Abstract
Artemisia absinthium L. contributes to ecological stabilization in arid
regions through its deep root system for sand fixation and soil
microenvironment modulation, thereby effectively mitigating
desertification. Total terpenoids have been extracted from A.
absinthium (AATP) and found to have antioxidant and anti-inflammatory
activities. Terpenoids are a class of natural products derived from
methyl hydroxypropanoic acid, for which their structural units consist
of multiple isoprene (C5) units. They are one of the largest and most
structurally diverse classes of natural compounds. However, there are
still large gaps in knowledge regarding their exact biological
activities and effects. Atherosclerosis (AS) is a prevalent
cardiovascular disease marked by the chronic inflammation of the
vascular system, and lipid metabolism plays a key role in its
pathogenesis. This study determined the extraction and purification
processes of AATP through single-factor experiments and response
surface optimization methods. The purity of AATP was increased from
20.85% ± 0.94 before purification to 52.21% ± 0.75, which is 2.5 times
higher than before purification. Studies have shown that the total
terpenoids of A. absinthium significantly reduced four indices of serum
lipids in atherosclerosis (AS) rats, thereby promoting lipid
metabolism, inhibiting inflammatory processes, and hindering aortic
wall thickening and hepatic fat accumulation. It is known from network
pharmacology studies that AATP regulates the Janus kinase/signal
transducer (JAK/STAT) signaling axis. Molecular docking studies have
indicated that the active component of AATP effectively binds to Janus
kinase (JAK2) and signal transducer (STAT3) target proteins. The
results indicate that AATP can inhibit the release of pro-inflammatory
mediators (such as reactive oxygen species (ROS)) in LPS-induced
RAW264.7 macrophages. It also inhibits the M1 polarization of RAW264.7
macrophages. Protein immunoblotting analysis revealed that it
significantly reduces the phosphorylation levels of Janus kinase (JAK2)
and the signal transducer and activator of transcription 3 (STAT3).
Research indicates that the active components in A. absinthium may
exert anti-atherosclerotic effects by regulating lipid metabolism and
inhibiting inflammatory responses. It holds potential value for
development as a functional food or drug for the prevention and
treatment of atherosclerosis.
Keywords: terpenoids, Artemisia absinthium L., extraction and
purification, atherosclerosis
1. Introduction
Cardiovascular disease is one of the leading causes of mortality
worldwide [[30]1]. Atherosclerosis (AS), a prevalent cardiovascular
disorder, develops through chronic lipid-driven vascular inflammation
[[31]2]. It serves as the primary pathological basis for multiple
cardiovascular conditions, including myocardial infarction and acute
coronary syndromes [[32]3,[33]4]. AS was recognized as a widespread and
life-threatening disease that could lead to severe clinical outcomes
and pose substantial public health risks [[34]5]. Therefore, the
prevention and treatment of atherosclerosis are considered crucial
medical priorities. The mechanisms underlying the initiation and
progression of atherosclerosis were complex and involved multiple
pathological processes, including inflammatory responses, dysregulated
lipid metabolism, oxidative stress, endothelial dysfunction, and
neointimal hyperplasia [[35]6,[36]7]. The pathological process is
initiated with vascular endothelial injury. Under various pathogenic
stimuli, multiple inflammatory mediators activate endothelial cells,
triggering the secretion of monocyte chemoattractant proteins that
subsequently induce monocyte recruitment. These cells differentiate
into macrophages, which phagocytose modified LDL particles, accumulate
lipids, and ultimately transform into cholesterol-laden foam cells.
Cumulatively, it causes vascular injury and accelerates atherogenesis
[[37]8,[38]9,[39]10,[40]11]. From the initial lesion to plaque
formation, the inflammatory response is always involved and drives the
entire pathologic process of atherosclerosis. The pathological
progression of atherosclerosis is characterized by the aberrant
activation of inflammatory cascades and the massive infiltration of
lipid-laden macrophages, which constitute the hallmark pathological
features. Lipid and cholesterol deposition in the vascular system,
coupled with elevated circulating inflammatory factors, trigger
localized inflammatory responses [[41]12]. However, existing
therapeutic strategies for atherosclerosis exhibit significant
limitations, and treatment options with minimal adverse effects remain
inadequate.
A. absinthium is extremely drought-, heat-, and cold-tolerant and is
widely distributed in wild wasteland and grassland habitats [[42]13].
A. absinthium is described in the pharmacopeias of many countries under
different names, which vary depending on the country in question. It
was a commonly used medicinal plant in various regions, including
Europe and Central Asia, for the treatment of hepatitis, dyspepsia,
stomach pain, anemia, and anorexia [[43]14]. A. absinthium is the
principal component of absinthe, a beverage consumed in Europe for
approximately 300 years. It was thought to have properties that
stimulated the appetite, promoted digestion, and nourished the body
[[44]15,[45]16]. A. absinthium is rich in bioactive components,
including total terpenoids, flavonoids, and polyphenols. These
ingredients have cardiovascular, anti-inflammatory, and antioxidant
properties. The chemical composition and bioactivity of ethanol
extracts obtained primarily from A. absinthium leaves and stems were
investigated to enhance the understanding of the phytochemistry and
bioactivity of this ancient medicinal plant with significant medicinal
potential. To this end, the ethanol extracts of the leaves and stems
were analyzed using liquid chromatography–mass spectrometry (LC-MS),
thermal analysis (TG-DSC), and Fourier transform infrared spectroscopy
(FT-IR). The anti-inflammatory effects of the extracts were tested in a
mouse ear edema model [[46]17,[47]18,[48]19]. But which group of
substances in absinthe exerts this anti-inflammatory effect, through
what pathways, and whether they inhibit the progression of
atherosclerosis remain unknown. Finally, how these substances are
extracted is also unclear. These questions are worth investigating by
the authors.
Terpenoids are among the largest and most structurally diverse
compounds in nature. Terpenoids are relatively common compounds found
in natural products. They are critical to the physiological processes,
growth, and developmental capacity of plants [[49]20]. Recent research
data reveal that the pharmacological value of medicinal plant-derived
terpenoids is becoming increasingly prominent, and their potential for
clinical applications is being continuously explored. They prevent and
treat cardiovascular disease, and they are anti-inflammatory and
hypoglycemic [[50]21,[51]22,[52]23]. Terpenoids are widely distributed
in various natural herbs and have the potential to become natural
medicinal drugs [[53]24]. Studies have shown that terpenoids,
particularly terpenoids, can treat cardiovascular diseases by reducing
oxidative stress and activating the Nrf2/HO-1 pathway [[54]24].
Apigenin, 2-methyl-5-(1-methylethyl)phenol, is the main component of
essential oils from the Labiatae family [[55]25]. Before apigenin was
studied, it was generally considered a safe additive and flavoring
agent. Subsequent studies have demonstrated that apiole exhibits broad
protective properties against disease states, including inflammation,
oxidative stress, tumor growth, and microbial infections [[56]26].
Vascular smooth muscle cell (VSMC) migration and proliferation are key
processes in neointimal formation during atherosclerosis [[57]27].
Studies have shown that apigenin inhibits PDGF-BB-induced RASMC
(vascular smooth muscle cell) migration and proliferation, suppresses
PDGF-BB-induced MAPK phosphorylation, and also inhibits the increased
sprouting growth of aortic strips [[58]28].
Experimental design enhancement has significantly utilized the response
surface methodology (RSM) [[59]29]. This optimization method defines
the functional relationship between several parameters and their
related response values using numerous quadratic regression equations.
By examining these regression equations, the optimal process parameters
were determined and predicted using Ordel [[60]30]. This method offered
several advantages, such as short experimental duration, ease of use,
and high accuracy and predictive power. At that time, it was used in
the process optimization of chemical and food products [[61]31,[62]32].
Cyberpharmacology systematically predicts complex interactions between
drugs and multiple targets by constructing networks of biomolecular
interactions [[63]33] and elucidating the latent complexity
relationships between diseases, compounds, and protein targets for drug
discovery and development efforts [[64]34]. Currently, network
pharmacology analysis mainly uses the chemical constituents of Chinese
medicines in databases for target prediction and functional analysis.
The chemical composition data obtained through measurement will be more
realistic and reliable once network pharmacology analysis is conducted
[[65]35]. Network pharmacology methods provide an effective way to
analyze the effects of complex herbal medicines [[66]36]. The drug
design technique of molecular docking involves connecting a receptor
macromolecule to the three-dimensional structure of a ligand compound
[[67]37]. To further understand the molecular relationships between TCM
active ingredients and illness targets, the small-molecule components
of TCM will be molecularly docked with target proteins [[68]38]. The
mutual corroboration of computational predictions and experimental
results greatly enhances the credibility of the conclusions on the
drug’s mechanism of action [[69]39,[70]40]. The present study
rationally combines predictive techniques and a rational experimental
design to explore the possible pathways of drug action.
