A total of 86 patients with acute asthma from the Respiratory Department in our Hospital were enrolled between January 2021 and December 2024. Asthma diagnosis was based on the diagnostic criteria of the Global Initiative for Asthma (GINA) (Girodet and Molimard, 2021). Asthma severity was assessed and further divided into mild (n = 41), moderate (n = 26), and severe (n = 19) groups. The inclusion criteria were as follows: (i) in line with the diagnostic criteria of the Global Initiative for Asthma; (ii) age ≥18 years; (iii) first onset of illness; and (iv) complete clinical data. The exclusion criteria were as follows: (i) other respiratory or immune system-related diseases; (ii) diseases that combine with circulatory, digestive, urinary, and neurological systems; (iii) history of allergic diseases or family history of asthma; and (iv) use of medications such as glucocorticoids within the past 3 months. The control group included healthy subjects who came for routine health screenings or outpatient asthma patients on admission with matched age and sex. The research procedure complied with the Declaration of Helsinki and was approved by the Medical Ethics Committee of our hospital. Figure 1 illustrates the overall framework of this study.

The complete clinical and laboratory data of enrolled patients with asthma in remission and with acute asthma were collected, including age, sex, body mass index (BMI), smoking status, total immune globulin E (IgE), blood eosinophils, and blood neutrophils. Pulmonary function tests (PFT) were performed using portable spirometry to determine forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The FEV1/FVC ratio was FEV1 predicted was calculated according to the following formula: male: 0.041 × height (cm) - (0.018 × age) - 2.69; female: 0.033 × height (cm) - (0.022 × age) - 2.49.

Whole blood (5 mL) was collected from fasting participants between 8:00 a.m. and 9:00 a.m. using serum separation tubes without anticoagulant. The samples were allowed to clot at room temperature for 30 min and were then centrifuged within 4 h at 3,000 rpm for 10 min. The supernatant serum was carefully collected, aliquoted to avoid repeated freeze-thaw cycles, and stored at −80 °C until further analysis.

Whole blood (5 mL) was collected from each fasting participant and placed in a common biochemical tube. This blood sample was mixed with equal volume phosphate buffered saline (PBS) to form a diluent of peripheral blood. This diluted peripheral blood was added slowly in another centrifuge tube containing lymphocyte separation solution (Ficoll-Paque™ PLUS; GE Healthcare, Chicago, IL, United States; Cat. No. 17–1440–03). Then the solution was centrifuged at room temperature for 20 min (2000 r/min), and obvious delamination can be seen in the centrifuge tube. The white film layer was drawn with a Pasteur tube, and place it in a new centrifuge tube. After washed by PBS, the supernatant was discarded and cell pellet was obtained as PBMCs and counted.

After isolation of PBMCs, 1000 μL of RPMI 1640 medium was added to resuspend the cell pellet, followed by centrifugation at 300 g for 5 min, the supernatant was discarded, and the cells were resuspended with 100 μL of pre-cooled PBS. The PBMCs were incubated with anti-human CD3 mAb (BD Biosciences, San Jose, CA, United States; Cat. No. 555339) and anti-human CD8 mAb (BD Biosciences; Cat. No. 555369) at 4 °C in the dark for 30 min (for anti-labeling CD4 + T cells). Then cells were washed by 3 mL pre-cooled PBS by centrifugation at 300 g for 5 min. After discarding the supernatant, cells were resuspend with PBS. Cells were incubate with 100 μL membrane permeabilization solution (BD Cytofix/Cytoperm™, BD Biosciences; Cat. No. 554714) at room temperature for 10 min, and then add with anti-human IL-4 mAb (BD Biosciences; Cat. No. 554486) and anti-human-IL-17A mAb (BD Biosciences; Cat. No. 560486), respectively. After incubation at 4 °C in the dark for 30 min, cells were washed with PBS, and resuspend by adding 300 μL pre-cooled PBS and immediately perform a BD FACSCanto™ II flow cytometer (BD Biosciences) to analyze Th2 and Th17 cells. Data acquisition and analysis were performed using FlowJo software (version 10.8.1; BD Biosciences). (CD3⁺ CD8⁻IL-IL-4⁺) accounted for the proportion of Th2 cell population, and (CD3⁺CD8⁻IL-17A⁺) accounted for the proportion of Th17 cell population.

