Unique metabolomics characteristics for distinguishing cirrhosis related to different liver diseases: A systematic review and meta-analysis.

BACKGROUND AND AIM: Clinical evidence for early identification and diagnosis of liver cirrhosis (LC) caused by different types of liver disease is limited. We investigated this topic through a meta-analysis of quantitative metabolomics. METHODS: Four databases were searched until October 31, 2022 for studies comparing metabolite levels between patients with different types of liver disease and control individuals. A random-effects model was applied for the meta-analysis. RESULTS: This study included 55 studies with 8266 clinical participants, covering 348 metabolites. In LC related to drug-induced liver injury (DILI), hepatitis B virus (HBV) infection, and non-alcoholic fatty liver disease (NAFLD), the primary bile acid biosynthesis (taurocholic acid: SMD, 1.08[0.81, 1.35]; P < 0.00001; glycocholic acid: SMD, 1.35[1.07, 1.62]; P < 0.00001; taurochenodeoxycholic acid: SMD, 1.36[0.94, 1.78]; P < 0.00001; glycochenodeoxycholic acid: SMD, 1.49[0.93, 2.06]; P < 0.00001), proline and arginine (l-proline: SMD, 1.06[0.53, 1.58]; P < 0.0001; hydroxyproline: SMD, 0.81[0.30, 1.33]; P = 0.002), and fatty acid biosynthesis (palmitic acid: SMD, 0.44[0.21, 0.67]; P = 0.0002; oleic acid: SMD, 0.46[0.19, 0.73]; P = 0.0008; stearic acid: SMD, 0.37[0.07, 0.68]; P = 0.02) metabolic pathways were significantly altered. CONCLUSION: We identified key biomarkers and metabolic characteristics for distinguishing and identifying LC related to different types of liver disease, providing a new perspective for early diagnosis, disease monitoring, and precise treatment.

Chemical composition analysis of Qingyan dropping pills using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry.

RATIONALE: This study developed a method for the rapid classification and identification of the chemical composition of Qingyan dropping pills (QDP) to provide the theoretical basis and data foundation for further in-depth research on the pharmacological substance basis of the formula and the selection of quality control indexes. METHODS: Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) and data postprocessing technology were used to analyze the chemical composition of QDP. The fragmentation information on possible characteristic fragments and related neutral losses was summarized based on the literature and was compared with the MS data obtained from the assay, and thus a rapid classification and identification of chemical components in QDP could be achieved. RESULTS: A total of 73 compounds were identified, namely 24 flavonoids, 14 terpenoids, 30 organic acids and their esters, 3 alkaloids, and 2 phenylpropanoids. CONCLUSIONS: In this study, UHPLC-Q-TOF-MS and data postprocessing technology were used to realize the rapid classification and identification of the chemical constituents of QDP, which provided a comprehensive, efficient, and fast qualitative analysis method, a basis for further quality control and safe medication of QDP.

Enhanced optical imaging and fluorescent labeling for visualizing drug molecules within living organisms.

The visualization of drugs in living systems has become key techniques in modern therapeutics. Recent advancements in optical imaging technologies and molecular design strategies have revolutionized drug visualization. At the subcellular level, super-resolution microscopy has allowed exploration of the molecular landscape within individual cells and the cellular response to drugs. Moving beyond subcellular imaging, researchers have integrated multiple modes, like optical near-infrared II imaging, to study the complex spatiotemporal interactions between drugs and their surroundings. By combining these visualization approaches, researchers gain supplementary information on physiological parameters, metabolic activity, and tissue composition, leading to a comprehensive understanding of drug behavior. This review focuses on cutting-edge technologies in drug visualization, particularly fluorescence imaging, and the main types of fluorescent molecules used. Additionally, we discuss current challenges and prospects in targeted drug research, emphasizing the importance of multidisciplinary cooperation in advancing drug visualization. With the integration of advanced imaging technology and molecular design, drug visualization has the potential to redefine our understanding of pharmacology, enabling the analysis of drug micro-dynamics in subcellular environments from new perspectives and deepening pharmacological research to the levels of the cell and organelles.

