondrial dysfunction. Based on research findings on the construction, targeted delivery, and intracellular morphological transformation of copper death inhibitors, this study evaluated the regulatory role of GFC@IE in neuronal copper overload and mitochondrial dysfunction. Figure 7a). First, a copper overload cell model was established to investigate the ability of GFC@IE to clear excess copper ions in neurons. CLSM and flow cytometry results showed that the intracellular copper ion fluorescence intensity was weakest in GFC@IE-treated cells. The intracellular copper ion fluorescence intensity in the model group decreased to 29.94% ( Figure 7 b and Figure 29 , 30 Notably, the copper chelating effect of GFC@IE was comparable to that of the clinical copper chelator sodium dimethylpropane sulfonate (DMPS). This effect may be attributed to the synergistic effect of GFC@IE in inhibiting PrP-mediated extracellular copper influx and simultaneously chelating intracellular copper ions through GHK peptides. Dynamic monitoring showed that intracellular copper ion levels decreased after GFC@IE treatment, decreasing by 46.01% compared to the initial level after 20 min. Figure 7 c). Under the pathological state of WDCI, excessive copper ions can catalyze the production of large amounts of ROS through the Fenton reaction, thereby inducing oxidative stress damage. Intracellular ROS levels in different groups were detected using the ROS fluorescent probe DCFH-DA. The results showed that high-concentration copper ion stimulation increased intracellular ROS fluorescence intensity by 5.81-fold. In contrast, GFC@IE treatment showed the most significant ROS scavenging effect, with fluorescence intensity reduced by 59.27% ​​compared to the model group. Figure 7 d and Figure 31 , 32 )

[0137] Given that oxidative stress is a key factor in inducing mitochondrial damage, excessive ROS can disrupt mitochondrial membrane stability, leading to loss of membrane potential and structural damage, thereby causing mitochondrial dysfunction. Changes in mitochondrial membrane potential (Δψm) were detected using the JC-1 fluorescent probe. JC-1 staining showed that mitochondria in the model group were predominantly green monomers, indicating a significant decrease in membrane potential. After GFC@IE treatment, the damaged mitochondrial function was restored, exhibiting a normal state with predominantly red aggregates. Figure 33 Flow cytometry quantitative analysis showed that the red / green fluorescence ratio of JC-1 in the model group was 1.12, while it significantly increased to 6.14 in the GFC@IE treatment group, approaching the level of the control group. Figure 7 e, f). To elucidate the protective effect of GFC@IE on mitochondrial structure, morphological analysis was performed using MitoTracker staining. (e.g., f.) Figure 7 g, h and Figure 34As shown, copper overload induced severe fragmentation of neuronal mitochondria. However, GFC@IE treatment significantly improved mitochondrial branch length, mean morphology factor, and mean area compared to the model group. Bio-TEM observations further confirmed that mitochondria in the model group neurons exhibited typical damage characteristics, including increased membrane density and reduced or even absent cristae. In contrast, GFC@IE treatment significantly improved mitochondrial morphology, restored clear and intact cristae, and significantly reduced vacuolation. These findings indicate that GFC@IE effectively repairs mitochondrial structure (…). Figure 7 i).