FeNO levels were measured using a nitric oxide analyzer (Sunvou-CA2122 system, China) that operates at a 50 mL/s exhalation flow rate, with the results expressed in parts per billion (ppb) (Menzies et al., 2007). Fractional exhaled nitric oxide (FeNO) and nasal nitric oxide (FnNO) levels were measured. Each participant underwent two measurements, maintaining an exhalation time of 10 s for each test.

An enzyme-linked immunosorbent assay (ELISA) was used to measure the serum levels of interleukin-4 (IL-4; D4050, R&D Systems), interleukin-5 (IL-5; D5000B, R&D Systems), interleukin-13 (IL-13; D1300B, R&D Systems), vascular endothelial growth factor A (VEGF-A; SEKH-0052, Solarbio), stromal cell-derived factor 1 alpha (SDF-1α; ml038196, Shanghai Enzyme-linked Biotechnology), transforming growth factor beta 1 (TGF-β1; DY240, R&D Systems), matrix metallopeptidase 9 (MMP-9; DMP900, R&D Systems), hyaluronan (DHYAL0, R&D Systems), and soluble lymphatic vessel endothelial hyaluronan receptor 1 (sLYVE1; DY2089, R&D). Experiments were performed according to the manufacturer’s instructions.

Human airway smooth muscle cells (ASMCs) were purchased from ScienCell Research Labs (Carlsbad, CA, USA) and cultured in high-glucose DMEM (Gibco, Waltham, MA, USA) and 10% FBS (Gibco) at 37 °C with 5% CO₂. ASMCs were divided into four groups: (i) Control group: conventional culture; (ii) Model group (PDGF-BB + si-NC): cells were transfected with si-NC for 24 h, and then treated with PDGF-BB (20 ng/mL) for further 24 h; (iii) LYVE-1 silencing group (PDGF-BB + si-LYVE-1): cells were transfected with si-LYVE-1 for 24 h, and stimulated with 20 ng/mL PDGF-BB for 24 h (iv) Pathway inhibitor group (PDGF-BB + si-LYVE-1 + IGF-1): Cells were transfected with si-LYVE-1 for 24 h and then co-treated with IGF-1 (100 ng/mL) and PDGF-BB (20 ng/mL) for a further 24 h.

ASMCs in the logarithmic growth phase were cultured in high-glucose DMEM with 10% FBS and seeded in 6-well plates (1.0 × 10⁵ cells/well). Cells were starved in DMEM with 1% FBS for 12 h. LYVE-1 siRNA (si-LYVE-1) or its negative control (si-NC) was introduced into ASMCs using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). After incubation overnight, the cells were replaced with DMEM with 10% FBS. After 48 h, transfection efficiency was verified using RT-qPCR and Western blotting. LYVE-1 siRNA and control siRNA sequences were synthesized by Suzhou Jima Gene Co., Ltd. The sequence of siRNA is as follows: si-LYVE-1-1: (forward, 5′GCA GCA GCA UGA AGA AAC A-3′; reverse, 5′-CGU CGU CGU ACU UCU UUG U-3′), si-LYVE-1-2: (forward, 5′-GCU GCU GCU UUG GAU GAA G-3′; reverse, 5′-CGA CGA CGA AAC CUA CUU C-3′); si-LYVE-1-3: (forward, 5′-CCA UGU GGA UGC UGA UGA A-3′; reverse, 5′-GGU ACA CCU ACG ACU ACU U-3′); si-NC (forward, 5′-UUC UCC GAA CGU GUC ACG U-3′; reverse, 5′-AAG AGG CUU GCA CAG UGC A-3′).

