To establish a multiple fingerprint analysis method for polysaccharides from Sanghuangporus sanghuang, providing a reference for quality evaluation.

High-performance gel filtration chromatography(HPGFC-RID) was used with a TSK-GEL^®G3000 PWXL column (7.8 mm×30 cm, 7 μm). The mobile phase was 20 mmol·L^-1 HAc-NaAc buffer (pH 5.7) at a flow rate of 0.5 mL·min^-1. The injection volume was 15 μL, column temperature was 35 ℃, and detection was carried out using a RID detector. Fourier transform infrared(FT-IR) spectroscopy was performed in the range of 4 000 to 400 cm^-1 with a resolution of 4 cm^-1 and 16 scans. HPLC-UV monosaccharide profiling was done using an Agilent 5 HC-C₁₈ column (250 mm×4.6 mm, 5 μm), with acetonitrile-0.02 mol·L^-1 ammonium acetate (20：80) as the mobile phase, at a flow rate of 1 mL·min^-1, detection wavelength of 250 nm, an injection volume of 10 μL, and column temperature of 35 ℃. An UV detector was used for detection. Multiple fingerprints of Sanghuangporus polysaccharides were established, and the mass average molar mass, characteristic absorptive functional groups, and monosaccharide compositions of 29 batches of Sanghuangporus polysaccharides were compared and analyzed for their intraspecific and interspecific variations by combining with chemometrics and principal component analysis (PCA).

HPGFC-RID monosaccharide profiling revealed that the polysaccharides from Sanghuangporus sanghuang (SH), Sanghuangporus vaninii (YH), Sanghuangporus baumii (BH), and Phellinus pini (SHH) all exhibited two major chromatographic peaks (P1, P2). For P1, BH polysaccharides had the highest molecular weight, followed by SSH, SH, and YH polysaccharides. For P2, YH polysaccharides had the highest molecular weight, followed by SSH, SH, and BH polysaccharides. FT-IR analysis indicated that SH, YH, BH, and SSH polysaccharides shared similar infrared absorption peaks, with no significant differences between species or within species. However, the intensity of the main uptake peaks in the range of 1 800-900 cm^-1 was different between bagged and linden cultivated Sanghuangporus polysaccharides. HPLC-UV monosaccharide profiling combined with chemometrics revealed that Sanghuangporus polysaccharides consist of mannose, rhamnose, glucose, xylose, and fucose. Glucose content was the highest in SH, YH (linden cultivation), BH, and SSH polysaccharides, while xylose was the highest in YH (bagged cultivation). Monosaccharide composition varied significantly among different Sanghuangporus varieties. PCA grouped YH (bagged cultivation) as one class, and SH, YH (linden cultivation), BH, and SSH as another, indicating that cultivation methods also influence Sanghuangporus quality.

The multiple fingerprint analysis method for Sanghuangporus polysaccharides effectively evaluates the quality of different Sanghuangporus varieties, providing a foundation for quality control.

To establish a method for the identification and characterization of Herba Hyssopi and its adulterants, Nepeta bracteata and Hyssopus officinalis.

Applying stereo microscopy, optical microscopy, and their digital image techniques, the author conducted a comparative study on Herba Hyssopi its adulterants in terms of macroscopic and microscopic characteristics of the whole plant, small samples, and local features (stems, leaves, and flowers), well as the cross sections of stems and leaves and the microscopic characteristics of powders.

There were significant differences in stem, leaf, flower and odor among Hyssopus cuspidatus, Hyssopus officinalis and Nepeta bracteata. The microscopical characteristics of stem cross section were slightly different, but there were obvious differences in leaf cross section and medicinal powder of the three species.

In this study, the pharmacognostic identification characteristics of Herba Hyssopi and its adulterants, Nepeta bracteata and Hyssopus officinalis, were summarized, which can provide the identification basis for the supervision, standard revision and clinical use of Herba Hyssopi.

To investigate an unknown peak at relative retention time (RRT) 0.95 of N-nitrosodiethylamine (NDEA) of irbesartan API with the LC-MS/MS detection method. To elucidate the structure and origin of this unknown peak. Its structure was confirmed with a reference compound, and a method optimization strategy was proposed to eliminate the impact of this unknown peak.

The unknown peak causing interference in the determination of NDEA within sartan drug substances was examined using a full scan method of LC-MS/MS analysis. The unknown peak at RRT 0.95 was validated by conducting high resolution LC-MS analyses and comparing with that of a reference sample. Additionally, a strategy for resolving this issue was proposed in the further investigation.

According to the LC-Q TOF MS results, the unknown peak at RRT 0.95 was confirmed to be 1-pentanamide, a trace regular impurity commonly existing in the sartan samples. As the extract mass of 1-pentanamide was 1 less than that of NDEA, the m/z value of an isotope in 1-pentanamide ([M+H]⁺+1) was 103 and was equal to the m/z value of the main [M+H]⁺ isotope of NDEA under the MRM mode. Furthermore, the [M+H]⁺+1 isotope ion of 1-pentanamide could occur a neutral lose by leaving a molecule of ethylene to generate the isotope ion of m/z 75, which was similar to NDEA in the MRM analysis under ESI positive mode. Therefore, when m/z 103 was used as the precursor ion and m/z 75 was used as the quantitative ion, 1-pentanamide will interfere with detection of NDEA.

