Search Results (580)

Mental health disorders, particularly anxiety and insomnia, are increasingly prevalent worldwide, prompting interest in herbal-based complementary therapies. This study surveyed 168 Hungarian healthcare professionals to evaluate their knowledge and recommendations regarding herbal sedatives and analyzed seven commonly suggested OTC products available in Hungary, using thin-layer chromatography (TLC) and UV–Vis spectrophotometry according to the European Pharmacopoeia. The survey revealed that 86.9% of respondents recommend herbal products for nervous system complaints, with Valeriana officinalis and Melissa officinalis being the preferred ingredients. Herbal teas and traditional herbal medicines were the most frequently suggested product categories. Laboratory analysis confirmed the presence of marker compounds in all tested products; however, significant variability in active ingredient concentrations was observed. One homeopathic product contained an unidentified alkaloid-like compound, raising safety concerns. Essential oil yields from tea mixtures also varied markedly, and some products did not meet pharmacopoeial standards for hypericin content. These findings highlight the popularity of phytotherapy among healthcare professionals and the need for stricter quality control of OTC herbal sedatives. Future research should include multi-batch analyses and clinical trials to establish robust evidence for efficacy and safety. Full article

Psychotropic medicinal plants are commonly used among oncology patients, yet their relevance in the perioperative setting remains insufficiently characterized. We conducted a literature-based identification of 18 neuroactive plants and surveyed 123 cancer patients and 109 healthcare professionals at a tertiary hospital in Northern Thuringia, Germany. Seventy-five percent of patients reported using at least one psychotropic plant. Knowledge levels were high and similar across groups (median 11 plants), while professionals reported a broader usage spectrum (p = 0.042). Frequently known and applied species included Valeriana officinalis, Lavandula angustifolia, Hypericum perforatum, and Urtica. Women used more plants than men (p = 0.024), and higher usage rates were observed in breast cancer and head and neck cancer patients. Heat-map analyses showed substantial overlap in knowledge but differences for species such as Atropa, Cannabis, and Papaver somniferum. Given the potential interactions with anesthetic and analgesic medications, structured preoperative assessment of herbal use is warranted to enhance perioperative safety. Full article

Medicinal and aromatic plants contain valuable natural compounds widely used in health, food, and cosmetics. This study compares the antioxidant capacities and phenolic compositions of tea and ethanol extracts from eight species naturally growing in Fethiye, Muğla, Türkiye. Antioxidant activity was assessed using the β-carotene bleaching method, 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS⁺), cupric reducing antioxidant capacity (CUPRAC), and metal chelating activity. Herbal teas generally showed stronger antioxidant activity than ethanol extracts. Rosemary tea had the highest activity (2.90 µg/mL), followed by lavender (11.30 µg/mL). In metal chelating, rosemary tea exhibited a half-maximal inhibitory concentration (IC₅₀) of 9.22 µg/mL, close to ethylenediaminetetraacetic acid (EDTA). Phenolic profiling showed rosemary tea contained 30.74 mg/g rosmarinic acid and 0.74 mg/g quercetin. These results support the traditional use of southwestern Türkiye’s medicinal plants and emphasize the antioxidant potential of herbal teas. Integrating ethnobotanical knowledge with phytochemical data provides a basis for functional food development, crop improvement, and conservation of local plant genetic resources. Unlike previous studies focusing on single species or limited solvent comparisons, this research simultaneously evaluates both herbal tea and ethanol extracts of eight locally grown medicinal plants, offering a unique perspective on their comparative antioxidant and phenolic diversity. Full article

