Investigation of the mechanism of Yijing Decoction in the treatment of premature ovarian insufficiency: A network pharmacology study.

The original datasets used during the current study are available from the corresponding author upon reasonable request. The datasets generated and analyzed during the current study are available in the supplementary tables.

Yaqiong Xu: Conceptualization, Methodology, Validation, Writing – original draft. Xiaomei Zhao: Data curation, Validation, Writing – original draft. Wanhong Yu: Formal analysis, Funding acquisition. Peiyu Zhang: Resources, Validation. Zengmei Cheng: Resources, Validation. Lu Yang: Resources, Validation. Hua Zhou: Data curation, Funding acquisition, Project administration, Writing – review & editing.

The experimental procedures for animal handling were all approved by the Animal Ethics Committee of Guizhou Medical University Hospital (approval number:2101344).

All authors have agreed to publish.

This study was funded by the Guizhou Provincial Science and Technology Program (Qiankeheji - ZK [2023] Key 040 ), the Guizhou Provincial Department of Science and Technology Basic Research Program (Qiankeheji [2020] 1Y337 ), and the Guizhou Provincial Health Care Commission Science and Technology Fund Project ( gzwjkj2019-1-008 ).

After modeling, the rats showed lethargy, dull fur, and, in some cases, hair loss. Their responses to external stimuli were slowed. A subset of animals developed localized scattered skin petechiae, ulceration at the distal limbs, epistaxis, and hematochezia. Most rats died within 1 week after modeling; however, some animals presenting with skin petechiae survived and the lesions resolved following treatment with Yijing Decoction. After 14 consecutive days of observation, 92 of 100 rats exhibited more than two complete estrous cycles. Representative methylene-blue–stained vaginal cytology for the proestrus, estrus, metestrus, and diestrus phases is shown in Fig. 2 A. Following modeling, the estrous cycle was progressively disrupted in model rats, manifesting as prolonged proestrus or diestrus phases and loss of normal cyclicity. Oral gavage with Yijing Decoction did not produce an obvious improvement in estrous cyclicity within the first week of treatment; however, gradual restoration of cycles was evident after 1 week of treatment. Typical group-specific alterations in the estrous cycle are illustrated in Fig. 2 B. The proportion of rats maintaining regular estrous cycles over 14 consecutive days, assessed after 1 week of treatment, is presented in Fig. 2 C. The proportions of animals with regular cycles were 93.33 % in the control group, 10.00 % were in the model group, and 85.00 % were in the Yijing Decoction treatment group. The differences between the control and model groups were statistically significant ( P  < 0.05); similarly, the Yijing Decoction treatment group differed significantly from the model group ( P  < 0.05). Fig. 2 Rat estrous cycle, body weight, ovarian weight and ovarian index (A) Representative methylene-blue–stained vaginal cytology showing proestrus (red arrows indicate nucleated epithelial cells), estrus (red arrows indicate keratinized epithelial cells), metestrus/postestrus (red arrows indicate leukocytes; yellow arrows indicate nucleated epithelial cells; black arrows indicate keratinized epithelial cells), and diestrus/interestrus (red arrow indicates leukocytes); scale bar: 100 μm. (B) Graphical representation of typical estrous-cycle changes in each group (P: preestrus, E:estrus, M:postestrus, D:interestrus). (C) Proportion of animals in each group exhibiting ≥2 estrous cycles within a 14-day interval, assessed after 1 week of treatment and continuing through 3 weeks of treatment with Yijing Decoction. (D) Changes in body weight for each group before and after pairing males and females for mating (n = 10). (E) Body weight, bilateral ovarian wet weight and ovarian index for rats in each group (n = 10). Data are presented as mean ± SD. ∗ P  < 0.05; ns, not significant ( P  ≥ 0.05). Fig. 2 Rat estrous cycle, body weight, ovarian weight and ovarian index (A) Representative methylene-blue–stained vaginal cytology showing proestrus (red arrows indicate nucleated epithelial cells), estrus (red arrows indicate keratinized epithelial cells), metestrus/postestrus (red arrows indicate leukocytes; yellow arrows indicate nucleated epithelial cells; black arrows indicate keratinized epithelial cells), and diestrus/interestrus (red arrow indicates leukocytes); scale bar: 100 μm. (B) Graphical representation of typical estrous-cycle changes in each group (P: preestrus, E:estrus, M:postestrus, D:interestrus). (C) Proportion of animals in each group exhibiting ≥2 estrous cycles within a 14-day interval, assessed after 1 week of treatment and continuing through 3 weeks of treatment with Yijing Decoction. (D) Changes in body weight for each group before and after pairing males and females for mating (n = 10). (E) Body weight, bilateral ovarian wet weight and ovarian index for rats in each group (n = 10). Data are presented as mean ± SD. ∗ P  < 0.05; ns, not significant ( P  ≥ 0.05). Body weight increased with age in control rats; in contrast, body weight in the model group continued to decline after modeling. Rats receiving Yijing Decoction by oral gavage showed partial recovery of body weight, but values remained substantially lower than those of controls. In rats that became pregnant, body weight decreased slightly 1–2 days after pairing and then increased rapidly thereafter ( Fig. 2 D). Pre-sacrifice body weight was significantly greater in the control group than in the model group ( P  < 0.05); body weight in the Yijing Decoction group was also significantly greater than in the model group ( P  < 0.05). Bilateral ovarian wet weight was significantly greater in the control group than in the model group ( P   0.05). No significant differences were observed among groups for ovarian index ( P  > 0.05) ( Fig. 2 E). Two weeks after modeling, serum FSH and LH levels in the model group were significantly higher than in the control group ( P  < 0.05), whereas serum E2 and AMH levels were significantly lower than in controls ( P  < 0.05). After 2 weeks of treatment with Yijing Decoction, the serum FSH and LH levels in the rats were lower than those in the model group (P  0.05), whereas serum FSH remained significantly different from control levels ( P  < 0.05). Additionally, serum E2 was significantly higher than in the model group ( P   0.05); similarly, serum AMH was significantly increased relative to the model group ( P   0.05) ( Fig. 3 A). Fig. 3 Serum hormone levels and follicle counts (A) Serum basal FSH, LH, E2, and AMH levels in rats of each group. (n = 10). (B) Microscopy images of typical ovarian tissues from the control, model and Yijing decoction treatment groups; HE staining. Red arrows indicate follicles of various stages; scale bar:1 mm. (C) Number and proportion of ovarian follicles at each stage. (n = 10). All values are expressed as mean ± SD. ∗ P  < 0.05, ns P  ≥ 0.05. Fig. 3 Serum hormone levels and follicle counts (A) Serum basal FSH, LH, E2, and AMH levels in rats of each group. (n = 10). (B) Microscopy images of typical ovarian tissues from the control, model and Yijing decoction treatment groups; HE staining. Red arrows indicate follicles of various stages; scale bar:1 mm. (C) Number and proportion of ovarian follicles at each stage. (n = 10). All values are expressed as mean ± SD. ∗ P  < 0.05, ns P  ≥ 