[0138] To investigate the metabolic regulatory mechanism by which GFC@IE improves mitochondrial function, the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were monitored in real time using a Seahorse XF energy metabolism analyzer. OCR results showed that copper overload significantly reduced basal respiratory level, ATP-coupled respiration, and maximum respiratory capacity. GFC@IE treatment significantly reversed the inhibition of mitochondrial oxidative phosphorylation induced by copper overload. Figure 7 j, k and Figure 35 ECAR measurements showed that glycolysis, glycolytic capacity, and non-glycolytic acidification were significantly increased in the model group, indicating that cellular energy metabolism shifted to the glycolytic pathway after impaired mitochondrial oxidative phosphorylation. GFC@IE treatment downregulated abnormally elevated glycolysis-related parameters and restored normal cellular energy metabolism. Figure 7 l, m and Figure 36 ELISA quantitative analysis further revealed a significant decrease in intracellular levels of key TCA cycle metabolites, including succinate (SUCN), α-ketoglutarate (AKG), and ATP, in the model group, indicating TCA cycle obstruction. Compared to the model group, GFC@IE treatment increased SUCN, AKG, and ATP levels by 1.94-fold, 2.58-fold, and 4.45-fold, respectively. This suggests that the inhibitor restores cellular energy homeostasis by repairing mitochondrial function. Figure 37 Overall, GFC@IE can completely break the vicious cycle of copper overload and mitochondrial dysfunction through the synergistic effect of regulating intracellular copper levels and restoring mitochondrial function.

[0139] 7. Study on the inhibitory effect and mechanism of GFC@IE on neuronal copper death

[0140] To clarify the protective effect of GFC@IE on neurons, the optimal treatment concentration of 5 μM and the optimal treatment time of 24 h were first determined through CCK-8 assay screening. Figure 38 Under these optimized conditions, the neuroprotective effects of different samples were compared and evaluated. Figure 8As shown in Figure a, the cell viability after GFC@IE treatment reached 87.75%, the highest among all groups. The protective effect of GFC@IE was also superior to the positive control drug DMPS. This may be attributed to the synergistic effect of GFC@IE in regulating intracellular copper levels and repairing mitochondrial function. Live / dead cell staining with calcein-AM and propidium iodide (PI) further confirmed this result. HT22 cells treated with GFC@IE showed a significant reduction in the number of red fluorescent (dead) cells, while exhibiting strong green fluorescence (live cells), confirming the neuroprotective ability of GFC@IE. Figure 8 b). To determine whether this neuroprotective effect is related to the inhibition of copper death pathway activation, the expression levels of copper death-related proteins were assessed by Western blot and immunofluorescence staining. The results showed that, compared to the normal control group, the levels of key copper death proteins—feroxonin 1 (FDX1), dihydrolipoic acid S-acetyltransferase (DLAT), and lipoic acid synthase (LIAS), as well as the downstream lipoylated dihydrolipoic acid S-acetyltransferase (Lip-DLAT)—were significantly upregulated in the model group. However, GFC@IE significantly reversed the abnormally high expression of these copper death-related proteins. Figure 8 c, d and Figure 39 Quantitative ELISA analysis further confirmed that, compared with the model group, GFC@IE treatment downregulated the expression levels of FDX1 and LIAS in hippocampal neurons by 78.45% and 66.36%, respectively. Figure 8 e). These results collectively confirm that GFC@IE exerts its neuroprotective effect by inhibiting the expression of FDX1 and LIAS and reducing aberrant thioacrylation of downstream proteins, thereby blocking the abnormal activation of the copper death core pathway. Figure 8 f).

[0141] Based on the pathological vicious cycle of neuronal copper death, the regulatory role of GFC@IE on Nrf2 and PrP was evaluated. ELISA results showed that, compared with the model group, the Nrf2 expression level in the GFC@IE group was upregulated by 3.08 times (…). Figure 40 Previous studies have shown that Nrf2 activation downregulates PrP expression, thereby persistently inhibiting extracellular copper influx. Subsequent examination of PrP expression revealed significantly increased PrP levels in the model group, while GFC@IE treatment significantly inhibited expression. Figure 41These results collectively demonstrate that GFC@IE can effectively inhibit the continuous influx of copper ions by blocking the feedback loop of Nrf2-PrP-copper overload, thereby breaking the vicious cycle of "PrP overexpression - increased copper influx - mitochondrial dysfunction - upregulation of PrP expression" in copper death. Furthermore, neuronal copper death is often accompanied by an inflammatory response. ELISA results showed that the GFC@IE treatment group significantly downregulated the expression of pro-inflammatory factors (TNF-α and IL-6) compared to the model group. Figure 8 g, h). Simultaneously upregulates the expression of anti-inflammatory factors (IL-4 and IL-10). Figure 8 These results indicate that GFC@IE effectively alleviates neuronal inflammatory responses.