Adipose-derived stem cell exosomes loaded with icariin attenuated M1 polarization of macrophages via inhibiting the TLR4/Myd88/NF-κB signaling pathway.

Abnormal macrophage polarization is one of the common pathological bases of various inflammatory diseases. The current research focus involves targeting macrophages to remodel their phenotype as a treatment approach for inflammatory diseases. Notably, exosomes can be delivered to specific types of cells or tissues or inflammatory area to realize targeted drug delivery. Although icariin (ICA) exhibits regulatory potential in macrophage polarization, the practical application of ICA is impeded by its water insolubility, poor permeability, and low bioavailability. Exploiting the inherent advantages of exosomes as natural drug carriers, we introduce a novel drug delivery system-adipose-derived stem cells-exosomes (ADSCs-EXO)-ICA. High-performance liquid chromatography analysis confirmed a loading rate of 92.7 ± 0.01 % for ADSCs-EXO-ICA, indicating the successful incorporation of ICA. As demonstrated by cell counting kit-8 assays, ADSCs-EXO exerted a significantly higher promotion effect on macrophage proliferation. The subsequent experimental results revealed the superior anti-inflammatory effect of ADSCs-EXO-ICA compared to individual treatments with EXO or ICA in the lipopolysaccharide + interferon-gamma-induced M1 inflammation model. Additionally, results from enzyme-linked immunosorbent assay, quantitative polymerase chain reaction, and western blot analyses revealed that ADSCs-EXO-ICA effectively inhibited macrophage polarization toward the M1-type and concurrently promoted polarization toward the M2-type. The underlying mechanism involved the modulation of macrophage polarization through inhibition of the Toll-like receptor 4/myeloid differentiation factor 88/nuclear transcription factor-kappa B signaling pathway, thereby mitigating inflammation. These findings underscore the potential therapeutic value of ADSCs-EXO-ICA as a novel intervention for inflammatory diseases.

Pomegranate polyphenol punicalagin as a nutraceutical for mitigating mild cognitive impairment: An overview of beneficial properties.

Dementia treatment has become a global research priority, driven by the increase in the aging population. Punicalagin, the primary polyphenol found in pomegranate fruit, exhibits a variety of benefits. Today, a growing body of research is showing that punicalagin is a nutraceutical for the prevention of mild cognitive impairment (MCI). However, a comprehensive review is still lacking. The aim of this paper is to provide a comprehensive review of the physicochemical properties, origin and pharmacokinetics of punicalagin, while emphasizing the significance and mechanisms of its potential role in the prevention and treatment of MCI. Preclinical and clinical studies have demonstrated that Punicalagin possesses the potential to effectively target and enhance the treatment of MCI. Potential mechanisms by which punicalagin alleviates MCI include antioxidative damage, anti-neuroinflammation, promotion of neurogenesis, and modulation of neurotransmitter interactions. Overall, punicalagin is safer and shows potential as a therapeutic compound for the prevention and treatment of MCI, although more rigorous randomized controlled trials involving large populations are required.

Construction of a physiologically based pharmacokinetic model of paclobutrazol and exposure estimation in the human body.

Paclobutrazol (PBZ) is a plant growth regulator that can delay plant growth and improve plant resistance and yield. Although it has been widely used in the growth of medicinal plants, human beings may take it by taking traditional Chinese medicine. There are no published studies on PBZ exposure in humans or standardized limits for PBZ in medicinal plants. We measured the solubility, oil-water partition coefficient (logP), and pharmacokinetics of PBZ in rats and established a physiologically based pharmacokinetic (PBPK) model of PBZ in rats. This was followed by extrapolation to healthy Chinese adult males as a theoretical foundation for future risk assessment of PBZ. The results showed that PBZ had low solubility and high fat solubility. Pharmacokinetic experiments showed that PBZ was absorbed rapidly but eliminated slowly in rats. On this basis, the rat PBPK model was successfully constructed and extrapolated to healthy Chinese adult males to predict the plasma concentration-time curve and exposure of PBZ in humans. The construction of the PBPK model of PBZ in this study facilitates the determination of the standard formulation limits and risk assessment of PBZ residues in medicinal plants.

