In this thesis, we propose to establish a phage display method for screening adalimumab (ADM)-specific binding peptide to provide a particular element of recognition for clinical studies of ADM, and to successfully establish an indirect enzyme-linked immunosorbent assay (i-ELISA) based on this peptide for clinical detection of ADM. With ADM as the target molecule, five rounds of peptide elution were performed using phage display technology by putting it into the M13 linear dodecapeptide library. By measuring the titer of each round of eluate, it was found that the recovery rate increased from 7.28×10^-6 to 1.55×10^-3, indicating that the peptides binding to ADM in the eluate were continuously enriched, and the enrichment effect was better; the fifth round of screening amplicons were sequenced, and it was found that five peptide sequences appeared with high frequency, which were considered to be potentially able to bind specifically to ADM and were synthesised; the specific binding ability of the five peptide sequences to ADM was verified and identified by surface plasmon resonance (SPR) and ELISA experiments, respectively, and the results showed that the first peptide sequence (Pep1) and the second peptide sequence (Pep2) showed specific binding to ADM, with the affinity constants (K_D) of 7.91×10^-5 mol·L^-1 and 1.67×10^-5 mol·L^-1, respectively, and of which the affinity constant of Pep1 with ADM isotype antibody IgG was 1.35×10^-4 mol·L^-1, which was one order of magnitude lower than that with ADM, and thus Pep1 was determined to be a specific binding peptide for ADM. Based on Pep1, an indirect ELISA method for the analysis of the antibody-drug ADM was successfully established. With the increasing concentration of ADM the OD₄₅₀ value showed a regular change, and the method can be used for clinical ADM blood concentration monitoring. In this study, we obtained a peptide that can specifically bind to ADM, and this peptide sequence can be used as a specific recognition element for ADM, which not only enables the monitoring of ADM blood concentration, but also provides an effective tool for the accurate qualitative and quantitative quantification of ADM in vivo and ex vivo, and at the same time provides a new strategy and idea for the discovery of recognition elements of other monoclonal antibody drugs.

A detection method using UHPLC-MS/MS was established for the determination of 53 prohibited veterinary drug residues in goat horns, including 16 tranquilizers, 14 β-agonists, chloramphenicol, 4 fluoroquinolones, 7 nitroimidazoles, 3 quinoxalines, and 8 other compounds. Samples were extracted using salting-out assisted liquid-liquid extraction (SALLE). A Zorbax Eclipse Plus C18 column (1.8 μm, 3.0 mm × 150 mm, Agilent) was used with 0.1% formic acid solution-acetonitrile as the mobile phase for gradient elution. Detection was performed in positive and negative electrospray ionization modes using multiple reaction monitoring (MRM). All 53 analytes showed good linearity within their respective concentration ranges, with correlation coefficients above 0.99. The average recoveries at three spiked levels ranged from 70.4% to 118.7%, with relative standard deviations (RSDs) ranging from 0.69% to 12.07%. The limits of detection (LODs) ranged from 0.1 to 50 μg·kg^-1, and the limits of quantitation (LOQs) ranged from 0.2 to 100 μg·kg^-1. This method has been applied to the determination of real samples.

The HIV-1 capsid protein (CA) is an effective target for antiviral drug discovery. Targeting the capsid assembly inhibitor peptide (CAI) binding pocket in the C-terminal domain of HIV-1 CA (CA CTD) can be used to screen for CA protein inhibitors. In this study, we found that the small molecule suramin targets HIV-1 CA by binding to this pocket, with an IC₅₀ value of 2.1 μmol·L^-1 for inhibiting the CA CTD-CAI interaction, based on homogeneous time-resolved fluorescence (HTRF) technology. Bio-layer interferometry (BLI) experiments demonstrated that suramin binds directly to CA, with a binding affinity to CA hexamer (K_D = 248 nmol·L^-1) higher than to CA monomer (K_D = 227 μmol·L^-1). In addition, in vitro CA protein assembly assays showed that suramin promotes disordered multimerization of CA protein. Binding model analysis revealed that suramin binds to the interface between adjacent CA monomers in the CA hexamer through the N57, Q63, Q67 and Y169 residues, thereby enhancing CA multimerization. In summary, suramin is a CA protein inhibitor that targets the CA hexamer and can serve as a starting point for the discovery of new CA inhibitors.