Compared with the traditional one-factor method, the one-factor
experiment combined with the BBD experimental design was optimized for
the extraction process of AATP, and a more ideal enrichment effect was
obtained with the graded purification of macroporous resin. Current
treatments mainly focus on insufficient intervention in the early
stages of advanced atherosclerosis. Obesity exacerbates some risk
factors for atherosclerosis [[71]2]. Even though there are now many
treatments available for atherosclerosis, their high costs prevent many
people from choosing the best treatment [[72]6]. The disease has a high
recurrence rate, and progress in later-stage treatment is slow,
urgently requiring the development of highly effective drugs with
preventive properties. This paper innovatively combines pharmacological
predictions from a combined network with experimental pharmacology to
investigate the therapeutic effects of AATP against
anti-atherogenicity. This investigation provides a new theoretical
strategy for analyzing the pathological mechanisms of atherosclerosis
and developing therapeutic strategies with fewer side effects.
2. Materials and Methods
2.1. Materials and Reagents
A. absinthium powder was provided by Xinjiang Urumqi Tianyifeng
Biological Technology Co., Ltd., Urumqi, Xinjiang, China, courtesy of
Xinjiang Baokang Pharmaceutical Co. OX-LDL was provided by Medical
Source Biotechnology (Guangzhou, China). LPS (L8880) was purchased from
Beijing Solarbio Science & Technology Co. Simvastatin was purchased
from Shanghai Yuanye Biotechnology Co. Total cholesterol (TC)
(A111-1-1), triglycerides (TGs) (A110-1-1), low-density-lipoprotein
cholesterol (LDL-C) (A112-1-1), and high-density-lipoprotein
cholesterol (HDL-C) (A113-1-1) assay kits were purchased from Nanjing
Jianche Bioengineering Institute (Nanjing, China), in addition to
rabbit anti-mouse JAK2, STAT3, p-JAK2, and p-STAT3.
2.2. Extraction Process of AATP
The total terpenoids of A. absinthium were extracted by adding A.
absinthium powder to distilled water or different concentrations of
ethanol, depending on the extraction temperature and number of
extractions. The filtrate is then swirled at 8000× g for 10 min. The
liquid was reacted with a rotary evaporator at 60 °C under vacuum.
2.2.1. A One-Way Experiment to Extract AATP
For this, the total terpenoids are used as an indicator. A univariate
experimental design was applied to examine the influence of water and
ethanol concentrations (45, 65, 75, 80, and 95%), solid–liquid ratios
(1:10, 1:15, 1:20, 1:25, and 1:30 g/mL), extraction times (20, 30, 40,
50, 60, 60, and 70 min), extraction temperatures (40, 50, 60, 70, 80,
and 90 °C), and number of extractions (1, 2, 3, and 4) on the total
terpenoids. The best conditions for each factor were found. In a
single-factor experiment, a single factor is altered in each instance,
while the remaining factors remain constant. The optimal extraction
combination is ultimately determined by selecting optimal conditions at
three levels of each factor for response surface design.
2.2.2. Response Surface Experimental Design for the Extraction of AATP
The material–liquid ratio (A), extraction temperature (B), and
extraction duration (C)—the three independent variables—were selected
as critical parameters for optimizing absinthe terpenoid yields based
on single-factor experimental results. The data analysis of the
response surface optimization was conducted using the Design Expert 13
software, resulting in the generation of a three-factor, three-level
model comprising 17 experimental groups.
2.3. Purification Using Macroporous Adsorption Resin
2.3.1. Static Sorption and Desorption Experiments for Macroporous Resin-Type
Screening
After soaking in 95% ethanol for 24 h, macroporous resins D101, AB-8,
NKA-9, DM130, and X-5 were repeatedly rinsed with distilled water until
they were clean of any ethanol smell. After soaking in a 5% HCl
solution for five hours, pure water was used to rinse the resin, which
was then inserted in a 5% NaOH solution for five hours and then rinsed
again with distilled water until the effluent’s pH was neutral. For
subsequent usage, it was allowed to dry at ambient temperature
[[73]41].
The five macroporous resins were weighed at 2.0 g and combined with 20
mL of AATP in 100 mL Conical flasks. Filtration resin and AATP content
in the filtrate were determined. Using the same oscillation parameters
and adsorption conditions, the saturated resin was desorbed with 40 mL
of aqueous 95% ethanol solution, the resin was filtered, and the AATP
content of the filtrate was determined. The adsorptive and adsorbent
property rates for each packing material were calculated using the
following equations:
[MATH:
sorption capability (mg/g) Qe=(C0−C<
mrow>e)V1m :MATH]
[MATH:
sorption ratio (%) A=(C0−C<
mrow>e)C0×100% :MATH]
[MATH:
desorption capability <
mo>(mg/g) Qd=C2V2m
:MATH]
[MATH:
desorption ratio (<
/mo>%) D=C2V2(C
0−Ce<
/mi>)V1×100% :MATH]
In the above equation: C[0] is the concentration of AATP in the sample
solution (mg/mL); C[e] is the concentration of AATP in the adsorption
solution (mg/mL); C2 is the concentration of AATP in the desorption
solution (mg/mL); V1 is the volume of the AATP adsorption solution
(mL); V2 is the volume of the AATP desorption solution; m is the weight
of the resin (g).
2.3.2. Dynamic Sorption and Desorption
Dynamic leakage curves were studied during adsorption, and the effect
of sample concentrations (0.4, 0.6, 0.8, 1.0, and 1.2 mg/mL) on the
adsorption of AATP was determined. In addition, the effect of eluent
ethanol volume fractions (50, 60, 70, 80, and 90%) on the elution
capacity of AATP during desorption was investigated, and dynamic
elution curves were plotted. The effect of upsampling and elution
stream rates (1.0, 2.0, 3.0, and 4.0 mL/min) during dynamic sorption
and desorption on the purification of AATP was investigated. When one
of the factors was raised from the minimum to the maximum change, the
other five factors were kept constant.
2.4. LC-MS
2.4.1. Sample Preparation
In total, 25 mg of the AATP sample was weighed; 500 μL of
methanol–acetonitrile–water = 2:2:1 (V/V/V) was added, ground, and
sonicated, and this was repeated three times. The sample should then be
left at −40 °C for one hour and centrifuged for fifteen minutes at
12,000 rpm and 4 °C (RCF = 13800× g, R = 8). Following centrifugation,
the supernatant was filtered through a 0.22 µm membrane and
cryopreserved at −80 °C in sterile containers for subsequent
assessment.
2.4.2. Sample Detection
The target chemicals were separated chromatographically using Vanquish
ultra-performance liquid chromatography (UPLC) under the following
chromatographic conditions. The chromatography’s A-phase was 0.01%
acetic acid in water, and the B-phase was isopropanol–acetonitrile
(1:1, v/v). Mass spectrometry analysis was performed on an Orbitrap
Exploris 120 mass spectrometer with the following mass spectrometry
conditions: sheath gas flow rate: 50 Arb; auxiliary gas flow rate: 15
Arb; capillary temperature: 320 °C; full ms resolution: 60,000; ms/ms
resolution: 15,000; collision energy: SNCE 20/30/40; beam voltage: 3.8
kV (positive) or −3.4 kV (negative).
2.5. Cyberpharmacology and Molecular Docking
2.5.1. Collection of Active Ingredient Targets of AATP
The relevant terpenoids contained in AATP were screened by literature
mining and combined with preliminary LC-MS results. The standard 3D
molecular structure and Smiles ID of AATP were downloaded from the
PubChem database. The structures were entered into the SwissADME screen
to derive suitable compounds. The compounds were then screened for
relevant targets using Swiss Target Prediction
([74]https://www.swisstargetprediction.ch/) and SEA Search Server
([75]https://sea.bkslab.org/).
2.5.2. Determine the Target
The keyword “atherosclerosis” was searched in four databases—GeneCards
([76]https://www.genecards.org/), PharmaGKB
([77]https://www.pharmgkb.org/), DrugBank
([78]https://go.drugbank.com/), and Disgenet
([79]https://www.pharmgkb.org/)—to identify known targets for
atherosclerotic disease. The resulting data was plotted in a Venn map
to reflect the number of targets associated with atherosclerosis.
Following the removal of duplicate targets, a Venn diagram was
constructed to visualize the intersection between AATP targets and
atherosclerosis-related targets. The repeat target is the potential
therapeutic atherosclerotic goal of AATP.