Cell viability was assessed using the MTT assay. Airway smooth muscle cells (ASMCs) were seeded in 96-well plates at a density of 1 × 10⁴ cells/well and cultured overnight at 37 °C in a humidified atmosphere containing 5% CO₂ to allow cell attachment. After the indicated treatments, 20 µL of MTT solution (1 mg/mL; M1020, Solarbio, Beijing, China) was added to each well and incubated for 3–4 h at 37 °C to allow the formation of purple formazan crystals. The supernatant was carefully removed, and 100 µL of dimethyl sulfoxide (DMSO) was added to dissolve the formazan crystals. Absorbance was measured at 570 nm using a microplate reader, and the background absorbance from the blank wells was subtracted. Cell viability was expressed as a percentage of the untreated control according to the following formula: viability (%) = [(A_sample-A_blank)/(A_control-A_blank)] × 100. All experiments were performed in at least six technical replicates and repeated independently thrice to ensure reproducibility.

Cell migration was evaluated using a Transwell chamber assay. Cell migration was assessed using 24-well Transwell inserts (BD Biosciences, San Diego, CA, USA) with 8-μm pore polycarbonate membranes. ASMCs were resuspended in serum-free medium, and 5 × 10⁴ cells in 500 μL were seeded into the upper chamber of each insert. The lower chamber was filled with 700 μL of complete medium containing 10% FBS, which served as a chemoattractant. After incubation for the indicated time at 37 °C in a humidified 5% CO₂ atmosphere, non-migrated cells remaining on the upper surface of the membrane were gently removed using a cotton swab. The migrated cells on the lower surface were fixed with 4% paraformaldehyde for 15 min and stained with 0.1% crystal violet for 10–15 min at room temperature. The stained cells were washed with PBS to remove excess dye, air-dried, and imaged under an inverted microscope at ×100 magnification. The migrated cells were counted in at least five randomly selected microscopic fields per insert, and the average number was used for the statistical analysis. All experiments were performed in triplicate to ensure reproducibility.

Culture supernatants from treated ASMCs were collected, centrifuged at 1,000–2,000 × g for 5 min to remove cellular debris, aliquoted, and stored at −80 °C until analysis. Secreted levels of TNF-α (DTA00D), IL-1β (DLB50), and IL-6 (D6050B) were quantified using commercial enzyme-linked immunosorbent assay (ELISA) kits (R&D Systems) according to the manufacturer protocol. Briefly, standards and samples were loaded in duplicate onto pre-coated 96-well plates, incubated with the supplied detection reagents, and subjected to the recommended wash steps to remove unbound antibodies. After the addition of the substrate solution and termination of the reaction, the optical density was measured at 450 nm with a wavelength correction of 540–570 nm using a microplate reader.

Intracellular reactive oxygen species (ROS) levels were measured using the fluorescent probe dihydroethidium (DHE; S0063, Beyotime). Briefly, after the indicated treatments, ASMCs cultured on glass-bottom dishes or coverslips were washed twice with warm PBS and incubated with DHE (10 µM in serum-free medium) for 30 min at 37 °C in the dark. Following incubation, the cells were gently washed twice with PBS and immediately imaged live using an inverted fluorescence microscope at ×200 magnification. DHE-derived red fluorescence (oxidized ethidium intercalated into DNA) was detected using the appropriate red fluorescence filter settings. For each condition, images were acquired from at least five randomly selected fields per replicate, and experiments were performed in three independent biological replicates for each condition. Intracellular ROS levels were quantified by measuring the mean fluorescence intensity per field using ImageJ (NIH) after background subtraction and normalization to the cell number.