The purpose of this study is not only to investigate the effects of Angelica sinensis polysaccharide (ASP) as a potential vaccine adjuvant on immune activation and cytokine release in RAW264.7 macrophages, but also to elucidate its underlying involved signaling mechanisms. Cell viability was evaluated by the CCK-8 assay. Flow cytometry was used to analyze the influence of ASP at five distinct concentration gradients on the expression of cluster of differentiation (CD) 80, CD86, and major histocompatibility complex Ⅱ (MHC Ⅱ) on RAW264.7 cell surfaces. The levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in cell culture supernatant were determined by enzyme-linked immunosorbent assay (ELISA) method. Molecular techniques, including quantitative polymerase chain reaction (qPCR) were utilized to assess the mRNA expression levels of Toll-like receptor 4 (TLR4)-myeloid differentiation factor 88 (MyD88)-TNF receptor associated factor 6 (TRAF6)-nuclear factor kappa-B (NF-κB) signaling pathway. The levels of TRAF6, and the phosphorylation levels of IκB kinase (IKK) and p65 proteins were detected by Western blot. The results show that ASP at varying concentrations promote the proliferation of RAW264.7 cells without cytotoxicity. Surface molecules CD80, CD86, and MHC Ⅱ on RAW264.7 cells showed statistically significant up-regulation in response to ASP compared to the blank control (P < 0.05), with a dose-dependent effect within an optimal range. Furthermore, ASP also elevated cytokines IL-6 and TNF-α secretion levels by RAW264.7 cells compared to the normal control (P < 0.05), exhibiting a dose-response relationship within a specific concentration span. The qPCR results indicated that ASP groups at different concentrations all led to upregulation of mRNA expression levels of TLR4, MyD88, TRAF6, and NF-κB signaling pathway. The expression levels of TRAF6, p-IKK and p-p65 were increased by different concentrations of ASP. The TLR4 inhibitor TAK-242 significantly reduced the secretion of cytokines induced by APS (P < 0.05). This study highlights the immunostimulatory properties of ASP, emphasizing its potential as a vaccine adjuvant. By significantly enhancing the expression of co-stimulatory molecules and cytokines via the TLR4-MyD88-TRAF6-NF-κB signaling pathway, ASP offers a promising approach for modulating immune responses.

Colorectal cancer is a major cancer threatening the life and health of people worldwide. With the transformation of modern medical models, treatment strategies represented by traditional Chinese medicine (TCM) with multiple targets have become a new research direction in the treatment of colorectal cancer. In the study of TCM, in addition to deconstructing the components and targets of TCM based on reductionism, more attention should be paid to the holistic concept in the basic theories of TCM, analyzing and understanding the mechanism of action of TCM treatment from a holistic perspective. TCM compound prescriptions, as a collection of single herbs, are composed of various monomers. Viewing TCM from different levels and considering different herbs and monomers as a whole helps us better understand TCM. At the same time, TCM has the characteristic of multiple targets. In addition to directly acting on tumor cells themselves, it can also affect the intestinal flora to improve the tumor microenvironment, treating tumors in an all-round and multi-dimensional way, regulating the physical functions of tumor patients from a holistic perspective, and comprehensively improving the health status of the individual. This review aims to systematically elaborate on the efficacy and multi-target mechanism of TCM in the treatment of colorectal cancer from three levels: TCM compound prescriptions, single herbs, and TCM monomers, based on clinical trials and preclinical research results. Meanwhile, this article will combine systems biology with the holistic view of TCM to conduct an in-depth analysis of related research on TCM treatment of colorectal cancer.