Traditional herbal prescriptions composed of multiple botanicals remain central to ethnopharmacological practice; however, their chemical basis and classification remain poorly understood. Non-volatile compound analyses of herbal medicines are well established, but comparative studies focusing on volatile organic compounds (VOCs) across multi-herbal prescriptions are scarce. To enhance the chemical understanding of traditional formulations and clarify prescription-level characteristics, this study applied headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME–GC–MS) to characterize VOC-based chemical signatures in 30 prescriptions composed of 76 herbal ingredients. Multivariate analyses such as principal component analysis, partial least squares discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA) enabled systematic differentiation of various prescriptions and identified 25 discriminant VOCs, 9 of which were common among multiple therapeutic categories. These shared compounds, such as 5-hydroxymethylfurfural (5-HMF) and 4H-pyran-4-one derivatives, reflect recurrent chemical patterns associated with broad-spectrum applications, whereas category-specific volatiles (including isopsoralen, senkyunolide, and fenipentol) delineated therapeutic boundaries, even among prescriptions with overlapping botanicals. Capturing both shared and distinct volatile signatures clarified ambiguous boundaries between categories such as cold, inflammation, or diabetes versus kidney disorder prescriptions, thereby linking chemical patterns with ethnopharmacological indications. Together, these findings highlight VOC profiling as a valuable diagnostic and interpretive tool that bridges traditional categorization systems with modern chemical analysis, offering a robust framework for future pharmacological and mechanistic investigations. Such an approach not only substantiates traditional categorization but also provides a practical basis for quality control and pharmacological evaluation of multi-herbal formulations. Full article

Geranium wilfordii Maxim. is a traditional medicinal plant rich in ellagitannins such as corilagin (CG) and geraniin (GR), which possess antioxidant and anti-inflammatory properties. However, accurate quantification of CG and GR in complex herbal matrices is hindered by co-eluting impurities and poor UV resolution. Here, we developed and validated a simple isocratic HPLC–UV method for their simultaneous determination in G. wilfordii extract. Separation was achieved on a Polaris 3 C18-A column (250 mm × 4.6 mm, 3 µm) using acetonitrile/0.2% formic acid in water (11:89, v/v) with UV detection at 270 nm. The method showed excellent linearity (25–300 µg/mL, R² > 0.995), precision (RSD < 2.7%), accuracy (recovery 99.5–101.2%), and low detection limits (<3 µg/mL). Previous approaches have relied on gradient HPLC or MS-based techniques, often requiring long run times, costly instrumentation, or additional purification (e.g., HSCCC). In contrast, this study demonstrates a validated isocratic method that enables baseline separation and simultaneous quantification of CG and GR in a single run. This robust and simplified analytical strategy provides a practical tool for routine quality control and phytochemical standardization, with potential applications across pharmaceutical, food, and cosmetic industries. Full article

The study was conducted to determine whether the origin of medicinal plants (conventional vs. organic cultivation) may affect the content of selected bioactive ingredients. This work complements the current state of knowledge on this subject by analysing the content of selected groups of bioactive compounds in four popular herb species (Mentha piperita, Melissa officinalis, Salvia officinalis, Urtica dioica). The aim of the study was to compare the total polyphenol (TPC) and flavonoid (TFC) content, antioxidant activity (AA) and phenolic compound profile in herbal extracts of organic and conventional origin. For all species examined, it was demonstrated that water-ethanol extracts from organically grown herbs contain statistically (p << 0.05) significantly more TPC, TFC and AA than water-ethanol extracts from conventionally grown herbs. Among the analysed extracts, the highest TPC was found in organic M. officinalis (7023.3 mg GAE/100 g d.m.), while the extract of this species from conventional cultivation contained only 3679.4 mg GAE/100 g d.m. TFC in the extracts of organic and conventional M. piperita was 1607.6 and 499.4 mg QE/100 g d.m., respectively. Based on GC-MS analysis, between 15 and 25 phenolic compounds were identified, depending on the species of herbal plant. Almost all the identified compounds were phenolic acids. The studies conducted indicate a statistically significantly higher content of antioxidant compounds in herbs from organic farming compared to conventionally grown herbs, and thus their greater health-promoting potential. Full article

