Parkinson's disease (PD) is a neurodegenerative disorder characterised by neuronal loss in the substantia nigra, α-synuclein accumulation, mitochondrial impairment, oxidative stress, neuroinflammation, and apoptotic cell death. Although various pharmacological treatments, including levodopa and dopamine receptor agonists, can ameliorate PD symptoms, no disease-modifying agents with neuroprotective effects are currently available to prevent progression of neurodegeneration. As a result, there is a growing need for novel disease-modifying agents, particularly for agents with multi-target neuroprotective activity. Lactone derivatives, collectively called phthalides, from various medicinal plants, particularly from compounds of Ligusticum chuanxiong and Angelica sinensis, have been lately identified as promising drugs in this context. In the following review, a comprehensive discussion is given about the etiology of PD, its progression, molecular correlations with the pathogenesis process, latest pharmacological treatments, adverse effects with prolonged administration of drugs, etiology, and relevance of naturally occurring phthalide compounds such as DL-3-n-butylphthalide, ligustilide, senkyunolide H, sedanolide, neocnidilide, among others, with regards to their activity as neuroprotective agents in animal studies of Parkinson's disease. Results from in vitro as well as animal studies highlight their anti-oxidative, anti-inflammatory, anti-ferroptotic, anti-α-synuclein, as well as anti-MAO-B activity, and their roles as multi-target drugs in the context of disease pathogenesis.

Although Angelica sinensis (Oliv.) Diels possesses anti-glioma potential, its active compounds and molecular targets and molecular mechanisms are still not fully understood. This study aims to systematically identify the active components of Angelica sinensis involved in glioma treatment, elucidate its molecular mechanisms, and validate these findings through an integrated approach combining network pharmacology and experimental verification. An integrated methodological approach-incorporating network pharmacology, molecular docking techniques, and in vitro experiments-was adopted in the present research. Using network pharmacology, common targets of Angelica sinensis and stigmasterol in glioma were identified and subjected to GO and KEGG enrichment analysis. To evaluate the molecular interaction, docking simulations were performed between active constituents of Angelica sinensis and the core target proteins. Finally, we performed a battery of cellular assays to validate the effects of Angelica sinensis and stigmasterol on proliferation, clonogenicity, migration, invasion, and ferroptosis in U251-MG cells. Network pharmacology predictions indicated that the p53 signaling pathway is a key pathway mediated by stigmasterol. In vitro experiments confirmed that Angelica sinensis and stigmasterol significantly suppressed malignant phenotypes in U251-MG cells. Mechanistically, stigmasterol activated the p53 pathway, upregulating ACSL4 while downregulating GPX4 and SLC7A11 expression, thereby inducing ferroptosis. This study reveals that stigmasterol, an active component of Angelica sinensis, can inhibit the proliferation of glioma cells by activating the p53 signaling pathway to induce ferroptosis. These findings provide a theoretical basis for the development of novel stigmasterol-based therapeutic strategies against glioma.

Angelica sinensis (Oliv.) Diels (AS) is a medicinal and food plant that has long faced a persistent challenge: its quality and price are often influenced by environmental conditions and geographical origins. To achieve substantial profits, items that are not produced in primary regions, along with counterfeit products, are frequently misbranded as originating from main production areas; this leads to fraud regarding geographic origin and product tampering. Rapid, effective and feasible methods for distinguishing the geographic origin of AS are important for ensuring consumer safety and protecting their interests. This study establishes the authenticity and geographical origins of AS. Meanwhile, diverse machine learning strategies are used to identify the optimal combination by incorporating spectral pre-processing techniques, feature wavenumber selection methods and classification algorithms. The findings reveal that the backpropagation neural network (BPNN), convolutional neural network (CNN) and radial basis function neural network (RBF) excel in determining the authenticity of AS. To distinguish among different growing environments of AS, three models obtained 98.94% classification accuracy on the test set: (1) multiplicative scatter correction (MSC) pre-processing with an RBF classifier, (2) standard normalised variate (SNV) pre-processing with an RBF classifier and (3) Savitzky-Golay (SG) smoothing pre-processing, competitive adaptive reweighted sampling (CARS) for selecting features and a BPNN for classification. This study validates the feasibility of ensemble learning combined with MIR for discriminating AS from authenticity and different geographical sources.