[0142] 8. Evaluation of GFC@IE's in vivo targeting ability

[0143] To evaluate the in vivo targeting ability of GFC@IE, blood compatibility was first assessed, laying the foundation for subsequent in vivo safety experiments with intravenous administration. Hemolysis experiments were conducted using fresh whole blood from healthy homologous Dunn-Lewis (DL) mice. Results showed that the hemolysis rate of GFC@IE was less than 5% across the administered concentration range, confirming its excellent in vivo biocompatibility. Figure 42 Next, using WD cognitive impairment model mice as the research subjects, different samples labeled with Cy5 were administered via tail vein, and pharmacokinetic analysis and in vivo fluorescence imaging were performed. In vivo imaging system (IVIS) results showed that the fluorescence intensity of free Cy5 rapidly decayed within 24 hours after administration, with a half-life of only 1.33 hours. In contrast, GFC@IE significantly prolonged the in vivo circulation time, extending the half-life to 4.48 hours. Figure 9 (a, b) demonstrates that EV loading effectively slows the clearance rate of GFC@IE in vivo, providing the necessary conditions for its penetration of the BBB and targeting of neurons. Further dynamic monitoring of the distribution of different samples in the brain was conducted. Significant brain fluorescence signals were observed in the GFC@IE group 9 hours after tail vein injection, and the signal intensity continued to increase over time, remaining at a high level at 24 hours. Figure 9 c). Quantitative analysis showed that the brain fluorescence intensity of the GFC@IE group and the GFC@E group was significantly higher than that of the GFC group at all time points after drug administration, indicating that the natural blood-brain barrier penetration properties of EVs can improve the brain-targeted delivery efficiency of GFC@IE. Figure 9 e). Ex vivo imaging of major organs showed that the samples were mainly distributed in the liver, which is similar to the metabolic process of most other intravenously administered drugs. Figure 9(d, f). Furthermore, the neuronal targeting ability of GFC@IE is crucial for the therapeutic effect of WDCI. Brain tissue sections were collected 24 hours after administration to observe the colocalization between Cy5 fluorescence signal and microtubule-associated protein 2 (MAP2, a neuronal marker). Results showed high colocalization of Cy5 red fluorescence and MAP2 green fluorescence in the GFC@IE group, indicating that GFC@IE can accurately target hippocampal neurons. In contrast, no significant fluorescence colocalization was observed in GFC and GFC@E. Figure 9 This result confirms that the specific recognition of neuronal receptors by IKRG peptides is key to achieving efficient targeting. Flow cytometry analysis verified the targeting efficiency of GFC@IE across the BBB. The study found that the proportion of cells co-expressing Cy5 and MAP2 in the hippocampus of mice treated with GFC@IE reached 84.37%, an increase of 1.34 times compared to the GFC@E group. Figure 9 j). In summary, these results indicate that the synergistic effect of EV encapsulation and IKRG peptide modification endows GFC@IE with the ability to selectively accumulate in hippocampal neurons across the BBB.

[0144] 9. Evaluation of the therapeutic effect of GFC@IE on cognitive impairment in WD mice