In recent years, herbal medicines (HMs) have been gaining significant attention as alternative or complementary therapeutic options. This is because synthetic drugs are expensive and have side effects, but also because herbal medicines have a rich content of effective bioactive compounds. These natural agents have been widely investigated for their potential in the prevention and management of chronic diseases including cardiovascular disorders, infections, metabolic disorders, neurological disorders, inflammatory disorders digestive diseases, oxidative stress-related diseases, and diabetes mellitus. In this review, we highlight the roles and impacts of various medicinal plants originating from diverse families, showing their bioactive characteristics, and the mechanisms through which they exert antidiabetic effects by regulating insulin secretion, oxidative stress, glucose uptake, and inflammatory pathways. In contrast to previous reviews, our study highlights the role of plants that are less explored, and integrates recent findings as well as future directions and biotechnological applications in plant-based management of diabetes. Full article

Mycotoxins commonly contaminate grains and traditional Chinese medicinal materials, posing serious health risks to humans and animals. To address this issue, a magnetic microporous organic network (MMON) was synthesized via an in situ growth method and Sonogashira–Hagihara coupling for the simultaneous adsorption of seven mycotoxins, followed by UPLC-MS/MS detection. The optimized MMON featured a high surface area, uniform micropores, and rapid magnetic separation within 5 s. Structural and compositional analyses confirmed its tailored architecture, while DFT calculations revealed a pore confinement effect, π–π stacking, and hydrophobic interactions as the primary adsorption mechanisms. A magnetic solid-phase extraction (MSPE) method using 8 mg of MMON achieved adsorption equilibrium within 10 s in 5 mL of a 4 mg/L mycotoxin standard solution. The material maintained over 95% efficiency across ten reuse cycles at a low cost. Under optimal conditions, an MSPE-UPLC-MS/MS method with a low detection limit (0.002–0.15 μg/L), wide linear range (0.01–100.0 μg/L), large enrichment factor (20.1–21.9), low adsorbent dosage, and short extraction time was developed. The determination of mycotoxins in complex grain-based foods and herbal products was also realized with recoveries of 81.32% to 116.10%. This work offers a rapid, cost-effective, and high-throughput approach for mycotoxin detection, supporting quality control in food and herbal product safety. Full article

Background: Cancer patients often use natural health products (NHPs) during chemotherapy without medical supervision. We have previously described the clinical cases of two patients taking capecitabine in combination with folate supplements who suffered from severe diarrhoea and hand-foot syndrome, emphasising that the combination of NHPs with chemotherapeutic agents such as fluoropyrimidines (FPs) can lead to life-threatening events. Although the potential harmful interaction between folate supplements and capecitabine is reported in the summary of product characteristics for this FP, it remains unclear, and evidence regarding interactions with other NHPs is even more limited. Objectives/Methods: This narrative review aimed to provide an update on the literature regarding the effects of combining NHPs and FPs, describing the results of randomised clinical trials and observational studies to provide a critical analysis of the factors influencing the clinical outcomes of cancer patients following this therapeutic approach. Results: Herbal supplements belonging to traditional Chinese medicine and other NHPs, including polyunsaturated fatty acids and probiotics, may reduce the incidence and severity of gastrointestinal, haematological, and skin toxicities related to FPs. In addition to potential safety benefits, NHPs may improve the efficacy of FP-based therapy. Folate supplements appear to improve efficacy outcomes, such as disease-free survival and overall survival, but have also been associated with serious FP-related adverse events. However, the results are mixed, partly because they are influenced by the patient’s genetic background. Conclusions: Overall, the available data are inconclusive and do not support the introduction of natural products as complementary therapy in cancer patients undergoing FP-based chemotherapy, highlighting the need for further investigation. Full article

