To conduct odor analysis of the main effective components, namely volatile oils, contained in two varieties, Notopterygium incisum Ting ex H.T.Chang and Notopterygium franchetii H.de Boiss, to provide a feasible method for promptly and accurately distinguishing between the differences in volatile oils of these two varieties of Notopterygii Rhizoma et Radix. This enriches the traditional evaluation content and serves as a reference for assessing the quality of extracts predominantly governed by volatile oils.

The flavors of two samples of Notopterygii Rhizoma et Radix volatile oil were analyzed using electronic nose technology and sensory evaluation. The electronic nose data obtained were subjected to analysis and identification through principal component analysis (PCA) and linear discriminant analysis (LDA). Additionally，two nondestructive testing models-Fisher discrimination and multilayer perceptron (MLP) neural network discrimination were established for sample differentiation.

Sensory evaluation results indicated that pine resin flavor，cool flavor and woody flavor were the primary odor characteristics of both Notopterygii Rhizoma et Radix volatile oils. Additionally，the key flavor attribute influencing acceptance and differentiation was identified as spoiled yuba flavor，with the Notopterygium franchetii H. de Boiss volatile oil exhibiting a stronger presence of this attribute than the Notopterygium incisum Ting ex H. T. Chang volatile oil. The electronic nose results revealed that the nitrogen oxides’ response values in Notopterygium franchetii H. de Boiss volatile oil were significantly higher than those in Notopterygium incisum Ting ex H. T. Chang volatile oil. Meanwhile，the response values of hydrides，alcohol ether aldehydes，and ketones were slightly lower in Notopterygium franchetii H. de Boiss volatile oil compared to Notopterygium incisum Ting ex H. T. Chang volatile oil. The Fisher discriminant model demonstrated overall discrimination rates of 93.8% for the training set and 87.5% for the prediction set of the two volatile oils. In contrast，the MLP model achieved discrimination rates of 89.3% for the training set and 91.7% for the prediction set. Notably，the MLP model proved effective for identifying volatile oils，while the Fisher model exhibited greater suitability for discriminating volatile oils with broad-leaved characteristics.

The combination of artificial senses and intelligent senses can be characterized from both subjective and objective perspectives，elucidating the flavor differences between the two kinds of Notopterygii Rhizoma et Radix volatile oils. The established Fisher discriminant function and MLP discriminant models can rapidly and accurately distinguish between the two kinds of Notopterygii Rhizoma et Radix volatiles. This lays a preliminary foundation for quality control in Notopterygii Rhizoma et Radix volatiles and offers new ideas and directions.

To establish the substances benchmarks fingerprint of Daqinglong decoction and determine the content and transfer rate of 6 index components，and study the transfer rule of Daqinglong decoction substances benchmarks value，which laid the foundation for the study of Daqinglong decoction compound preparation and quality standard.

Fifteen batches of substances benchmarks of Daqinglong decoction were prepared，and the paste rate was determined. To determine the contents of ephedrine，pseudoephedrine，amygdalin，and cinnamic acid，HPLC method was performed on a Dikma Platisil C₁₈ column (250 mm×4.6 mm，5 μm). And 0.15% phosphoric acid water (A) and acetonitrile (B) were used as mobile phases with gradient elution at a flow rate of 1 mL·min^-1. The column temperature was 25 ℃，the detection wavelength was 207 nm，and the injection volume was 10 μL. To determine the contents of liquiritin and glycyrrhizic acid，0.05% phosphoric acid water (A) and acetonitrile (B) were used as mobile phases with gradient elution. The detection wavelength was 237 nm. The transfer rate was calculated，and the transfer analysis from the decoction pieces to the substances benchmarks was carried out.

The fingerprint similarities of 15 batches of Daqinglong decoction substances were ≥0.921. Fifteen common peaks were identified，including 8 from Ephedrae Herba，3 from Cinnamomi Ramulus，2 from Glycyrrhizae Radix et Rhizoma(fried)，and 2 from Armeniacae Semen Amarum(here). The contents of ephedrine，pseudoephedrine，amygdalin，liquiritin，cinnamic acid and glycyrrhizic acid were 0.94%-1.30%，0.56%-1.02%，0.70%-1.25%，0.18%-0.32%，0.05%-0.10% and 0.46%-1.23%，respectively. The transfer rates were 41.67%-59.47%，42.66%-59.74%，17.59%-36.34%，21.48%-44.75%，31.06%-48.89% and 12.95%-25.15%，respectively. The paste yields of substances benchmarks were 11.98%-13.38%.

The fingerprint combined with the determination of paste rates and index component contents are used to study the quantitative value transfer of Daqinglong decoction substance benchmarks，and initially establish a scientific and stable substance benchmarks quality evaluation method，which can provide reference for the future research on compound preparation.