Renal ischemia-reperfusion (I/R) injury, a primary cause of acute kidney injury (AKI), is driven by a self-amplifying loop of oxidative burst and immune cell infiltration. In this work, the classical herb pair Astragalus membranaceus (AM) and Angelica sinensis (AS) is employed as a composite precursor to synthesize nitrogen-rich carbon-dot nanozymes (AM-AS@CDs) via a one-step hydrothermal method. AM‑AS@CDs exhibit superoxide dismutase (SOD)-mimetic activity superior to that of CDs derived from single herbs. In vitro, AM-AS@CDs effectively alleviate oxidative stress-induced cellular damage and significantly inhibit apoptosis. In vivo, AM-AS@CDs markedly attenuate I/R-induced AKI and reduce immune cell infiltration in renal tissues. Transcriptomic analyses reveal that AM-AS@CDs downregulate the expression and phosphorylation of Fosl1 and c-Jun. Consequently, the AP-1-chemokine signaling axis is disrupted, which reduces immune cell recruitment. Furthermore, AM-AS@CDs restore redox homeostasis by upregulating antioxidant enzymes such as SOD, glutathione peroxidase 4 (GPX4), and catalase (CAT). They also attenuate the excessive activation of the Nrf2/HO-1 pathway. Overall, this precursor-formulation strategy enables precise modulation of heteroatom doping and surface chemistry in CDs. AM-AS@CDs effectively interrupt the oxidative-inflammatory positive feedback loop through dual mechanisms. These findings provide both theoretical and material foundations for the development of natural product-based nanozymes for I/R-related diseases.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by joint inflammation and systemic complications. Recent evidence has indicated that disrupted iron metabolism, notably elevated hepcidin expression and excessive iron accumulation in tissues, contributes to RA progression. In RA, Macrophages, which play a central role in both immune regulation and iron homeostasis, are often polarized toward the proinflammatory M1 phenotype. In this study, we investigated the therapeutic effects of Angelica sinensis polysaccharides (ASP, 100-400 mg/kg) in a collagen-induced arthritis (CIA) mouse model. ASP significantly alleviated joint swelling, histopathological damage, and iron deposition in the liver and spleen. It also downregulated hepcidin expression and restored the M1/M2 macrophage balance. Furthermore, immunofluorescence and western blotting confirmed increased ferroportin (FPN) and decreased ferritin levels in splenic macrophages. In an in vitro coculture model mimicking inflammation, ASP indirectly modulated macrophage iron handling and polarization by suppressing hepatocyte-derived hepcidin. RNA-seq analysis revealed that ASP treatment downregulated HIF-1α and NF-κB pathways, which link iron metabolism to macrophage activation, whereas the results of reactive oxygen species (ROS) assays supported its role in reducing oxidative stress associated with iron overload. Together, these findings suggest that ASP alleviates RA symptoms by restoring iron homeostasis and modulating macrophage polarization, primarily by targeting the hepcidin-FPN axis and related inflammatory pathways. ASP therefore holds promise as a low-toxicity, immunomodulatory candidate for RA therapy.

Herbal adulteration has become a common malpractice, often undertaken to increase the weight or perceived potency of medicinal products or to reduce production costs. Consequently, the development of effective methods for detecting and preventing herbal adulteration is of critical importance. Angelica sinensis root is a well-known medicinal and edible plant with diverse pharmacological activities. However, owing to its increasing demand and market price, various adulterants have emerged, among which Angelica pubescens root is one of the most prevalent. The identification of A. sinensis becomes particularly challenging when it is processed into Chinese patent medicine. To address this issue, a novel analytical strategy was proposed. Amplicon sequencing combined with gas chromatography-ion mobility spectrometry was employed for the rapid screening of A. sinensis root adulteration with A. pubescens root in raw materials used for Chinese patent drugs. First, adulteration was confirmed using ITS2 amplicon sequencing. Subsequently, a simple and rapid GC-IMS-based screening method was established. Finally, the developed method was validated using two Chinese patent drugs to assess the presence of A. pubescens adulteration. This integrated strategy provides an effective tool for the rapid screening of commercial products and contributes to combating the adulteration of raw materials used in Chinese patent drugs.