2.5.3. Building the AATP PPI Network in Opposition
Protein–protein interaction (PPI) refers to the physical and functional
interactions between proteins, which play crucial roles in genetic
networks and biochemical pathways [[80]42]. The target profiles of
bioactive terpenoids from A. absinthium were intersected with known
atherosclerosis targets. Subsequently, the authors utilized
anti-atherosclerotic targets derived from the STRING database
([81]https://string-db.org/) in order to build protein interaction
networks. The minimum interaction score of ≥0.99 was selected, and the
default parameters were employed for all other settings. The final step
was to construct a protein–protein interaction network. The
protein–protein PPI network was constructed using Cytoscape 3.7.2.
2.5.4. Associated Signaling Networks Revealed by KEGG Pathway Enrichment
Analysis
Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of
Genomes (KEGG) signaling pathway enrichment analysis were performed
using the Metascape database to annotate gene function
([82]https://metascape.org/). The major objective of this research was
to look at the antagonistic effects of AATP. KEGG advanced bubble plots
were created using an internet program
([83]https://www.bioinformatics.com.cn/), and pathways of interest at p
< 0.05 were chosen for investigation and presentation.
2.5.5. Molecular Docking
The total terpenoids of Artemisia annua and their related core targets
JAK2 (PBD ID: 2B7A) and STAT3 (PBD ID: 6TLC) were subjected to
molecular docking analysis to further validate the binding between the
active components and the targets and to explore the potential target
sites for the treatment of AS by the total terpenoids of Artemisia
annua. The structural information of the active components of Artemisia
annua’s total terpenoids was obtained from the PubChem database, and
then, AutoDock 1.5.6 was used to determine the ligand’s rotatable
bonds, etc. The 3D structures of the core targets were obtained from
the PDB database, preprocessed, and then docked with the active
components using AutoDock software. The docking results with binding
energies meeting the requirements were visualized using PyMOL 2.5.2
software.
2.6. Study on the Anti-Atherosclerotic Effect of AATP
2.6.1. Establishment and Administration of Animal Models
Xinjiang Medical University Laboratory Animal Center purchased the SD
Rats. All experimental animals were maintained under controlled
environmental conditions (22 ± 1°C, 55 ± 5% relative humidity) with a
12 h light/dark cycle. After 7 days of acclimatization, they were split
into a control group and an atherosclerosis model group. For 16 weeks,
the model group was fed a diet heavy in fat. VD3 (600,000 IU/kg) was
injected intraperitoneally before modeling, and 100,000 IU/kg was
injected 2, 4, 6, 8, and 10 weeks after modeling. The control group
received normal food and water. At week 12 of modeling, animals were
rectally divided into control, model, positive control (simvastatin, 5
mg/kg/d), and AATP (100 and 200 mg/kg) groups. The drug was delivered
by gavage for 4 weeks. Rat body weights were measured weekly. The
Animal Ethics Committee of Xinjiang University approved all animal
experiments (approval number: XJUAE-2023-019).
2.6.2. Serum Biochemical Indicator Tests
Centrifuge blood at 1000× g for 1800 s. The upper blood layer was then
immediately shifted to a new test tube. Triglycerides (TGs), total
cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), and
low-density-lipoprotein cholesterol (LDL-C) were measured according to
the reagent instructions.
2.6.3. Histopathological Observation
After being submerged in a 10% formaldehyde solution, the liver and
aorta were gradually dehydrated using a series of graded ethanol
solutions and then cut into pieces that were 3–5 μM thick. Light
microscopy was used to evaluate the pathology of rat liver and aorta
after hematoxylin and eosin staining.
2.6.4. Cell Culture
RAW 264.7 cells are murine macrophage lines, obtained from the Cell
Bank of the Chinese Academy of Sciences. RAW 264.7 cells were cultured
in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% fetal
bovine serum (Gibco, Waltham, MA, USA) in a humidified incubator at 37
°C and 5% CO[2] (Thermo Fisher Scientific, Waltham, MA, USA).
2.6.5. Cell Viability Assay
After the cells were fully grown, they were treated with different
concentrations of AATP (5, 10, 20, 30, 40, and 50 μg/mL) and 100 μL of
complete medium as a normal reference. After 24 h of incubation, the
influence of drugs on cell viability was tested by the MTT method.
2.6.6. Oil Red O Staining
Then, 96-well plates were inoculated with 5 × 10^4 RAW264.7 cells per
well, which were subsequently randomly assigned to the control, model,
and culture groups. (80 µg/mL OX-LDL), a positive control group (5 µM
simvastatin), and an AATP group (5, 10, and 20 µg/mL). After dissolving
Oil Red O in isopropanol, the absorbance was measured at 550 nm.
2.6.7. Inflammatory Factor Assay
The inflammatory factors in the serum of the rats, including TNF-α and
IL-6, were tested using ELISA detection kits. In a 24-well plate,
inoculate RAW264.7 cells and incubate for 24 h. Following
randomization, the model group only received the 100 ng/mL
lipopolysaccharide (LPS) treatment, whereas the control group was
provided the entire medium. The drug group used 100 ng/mL LPS and
different amounts of AATP (5, 10, and 20 μg/mL). After 24 h of cell
incubation, the supernatant from each group was collected. The levels
of IL-6 and TNF-α secretion were quantified by ELISA methods.
2.6.8. ROS Detection
RAW264.7 cells were seeded in 6-well plates at a volume of 2 mL (2 ×
10^5/mL) per well and incubated for 24 h. RAW264.7 cells were
pretreated with LPS and AATP for 24 h. Subsequently, cells were
cultured with 10 μM DCFH-DA for 30 min. Finally, DCF fluorescence
intensity was detected by flow cytometry in the FITC pathway. The
fluorescence intensity of DCFH-DA was observed under an inverted
fluorescence microscope.
2.6.9. Flow Cytometry Analysis
Examine the representation of CD86 on AATP-treated RAW264.7 cells by
flow cytometry. The treated RAW264.7 cells were taken and incubated for
15 min with the APC-coupled anti-mouse CD86 antibody, as per
instructions. Quadrant segmentation analysis yielded the mean
fluorescent signal intensity.
2.7. Statistical Analysis
Statistical data analysis was performed using GraphPad Prism 8.0
software. All experiments included at least three independent
replicates. The results are expressed as the mean ± standard deviation.
Comparisons between multiple groups were performed using one-way ANOVA
combined with Tukey’s multiple-comparison test. The specific sample
size (n value) and statistical significance (p value) are noted in the
corresponding figure captions, with p < 0.05 indicating statistical
significance. Data visualization was performed using GraphPad Prism
software.
3. Results
3.1. Single-Factor Experimental Results of AATP Extraction
Results of Single-Factor Experiments with Different Ethanol Concentrations
[84]Figure 1A shows that the total terpenoid content of wormwood
increases with increasing ethanol concentration. When the ethanol
concentration reaches 95%, the total terpenoid content reaches its
maximum value. It may be that as the ethanol concentration increased,
the terpenoids were better leached, and hence, the content increased
([85]Figure 1A). The total terpenoid content of wormwood shows an
initial increase followed by a decrease as the ratio of sample mass to
extraction solvent volume increases. The total amount of terpenoids was
maximized at a solid-to-liquid ratio of 1:25 g/mL. However, the amount
of AATP decreased when the feed–liquid ratio exceeded 1:25. The
observed effect could originate from the low material–liquid ratio,
which reduces the concentration gradient between phases. This
diminished gradient hinders solute diffusion in the solvent, thereby
impeding terpenoid dissolution ([86]Figure 1B). The total terpene
content of absinthia increased slowly with increasing temperatures when
the extraction temperature was between 40 and 80 °C. This may be due to
the leaching of terpenoids by the gradual increase in temperature. The
highest total terpene levels were observed at an abstraction
temperature of 80 °C, while the total terpene levels decreased when the
temperature exceeded 80 °C. The extracts exhibited significantly
elevated terpene concentrations compared to the raw material. Maximum
terpenoid yields were achieved at 80 °C, with a marked decline observed
beyond this threshold temperature. This may be due to the change in the
structure of terpenoids under high-temperature conditions ([87]Figure
1C). Given the brief extraction period at the outset, the terpenoids
were not fully extracted. The extracted content of AATP reached its
maximum value at 40 min, beyond which the further extension of the
extraction time may have resulted in competition with other impurities,
leading to a reduction in the extracted content ([88]Figure 1D). As the
number of extractions increased, the AATP content tended towards
stability. This may be due to the fact that after a certain number of
extractions, the amount of AATP reaches equilibrium. In consideration
of the actual production process and the rational and efficient use of
resources, the quantity of extractions is determined to be one
([89]Figure 1E).
