These herbal extracts of GPCRAC were purchased from Shanxi Jiahe Biotechnology Co., Ltd. (Shanxi China). Scopolamine hydrobromide was purchased from Beijing Bailingwei Technology Co., Ltd., (Beijing China). Batch No. LI10Q53. Huperzine A (70 mg/tablet) was purchased from Henan Tai long Pharmaceutical Co., Ltd., (Henan China). Batch No.190202. Acetylcholine (Ach) assay kit, Choline acetyltransferase (ChAT) assay kit and Acetylcholinesterase (AchE) assay kit was purchased from Nanjing Jian Cheng Bioengineering Institute (Jiangsu, China).

GPCRAC extracts were prepared by Gastrodia elata Blume extract standardized to 1% Gastrodin (Batch No. C7M-A-803456), Polygala tenuifolia Willd extract standardized to 1% 3, 6′-Disinapoly sucrose (Batch No.CY2-A-808331), Acorus gramineus Aiton extract (10:1) (Batch No.CSCP-A-710215), Cistanche deserticola Ma extract standardized to 20% phenylethanol glycosides (Batch No.190501), Rehmannia lutinosa (Gaertn.)DC.extract (5:1) (Batch No. CSDH-A-900106), Curcuma longa L.extract standardized to 95% total curcuma (Batch No. CJH-A-908220) at the ratio of 1.25:0.67:0.18:0.3:0.125:0.1 (The ratio is based on the calculation of pharmacopoeia recommended dosage and extracts rate). The ratio of Curcuma longa L. extract used the low daily dose of curcumin recommended by the Chinese Pharmacopoeia (the recommended dosage is 200 mg). The phytochemical standardization and HPLC characteristic fingerprint for each herbal extract was completed by Shanxi Jiahe Biotechnology Co., Ltd., (Shanxi China) (see Supplementary Materials). Briefly, the crude drugs of Gastrodia elata Blume, Polygala tenuifolia Willd, Cistanche deserticola Ma were pulverized to powder and sieved through a 20-mesh sieve. Gastrodia elata Blume was extracted three times with 70% ethanol for 2 h each time. Polygala tenuifolia Willd was extracted three times with 80% ethanol for 2 h each time. Cistanche deserticola Ma was extracted three times with 50% ethanol for 2, 1.5, 1.5 h, with a liquid-to-material ratio of 6, 5, 4, respectively. Curcuma longa L. was extracted two times with 95% ethanol for 2 h each time. Acorus gramineus Aiton was soaked with 8-fold of water for 3h, and then extracted three times, each time for about 2 h. Rehmannia lutinosa (Gaertn.)DC. was soaked with 8-fold of water for 1 h and extracted three times for 2, 2, 1 h, respectively. These extracts were then filtered, condensed under vacuum, freeze-dried into powder.

Dionex Ultimate 3000 UHPLC system equipped with a binary pump, an autosampler, a solvent degasser, and a thermostatic column compartment (Thermo Fisher, Waltham, MA, United States) were used for analysis component of GPCRAC extracts. All chromatographic separations were performed on a BDS HYPERSIL C18 column (150 mm × 2.1 mm, 2.4 μm; Thermo Fisher Scientific). The mobile phase consisted of acetonitrile (A) and 0.1% formic acid aqueous solution at a flow rate of 0.3 ml/min, with gradient elution as follows: 0∼45 min, 95%B; 45.0–45.1 min, 25%B; 45.1–50 min,95%B. And the column temperature was set to 45°C. Mass Spectrometer (MS) detection was performed on a Q Exactive™ Plus mass spectrometer (Thermo Fisher Scientific, United States) equip ed with an electrospray ionization source (ESI) using a positive ion spray voltage of 3.5 k eV and a negative ion spray voltage of 3.0 k eV. The mass spectrometry conditions were as follows: the sheath gas and auxiliary gas was both high-purity nitrogen (purity>99.99%); the flow rates were 40 arbitrary units and 20 arbitrary units respectively; the capillary temperature was 320°C; the sheath gas flow rate was 35.0 μl/min, the aux gas flow rate was 10 μl/min, the sweep gas flow rate was 10 μl/min; The mass scanning range was m/z 120∼1800.

