Assessing Dazhu Hongjingtian: Protection Against Acute Hypoxic Organ Damage and Analysis of Its Main Pharmaceutical Components

ABSTRACT

Dazhu Hongjingtian (DZ), a traditional Tibetan medicine used for altitude sickness and blood stasis syndrome, currently lacks comprehensive pharmacological and quality control data. This study evaluated its antihypoxic effects in mice and established an HPLC‐MS/MS method for quantifying 12 bioactive constituents. Acute hypoxic injury was induced by 12‐h normobaric hypoxia (10% O₂), and DZ water extract (DZE) was assessed via ELISA for oxidative stress, inflammation, and energy metabolism markers in brain, lung, heart, and liver. DZE dose‐dependently attenuated oxidative stress (reduced H₂O₂ and MDA; elevated SOD, T‐AOC, and GSH‐Px), inhibited inflammation (reduced TNF‐α, IL‐1β, and IL‐6), and improved energy metabolism (enhanced Na⁺‐K⁺‐ATPase and ATP; reduced LDH and lactate). The HPLC‐MS/MS method showed good linearity (r ≥ 0.9957), precision (RSD < 5%), and recovery (94.11%–102.46%). Gallic acid derivatives dominated the constituents (19.77 mg/g), followed by salidroside (12.15 mg/g) and flavonoids (6.62 mg/g). These findings demonstrate that DZE exerts potent antihypoxic effects through synergistic action of its macro‐ and micro‐components, providing a mechanistic and analytical foundation for its use in the prevention and treatment of hypoxia‐related diseases, particularly acute mountain sickness.

1. Introduction

Hypoxia is defined as a pathological process in which body tissues and cells experience insufficient oxygen supply or impaired oxygen utilization, leading to abnormal changes in cellular and tissue function, metabolism, and even structure (Dong et al. 2021). It is a central factor in the pathogenesis and progression of various diseases, including cardiovascular and cerebrovascular disorders, as well as high‐altitude illnesses (González‐Canadia et al. 2023; Li et al. 2021; Rahman et al. 2026). Hypoxia‐induced cellular responses include oxidative stress, inflammatory responses, and mitochondrial dysfunction, which may ultimately lead to cellular damage and apoptosis (Gong et al. 2026; Liang et al. 2026; Yu 2025). Therefore, the development of effective and safe antihypoxia agents to enhance the body's tolerance to hypoxia and mitigate hypoxic injury has always been an important area of pharmaceutical research.

Currently, commonly used clinical antihypoxia medications mainly include chemical drugs such as acetazolamide, dexamethasone, and nifedipine (Li et al. 2018; Alimire et al. 2023), as well as traditional Chinese medicines like Rhodiola rosea and Ginkgo biloba (T. T. Wang et al. 2020). Although chemical drugs can alleviate hypoxia‐induced symptoms to a certain extent, their long‐term use may be accompanied by side effects. For example, acetazolamide can lead to increased urination, paresthesia, fatigue, and gastrointestinal discomfort (Lipman et al. 2020). Meanwhile, the evidence supporting natural antihypoxia remedies remains insufficient. The supporting evidence is primarily empirical or derived from preclinical studies, and is further limited by insufficient data, low methodological quality, and contradictory findings (Cai et al. 2026; Dwivedi et al. 2025). Consequently, the current focus of research and development for natural antihypoxia drugs is to identify candidate substances with fewer adverse effects and definite efficacy from natural, pollution‐free botanical sources and to conduct high‐quality studies on them.

Dazhu Hongjingtian (DZ) (Rhodiola wallichiana [HK.] var. cholaensis [Praeger] S. H. Fu) is one of the most ancient Tibetan medicinal herbs. Its traditional functions, including clearing heat, removing toxins, and drying dampness, are well‐documented in numerous classical medical texts and modern pharmacopoeias (Ou et al. 2025). In contemporary practice, it is primarily indicated for the prevention and treatment of altitude sickness and blood stasis syndrome (Ou et al. 2020; Xue et al. 2024). Its broad pharmacological effects are largely attributed to its rich profile of bioactive constituents, such as salidroside, tyrosol, flavonoids, phenols, and phenylpropanoids (Ou et al. 2020), which possess multiple biological activities, including antioxidant, anti‐inflammatory, antiapoptotic, antihypoxic, and mitochondrial protective effects (Chen et al. 2025; Hu et al. 2021; Jiang et al. 2022; Ou et al. 2025; Wani and Banat 2025). However, its specific mechanisms of action, protective effects on vital organs, and the contribution of its main active components remain to be fully elucidated. Furthermore, the current quality standard for DZ Capsules (National Drug Standard WS3‐1047(Z‐271)‐2008Z, issued by the State Food and Drug Administration) only specifies the identification of salidroside by TLC and its quantitation by HPLC as a single marker. This significantly limits the comprehensive quality evaluation of the product and hinders the improvement of its quality standard.

Despite the long history of DZ use in Tibetan medicine and its inclusion in the Chinese Pharmacopoeia, several critical knowledge gaps persist. First, the protective effects of DZ on vital organs (brain, heart, lung, and liver) under hypoxic conditions have not been systematically evaluated using a multibiomarker approach. Second, the quantitative phytochemical profile of DZ remains incompletely characterized, hindering comprehensive quality control and mechanistic understanding. Third, the correlation between the quantified phytochemical composition and the observed pharmacological effects has not been established, leaving the synergistic contributions of multiple constituents largely speculative.