Dang Gui (Radix Angelica sinensis), a classic Chinese medicinal herb, is renowned for nourishing blood, promoting blood circulation, regulating meridians, and relieving pain, and widely used clinically for anemia, cancer, rheumatoid arthritis, ulcerative colitis, and other diseases. Studies have confirmed that Dang Gui and its major bioactive components (e.g., polysaccharides, ferulic acid, (Z)-ligustilide) exert diverse pharmacological activities including immunomodulation, neuroprotection, and hepatoprotection. Based on a systematic literature search, this review summarizes the traditional applications and main chemical constituents of A. sinensis, with a focused analysis of its immunomodulatory effects. Evidence shows that A. sinensis exerts bidirectional immunoregulation by improving immune organ indices, promoting the proliferation and activation of immune cells, including T/B lymphocytes (T/B cells), macrophages, and regulating cytokine secretion. Furthermore, it reviews its immunomodulatory mechanisms in immune-related diseases (e.g., cancer, aplastic anemia, chronic pain), analyzes its quality control standards from regulatory and pharmacopeial perspectives and summarizes relevant safety research. This review comprehensively integrates the immunoregulatory effects and underlying mechanisms of A. sinensis, aiming to provide a scientific basis for its future research and clinical application.

To achieve rapid, nondestructive, and intelligent quality detection of A. sinensis, this study combines NIR-HSI technology with deep learning. It proposes a multi-task convolutional neural network (MT-CNN) equipped with a multi-head hierarchical attention mechanism. First, a multi-task sample partitioning algorithm (MSPXY) was developed with two target variables to improve the representativeness and balance of sample division. Second, a multi-head hierarchical attention mechanism (4HSA + 8HSA) was added to the convolutional neural network to capture both local and global spectral features. Finally, an uncertainty-driven adaptive loss-balancing strategy (UW) was used to achieve dynamic collaborative optimization of multiple tasks. The model that combines these strategies (4HSA + 8HSA + 1DCNN(MSPXY) + UW) achieved the best performance in predicting the moisture and ferulic acid contents of Angelica sinensis. The R[2] values reached 0.9925 and 0.9880, and both RPD values exceeded 9. The model performed much better than traditional PLSR and single-task CNN models. This study demonstrates that the method can effectively and accurately predict both the moisture content and ferulic acid content of Angelica sinensis. It provides a rapid, convenient, and non-destructive testing approach for quality control in industrial production. Furthermore, this method offers an efficient and accurate new approach for quality testing in other food products.

Angelica sinensis (dong quai) is a widely used Traditional Chinese Medicine herb whose constituents are associated with antioxidant and anti-inflammatory activity, making it a plausible candidate for skin-care applications. Here, we evaluated whether an Angelica sinensis extract containing 1% ligustilide exerts antioxidant, anti-senescence, antimicrobial, and anti-inflammatory effects in human skin cell models and explored extracellular matrix-related readouts. Human keratinocytes (HaCaT) and dermal fibroblasts (BJ-5ta) were treated with the extract (10, 30, 50 μg/mL); anti-inflammatory activity was assessed by lipopolysaccharide-induced nuclear factor κB (NF-κB) p65 nuclear translocation, antioxidant effects by reactive oxygen species detection with and without hydrogen peroxide challenge, senescence by senescence-associated β-galactosidase after UVB irradiation, and matrix support by collagen type I alpha 1 (COL1A1) immunofluorescence in fibroblasts; scratch-wound assays evaluated migration, and broth microdilution tested activity against Staphylococcus aureus, Staphylococcus epidermidis, Cutibacterium acnes, and Malassezia globosa. The extract reduced lipopolysaccharide-induced NF-κB nuclear localization in keratinocytes, lowered basal and hydrogen peroxide-induced reactive oxygen species at 3 and 24 h in both cell types, and attenuated ultraviolet B (UVB)-induced senescence in keratinocyte and fibroblast models; in fibroblasts, it increased COL1A1 signal, while migration was unchanged. The extract showed strong inhibition of Staphylococcus species and partial, concentration-dependent inhibition of C. acnes and M. globosa after 24 h, with acceptable viability across the tested range. Overall, these results indicate that A. sinensis extract combines anti-inflammatory and antioxidant activity with reduced UVB-associated senescence, fibroblast matrix-supportive signaling, and antimicrobial effects against skin-relevant microbes, supporting further evaluation in more advanced skin models and finished-product formulations before inferring topical performance.