To establish the HPLC characteristic chromatogram for Gujing Maisiha tablets，and evaluate the quality using chemical pattern recognition.

The Welch Xtimate C₁₈ column (250 mm × 4.6 mm, 5 μm) was used and the mobile phases were acetonitrile (A) and 0.1% formic acid (B) in gradient elution (0-10 min，5%A→15%A；10-20 min，15%A；20-40 min，15%A→40%A；40-65 min，40%A→70%A；65-66 min，70%A→90%A；66-80 min，90%A；80-81 min，90%A→5%A；81-85 min，5%A). The detection wavelength was 254 nm. The column temperature was 35 ℃ and the flow rate was 1.0 mL·min^-1. Gujing Maisiha tablets were analyzed to construct characteristic chromatogram. The quality of Gujing Maisiha tablets was assessed through similarity evaluation，cluster analysis，principal component analysis (PCA)，and partial least squares discriminant analysis (PLS-DA).

The characteristic chromatogram of Gujing Maisiha tablets was established，which contained the twenty-eight distinct peaks，and seven compounds identified as gallic acid，chlorogenic acid，picrocrocin，isoquercitrin，crocin-Ⅰ，crocin-Ⅱ，eugenol. The similarities for the ten batches of Gujing Maisiha tablets were more than 0.98，with no significant difference observed. Cluster analysis segregated the samples into two distinct groups according to the Euclidean distance of 10，which was consistent with the results of PCA analysis. PLS-DA analysis screened out five components from Flos Caryophylli，Rosae Rugosae Flos，Olibanum that may cause differences between samples.

The method of HPLC characteristic chromatogram of Gujing Maisiha tablets is effective，feasible and reproducible，which can provide reference for the study of quality standard of this product.

To establish an HPLC fingerprint of Zuoyu’an San and conduct quality control by combining chemometrics and quantitative analysis of multi-components with a single-marker（QAMS）.

HPLC was used to establish the fingerprint spectra of 12 batches of Zuoyu’an San and perform similarity evaluation. Cluster analysis (CA)，principal component analysis (PCA)，and orthogonal partial least squares discriminant analysis (OPLS-DA) were combined to perform chemical pattern recognition analysis on different batches of Zuoyu’an San. At the same time，QAMS method was established using rhein as the internal standard reference. The relative correction factors between the internal reference and jatrorrhizine，palmatine，berberine，aloe-emodin，emodin，chrysophanol，and physcion were established. The external standard method (ESM) and QAMS method were used to determine jatrorrhizine，palmatine，berberine，aloe-emodin，rhein，emodin，chrysophanol，and physcion in Zuoyu’an San，respectively. To verify the reliability of QAMS metod results，the contents of 8 components of physcion were determined.

A total of 23 common peaks were calibrated in the fingerprint，and 8 components were identified by comparing with the mixed reference solution. The similarity between the samples and the control spectrum was between 0.952 and 0.994；CA divided 12 batches of Zuoyu’an San samples into 3 categories；PCA showed that there were certain differences in the chemical composition of different batches of Zuoyu’an San，and extracted 5 principal components that affected the quality evaluation of Zuoyu’an San；OPLS-DA screened out 13 potential marker components (VIP>1) among 23 common peaks that caused quality differences between different batches of Zuoyu’an San samples；There was no significant difference between the QAMS method calculated value and the ESM measured value.

The established HPLC fingerprint and multi-index component determination method was accurate and simple，and combined with chemometric methods，could provide reference for the quality control and evaluation of Zuoyu’an San.

To screen the suitable monitoring method applicable to oligotrophs and review the bioburden and microbial species of oligotrophic environments in pharmaceutical water systems and cleanrooms.

The culture conditions and detection methods suitable for microorganisms under oligotrophic conditions were optimized by comparing the counting results of microorganisms in laboratory pure water with R₂A and TSA media at different temperatures，media，and incubation times. In addition，monitoring of oligotrophs in pharmaceutical environments using both the traditional and oligotrophic assays were conducted，combining with the techniques of 16s rDNA sequencing and MALDI-TOF MS for multiphase microbial identification and analysis of the isolated microorganisms under oligotrophic conditions.

The colony counting methods，the type of culture media，and the incubation intervals significantly affected microbial enumeration. The isolation method using oligotrophic medium R₂A was more effective than the TSA medium in this study. The profiles of microorganisms isolated from the R₂A and TSA media were unique. The isolation rate of Gram-negative bacteria in the R₂A medium reached 37.0%，however，that of Gram-negative bacteria in the TSA medium was only 14.0%. In addition，several strains of potential pathogens initially isolated from the R₂A medium grew slowly in the TSA medium and were easily missed by the traditional monitoring method.