Enhancing patient comfort in varicose vein treatment through combined lidocaine and ropivacaine tumescent anesthesia.

Objective: To compare the analgesic effects of specific tumescent anesthetic solutions composed of lidocaine, ropivacaine, or a combination of lidocaine and ropivacaine during endovenous radiofrequency ablation for the treatment of great saphenous vein varicosities. Method: This study included 149 patients with lower limb varicose veins who were admitted to our department between 2019 and 2023. The patients were randomly assigned to three groups: the lidocaine group (Group I), the ropivacaine group (Group II), and the lidocaine + ropivacaine group (Group III). Intraoperative vital signs, intraoperative and postoperative visual analog scale (VAS) pain scores, and long-term treatment outcomes were assessed using the venous clinical severity score (VCSS) based on clinical performance. Results: There were no significant differences in age, body mass index, operative time, or blood loss among the three groups (P ≥ 0.05). The differences in the mean arterial pressure and heart rate during surgery in Group II were significantly greater than those in Groups I and III (P < 0.05). The intraoperative VAS scores in Group II were higher than those in Groups I and III (P < 0.05) and at 8 and 12 h postoperatively. There were no significant differences in VCSS among the groups (P ≥ 0.05). Conclusion: The use of a tumescent anesthetic solution composed of lidocaine and ropivacaine significantly improved patient comfort during the perioperative period without affecting surgical outcomes. This formulation can be considered safe and reliable for preparing tumescent anesthesia solutions.

Development and application of the physiologically-based toxicokinetic (PBTK) model for ochratoxin A (OTA) in rats and humans.

Ochratoxin A (OTA) is a common fungal toxin frequently detected in food and human plasma samples. Currently, the physiologically based toxicokinetic (PBTK) model plays an active role in dose translation and can improve and enhance the risk assessment of toxins. In this study, the PBTK model of OTA in rats and humans was established based on knowledge of OTA-specific absorption, distribution, metabolism, and excretion (ADME) in order to better explain the disposition of OTA in humans and the discrepancies with other species. The models were calibrated and optimized using the available kinetic and toxicokinetic (TK) data, and independent test datasets were used for model evaluation. Subsequently, sensitivity analyses and population simulations were performed to characterize the extent to which variations in physiological and specific chemical parameters affected the model output. Finally, the constructed models were used for dose extrapolation of OTA, including the rat-to-human dose adjustment factor (DAF) and the human exposure conversion factor (ECF). The results showed that the unbound fraction (Fup) of OTA in plasma of rat and human was 0.02-0.04% and 0.13-4.21%, respectively. In vitro experiments, the maximum enzyme velocity (Vmax) and Michaelis-Menten constant (Km) of OTA in rat and human liver microsomes were 3.86 and 78.17 µg/g min-1, 0.46 and 4.108 µg/mL, respectively. The predicted results of the model were in good agreement with the observed data, and the models in rats and humans were verified. The PBTK model derived a DAF of 0.1081 between rats and humans, whereas the ECF was 2.03. The established PBTK model can be used to estimate short- or long-term OTA exposure levels in rats and humans, with the capacity for dose translation of OTA to provide the underlying data for risk assessment of OTA.

Rapid identification and determination of chemical components of huai yam based on UPLC-Q-Exactive-MS and fragmentation patterns.

Huai Yam (Dioscoreae Rhizoma) contains many active ingredients such as flavonoids, saponins, and amino acids. In this study, an efficient method for the classification and rapid identification of yam components was established based on UPLC-Q-Exactive-MS and data post-processing techniques. First, the mass spectrometry information including the characteristic fragmentations (CFs) and neutral losses (NLs) of yam reported in the literature were summarised and a database of compounds was established. Then, the mass spectrometry data detected by the yam sample are compared with those described in database for rapid identification of target compounds. Finally, 60 compounds were identified, including 18 flavones, 2 saponins, 10 amino acids, 7 organic acids, 3 carbohydrates, 8 fatty acids and 12 others. A new strategy for identifying target constituents based on CFs and NLs was successfully established, laying the foundation for further research on yam and promoting the development of composition analysis of Traditional Chinese Medicine (TCM).