0.05. Overall ovarian volume was reduced in the model group; follicle numbers at all developmental stages were markedly decreased, and the ovarian stroma appeared dense. Representative H&E-stained ovarian tissue sections from each group are shown in Fig. 3 B. Per-ovary follicle counts indicated that numbers of primordial follicles, sinus follicles (including primary, secondary and preantral follicles), and mature follicles were significantly lower in the model group than in controls ( P  < 0.05). The model group exhibited a marked increase in atretic follicles ( P   0.05). No significant differences were observed among groups in the numbers of cystic follicles or corpora lutea ( P  > 0.05). The proportion of follicles across all stages was significantly lower in the model group than in controls ( P  < 0.05). In particular, the proportion of sinusoidal follicles (primary, secondary and preantral follicles) was significantly reduced in the model group compared with both the control and Yijing Decoction groups ( P  < 0.05 vs both). Furthermore, proportions of atretic and cystic follicles were significantly increased in the model group compared with controls ( P   0.05). Finally, there were no significant differences in the proportions of follicles at any stage between the Yijing Decoction treatment group and the control group ( P  > 0.05) ( Fig. 3 C). Apoptotic cells were primarily granulosa cells within the follicles, whereas almost no apoptotic cells were observed in the ovaries of the control group ( Fig. 4 A and B). Quantification using ImageJ indicated that the number of apoptotic cells in follicles was significantly higher in the model group ( P  < 0.05) and significantly lower in the Yijing Decoction group compared with the model group ( P  < 0.05); however, there was no significant difference between the control and treatment groups ( P  < 0.05). Fig. 4 Ovarian regressed cell and embryo count (A) Representative image of normal TUNEL staining; scale bar: 250 μm in the upper figure. The lower figure is the magnified image corresponding to the red "□" in the upper figure; the brown color represents apoptotic cells (as indicated by the red arrow); scale bar: 50 μm (n = 3). (B) Representative TUNEL fluorescence image; green fluorescence indicates apoptotic cells (red arrow), and blue fluorescence indicates DAPI; scale bar: 250 μm. The right panel shows fluorescence intensity relative to area (%) (n = 3). (C) Anatomical images of the uterus and ovaries of each group on day 8 of gestation and statistical analysis of embryo counts (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05, ns P  ≥ 0.05. Fig. 4 Ovarian regressed cell and embryo count (A) Representative image of normal TUNEL staining; scale bar: 250 μm in the upper figure. The lower figure is the magnified image corresponding to the red "□" in the upper figure; the brown color represents apoptotic cells (as indicated by the red arrow); scale bar: 50 μm (n = 3). (B) Representative TUNEL fluorescence image; green fluorescence indicates apoptotic cells (red arrow), and blue fluorescence indicates DAPI; scale bar: 250 μm. The right panel shows fluorescence intensity relative to area (%) (n = 3). (C) Anatomical images of the uterus and ovaries of each group on day 8 of gestation and statistical analysis of embryo counts (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05, ns P  ≥ 0.05. Embryo implantation was clearly observable on day 8 of gestation. Bilateral uteri in the control group contained closely spaced, bead-like embryos without obvious gaps. Embryos in the model group were sparsely distributed or present in only one uterus. In the Yijing Decoction group, embryos were more spaced apart, but the number of embryos was significantly higher than in the model group. Statistical analysis revealed that embryo numbers were significantly lower in the model group than in the control group ( P  < 0.05) or the Yijing Decoction group ( P   0.05) ( Fig. 4 C). The Yijing Decoction consisted of 11 Chinese herbal medicines, such as Shudihuang, Baizhu, Shanyao, Danggui, Baishao, Suanzaoren, Nanshashen, Mudanpi, Dangshen, Chaihu, Duzhong. The compositions of the 11 herbs were retrieved from the TCMSP database by entering the herb names in the search box. A total of 111 active ingredients with OB ≥ 30 % and DL ≥ 0.18 were obtained according to the screening criteria (see Appendix 1 , Table 2 ). The ingredients with the highest number of targets included MOL000098 (quercetin), MOL000546 (diosgeninogen), MOL000422 (kaempferol), MOL000006 (lignocerotoxin), and MOL000449 (stigmasterol). Subsequently, a total of 257 targets corresponding to the above active ingredients were identified from the TCMSP database (see Appendix 2 , Table 3 ), mainly including Progesterone receptor, Mineralocorticoid receptor, Nuclear receptor coactivator 2, Alcohol dehydrogenase 1C, Ig gamma-1 chain C region, Retinoic acid receptor RXR-alpha, Alpha-2A adrenergic receptor, Beta-2 adrenergic receptor. In addition, 4474 targets associated with POI were identified using the GeneCards database. After filtering for a relevance score >5, 1735 POI targets were ultimately obtained. The relevance scores, from highest to lowest, were BRCA2, BRCA1, TP53, STAG3, FMR1, POF1B, FOXL2, CHEK2, TTN, BMP15, etc. (see Appendix 3 , Table 4 for the top 100 targets in terms of relevance). By integrating targets of active ingredients with disease-related targets, 146 targets were identified for the treatment of POI by Yijing Decoction ( Fig. 5 A). The 146 therapeutic targets corresponded to 72 active ingredients and 11 herbal components in Yijing and Tang and were used to construct the target network of herbal ingredients ( Fig. 5 B). In the network, blue circles represent targets, and yellow hexagons represent active ingredients. Ingredients with the highest number of targets included MOL000098 (quercetin), MOL000546 (diosgeninogen), MOL000422 (kaempferol), MOL000006 (lignocerotoxin), and MOL000449 (stigmasterol), suggesting that these active ingredients may have a significant therapeutic effect on POI. The network also demonstrated complex relationships between components and their corresponding therapeutic targets, providing a basis for the molecular mechanisms of Yijing Decoction in treating POI. Fig. 5 “Drug-Disease” network diagram (A) Venn diagram of drug active ingredient targets and disease-related targets, showing the 146 overlapping genes between Yijing Decoction and POI. (B) “rb-ingredient-target” network, blue circles represent targets, and the yellow hexagons represent active ingredients. Fig. 5 “Drug-Disease” network diagram (A) Venn diagram of drug active ingredient targets and disease-related targets, showing the 146 overlapping genes between Yijing Decoction and POI. (B) “rb-ingredient-target” network, blue circles represent targets, and the yellow hexagons represent active ingredients. GO analysis of the 146 therapeutic targets revealed enrichment across the Biological Process, Molecular Function, and Cellular Component categories. Enriched biological processes included response to antibiotics, reactive oxygen metabolism, cellular response to oxidative stress, response to reactive oxygen species, response to oxidative stress, response to lipopolysaccharide, and cellular response to chemical stress. For Molecular Function and Cellular Component categories, enriched terms included serine/threonine protein kinase complex, cell-cycle protein-dependent kinase holoenzyme complex, membrane