With the development of the pharmaceutical industry，the contamination proportion of human-associated Gram-positive cocci might gradually decrease，the oligotrophic culture method as a powerful supplement to traditional monitoring techniques can help to detect potential objectionable microorganism contamination risks at an early stage.

To study the dynamic changes of puerarin and icariin in plasma and hippocampus of mice，to observe the changes of depression-related protein expression in hippocampus，and to explore the pharmacokinetic changes of Shenge Bushen capsules (SBC) and its correlation with the changes of hippocampus-related protein expression.

Puerarin and icariin in plasma and hippocampus of normal mice were analyzed by UPLC-MS/MS-ABSCIEX QTRAP 5500 triple quadrupole series linear ion trap mass spectrometry method using Waters Acquity HSS T3 (50 mm×2.1 mm，1.8 μm) column with 0.05% formic acid water-acetonitrile-methanol (1:1) containing 0.05% formic acid as mobile phases gradient elution at a flow rate of 0.2 mL·min^-1 and electrospray ion source under negative ion model. The proteins in hippocampus were expressed by Western blot assay.

Puerarin and icariin were detected in plasma and hippocampus after the oral administration，including plasma puerarin t_1/2 2.45 h，icariin t_1/2 3.59 h，hippocampus puerarin t_1/2 4.37 h and icariin t_1/2 8.5 h. The plasma concentration of puerarin accounts for 27.3% and that of icariin accounts for 1.34% of the dosage taken. Puerarin in hippocampus accounts for 2.47% of puerarin absorbed into blood，while icariin in hippocampus accounts for 73.56% of icariin absorbed into blood. The expressions of restrictive silencing factor (NRSF)，brain-derived neurotrophic factor (BDNF) and its downstream protein tyrosine kinase B (TrkB)，solute carrier transporter 6a4 (SLC6A4)，glucocorticoid receptor (GR) and μ opioid receptor (MOR) in hippocampus were all up-regulated after SBC administration，in which icariin was negatively correlated with NRSF expression，puerarin was positively correlated with BDNF-TrkB and MOR，and GR had no obvious correlation with the proteins.

Puerarin and icariin can be absorbed into the blood and distributed in the hippocampus after oral administration of SBC in mice. Icariin was easier to pass through the blood-brain barrier and distribute in the hippocampus than puerarin. The expression of hippocampus-related proteins was related to the changes of puerarin and icariin concentrations，suggesting that the targets of the two components as well as SBC were related to these proteins. This study provides an important experimental basis for the pharmacokinetic study of SBC and also provides a material basis of its antidepressant effect.

To establish a quantitative model to in-line in situ determination of the water content of domperidone tablets particles in fluidized bed granulation drying process.

Using micro near infrared spectrometer，in-line collected near infrared（NIR） spectrum of domperidone tablets particles in granulation drying process，took sample at different drying time to acquire sample in different level of water content. The pretreatment method of first derivative（FD），multiplicative scatter correction (MSC) and Savitzky-Golay smoothing were selected. The modeling band was 1 100-1 600 nm，model was established by partial least square（PLS） method，and validation was executed including accuracy，precision，specificity，linearity and range，robustness.

The root mean square error of cross validation(RMSECV) was 0.079 7，the coefficient of determination(R²) was 0. 994 5，the root mean square error of prediction(RMSEP) was 0.092 3，the R² was 0.986 0. All validation results met predefined criteria.

It is feasible for using micro NIR spectrometer to in-line measure the water content of domperidone tablets particles which provides an experimental basis for the in-line application of process analysis technology in pharmaceutical industry.

To optimize the extraction process of Impatientis Balsaminae Caulis in the treatment of degenerative osteoarthritis based on network pharmacology，mixture weighting and response surface method.

Network pharmacology and LC-MS techniques were used to determine the active ingredients of Impatientis Balsaminae Caulis in the treatment of osteoarthritis，and they were taken as evaluation indexes. The extraction process of Impatientis Balsaminae Caulis was optimized by analytic hierarchy process（AHP）-criteria importance through intercriteria correlation(CRITIC) mixed weighting method and Box-Behnken response surface design.

Scopoletin，quercetin and kaempferol were the active ingredients in the treatment of osteoarthritis. The optimal extraction process was to add 5 times of 82% ethanol and reflux twice，35 min each time.

The treatment of osteoarthritis can be achieved by regulating target genes and related signaling pathways through various active components. The weight coefficient determined by AHP-CRITIC hybrid weighting method is objective and reasonable，and the optimized extraction process is stable and feasible.