102 SPF male C57BL/6J mice (weight 20 ± 2 g) were used in our study. All animals were produced by Jinan Pengyue Experimental Animals Education Co., Ltd (Beijing, China). License number: SCXK (Lu) 2018-0,003.6. The feeding procedures of animals and experimental operations have been approved by the Animal Care and Use Committee of Beijing University of Chinese Medicine (BUCM-4-2019102105-4119). Mice were housed in cages and kept under standard breeding conditions (12:12 h light/dark cycle, controlled room temperature (23 ± 2°C), sanitary conditions, standard diets, and stress-free environment. After 1 week of accommodation, mice were randomly divided into six equal-sized groups: control group, model group (scopolamine hydrobromide of 3 mg/kg/day), HupA group (HuperzineA, positive drug), GPCRAC-L group (GPCRAC extracts of 128 mg/kg/day), GPCRAC-M group (GPCRAC extracts of 256 mg/kg/day), GPCRAC-H group (GPCRAC extracts of 512 mg/kg/day), every seventeen mice were divided into one group. The administration dosage of GPCRAC extracts was calculated using dosage conversion relationship between mice and human. All mice were administered intragastrically for 30 consecutive days. Behavioral tests were then performed to examine mouse cognitive deficits at 31, 36, 40 days, respectively. One hour after GPCRAC extracts treatment, behavioral tests were conducted. Mice were administrated intraperitoneally with scopolamine (3 mg/kg) 15–20 min before behavioral test. After the last behavioral test, mice were euthanized by cervical dislocation, the hippocampus tissues were isolated and collected on ice and then stored in a −80°C cryo-freezer for label-free shotgun proteomics analysis and bioinformatics to provide insights on the protein responses induced by GPCRAC extracts in the brain of AD mice.

In this experiment, there were four groups of mice (n = 17 per group) to evaluate the proteome treated by GPCRAC extracts. In each group, nine hippocampus samples isolated from different animals were pooled into three samples for proteomic analyses, followed by protein extraction and quantification. The proteomics analysis protocol has been reported previously (Zhang L. et al., 2021; Hao et al., 2021). The proteins were extracted with the mammalian tissue total protein extraction kit (AP0601-50, Bang Fei Bioscience Co, Ltd, Beijing, China), and the protein concentration was determined using the protein quantification kit according to the manufacturer’s instructions. Approximately 25 ug of brain tissues was homogenized in 250 ul of extraction buffer for 2 min using a homogenizer. Then, the lysates were centrifuged at 20,000 × g for 10 min at 4°C. Next, the supernatant was recovered. The protein concentration was measured by BCA (bicinchoninic acid) kit (Thermo Fisher Scientific, America) according to the manufacturer’s protocol. After protein quantification, Protein solution samples were prepared (Hao et al., 2021). Then, the samples were digested with trypsin following the Filter Aided Sample Preparation (FASP) protocol. All the peptide samples were collected for mass spectrometry analysis.

Each sample was separated using a nanoliter flow rate Easy nLC1000 system. Digested peptide mixtures were pressure-loaded onto a C18 trapping column (150 μm × 120 mm, 1.9 μm, Thermo Fisher Scientific, United States) and the column was washed with buffer A (water, 0.1% formic acid) and buffer B (80% acetonitrile and 0.1% formic acid) at a flow rate of 600 nL/min. After chromatographic separation, LC-MS/MS analysis was conducted using Q Exactive HF-X mass spectrometer (Thermo Scientific) that was coupled with Easy nLC (Thermo Fisher Scientific) for 88 min. The mass spectrometer was operated in positive ion mode with MS1 survey scan (m/z: 350–1,550). The resolution of the primary mass spectrum was 120,000, Automatic gain control (AGC) target was set to 3e6, and the maximum time of the primary ion was 20 ms. Normalized collision energy was 30 eV.

Peptide targeted identification was conducted with the SEQUST search engine, using sequences of human proteins downloaded from Uniprot (Zhang W. et al., 2021). All peptide raw files were analyzed by the Proteome Discover (2.2.0.388) and compared against the Uniprot Mus protein database (uniprot-Mus + musculus_20190102. fasta). Results were filtered with Peptide false discovery rate (FDR) ≤0.01. The following parameters were used in this analysis: Enzyme, Trypsin; Max Missed Cleavages, two; Peptide Mass Tolerance, ± 15 ppm; Fixed modifications, Carbamidomethyl (C); Variable modifications, Oxidation (M); Acetyl (Protein N-term); Fragment Mass Tolerance, 20 mmu; peptide confidence, high.