To address these gaps, this study was designed with two integrated objectives: (i) to evaluate the in vivo protective effects of DZE on multiple organs in a normobaric acute hypoxia mouse model, using a panel of 13 biochemical markers across oxidative stress, inflammatory, and energy metabolism pathways, and (ii) to develop and validate a sensitive HPLC‐MS/MS method for the simultaneous quantification of 12 representative pharmaceutical components in DZE, thereby establishing a phytochemical basis for its antihypoxic efficacy. This integrated pharmacological–analytical approach provides a scientific foundation for the quality control and clinical application of DZ in hypoxia‐related diseases, particularly acute mountain sickness (AMS).

2. Materials and Methods

2.1. Materials and Reagents

DZE (water extract from roots and rhizomes of DZ) (Batch Number: Z191001) was provided by Jiangsu Kanion Pharmaceutical Co. Ltd. (Lianyungang, China). acetazolamide (ACTZ) was provided by Beijing Vokai Biotechnology Co. Ltd. (Beijing, China). Sodium carboxymethylcellulose (CMC‐Na) and soda lime were provided by Sinopharm Chemical Reagent Co. Ltd. (Shanghai, China). Chloromycetin (the internal standard [IS]) was provided by Shanghai Yuanye Bio‐Technology Co. Ltd. (Shanghai, China). The other chemicals and reagents were the same as Ref. (Ou et al. 2020).

Bicinchoninic acid (BCA) protein assay kit was purchased from Biyuntian Biotechnology Co. Ltd. (Shanghai, China). Superoxide dismutase (SOD), total antioxidant capacity (T‐AOC), malondialdehyde (MDA), hydrogen peroxide (H₂O₂), lactic acid (LD), lactate dehydrogenase (LDH), adenosine triphosphate (ATP), Na⁺‐K⁺‐adenosine triphosphatase (Na⁺‐K⁺‐ATPase), and glutathione peroxidase (GSH‐Px) assay kits were purchased from Nanjing Jiancheng Bioengineering Institute (Jiangsu, China). ELISA kits for human interleukin 6 (IL‐6), interleukin 1β (IL‐1β), tumor necrosis factor‐α (TNF‐α), and creatine kinase (CK) assay kit were obtained from Cloud‐Clone Corp. (Wuhan, China).

2.2. Antihypoxic Activity of DZE In Vivo

2.2.1. Animals

All experimental protocols and care of mice were in accordance with the Guideline for Animal Experimentation of Nanjing University of Chinese Medicine. Specific pathogen‐free (SPF) male Kunming (KM) mice (aged 4–5 weeks, body weight of 20 ± 2 g) were purchased from the Shanghai Jiesijie Laboratory Animal Technology Co. Ltd. (Shanghai, China, License No. SCXK (Hu)2018‐0004). Mice were housed in groups of five per cage in individually ventilated cages (IVCs) with sterile corncob bedding. They were maintained under controlled conditions (temperature 25°C ± 2°C, relative humidity 60°C ± 10%, 12‐h light/dark cycle) for 1 week of acclimatization. Purified water and standard irradiated rodent chow were provided ad libitum before the experiment. During the 12‐h fasting period prior to drug administration, water remained freely available. No animals were excluded from the study based on predefined health criteria.

2.2.2. Acute Hypoxia Experiment

After fasting, mice were randomly assigned to six groups: the normal control group (NCG, 0.5% CMC‐Na), hypoxia model group (HMG, 0.5% CMC‐Na), positive control group (ACTZ (Ma et al. 2011), 0.2 g/kg), DZE low‐dose group (DZE‐L, 0.6 g/kg), DZE medium‐dose group (DZE‐M, 1.2 g/kg), and DZE high‐dose group (DZE‐H, 2.4 g/kg). The sample size (n = 10 per group) was determined based on previous studies using similar hypoxia‐induced mouse models (Jiang et al. 2022; Shi et al. 2021). All drugs or vehicle were administered once daily via oral gavage (volume 10 mL/kg) for five consecutive days. Thirty minutes after last treatment, mice (except NCG) were placed into a self‐made hypoxic chamber (Figure S1, 120 cm × 60 cm × 25 cm) equipped with a gas inlet, outlet, and four soda lime containers (200 g, renewed every 4 h) to absorb exhaled CO₂. A gas mixture of 90% N₂ and 10% O₂ (premixed certified gas cylinder, Nanjing Special Gas Co.) was continuously infused at 4 L/min for the first 10 min to rapidly achieve hypoxia, and then the flow rate was adjusted to maintain an O₂ concentration of 10.0% ± 0.2% (equivalent to ~6000 m altitude) for 12 h. O₂ concentration was continuously monitored using a portable gas sensor (CY‐12C, Hangzhou, China). NCG mice were kept in normoxic room air (21% O₂) for the same duration. At the end of exposure, mice were removed from their cages, euthanized by cervical dislocation. Brain, heart, liver, and lung tissues were rapidly dissected, rinsed with ice‐cold normal saline, blotted dry, weighed, snap‐frozen in liquid nitrogen, and stored at −80°C until analysis. No mortality occurred in any group.

2.2.3. Biochemical Analysis and Cytokine Assay

Frozen tissue samples (0.2 g) were thawed on ice and homogenized in 1.8 mL of ice‐cold phosphate‐buffered saline (1 × PBS) using a motor‐driven Teflon‐stainless steel homogenizer. The homogenate was centrifuged at 14,000 rpm for 10 min at 4°C, and the supernatant was collected for analysis. Protein concentration was determined using a BCA assay kit. According to the manufacturer's instructions of the respective assay kits, the following parameters were measured in duplicate: SOD, T‐AOC, MDA, H₂O₂, LDH, LD, ATP, Na⁺‐K⁺‐ATPase, GSH‐Px, IL‐6, IL‐1β, and TNF‐α. All values were subsequently normalized to the protein concentration of each sample.

