Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

This study aimed to compare the ameliorative effects of Lycii Fructus and Chrysanthemi Flos at different ratios on retinal damage in mice and to elucidate the underlying mechanisms. A retinal injury model was established by intraperitoneal injection of sodium iodate(NaIO_3) solution. The mice were divided into the following groups: blank group, model group, positive drug(AREDS 2) group, low-and high-dose groups of Lycii Fructus and Chrysanthemi Flos at 1∶1, low-and high-dose groups at 3∶1, and low-and high-dose groups at 1∶3. Administration was carried out 15 days after modeling. The visual acuity of the mice was assessed using the black-and-white box test. The fundus was observed using an optical coherence tomography device, and retinal thickness was measured. HE staining was used to observe the morphology and pathological changes of the retina. The levels of oxidative factors in serum and ocular tissues were measured using assay kits. The levels of inflammatory factors in serum and ocular tissues were detected by enzyme-linked immunosorbent assay(ELISA), and the expression of Nrf2, HO-1, and NF-κB proteins in ocular tissues was analyzed by Western blot. The results showed that after administration of Lycii Fructus and Chrysanthemi Flos at different ratios, the model group showed improved retinal thinning and disordered arrangement of retinal layers, elevated content of SOD and GSH in the serum and ocular tissues, and reduced levels of MDA, TNF-α, IL-1β, and IL-6. Lycii Fructus and Chrysanthemi Flos at 1∶1 and 1∶3 showed better improvement effects. The combination significantly upregulated the expression levels of Nrf2 and HO-1 and downregulated the expression of NF-κB p65. These results indicate that Lycii Fructus and Chrysanthemi Flos at different ratios can improve retinal damage, reduce oxidative stress, and alleviate inflammation in both the body and ocular tissues of mice. The mechanism may be related to the regulation of the Nrf2/HO-1 and NF-κB signaling pathways in ocular tissues. These findings provide a theoretical basis for the clinical application of Lycii Fructus and Chrysanthemi Flos in the treatment of dry age-related macular degeneration.
Animals ; Mice ; Retina/injuries* ; Male ; Lycium/chemistry* ; Drugs, Chinese Herbal/administration & dosage* ; Chrysanthemum/chemistry* ; NF-kappa B/genetics* ; Humans ; Retinal Diseases/metabolism* ; NF-E2-Related Factor 2/metabolism* ; Oxidative Stress/drug effects* ; Flowers/chemistry* ; Heme Oxygenase-1/genetics*

As one of the chronic diseases with high incidence in contemporary society, cervical spondylosis has increasing patient groups who gradually present a low age, and it seriously affects social and public health. Although modern medicine has made great progress in the pathological research and clinical treatment of cervical spondylosis, patients still face gastrointestinal side effects of nonsteroidal anti-inflammatory drugs(NSAIDs), neck pain, limited mobility, upper limb numbness, and other symptoms after conservative or surgical treatment. In the theory of traditional Chinese medicine(TCM), cervical spondylosis belongs to the categories of "Bi syndrome" "stiff neck" "stiff Bi", etc. With the change of the times, the change of lifestyle, and the application of western medicine treatment, the etiology and pathogenesis of TCM in cervical spondylosis also show new characteristics. In terms of etiology and pathogenesis, it involves the invasion of wind, cold, and dampness, long-term strain, liver and kidney deficiency, Qi and blood stasis, which are associated with factors such as cervical degeneration, muscle tension and spasm, intervertebral disc herniation, and nerve root compression in modern medicine. In terms of the evolution of pathogenesis, in the early stage, wind, cold, and dampness, were more common in Xuanfu, resulting in unfavorable muscles and bones, poor flow of Qi and blood, and cervical spondylosis and radiculopathy. Medium-term phlegm stasis and internal knots, sluggish muscles and veins, and long-term weathering and fire are more likely to occur in the vertebral artery and sympathetic radiculopathy. In the later stage, the positive Qi is depleted; the true Yin is damaged, and the viscera Qi and blood are deficient, which is most common in cervical myelopathy. The strategy of treating cervical spondylosis with TCM classic formulas applies Gegen Decoction, Wutou Decoction, Qianghuo Shengshi Decoction, Mahuang Jiazhu Decoction to patients with wind, cold, and dampness. Patients with phlegm dampness and blood stasis are treated with Huoxue Xiaoling Dan, Jinlingzi Powder, Siwu Decoction, Banxia Baizhu Tianma Decoction, Shuanghe Decoction, etc. For those patients with liver, spleen, and kidney deficiency, Huangqi Guizhi Wuwu Decoction, Tianma Gouteng Decoction, Guishao Dihuang Pills, Shenling Baizhu Powder, and Lizhong Decoction are used to invigorate the spleen, nourish Qi and blood, and tonify liver and kidney. In clinical practice, the authors advocate a safe and effective treatment plan of classic formulas based on deficiency and excess, the integration of formulas and syndromes, and the combination of modern research results, so as to relieve symptoms, reduce recurrence, and reduce medical burden.
Humans ; Spondylosis/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Cervical Vertebrae/pathology*

Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis* ; Saccharomyces cerevisiae/genetics* ; Triterpenes/metabolism* ; Metabolic Engineering ; Oleanolic Acid/biosynthesis* ; Ursolic Acid

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

This study employed bioinformatics to screen the feature genes related to efferocytosis in diabetic kidney disease(DKD) and explores traditional Chinese medicine(TCM) regulating these feature genes. The GSE96804 and GSE30528 datasets were integrated as the training set, and the intersection of differentially expressed genes and efferocytosis-related genes(ERGs) was identified as DKD-ERGs. Subsequently, correlation analysis, protein-protein interaction(PPI) network construction, enrichment analysis, and immune infiltration analysis were performed. Consensus clustering was conducted on DKD patients based on the expression levels of DKD-ERGs, and the expression levels, immune infiltration characteristics, and gene set variations between different subtypes were explored. Eight machine learning models were constructed and their prediction performance was evaluated. The best-performing model was evaluated by nomograms, calibration curves, and external datasets, followed by the identification of efferocytosis-related feature genes associated with DKD. Finally, potential TCMs that can regulate these feature genes were predicted. The results showed that the training set contained 640 differentially expressed genes, and after intersecting with ERGs, 12 DKD-ERGs were obtained, which demonstrated mutual regulation and immune modulation effects. Consensus clustering divided DKD into two subtypes, C1 and C2. The support vector machine(SVM) model had the best performance, predicting that growth arrest-specific protein 6(GAS6), S100 calcium-binding protein A9(S100A9), C-X3-C motif chemokine ligand 1(CX3CL1), 5'-nucleotidase(NT5E), and interleukin 33(IL33) were the feature genes of DKD. Potential TCMs with therapeutic effects included Astragali Radix, Trionycis Carapax, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma, which mainly function to clear heat, replenish deficiency, activate blood, resolve stasis, and promote urination and drain dampness. Molecular docking revealed that the key components of these TCMs, including β-sitosterol, quercetin, and sitosterol, exhibited good binding activity with the five target genes. These results indicated that efferocytosis played a crucial role in the development and progression of DKD. The feature genes closely related to both DKD and efferocytosis, such as GAS6, S100A9, CX3CL1, NT5E, and IL33, were identified. TCMs such as Astragali Radix, Trionycis Carapa, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma may provide a new therapeutic strategy for DKD by regulating efferocytosis.
Humans ; Computational Biology ; Diabetic Nephropathies/physiopathology* ; Protein Interaction Maps ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Phagocytosis/genetics* ; Efferocytosis