[0145] To evaluate the in vivo therapeutic effect of GFC@IE, the classic WD animal model, the TX mouse, was used in the experiment. WD mice diagnosed with CI through behavioral testing were designated as WDCI model mice and included in subsequent experiments. Figure 10 As shown in figure a, WDCI mice received the drug for 28 consecutive days and underwent a series of cognitive behavioral tests to assess improvements in cognitive function. First, the Morris water maze test was used to assess the mice's spatial learning and memory abilities. (See figure a for details.) Figure 10 As shown in Figure 2, the model mice exhibited severe stereotyped boundary search behavior, with an escape latency of 57.90 s. In contrast, the GFC@IE WDCI mice showed spatially guided swimming paths, with a significantly shortened escape latency of 11.78 s. Furthermore, the time spent in the target quadrant and the number of platform crossings were further examined. The results showed that the memory performance of the GFC@IE group was significantly better than that of the model group and comparable to that of the control group. Figure 10 (e, f). Notably, GFC@IE outperformed the clinical copper chelator DMPS in spatial learning and memory retrieval. Subsequently, spatial reference memory and spatial recognition memory were assessed using the Y-maze test. Figure 10As shown in h, one arm was closed during the training phase to establish spatial memory. After 24 hours of testing, the previously closed arm was opened, and the number of entries and dwell time on the novel arm were recorded. Results showed that WDCI mice spent longer periods in the familiar arm, while the proportion of entries into the novel arm and the dwell time were significantly reduced, reflecting impaired spatial memory. After GFC@IE treatment, the mice exhibited a reverse exploration pattern, showing a strong preference for exploring the novel arm. Compared to the model group, the percentage of novel arm entries and the dwell time on the novel arm increased by 2.34 times and 2.88 times, respectively. Figure 10 i, j, k).

[0146] The non-spatial memory ability of mice was further evaluated using the Novel Object Recognition (NOR) test. During the testing phase, a familiar object was replaced with a new object during the training phase, and the exploration time for both objects was recorded. Figure 10 l). WDCI mice exhibited significantly shorter exploration time for novel objects and lower discrimination indices compared to the control group. GFC@IE treatment restored WDCI mice's ability to recognize novel objects to a level comparable to normal mice, increasing the discrimination index from -0.24 to 0.72 ( Figure 10 (m, n). Furthermore, no significant differences were observed in the exploration time for two identical objects among all groups during the training phase, confirming the consistency of baseline exploration behavior. Meanwhile, the position bias test eliminated interference from object position preferences, ensuring the reliability of the NOR results. Figure 43 Finally, the open field test (OFT) was used to assess spontaneous exploration behavior and motor abilities. The mice's movement trajectories in the open field were recorded over 5 minutes. Results showed that, compared to the control group, WDCI mice exhibited a shorter exploration distance in the central area, demonstrating avoidance behavior towards the center. After GFC@IE treatment, the preference for exploring the central area was significantly restored. Figure 44 and Figure 45 a). Furthermore, the total distance traveled and the average speed of the GFC@IE group increased by 1.79 times compared to the model group ( Figure 45 (b, c). Overall, these results indicate that GFC@IE significantly improved severely impaired spatial learning, spatial recognition, and non-spatial memory abilities in WDCI mice. GFC@IE demonstrated superior overall cognitive improvement compared to the clinical drug DMPS.

[0147] The therapeutic mechanism of 10 GFC@IE in improving cognitive impairment in WD mice

[0148] Based on the above behavioral results, we further investigated the neural repair mechanism by which GFC@IE improves cognitive function in WD mice. Figure 11 a) First, the copper content in mouse hippocampal tissue was detected using inductively coupled plasma mass spectrometry (ICP-MS). The results are as follows: Figure 11As shown in b, compared with the normal control group, the copper level in the hippocampus of WD cognitive impairment model mice was significantly increased. GFC@IE treatment significantly reduced the copper overload in the hippocampus, with copper content decreasing by 66.25% compared to the model group, demonstrating excellent ability to regulate copper homeostasis in the brain. Simultaneously, after GFC@IE treatment, the expression level of Nrf2 in the hippocampus was upregulated, while the expression of PrP was downregulated, confirming that GFC@IE downregulates PrP-mediated copper ion influx by activating Nrf2 activity. Figure 46 Mitochondrial dysfunction is a core component of copper death, such as... Figure 11 As shown in c, mitochondrial dysfunction is a core component of copper death formation; therefore, ELISA was used to quantitatively detect mitochondrial function-related indicators in mouse hippocampus. The results showed that, compared with the normal control group, the levels of SUCN, AKG, and ATP in the hippocampus of the model group mice were significantly decreased. Figure 11 The results (df) indicate that the mitochondrial tricarboxylic acid cycle is blocked and energy metabolism is severely disordered. In contrast, after GFC@IE treatment, the levels of SUCN, AKG, and ATP in the hippocampus of mice recovered to 2.03 times, 3.00 times, and 3.18 times that of the model group, respectively, confirming that GFC@IE can effectively repair mitochondrial functional damage caused by copper overload in vivo.