Then, Gene Ontology-term annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis using DAVID Bioinformatics Resources 6.8 (https://david.abcc.ncifcrf.gov/home.jsp) was performed. The protein–protein interaction (PPI) networks was constructed using STRING (https://www.stringdb.org), and the Cytohubba plugins of Cytoscape (version 3.6.0, Boston, MA, United States) was used to further analysis the PPI network. Principal Component Analysis (PCA), Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) model and Samples correlation heatmaps was constructed using MetaboAnalyst5.0 (https://www.metaboanalyst.ca/MetaboAnalyst/Secure/analysis/AnalysisView.xhtml). Partial Least-Squares Discriminant Analysis (PLS-DA) model and Permutation Test were performed with SIMCA-P software (version 14.1; Umetrics, Umea, Sweden). GraphPad Prism (version 8.0.2, San Diego, CA, United States) was used to visualize the volcano plot and box plots. Differential protein correlation graph used bioinformatics website(http://www.bioinformatics.com.cn/). The protein number map was generated using R software (version 3.3.3, Vienna, Austria). Pathway based data integration and visualization was performed using Pathview (https://pathview.uncc.edu/analysis).

The hippocampus of mice was collected and homogenized with 10-fold volume of RIPA buffer. After centrifuge, the upper liquid was obtained and used to detect the content of Ach and the activities of ChAT and AchE in the hippocampus according to the manufacturer’s instructions of the Ach assay kit (CAT: A105-1-2), ChAT assay kit (CAT: A079-1-1) and AchE assay kit (CAT: A024-1-1).

Total RNA was extracted from hippocampus tissue using RNeasy^® Lipid Tissue Mini Kit (QIAGEN, Valencia, CA, United States). The quality and quantity of RNA were measured using spectrophotometer (Thermo Nano Drop™ 2000c, United States). We used the following Primers: Forward Primer-PPP2CA TGG​GTT​CTA​CGA​CGA​GTG​TT, Reverse Primer-PPP2CA Reverse Primer AGA​AGA​TCT​GCC​CAT​CCA​CC. Forward primer-PPP3CC TGC​ACA​CAG​GAT​CCG​AAG​TT, Reverse Primer-PPP3CC CTT​TCG​GGG​TGG​CAT​TCT​CTC. Forward Primer-Caspase-3 CGG​AAT​TCG​AGT​CCT​TCT​CC, Reverse Primer-Caspase-3 AGC​ATG​GAC​ACA​ATA​CAC​GG. Forward Primer-GAPDH AGG​TTG​TCT​CCT​GCG​ACT​TCA, Reverse Primer-GAPDH TGG​TCC​AGG​GTT​TCT​TAC​TCC. RNA (2 μg) was converted into complementary DNA using Reverse Transcription Master Mix (QIAGEN, Valencia, CA, United States). RT-qPCR was determined using SYBR Green Master mix on a CFX-96 system (QIAGEN, Valencia, CA, United States). We used the 2 ^ -delta Ct method for the quantification of samples. GAPDH gene was chosen as the endogenous control to normalize variance between samples.

Total protein was extracted from frozen Brain tissue by RIPA Lysis Buffer (Applygen Technology Co., Ltd., Beijing, China, Catalog number: C1055) with protease inhibitor (100X) and a phosphatase inhibitor (100X). Protein concentration from tissue homogenates was measured with a BCA protein assay kit (Applygen, Beijing, China). 20 μg samples were separated by 8–12% SDS-PAGE, and then the protein was transferred to PVDF membranes (0.45 or 0.22 μm, Millipore, United States) and were blocked with 5% fat-free milk. After blocking for 2 h, the membranes were washed three times for 10 min per time by TBST. The membranes were incubated with indicated primary antibodies: anti-PP2A-alpha (ab106262,abcam, 1:1,000), phosphor-PKAC-α (D45D3, cell signaling technology, 1:500), PKAC-α (D38C6, cell signaling technology, 1:1,000), PPP3CC (ab154863,abcam, 1:1,000), Phospho-GSK3β (Ser9) (67558-1-Ig, proteintech, 1:3,000), GSK3β (22104-1-AP, proteintech, 1:3,000), BCL-2 (ab194583, abcam, 1:3,000), Bax (ab173026, abcam, 1;3,000) and GAPDH (ab8245, abcam, 1:4,000) overnight at 4 °C.Then the membranes incubated with primary antibodies goat anti-rabbit IgG or rabbit anti-mouse after washed three times for 2 h. ChemiDoc™ MP Imaging system (Bio-Rad Co, United States) and ImageJ software were used to quantify the protein bands.