Spatial Shifts of Reflected Light Beam on Hexagonal Boron Nitride/Alpha-Molybdenum Trioxide Structure.

This investigation focuses on the Goos-Hänchen (GH) and Imbert-Fedorov (IF) shifts on the surface of the uniaxial hyperbolic material hexagonal boron nitride (hBN) based on the biaxial hyperbolic material alpha-molybdenum (α-MoO3) trioxide structure, where the anisotropic axis of hBN is rotated by an angle with respect to the incident plane. The surface with the highest degree of anisotropy among the two crystals is selected in order to analyze and calculate the GH- and IF-shifts of the system, and obtain the complex beam-shift spectra. The addition of α-MoO3 substrate significantly amplified the GH shift on the system's surface, as compared to silica substrate. With the p-polarization light incident, the GH shift can reach 381.76λ0 at about 759.82 cm-1, with the s-polarization light incident, the GH shift can reach 288.84λ0 at about 906.88 cm-1, and with the c-polarization light incident, the IF shift can reach 3.76λ0 at about 751.94 cm-1. The adjustment of the IF shift, both positive and negative, as well as its asymmetric nature, can be achieved by manipulating the left and right circular polarization light and torsion angle. The aforementioned intriguing phenomena offer novel insights for the advancement of sensor technology and optical encoder design.

Studies of Mycotoxins in Medicinal Plants Conducted Worldwide over the Last Decade: A Systematic Review, Meta-Analysis, and Exposure Risk Assessment.

BACKGROUND: Mycotoxins have been reported to be present in medicinal plants. With the growing usage of medicinal plants, contamination of mycotoxins has emerged as one of the biggest threats to global food hygiene and ecological environment, posing a severe threat to human health. PURPOSE: This study aimed to determine the mycotoxin prevalence and levels in medicinal plants and conduct a risk assessment by conducting a systematic review and meta-analysis. METHODS: A thorough search on Web of Science and PubMed was conducted for the last decade, resulting in 54 studies (meeting the inclusion criteria) with 2829 data items that were included in the meta-analysis. RESULTS: The combined prevalence of mycotoxins in medicinal plants was 1.7% (95% confidence interval, CI = 1.1% - 2.4%), with a mean mycotoxin concentration in medicinal plants of 3.551 µg/kg (95% CI = 3.461 - 3.641 µg/kg). Risk assessment results indicated that aflatoxins and ochratoxin A found in several medicinal plants posed a health risk to humans; additionally, emerging enniatins exhibited possible health risks. CONCLUSION: Therefore, the study underlines the need for establishing stringent control measures to reduce the severity of mycotoxin contamination in medicinal plants.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls.

Early detection of bipolar depression (BPD) and major depressive disorder (MDD) has been challenging due to the lack of reliable and easily measurable biological markers. This study aimed to investigate the accuracy of discriminating patients with mood disorders from healthy controls based on task state skin potential characteristics and their correlation with individual indicators of oxidative stress. A total of 77 patients with BPD, 53 patients with MDD, and 79 healthy controls were recruited. A custom-made device, previously shown to be sufficiently accurate, was used to collect skin potential data during six emotion-inducing tasks involving video, pictorial, or textual stimuli. Blood indicators reflecting individual levels of oxidative stress were collected. A discriminant model based on the support vector machine (SVM) algorithm was constructed for discriminant analysis. MDD and BPD patients were found to have abnormal skin potential characteristics on most tasks. The accuracy of the SVM model built with SP features to discriminate MDD patients from healthy controls was 78% (sensitivity 78%, specificity 82%). The SVM model gave an accuracy of 59% (sensitivity 59%, specificity 79%) in classifying BPD patients, MDD patients, and healthy controls into three groups. Significant correlations were also found between oxidative stress indicators in the blood of patients and certain SP features. Patients with depression and bipolar depression have abnormalities in task-state skin potential that partially reflect the pathological mechanism of the illness, and the abnormalities are potential biological markers of affective disorders.

Rapid classification and identification of chemical components in three different Zanthoxylum species by ultra-high-performance-liquid chromatography quadrupole-orbitrap-mass spectrometry.