components, cytokine receptor binding, and scaffold-protein binding ( Fig. 6 A). KEGG pathway enrichment analysis ( Fig. 6 B) revealed multiple signaling pathways potentially implicated in the therapeutic effects against POI. The therapeutic targets associated with the top 5 KEGG pathways, such as the AGE-RAGE signaling pathway, in diabetic complications, hepatitis B, prostate cancer, lipids and atherosclerosis, and fluid shear stress and atherosclerosis, are shown in Fig. 6 C–G. Genes highlighted in red within these pathway maps denote the identified therapeutic targets. Fig. 6 Functional enrichment analysis of therapeutic targets (A) GO enrichment analysis histogram. The horizontal axis indicates the number of enriched genes; the vertical axis lists GO terms. Darker red indicates greater statistical significance (lower P value). (B) KEGG pathway enrichment analysis. The x-axis indicates the proportion of genes; the y-axis lists pathway names. (C–G) Visualization of the KEGG pathways associated with the top 5 therapeutic targets. Fig. 6 Functional enrichment analysis of therapeutic targets (A) GO enrichment analysis histogram. The horizontal axis indicates the number of enriched genes; the vertical axis lists GO terms. Darker red indicates greater statistical significance (lower P value). (B) KEGG pathway enrichment analysis. The x-axis indicates the proportion of genes; the y-axis lists pathway names. (C–G) Visualization of the KEGG pathways associated with the top 5 therapeutic targets. A total of 146 potential therapeutic targets associated with POI were identified using the STRING database. Consequently, a PPI network comprising 146 nodes and 605 edges was constructed and visualized using Cytoscape ( Fig. 7 A). The MCC algorithm (via the cytoHubba plugin) identified the top 10 hub genes by degree: CDK4, cyclin-dependent kinase inhibitor 1A (CDKN1A), E2F1, cyclin-dependent kinase 2 (CDK2), PCNA, CDK1, CCNB1, cyclin A2 (CCNA2), RB1, and CCND1. Interactions among these top 10 hub genes are shown in Fig. 7 B. Fig. 7 Protein‒protein interaction network component target docking analysis (A) PPI network containing 146 nodes and 605 edges. (B) The top 10 most highly associated genes in the PPI network (CDK1, CDK2, CNKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1); the darker the red color, the higher the association. (C) Three-dimensional view of AKT1 docked to lignin and two-dimensional view with hydrogen bonds and residues labeled in the two-dimensional view. (D) Three-dimensional view of CDK1 docked to kaempferol in two dimensions with hydrogen bonds and residues labeled in the two-dimensional view. (E) Two-dimensional view of CDK1 docked to quercetin in Three-dimensional with hydrogen bonds and residues labeled in the Two-dimensional view. (F) Two-dimensional view of ESR docked to glycine with hydrogen bonds and residues labeled in the Two-dimensional plot. Fig. 7 Protein‒protein interaction network component target docking analysis (A) PPI network containing 146 nodes and 605 edges. (B) The top 10 most highly associated genes in the PPI network (CDK1, CDK2, CNKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1); the darker the red color, the higher the association. (C) Three-dimensional view of AKT1 docked to lignin and two-dimensional view with hydrogen bonds and residues labeled in the two-dimensional view. (D) Three-dimensional view of CDK1 docked to kaempferol in two dimensions with hydrogen bonds and residues labeled in the two-dimensional view. (E) Two-dimensional view of CDK1 docked to quercetin in Three-dimensional with hydrogen bonds and residues labeled in the Two-dimensional view. (F) Two-dimensional view of ESR docked to glycine with hydrogen bonds and residues labeled in the Two-dimensional plot. After reviewing the literature and the PPI network, cyclin-dependent kinase 1 (CDK1), AKT serine/threonine kinase 1 (AKT1), and estrogen receptor 1 (ESR1) were selected for molecular docking. Crystal structures with PDB IDs 4Y72 , IUNQ , and 1XP6 were downloaded from the Protein Data Bank (PDB). Corresponding active ingredients for these three targets were retrieved from the herbal component–target network. Docking results indicated that CDK1 exhibited strong predicted binding affinity, with binding energies of −9.8 kcal/mol for quercetin and −7.4 kcal/mmol for both CDK1 and kaempferol. Additionally, glycidin showed favorable binding to the ESR1 structure (PDB ID 1XP6 ). Furthermore, AKT1 displayed a predicted binding energy of −6.3 kcal/mol for representative lignans, indicating modest affinity for the target protein ( Fig. 7 C–F). Quercetin, kaempferol, lignans, and glycidine may act on CDK1, AKT1 and ESR1 to modulate pathways relevant to POI progression. Three samples were randomly selected from each group for qPCR analysis performed in triplicate, results are shown in Fig. 8 A. CDK1 expression was significantly reduced in the model group relative to controls ( P  < 0.05), and was increased in the Yijing Decoction group compared with the model group ( P  < 0.05), Yijing Decoction group lower than control levels ( P   0.05). CDKN1A was upregulated in the model group compared with the control group ( P  < 0.05) and in the Yijing Decoction treatment group compared with the model group ( P  < 0.05). E2F1 was downregulated in the model group compared with the control group ( P  < 0.05) and upregulated in the Yijing Decoction treatment group compared with the model group ( P  < 0.05). CDK4 was significantly downregulated in the model group compared with controls ( P   0.05). PCNA was reduced in the model group versus controls ( P  < 0.05), increased in the Yijing Decoction group relative to the model group ( P   0.05). No significant difference in RB1 expression was observed among the groups ( P  > 0.05). CCNA2 expression was reduced in the model group relative to controls ( P  < 0.05). No significant difference was detected for CCNA2 expression between the model and Yijing Decoction groups ( P  < 0.05). CCNA2 was significantly downregulated in the model group ( P   0.05). CCND1 was downregulated in the model group versus controls ( P  < 0.05) and was increased in the Yijing Decoction group compared with the model group ( P  < 0.05); although CCND1 approached control levels, it remained significantly different from controls ( P  < 0.05). Fig. 8 Expression of CDK1, CDK2, CDKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1 genes (A) Relative fold amplification of CDK1, CDK2, CDKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1. Data are expressed as mean ± SD of fold change (2^–ΔΔCt) (n = 3). (B) WB bar graphs and quantitative gray-value statistics for PCNA and E2F1 protein expression levels. (n = 3). (C) Bar graph and quantitative gray-value statistics of CCND1, CDK1 and CDK4 protein expression levels (n = 3). All values are expressed as mean ± SD. ∗ p  < 0.05; ns, P  ≥ 0.05). Fig. 8 Expression of CDK1, CDK2, CDKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1 genes (A) Relative fold amplification of CDK1, CDK2, CDKN1A, E2F1, CDK4, PCNA, RB1, CCNA2, CCND1, and CCNB1. Data are expressed as mean ± SD of fold change (2^–ΔΔCt) (n = 3). (B) WB bar graphs and quantitative gray-value statistics for PCNA and E2F1 protein expression levels. (n = 3). (C) Bar graph and quantitative gray-value statistics of CCND1, CDK1 and CDK4 protein expression levels (n = 3). All values are expressed as mean ± SD. ∗ p  < 0.05; ns, P  ≥ 0.05). PCNA immunoblot bands were markedly reduced in intensity in the model