Oxidative stress in ASMCs was evaluated by determining the levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) using commercial assay kits (Beyotime, Shanghai, China). Lipid peroxidation was quantified by measuring the MDA concentration using an MDA assay kit (S0131S), and absorbance was measured at 532 nm. SOD activity was determined using an SOD assay kit (S0109), and the absorbance was measured at 450 nm. GPx activity was assessed using a GPx assay kit (S0056) according to the manufacturer’s instructions, and the absorbance was measured at 340 nm. All measurements were performed in triplicate and expressed as units per milligram of protein or relative to control values. Each experiment was independently repeated at least thrice to ensure reproducibility.

Total RNA was extracted from the treated airway smooth muscle cells using TRIzol reagent (Invitrogen) according to the manufacturer’s instructions, and RNA concentration and purity (A260/A280) were assessed using a NanoDrop spectrophotometer. One microgram of total RNA was reverse-transcribed to cDNA using a commercial reverse transcription kit (PrimeScript RT kit, Takara) in a 20 µL reaction, following the manufacturer’s protocol. Quantitative real-time PCR (RT-qPCR) was performed on an ABI 7500 Real-Time PCR System (Applied Biosystems) using an SYBR Green–based master mix (SYBR Green PCR Master Mix, Applied Biosystems) in 20 µL reaction volumes containing 2 µL of cDNA and 400 nM of each primer. Primer sequences are listed in Supplementary Table S1 and the housekeeping gene used for normalization is indicated therein. The thermal cycling conditions were as follows: initial denaturation at 95 °C for 3 min, followed by 40 cycles of 95 °C for 10 s and 60 °C for 30 s, with a final melting curve analysis to verify product specificity. Each sample was run in technical triplicate, and the experiments were repeated at least three times independently. Relative transcript levels were calculated using the 2^−ΔΔCt method and expressed as fold changes relative to those of the control group.

Protein expression was analyzed using Western blotting. After the indicated treatments, ASMCs were washed twice with ice-cold PBS and lysed in 100 µL RIPA buffer (Beyotime, Shanghai, China) supplemented with 1 µL of protease and phosphatase inhibitor cocktails (Roche). The lysates were incubated on ice for 30 min and centrifuged at 12,000 × g for 15 min at 4 °C to remove debris. Supernatants were collected for protein quantification using the bicinchoninic acid (BCA) assay (Thermo Fisher Scientific). Equal amounts of protein (50 µg) were separated by 10% SDS-PAGE and transferred onto polyvinylidene difluoride (PVDF) membranes (Millipore). After blocking with 5% nonfat milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 h at room temperature, membranes were incubated overnight at 4 °C with the following primary antibodies: LYVE-1 (1:500, ab219556, rabbit monoclonal, Abcam), p-PI3K (p85, Tyr458; 1:400, ab278545, rabbit monoclonal, Abcam), PI3K (1:500, ab302958, rabbit monoclonal, Abcam), p-Akt (Ser473; 1:400, ab81283, rabbit monoclonal, Abcam), Akt (1:400, ab8805, rabbit polyclonal, Abcam), and GAPDH (1:2000, ab8245, mouse monoclonal, Abcam). Membranes were then washed with TBST and incubated with HRP-conjugated secondary antibodies for 1 h at room temperature. Protein bands were visualized using enhanced chemiluminescence (ECL) reagents (Thermo Fisher Scientific) and imaged using a ChemiDoc MP system (Bio-Rad). Densitometric analysis was performed using ImageJ software (NIH), and the protein expression levels were normalized to GAPDH and expressed relative to those of the control group. All experiments were independently repeated at least thrice.

All statistical analyses were performed using IBM SPSS Statistics software (version 20.0). Continuous data are expressed as mean ± standard deviation (SD). Categorical data were expressed as frequencies (percentages). Dermographic data were compared using one-way analysis of variance (ANOVA) or the Kruskal–Wallis test, followed by the LSD-Mean Multiple Comparison Test. Sex and smoking status were compared using the chi-square test. Pearson’s correlation analysis was performed to assess the correlations between sLYVE-1 levels, lung function, and other serum biomarkers. p < 0.05 was considered statistically significant.