2.3. Determination of Main Pharmaceutical Components in DZE

2.3.1. Analytical System

Quantitative analysis was performed on an ultra‐performance liquid chromatography (UPLC) system (Nexera X2 Series, Shimadzu, Kyoto, Japan), which included a binary solvent delivery unit, a gradient mixer, an autosampler, and a column temperature controller. Separation was achieved on a ZorBax Eclipse Plus C18 column (2.1 mm × 100 mm, 1.8‐μm film thickness—Agilent, CA, USA) maintained at 40°C. The mobile phase consisted of 0.1% formic acid in water (A) and methanol (B), with the following gradient program: 15% B at 0–2 min, 15%–35% B at 2–4 min, 35% B at 4–7 min, 35%–55% B at 7–9 min, 55%–95% B at 9–11 min, and 95% B at 11–12 min. The flow rate was set at 0.5 mL/min.

MS analysis was performed on a high‐resolution quadrupole time‐of‐flight mass spectrometer (Triple Quad 6500⁺ System, AB Sciex, Framingham, MA, USA) equipped with an electrospray ionization (ESI) source. Data were acquired in negative ion mode using multiple reaction monitoring (MRM). For each analyte, MS/MS parameters were individually optimized by direct infusion of reference standard solution (100 ng/mL or 1 μg/mL in methanol) at 10 μL/min rate via a syringe pump. After selection of the precursor ion (Pre. I.), the corresponding product ion (Pro. I.) was determined by optimizing the declustering potential (DP) and collision energy (CE). Nitrogen was used as the curtain gas (CUR, 20 psi), nebulizing gas (GS1, 15 psi), heating gas (GS2, 60 psi), and collision gas (CAD, 8 psi). Other MS parameters were set as follows: ion‐spray voltage (IS), − 4500 V; source temperature (TEM), 500°C; entrance potential (EP), − 10 V; and collision cell exit potential (CXP), − 18 V. Data acquisition and processing were performed using Analyst Software (Version 1.6.1, AB Sciex, Framingham, MA, USA). The MRM transitions, retention times, and optimized DP/CE values for each analyte are summarized in Table 1.

TABLE 1.

Retention time and related MS data of the 12 pharmaceutical components.

Analyte (no.)	t R (min)	Pre. I. (m/z)	Pro. I. (m/z)	CE (V)	DP (V)
Gallic acid (C1)	0.80	168.9 [M‐H]−	125.0	−70	−20
Salidroside (C2)	2.23	345.1[M+HCOOH‐H]−	299.1	−26	−14
Bergeninum (C3)	2.60	327.1 [M‐H]−	192.1	−70	−35
Ethyl gallate (C4)	4.59	196.9 [M‐H]−	124.1	−90	−30
Epicatechin gallate (C5)	4.79	441.2 [M‐H]−	169.0	−60	−25
p‐Coumaric acid (C6)	4.68	163.0 [M‐H]−	118.9	−20	−20
Quercitrin (C7)	8.21	447.1 [M‐H]−	299.9	−120	−40
Rhodiosin (C8)	9.41	609.3 [M‐H]−	301.2	−207	−45
Quercetin (C9)	9.41	301.0 [M‐H]−	151.0	−110	−30
Luteolin (C10)	9.81	284.7 [M‐H]−	133.0	−80	−40
Kaempferol (C11)	10.14	285.1 [M‐H]−	187.1	−100	−40
Rhodionin (C12)	9.38	447.1 [M‐H]−	301.0	−200	−104
Chloramphenicol (IS)	5.47	321.0 [M‐H]−	151.9	−63	−22

2.3.2. Preparation of Standard Solutions and Sample Solutions

Individual standard stock solution of each analyte (0.2 mg/mL) was prepared by dissolving the corresponding analyte in methanol. Sonication was applied when necessary to achieve complete dissolution. A mixed stock solution containing all analytes was prepared by combining appropriate volumes of the individual stock solution. Working standard solutions were obtained by serially diluting the mixed stock solution with methanol–water (50:50, v/v) to appropriate concentrations. After storage at 4°C, all solutions were centrifuged at 12,000 rpm for 10 min, and the resulting supernatants were transferred to autosampler vials prior to analysis.

The sample solution was prepared according to the procedure described in Ref. (Ou et al. 2020). For quantitative analysis, the supernatant was diluted 2000‐fold for the simultaneous determination of gallic acid, salidroside, and p‐coumaric acid, and 200‐fold for the simultaneous determination of the other nine constituents.

An IS stock solution of 0.2 mg/mL was prepared in methanol. This stock solution was diluted with methanol–water (50:50, v/v) to yield an IS working solution at a concentration of 80 ng/mL. Then, 1 mL of the IS working solution was added to 1 mL of either the mixed standard solution or the sample solution. The mixture was vortexed, centrifuged at 12,000 rpm for 10 min, and the supernatant was subsequently subjected to analysis.

2.3.3. Method Validation

2.3.3.1. Linearity and MQL

A series of mixed standard solutions with six different concentrations were analyzed by an established method in triplicate. Every calibration curve was plotted based on linear regression analysis of peak area ratio of analyte to IS (Y) versus concentration (X, ng/mL). The correlation coefficient and linear range for each component were obtained. The lowest concentration of the calibration curve was defined as the method quantitation limit (MQL).

2.3.3.2. Precision, Repeatability, Stability, and Accuracy

The intraday precision was evaluated by analyzing the same mixed standard solution six times within a single day. The interday precision was evaluated by performing three consecutive injections each day over three consecutive days. The repeatability was analyzed on six sample solutions from the same sample in parallel. The stability was appraised by analyzing the same sample solution and the mixed standard solution at 0, 2, 4, 6, 12, and 24 h at room temperature. The accuracy was evaluated on recovery determination. Known amounts of the mixed standard solutions at different concentration levels (50%, 100%, and 150% as compared to the nominal concentration) were mixed with known amounts of DZE samples. Then, the samples were extracted and analyzed by the above‐established method.