Accurate species identification is essential for the quality control and standardization of herbal medicines. Agrimonia species, the authentic sources of Agrimoniae Herba, have long been used in traditional medicine, yet limited genomic resources have hindered the establishment of reliable molecular approaches for accurate species discrimination within this genus. Here, we report the newly assembled complete chloroplast genomes (155,156–155,302 bp) of four Agrimonia species, which exhibit the typical quadripartite structure and contain 112 unique genes. Comparative analysis revealed 684 variable sites, including 497 single nucleotide polymorphisms (SNPs) and 187 insertions/deletions (InDels), predominantly located in the single-copy regions. Based on these species-specific variations, we developed nine PCR-based molecular markers that distinguished the four species. The markers were validated using herbarium specimens and commercial herbal products, demonstrating reproducibility and practical applicability. Phylogenetic analysis supported the monophyly of the genus Agrimonia and resolved each species into distinct clusters within the subtribe Agrimoniinae. These results showed that chloroplast genome sequences of the genus Agrimonia can serve as effective super DNA barcodes for species identification. Our study provides fundamental genomic resources for Agrimonia and reliable molecular tools for species authentication, providing a basis for ensuring the authenticity and safety of Agrimoniae Herba. Full article

Background: National Health Insurance Herbal prescriptions (NHPs) are widely used; however, their multi-component composition complicates mechanistic interpretation and impedes the development of evidence-based approaches in traditional medicine and healthcare policy. In this study, we applied a systems biology approach to link molecular mechanisms to clinical effects. Methods: From 56 NHPs, 13 with sufficient clinical evidence were selected. Multi-layer networks connecting herbs, ingredients, genes, and diseases were constructed using SymMap, with interactions filtered for oral bioavailability and statistical significance (false discovery rate < 0.05). Network-predicted diseases were validated against a clinically validated benchmark using permutation-based null model analysis, and gene set enrichment analysis (GSEA) was used to identify key molecular pathways. Results: Networks predicted an average of 1359 diseases per NHP, reflecting their polypharmacology. Importantly, the overall predicted disease sets for 10 of 13 NHPs showed statistically significant overlap with known clinical uses (p < 0.05, several with p < 0.001). GSEA indicated that NHPs commonly modulate three biological axes—hormone–metabolic regulation, neural signaling, and cell proliferation control. Conclusions: NHPs act as potential systemic homeostasis regulators. Our study introduces a computationally validated framework integrating network pharmacology with permutation-based statistical testing, providing a data-driven rationale for NHP use. These computational findings are exploratory and require future biological and clinical validation. Full article

Colorectal cancer cases are on the rise and have become a leading cause of cancer-related deaths. Ginger (Zingiber officinale) is widely used in traditional herbal medicine and has been proposed as a potential treatment for colorectal cancer. This study aimed to explore the network pharmacology and pharmacodynamics of ginger in colorectal cancer treatment. Colorectal cancer patient data from the GEO dataset were analyzed to identify differentially expressed genes (DEGs). Six key components of ginger were selected based on specific criteria, and their target proteins were predicted using the TCMSP database. By overlapping DEGs with predicted targets, 36 candidate drug targets were identified. These targets were analyzed for biological alterations, pathway enrichment, protein–protein interactions, and hub-gene selection, integrating network pharmacology. Molecular docking simulations were conducted to confirm the binding interactions between ginger components and target proteins. The findings showed that GABAergic signaling and apoptosis were the most enriched pathways, suggesting their potential role in colorectal cancer treatment. Docking simulations further revealed that ginger’s active compounds bind to COX2 and ESR1, indicating anti-inflammatory effects and modulation of estrogenic activity. This study provides insight into the systemic mechanisms of ginger in colorectal cancer treatment through an integrated “drug–gene–pathway–disease” network approach. Full article