[0149] To clarify the role of GFC@IE in comprehensively inhibiting neuronal copper death, immunofluorescence staining was used to detect the expression of key copper death proteins in hippocampal tissue. The results showed that the fluorescence intensity of FDX1 and DLAT in the model group was significantly higher than that in the control group. Figure 11 g, Figure 47 This confirmed that cognitive impairment in WD was significantly associated with neuronal copper death. ELISA quantification further showed that, compared to the model group, the expression levels of FDX1 and LIAS in the hippocampus of mice treated with GFC@IE were downregulated by 84.53% and 82.98%, respectively. Figure 11 h、 Figure 48 This provides conclusive evidence that GFC@IE effectively inhibits neuronal copper death. Furthermore, copper death can further trigger neuroinflammatory responses in the brain, exacerbating neuronal damage and cognitive decline. The expression levels of inflammatory factors in the mouse hippocampus were detected by ELISA. The results showed that the expression levels of pro-inflammatory factors TNF-α and IL-6 were significantly increased, while the levels of anti-inflammatory factors IL-4 and IL-10 were significantly decreased in the model group. However, GFC@IE treatment significantly reversed the abnormal expression of these inflammatory factors, effectively alleviating the neuroinflammatory environment (…). Figure 11 il).

[0150] The protective effect of GFC@IE on mouse hippocampal neurons was further evaluated. 1H-MRS images showed a significantly decreased NAA / Cr ratio in the hippocampus of WD cognitively impaired mice compared to the control group, indicating severe damage to hippocampal neurons. After GFC@IE treatment, the NAA / Cr ratio significantly increased, recovering to levels close to the control group. Figure 11 m, n, Figure 49 Further immunofluorescence staining with neuronal nuclear antigen (NeuN) and hematoxylin and eosin (H&E) staining showed a reduction in the number of neurons in the hippocampus in the model group, while neuronal damage was significantly improved after GFC@IE treatment. Figure 11 o, Figure 50 The above results indicate that GFC@IE can effectively reduce neuronal damage in the hippocampus of WD cognitively impaired mice, exerting a neuroprotective effect. Finally, during the 28-day treatment period, no acute weight loss was observed in any group of mice. Figure 51 H&E staining of major organs (heart, liver, spleen, lungs, and kidneys) showed no significant pathological changes in any of the treatment groups. Figure 52 Routine blood test results were all within the normal range (Table 1). These results confirm that GFC@IE has good biocompatibility in vivo. In summary, GFC@IE effectively breaks the vicious cycle of copper influx and mitochondrial damage by synergistically regulating intracellular copper ion levels and repairing mitochondrial function, achieving comprehensive inhibition of neuronal copper death, thereby exerting a neuroprotective effect and improving cognitive dysfunction in WD mice, providing a new strategy for the treatment of cognitive impairment in WD patients.

[0151] Table 1. Routine blood analysis of mice after different sample treatments.