2.4. Statistical Analysis

All data were expressed as mean ± standard deviation (SD). Normality was assessed using the Shapiro–Wilk test, and homogeneity of variances was verified by Levene's test. For comparisons among multiple groups, one‐way analysis of variance (ANOVA) was performed, followed by Tukey's post hoc test for multiple comparisons when the overall F‐test was significant; to control the family‐wise error rate, a correction for multiple comparisons was applied. For comparisons between two specific groups (e.g., DZE‐H vs. ACTZ), unpaired two‐tailed Student's t‐tests were used. A p value of < 0.05 was considered statistically significant. Post hoc power analysis was performed based on SOD levels in liver and brain using the observed means and standard deviations; with α = 0.05 (two‐tailed) and n = 10 per group, the achieved power exceeded 0.99. Power calculations were conducted using ClinCalc software (https://clincalc.com/stats/Power.aspx). All statistical analyses were performed using SPSS Version 25.0 (IBM, Armonk, NY, USA).

3. Results

3.1. Protective Effect of DZE on Acute Hypoxic Mice

3.1.1. Observation on Survival State of Acute Hypoxia Mice

Mice behaved normally during the first 3 h of hypoxia, then showed progressively reduced intake. By 6 h, they developed limb weakness, huddling, abdominal resting, disordered hair, and perioral/nasal cyanosis. At 9 h, they became largely immobile, refused food/water, and had aggravated cyanosis. In contrast, NCG mice remained normal. DZE and ACTZ groups exhibited milder symptoms (reduced intake, better activity, mild hair disorder, and cyanosis). No mortality occurred.

3.1.2. DZE Attenuated Hypoxia‐Induced Oxidative Stress Injury in Multiple Tissues

3.1.2.1. T‐AOC and H₂O₂ in Brain and Liver Tissues

As illustrated in Figure 1A, compared with the NCG, T‐AOC levels in the brain and liver tissues of HMG mice were significantly decreased to 4.5‐fold and 4.4‐fold of the control values, respectively. In contrast, H₂O₂ levels (Figure 1B) in the brain and liver tissues of HMG mice were markedly increased to 2.58‐fold and 3.13‐fold of the control values, respectively. Treatment with DZE‐L, DZE‐M, DZE‐H, and ACTZ effectively reversed these alterations. Compared with the HMG group, DZE treatment elevated T‐AOC levels in the brain of hypoxic mice to 1.04‐, 2.00‐, 2.91‐, and 3.62‐fold of the HMG values, respectively. In the liver, T‐AOC levels were increased to 1.09‐, 1.87‐, 3.08‐, and 3.04‐fold, respectively. Simultaneously, all treatments significantly suppressed H₂O₂ levels in the brain to 26.2%, 44.7%, 62.8%, and 61.9%, respectively, and in the liver to 21.0%, 40.9%, 60.2%, and 61.5%, respectively. All these changes showed statistically significant differences (p < 0.001).

FIGURE 1.

DZE regulated the oxidative stress markers in hypoxic‐injured tissues. Data are expressed as mean ± SD (n = 10/group) (A: T‐AOC; B: H₂O₂; C: SOD; D: MDA; E: GSH‐Px). Note: ^### p < 0.001 NCG vs. HMG; *p < 0.05, **p < 0.01, ***p < 0.001, HMG vs. medication groups; ^&&& p < 0.001, DZE‐H versus ACTZ. ACTZ, positive control group; DZE‐H, DZE high‐dose group; DZE‐L, DZE low‐dose group; DZE‐M, DZE medium‐dose group; HMG, hypoxia model group; NCG, normal control group.

Comparison between DZE‐H and ACTZ: Statistical analysis revealed that in brain tissue, T‐AOC levels were significantly lower in the DZE‐H group compared with the ACTZ group (p < 0.001). In contrast, no significant difference was observed in liver tissue between DZE‐H and ACTZ. For H₂O₂ levels, no significant differences were found between DZE‐H and ACTZ in either brain or liver. Post hoc comparisons using Tukey's test confirmed that the differences between each treatment group and the HMG group were statistically significant (adjusted p < 0.001 for all).

3.1.2.2. SOD in the Brain, Heart, Lung and Liver Tissues

As illustrated in Figure 1C, compared with the NCG, SOD activities in the brain, heart, lung, and liver tissues of HMG mice were significantly decreased to 21.0%, 36.3%, 37.5%, and 33.3%, respectively (all p < 0.001). After intervention with DZE‐L, DZE‐M, DZE‐H, and ACTZ, compared with the HMG, SOD activities in hypoxic mice were elevated as follows:

In brain: to 19.0% (n.s.), 28.1% (p < 0.01), 30.9% (p < 0.001), and 30.2% (p < 0.001).

In heart: to 39.0%, 63.2%, 91.6%, and 88.6% (all p < 0.001).

In lung: to 18.7% (n.s.), 28.0% (p < 0.01), 52.0% (p < 0.001), and 59.8% (p < 0.001).

In liver: to 7.0% (n.s.), 34.4% (p < 0.001), 58.3% (p < 0.001), and 58.4% (p < 0.001).

Comparison between DZE‐H and ACTZ: No statistically significant differences in SOD activities were observed between DZE‐H and ACTZ in any of the four tissues examined, indicating comparable antioxidant enzyme restoration efficacy between DZE‐H and ACTZ.