Zanthoxylum, as a medicinal and edible herbal medicine, has a long history and complex chemical composition. There are many varieties of Zanthoxylum, and there are differences in composition between varieties. In this study, a rapid classification and identification method for the main components of Zanthoxylum was established using ultra-high-performance-liquid chromatography quadrupole-orbitrap-mass spectrometry. The components of Shandong Zanthoxylum bungeanum, Wudu Zanthoxylum bungeanum, and Zanthoxylum schinifolium were identified by studying the characteristic fragmentations and neutral losses of characteristic components. A total of 48 common components and 24 different components were identified and the fragmentation patterns of the main components, such as flavonoids, alkaloids, and organic acids were summarized. These findings provided a reference for the study of pharmacodynamic substance basis and quality control of different varieties of Zanthoxylum.

Risk factors for dysphagia in patients with acute and chronic ischemic stroke: A retrospective cohort study.

Background: Dysphagia is a common and clinically significant complication of ischemic stroke. The prevalence and risk factors for dysphagia may vary at different stages following an ischemic stroke. Methods: This study included patients with acute and chronic ischemic stroke who were treated at the Department of Rehabilitation, First Affiliated Hospital, Zhejiang University School of Medicine from 2019 to 2022. Various demographic, clinical, and laboratory parameters were collected, and statistical analyses were performed to investigate their association with dysphagia. Results: Among the 399 ischemic stroke patients included in the study, 165 (41.4 %) experienced dysphagia, with 72 (38.7 %) in the acute phase and 93 (43.7 %) in the chronic phase. Univariate analysis revealed significant associations (p < 0.05) between dysphagia and factors such as pulmonary infection, aphasia, NIHSS score, ADL score, NLR score, lower extremity Brunnstrom's stages, and sit-to-stand balance. Multiple logistic regression analysis, after adjusting for confounding factors, identified the ADL score as an independent predictor of dysphagia. These findings were consistent across three time-windows: the acute phase, the chronic phase, and 180 days after stroke onset. Additionally, the lymphocyte count and pulmonary infection were identified as potential independent indicators. Conclusions: This study investigated the prevalence and risk factors for dysphagia in ischemic stroke patients at different time-windows. A low ADL score (<40) may serve as a valuable and reliable predictor for poststroke dysphagia in clinical settings.

Identification and Characterization of the Chemical Constituents of Qianlie Shule Capsules by UPLC-Q-Orbitrap-MS/MS.

BACKGROUND: The Qianlie Shule capsule is a classical Chinese medicine compound preparation frequently used in therapeutic settings to alleviate astringent pain in the urethra, prostatic hypertrophy, and chronic prostatitis or urinary frequency. However, a comprehensive analysis of the chemical composition of Qianlie Shule capsules has not been reported. OBJECTIVE: To establish a quick and effective analytical method based on hybrid quadrupole-orbitrap mass spectrometry ultrahigh-performance liquid chromatography (UPLC-Q-Orbitrap-MS/MS) for the identification and characterization of chemical components in Qianlie Shule capsules. METHOD: Using ultrahigh-performance liquid chromatography with hybrid quadrupole-orbitrap mass spectrometry and data post-processing, the samples of Qianlie Shule capsules were examined. First, the whole extract of the Qianlie Shule capsules was separated using a UPLC machine, and the fragmentation data were collected in both positive and negative ion mode. The target molecule is then quickly identified by comparing the fragmentation information of the neutral loss (NLs) and characteristic fragments (CFs) reported in the literature. RESULTS: A total of 145 chemical components were identified. It includes flavonoids, triterpenoids, phenylpropanoids, organic acids, alkaloids, phenylethanoids, iridoids, and anthraquinones. CONCLUSIONS: This study is a method for the rapid qualitative analysis of the chemical composition of Qianlie Shule capsules, which provides a method for the rapid, sensitive, and high-throughput identification of the prescription components of Chinese medicine. HIGHLIGHTS: Systematic identification of the chemical composition of QLSL capsules provides a theoretical basis for studying the substance basis of QLSL capsules and the improvement of the quality control level.

Rapid classification and identification of chemical compositions of Pu-zhi-hui-ling decoction by UHPLC-Q-Orbitrap HRMS.