Arjunic acid (AR), a main bioactive triterpenoid isolated from acorns, has been reported to exert pronounced anti-inflammatory activities. However, its anti-inflammatory mechanisms have not been elucidated. In this study, the model of lipopolysaccharide (LPS)-induced inflammation in RAW264.7 cells were established to investigate the anti-inflammatory activity of AR. The potent targets and signaling pathway of AR for the treatment of inflammation-related disease were predicted based on network pharmacology. Furthermore, the expression of pro-inflammatory cytokines and mediators was determined by Griess assay, enzyme-linked immunosorbent assay (ELISA), qRT-PCR, and Western blot. The protein expression of NF-κB, MAPK, Nrf2/HO-1, PI3K/Akt/mTOR, and autophagy signaling pathways were gauged by Western blot. As the result, in the inflammatory model of LPS-induced RAW264.7 cells, AR could significantly inhibit the expression of pro-inflammatory cytokines and mediators, suppress the phosphorylation and translocation of NF-κB, and downregulate the phosphorylation of JNK/ERK signaling pathways. AR also inhibited ROS production and activated the Nrf2/HO-1 signaling pathway by degrading Keap1. Furthermore, AR activated autophagic flux by inhibiting the PI3K/Akt/mTOR signaling pathway. Collectively, AR was a potential natural product for the treatment of inflammation-related diseases.

Usenamine A (UA) is a dibenzofuran compound isolated from Usnea longissima Arch. Previous studies have demonstrated that UA exhibited significant in vitro and in vivo anti-hepatocellular carcinoma activity, inducing both apoptosis and autophagy in human hepatocellular carcinoma cells. This study aims to further elucidate the molecular mechanism underlying its anti-hepatocellular carcinoma effect. Based on data obtained from gene chip assay, real-time quantitative PCR, and Western blot analysis, we found that UA effectively inhibited the expression of polo-like kinase 1 (PLK1) in human hepatocellular carcinoma HepG2 and SK-HEP-1 cells. Furthermore, the administration of BI 6727, a PLK1 inhibitor, significantly diminished the inhibitory effect of UA on the viability of human hepatocellular carcinoma cells. Additionally, the knockdown of PLK1 expression via RNA interference markedly inhibited the proliferation of human hepatocellular carcinoma cells, and the inhibitory effect of UA on cell viability was attenuated upon PLK1 knockdown. The knockdown of PLK1 expression significantly upregulated the apoptosis rate of human hepatocellular carcinoma cells and notably diminished the apoptosis-inducing effect of UA on these cells. Additionally, the inhibition of autophagy using the autophagy inhibitor 3-MA reduced the proliferation-inhibitory effect of UA on human hepatocellular carcinoma cells. Utilizing the PLK1 inhibitor BI 6727 or RNA interference, we further demonstrated that PLK1 negatively regulated autophagy in human hepatocellular carcinoma cells. Consequently, the inhibition of PLK1 attenuated the autophagy induction by UA on these cells. Thus, PLK1 plays a crucial role in the inhibition of human hepatocellular carcinoma cell proliferation and the induction of apoptosis by UA. Moreover, UA activates autophagy through the inhibition of PLK1, which subsequently exerts an inhibitory effect on the growth of human hepatocellular carcinoma cells.

To prepare a progesterone pressure-sensitive gel patch combined with a microneedle to enhance drug release, HPLC was used to determine the preparation's progesterone content. One-way and orthogonal experiments were used to optimize the patch's prescription. Adhesion, sensory evaluation, cumulative release, and cumulative penetration were used as evaluation indices. Three microneedles with varying needle heights were made using 3D printing, and the cumulative penetration of the patch and microneedles was calculated and compared with the patch alone. The orthogonal experiments showed that the optimal prescription for the patches was Duro-Tak 87-2677 pressure-sensitive adhesive (87.5%), tributyl citrate (2%), isopropyl myristate (5%), dibutylated hydroxytoluene (0.5%), and drug (5%). The patches were prepared according to the optimized prescription, resulting in good patch formability and adhesion. In the transdermal penetration test, the cumulative penetration of the patch was 52.35 ± 7.88 μg·cm^-2 at 24 h, and the cumulative penetration of the patch in combination with 500, 750, and 1 000 μm microneedles was 226.01 ± 7.46, 278.78 ± 6.59, 422.95 ± 16.81 μg·cm^-2, respectively. The experiment was approved by the Experimental Animal Ethics Committee of Xinjiang Medical University (IACUC-20220725-8). The optimal patch prescription was screened through one-way and orthogonal experiments, and the transdermal penetration effect of patch and microneedle combination preparation was better than that of single use, which can effectively increase the in vitro transdermal penetration of the drug, and the above study provides a theoretical basis for the application of transdermal patches of progesterone.