Figure 1.
[90]Figure 1
[91]Open in a new tab
The effects of (A) ethanol concentration, (B) material–liquid ratio,
(C) extraction temperature, (D) extraction time, and (E) number of
extractions on the total terpene content were investigated by a
single-factor experiment. Compared with the first group:*** p < 0.001
** p < 0.01 and * p < 0.05.
That is, the one-way experiment yielded the following conditions for
AATP extraction: an extraction solvent of 95% ethanol, a
material-to-liquid ratio of 1:25 g/mL, an extraction temperature of 80
°C, an extraction time of 40 min, and a single extraction.
3.2. Analysis of Extraction Parameters Using Response Surface Method
3.2.1. Response Surface Regression Model and Profiling of Variance
Response surfaces are an integrated statistical testing technique for
addressing the consequences of multiple elements of a structure or
system. In other words, they are used to investigate the
transformational relationship between the inputs (variable values) and
the outputs (responses) of a framework or system [[92]43]. The data
indicate that the material-to-liquid ratio, extraction temperature, and
extraction time have a marked influence on the results of the
extraction. The response surface analysis scheme and results are
presented in [93]Table 1 and [94]Table 2. After multiple regression
analysis, the following binary multiple recurrence model was derived:
Y = −168.23 + 3.93A + 2.8024B + 1.16C + 0.0028AB + 0.012AC + 0.00054BC
− 0.092A2 − 0.017B2 − 0.018C2.
Table 1.
Factors and levels in response surface design.
Levels Material–Liquid Ratio (A) (g/mL) Extraction Temperature (B) (°C)
Extraction Time (C) (min)
−1 20 70 30
0 25 80 40
1 30 90 50
[95]Open in a new tab
Table 2.
Analytical factors and levels for BBD.
Test Number Material–Liquid Ratio (A) Extraction Temperature (B)
Extraction Time (C) Total Terpenoid Content (mg/g)
1 30 80 30 13.63
2 25 80 40 18.39
3 25 70 30 14.26
4 25 80 40 18.26
5 25 90 30 14.53
6 30 80 50 15.11
7 25 90 50 14.77
8 20 80 50 13.05
9 30 70 40 13.61
10 30 90 40 14.58
11 20 80 30 14.02
12 20 90 40 14.17
13 25 80 40 17.61
14 25 80 40 18.26
15 25 70 50 14.28
16 25 80 40 18.13
17 20 70 40 13.77
[96]Open in a new tab
The ANOVA of the response surface model in [97]Table 3 indicates that
the regression model is highly notable (p < 0.001) and that the
difference is statistically significant. The mismatch term p = 0.4395 >
0.05 indicates that the mismatch is not significant (** p < 0.01). This
suggests that the model fits well with the experiment and that the
experiment produces fewer errors. The R2 value of 0.9886 indicated that
98.86% of the variation in the total terpenoids content of absinthe was
attributable to the selected experimental factors. [98]Table 3 shows
the test results obtained under different combinations of experimental
conditions. The regression equations accurately reflect the link
between the experimental parameters and the response values, thus
helping to predict and analyze the parameters related to the AATP
extraction process. The modified coefficient of determination, R^2 =
0.9739, indicated that the model could account for 97.39% of the
observed change in the response values; The ANOVA data from the fitted
regression equation proved that terms B, AC, A2, B2 and C2 in the first
term of the equation had a significant effect on the extracted content
of AATP. Conversely, the remaining terms were not found to be marked,
indicating that the relationship between the experimental factors and
the AATP content was not a straightforward linear relationship. As
illustrated in the table, the F-values for the individual factors A, B,
and C were 4.73, 5.76, and 0.76, respectively. This indicates that the
degree of influence of these three factors on the total terpene content
was B > A > C.
Table 3.
ANOVA results of the response model.
Source Sum of Squares Df Mean Square F Value p-Value Significance
95%Confidence Interval
Lower Bound Upper Bound
Model 54.95 9 6.11 56.28 <0.0001 ** significant
A 0.46 1 0.46 4.25 0.0782 −0.0353 0.5153
B 0.56 1 0.56 5.23 0.0561 −0.0091 0.5416
C 0.074 1 0.074 0.68 0.4357 −0.1791 0.3716
AB 0.081 1 0.0812 0.74 0.4155 −0.2469 0.5319
AC 1.50 1 1.50 13.83 0.0075 ** 0.2231 1.00
BC 0.012 1 0.012 0.11 0.7482 −0.3344 0.4444
A2 20.84 1 20.84 192.08 <0.0001 ** −2.60 1.84
B2 12.41 1 12.41 114.44 <0.0001 ** −2.01 −1.34
C2 13.06 1 13.60 125.35 <0.0001 ** −2.18 −1.42
Lack of Fit 0.3064 3 0.10 0.90 0.5144 not significant
Pure Error 0.452 4 0.01132
Cor Total 55.71 16
R2 0.9864
R2adj 0.9688
[99]Open in a new tab
3.2.2. Response Surface Interaction Analysis
The test results were used to plot response surfaces and contour lines,
as illustrated ([100]Figure 2), to assess the effects of every
extraction condition on the sum terpene content and the interactions
between the factors. Dynamic associations between factors can be
resolved by response surface slope analysis. If the response surface’s
slope is greater, the total terpene content of absinthe is more
impacted by the combination of the two elements. Conversely, if the
effect is smaller, the shape of the dense contour is elliptical,
suggesting that the way the two interact has a noteworthy impact on the
response value. In contrast, the circular structure of the sparse
profile suggests that the effect of the interaction is not significant
[[101]43]. The analysis revealed that the response surface slope for
the A and C interaction was the highest, and the ellipticity of its
contour plot was the greatest, indicating that the most noticeable
impact on the total terpene content was caused by the interplay between
the ratio of the material to the liquid and the duration of extraction.
The material–liquid ratio and extraction temperature, together with the
temperature and duration of extraction, exhibited minimal influence,
and the ellipticity of the contour plots was not conspicuous,
suggesting that the interaction was not statistically significant.
Figure 2.
[102]Figure 2
[103]Open in a new tab
Response surface plots (A–C) and contour plots (D–F) showing the
effects of different extraction parameters on the yield of total
terpenoids. (A,D) Material–liquid ratio and extraction temperature. (C,
D) Material–liquid ratio and extraction time. (E, F) Extraction
temperature and extraction time.
3.2.3. Determination and Verification of Optimal Conditions for Optimization
The model analysis indicated that ideal circumstances for the
extraction of total terpenoids from absinthe were as follows: a
material-to-liquid ratio of 25.30 g/mL, an extraction heat level of
80.77 °C, and a recovery time of 40.36 min. The experimental conditions
were adjusted as follows: The material–liquid ratio was 25 g/mL, the
extraction temperature was 80 °C, and the extraction time was 40 min.
The total terpene content measured was 18.00 ± 0.28 mg/g, which is not
much different from the theoretical value of 18.15 mg/g. The total
terpene content of 18.00 ± 0.28 mg/g is not very different from the
theoretical value.
3.3. Purification Results of Macroporous Resins
3.3.1. Selection of Macroporous Resins
The chemical structure, polarity, specific surface area, and hole size
of the sorbent material are important factors affecting the adsorption
and desorption of the resin [[104]44,[105]45]. Through balanced
adsorption and subsequent desorption studies, six types of macroporous
resins were systematically screened to select a resin for the
purification of AATP. The outcomes, as displayed in [106]Table 4 and
[107]Figure 3, revealed that the D101 resin exhibited superior
adsorption and desorption effects on AATP compared with the other five
resins. Consequently, the D101 resin was selected for use in the
purification of AATP in this experiment according to its superior
properties of adsorption and desorption.
Table 4.
Comparison of the static adsorption and desorption properties of
different macroporous resins.
Resin Type HPD600 D101 AB-8 NKA-9 DM130 X-5
Polarity category Polarity Non-polar Weak polarity Polarity Weak
polarity Non-polar
Specific surface area/(m^2/g) 550 500–550 480–520 250–290 500–550
500–600
Average aperture/nm 10~12 9~11 13~14 10~12 9~10 29~30
Moisture content% 73.5 67.50 71.64 72.50 74.20 71.00
Adsorption capacity mg/g 5.72 ± 0.15 7.25 ± 0.22 7.04 ± 0.23 6.55 ±
0.14 6.29 ± 0.20 7.09 ± 0.14
Desorbent capacity mg/g 1.71 ± 0.20 2.58 ± 0.095 2.18 ± 0.010 1.75 ±
0.044 2.02 ± 0.080 2.27 ± 0.012
[108]Open in a new tab
Figure 3.