In the LC-MS/MS analysis for NDEA, the unknown peak observed at a retention time of 0.95 has been identified as 1-pentanamide. This compound is confirmed as a common trace impurity that regularly occurs during the production of sartan active pharmaceutical ingredients (APIs), rather than being another nitrosamine impurity. Subsequent research has revealed that employing a more selective quantitative model and choosing m/z 47 as the quantifier ion effectively avoid the unknown peak caused by 1-pentanamide.

To collect 37 batches of Scrophulariae Radix decoction pieces from the market as the research object, and to establish a quality grade standard of Scrophulariae Radix decoction pieces based on the correlation between quantitative appearance characteristics and intrinsic quality.

According to the traditional quality evaluation method, 37 batches of Scrophulariae Radix decoction pieces were divided into two grades—A and B. Their appearance characteristics were quantified while their moisture, ash, leaching and intrinsic quality indexes were detected, respectively. Finally, the independent sample t test analysis, orthogonal partial least squares discriminant analysis (OPLS-DA) and Pearson correlation analysis were carried out to reveal the correlation between appearance characteristics and intrinsic quality.

On the basis of meeting the quality control standard of Scrophulariae Radix recorded in the 2020 edition of the Pharmacopoeia of the People's Republic of China（referred to as Chinese Pharmacopoeia, ChP）, it was found that water-soluble extractives and alcohol-soluble extractives were the key indexes for the grades classification of Scrophulariae Radix decoction pieces. In summary, the lower the chromatic value and the greater the density（ρ）of Scrophulariae Radix decoction pieces, the higher the water-soluble extractives and the lower the alcohol-soluble extractives. The grading quality standard of “selected goods” and “gradeless and uniformly priced goods” of Scrophulariae Radix decoction pieces were preliminarily drawn up: the chromatic value（E^*ab）of “selected goods” of Scrophulariae Radix decoction pieces should be less than or equal to 5.5, the ρ of Scrophulariae Radix decoction pieces should be greater than or equal to 1.4 g·cm^-3, and the content of water-soluble extractives should be greater than or equal to 77%, the value of E^*ab of “gradeless and uniformly priced goods” of Scrophulariae Radix decoction pieces should be between 5.5 and 14, the value of ρ should be between 0.8 and 1.4 g·cm^-3, and the content of water-soluble extractives should be greater than or equal to 60%.

The appearance characteristics of Scrophulariae Radix decoction pieces are related with the internal quality, which is consistent with the traditional quality evaluation method, and it is convenient to scientifically judge the internal quality of Scrophulariae Radix decoction pieces from its appearance characteristics.

To establish a method combining size exclusion chromatography (SEC) with an optimized Infogest in vitro static digestion model for determining the relative molecular mass distribution of short-peptide-based enteral nutrition before and after digestion. To evaluate and assess the quality of three different products, to explore product quality characteristics and digestive stability, and to provide guidance for quality control and clinical individualized application of short-peptide-based enteral nutrition.

The SEC method was performed using two ECOSIL SEC G 2000 columns (300 mm×7.8 mm, 5 μm) in series, with acetonitrile-water-trifluoroacetic acid(15：8 5：0 .1) as the mobile phase, a flow rate of 0.7 mL·min^-1, the column temperature 30 ℃, the detection wavelength 215 nm, and the sample volume 20 μL. The in vitro simulated digestion process referred to and optimized the Infogest in vitro static digestion model, divided into simulated gastric digestion, simulated intestinal digestion, and simulated gastro-intestinal total digestion stages. The established SEC method was used to compare changes in the relative molecular mass distribution before and after digestion to evaluate in vitro digestive stability.

Within the range of relative molecular mass from 165.19 to 12 327, the logarithms of the relative molecular mass of the 8 reference standards showed good linear relationships with retention time. Specificity tests indicated that blank solvent and the simulated gastric-intestinal digestion solution had minimal impact on the measurement of relative molecular mass distribution. The RSDs for precision, repeatability, and 24 h stability tests were all less than 1.0%. The relative molecular mass of various short peptide enteral nutrition products was mainly concentrated between 150 and 1 000, but there were significant differences in the distribution ratios of relative molecular mass among different products. The hydrolysis of peptide components primarily occurred during the production stage, and after in vitro simulated digestion, their relative molecular mass distribution characteristics remained largely unchanged, with the degree of change mainly related to the original hydrolysis level of the product.

The SEC method combined with the optimized Infogest model is suitable for studying the molecular mass distribution and digestive stability of short-peptide-based enteral nutrition. The method is straightforward and rapid, facilitating a comprehensive assessment of the products quality characteristics and nutritional value.

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 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.