For comparisons between two groups, we used Student’s unpaired t-test. One-way ANOVA with post-hoc test was applied to determined significant differences for multiple groups. All data are shown as mean ± SE, and p ≤ 0.05 was considered.

To assess the neuroprotective effect of GPCRAC extracts in vivo, a mouse model of scopolamine-induced cognitive impairment was created. Novel Object Recognition (NOR) test, Step-Down Passive Avoidance (SDA) test, and Morris Water Maze (MWZ) test were conducted to evaluate the neuroprotective of GPCRAC extracts on the scopolamine-induced learning and memory deficit in mice (Figure 1). In the NOR test, scopolamine-treated group (model group) exhibited low-level characteristics in recognize recognition index compared with control group, however, middle-dose group and high-dose group of GPCRAC extracts dramatically improved the reduced RI in AD mice (Figure 1A). By SDA test, we detected that the treatment of GPCRAC extracts notably recovered scopolamine-induced shorter step-down latency in a dose-dependent manner (Figure 1B) and GPCRAC extracts with high-dose group significantly reduced the number of errors in mice compared with model group (Figure 1C). In the Morris water maze (MWZ) test, the AD mice showed learning and memory deficits than that of control group, while GPCRAC extracts with high dose group improved cognitive impairment as evidenced by the decreased escape latency to find the platform site and more crossing numbers in platform area on the final day after removed the platform (Figures 1D,E). During the exploration period, decreased time of staying at target quadrant was also observed in scopolamine treated mice (Figure 1F). Additionally, the escape latency recorded during positioning navigation test revealed that AD mice took longer to reach the platform (escape latency) than the control and GPCRAC extracts group, with the effect most prominent on Day 4 (Figure 1G), indicating significant spatial learning and memory impairment after scopolamine exposure.

Acetylcholine (Ach), the first identified neurotransmitter, plays an important role in hippocampal memory function and deeply involved in the pathogenesis of AD (Haam & Yakel, 2017; Jing et al., 2018). choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine (Ach), is thought to be present in both cerebrospinal fluid (CSF) and plasma (Karami, Darreh-Shori, Schultzberg, & Eriksdotter, 2021), and acetylcholinesterase (AchE) is an enzyme that metabolizes the Ach at synaptic cleft, resulting in cognitive impairment (Patel, Raghuwanshi, Masood, Acharya, & Jain, 2018). To further evaluate the neuroprotective of GPCRAC extracts on hippocampal neuron damage, cholinergic dysfunction as indicated by decreased Ach content, ChAT activity and increased AchE activity was evaluated. As shown in Figure 2, GPCRAC extracts significantly reversed the decreased content of Ach (Figure 2A), activity of ChAT (Figure 2B), as well as the increased activity of AchE (Figure 2C) in hippocampal tissue of scopolamine-treated mice, especially the high-dose group, confirming an ameliorating effect of GPCRAC extracts on cholinergic function after scopolamine exposure. Together with behavioral experiments, our findings suggested that high-dose GPCRAC extracts were helpful in alleviating scopolamine-induced cognitive impairment, thus, GPCRAC extracts with high dosage was selected for further mechanism studies.

The mass spectra were recorded across the range of m/z 120-1800. All of the data were processed using Xcalibur software (version 2.7). The major components were well separated and detected under optimized UHPLC and MS conditions (Figure 3). The chemical composition of GPCRAC extracts was determined by comparing the UPLC-Q-Orbitrap MS analysis with the TCMSP database (https://old.tcmspe.com/tcmsp.php) and references. The molecular ion peak in the positive and negative ion mode was employed for the analysis of the relative molecular mass of the compounds. And then the compounds were qualitatively identified by comparing chromatographic retention time and MS/MS information. Finally, 38 compounds were identified from GPCRAC extracts including such as Gastrodin, SibiricoseA5, 3, 6′-Disinapoly sucrose, OnjisaponinB, Echinacoside, Acteoside, Curcumin, 1′, 2′-dihydroxyasarone (Table 1).