[109]Figure 3
[110]Open in a new tab
Static adsorption (A) and desorption (B) effects of different types of
macroporous resins. Compared with the HPD600 group: *** p < 0.001, ** p
< 0.01, and * p < 0.1.
3.3.2. Results of Dynamic Absorption Experiments
The sorption of macroporous resins on the target is subject to
alterations when different dynamic adsorption and desorption conditions
are employed, which may have implications for the interpretation of
experimental results. The total terpenoid concentration in the effluent
demonstrated a gradual increase with the expansion of the sample
volume, and a considerable quantity of terpenoids commenced flow at 150
mL. When the volume reaches 200 mL, the total terpene concentration in
the effluent reaches a stable equilibrium, suggesting that the resin
has reached its sorption point of saturation. This phenomenon may be
due to the dynamic sorption process of macroporous resins, whereby the
ability to adsorb terpenoids diminishes after reaching saturation. As a
consequence, the unsuccessful adsorption of terpenoids occurs,
resulting in their leakage from the resin. This results in the
stabilization of the terpenoid concentrations in the effluent at 200 mL
([111]Figure 4A). When the sample’s concentration rises, the resin does
not saturate, allowing for the adsorption of terpenoids and increasing
the rate of adsorption. However, when the concentration of such a
sample is very large, the number of impurities in the solution also
increases. The impurities and the target compounds then compete for the
limited active sites of the resin, causing a decrease in adsorption
capacity. Furthermore, when the concentration was excessive, it caused
the resin to become clogged, which in turn affected the adsorption
effect [[112]46]. The resin achieved peak sorption efficiency at a
sample concentration of 0.8 μg/mL ([113]Figure 4B). The experimental
results show that both adsorption and desorption decrease with
increasing flow rates. The flow rate was excessive, which caused a
decrease in the sorption affinity of the macroporous resin for the
target species. Moreover, the AATP did not achieve sufficient contact
with the resin, resulting in incomplete adsorption or elution. Given
the requisite productivity and time constraints, the stream rates of 1
mL/min and 2 mL/min were thus identified as optimal for upsampling and
elution, respectively ([114]Figure 4C, E). The highest total terpenoid
concentration was observed when ethanol reached a concentration of 90%
during resin elution. This effect could be explained by AATP’s
increased solubility in high ethanol concentrations ([115]Figure 4D).
The total terpenoids were predominantly eluted from the resin once the
volume of eluent reached 210 mL ([116]Figure 4F).
Figure 4.
[117]Figure 4
[118]Open in a new tab
Factors affecting the adsorption and desorption performance of D101
resin. (A) Leakage curves. (B) Effect of sample concentration values on
adsorption capacity. Compared with the first group: *** p < 0.001. (C)
Effect of sample flow rate on adsorption capacity. Compared with the
first group: *** p < 0.001 and * p < 0.1. (D) Effect of eluent ethanol
concentration on desorption capacity. Compared with the first group:
*** p < 0.001. (E) Effect of elution flow rate on resolving capacity.
Compared with the first group: *** p < 0.001 and * p < 0.1. (F) Elution
curve.
In summary, the preferred process data for the purification of AATP by
D101 macroporous resin were as follows: sample consistency of 0.8
mg/mL, sample volume of 150 mL, rate of effusion of 1.0 mL/min, eluent
of 90% ethyl alcohol, rate of effusion of 2.0 mL/min, and volume of
effusion of 210 mL. Before and after purification, the purity of AATP
increased from 20.85% ± 0.94% to 52.21% ± 0.75% and that of AATP was
increased from 20.85% ± 0.94% to 52.21% ± 0.75%. Before and after
purification, the purity of AATP increased from 20.85% ± 0.94% to
52.21% ± 0.75%.
3.4. Outcomes of Cyberpharmacology
3.4.1. AATP and Potential Targets in Atherosclerosis
The constituents of AATP were characterized by LC-MS, and the
chromatograms were given in positive and negative ion modes
([119]Figure 5A, B). A total of 22 active ingredients of AATP were
identified through database screening as potential treatments for AS. A
search of the GeneCards, DisGeNET, PharmGKB, and DrugBank databases
identified 3320 targets associated with atherosclerosis. The
distribution of the 3319 targets according to their compositional
relevance was as follows: 1257 in GeneCards, 2044 in DisGeNET, 13 in
PharmGkb, 13 in DrugBank, and 5 in DrugBank ([120]Figure 5C). Following
the elimination of duplicate values, a total of 2251 disease targets
were identified. Subsequently, Venn diagrams were constructed to
identify 221 target genes that were common to both the AATP-effective
ingredient targets and the atherosclerosis targets ([121]Figure 5D).
The 221 targets were deemed to be prospective candidates for
AATP-mediated anti-atherosclerosis. Subsequently, the
active-ingredient-targeted network of protein–protein interactions was
built using Cytoscape 3.7.2 ([122]Figure 5E), which is accessible for
further investigation. The potential target network is depicted
([123]Figure 5F), which suggests a close association between the
targets. Thirty-seven key targets were screened according to the degree
value, median centrality (BC), and neighboring centralities (CC)
([124]Figure 5G), including STAT3, JAK2, TNF, IL-6, PPARG, and IL-1β.
Figure 5.
[125]Figure 5
[126]Open in a new tab
LC-MS (A) positive and (B) negative ion chromatograms of AATP. (C) Venn
diagram of disease-associated targets. (D) Venn diagram of active
ingredient-disease-associated targets. (E) Network diagram of the
active ingredient’s potential targets. (F) PPI network of intersecting
targets of AS and AATP. (G) Key targets of AATP for AS based on the
CytoNCA analysis. (H) GO enrichment analysis. (I) KEGG pathway
enrichment analysis.
3.4.2. GO and KEGG Pathway Enrichment Analysis
The Metascape database was utilized for GO and KEGG enrichment studies
of relevant AATPs against atherosclerotic targets. The GO functions
mainly included kinase binding, steroid binding, and the regulation of
cellular inflammatory responses ([127]Figure 5H), while the
KEGG-enriched pathways primarily included the JAK/STAT signaling
pathway, the PPAR signaling pathway, the platelet activation pathway,
and the cAMP signaling pathway, among others ([128]Figure 5I). This
suggests that AATP may inhibit the development of atherosclerosis by
modulating many biological processes and the JAK/STAT signaling
pathway.
3.4.3. Molecular Docking Analysis
Based on the target proteins (STAT3 and JAK2) predicted by network
pharmacology analysis and the related inflammatory signaling pathway
JAK/STAT, molecular docking was performed between JAK2 and STAT3, and
the active components (Artemisinic acid, Capsidiol, Isoalantolactone,
Zedoarondiol, Dehydrovomifoliol, Fukinone, and Procurcumenol) were
subjected to molecular docking ([129]Figure 6). The binding efficiency
of each component with the target protein was indicated by the
magnitude of the binding energy. A binding energy below −4.25 kcal/mol
typically indicates the presence of binding activity between the
receptor and ligand, while a binding energy below −5.00 kcal/mol
corresponds to a stable binding conformation. The results are shown in
[130]Table 5. The binding free energies of the active components with
the target proteins were all below −5.00 kcal/mol, indicating
spontaneous and stable interactions. Therefore, AATP can effectively
and stably bind to the key target sites predicted by network
pharmacology.
Figure 6.
[131]Figure 6
[132]Open in a new tab
The three-dimensional conformation of the AATP active ingredient
(artemisinic acid, calcidiol, isoalantolactone, zedoarondiol,
dehydrovomifoliol, quinone, and procurcumenol) docked to JAK2 and STAT3
target protein molecules.
Table 5.
Molecular docking binding energy (in kcal/mol).
Compound JAK2 STAT3
Artemisinic acid −5.28 −5.80
Capsidiol −5.94 −5.64
Isoalantolactone −5.84 −6.12
Zedoarondiol −5.59 −5.80
Dehydrovomifoliol −5.03 −5.75
Fukinone −5.67 −6.22
Procurcumenol −6.03 −6.40
[133]Open in a new tab
3.4.4. Effects of AATP on Body Weight and Organ Indexes in Atherosclerotic
Rats
An animal model of atherosclerosis was created by administering a
high-fat diet and injecting VD3. Following AATP intervention, a gradual
increase in body weight, followed by a gradual decrease in body weight
in rats eating fatty foods ([134]Figure 7A), was observed. In
[135]Figure 7B, the post-treatment weight was significantly different
from that of the model group (p < 0.01). A significant increase in
liver index was noted within the model group of rats in comparison to
the control group (p < 0.01) in the organ index analysis. However,
compared with model rats, liver indicators were significantly reduced
after AATP treatment (p < 0.01), while the indicators of other organs
remained basically unchanged and were not statistically significant
([136]Figure 7B–D, F). This suggests that AATP does not produce marked
toxic actions on the organs of AS rats and attenuates the abnormal
proliferation and hypertrophy of the liver in AS rats.