Brucea javanica (BJ), a key representative of traditional Chinese herbal medicine, is derived from the dried mature fruit of Brucea javanica (L.) Merr., a plant in the Simaroubaceae family. Its pharmacological activity is largely attributed to diverse chemical constituents. To date, approximately 200 distinct chemical constituents have been isolated and identified, mainly comprising quassinoids, triterpenes, alkaloids, steroids, phenylpropanoids, and flavonoids. Contemporary pharmacological studies have demonstrated the significant activities of BJ in various areas, including anti-tumor, anti-inflammatory, and anti-parasitic effects. Notably, its oil form (Brucea javanica oil) has been extensively utilized in treating various cancer types. This review aims to systematically summarize the antitumor components, mechanisms of action, and clinical applications in cancer therapy, with the goal of providing theoretical support for further antitumor research and the development of new BJ-based drugs, highlighting its potential as an antitumor agent. Full article

Background: Accurately detecting the onset of saturated boiling in herbal medicine extraction processes is critical for improving production efficiency and reducing energy consumption. However, the traditional monitoring methods based on temperature suffer from time delays. To address the challenge, acoustic emission (AE) signals were used in this study owing to its sensitivity to bubble behavior. Methods: An AE signal acquisition system was constructed for herbal extraction monitoring. Characteristics of AE signals at different boiling stages were analyzed in pure water systems with and without herbs. The performance of AE-based and temperature-based recognition of boiling stages was compared. To enhance applicability in different herb extraction systems, multivariate statistical analysis was adopted to compress spectral–frequency information into Hotelling’s T² and SPE statistics. For real-time monitoring, a self-adaptive decision-making boiling judgment method (BoilStart) was proposed. To evaluate the robustness, the performance of BoilStart under different conditions was investigated, including extraction system mass and heating medium temperature. Furthermore, BoilStart was applied to a lab-scale extraction process of Dabuyin Wan, which is a practical formulation, to assess its performance in energy conservation and efficiency improvement. Results: AE signal in the 75–100 kHz frequency band could reflect the boiling states of herbal medicine extraction. It was more sensitive to the onset of saturated boiling than the temperature signal. Compared with SPE, Hotelling’s T² was identified as the optimal indicator with higher accuracy. BoilStart could adaptively monitor saturated boiling across diverse herbal systems. The absolute error of BoilStart’s boiling determination ranged from 1.5 min to 2.0 min. The increasing-temperature time was reduced by about 22–36%. For the extraction process of Dabuyin Wan, after adopting BoilStart, the increasing-temperature time was reduced by about 29%, and the corresponding energy consumption was lowered by about 26%. Conclusions: The first AE-based method for precise boiling state detection in herbal extraction was established. BoilStart’s model-free adaptability met industrial demands for multi-herb compatibility. This offered a practical solution to shorten ineffective heating phases and reduce energy consumption. Full article

Quercetin, a key flavonoid in Anoectochilus roxburghii (Wall.) Lindl., plays an important role in determining the pharmacological value of this medicinal herb. However, traditional methods for quercetin quantification are destructive and time-consuming, limiting their application in real-time quality monitoring. This study investigates the hyperspectral response characteristics of quercetin using near-infrared hyperspectral imaging and establishes a feature-based model to explore its detectability in A. roxburghii leaves. We scanned standard quercetin solutions of known concentration under the same imaging conditions as the leaves to produce a dilution series. Feature-selection methods used included the successive projections algorithm (SPA), Pearson correlation, and competitive adaptive reweighted sampling (CARS). A 1D convolutional neural network (1D-CNN) trained on SPA-selected wavelengths yielded the best prediction performance. These key wavelengths—particularly the 923 nm band—showed strong theoretical and statistical relevance to quercetin’s molecular absorption. When applied to plant leaf spectra, the standard-trained model produced continuous predicted quercetin values that effectively distinguished cultivars with varying flavonoid contents. PCA visualization and ROC-based classification confirmed spectral transferability and potential for functional evaluation. This study demonstrates a non-destructive, spatially resolved, and biochemically interpretable strategy for identifying bioactive markers in plant tissues, offering a methodological basis for future hyperspectral inversion studies and intelligent quality assessment in herbal medicine. Full article