To systematically analyze the pharmacokinetic parameters, oral bioavailability and in vivo metabolites of trilobatin in Sprague-Dawley (SD) rats using liquid chromatography - triple quadrupole mass spectrometry (LC-MS/MS).

The chromatographic conditions were performed on an ACQUITY UPLC BEH C₁₈ column (50 mm×2.1 mm, 1.7 µm) with 0.1% formic acid (mobile phase A) and acetonitrile (mobile phase B) as the mobile phase. A gradient elution program was carried out with an accompanying flow rate of 0.3 mL·min^-1, a column temperature of 40 ℃, and an injection volume of 2 μL. The mass spectrometry conditions comprised an electrospray ion source in conjunction with negative ionization mode, with an ionogenic temperature of 150 ℃, a capillary voltage of -3.0 kV, and a desolvation-gas flow temperature of 500 ℃. The desolvation-gas flow rate was set at 750 L·h^-1, and the conical pore gas volumetric flow rate was fixed at 150 L·h^-1. The analysis was conducted in multiple reaction monitoring mode. Trilobatin was given to rats via gavage and intravenous injection, respectively. Plasma, urine and fecal samples were collected, and the drug concentration was determined after methanol precipitation of proteins. Pharmacokinetic parameters and metabolites were analyzed by pharmacokinetic software and metabolite analysis and identification software.

Following the administration of trilobatin to SD rats at a dose of 100 mg·kg^-1 via gavage and intravenous injection, respectively. The area under the curve (AUC_0-t) was found to be (423.98 ± 295.42) ng·h·mL^-1 and (90 894.75 ± 25 472.44) ng·h·mL^-1, respectively. The oral bioavailability was determined to be 0.46%; C_max was (203.83±25.88) ng·mL^-1 and (181 814.90±113 461.60) ng·mL^-1, respectively. The oral half-life was 1.65 h, while the intravenous half-life was 3.82 h. Trilobatin was metabolized to phloretin in the intestine and underwent further biotransformation in vivo through deglycosylation, methylation, deoxygenation and hydrolysis.

The pilot study represents a preliminary investigation into the in vivo pharmacokinetics and metabolism of trilobatin in rats, providing a foundation for further pharmacodynamics research and subsequent formulation development.

To establish a quality evaluation method for Chaihu Yujinxiang granules based on fingerprint, multi-component content determination, and chemical pattern recognition, providing important basis for its quality control.

The “Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (2012 Edition)” was used to establish HPLC fingerprints of 10 batches of Chaihu Yujinxiang granules, identify common peaks, and perform similarity evaluation. HPLC method for determining the content of four active ingredients, namely liquiritin apioside, liquiritin, liquiritigenin, and isoliquiritigenin was established. Cluster analysis and orthogonal partial least squares discriminant analysis were conducted on Chaihu Yujinxiang granules using SPSS 26.0 and SIMCA 14.1 software. Differential components affecting the quality of Chaihu Yujinxiang granules were screened based on the criterion of variable importance projection (VIP) value>1.0.

The established fingerprint and multi-component content determination method achieved satisfactory results after methodological investigation. The similarity of the fingerprint of 10 batches of Chaihu Yujinxiang granules ranges from 0.953 to 0.977, with a total of 11 common peaks, 4 of which were identified. The average contents of active ingredients such as liquiritin apioside, liquiritin, liquiritigenin, and isoliquiritigenin in 10 batches of Chaihu Yujinxiang granules were 2.71 mg·g^-1, 10.17 mg·g^-1, 2.47 mg·g^-1, and 1.86 mg·g^–1, respectively. The results of cluster analysis and principal component analysis indicates that 10 batches of Chaihu Yujinxiang granules could be clustered into two categories, with S3, S6, and S8 in one category and the rest in another category. The VIP values of peaks 2, 9, 7, and 3 were above 1.0.

The established fingerprint and content determination method are stable and reliable. Combined with chemical pattern recognition technology, they can be used to evaluate the overall quality of Chaihu Yujinxiang granules. Peaks 2, 9, 7, and 3 are differential components that affect the quality of Chaihu Yujinxiang granules.

To identify the authenticity of four batches of “Ophiopogonis Radix” in the market by means of multiple means, and to explore the reasons for exceeding the limit of its phloem bundles, so as to provide evidence for its inspection and detection.

Based on the relevant provisions of Ophiopogon japonicus (L. f.) Ker-Gawl., a variety in the 2020 edition of Chinese Pharmacopoeia, comparing the common confused products of Ophiopogon japonicus (L. f.) Ker-Gawl., Combined with traditional identification methods (character identification, microscopic identification) and modern analysis techniques (molecular biology ITS 2 sequence), the data of genuine products with mixed products and substandard phloem bundle samples were campared and analyzed.