A total of 238 participants were included in this study: 80 healthy controls, 72 patients with asthma in remission, and 86 patients with acute asthma. There were no significant differences in age or sex distribution among the groups, while the body mass index was slightly lower in patients with acute asthma (22.06 ± 2.75 kg/m²) than in controls (23.55 ± 2.47 kg/m²) and patients with remission (23.12 ± 2.80 kg/m²; p = 0.001). The prevalence of smoking was comparable across the groups (32.5%, 38.9%, and 40.7%; p = 0.525). Pulmonary function was markedly impaired in acute asthma, with reductions in FEV1 (1.89 ± 0.56 L), FEV1/FVC ratio (65.58% ± 4.90%), and predicted FEV1 (58.74% ± 8.35%) compared to those in the controls (3.15 ± 0.72 L, 80.52% ± 5.23%, and 98.24% ± 13.47%, respectively; all p < 0.001). Serum total IgE (199.71 ± 57.65 IU/mL) and eosinophil percentage (3.66% ± 0.80%) were significantly elevated in acute asthma relative to controls and remission patients (both p < 0.001), whereas neutrophil percentages did not differ significantly (p = 0.140). The proportions of Th2 and Th17 cells were significantly higher in acute asthma (3.01% ± 0.63% and 2.62% ± 0.56%, respectively; p < 0.001), consistent with elevated airway inflammation, as indicated by FeNO levels (44.66 ± 7.20 ppb; p < 0.001). Importantly, serum soluble LYVE-1 (sLYVE-1) levels progressively increased from healthy controls (376.89 ± 55.38 ng/mL) to remission (462.27 ± 58.52 ng/mL) and acute asthma patients (593.94 ± 101.94 ng/mL; p < 0.001) (Table 1), suggesting a potential role for LYVE-1 as a biomarker associated with asthma severity and airway inflammatory status.

Among the 86 patients with asthma stratified by disease severity, 41 had mild asthma, 26 had moderate asthma, and 19 had severe asthma. There were no significant differences in age, sex distribution, BMI, or smoking prevalence across the severity groups. Pulmonary function declined progressively with increasing asthma severity, as evidenced by reductions in FEV1 (2.12 ± 0.54 vs. 1.76 ± 0.50 vs. 1.55 ± 0.46 L), FEV1/FVC ratio (67.73% ± 4.78% vs. 64.62% ± 4.17% vs. 62.25% ± 3.88%), and predicted FEV1 (62.42% ± 7.52% vs. 57.77% ± 7.30% vs. 52.15% ± 7.15%; all p < 0.001). Total serum IgE (179.27 ± 48.96 vs. 206.78 ± 55.15 vs. 234.15 ± 62.21 IU/mL; P = 0.002) and eosinophil percentages (3.27% ± 0.65% vs. 3.81% ± 0.71% vs. 4.33% ± 0.77%; p < 0.001) increased with severity, whereas neutrophil percentages remained similar (p = 0.560). The proportions of Th2 and Th17 cells were significantly elevated in moderate and severe asthma (Th2:2.69% ± 0.50% vs. 3.12% ± 0.53% vs. 3.54% ± 0.65%; Th17:2.28% ± 0.37% vs. 2.71% ± 0.43% vs. 3.25% ± 0.47%; both p < 0.001), consistent with increased airway inflammation, as reflected by FeNO levels (40.44 ± 5.01 vs. 45.67 ± 5.82 vs. 52.40 ± 6.08 ppb; p < 0.001). Similarly, type 2 cytokines IL-4, IL-5, and IL-13 increased progressively with disease severity (IL-4: 28.69 ± 3.92 vs. 33.36 ± 4.35 vs. 38.37 ± 4.91 pg/mL; IL-5: 83.31 ± 11.66 vs. 93.23 ± 12.69 vs. 101.08 ± 15.82 pg/mL; IL-13: 18.09 ± 4.07 vs. 24.97 ± 4.44 vs. 31.46 ± 5.22 pg/mL; all p < 0.001). The markers of airway remodeling and angiogenesis, including VEGF-A, SDF-1α, TGF-β1, MMP-9, and hyaluronan, also increased significantly with asthma severity (all p < 0.001). Notably, serum soluble LYVE-1 (sLYVE-1) levels progressively increased from mild (532.71 ± 74.80 ng/mL) to moderate (621.96 ± 80.72 ng/mL) and severe asthma (687.75 ± 92.86 ng/mL; p < 0.001) (Table 2), indicating a potential association between LYVE-1 and disease severity, airway inflammation, and airway remodeling.