Figure 7.
[137]Figure 7
[138]Open in a new tab
Effect of AATP on body weight and organ indices in AS rats (mean ± SD,
n = 8). (A) Modeling AS with high-fat feeds combined with vitamin D3.
(B) Changes in body weight of rats. Changes in (C) heart, (D) kidney,
(E) liver, and (F) aortic weight indices. Compared with the control
group: ## p < 0.01; compared with the model group: ** p < 0.01.
3.4.5. AATP Attenuates Aortic and Hepatic Lesions in AS Rats
Tissue staining was performed on the rats to visualize the lesions. The
model’s aortic wall was noticeably thicker than that of the control
group. AS rats (p < 0.01) and most of the cells in the wall showed
irregular arrangement. Compared with the model group, a thinner aortic
wall and more aligned cells were observed visually in the AATP and
simvastatin groups (p < 0.01) ([139]Figure 8A, B). Moreover, the livers
of the model group exhibited disorganization and an increased number of
fat vacuoles in contrast to the control group. However, following
gavage therapy using AATP and simvastatin, cells in the liver are
organized, and the fat vacuoles were significantly reduced ([140]Figure
8C). Furthermore, in comparison to the control group, the livers of the
model group exhibited a notable accumulation of fat. In contrast, the
administration of AATP via gavage resulted in a reduction in the
accumulation of lipids in the liver, accompanied by a notable decline
in the number of lipid droplets ([141]Figure 8D). These findings
indicate that AATP may possess the potential to mitigate the thickening
of the aortic wall in rat AS, suppress the formation of substantial
quantities of fat vacuoles in the liver, and attenuate the accumulation
of lipids. It may also help inhibit the progression of aortic and liver
lesions.
Figure 8.
[142]Figure 8
[143]Open in a new tab
(A) HE staining of the aorta. (B) Aortic intima-media thickness. (mean
± SD, n = 3). (C) HE staining of the liver. (D) Oil red O staining of
the liver. Compared with the control group: ## p < 0.01; compared with
the model group: ** p < 0.01.
3.4.6. AATP Improves Lipid Levels, Liver Function, and Inflammatory Factors
Compared with the control group, the serum levels of TC, TG, and LDL-C
were found to be significantly elevated in the model group of rats,
even though HDL-C was significantly decreased (p < 0.01). In contrast,
all other indices were observed to be reduced in both the Stimavastin
group and the AATP group, except for the increase in HDL-C (p < 0.01)
([144]Figure 9A–D). A subsequent assessment of serum liver function
indices, aspartate aminotransferase (AST), and alanine aminotransferase
(ALT) demonstrated that AATP was effective in decreasing the blood
levels of AST and ALT in AS rats, indicating that it improves impaired
hepatic function due to long-term hepatic steatosis ([145]Figure 9E,F).
Given the well-documented role of inflammation in promoting
atherosclerotic plaque formation, an investigation was also conducted
into the effect of AATP on inflammatory factors. This study’s findings
demonstrated that serum TNF-α and IL-6 levels were considerably raised
in AS rats compared with the control group (p < 0.01). Significantly
lower levels of TNF-α and IL-6 were found after AATP treatment compared
with the model group. In conclusion, AATP proved effective in improving
lipid levels, liver function, and inflammatory cytokine levels in AS
rats.
Figure 9.
[146]Figure 9
[147]Open in a new tab
AATP effects on rat lipid, liver, and cytokine levels (mean ± SD, n =
8). Serum concentrations of (A) TC, (B) TG, (C) LDL-C, (D) HDL-D, (E)
AST, (F) ALT, (G) TNF-α, and (H) IL-6. Compared with the control group:
## p < 0.01; compared with the model group: * p < 0.05; ** p < 0.01.
3.4.7. Effect of AATP on the Viability of RAW264.7 Cells
Compared with the control group, no notable cytotoxic impact on
RAW264.7 cells was observed when the AATP concentration remained below
20 μg/mL (p > 0.05) ([148]Figure 10A). Furthermore, microscopic
observation revealed a notable reduction in cell number at
concentrations exceeding 20 μg/mL ([149]Figure 10B). Accordingly, the
AATP at concentrations of 5, 10, and 20 μg/mL was selected for
subsequent experimentation.
Figure 10.
[150]Figure 10
[151]Open in a new tab
Impact of AATP on (A) viability and (B) morphology of RAW264.7 cells.
(C) Oil red O staining of RAW264.7 cells. (D) Quantification of oil red
O content at 550 nm. Compared with the control group: ### p < 0.001;
compared with the model group: ** p < 0.01 and *** p < 0.001.
3.4.8. AATP Inhibits Ox-LDL-Induced Foam Cell Formation
Macrophages can take up OX-LDL to form foam cells, which ultimately
leads to plaque destabilization and rupture [[152]47]. To further
investigate the effect of AATP on plaque vulnerability, an OX-LDL
treatment was applied to create a macrophage-derived foam cell model.
No notable formation of lipid droplets was observed in the normal
control cells, whereas a considerable increase in lipid droplets was
evident within the model cells that were contrasted with the controls
(the concentration of DMSO is the concentration of DMSO in the highest
drug dose group) (p < 0.001). Following intervention with AATP at
levels of 5, 10, and 20 μg/mL, a pronounced reduction in intracellular
lipid droplets was observed (p < 0.001) ([153]Figure 10C,D). The
findings suggest that AATP may be able to reduce intracellular lipid
accumulation and impede OX-LDL-induced foaminess in RAW 264.7
macrophages. This suggests that AATP may be involved in the prevention
of atherosclerosis.
3.4.9. AATP Suppresses Pro-Inflammatory Mediator Synthesis in RAW264.7
Macrophages
Macrophages initiate the proinflammatory process by launching a variety
of pro-arthritic mediators and contribute to the worsening of a number
of inflammation-associated diseases [[154]7,[155]48]. AATP treatment
resulted in significantly attenuated inflammatory responses relative to
simvastatin, as evidenced by reduced cytokine secretion (p < 0.001)
([156]Figure 11A–C). In addition, there is evidence that LPS stimulates
the infiltration of inflammatory cells into lung tissue, resulting in
the release of large amounts of reactive oxygen species. This, in turn,
allows inflammatory cells to accumulate, promoting an inflammatory
reaction that may affect atherosclerosis [[157]49]. The administration
of LPS resulted in a notable elevation in intracellular ROS production,
whereas the administration of AATP was observed to exert a pronounced
inhibitory effect on ROS generation (p < 0.001) ([158]Figure 11D–F).
Experimental data revealed that AATP exhibited significant
anti-inflammatory activity by inhibiting the secretion of key
inflammatory factors (e.g., IL-6, TNF-α).
Figure 11.
[159]Figure 11
[160]Open in a new tab
Cellular concentrations of (A) TNF-α, (B) IL-6, and (C) NO. (D)
Inverted fluorescence microscopy to observe the effect of AATP on ROS.
(E,F) Flow cytometry to detect ROS. Compared with the control group:
### p < 0.001; compared with the model group:*** p < 0.001.
3.4.10. AATP Inhibits M1 Polarization in RAW264.7 Macrophages
Activated M1 macrophages secreted multiple proinflammatory cytokines,
which promoted inflammatory progression and contributed to
atherosclerosis development. To determine whether AATP alleviated
atherosclerosis by inhibiting M1 macrophage polarization, CD86
expression (an M1 polarization marker) was quantified using flow
cytometry. The results demonstrated significantly elevated CD86
expression in LPS-treated model groups versus controls (p < 0.001),
whereas AATP treatment markedly reduced surface CD86 levels compared to
model groups ([161]Figure 12A, B). These findings indicated that AATP
effectively suppressed LPS-induced M1 polarization in RAW264.7
macrophages.
Figure 12.
[162]Figure 12
[163]Open in a new tab
(A,B) Effect of AATP on CD86 expression on the surface of RAW264.7
cells using flow cytometry. (C–E) Effect of AATP on the expression of
JAK2, p-JAK2, STAT3, and p-STAT3 proteins in RAW264.7 cells. Compared
with the control group: # p< 0.05; ### p < 0.001; compared with the
model group: * p < 0.05, ** p < 0.01, and *** p < 0.01.