3.1.2.3. MDA and GSH‐Px in Liver Tissue

As shown in Figure 1D, compared with the NCG, MDA levels in the liver of HMG mice were significantly increased to 2.79‐fold of the control value (p < 0.001). In contrast, GSH‐Px activity (Figure 1E) in the liver of HMG mice was markedly decreased to 77.4% (p < 0.001). After giving drug intervention, compared with the HMG, the levels of MDA in the liver tissues in DZE‐L, DZE‐M, DZE‐H, and ACTZ groups were decreased to 24.30%, 40.03%, 57.15%, and 59.34% (all p < 0.001), and the activities of GSH‐Px were increased to 1.77‐ (p < 0.05), 2.77‐ (p < 0.01), 3.74‐ (p < 0.001), and 4.07‐fold (p < 0.001), respectively.

Comparison between DZE‐H and ACTZ: No significant differences were found between DZE‐H and ACTZ in either MDA levels or GSH‐Px activities, demonstrating that DZE‐H achieves comparable efficacy to ACTZ in alleviating oxidative stress and restoring antioxidant capacity in the liver.

3.1.3. DZE Alleviated Hypoxia‐Induced Inflammatory Response in Multiple Tissues

As shown in Figure 2A–C, compared with the NCG, the HMG exhibited marked elevations in the levels of TNF‐α, IL‐1β, and IL‐6, which increased to 5.10‐, 8.84‐, and 5.48‐fold of the control values in brain tissue, and to 4.37‐, 5.56‐, and 5.74‐fold in lung tissue, respectively. Following intervention with DZE‐L, DZE‐M, DZE‐H, and ACTZ, compared with the HMG, all these factors were decreased as follows:

FIGURE 2.

DZE reduced the inflammatory factors in hypoxic‐injured tissues. Data are expressed as mean ± SD (n = 10/group) (A: TNF‐α; B: IL‐1β; C: IL‐6). Note: ^### p < 0.001 NCG versus HMG; ***p < 0.001, HMG versus medication groups; ^& p < 0.05, ^&&& p < 0.001, DZE‐H versus ACTZ. ACTZ, positive control group; HMG, hypoxia model group; DZE‐H, DZE high‐dose group; DZE‐L, DZE low‐dose group; DZE‐M, DZE medium‐dose group; NCG, normal control group.

In brain: TNF‐α to 45.4%, 60.5%, 74.5%, and 74.5%; IL‐1β to 14.1%, 54.8%, 88.4%, and 88.7%; IL‐6 to 47.5%, 62.5%, 76.2%, and 81.1%.

In lung: TNF‐α to 44.2%, 62.7%, 77.3%, and 79.2%; IL‐1β to 23.3%, 51.2%, 78.9%, and 81.1%; IL‐6 to 40.9%, 61.4%, 73.5%, and 86.2%.

All these changes showed statistically significant differences (p < 0.001).

Comparison between DZE‐H and ACTZ: For TNF‐α and IL‐1β, no significant differences were observed between DZE‐H and ACTZ in either lung or brain tissues. However, for IL‐6, ACTZ showed significantly greater suppression compared with DZE‐H in both lung (p < 0.001) and brain (p < 0.05), indicating that ACTZ exerts a more potent anti‐inflammatory effect specifically on IL‐6 production under acute hypoxic conditions.

3.1.4. DZE Improved Hypoxia‐Induced Energy Metabolism in Multiple Tissues

3.1.4.1. CK in the Heart Tissue

As shown in Figure 3A, compared with the NCG, the level of CK in heart tissue of HMG mice was significantly increased to 6.39‐fold of the control value (p < 0.001). Following drug intervention, compared with the HMG, the CK levels in DZE‐L, DZE‐M, DZE‐H, and ACTZ groups mice were decreased to 20.57% (p < 0.01), 54.29% (p < 0.001), 71.90% (p < 0.001), and 78.34% (p < 0.001), respectively.

FIGURE 3.

DZE improved the energy metabolism indicators in hypoxic‐injured tissues. Data are expressed as mean ± SD (n = 10/group) (A: CK; B: Na⁺‐K⁺‐ATPase; C: ATP; D: LDH; E: LD). Note: ^### p < 0.001 NCG versus HMG; *p < 0.05, **p < 0.01, ***p < 0.001, HMG versus medication groups. ACTZ, positive control group; HMG, hypoxia model group; DZE‐H, DZE high‐dose group; DZE‐L, DZE low‐dose group; DZE‐M, DZE medium‐dose group; NCG, normal control group.

Comparison between DZE‐H and ACTZ: No significant difference was observed between DZE‐H and ACTZ in CK levels, indicating comparable myocardial protection efficacy.

3.1.4.2. Na⁺‐K⁺‐ATPase and ATP in Brain, Heart and Liver Tissues

Compared with the NCG, the activities of Na⁺‐K⁺‐ATPase (Figure 3B) and the ATP levels (Figure 3C) in the brain, heart, and liver tissues of HMG mice were significantly decreased to 61.62%, 61.99%, and 51.00%, as well as 76.63%, 73.59%, and 75.50%, respectively (all p < 0.001). Following intervention with DZE‐L, DZE‐M, DZE‐H, and ACTZ, compared with the HMG group:

Na⁺‐K⁺‐ATPase activities were increased:

In brain: to 1.43‐, 1.63‐, 2.19‐, and 2.32‐fold, respectively (all p < 0.001).

In heart: to 50.8%, 2.22‐, 2.95‐, and 2.78‐fold, respectively (all p < 0.001).

In liver: to 50.5% (p < 0.05), 62.9% (p < 0.001), 74.3% (p < 0.001), and 91.2% (p < 0.001), respectively.

ATP levels were increased:

In brain: to 1.38‐, 3.28‐, 4.13‐, and 3.40‐fold, respectively (p < 0.001 for all except 1.38‐fold which was no significance).

In heart: to 2.46‐, 3.33‐, 3.61‐, and 3.54‐fold, respectively (all p < 0.001).

In liver: to 92.8%, 2.91–, 4.13, and 3.81‐fold, respectively (p < 0.001 for all except 92.8% which was no significance).