group compared with the control and Yijing Decoction groups, and E2F1 expression in the Yijing Decoction group appeared variable ( Fig. 8 B). Band intensities were quantified as gray values using ImageJ software. Quantification indicated that PCNA expression was significantly lower in the model group than in controls ( P  < 0.05) and significantly higher in the Yijing Decoction group compared with the model group ( P   0.05). CCND1, CDK1, and CDK4 expression were significantly reduced in the model group compared with controls ( P  < 0.05). Following Yijing Decoction treatment, levels of CCND1, CDK1, and CDK4 increased relative to the model group ( P  < 0.05), and these differences among groups were statistically significant ( Fig. 8 C). PCNA protein was expressed predominantly in follicular granulosa cells. The percentage of PCNA-positive cells was significantly lower in the POI group than in the control group ( P  < 0.05) and in the Yijing Decoction group ( P   0.05) ( Fig. 9 A). CCND1 was expressed mainly in a few cells of the ovarian luteum. The proportion of CCND1-positive cells in the POI group was significantly lower than in the control group ( P  < 0.05) and in the Yijing Decoction group ( P  < 0.05); however, CCND1 levels in the Yijing Decoction group remained significantly lower than those in the control group ( P  < 0.05) ( Fig. 9 B). Fig. 9 Immunohistochemical staining of PCNA and CCND1 (A) Representative images of PCNA-immunostained ovarian sections from each group. Upper panel scale bar: 250 μm; lower panel is the magnified region indicated by the red box (□). Brown staining indicates PCNA-positive cells (red arrows). The adjacent graph depicts the proportion of positive area per group (x-axis: group; y-axis: proportion of positive area) (n = 3). (B) CCND1 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 25 μm (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05; ns, P  ≥ 0.05. Fig. 9 Immunohistochemical staining of PCNA and CCND1 (A) Representative images of PCNA-immunostained ovarian sections from each group. Upper panel scale bar: 250 μm; lower panel is the magnified region indicated by the red box (□). Brown staining indicates PCNA-positive cells (red arrows). The adjacent graph depicts the proportion of positive area per group (x-axis: group; y-axis: proportion of positive area) (n = 3). (B) CCND1 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 25 μm (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05; ns, P  ≥ 0.05. CDK1 expression was predominantly localized to granulosa cells within follicles. The proportion of CDK1-positive cells was significantly lower in the POI group compared with both the control group and the Yijing Decoction group (P  0.05) ( Fig. 10 A). CDK4 protein was expressed mainly in follicular granulosa cells and in ovarian mesenchymal stromal cells. No significant difference in the percentage of CDK4-positive cells was observed among the groups ( P  > 0.05) ( Fig. 10 B). CD34 is a vascular endothelial cell-specific factor that is expressed mainly in vascular endothelial cells. The results showed that the percentage of positive cells in ovarian tissue was significantly lower in the POI group than in both the control group and the Yijing Decoction treatment group (P < 0.05), and also lower in the Yijing Decoction group than in the control group ( P  < 0.05) ( Fig. 10 C). Fig. 10 Immunohistochemical staining of CDK1, CDK4, and CD34 (A) Representative images of CDK1-immunostained ovarian sections from each group. Upper panel scale bar: 100 μm; lower panel is the magnified region indicated by the red box (□). Brown staining indicates CDK1-positive cells (red arrows). The adjacent graph shows the proportion of positive area per group (x-axis: group; y-axis: proportion of positive area) (n = 3). (B) CDK4 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 50 μm (n = 3). (C) CD34 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 50 μm (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05; ns, P  ≥ 0.05. Fig. 10 Immunohistochemical staining of CDK1, CDK4, and CD34 (A) Representative images of CDK1-immunostained ovarian sections from each group. Upper panel scale bar: 100 μm; lower panel is the magnified region indicated by the red box (□). Brown staining indicates CDK1-positive cells (red arrows). The adjacent graph shows the proportion of positive area per group (x-axis: group; y-axis: proportion of positive area) (n = 3). (B) CDK4 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 50 μm (n = 3). (C) CD34 immunostaining; upper panel scale bar: 250 μm; lower panel scale bar: 50 μm (n = 3). All values are expressed as mean ± SD. ∗ P  < 0.05; ns, P  ≥ 0.05.

Both CTX and BUS are alkylating agents known for their high ovotoxicity. They can alkylate cellular DNA, potentially inhibiting primordial follicle proliferation [ 13 ], causing direct follicle depletion and oocyte loss, ultimately leading to ovarian dysfunction or premature ovarian failure (POF). Patients with cancer treated with alkylating agents have the highest risk of POI, and using a CTX combined with BUS-induced POI model better replicates the effects of alkylator-induced POI [ 14 ]. Therefore, a chemotherapy-induced POI rat model was established using CTX and BUS. In this study, a rat model of POI was induced using CTX combined with BUS and subsequently treated with Yijing Decoction (TCM) to evaluate its efficacy in managing POI. Network pharmacological analysis was used to construct a “main active ingredient-core target-critical pathway” network for Yijing Decoction in POI and to explore potential mechanisms. Reverse transcription quantitative polymerase chain reaction (RT‒qPCR), Western blotting, and immunohistochemistry were used to validate the predictions from network pharmacology. We then constructed a network linking the main active ingredients, core targets, and key pathways involved in POI treatment, and explored the possible underlying mechanisms. The validation results using RT‒qPCR, western blotting (WB), and immunohistochemistry (IHC) are presented, and the overall study workflow is shown in Fig. 1 . Fig. 1 Flow chart of the study. Fig. 1 Flow chart of the study. One hundred female SD (Sprague–Dawley) rats (8 weeks old, 190–220 g) of specific-pathogen-free (SPF) status and 5 male SD rats (8 weeks old, 290–240 g) of SPF status were purchased from Guangdong Viton Lever Experimental Technology Co., Ltd. (License No. SCXK (GD) 2022-0063). The rats were housed in the animal facility of the Clinical Laboratory Center, Guizhou Medical University Hospital. Rats were housed in separate cages (temperature 20 ± 4 °C; 12 h light/12 h dark cycle; relative humidity 60–70 %) and acclimated for 1 week without experimental manipulation. All experimental procedures were approved by the Animal Ethics Committee of Guizhou Medical University Hospital (Approval No.: 2101344). Cyclophosphamide (CTX; Baxter, Shanghai, China) and leucovorin (BUS; purity ≥98 %; Solarbio Beijing, China), were provided by Guiyang Chaoyan Bioengineering Co. The TCM Yijing Decoction (formula: Shudihuang 30 g, Baizhu 30 g, Shanyao 15 g, Danggui 15 g, Baishao 15 g, Suanzaoren 9 g, Nanshashen 9 g, Mudanpi Pi 6 g, Dangshen 6 g, Chaihu 6 g, Duzhong 3 g) [ 15 ] was purchased from the Chinese Pharmacy of the Affiliated Hospital of Guizhou Medical University and supplied as a concentrated granule. Reagents included methylene blue staining solution (Solarbio, Beijing, China); an ELISA kit for luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol (E2), and anti-Müllerian hormone (AMH) (Jingmei, Jiangsu, China); an H&E staining kit (Solarbio, Beijing, China); a TUNEL apoptosis detection kit (KeyGEN, Jiangsu, China); a one-step TUNEL assay kit (FITC; Elabscience, Hubei, China); an RNA wash kit (Solarbio, Beijing, China); an RNA extraction kit (Omega Bio-Tek, USA); a reverse-transcription kit (Thermo Fisher Scientific, USA); Universal Blue qPCR mix (YEASEN, Dalian, China); radioimmunoprecipitation assay (RIPA) lysis buffer (Solarbio, Beijing, China); protease inhibitor (Thermo Fisher Scientific, Waltham, MA, USA); β-actin antibody (Proteintech, Hubei, China); PCNA antibody (Cell Signaling, Shanghai, China); CCND1 antibody (Abcam, Cambridge, UK); CDK1 antibody (Proteintech, Hubei, China); CDK4 antibody (Proteintech, Hubei, China); cyclin B1 (CCNB1) antibody (Zenbio, Chengdu, China); E2F1 antibody (Proteintech, Hubei, China); CD34 antibody (Abcam, Cambridge, UK); and Super ECL luminescent solution (YEASEN, Dalian, China). Instrumentation was provided by the Clinical Research Center of Guizhou Medical University Hospital. Ninety SD rats with regular estrous cycles (at least two consecutive cycles within 2 weeks) [ 16 ] and weighing 190–220 g were screened and randomly assigned to a control group (n = 25) and a model group (n = 65). In the model group, CTX was dissolved in 0.9 % saline at a dosage of 83.52 mg/kg; BUS was dissolved in dimethyl sulfoxide (DMSO) at 20.88 mg/kg; both drugs were administered concurrently by a single intraperitoneal injection [ 17 ]. In the control group, an equivalent volume of saline was administered intraperitoneally. After 2 weeks of modeling, 10 rats were randomly selected from each group and euthanized to evaluate model establishment. After confirming successful model establishment, 20 rats were randomly selected from the model group as the treatment cohort and received oral gavage. The standard human clinical dose of Yijing Decoction is 131 g of raw herbs per day, and the equivalent dose for animals was calculated using the body surface area conversion method described in the “Methodology of Traditional Chinese Medicine Pharmacological Research”. The resulting doses for SD rats were 11.79 g raw drug/kg for the mid-dose and 23.58 g raw drug/kg for the high dose. This study focused on the mid-dose (11.79 g/kg), as previous work indicated that this dose is most appropriate and suitable for clinical translation [ 18 ]. Yijing Decoction (11.79 g/kg raw drug) was administered daily by oral gavage for 21 days. The remaining 20 rats in the model group (after 15 died within 1 week of modeling) received equal volumes of saline by gavage over the same period. At the end of treatment, 5 rats from each group were randomly selected and housed with sexually mature male rats at a ratio of 3:1 for mating. The rats were observed daily for mental state, activity, fur luster and denseness, responsiveness to external stimuli, food intake, feces and urine, and the presence of any abnormal secretions. After 1 week of acclimatization, the estrous cycle of the SD rats was evaluated using microscopic examination of vaginal smears obtained daily between 18:00 and 19:00. A small cotton swab dipped in saline was inserted approximately 5 mm into the vagina of each rat, rotated clockwise 1–2 turns, and the collected material was smeared evenly onto a slide and air-dried. After 15–20 min, slides were stained with an appropriate volume of methylene blue solution using a pipette, excess stain was gently rinsed away with tap water, slides were air-dried, and then examined under a microscope (Leica, Germany) [ 18 ]. The normal estrous cycle of the rat consists of four consecutive phases: proestrus, estrus, metestrus, and diestrus. The criteria for determining the estrous phase according to the swab method proposed by Chen et al. [ 19 ] were as follows: proestrus (predominantly nucleated epithelial cells with few keratinized cells); estrus (abundant keratinized epithelial cells with few nucleated epithelial cells); metestrus (late estrus) (keratinized epithelial cells with leukocytes); and diestrus (interestrus) (numerous leukocytes with a small amount of mucus). Rats with at least two consecutive estrous cycles within a 2-week period were included in the study. Rat body weights were measured and recorded daily between 18:00 and 19:00, both before and after caging. Rats were euthanized under ether anesthesia. Bilateral ovaries were excised intact, adhering fascia and adipose tissue were removed, and the wet weight of the bilateral ovaries was measured on an electronic balance. The ovarian index was calculated as: ovarian index = (wet weight of bilateral ovaries [g]) ÷ (body weight prior to euthanasia [g]) [ 20 ]. At baseline (before modeling), weekly after modeling, and weekly after Yijing Decoction treatment, rats in the intermotility period were selected, and anesthesia was induced by rapid ether inhalation for 30 s. Then, 0.5–1.0 ml of blood was collected via retro-orbital sampling and centrifuged at 4500 r/min for 15 min to 2 h; serum was separated and stored at −80 °C until analysis. Serum levels of FSH, LH, E2 and AMH in rat serum were measured using double-antibody sandwich ELISA. ELISAs were performed according to the manufacturers’ instructions. After 2 weeks of modeling, ovarian follicle morphology was examined to confirm successful model establishment. Ten rats were randomly selected from each of the control and model groups and euthanized under ether anesthesia. Collected ovaries were fixed in 4 % paraformaldehyde for 24 h, dehydrated through a fractionated ethanol series, vitrified in xylene, and embedded in paraffin. Paraffin blocks containing whole ovaries were serially sectioned at 5 μm, every fourth section was mounted on slides [ 21 ], and slides were stained with H&E. Follicle morphology and counts were assessed using light microscopy, including primordial, primary, secondary, antral (sinus), mature, atretic and cystic follicles, as well as corpora lutea. The proportion of each follicle type per ovary was subsequently calculated. After 3 weeks of treatment, the same method was used to assess the therapeutic efficacy of Yijing Decoction. Paraffin blocks were sectioned at 5 μm; ovarian tissues from all groups were processed and stained using the TUNEL method, with apoptotic nuclei visualized as dark brown signals in the colorimetric assay. Colorimetric TUNEL-stained sections were examined and imaged using light microscopy. Preparation of fluorescent sections was performed under light-protected conditions, and a one-step TUNEL apoptosis detection kit was used to detect nuclear DNA fragmentation during apoptosis in ovarian tissue. Nuclei were counterstained with 4′,6-diamidino-2-phenylindole dihydrochloride (DAPI) according to the manufacturer's instructions. Apoptotic cells were detected as green fluorescence; sections were imaged using a fluorescence microscope and images were processed and quantified using ImageJ software. Five female rats were randomly selected from each of the control, model and Yijing Decoction treatment groups and mated with adult male rats at a ratio of 3:1. Vaginal secretions were collected on the morning after mating for microscopic examination; the presence of spermatozoa or a copulatory plug in the smear was designated as gestational day 1. After confirmation of mating, male rats were returned to separate cages. On gestational day 8, pregnant females were euthanized under ether anesthesia [ 22 ]; uteri and ovaries were removed intact, surrounding fascia and adipose tissue were trimmed, and the number of embryos was recorded. The Traditional Chinese Medicine Systematic Pharmacology Database (TCMSP) ( http://tcmspw.com/tcmsp.php ) is a curated pharmacology database detailing herbal constituents, their corresponding targets, and associated diseases [ 23 ]. In this study, active ingredients of Yijing Decoction were identified from TCMSP database using the screening criteria of oral bioavailability (OB) ≥30 % and drug likeness (DL) ≥0.18. Corresponding targets for the identified active ingredients were predicted using TCMSP. The GeneCards database integrates genomics, proteomics and transcriptomics data and provides gene-centric annotations [ 24 ]. The keyword “premature ovarian insufficiency” was queried in GeneCards ( https://www.genecards.org/ ) to retrieve disease-associated genes; entries with a relevance score >5 were retained as candidate POI targets. POI-related targets of Yijing Decoction were identified by overlapping the predicted active-ingredient targets with the disease-associated targets. Herbal component–target networks were constructed using Cytoscape v3.7.2 to illustrate the associations between active components and potential therapeutic targets. In the network representation, nodes represent active components and therapeutic targets, and edges represent interactions between components and targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of these therapeutic targets were performed using the clusterProfiler R package. GO annotations were used to classify targets into Biological Process (BP), Molecular Function (MF), and Cellular Component (CC) categories, while KEGG enrichment analysis was performed to identify associated biological pathways. Terms with P  ≤ 0.05 were considered statistically significant. Therapeutic targets were entered into the Search Tool for Retrieval Interacting Genes (STRING) database ( http://string-db.org/ ) to generate PPI networks using a confidence score threshold of ≥0.9; resulting networks were visualized using Cytoscape v3.7.2. The top 10 hub genes in the PPI network were identified using the maximal clique centrality (MCC) algorithm implemented in the cytoHubba plugin in Cytoscape. Target protein crystal structures were downloaded from the Protein Data Bank (PDB) and imported into PyMOL for preparation, including removal of crystallographic water molecules. Structures were then imported into AutoDock Tools to add polar hydrogens and compute partial charges. Ligand MOL2 files for active ingredients were obtained from TCMSP and imported into AutoDock Tools to verify protonation state, charge assignment and rotatable bond definitions. Docking grids were defined around the receptor active site, and AutoDock Vina was used to perform receptor–ligand docking; the conformation with the lowest predicted binding free energy (highest affinity) was selected. Finally, PyMol and LigPlot were used to visualize docking conformations and protein–ligand interactions. Left ovarian tissues were collected at each experimental time point, rinsed with saline, placed in RNase-free tubes containing RNA preservation solution, stored at 4 °C overnight (≈24 h), and then transferred to −80 °C until analysis using RT‒qPCR and WB. Total RNA was isolated using a commercial RNA extraction kit according to the manufacturer's instructions. RNA concentration and purity were assessed (e.g., by spectrophotometry), and 1 μg of total RNA was reverse-transcribed to cDNA using the supplied reverse-transcription kit per the manufacturer's protocol. Resulting cDNA was quantified using real-time PCR using Universal Blue qPCR SYBR Mix on a real-time PCR instrument. The reaction conditions were as follows: 40 cycles at 95 °C for 2 min; 95 °C for 10 s; and 60 °C for 30 s. Gene expression was quantified using threshold cycle (Ct) values, and β-actin was used as the endogenous control. Relative gene expression levels were calculated using the 2^−ΔΔCt method. RT‒qPCR analysis was performed for selected hub genes identified from the network pharmacology PPI analysis [ 25 ]. Primer sequences are listed in Table 1 . Table 1 Primer sequences. Table 1 Name Forward primer Reverse primer β-actin CCCATCTATGAGGGTTACGC TTTAATGTCACGCACGATTTC CDK1 GGAACAGAGAGGGTCCGTTG GAGATTTCCCGGATTGCCGT CDK2 AGCTCTGCTTGCGTTCCAT ACGTGCCCTCTCCAATCTTC CDKN1A TGTGATATGTACCAGCCACAGG AAAGTTCCACCGTTCTCGGG E2F1 GATCCTGACGTGCTGCTCTT TTCACACCTTTCCCTGGGTG CDK4 CGAGCGTAAGGCTGATGGAT CGCTTAGAAACTGGCGCATC PCNA TGGCTCCCAAGATCGAAGATG AAGACCTCAGAACACG RB1 TTGCATGGCTTTCTGATTCACC AGGCTGAGAGAACAAGCAGAC CCNA2 GATGGTAGTTTTGAATCACCCCA TGGCCCGCATACTGTTAGTG CCND1 GATGCTAGAGGTCTGCGAG AGACAAGAAACGGTCCAGG Primer sequences. Proteins corresponding to genes whose expression was significantly restored by Yijing Decoction, as determined using RT-qPCR, were selected for WB analysis. Total protein was extracted using prechilled RIPA lysis buffer supplemented with protease inhibitors. Protein samples were separated using polyacrylamide gel electrophoresis and transferred to polyvinylidene difluoride membranes using a transfer apparatus (semidry or wet transfer). Membranes were blocked, incubated with primary antibodies against β-actin, PCNA, CCND1, CDK1, CDK4, CCNB1, or E2F1 overnight at 4 °C, incubated with appropriate horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature, and visualized using Super ECL luminescent substrate. Relative band intensities were quantified by densitometry using β-actin as the loading control, with image analysis performed in ImageJ (NIH, Bethesda, MD, USA). Immunohistochemical staining was performed to assess ovarian expression of PCNA, CCND1, CDK1 and CDK4 in the control, POI and Yijing Decoction treatment groups. IHC was also used to evaluate CD34 expression for assessment of microvessel density in ovarian tissue. Ovarian tissue sections were prepared and subjected to heat-induced antigen retrieval in ethylenediaminetetraacetic acid buffer (microwave: high power 5 min, then medium–low power 15 min). Sections were then treated with 3 % hydrogen peroxide for 10 min to block endogenous peroxidase activity and incubated in 10 % normal goat serum at 37 °C for 1 h to block nonspecific binding. After blocking, sections were incubated overnight at 4 °C with primary antibodies against PCNA, CCND1, CDK1, CDK4, or CD34. The following day, sections were equilibrated at 37 °C for 30 min, washed in PBS, and incubated with HRP-conjugated secondary antibodies at 37 °C for 1 h. Sections were washed, developed with 3,3′-diaminobenzidine, counterstained with hematoxylin (2 min), dehydrated through graded ethanol, cleared in xylene, mounted with coverslips, and imaged using light microscopy [ 26 ]. Finally, staining intensity and positive-cell counts were quantified using ImageJ software. Data were analyzed using SPSS v27.0 and GraphPad Prism 8 for P -value calculation and figure generation. One-way analysis of variance (ANOVA) was used to compare groups, with Bartlett's test assessing homogeneity of variances. When this assumption was violated, Welch's ANOVA was applied as a correction. Densitometric quantification of western-blot band intensities and measurement of fluorescence signal intensities were performed using ImageJ. Figure assembly and group panels were prepared using Adobe Photoshop 2024. Experimental data are presented as mean ± standard deviation (SD). A two-tailed P  < 0.05 was considered statistically significant (∗ P  < 0.05).