Pu-zhi-hui-ling decoction (PZHLD) is a traditional Chinese medicine (TCM) formula for the treatment of Alzheimer's disease (AD), but its chemical composition has not been reported. In this study, we aimed to establish a mass spectrometry (MS) analysis method for rapid classification and identification of the chemical constituents in PZHLD. The sample was analysed by ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). The chemical constituents of PZHLD were identified based on accurate MS data, fragmentation characteristics of MS/MS, and reference information described in the literature. A total of 123 chemical constituents were identified. In addition, we summarised the fragmentation pathways of the chemical constituents in PZHLD. Our finding might lay the foundation for the further pharmacodynamic study and clinical application of PZHLD.

Non-targeted analysis based on quantitative prediction and toxicity assessment for emerging contaminants in tire particle leachates.

Non-targeted analysis (NTA) has great potential to screen emerging contaminants in the environment, and some studies have conducted in-depth investigation on environmental samples. Here, we used a NTA workflow to identify emerging contaminants in used tire particle (TP) leachates, followed by quantitative prediction and toxicity assessment based on hazard scores. Tire particles were obtained from four different types of automobiles, representing the most common tires during daily transportation. With the instrumental analysis of TP leachates, a total of 244 positive and 104 negative molecular features were extracted from the mass data. After filtering by a specialized emerging contaminants list and matching by spectral databases, a total of 51 molecular features were tentatively identified as contaminants, including benzothiazole, hexaethylene glycol, 2-hydroxybenzaldehyde, etc. Given that these contaminants have different mass spectral responses in the mass spectrometry, models for predicting the response of contaminants were constructed based on machine learning algorithms, in this case random forest and artificial neural networks. After five-fold cross-validation, the random forest algorithm model had better prediction performance (MAECV = 0.12, Q2 = 0.90), and thus it was chosen to predict the contaminant concentrations. The prediction results showed that the contaminant at the highest concentration was benzothiazole, with 4,875 µg/L in the winter tire sample. In addition, the joint toxicity assessment of four types of tires was conducted in this study. According to different hazard levels, hazard scores increasing by a factor 10 were developed, and hazard scores of all the contaminants identified in each TP leachate were summed to obtain the total hazard score. All four tires were calculated to have relatively high risks, with winter tires having the highest total hazard score of 40,751. This study extended the application of NTA research and led to the direction of subsequent targeting studies on highly concentrated and toxic contaminants.

Exploring quality evaluation markers of Fructus Psoraleae based on chemometric analysis integrated with network pharmacology.

INTRODUCTION: Fructus Psoraleae (FP) is a well-known traditional Chinese medicine for the treatment of osteoporosis. However, major quality differences were witnessed owing to its various origins, thus influencing its safety and efficacy. OBJECTIVES: The study aimed to evaluate the quality of FP from different origins and predict its quality evaluation markers. METHODS: Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry was employed for tentative characterisation of the constituents in 10 batches of FP, followed by the utilisation of multivariate statistical analysis methods including principal component analysis and orthogonal partial least squares discriminant analysis for quality evaluation. Network pharmacology approaches were utilised to explore the underlying mechanism of the screened chemotaxonomic markers in treating osteoporosis. RESULTS: Forty-one components in FP including, chalcones, coumarins, coumestans, flavonoids, iso-flavonoids, and phenolics, were characterised based on their fragmentation pathways. Ten batches of FP were basically divided into three categories, and eight chemotaxonomic markers including isopsoralen, calamenene, bakuchiol, psoralen, bavachinin, isoneobavaisoflavone, corylifol C, and neobavaisoflavone were screened. Network pharmacology revealed that the chemotaxonomic markers can act on targets such as AKT1, HSP90AA1, and EGFR and possess effects mainly through glycolysis and wnt/ß-catenin signalling to alleviate osteoporosis. Molecular docking and molecular dynamic simulation confirmed the good binding affinity and stability between proteins and selected markers. So, eight chemotaxonomic markers were all preferentially recommended as quality evaluation markers. CONCLUSION: The study not only provides a reference for the improvement of quality control of FP but also offers a theoretical basis for its further in-depth research in osteoporosis.