3.4.11. AATP Modulated JAK2/STAT3 Pathway
It is widely accepted that activation of the JAK/STAT signaling pathway
is a hallmark of the inflammatory process. The LPS-induced cytokine
cascade in macrophages initiated JAK-receptor complex formation and
downstream STAT phosphorylation events [[164]50]. Beyond that, the
activated JAK/STAT signaling pathway has been proven to promote
aberrant pro-inflammatory cytokines and to regulate macrophage
polarization, eventually leading to inflammatory diseases [[165]51].
Protein immunoblotting demonstrated that JAK2 and STAT3 phosphorylation
was markedly elevated (p < 0.05) in LPS-induced RAW264.7 cells, whereas
total absinthium terpenoids (10 and 20 μg/mL) exhibited a pronounced
inhibitory effect on JAK2 and STAT3 phosphorylation (p < 0.05)
([166]Figure 12C–E). Thus, AATP may inhibit the atherosclerotic process
by regulating the JAK2/STAT3 signal transduction cascade.
4. Discussion
Artemisia absinthium L. plays a prominent role in traditional medicine.
It is a therapeutic plant with important medicinal and economic values
[[167]52]. In recent years, extensive research has been conducted on
the chemical composition of A. absinthium raw materials and the
bioactivity of its extracts. These studies identified essential oils,
bitter sesquiterpene lactones, flavonoids, other bitter compounds, and
chamomile derivatives as the primary bioactive constituents [[168]53].
Terpenoids, which are plentiful in medicinal plants, make up a category
of natural active products with an extensive range of medicinal actions
and pharmacological activity and a multitude of applications utilized
to treat a variety of diseases. They exhibit considerable potential for
further development and application. As a class of natural products,
terpenoids exhibit structural diversity, comprising multiple
subclasses. Each subclass of terpenoids possesses distinctive
biological properties [[169]26].
Multiple factors affected the extraction process, including the plant
material’s particle size, solvent type, solvent-to-solid ratio,
extraction duration, and processing temperature [[170]54]. Attar et al.
[[171]55] reported that conventional Soxhlet extraction demonstrated
superior efficiency in extracting tetracyclic triterpene cucurbitacin I
from Cucurbita pepo compared to microwave-assisted and
ultrasound-assisted extraction techniques. Response surface methodology
(RSM), a statistical optimization approach, was widely applied in
process optimization studies due to its capacity to expand the
parameter space [[172]56]. This method proved effective for optimizing,
designing, and improving processes where output variations depended on
multiple input variables [[173]57]. The Box–Behnken design (BBD) can be
fitted by a non-linear model to better reflect the objective reality of
the process conditions, and at the same time, it can take into account
the different influencing factors and evaluation indexes in the
experimental design of the accuracy of the outcomes of the precision
prediction of the optimization method based on the BBD. Compared with
other methods, BBD optimization demonstrated the ability to reduce the
total number of experiments required for process optimization. The
optimized protocol exhibited simplicity, rationality, and stability,
providing a methodological foundation for enhancing natural product
extraction processes [[174]58]. The authors use response surface
optimization to analyze the factors affecting the response with a
fitted model and find the optimal operating conditions. This approach
saves time and is more operational.
First, a one-way experimental design was implemented to evaluate the
effects of ethanol concentration, material-to-liquid ratio, extraction
temperature, extraction duration, and extraction cycles on AATP yield.
Subsequently, these parameters were further optimized using response
surface optimization (RSD) to determine the optimal extraction
conditions for AATP. Combining the results of single factor and BBD
response surface design optimization, the optimal extraction process of
total terpenoids from A. absinthium was obtained as follows: 95%
ethanol as the extraction solvent, 1:25 g/mL as the material–liquid
ratio, 80 °C as the extraction temperature, and 40 min as the
extraction time. Additionally, there was only one extraction. Examining
the impact of the feed-to-liquid ratio on total terpenoid extraction,
the AATP content first increased and then decreased with an increase in
the feed–liquid ratio. This might be because when the feed–liquid ratio
is too low, there is little difference in concentration between the
liquid and feed phases, which hinders the diffusion of substances in
the solvent and is not conducive to the production of terpenoids in
large quantities of the active substances being leached. As a result,
the total amount of terpenoids is relatively small; as the
material-to-liquid ratio steadily increases, the specific surface area
of the molecules with solvent exposure increases. This process allows
for the gradual dissolution of terpenoids, thereby increasing the total
amount of terpenoids in the material. However, an excess of solvent can
lead to a dilution effect, accompanied by a rise in the concentration
of impurities in the extracted solution. Consequently, the extraction
amount is reduced [[175]59]. The effect of extraction duration on the
total terpenoid yield was investigated. It was observed that the total
terpenoid content decreased significantly when the extraction time
exceeded 40 min. This phenomenon was attributed to the structural
degradation of terpenoids during prolonged extraction, coupled with the
increased dissolution of impurities that compromised the overall
terpenoid yield. Additional experiments were conducted to evaluate the
influence of temperature parameters on terpenoid extraction efficiency.
The total terpenoids decreased as the temperature rose beyond 80 °C.
This phenomenon may be credited with the deterioration of active
compounds and a reduction in the extracted content, which occurs at
elevated temperatures [[176]54].
These compounds demonstrated stability in acids, bases, and organic
solvents. They also exhibited effective separation and screening
capabilities with minimal interference. Additionally, they showed
strong adsorption capacity, easy regeneration potential, and a long
service life. These properties provided unique advantages for the
standardized isolation and commercial-scale production of natural
products, making them widely applicable in natural product purification
[[177]60,[178]61,[179]62]. In addition, macroporous resin adhesion is a
type of approach to purification using adsorbents that takes advantage
of the differences between the adsorbent resin and the substance, and
the nature of the functional clusters on the exterior of the adsorbent
particles, such as polarity, acid–base, and hydrogen-bonding capacity,
can impact the selectivity of adsorption and adsorption behavior
[[180]63]. As the fluid medium passed through the porous adsorbent bed,
the reactive sites on solid-phase surfaces selectively interacted with
fluid molecules [[181]64]. The substance obtained from the preliminary
extraction contained significant impurities (e.g., proteins and
sugars), which affected the study of its physiological activity.
Therefore, further separation and purification were required to remove
these impurities and improve the purity of the target compound. In the
current work, macroporous resin was employed for AATP purification. A
screening of the available macroporous resins revealed that different
resins exerted varying effects on the adsorption and desorption of
total terpenoids. Based on the experimental findings, D101 packing was
chosen for the purification of AATP. The optimal purification values
were determined by dynamic sorption and desorption tests, i.e., a
sample density of 0.8 mg/mL, a sample volume of 150 mL, and a sample
flow speed of 1.0 mL/min. The elution solvent was 95% ethanol at a flow
rate of 2.0 mL/min for a volume of 210 mL. The above conditions
resulted in the improvement of the purity of AATP from 20.85% ± 0.94%
before purification to 52.21 ± 0.75% after purification. Practical
operation showed that this method is simple, low-cost, easy to promote,
and is the best choice for the enrichment and purification of AATP.
It is now understood that atherosclerosis is an inflammatory condition
with underlying mechanisms involving apoptosis, endothelial
dysfunction, and oxidative stress [[182]65]. It has been demonstrated
that during the progression of atherosclerosis, LDL is reactive oxygen
species-oxidized, leading to the production of oxidized LDL, which
impairs endothelial cell function and activates the secretion of
inflammatory cytokines by monocytes and macrophages to amplify
inflammation [[183]66]. Research had confirmed that natural terpenoids
exhibited diverse pharmacological activities; therefore, it was
speculated that AATP might possess anti-atherogenic properties.
Experimental data demonstrated a significant inhibitory effect of AATP
on atherosclerosis. Lipid metabolism disorders, as one of the key
pathogenic factors in atherosclerosis, could be evaluated by measuring
the serum levels of TC, TG, LDL-C, and HDL-C [[184]67]. TC represented
the total cholesterol content in blood lipoprotein particles and served
as a risk predictor for atherosclerosis, while elevated TG levels were
a contributing factor to atherosclerosis progression [[185]68].
“Cholesterol hypothesis” was proposed, suggesting that lowering LDL
cholesterol levels reduces the risk of atherosclerotic cardiovascular
disease [[186]69]. HDL-C can deliver cholesterol from plaque to the
liver for catalysis, thus reversing cholesterol transit, reducing
cholesterol deposition in the vessel wall, and playing an
anti-atherosclerotic role [[187]70]. The results suggested that the
serum total cholesterol, total cholesterol, and LDL cholesterol levels
were significantly reduced in AS rats after AATP intervention. This
implies that AATP may play a therapeutic role in the treatment of
atherosclerosis by regulating lipid metabolism disorders in AS rats.