The differences between Liriope spicata (Thunb.) Lour. and Ophiopogon japonicus (L. f.) Ker-Gawl. were the surface color, the depth of vertical wrinkles and the thickness of the middle column, and the differences in microscopic cross-sections lay in the number of phloem bundles and whether the inner cortex cells were uniformly thickened. The four batches of “Ophiopogonis Radix” in the market all complied with the relevant regulations under Ophiopogon japonicus (L. f.) Ker-Gawl.. The number of unqualified phloem bundled into microscopic cross-sections. was more than 40%, but the inner cortex cells in the samples showed a comprehensive thickening phenomenon. The results of molecular biology study showed that the four batches of “Ophiopogonis Radix” on the market and the Ophiopogon japonicus (L. f.) Ker-Gawl. were clustered into one, the Liriope spicata (Thunb.) Lour.var. prolifera Y. T. Ma and the Liriope muscari (Decne.) Baily were clustered into one, and showed obvious bar code spacing. The number of phloem bundles was obvious positively correlated with the diameter of wood core by correlation analysis of the number of phloem bundles and the quantitative indexes related to traits.

These four batches of “Ophiopogonis Radix” on the market are the original of genuine products. Combined with the experimental research, it is speculated that the cause of the unqualified number of phloem bundles may be related to the growth years, and the middle column thickness can roughly predict whether it can meet the requirements of pharmacopoeia. To determine whether Ophiopogonis Radix is an accurate medicinal material based on the original, we should not only make a conclusion based on a certain feature of a certain identification method, but also should combine multiple methods to determine accurately.

To establish an HPLC method for the determination of residual solvent formic acid and cyanoacetic acid content in tofacitinib citrate.

The separation was performed on a Waters Atlantis T3(250 mm×4.6 mm, 5 μm) column with a gradient elution of 0.02 mol·L^-1 potassium dihydrogen phosphate (pH was adjusted to 2.5 with phosphoric acid) (A) - methanol (B) as the mobile phases. The flow rate was 0.5 mL·min^-1 and the column temperature was 35 ℃. Detection wavelength was 210 nm.

Formic acid and cyanoacetic acid were well separated from the adjacent peaks (R>5). The linearity was good in the concentration ranges of 9.930-107.780 μg·mL^-1 and 14.727-98.908 μg·mL^-1 (r = 0.999 9, 0.999 8), respectively. The average recoveries (n=9) were 100.2% and 105.3%, with RSDs of 2.3% and 4.1%, respectively. The determination results of three batches of samples were 0.024%, 0.026%, 0.028% (cyanoacetic acid), respectively.

The established method is proved to be suitable for the determination of formic acid and cyanoacetic acid in tofacitinib citrate.

To establish an LC-MS/MS method for determining the concentrations of imipenem and cilastatin in human plasma, for monitoring clinical therapeutic drug concentrations, and to investigate the effects of adding stabilizers during the sample pretreatment on mass spectrometry signal intensity.

After protein precipitation, the sample was subjected to gradient elution using an Agilent TC-C₁₈ (2) (150 mm×4.6 mm, 5 µm) column with a mobile phase system of 0.15% formic acid in water and methanol. The electrospray ionization (ESI) mass spectrometer was operated in positive ion mode using multiple reaction monitoring (MRM): m/z 300.1 → 141.9 (imipenem),m/z 359.7 → 97.0 (cilastatin) and m/z 384.1 → 141.1 (meropenem, internal standard). The samples containing and without 3-(N-morpholino) propane sulfonic acid (MOPS) as stabilizers were pretreated and continuously analyzed to compare the changes in mass spectrometry signal intensity.

Both imipenem and cilastatin showed good linearities in the concentration ranges of 0.1-100.0 μg·mL^-1 (r>0.99). The intra-day and inter-day accuracy ranges from 95.3% to 108.5%, the precision (RSDs) were less than 9.3%, the extraction recovery rate ranges from 77.4% to 84.3%, and the matrix effect ranges from 97.1% to 111.2%. Imipenem in plasma samples was stable at room temperature for 3 h, at 4 ℃ for 6 h, and at -80 ℃ for 12 d, while it was significantly degraded at -20 ℃ for 12 d. Cilastatin was stable under a variety of conditions. The method was robust to changing conditions of column temperature ±5 ℃, flow rate ±0.1 mL·min^-1, formic acid concentration in the aqueous phase ±0.025%, and ion source temperature ±50 ℃. The samples containing stabilizers exhibited significant ion inhibition on mass spectrometry after continuous injection, while samples without stabilizers had no significant effect on the signal intensity of mass spectrometry.

The method is simple and accurate and can be used for clinical drug monitoring of imipenem and cilastatin. Nonvolatile salt stabilizers such as MOPS can reduce mass spectrometry sensitivity, and the absence of such stabilizers is more suitable for long-term analysis by LC-MS/MS.

To establish a principal component external standard method with HPLC and calibration factors for the determination of 11 impurities in flurbiprofen axetil injection, and to explore its detection results and limit values.