Backgrounds: Premature ovarian insufficiency (POI) is a clinical syndrome characterized by premature ovarian dysfunction, amenorrhea, and infertility. Ferulic acid (FA) is a prominent bioactive phenolic compound derived from traditional Chinese herbs Angelica sinensis (Oliv.) Diels and Ligusticum chuanxiong Hort. These herbs are commonly used to treat gynecological disorders including menstrual irregularities and infertility, and are known to modulate endoplasmic reticulum (ER) stress. However, the therapeutic potential and molecular mechanisms of FA in the context of POI remain largely unexplored. This study aimed to investigate the protective effects of FA against POI and to elucidate the underlying pharmacological mechanisms. Methods: In vivo, a mouse model of POI was established via a single intraperitoneal injection of cyclophosphamide (CTX; 120 mg/kg), and using FA for 28 days of continuous gavage to observe its therapeutic effect. Ovarian function and pathological changes were assessed by hormone levels, follicle development and oxidative stress (OS) level. In vitro, the effects of FA were examined using 4-hydroperoxy cyclophosphamide (4-OHCP)-treated KGN granulosa cells. Transcriptome sequencing, molecular docking, and molecular dynamics simulations were employed to identify potential targets of FA. Results: Our findings demonstrated that FA administration helped preserve regular estrous cycles, promoted follicle development and hormone secretion, and attenuated OS in both ovarian tissue and granulosa cells (GCs). Transcriptomic profiling combined with molecular docking and molecular dynamics simulations suggested that FA potentially targets key ER stress proteins, specifically Grp78 and Perk. Further in vivo and in vitro experiments confirmed that FA alleviates ER stress by inhibiting the overactivation of the Perk/eIF2α/ATF4/CHOP signaling pathway. Notably, the protective effects of FA were comparable to those of the ER stress inhibitor 4-Phenylbutyric acid (4-PBA) and were reversed by the ER stress activator tunicamycin (TM). Additionally, FA downregulates ERO1α expression, further blocking secondary oxidative damage triggered by ER stress. In KGN cells, FA significantly inhibits 4-OHCP-induced apoptosis and upregulates the anti-apoptotic proteins BCL-2 and BCL-xL, exhibiting efficacy similar to 4-PBA. Conclusions: FA improves ovarian function in CTX-induced POI by coordinately regulating OS and ER stress, inhibiting the Perk/eIF2α/ATF4/CHOP pathway, and suppressing GC apoptosis. These findings provide experimental evidence supporting FA as a potential therapeutic candidate for POI.

Pharmacological preconditioning of mesenchymal stem cells (MSCs) is a promising strategy to enhance their therapeutic efficacy for end-stage liver disease; however, maximizing this benefit remains a major clinical challenge. Senkyunolide H (SNH), a small-molecule compound derived from Angelica sinensis, exhibits anti-inflammatory, antioxidant, and anti-apoptotic properties. Nevertheless, its capacity to optimize MSCs-based therapy for liver disease has not been fully elucidated. Here, we demonstrate that SNH preconditioning significantly enhances the therapeutic efficacy of bone marrow mesenchymal stem cells (BMSCs) in a murine model of liver cirrhosis. Specifically, SNH-pretreated BMSCs markedly alleviated hepatocellular injury, promoted hepatocyte proliferation, and attenuated collagen deposition. Mechanistically, SNH augments the therapeutic potency of BMSCs by partly binding to macrophage erythroblast attacher (MAEA), a subunit of the E3 ubiquitin ligase complex. This interaction stabilizes MAEA, which in turn facilitates the ubiquitination and proteasomal degradation of dual specificity phosphatase 6 (DUSP6), thereby activating ERK/STAT3 signaling and upregulating the secretion of hepatocyte growth factor (HGF). Collectively, our findings highlight SNH preconditioning as a robust approach to enhance the paracrine function and therapeutic potential of BMSCs, and identify MAEA as a novel therapeutic target for BMSCs-based interventions in liver cirrhosis.