Based on rat model experiments and network pharmacology analysis, this study preliminarily suggests that Yijing Decoction may exert its effects primarily by upregulating CDK1, PCNA, and CCND1, thereby influencing the downstream expression of CDK4, E2F1, and CD34. This mechanism may reduce granulosa cell death and promote angiogenesis, thereby delaying chemotherapy-induced ovarian dysfunction. These findings provide a theoretical basis for clinical application and for further research. The following section presents an in-depth discussion of this study. POI is characterized by the premature depletion of ovarian function and affects a substantial proportion of women [ 27 ]. POI is a refractory condition defined by cessation of ovarian function before 40 years of age, severely compromising women's reproductive health and quality of life. Chemotherapy, commonly used to treat malignant tumors, can cause ovarian failure and impair fertility in young women. Indeed, 42 % of female patients with cancer treated with alkylating agents subsequently develop POI [ 28 ]. Although several novel treatments for POI remain experimental, hormone replacement therapy (HRT), including estrogens, progesterone, and androgens, remains the standard treatment because it substantially relieves symptoms of estrogen deficiency (e.g., hot flashes and insomnia) and improves patients' quality of life [ 6 ]. However, HRT may adversely affect lipid profiles and blood pressure and could negatively influence longer-term health outcomes. Replacement therapy may have potential adverse effects on lipids and hemostatic factors, thereby increasing the risk of cardiovascular events such as venous thromboembolism and coronary heart disease [ 29 ]. In addition, HRT is contraindicated in women with hormone-dependent tumors because it may increase the risk of breast cancer and exacerbate endometriosis [ 30 ]. Moreover, HRT does not restore intrinsic ovarian reproductive function, and POI remains a significant problem for patients seeking fertility preservation. Therefore, developing non-HRT interventions for patients with POI is particularly important. The description of “breakage of menstrual flow before old age” in Fu Qingzhu's Woman Section closely corresponds to the clinical manifestations of POI. An analysis of the diagnostic concepts and prescribing principles in Fu Qingzhu's Gynecology suggests that he primarily attributed the occurrence of POI to kidney deficiency, with secondary involvement of the heart, liver, and spleen. Consequently, he advocated for diagnosis and treatment based on the condition of these four organs, with kidney tonification as the core principle. He also developed the therapeutic approach of ‘softening the liver and relieving depression,’ while emphasizing spleen strengthening and calming the heart. He promoted kidney tonification as the cornerstone of therapy and pioneered the approach of ‘softening the liver and relieving depression.’ Emphasizing the importance of strengthening the spleen and calming the heart, he treated the heart, liver, spleen, and kidneys as an integrated meridian system, applying strategies of tonification, regulation, and dispersion as clinically appropriate. His self-formulated Yijing Decoction thus provided a novel conceptual framework for the prevention and treatment of POI, influencing subsequent generations of practitioners [ 31 ]. Compared with similar TCM formulas (such as Zishen Yutai Wan), Yijing Decoction comprehensively targets the heart, liver, spleen, and kidneys, and places greater emphasis on a balanced approach of both tonification and drainage to restore physiological function. In addition to modulating hormonal balance, Yijing Decoction exerts effects described in TCM as “soothing the liver” and “relieving depression,” and it is reported to calm the mind and promote sleep. The “balanced tonification and drainage” formulation strategy offers potential advantages for preventing further decline in ovarian function [ 32 , 33 ]. Under normal physiological conditions, most primordial follicles remain dormant to prevent premature depletion of the follicular pool. During each menstrual cycle, a small group of primordial follicles is activated and begins to grow and develop. However, chemotherapy disrupts hormonal secretion and leads to excessive follicular maturation, increased follicular atresia, and reduced ovarian reserve. E2 (17β-estradiol) is the predominant intracellular estrogen and is synthesized and secreted in large quantities by follicles before menopause [ 34 ]. Abnormal apoptosis of oocytes and granulosa cells is the main cause of follicular atresia, leading to premature ovarian aging [ 9 ]. The present study showed that chemotherapeutic agents significantly reduced primordial follicles, primary follicles and secondary follicles and increased atretic follicles and cystic follicles, accompanied by structural destruction of the follicular granulosa cell layer. POI rats presented significantly lower levels of E2 and AMH, higher levels of FSH and LH, and increased granulosa cell regression. Contemporary medical treatments for infertility include pharmacotherapy, surgery, and assisted reproductive technologies; however, these approaches have limitations such as adverse effects, high cost, and variable success rates. Chinese medicine has a long history of treating infertility and is widely used in clinical practice [ 35 ]. Yijing Decoction treatment slowed the progression of premature ovarian failure and increased the number of fertilized embryos per litter, indicating improved ovulation and pregnancy rates. The results also showed that treatment with Yijing Decoction increased the total number of follicles at the same developmental stage in POI rats, reduced serum FSH and LH levels, and normalized estrous cycle irregularities. These parameters are standard metrics for evaluating improvements in ovarian reproductive function [ 36 ]. The significant increase in AMH observed after Yijing Decoction treatment, in some cases exceeding control values may be attributable to factors such as animal age and baseline AMH levels, which influence AMH recovery during the late stage after chemotherapy [ 37 ]. Network pharmacology analyses have suggested that Yijing Decoction may exert ovarian-protective effects in POI via active ingredients such as ginsenosides, baicalin, and quercetin [ 13 ]. Separately, a study investigating Zishen Yutai pills identified quercetin and kaempferol as principal active ingredients potentially relevant to the treatment of premature ovarian failure/POI [ 4 ]. However, these results lack sufficient experimental validation. Our network prediction identified quercetin, kaempferol, lignocerol, and glycine were identified as the principal bioactive components of the Yijing Decoction. Molecular docking predicted strong binding interactions between CDK1 and quercetin/kaempferol, ESR1 and glycine, and AKT1 and lignocerol. Therefore, CDK1, AKT1, and ESR1 are proposed as potential therapeutic targets for POI. GO and KEGG enrichment analyses identified several relevant biological functions and pathways. In particular, Yijing Decoction–associated targets were enriched for molecular functions and cellular components including the serine/threonine protein kinase complex, cell-cycle protein-dependent kinase holoenzyme complex, membrane regions, cytokine receptor binding, and scaffold-protein binding. However, network pharmacology has inherent limitations. For example, database annotations may lag behind current research advances. Consequently, expanded in vivo experimentation is essential to validate these predictions [ 38 ]. RT‒qPCR experiments were performed to validate genes that showed high association within the PPI network. The results showed that CDK1, E2F1, CDK4, PCNA, and CCND1 were downregulated in the model group relative to controls and were upregulated following gavage treatment with Yijing Decoction compared with the model group. Further WB and immunohistochemical experiments showed that CDK1, CDK4, PCNA, and CCND1 were expressed at the protein level, consistent with the results of RT–qPCR experiments, and that E2F1 expression was unstable. In the immunohistochemistry experiment section, vascular endothelial cell-specific expression of the antibody CD34 were also evaluated. CDKs are central regulators of the cell cycle and drive progression through its distinct phases. CDK1 can substitute for other CDKs and is sufficient to drive the mammalian cell cycle [ 39 ]. CDK1 has also been implicated in the regulation of M-phase protein synthesis [ 40 , 41 ]. CDK1 functions as a general activator of translation outside mitosis, enabling protein synthesis to adapt directly to the rate of cell proliferation [ 42 ]. The results of this study suggest that Yijing Decoction increases CDK1 expression