Serum soluble LYVE-1 (sLYVE-1) levels were measured using ELISA to evaluate their association with asthma and disease severity. As shown in Supplementary Figure S1A, circulating sLYVE-1 concentrations were significantly higher in patients with asthma than in healthy controls and progressively increased from patients in remission to those with acute asthma (p < 0.001). Further stratification by disease severity demonstrated a stepwise elevation in sLYVE-1 levels from mild to moderate and severe asthma (p < 0.01; Supplementary Figure S1B).

To assess the relationship between sLYVE-1 and pulmonary function, Pearson’s correlation analysis was performed in patients with acute asthma. Serum sLYVE-1 levels were negatively correlated with FEV1, FEV1/FVC ratio, and predicted FEV1 (Supplementary Figure S1C-E), indicating that higher sLYVE-1 concentrations were associated with more severe airflow limitations. Collectively, these findings suggest that elevated circulating sLYVE-1 levels reflect both asthma severity and impaired pulmonary function, supporting its potential utility as a biomarker for asthma disease progression.

Pearson’s correlation analysis was performed to investigate the relationship between circulating soluble LYVE-1 (sLYVE-1) levels and airway inflammation in patients with acute asthma. As shown in Supplementary Figure S2A-F, serum sLYVE-1 levels were positively correlated with total IgE, eosinophil percentage, neutrophil percentage, Th2 cell proportion, Th17 cell proportion, and FeNO, indicating that higher sLYVE-1 concentrations were associated with heightened systemic and airway inflammatory activity.

In addition, circulating sLYVE-1 levels showed significant positive correlations with type 2 inflammatory cytokines, including interleukin (IL)-4, IL-5, and IL-13 (Supplementary Figure S2G-I), further supporting a close association between sLYVE-1 and Th2-mediated immune responses in acute asthma. Collectively, these findings suggest that sLYVE-1 reflects both the magnitude of airway inflammation and type 2 immune activation, highlighting its potential utility as a biomarker of the inflammatory burden in acute asthma.

Pearson’s correlation analysis was performed to evaluate the association between circulating LYVE-1 levels and airway remodeling in patients with acute asthma. As shown in Supplementary Figure S3, serum sLYVE-1 levels were positively correlated with VEGF-A (Supplementary Figure S3A), SDF-1α (Supplementary Figure S3B), TGF-β1 (Supplementary Figure S3C), MMP-9 (Supplementary Figure S3D), and hyaluronan (Supplementary Figure S3E). These findings indicate that elevated sLYVE-1 levels reflect enhanced airway remodeling activity and suggest its potential role as a biomarker for structural changes in the asthmatic airways.

To investigate the regulation of LYVE-1 in airway smooth muscle cells (ASMCs), the cells were treated with increasing concentrations of PDGF-BB (0, 1, 5, 10, and 20 ng/mL) for 24 h. MTT assays demonstrated that PDGF-BB enhanced ASMC viability in a dose-dependent manner (Figure 2A). Correspondingly, LYVE-1 mRNA expression was significantly upregulated following PDGF-BB treatment, as determined by RT-qPCR (Figure 2B). Western blot analysis confirmed a dose-dependent increase in LYVE-1 protein levels (Figure 2C), which were quantified relative to GAPDH (Figure 2D). To assess the functional role of LYVE-1, ASMCs were transfected with three independent LYVE-1 siRNA sequences (si-LYVE-1#1, #2, and #3) or a control siRNA (si-NC). RT-qPCR analysis at 48 h post-transfection revealed a significant knockdown of LYVE-1 mRNA, with si-LYVE-1#2 exhibiting the most potent inhibitory effect (Figure 2E). Western blot analysis corroborated these findings at the protein level (Figure 2F), and quantification confirmed maximal LYVE-1 suppression with the sequence #2 sequence (Figure 2G). Therefore, si-LYVE-1#2 was selected for subsequent functional experiments.