We performed a high-throughput quantitative proteomic using three replicates of hippocampal proteomes obtained from scopolamine-induced AD mice, the workflow chart based on label-free quantitative proteomics was given in Figure 4A. In detail, to verify whether the hippocampal proteome data of AD mouse model could be applied to further AD studies, we assessed the quantitative reproducibility (differences in technology and experimental conditions) of the hippocampal proteomes. Normalized protein expression of per sample revealed similarly distributions (Figure 4B). Moreover, principal component analysis (PCA) was applied to characterize the degree of proteome alterations within and between hippocampal samples. As demonstrated in Figure 4C, the first two principal components (PC1 and PC2) account for 87.9% of the overall cumulative variance contribution rate. It also showed a clear distinction between the control and model groups. Furthermore, as compared to the model group, the varied samples from the GPCRAC extracts group were more compactly packed, demonstrating superior reproducibility. Similarly, as shown in Figure 4D, we discovered strong Pearson correlations among biological replicates of the same groups (R, 0.990–1) and significantly lower correlations across different groups. The distribution of samples correlation heatmap also indicated a good biological reproducibility of the dataset. In conclusion, the observed variations in quantitative protein expression reflect the variety of molecular alterations across groups in mouse tissues rather than the effect of our label-free strategy. Thus, the workflow for proteomic analysis was stable and reliable, and the high degree of quantitative accuracy offered by the label-free quantification (LFQ) technique allows us to investigate proteomic alteration in the pathological development of AD.

To characterize the differentially expressed in protein profiles, the Partial Least-Squares Discriminant Analysis (PLS-DA) model was used to further optimize the population separation of different groups (Figure 5A). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) analysis, a supervised identification method, was applied to strengthen an established separation between the control vs. model group (Figure 5B, R2Y = 0.941, Q2 = 0.685) and model vs. GPCRAC group (Figure 5C, R2Y = 0.986, Q2 = 0.79). Subsequently, the permutation test was used to evaluate the possible overfitting of the OPLS-DA model. The corresponding validation plot showed that all of the PLS-DA models built for duplicate samples at different groups were valid (Figures 5D,E). Results obtained by OPLS-DA classification reveal a clear segregation of each group, indicating the significant changes in the expression of differentially expressed proteins in different groups. The proteins with M C N C fold-change>1.2 or <0.83 and p < 0.05 were chosen for further analysis. A subset of 4,112 proteins were quantified (unique peptides ≥ 2), and 390 quantified proteins were identified as differential expression proteins. Changes in protein levels were shown in Figure 5F, specifically, there are 135 differentially expressed proteins between control and model group, of which 110 are significantly up-regulated proteins and 25 are significantly down-regulated proteins. And, we identified 211 proteins regulated by GPCRAC extracts (128 up-regulated and 83 down-regulated). The overlaps of differentially expressed proteins between model vs. control and GPCRAC extracts vs. mod were 9 (Figure 5G).

The integrated bioinformatics analysis based on proteomics was undertaken to discover the hub target proteins mediated by GPCRAC extracts in treating AD.

To begin, the GO and KEGG analysis were perform to explore the potential functions of the differentially expressed protein involved in the GPCRAC extracts-mediated treatment of AD. The biological process of Gene Ontology (GO) analysis revealed that these differentially expressed proteins were primarily enriched in the positive regulation of autophagosome, presynaptic active zone membrane, ATPase activator activity, postsynaptic potential, postsynapse assembly, which is consistent with the fact that the pathology of AD correlates positively with synaptic function in hippocampal neurons (Figure 6A). KEGG analysis showed relevant pathways with p < 0.05 (Figure 6B). Spliceosome, RNA transport, Ribosome, Dopaminergic synapse, Long-term depression, Glutamatergic synapse, GABAergic synapse, Apoptosis, and other highly enriched terms were found in the KEGG pathway analysis. We discovered that most of the pathways play an important role in modulating the neurological function of the hippocampal, with the dopaminergic synaptic pathway being the best discriminant neural-related pathway, indicating that the dopaminergic pathway may be a necessary signaling pathway of target enrichment for the treatment of AD. Furthermore, neuronal apoptosis is a well-known pathway implicated in the degenerative process of AD.