[0152] <![CDATA[White Blood Cell Count(10 9 L -1 )]]> 4.3 6.2 6.9 4.6 7.5 4.1 4.9 <![CDATA[Lymphocyte Count(10 9 L -1 )]]> 3.2 4.2 5.0 3.0 5.2 2.9 3.8 <![CDATA[Monocyte Count(10 9 L -1 )]]> 0.1 0.2 0.2 0.2 0.3 0.1 0.1 <![CDATA[Granulocyte Count(10 9 L -1 )]]> 1.0 1.8 1.7 1.4 2.0 1.1 1.0 Lymphocyte Percentage (%) 73.6 67.1 71.9 65.8 69.7 70.4 76.9 Monocyte Percentage (%) 2.7 3.1 3.9 3.5 3.9 3.7 3.6 Granulocyte Percentage 23.7 29.8 24.2 30.7 26.4 25.9 19.5 <![CDATA[Red Blood Cell(10 12 L -1 )]]> 9.07 9.46 9.96 9.6 9.91 10.7 10.27 <![CDATA[Hemoglobin(g L -1 )]]> 140 146 161 156 170 166 161 Hematocrit (%) 44.5 48.5 52.4 51.8 52.3 58.2 55.1 Mean Corpuscular Volume (fL) 49.1 51.3 52.7 54.0 52.8 54.4 53.7 Mean Corpuscular Hemoglobin(pg) 15.4 15.4 16.1 16.2 17.1 15.5 15.6 Mean Corpuscular Hemoglobin Concentration 314 301 307 301 325 285 292 RBC volume distributing width (%) 14.8 18.1 16.1 15.5 16.4 15.5 15.8 <![CDATA[Platelet Count(10 9 L -1 )]]> 1858 2136 1771 1423 1472 1217 1111

[0153] 11. Transcriptomic analysis of the mechanism by which GFC@IE improves cognitive dysfunction in WD mice

[0154] To elucidate the molecular mechanism by which GFC@IE improves cognitive impairment in WD at the gene level, transcriptome sequencing analysis was performed on the hippocampus tissue of mice in the GFC@IE treatment group and the model group. Venn diagrams showed that a total of 23,011 common genes were identified between the two groups. Figure 12 a). Volcano map analysis, such as Figure 12 As shown in Figure c, compared with the model group, a total of 1799 significantly differentially expressed genes were screened after GFC@IE treatment, of which 661 genes showed significantly upregulated expression levels (red dots) and 1138 genes showed significantly downregulated expression levels (blue dots). The clustering heatmap of differentially expressed genes further showed that in the model group, core regulatory genes of copper death (FDX1, LIAS, DLAT) and neuroinflammation-related genes (IL-1β, IL-16) were all significantly overexpressed. However, after GFC@IE treatment, all of the above genes showed significant downregulation. Figure 12b). Enrichment analysis by the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that after GFC@IE treatment, key pathways involved in hypoxic stress, neuroinflammation, and oxidative stress (NF-κB signaling pathway and MAPK signaling pathway) were downregulated. Figure 12 f), in contrast, pathways related to mitochondrial energy metabolism, synaptic transmission, and neuronal survival, such as the TCA cycle, oxidative phosphorylation, and cholinergic synapses, were significantly upregulated (f). Figure 12 g). Gene Ontology (GO) functional enrichment analysis showed that GFC@IE-downregulated pathways were closely related to the core pathology of WDCI, including cellular responses to copper ion influx and oxidative stress pathways. Simultaneously, pathways closely related to neuronal functional repair and cognitive improvement were significantly enriched. These included learning and memory, regulation of neuronal synaptic plasticity, and long-term synaptic enhancement (…). Figure 12 h、i).

[0155] The above results confirm the role of GFC@IE in inhibiting copper death and improving neuronal function. Furthermore, gene set enrichment analysis (GSEA) further confirmed the core role of GFC@IE in alleviating oxidative stress, restoring mitochondrial energy metabolism, and thus improving copper deposition-induced neuronal damage. Figure 12 d, e).

[0156] The transcriptomic analysis results confirmed the molecular mechanism by which GFC@IE comprehensively inhibits neuronal copper death: on the one hand, GFC@IE can inhibit the abnormal influx of copper ions into neurons by downregulating the transcriptional level of genes encoding copper ion transporters, thus blocking copper death at its source. On the other hand, GFC@IE can restore the mitochondrial TCA cycle and oxidative phosphorylation function, further blocking the progression of copper death, ultimately comprehensively inhibiting neuronal copper death and achieving effective improvement in cognitive impairment in WD. Figure 1 (As shown).