To investigate the role of LYVE-1 in PI3K/Akt pathway activation, ASMCs were transfected with LYVE-1 siRNA (si-LYVE-1#2) for 24 h and subsequently treated with PDGF-BB (20 ng/mL) in the presence or absence of the PI3K/Akt activator IGF-1 (100 ng/mL) for another 24 h. Western blot analysis revealed that PDGF-BB treatment markedly increased the phosphorylation of PI3K (p85, Tyr458) and Akt (Ser473) compared that to in the untreated controls. LYVE-1 knockdown significantly attenuated PDGF-BB-induced phosphorylation of both PI3K and Akt (Figures 3A–C). Notably, co-treatment with IGF-1 partially restored PI3K/Akt phosphorylation in LYVE-1-silenced ASMCs, confirming that LYVE-1 modulates PDGF-BB-induced PI3K/Akt pathway activation in airway smooth muscle cells.

MTT assays demonstrated that LYVE-1 silencing significantly reduced PDGF-BB-induced ASMC viability compared to that in the control siRNA (Figure 3D). Transwell migration assays revealed that LYVE-1 knockdown markedly inhibited PDGF-BB-stimulated ASMC migration, as visualized by crystal violet staining (Figure 3E) and quantification of the number of migrated cells (Figure 3F). Additionally, RT-qPCR analysis showed that LYVE-1 silencing significantly decreased the mRNA expression of ECM-related genes, including Collagen I (Figure 3G), α-SMA (Figure 3H), and fibronectin (Figure 3I), indicating that LYVE-1 contributes to PDGF-BB-induced ASMC proliferation, motility, and ECM production.

To examine the role of LYVE-1 in airway smooth muscle cell (ASMC) inflammation, the cells were transfected with LYVE-1 siRNA (si-LYVE-1#2) and stimulated with PDGF-BB (20 ng/mL). RT-qPCR analysis revealed that LYVE-1 silencing significantly reduced PDGF-BB-induced mRNA expression of the pro-inflammatory cytokines TNF-α (Figure 4A), IL-1β (Figure 4B), and IL-6 (Figure 4C). Consistently, ELISA measurements of ASMC supernatants showed that LYVE-1 knockdown markedly decreased TNF-α (Figure 4D), IL-1β (Figure 4E), and IL-6 (Figure 4F) secretion compared with that in the control siRNA group. These results indicate that LYVE-1 contributes to PDGF-BB-stimulated inflammatory activation in ASMCs, highlighting its role in airway inflammation.

To evaluate the effect of LYVE-1 on oxidative stress, ASMCs were transfected with LYVE-1 siRNA (si-LYVE-1#2) and stimulated with PDGF-BB (20 ng/mL). Immunofluorescence analysis using DHE staining demonstrated that PDGF-BB markedly increased intracellular ROS levels, whereas LYVE-1 knockdown significantly reduced the number of DHE-positive cells relative to DAPI-stained nuclei (Figures 5A,B). Consistently, the assessment of oxidative stress markers in cell lysates showed that LYVE-1 silencing significantly decreased MDA levels (Figure 5C) and increased antioxidant enzyme activities, including SOD (Figure 5D) and GPx (Figure 5E), compared with the control siRNA. These results indicate that LYVE-1 contributes to PDGF-BB-induced oxidative stress in ASMCs and that its knockdown mitigates ROS accumulation and restores the antioxidant defenses.