The Thermo BDS Hypersil C₁₈ (250×4.6 mm, 5 μm) was selected for gradient elution, with water-0.15% acetic acid and acetonitrile-0.15% acetic acid as the mobile phase at a flow rate of 1.0 mL·min^-1. The column temperature was 40 ℃, the detection wavelength was 254 nm and the injection volume was 10 μL.

Flurbiprofen axetil and 11 impurities were well separated by the method. Good linearity was obtained with correlation coefficients of 1.000 for the 3-fluoro-4-phenylphenol (4-OHB), 1-acetoxyethyl-2-(2-fluoro-4-biphenylyl)-2-hydroxypropionate (2-OHP), 4-acetyl-2-fluorobiphenyl (4-ACB), flurbiprofen ethyl ester, allyl -(2-fluoro-4-biphenyl) propionate (ALE), ChP impurityⅠ , impurity B, impurity C and impurity E in the range of 0.10-20 μg·mL^-1. The average recovery rates was from 96.6% to 103.7% and the relative standard deviations(RSDs) were lower than 1.4%. The correction factors of flurbiprofen axetil related substances 4-OHB, 2-OHP,4-ACB, flurbiprofen, flurbiprofen ethyl ester, ALE, ChP impurity Ⅰ, impurity B, impurity C and impurity E were 0.55, 1.05, 1.01, 0.76, 0.95, 0.86, 0.55, 0.93, 0.76 and 0.81, respectively. Notablely, desfluoro fiurbiprofen axetil of detected was around the prescribed limit 0.1%.

The method above is rapid, simple, accurate, and reliable, and can be applied for the determination and quality control of related substances in flurbiprofen axetil injection.

To study the rapid identification of cow-bezoar and its substitutes medicinal herbs using the technique of rapid evaporative ionization mass spectrometry (REIMS) couple with machine learning.

The samples were ionized and determined by REIMS with m/z 50-1 200 as scanning range in sensitive mode and negative ion mode, 0.2 s as scanning time, and using dry burning method. REIMS data of samples was recorded as continuous mode. Then the general situation of REIMS data distribution was studied and analyzed through the methods of cluster analysis and principal component analysis. Some models or algorithms, such as partial least squares discriminant analysis (PLS-DA), logistic regression (LR), decision tree (DT), random forest (RF) and adaptive boosting (AdaBoost, with LR and DT as base estimator respectively) were established. In the models training procedure, simulation synthesis data generated by algorithms of GaussianCopula, CTGAN, CopulaGAN and TVAE joined the original training set data as the new training set.

AdaBoost (DT as base estimator) trained with the new training set was the best model which could accurately predict cow-bezoar and its substitutes medicinal herbs. The accuracy for identifying the test set was 0.97, the precision was 0.90, the recall was 0.97, the F1 score was 0.93, and the AUC of ROC was 1.00. The probability output from the model could also be flexibly used by adjusting the probability threshold according to the actual application scenarios of drug regulation.

The combination of REIMS technology and machine learning technology can achieve fast and accurate recognition of cow-bezoar and its substitutes medicinal herbs.

To explore the biological function methods of mesenchymal stem cells(MSCs) for quality analysis.

The surface markers of MSCs were detected by flow cytometry. MSCs osteogenic differentiation was induced by ascorbic acid and β-glycerophosphate sodium, etc., followed by Alizarin Red S staining. MSCs adipogenic differentiation was induced by IBMX, Rosiglitazone, etc., followed by Oil Red O staining. MSCs could differentiate into chondrocytes with treatment of ITS and TGFβ3, etc., followed by Alcian Blue staining. Cell co-culture of THP-1-macrophage with MSCs and ELISA assay were applied to detect the effects of MSCs on macrophage polarization. The expression levels of IL-10 and TNF α in the cell co-culture supernatant were detected by ELISA. To observe the effects of MSCs on lymphocyte proliferation, MSCs cultured with PBMCs, which were labeled with CFSE and activated by CD3/CD28, followed by flow cytometry.

The expression of MSCs surface markers, CD105, CD73, and CD90, was more than 95% respectively, while the expression of CD45, CD34, CD14, CD19, and HLA-DR expression was less than 2%. MSCs osteogenic differentiation assay showed red calcium nodules. Red lipid vacuoles were observed in MSCs adipogenic induction differentiation. Furthermore, MSCs have the differentiation potential to chondrocyte spheroids, and typical cartilage pits were observed. Coculture of MSCs with THP-1 macrophages, an increase in IL-10 expression and downregulate TNFα secretion were observed. MSCs played inhibitory effects on the proliferation of PBMC activated by CD3/CD28, with an inhibition rate of 76.4%.

This study established some of biological activity detection methods for MSCs, including MSCs surface markers, differentiation abilities, promotion of macrophage polarization, and inhibitory effects on lymphocyte proliferation. It provides a potential application for MSCs products quality control.