Artificial intelligence (AI) technology is increasingly applied across various fields, particularly in handling and analyzing large volumes of data, providing breakthroughs for numerous scientific studies. In Chinese medicine research, AI demonstrates significant advantages by enhancing the systematic, efficient, and accurate nature of studies through its exceptional learning and data processing capabilities. As a discipline with a long-standing history and rich theoretical framework, Chinese medicine research requires the integration of complex information, for which AI provides crucial support. AI technologies, especially machine learning and deep learning, can decipher complex biological and chemical data, advancing new discoveries in Chinese medicine pharmacology. Researchers can systematically analyze the multi-target mechanisms of Chinese medicine components and optimize formulation efficacy through these technologies. The combination of AI with multi-omics data and its application in cell phenotype analysis aids in accurately identifying drug targets and exploring new mechanisms. Additionally, AI-integrated network pharmacology combines experimental, computational, and clinical data to analyze multi-target drug mechanisms, enhancing the efficacy of TCM formule. AI accelerates the target identification of active compounds as well as dissecting the pharmacological effects. The development of large language models also plays a crucial role in constructing Chinese medicine knowledge graphs and literature analysis, extracting valuable information from extensive literature using natural language processing to build a systematic knowledge structure. The introduction of AI technology has propelled the modernization of Chinese medicine research and has a pivotal role in the development of internationalization and precision medicine. AI not only enhances the overall level of Chinese medicine research but also provides a solid foundation for interdisciplinary collaboration and innovation. With the continuous advancement of AI technology, Chinese medicine is anticipated to have a greater influence and role globally. This process is not only a significant marker of the modernization of Chinese medicine but also a reflection of the integration of science and traditional wisdom, which will undoubtedly drive progress and development in the entire medical field.

Twenty compounds were isolated from the twigs and leaves of the 95% ethanol extract of Miliusa tenuistipitata W. T. Wang by various chromatographic techniques including silica gel column chromatography, sephadex LH-20 and preparative HPLC. Their structures were determined by analysis of spectral data as tenuistone L (1), tenuistone K (2), sakuranetin (3), pachypodol (4), retusin (5), penduletin (6), casticine (7), 3, 7-dimetoxi-5, 3′, 4′-tri-hidroxiflavona (8), eupatin (9), (+)-miliusol (10), miliusane XIX (11), miliusane XVIII (12), miliusolide (13), 19, 20-dihydromiliusolide (14), debilisone C (15), goniothalamusin (16), 2, 10-dihydroxy-3, 9-dimethoxy-8-oxo-protoberberine (17), consanguine B (18), 6β-hydroxystigmasta-4, 22-dien-3-one (19) and 6β-hydroxystigmast-4-en-3-one (20), respectively. Among them, compounds 1 and 2 are new compounds, compounds 6, 9, 18 and 20 are isolated from Annonaceae plants for the first time and compounds 5, 7, 17 and 19 are isolated from the genus Miliusa for the first time. Human triple negative breast cancer cells (MDA-MB-231 and BT-549) were used to evaluate the antitumor activity of these isolates by MTT assay. Compounds 10 and 11 showed significant anti-proliferation activity against the test cells with half inhibition concentration (IC₅₀) of 0.98-4.85 μmol·L^-1.