The development of lipid foam cells within atherosclerotic plaques is a
pivotal process in the progression of lesions, including the
deterioration of the tips of fibers, necrotic nuclei, and ultimately,
plaque rupture. Foam cells are macrophages that overabsorb oxidized
low-density lipoproteins. It is a distinct pathological cell type in
atherosclerotic plaques [[188]71]. It could be reasonably deduced that
the inhibition of foam cell formation represented an efficacious
therapeutic strategy at all stages of atherosclerosis, from early to
advanced stages [[189]72]. In this context, the authors investigated
whether AATP inhibited lipid accumulation in macrophage-derived foam
cells induced by ox-LDL. The results demonstrated that treatment with
varying concentrations of AATP significantly reduced intracellular
lipid droplet accumulation and suppressed macrophage foam cell
formation.
In the treatment of atherosclerosis, a range of promising therapeutic
strategies for inflammation modulation were proposed, including the
inhibition of pro-inflammatory cytokines, the blockade of key
inflammatory signaling pathways, and the promotion of inflammation
resolution [[190]73]. The microenvironment of atherosclerotic plaques
is highly complex. Among the macrophage subtypes identified, there were
anti-inflammatory macrophages (M2, M(Hb), Mhem, and Mox) and
pro-inflammatory macrophages (M1 and M4). Various inflammatory
responses and atherosclerotic plaque formation were triggered by an
increase in pro-inflammatory macrophages and a decrease in
anti-inflammatory macrophages, which accelerated the progression of
cardiovascular diseases [[191]74,[192]75,[193]76]. Numerous stimuli,
such as lipopolysaccharides (LPSs) and interferon-γ (IFN-γ), activated
M1 macrophages, leading to the production and release of
pro-inflammatory cytokines (e.g., TNF-α, IL-1β, IL-6), as well as
reactive oxygen species (ROS) and nitric oxide (NO) [[194]77,[195]78].
The alterations in these pro-inflammatory mediators were examined both
in vivo and in vitro, and it was demonstrated that AATP significantly
reduced the blood levels of TNF-α and IL-6 in AS rats and LPS-induced
macrophages. The inhibitory effect of AATP on atherosclerosis was
further confirmed by the combined analysis of biochemical indices and
cellular experiments after modeling in rats. Additionally, AATP
potently inhibited the production of NO and ROS in vitro. Furthermore,
the effect of AATP on CD86 expression in LPS-induced macrophages was
evaluated, and it was found that AATP significantly decreased CD86
expression, indicating its inhibition of LPS-induced polarization of
RAW264.7 macrophages toward the M1 phenotype.
Since its initial proposal in 2007, network pharmacology has attracted
significant interest in the fields of drug development and mechanism
prediction. The rapid advancements in bioinformatics and integrative
pharmacology facilitated cost-effective drug development through cyber
pharmacology-based approaches. Molecular docking predicted
ligand–receptor binding affinity and conformation
[[196]79,[197]80,[198]81]. Numerous studies have employed integrated
strategies combining network pharmacology predictions with molecular
docking. Based on network pharmacological analysis, the potential
targets of AATP for atherosclerosis (AS) therapy include STAT3 and the
JAK/STAT pathway, which are associated with inflammatory responses.
Molecular docking demonstrated favorable interactions between
JAK2/STAT3 pathway-associated proteins and the active ingredients of
AATP. Therefore, it could be hypothesized that AATP exerts
anti-inflammatory effects on atherosclerosis by inhibiting the
JAK2/STAT3 signaling pathway. Recently, accumulating evidence has
indicated that JAK2 phosphorylation is linked to cardiovascular
conditions, including atherosclerosis, diabetes mellitus [[199]82],
myocardial fibrosis [[200]83], and myocardial ischemia–reperfusion
injury [[201]84]. The regulation of JAK2 phosphorylation and its
downstream pathways has the potential to ameliorate inflammation,
making JAK2 a prospective therapeutic target for preventing and
managing cardiovascular diseases (CVDs) [[202]85]. The STAT3 dimer is
rapidly translocated to the nucleus, ultimately regulating the
expression of downstream genes at the transcriptional level [[203]86].
The JAK2/STAT3 signaling pathway is a classical inflammatory signaling
pathway that regulates macrophage polarity toward the M1 phenotype and
modulates the secretion of inflammatory factors (e.g., TNF-α), which
exacerbates the course of atherosclerosis [[204]87,[205]88]. Several
studies have demonstrated that phytochemicals and natural plants exert
a protective effect against cardiovascular diseases and regulate
JAK2/STAT3 signaling [[206]89,[207]90,[208]91]. Evidence that AATP
inhibits LPS-triggered JAK2-STAT3 phosphorylation in macrophages
suggests that its anti-atherosclerotic effects may involve the
modulation of this proinflammatory signaling axis. Clinical drug
interventions primarily focus on reversing coronary atherosclerotic
plaques, with lipid-lowering drugs, especially statins and PCSK9
inhibitors, remaining central to treatment because they not only lower
cholesterol but also have anti-inflammatory and plaque-stabilizing
properties [[209]92]. Compared to single compounds, natural extracts
contain multiple active ingredients, and the synergistic effects of
each component through “multi-target-multi-pathway” enhance the
therapeutic effect. After long-term verification through folk medicine,
the toxicity and side effects are generally lower than those of
synthetic drugs. The cost-effectiveness ratio is high. The extraction
and purification process is relatively simpler than chemical synthesis
(especially crude extract preparations).
This study conducted a detailed investigation into the extraction and
purification process of AATP. Subsequent research can focus on
developing more terpenoid active components in AATP, with an emphasis
on their specific active effects. AATP exerts its anti-atherosclerotic
effects by inhibiting lipid accumulation and inflammatory responses in
RAW264.7 foam cells. Further research can be conducted to identify
additional targets of AATP in atherosclerosis and to explore its
anti-atherosclerotic mechanisms in greater depth, thereby providing a
promising natural drug for the treatment of atherosclerosis.
5. Conclusions
In conclusion, we determined the preferred extraction process for AATP,
purified the extracted AATP using macroporous resin, and investigated
the optimal conditions for purification. The anti-atherosclerotic
effects of AATP were investigated in vitro and in vivo by identifying
the targets of AATP in atherosclerosis through network pharmacology and
molecular docking. AATP exhibited potent antioxidant and
anti-inflammatory activities, which were related to its inhibition of
the expression of JAK2/STAT3 pathway-related proteins. AATP attenuated
the aortic and hepatic lesions in rats with AS, thereby exerting an
anti-atherosclerotic effect. The results of this study provide an
experimental basis for the further exploration of more targets of AATP
against atherosclerosis and a deeper investigation into its
anti-atherosclerotic mechanism, and the results also suggest a
promising natural drug for atherosclerosis.
Abbreviations
The following abbreviations are used in this manuscript:
AATP Total terpenoids of Arlemisia absinthtum L.;
AS Atherosclerosis;
CVD Cardiovascular disease;
RSM Response surface methodology;
HFD High-fat diet;
OX-LDL Oxidized low-density lipoprotein;
LPS Lipopolysaccharide;
BBD Box–Behnken design;
ROS Reactive oxygen species;
TC Total cholesterol;
TG Triglyceride;
TNF Tumor necrosis factor;
IL Interleukin;
JAK Janus Kinase;
STAT Signal transducer and activator of transcription;
LDL-C Low-density-lipoprotein cholesterol;
HDL-C High-density-lipoprotein cholesterol;
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Author Contributions
J.Y.: Writing—original draft, investigation, formal analysis, and
conceptualization. T.H.: Writing—original draft, investigation, formal
analysis, and data curation. L.X.: Writing—original draft,
visualization, funding acquisition, and conceptualization. J.L.:
Visualization, supervision, funding acquisition, and conceptualization.
All authors have read and agreed to the published version of the
manuscript.
Institutional Review Board Statement
The Animal Ethics Committee of Xinjiang University approved all animal
experiments (approval number: XJUAE-2023-019).
Informed Consent Statement
Not applicable.
Data Availability Statement
The original contributions presented in the study are included in the
article, further inquiries can be directed to the corresponding
authors.
Conflicts of Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.
Funding Statement
This work was financially supported by the Key Research and Development
program in Xinjiang Uyghur Autonomous Region (2023B03012-1,
2023B02030-3); the Natural Science Foundation of Xinjiang Uyghur
Autonomous Region, China (2023D01C36); and Tianshan Talent Training
Program (2023TSYCLJ0043).
Footnotes
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References