ObjectiveTo study the changing law of appearance color and physicochemical properties of Angelicae Sinensis Radix Carbonisata（ASRC） during the processing by color space method combined with statistical analysis， so as to provide reference for determining the processing endpoint and evaluating the quality of the decoction pieces. MethodsTaking processing time（4， 8， 12， 16 min） and temperature（180， 200， 220， 240 ℃） as factors， ASRC decoction pieces with different processing degrees were prepared in a completely randomized design. Then， the brightness value（L^*）， red-green value（a^*）， yellow-blue value（b^*）， and total chromaticity value （E^*ab） of the decoction pieces were determined by spectrophotometer， the color difference value（ΔE） was calculated， and the data of colorimetric values were analyzed by discriminant analysis. At the same time， the pH， charcoal adsorption， and contents of tannins， 5-hydroxymethylfurfural（5-HMF）， tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide of ASRC with different processing degrees were determined by pH meter， ultraviolet and visible spectrophotometry and ultra-high performance liquid chromatography（UPLC）. Principal component analysis（PCA） was used to analyze the data of physicochemical indexes， after determining the processing technology of ASRC， the canonical discriminant function was established to distinguish the decoction pieces with different processing degrees， and leave-one-out cross validation was conducted. Finally， Pearson correlation analysis was used to explore the correlation between various physicochemical indexes and chromaticity values. ResultsWith the prolongation of the processing time， L^*， a^*， b^* and E^*ab all showed a decreasing trend， and the established discriminant model based on color parameters was able to distinguish ASRC with different processing degrees. The pH showed an increasing trend with the prolongation of processing time， and the charcoal adsorption， and the contents of tannins， 5-HMF， and tryptophan all showed an increasing and then decreasing trend. Among them， the charcoal adsorption， contents of tannin and 5-HMF reached their maximum values successively after processing for 8-12 min. While the contents of chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide decreased with the increase of processing time， with a decrease of 60%-80% at 8 min of processing. Therefore， the optimal processing time should be determined to be 8-12 min. PCA could clearly distinguish ASRC with different processing degrees， while temperature had no significant effect on the processing degree. The 12 batches of process validation results（10 min， 180-240 ℃） showed that except for 3 batches identified as class Ⅱ light charcoal， all other batches were identified as class Ⅲ standard charcoal， and the chromaticity values of each batch of ASRC were within the reference range of class Ⅱ-Ⅲ sample chromaticity values. The correlation analysis showed that the chromaticity values were negatively correlated with pH and charcoal adsorption， and positively correlated with contents of tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H， and ligustilide. And both pH and charcoal adsorption were negatively correlated with the contents of the above components， but the charcoal adsorption was positively correlated with the content of 5-HMF. ConclusionThe chromaticity values and the contents of various physicochemical indicators of ASRC undergo significant changes with the prolongation of processing time， and there is a general correlation between chromaticity values and various physicochemical indicators. Based on the changes in color and physicochemical indicators， the optimal processing time for ASRC is determined to be 8-12 min. This study reveals the dynamic changes of the relevant indexes in the processing of ASRC， which can provide a reference for the discrimination of the processing degree and the quantitative study of the processing endpoint.

ObjectiveTo establish a method for the identification of Haliotidis Concha and its counterfeits， and to improve its quality evaluation method. MethodsA total of 17 batches of Haliotis discus hannai， 4 batches of H. ruber， 3 batches of H. laevigata， 3 batches of H. ovina， 3 batches of H. diversicolor， 3 batches of H. asinina， 3 batches of H. iris were collected. Ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS/MS） was used to analyze the hydrolysates of different original Haliotidis Concha and its counterfeits， and the potential characteristic ions of each species were screened by Venn diagram. UPLC-triple quadrupole tandem mass spectrometry（UPLC-QqQ-MS/MS） was used to validate the characteristic ions， and the specific detection method of the characteristic ions was established. ResultsA total of 1 182， 167， 47， 89， 104， 203， 424 potential characteristic ions were screened from H. discus hannai， H. ruber， H. laevigata， H. ovina， H. diversicolor， H. asinina and H. iris， respectively. And 9 characteristic ions were selected. The precision， stability and repeatability of the 9 characteristic ions in the established identification method met the requirements. Different original Haliotidis Concha and its counterfeits could detect their own characteristic ions， including m/z 631.83-886.48（double charge） and m/z 631.83-443.74（double charge） of H. discus hannai， m/z 699.28-232.11（double charge） and m/z 699.28-544.27（double charge） of H. ruber， m/z 535.76-752.37（double charge） and m/z 535.76-548.28（double charge） of H. laevigata， m/z 708.35-442.28（double charge） and m/z 708.35-215.14（double charge） of H. ovina， m/z 561.33-614.86（triple charge）， m/z 561.33-468.28（triple charge）， m/z 608.29-618.32（double charge） and m/z 608.29-390.21（double charge） of H. diversicolor， m/z 769.85-274.10（double charge）， m/z 769.85-532.75（double charge）， m/z 827.43-646.36（single charge）， m/z 827.43-257.12（single charge） of H. asinina， and m/z 468.24-576.29（double charge） and m/z 468.24-505.26（double charge） of H. iris. ConclusionIn this study， a total of 9 characteristic ions are screened from 6 kinds of original Haliotidis Concha and its counterfeits， and a specific identification method is established， which is helpful to solve the limitations of the existing quality evaluation methods of Haliotidis Concha， and provide a basis for the production， circulation and medication quality.