Comparison between DZE‐H and ACTZ: For Na⁺‐K⁺‐ATPase, no significant differences were observed between DZE‐H and ACTZ in any tissue. For ATP levels, ACTZ showed significantly lower ATP levels than DZE‐H in brain tissue (p < 0.05), while no significant differences were found in liver or heart. This suggests that DZE‐H may be particularly effective in restoring cerebral energy metabolism.

3.1.4.3. LDH and LD in Brain and Liver Tissues

Compared with the NCG, LDH activities (Figure 3D) in the brain and liver tissues of HMG mice were significantly increased to 2.40‐fold and 2.55‐fold of the control values, respectively. LD levels (Figure 3E) were increased to 2.04‐fold and 2.89‐fold, respectively. Following intervention with DZE‐L, DZE‐M, DZE‐H, and ACTZ, compared with the HMG group, LDH activities were decreased:

In brain: to 19.3%, 28.5%, 50.6%, and 53.7%.

In liver: to 30.4%, 37.1%, 48.4%, and 48.4%.

LD levels were decreased:

In brain: to 19.6%, 39.9%, 58.3%, and 64.9%.

In liver: to 27.6%, 31.3%, 47.6%, and 56.7%.

All these changes showed statistically significant differences (p < 0.001).

Comparison between DZE‐H and ACTZ: For LDH activities, no significant differences were observed between DZE‐H and ACTZ in either liver or brain. However, for LD levels, DZE‐H showed significantly higher levels compared with ACTZ in both liver (p < 0.001) and brain (p < 0.05), indicating that ACTZ was more effective in reducing anaerobic glycolysis and lactate accumulation under acute hypoxic conditions.

3.2. Quantitative Analysis of 12 Pharmaceutical Components in DZE

3.2.1. Optimization of LC–MS/MS Conditions

Based on our previous study (Liu et al. 2017), the LC–MS/MS conditions were established. The optimization process began with investigating the optimal mass detection parameters for each component using negative ion MRM mode. Subsequently, chromatographic conditions, including the analytical column, mobile phase composition, and gradient elution program, were systematically optimized. Figure 4 displays the extracted ion chromatograms (EICs) of the 12 analytes and IS. The final mass spectrometry parameters, such as MRM transitions, retention times, and optimized DP and CE values, are summarized in Table 1. Under the established conditions, all 12 analytes and the IS were well separated within 12 min. Quantitative analysis was carried out using the IS method.

FIGURE 4.

EICs of 12 pharmaceutical components and IS (A: sample; B: reference substance).

3.2.2. Validation Study

The validation results are summarized in Tables 2 and 3. The calibration curves exhibited good linearity (r = 0.9957–0.9997). The MQL ranged from 3.1 to 74.9 ng/mL. Intraday and interday precision, expressed as relative standard deviation (RSD), fell within 1.73%–4.97% and 2.93%–4.85%, respectively. Repeatability was below 4.55%, and the mean recoveries ranged from 94.11% to 102.46% (RSD ≤ 4.39%). The short‐term stability showed an RSD of less than 4.88%. These results demonstrate that the proposed method is precise and accurate, and is suitable for the simultaneous quantification of the 12 components in DZE.

TABLE 2.

Calibration curves, linear ranges and MQL of 12 pharmaceutical components.

Analyte	Calibration curves	Linear range (ng/mL)	r	MQL (ng/mL)
Gallic acid	Y = 6.16 × 10−2 X + 5.59 × 10−1	37.3–1192.3	0.9996	37.3
Salidroside	Y = 2.09 × 10−2 X + 2.69 × 10−1	31.4–1004.0	0.9993	31.4
Bergeninum	Y = 1.70 × 10−2 X + 1.41 × 10−2	3.2–102.0	0.9986	3.2
Ethyl gallate	Y = 1.73 × 10−1 X + 3.28 × 10−1	5.0–161.2	0.9983	5.0
Epicatechin gallate	Y = 5.19 × 10−2 X + 9.84 × 10−1	74.9–2397.3	0.9997	74.9
p‐Coumaric acid	Y = 1.64 × 10−1 X + 1.01	12.5–400.0	0.9984	12.5
Quercitrin	Y = 5.08 × 10−2 X + 2.51 × 10−2	3.1–100.0	0.9978	3.1
Rhodiosin	Y = 7.13 × 10−3 X‐2.9 × 10−2	49.7–1590.8	0.9963	49.7
Quercetin	Y = 8.94 × 10−2 X + 3.05 × 10−1	19.8–633.3	0.9983	19.8
Luteolin	Y = 1.09 × 10−1 X + 4.23 × 10−1	9.9–315.6	0.9979	9.9
Kaempferol	Y = 7.70 × 10−3 X + 2.88 × 10−1	49.7–1590.8	0.9957	49.7
Rhodionin	Y = 1.71 × 10−2 X‐6.13 × 10−2	62.2–1991.2	0.9976	62.2

TABLE 3.

Precision, repeatability, stability and recovery of 12 pharmaceutical components.