Next, to identify the core protein targets mediate by GPCRAC extracts in treating AD, volcano plot mapping was constructed to detect the proteins that were significantly regulated between control vs. Model (Figure 7A) and model vs. GPCRAC extracts (Figure 7B) groups. Specifically, PPP2CA (p63330), PRKACA (P05132), PPP3CC (Q80XK0), GSK3β (E9QAQ5) and BCL-2 (P10417) were confirmed a clearly altered protein profiles in model vs. control group, as well as these proteins were dramatically reversed following GPCRAC extract therapy. To examine the specific change levels of these significantly altered proteins that were genetically associated to AD, the ‘protein expression level’ represented by the ratio of individual samples compared to pooled samples (called “normalized protein abundance”) was investigated. As shown in Figure 7C, the expression level of GSK3β, PPP2CA, PRKACA, PPP3CC, and BCL-2, consist with volcano plot maps, were recovered after the administration of the GPCRAC extracts. Of these hub proteins, PPP2CA and PRKACA were down-regulated and GSK3β, PPP3CC and BCL-2 were down-regulated in AD group. Following that, we exploit Pearson’s correlation heatmap to interpret the ‘signs’of interactions (ie, activation-inhibition relationships) between core differential proteins. The correlation matrix data (Figure 7D) showed positive or negative correlations between these core regulated proteins, with PPP3CC and PRKACA being positively linked with BCL-2 and PPP2CA and GSK3β being negatively correlated.

We next sought to further attest the biological interpretations of hub proteins in the core network. Briefly, protein–protein interaction (PPI) networks with Cytohubba plugins of Cytoscape was conducted to characterize hub proteins flow within core networks. The top 35 nodes were first ranked using Maximal Clique Centrality (MCC) method. The pivot protein and its biological function were eventually discovered. PPI visualization result suggest that several of the altered proteins were significantly connected with each other (enrichment value p < 0.005) and most of the hub differential proteins were primarily concentrated in the dopaminergic synapse and apoptosis signaling pathways, moreover, these pathways and some identified core proteins are implicated in AD pathogenesis (Figure 8). Eventually, PP2CA, PRKACA, PPP3CC, GSK3β associated with dopaminergic synapse and BCL-2 were selected as further analysis targets due to their closely relevance to neuronal damage.

The hub differentially expressed proteins and pathways of GPCRAC extracts in mediating AD were further verified by western blot and qPCR. PPP2CA encoding the alpha (α)-isoform of catalytic subunit of serine/threonine-protein phosphatase 2A (PP2A) (Bhardwaj et al., 2014). PP2A and GSK3β are essential proteins involved in the regulation of synaptic plasticity in the dopaminergic synaptic pathway (Martin, Magnaudeix, Wilson, Yardin, & Terro, 2011), and they are linked to aberrant tau phosphorylation and neuronal death in AD (Wang et al., 2019). Additionally, PPP3CC and PRKACA are also important regulators of synaptic and neural plasticity, Figure 9 illustrates this. Representative western blotting images (Figures 9A–E) and fold changes in relative densitometric values of PPP2CA, P-PKA, PPP3CC, P-GSK3β, BCL-2 and Bax were determined by western blotting. In the hippocampus of mice exposed to scopolamine, reduced expression of PPP2CA, P-PKA, PPP3CC (Figures 9F,G,J) and over-activated P-GSK3β expression (Figure 9I) (p = 0.005) was detected as compared to controls. Intriguingly, high dosages of GPCRAC extracts caused a considerable reversal in the expression levels of PPP2CA, PPP3CC, P-PKA, and P-GSK3β. We also found lower levels of PPP2CA and PPP3CCmRNA expression in the scopolamine-treated model mice relative to the control animals (Figures 9L,N), which was restored by treatment with GPCRAC extracts.

The apoptosis signaling system is important pathway in animal growth and tissue homeostasis (Cheng & Ferrell, 2018). We discovered apparent alterations in the apoptosis-related protein BCL-2 using proteomics, therefore we wanted to learn more about the level of apoptosis in the hippocampus of mice given by scopolamine and the protective effects of GPCRAC extracts. Furthermore, qPCR and Western blotting were used to investigate the anti-apoptotic efficacy of GPCRAC extracts in the hippocampus of mice subjected to scopolamine. When compared with control animals, obviously higher protein expression levels of Bax (Figure 9K) and gene expressions levels of Caspase-3 (Figure 9M) were discovered, as well as lower protein levels of BCL-2 (Figure 9H). In the mouse brain, treatment with GPCRAC extracts drastically reduced the expression of Bax and Caspase-3 while increasing the expression of BCL-2. These findings shown that GPCRAC extracts may dramatically regulate the expression of dopaminergic synapse associated proteins and apoptosis-related proteins in scopolamine-induced mice brain tissues, thereby treating AD.