Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Ferroptosis, a programmed cell death modality discovered and defined in the last decade, is primarily induced by iron-dependent lipid peroxidation. At present, it has been found that ferroptosis is involved in various physiological functions such as immune regulation, growth and development, aging, and tumor suppression. Especially its role in tumor biology has attracted extensive attention and research. Breast cancer is one of the most common female tumors, characterized by high heterogeneity and complex genetic background. Triple negative breast cancer (TNBC) is a special type of breast cancer, which lacks conventional breast cancer treatment targets and is prone to drug resistance to existing chemotherapy drugs and has a low cure rate after progression and metastasis. There is an urgent need to find new targets or develop new drugs. With the increase of studies on promoting ferroptosis in breast cancer, it has gradually attracted attention as a treatment strategy for breast cancer. Some studies have found that certain compounds and natural products can act on TNBC, promote their ferroptosis, inhibit cancer cells proliferation, enhance sensitivity to radiotherapy, and improve resistance to chemotherapy drugs. To promote the study of ferroptosis in TNBC, this article summarized and reviewed the compounds and natural products that induce ferroptosis in TNBC and their mechanisms of action. We started with the exploration of the pathways of ferroptosis, with particular attention to the System X_c^--cystine-GPX4 pathway and iron metabolism. Then, a series of compounds, including sulfasalazine (SAS), metformin, and statins, were described in terms of how they interact with cells to deplete glutathione (GSH), thereby inhibiting the activity of glutathione peroxidase 4 (GPX4) and preventing the production of lipid peroxidases. The disruption of the cellular defense against oxidative stress ultimately results in the death of TNBC cells. We have also our focus to the realm of natural products, exploring the therapeutic potential of traditional Chinese medicine extracts for TNBC. These herbal extracts exhibit multi-target effects and good safety, and have shown promising capabilities in inducing ferroptosis in TNBC cells. We believe that further exploration and characterization of these natural compounds could lead to the development of a new generation of cancer therapeutics. In addition to traditional chemotherapy, we discussed the role of drug delivery systems in enhancing the efficacy and reducing the toxicity of ferroptosis inducers. Nanoparticles such as exosomes and metal-organic frameworks (MOFs) can improve the solubility and bioavailability of these compounds, thereby expanding their therapeutic potential while minimizing systemic side effects. Although preclinical data on ferroptosis inducers are relatively robust, their translation into clinical practice remains in its early stages. We also emphasize the urgent need for more in-depth and comprehensive research to understand the complex mechanisms of ferroptosis in TNBC. This is crucial for the rational design and development of clinical trials, as well as for leveraging ferroptosis to improve patient outcomes. Hoping the above summarize and review could provide references for the research and development of lead compounds for the treatment for TNBC.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

BACKGROUND:The extracellular-regulated protein kinase 5(ERK5)signaling protein is essential for the survival of organisms,and resveratrol can promote osteoblast proliferation through various pathways.However,whether resveratrol can regulate osteoblast function through the ERK5 signaling protein needs further verification. OBJECTIVE:To explore the regulatory effect of ERK5 on the proliferation of MC3T3-E1 cells and related secreted proteins,and to further verify whether resveratrol can complete the above process by activating ERK5. METHODS:Mouse MC3T3-E1 preosteoblasts were treated with complete culture medium,XMD8-92(an ERK5 inhibitor),epidermal growth factor(an ERK5 activator),resveratrol alone,XMD8-92+EGF,and resveratrol+XMD8-92,respectively.Western blot assay was used to detect the expression of ERK5 and p-ERK5 proteins,proliferation-related proteins Cyclin D1,CDK4 and PCNA,and osteoblast-secreted proteins osteoprotegerin and receptor activator of nuclear factor-κB ligand in MC3T3-E1 cells of each group.The fluorescence intensity of ERK5,osteoprotegerin and receptor activator of nuclear factor-κB ligand in each group was detected by cell immunofluorescence staining,and cell proliferation was detected by EdU staining,respectively.The appropriate concentration and time of resveratrol intervention in MC3T3-E1 cells were determined by cell morphology observation and cell counting kit-8 assay. RESULTS AND CONCLUSION:The activation of ERK5 signaling protein could effectively promote the proliferation of MC3T3-E1 cells,up-regulate the osteoprotegerin/receptor activator of nuclear factor-κB ligand ratio.The appropriate concentration and time for resveratrol intervention in MC3T3-E1 cells was 5 μmol/L and 24 hours,respectively.Resveratrol could activate ERK5 signaling protein,thereby promoting osteoblast proliferation and up-regulating the osteoprotegerin/RANKL ratio.All these results indicate that resveratrol can promote the proliferation of MC3T3-E1 cells and up-regulate the osteoprotegerin/RANKL ratio by activating the ERK5 signaling protein.

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

Syringa pinnatifolia, belonging to the family Oleaceae, is a species endemic to China. It is predominantly distributed in the Helan Mountains region of Inner Mongolia and Ningxia of China. The peeled roots, stems, and thick branches have been used as a distinctive Mongolian medicinal material known as "Shan-chen-xiang", which has effects such as suppressing "khii", clearing heat, and relieving pain and is employed for the treatment of cardiovascular and pulmonary diseases and joint pain. Over the past five years, significant increase was achieved in research on chemical constituents and pharmacological effects. There were a total of 130 new constituents reported, covering sesquiterpenoids, lignans, and alkaloids. Its effects of anti-myocardial ischemia, anti-cerebral ischemia/reperfusion, sedation, and analgesia were revealed, and the mechanisms of agarwood formation were also investigated. To better understand its medical value and potential of clinical application, this review updates the research progress in recent five years focusing on the chemical constituents and pharmacological effects of S. pinnatifolia, providing reference for subsequent research on active ingredient and support for its innovative application in modern medicine system.
Medicine, Mongolian Traditional ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Syringa/chemistry*

Macroporous resin adsorption column chromatography, silica gel column chromatography, ODS column chromatography, and semi-preparative high-performance liquid chromatography, combined with analytical methods such as NMR and MS, were employed to separate and identify compounds from the 70% ethanol extract of Ajania purpurea. A total of 30 compounds were isolated and identified, including 13 phenolic acids, 7 coumarins, 2 lignans, 1 flavonoid, 2 sesquiterpenes, 1 steroid, and 4 others. Among them, compounds 1 and 2 were newly discovered compounds, and compounds 4, 6, 8, 12, 14-23, 25, 28, and 30 were isolated from Ajania plants for the first time. Bioactivity screening showed that multiple compounds significantly inhibited the production of nitric oxide in lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, compound 2 elevated the levels of glutathione in LPS-induced BEAS-2B cells, reduced the expression of pro-inflammatory cytokines such as tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β, enhanced the mRNA of GPX4, HMOX1, NFE2L2, and enhanced protein levels of GPX4, HO-1, Nrf2, and SLC7A11, demonstrating potential anti-ferroptotic effect.
Mice ; Animals ; Lignans/isolation & purification* ; RAW 264.7 Cells ; Humans ; Nitric Oxide ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; NF-E2-Related Factor 2/metabolism* ; Macrophages/metabolism* ; Interleukin-6/immunology*

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*