Analyte	Precision (RSD %, n = 6)		Repeatability (RSD, %, n = 6)	Stability (RSD, % n = 6)	Recovery (%) (n = 9)
	Intraday	Interday			Mean	RSD
Gallic acid	2.47	3.36	3.08	3.70	100.54	1.70
Salidroside	3.59	4.27	2.99	4.87	97.82	3.88
Bergeninum	3.71	4.84	3.29	3.97	102.46	1.32
Ethyl gallate	4.97	4.22	4.55	4.86	95.52	1.30
Epicatechin gallate	4.76	4.26	1.87	4.54	99.01	3.14
p‐Coumaric acid	2.96	4.50	2.89	4.32	97.48	0.92
Quercitrin	2.55	4.43	1.98	3.27	96.86	1.97
Rhodiosin	4.30	4.62	3.70	4.88	94.11	0.99
Quercetin	3.99	2.93	4.48	3.88	97.91	4.39
Luteolin	1.73	3.88	3.41	3.54	99.20	1.14
Kaempferol	4.53	4.72	4.11	3.58	95.95	3.58
Rhodionin	4.39	4.85	3.11	4.59	98.30	1.56

3.2.3. Sample Analysis

The developed analytical method was subsequently applied to quantify 12 components in five batches of DZE supplied by Jiangsu Kanion Pharmaceutical Co. Ltd. Representative EICs are shown in Figure 4, and the contents of the analytes are summarized in Table 4.The results revealed that gallic acid was the most abundant compound (19.44 mg/g), followed by salidroside (12.15 mg/g), both exceeding the 1% level. Rhodionin (3.43 mg/g) and rhodiosin (2.73 mg/g) were present at levels above 0.1%. In addition, p‐coumaric acid (0.53 mg/g), kaempferol (0.34 mg/g), and epicatechin gallate (0.31 mg/g) all displayed contents above 0.01%. Meanwhile, the contents of bergenin, ethyl gallate, quercitrin, quercetin, and luteolin were relatively low, though all surpassed 10 μg/g.

TABLE 4.

Contents of 12 pharmaceutical components in five batches of sample.

Analyte	Content of each compound in five batches of samples (mg/g)
	Z180101	Z180102	Z180103	Z191001	Z191002	Average
Gallic acid	17.66	18.92	19.84	19.69	21.06	19.44
Salidroside	14.29	14.01	13.07	9.62	9.77	12.15
Bergenin	0.01	0.01	0.01	0.01	0.01	0.01
Ethyl gallate	0.02	0.02	0.02	0.02	0.02	0.02
Epicatechin gallate	0.28	0.29	0.35	0.32	0.31	0.31
p‐coumaric acid	0.54	0.47	0.35	0.65	0.63	0.53
Quercitrin	0.01	0.01	0.01	0.02	0.02	0.01
Rhodiosin	2.46	3.07	1.99	2.96	3.16	2.73
Quercetin	0.04	0.04	0.04	0.07	0.07	0.05
Luteolin	0.07	0.07	0.08	0.05	0.06	0.06
Kaempferol	0.21	0.20	0.38	0.45	0.48	0.34
Rhodionin	3.21	3.50	2.52	3.90	3.99	3.43

4. Discussion

Hypobaric hypoxia, the defining characteristic of high‐altitude environments, represents a primary pathogenic factor in high‐altitude illness (HAI) (Cai et al. 2026). Normobaric hypoxia models provide valid experimental platforms for simulating high‐altitude conditions, as the severity of AMS remains comparable under equivalent hypoxic conditions regardless of pressure differences (Kallenberg et al. 2007; Schommer et al. 2012). In this study, we established a normobaric hypoxic mouse model (10% O₂, 12 h) to evaluate the protective effects of DZE against acute hypoxic organ damage.

4.1. Tissue‐Specific Protective Effects of DZE

Our results revealed a notable organ‐specific hierarchy in DZE's protective efficacy, with the liver and brain showing the most pronounced responses, followed by the heart and lung. This differential susceptibility can be interpreted through three interconnected mechanisms.

4.1.1. Basal Antioxidant Reserves

Differences in baseline antioxidant capacity across organs may explain the observed hierarchy. The brain, characterized by high oxygen consumption and relatively low intrinsic antioxidant enzyme activities (SOD, H₂O₂, and GSH‐P_x), is exceptionally vulnerable to hypoxia‐induced oxidative stress (Lira‐Mejia et al. 2025). Similarly, the liver, as the primary metabolic hub, experiences massive ROS generation during hypoxia due to mitochondrial electron transport chain dysfunction (Cao et al. 2022). The robust restoration of T‐AOC and SOD activities in these two organs by DZE—2.91‐ and 3.08‐fold increases in brain and liver T‐AOC, respectively—suggests that DZE's antioxidant components, particularly gallic acid and its derivatives (19.77 mg/g), may preferentially target these high‐metabolic‐rate tissues. In contrast, the heart and lung exhibited relatively smaller responses, possibly due to their more robust endogenous protective mechanisms or differential pharmacokinetic profiles of DZE constituents.

4.1.2. Oxidative‐Inflammatory Crosstalk

The interplay between oxidative stress and inflammatory cascades amplifies organ damage in a tissue‐specific manner. Hypoxia stabilizes HIF‐1α, which subsequently activates NF‐κB signaling, driving the transcription of pro‐inflammatory cytokines including TNF‐α, IL‐1β, and IL‐6 (Zhang et al. 2025). DZE reduced these cytokines by 74.5%–88.4% in brain and 73.5%–86.2% in lung, aligning with the established anti‐inflammatory actions of salidroside via NF‐κB/NLRP3 pathway inhibition (Jiang et al. 2022). Notably, ACTZ showed superior IL‐6 suppression in both lung (p < 0.001) and brain (p < 0.05), reflecting fundamental mechanistic divergence: ACTZ improves systemic oxygenation via carbonic anhydrase inhibition, whereas DZE exerts multimodal effects through radical scavenging and broad inflammatory modulation. This suggests DZE and ACTZ may be complementary—DZE offering broader antioxidant coverage and ACTZ providing targeted IL‐6 suppression.