[0157] In summary, this invention establishes copper death as a key pathological driver of WDCI and develops a multi-stage intervention copper death inhibitor (GFC@IE). This inhibitor effectively targets neurons in the brain via engineered EVs. Utilizing the unique high-copper pathological microenvironment of WDCI, it triggers the in-situ self-assembly of GFCs from nanoparticles to nanofibers. This morphological transformation enhances the pharmacological activity of Cur and GHK peptides. Therefore, it completely breaks the vicious cycle of copper overload and mitochondrial dysfunction, achieving comprehensive inhibition at both the initiation and progression stages of neuronal death. In vitro and in vivo experiments show that Cur inhibits PrP-mediated copper ion influx by activating Nrf2 expression. This effect prevents the initiation of copper death at its source. Simultaneously, the GHK peptide repairs mitochondrial function while chelating excessive intracellular free copper, further blocking the progression of copper death. This synergistic effect effectively breaks the vicious cycle of copper overload and mitochondrial dysfunction, leading to the downregulation of key copper death proteins FDX1 and LIAS. Therefore, this inhibitor significantly improved spatial learning and memory deficits in WDCI mice through multi-step intervention of neuronal copper death, while exhibiting excellent biosafety. To date, this work represents the first comprehensive nanoplatform targeting the initiation and progression of copper death. This approach overcomes the limitations of current clinical WD therapies that focus solely on systemic copper clearance, and also surpasses the shortcomings of existing copper death intervention strategies that rely on single-step blockade. It highlights the significant advantages of multi-step synergistic copper death inhibition in the treatment of WDCI. This work provides a promising new strategy for the clinical treatment of WDCI and may offer a universal and feasible approach for various neurodegenerative diseases caused by copper death.

[0158] Furthermore, GFC@IE, as the first nanodelivery platform that comprehensively intervenes in the occurrence and development of copper death, has established a new approach to the precision treatment of cognitive impairment in WD and provided a complete pathway for research on the treatment of copper death-driven diseases.

Claims

1. A multi-stage intervention copper death inhibitor for treating cognitive impairment in Wilson's disease, characterized in that, The Cur-peptide conjugate (GFC) exhibits copper-responsive morphology transition properties and integrates three functional modules in its structure: GHK, as a response module, constitutes a morphological change "trigger"; LVFF, as a self-assembling module, serves as the structural basis for morphological transformation; Cur, as a drug module.

2. The multi-stage intervention copper death inhibitor for treating cognitive impairment in Wilson's disease as described in claim 1, characterized in that, Extracellular vesicles derived from mesenchymal stem cells were selected as delivery carriers, and their surfaces were modified with neuron-specific IKRG-targeting peptides (IKRG) (IE) to further enhance the blood-brain barrier (BBB) ​​penetration efficiency and precise neuronal targeting capability of the delivery system. Finally, GFCs were loaded into IKRG-EVs to construct a precise targeting-morphological transformation integrated nanodelivery system (GFC@IE).

3. The method for preparing the multi-stage intervention copper death inhibitor for treating cognitive impairment in Wilson's disease as described in claim 1 or 2, characterized in that, First, GHKLVFF was prepared by solid-phase synthesis, and then GHKLVFF-Cur (GFC) was prepared by chemical coupling. Second, extracellular vesicles (EVs) derived from mesenchymal stem cells were isolated and extracted, and IKRG-targeting peptides were modified on their surface by membrane insertion to obtain IKRG-EVs (IE). Finally, GFC and IE were mixed, and loaded by ultrasonic treatment and co-extrusion technology to obtain the precise targeting-morphological transformation integrated copper death inhibitor GFC@IE.

Images