at both the gene and protein levels. CTX and BUS have been suggested to cause loss of ovarian reserve by triggering activation of quiescent primordial follicles, an event that occurs concomitantly with granulosa cell apoptosis [ 43 ]. PCNA is a marker of cell proliferation and was used to detect granulosa cell proliferation in ovarian tissues from the control, POI, and Yijing Decoction treatment groups. A TUNEL assay was used to detect apoptosis of ovarian granulosa cells. The results indicated that Yijing Decoction increased granulosa cell proliferation and reduced granulosa cell apoptosis. The CCND1 gene encodes cyclin D1, a protein that promotes cell cycle progression by activating CDK4 to drive the G1-S transition. It may also activate estrogen receptors, thereby promoting angiogenesis [ 44 , 45 ]. The present study indicates that Yijing Decoction increases CCND1 expression at both the mRNA and protein levels. E2F1 is a multifunctional transcription factor involved in the G1-to-S phase transition of the cell cycle. Many chromatin-modifying enzymes are recruited to DNA damage sites to promote repair and to gene promoters to regulate transcription. An important regulator of E2F1 is the RB oncogene, which directly binds a subset of E2F1 and other E2F family members. Interaction with RB converts these E2F family members from transcriptional activators to transcriptional repressors. E2F transcriptional activity is tightly regulated by RB during the cell cycle and in nonproliferating cells [ 46 ]. CDK4, a member of the CDK family, functions as a principal upstream activator of E2F1 during cell-cycle progression [ 47 ]. The results showed that E2F1 mRNA was upregulated following Yijing Decoction treatment, but E2F1 protein levels remained unstable. This discrepancy is likely attributable to the complex regulatory interactions among E2F1, RB, CDK4, and associated regulatory factors. CD34 is a widely used cell surface marker for the detection and isolation of stem and progenitor cells with strong regenerative potential, and in endothelial cells, CD34 has been used to recognize endothelial tip cell sprouting during neovascularization in vitro [ 48 , 49 ]. In the present study, CD34 immunostaining was used to detect neovascularization in ovarian tissue. Based on the validation experiments, we hypothesize that Yijing Decoction may increase the expression of the CDK1, PCNA, and CCND1 genes, which in turn regulate downstream genes such as CDK4, E2F1, and CD34. This effect may occur by reducing ovarian granulosa cell death, promoting angiogenesis, and activating the estrogen receptor, thereby slowing the decline in ovarian function. Discrepancies exist between network pharmacology predictions and empirical results: active ingredients identified through computational methods may not align with the main quality-control markers or the most abundant components in current Chinese herbal medicine standards. As a result, some conclusions drawn from bioinformatics analyses may be unreliable. These observations underscore the importance of rigorous experimental validation of computational predictions. In addition, this study has several limitations. The CTX + BUS model uses a single high-dose intraperitoneal administration, which places considerable demands on laboratory personnel, and increases the risk of animal mortality if handling is suboptimal. Consequently, this modeling approach is limited because it reflects only chemotherapy-induced ovarian dysfunction. The conclusions of this study are applicable solely to chemotherapy-induced POI. Whether these findings generalize to ovarian dysfunction caused by other factors (e.g., surgery, aging, or immune-mediated mechanisms) or to non-specific ovarian dysfunction requires additional experimental investigation and validation. The experimental groups included in the analysis had small sample sizes; therefore, increasing and balancing group sizes is necessary to improve the reliability and reproducibility of the results. Furthermore, although targets with high network centrality in the PPI analysis were validated, expression of ESR1 and AKT1 was not assessed at the mRNA or protein levels. The principal active constituents of Yijing Decoction were not isolated for targeted mechanistic studies. Future studies will further investigate the molecular mechanisms underlying these effects, with the aim of improving understanding of the relationship between Yijing Decoction and ovarian function.

Yijing Decoction may primarily act on the CDK1–PCNA–CCND1 axis to increase expression, which in turn modulates downstream targets (CDK4, E2F1, and CD34), potentially by reducing granulosa cell apoptosis and promoting angiogenesis, thereby delaying chemotherapy-induced decline in ovarian function. These findings may provide a theoretical basis for the clinical application of Yijing Decoction in the treatment of chemotherapy-induced premature ovarian insufficiency.

Premature ovarian insufficiency (POI) is characterized by amenorrhea for at least 4 months before the age of 40 years accompanied by elevated FSH levels >25 mIU/ml on two occasions at least 4 weeks apart [ 1 ]. POI is associated with perimenopausal-like symptoms that can be physically and psychologically devastating for affected women. The prevalence of POI is typically less than 1 %, although racial and demographic factors may influence prevalence (China: 0.5 %; Japan: 0.1 %) [ 2 ]. A recent meta-analysis reported a global prevalence of POI at 3.5 %, with a higher prevalence in developing countries (5.3 %) compared to developed countries (3.1 %) [ 3 ]. The prevalence of POI has increased significantly over the past few decades [ 4 ]. With the rising incidence of cancer among young women, chemotherapy-induced gonadal toxicity has become a major cause of POI. Notably, POI prevalence continues to rise annually and increases with advancing age [ 5 , 6 ], posing a serious risk to women's reproductive health. Diminished ovarian reserve and poor oocyte quality are primary contributors to reduced pregnancy rates among patients with POI [ 7 ]. There is currently no definitive method to restore reproductive function in patients with POI, despite many of them having a strong desire for pregnancy. Therefore, there is an urgent need for new and effective strategies to improve fertility outcomes in women with POI. The Consensus Conference on the Guidelines for Integrating Chinese and Western Medicine in the Treatment of POI recommends using the term “symptoms before and after menstrual interruption” as the traditional Chinese medicine (TCM) equivalent for POI [ 8 ]. TCM, a time-honored system that has evolved through thousands of years of clinical practice, offers numerous candidate herbs and formulations for the treatment of POI [ 9 ]. As early as the Qing Dynasty, Fu Shan recorded in Fu Qingzhu's Gynecology ( Fu Qing Zhu Nv Ke – Tiao Jing ) that Yijing Decoction was prescribed for ‘symptoms of premature menstrual bleeding’ [ 10 ]. The formula includes Codonopsis to replenish vital energy, with an emphasis on generating body fluids, nourishing the blood, and tonifying the center. Treatment of POI with Yijing Decoction is associated with lower toxicity and fewer side effects than conventional medications for improving reproductive function, and it demonstrates more precise therapeutic effects. However, the complexity of components in Yijing Decoction (e.g., small organic molecules, macromolecules, inorganic ions) makes systematic study difficult, and the active components, targets, and pathways mediating its therapeutic effects remain unclear. Compared with western medicines that have well-defined compositions, it is currently difficult to conduct systematic, comprehensive studies of traditional formulas across holistic, cellular, and molecular levels; this limitation has hindered further development and clinical application. Therefore, exploring the underlying mechanisms is crucial. Network pharmacology is a multidisciplinary field that integrates computational and experimental methods to synthesize large datasets and generate new discoveries. It is grounded in systems biology, biological network analysis, and multi-target drug design aimed at selecting specific signaling nodes [ 11 ]. As an emerging discipline combining pharmacology and computer science, network pharmacology has the potential to elucidate the complex mechanisms of “multicomponent, multitarget, multisignaling” pathways in herbal compounds [ 12 ]. In the present study, the potential mechanism of action of Yijing Decoction in the treatment of POI was investigated using network pharmacology and experimental studies.

The authors declare no conflicts of interest.The authors declare that there are no known competing financial interests or personal relationships that may influence the work reported here.