4.1.3. Energy Metabolism Restoration

Hypoxia inhibits Na⁺‐K⁺‐ATPase activity, disrupting ion gradients and leading to cellular edema and ATP depletion (Jiang et al. 2022). DZE‐H significantly elevated ATP levels in brain tissue compared with ACTZ (p < 0.05), suggesting particular efficacy in preserving cerebral energy homeostasis, likely mediated by flavonoids (quercetin, kaempferol, and luteolin; total 6.62 mg/g) that protect mitochondrial function and maintain ATP synthesis under hypoxia (Duarte et al. 2025). The concurrent reduction in LDH activity and LD level indicates a shift from anaerobic glycolysis back toward oxidative phosphorylation, further supporting the bioenergetic benefits of DZE pretreatment—particularly meaningful in the brain, where lactate accumulation contributes to acidosis and neuronal injury.

4.1.4. Integrated Perspective

Collectively, these mechanisms provide a coherent framework for understanding the organ‐specific hierarchy of DZE's protective effects. The liver and brain, characterized by high metabolic rates, limited intrinsic antioxidant reserves, and pronounced inflammatory responses, exhibit the greatest vulnerability and consequently show the most substantial improvement. The heart and lung, with more robust endogenous defenses, demonstrate more modest but significant responses. This integrated perspective supports the clinical application of DZE for preventing hypoxic encephalopathy and hepatic dysfunction in AMS, with the DZE‐H dose (2.4 g/kg) establishing a therapeutic window comparable to ACTZ across most parameters.

4.2. Phytochemical Synergy Underpinning DZE Efficacy

Our quantitative analysis identified gallic acid (19.44 mg/g) and salidroside (12.15 mg/g) as the predominant constituents of DZE, followed by flavonoids (total 6.62 mg/g) and minor components including p‐coumaric acid (0.53 mg/g) and bergenin (0.01 mg/g). The therapeutic efficacy arises from synergistic interactions among these components across multiple pathways.

Gallic acid exerts antioxidant effects via Nrf2/HO‐1 activation while suppressing NF‐κB‐mediated inflammation (Sohrabi et al. 2021; Xiang et al. 2024). Salidroside provides neuroprotective and cardioprotective effects under hypobaric hypoxia through inhibition of mitochondrial permeability transition pore opening and reduction of mitophagy (Hu et al. 2021; Jiang et al. 2022; F. Wang et al. 2025). Flavonoids offer complementary benefits: quercetin and kaempferol directly scavenge ROS, while rhodiosin and rhodionin enhance HIF‐1α degradation, attenuating pathological angiogenesis and inflammation (Ou et al. 2020). Minor constituents also contribute—p‐coumaric acid improves mitochondrial function (Liang et al. 2026), and bergenin exerts antiapoptotic effects via SIRT1/FOXO3a/NF‐κB signaling (Alanazi et al. 2025).

The hierarchical abundance (gallic acid derivatives > salidroside > flavonoids > minor phenolics) likely underlies the dose‐dependent efficacy observed. The DZE‐H group (2.4 g/kg) achieved superior or comparable effects to ACTZ across most parameters, suggesting that at this dosage, combined bioactive constituents reach thresholds sufficient to engage multiple protective pathways simultaneously. This polypharmacological profile—targeting oxidative stress, inflammation, and energy metabolism through distinct but complementary mechanisms—represents a fundamental advantage of DZE over single‐target agents like ACTZ.

Unlike previous studies that focused on single compounds or single‐organ effects (Jiang et al. 2022; F. Wang et al. 2025), our integrated approach simultaneously evaluates multiorgan protection and comprehensive phytochemical profiling, providing a more holistic understanding of DZE's antihypoxic efficacy.

4.3. Study Limitations

Several limitations should be acknowledged.

First, while we observed significant improvements in biochemical markers, histopathological examination was not performed. Direct visualization of tissue morphology would provide complementary evidence for the organ‐protective effects of DZE.

Second, our acute hypoxia model (12 h) primarily captures early molecular events; whether DZE confers long‐term protection against chronic hypoxic injury remains to be determined.

Third, sex‐based analysis was not conducted, as only male mice were used to avoid estrogen‐related confounding effects on oxidative stress and inflammation; however, this limits the generalizability of our findings to female populations.

Fourth, we did not measure hematological parameters (e.g., hemoglobin, hematocrit, and red blood cells), which would have provided additional insight into DZE's effects on oxygen‐carrying capacity and polycythemia. Finally, while we identified 12 bioactive constituents, direct causal links between specific compounds and observed pharmacological effects remain inferential, as no pharmacokinetic and bioavailability studies were conducted. Future investigations incorporating these parameters, along with pathway‐specific inhibitors (e.g., Nrf2 siRNA and NF‐κB inhibitors), are warranted to definitively establish the mechanistic basis of DZE's antihypoxic activity.

5. Conclusions

This study demonstrates that DZE confers dose‐dependent protection against acute hypoxic injury in mice, with the most pronounced effects in the liver and brain. The protective mechanisms entail coordinated alleviation of oxidative stress, inflammatory responses, and energy metabolic disturbance. The optimal dose (2.4 g/kg, DZE‐H) achieved comparable or superior efficacy to acetazolamide (0.2 g/kg) across most parameters.

The antihypoxic efficacy of DZE arises from synergistic interactions among its predominant constituents—gallic acid and its derivatives (19.77 mg/g), salidroside (12.15 mg/g), and flavonoids (6.62 mg/g)—with minor contributions from p‐coumaric acid and bergenin.

Nevertheless, these conclusions must be tempered by the preclinical scope of our study. Critical limitations—namely, the absence of pharmacokinetic profiling, sex‐stratified analyses, and pathway‐specific mechanistic confirmation—preclude any direct extrapolation to human AMS, especially given species disparities in hypoxic metabolism and clinical complexity. Accordingly, our findings offer a hypothesis‐generating preclinical basis, not established therapeutic proof. Further validation in higher animal models is mandatory before clinical consideration.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Normobaric hypoxia chamber.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.