ObjectiveTo establish a method for the identification of Haliotidis Concha and its counterfeits， and to improve its quality evaluation method. MethodsA total of 17 batches of Haliotis discus hannai， 4 batches of H. ruber， 3 batches of H. laevigata， 3 batches of H. ovina， 3 batches of H. diversicolor， 3 batches of H. asinina， 3 batches of H. iris were collected. Ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS/MS） was used to analyze the hydrolysates of different original Haliotidis Concha and its counterfeits， and the potential characteristic ions of each species were screened by Venn diagram. UPLC-triple quadrupole tandem mass spectrometry（UPLC-QqQ-MS/MS） was used to validate the characteristic ions， and the specific detection method of the characteristic ions was established. ResultsA total of 1 182， 167， 47， 89， 104， 203， 424 potential characteristic ions were screened from H. discus hannai， H. ruber， H. laevigata， H. ovina， H. diversicolor， H. asinina and H. iris， respectively. And 9 characteristic ions were selected. The precision， stability and repeatability of the 9 characteristic ions in the established identification method met the requirements. Different original Haliotidis Concha and its counterfeits could detect their own characteristic ions， including m/z 631.83-886.48（double charge） and m/z 631.83-443.74（double charge） of H. discus hannai， m/z 699.28-232.11（double charge） and m/z 699.28-544.27（double charge） of H. ruber， m/z 535.76-752.37（double charge） and m/z 535.76-548.28（double charge） of H. laevigata， m/z 708.35-442.28（double charge） and m/z 708.35-215.14（double charge） of H. ovina， m/z 561.33-614.86（triple charge）， m/z 561.33-468.28（triple charge）， m/z 608.29-618.32（double charge） and m/z 608.29-390.21（double charge） of H. diversicolor， m/z 769.85-274.10（double charge）， m/z 769.85-532.75（double charge）， m/z 827.43-646.36（single charge）， m/z 827.43-257.12（single charge） of H. asinina， and m/z 468.24-576.29（double charge） and m/z 468.24-505.26（double charge） of H. iris. ConclusionIn this study， a total of 9 characteristic ions are screened from 6 kinds of original Haliotidis Concha and its counterfeits， and a specific identification method is established， which is helpful to solve the limitations of the existing quality evaluation methods of Haliotidis Concha， and provide a basis for the production， circulation and medication quality.

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

Objective:To explore the construction of abdominal aortocaval fistula (ACF) model in adenine-induced renal failure rats, and to provide a suitable animal model for subsequent mechanism and intervention researches.Methods:Adult female Sprague-Dawley rats (250-300 g) were fed with 0.75% adenine diet (renal failure group, n=60) and the same diet without adenine (control group, n=10) for 4 weeks, and the rats were randomly grouped by block randomization method with a ratio of 6∶1. Thirty rats in the renal failure group were randomly selected by block randomization method at a ratio of 1∶1 to undergo laparotomies to establish ACF models (renal failure+ACF group). The serum creatinine, blood urea nitrogen detection and Masson staining were used to evaluate the establishment of renal failure model. Small animal ultrasound imaging system was applied to verify the successful construction of the ACF model. After 6 weeks of ACF observation, blood samples were collected from the heart of rats, and ACF-vascular tissues were collected for pathological study (HE staining). Results:At 4 weeks of feeding, compared with the control group, serum creatinine [(63.8±23.5) μmol/L vs. (33.0±3.8) μmol/L, Z=3.651, P<0.001] and blood urea nitrogen [(13.1±6.9) mmol/L vs. (5.3±0.6) mmol/L, Z=3.254, P=0.001] in the renal failure group were both higher. Masson staining showed renal tubulointerstitial inflammatory cell infiltration, renal tubular epithelial cell atrophy, interstitial fibrosis and vascular injury. Five rats sacrificed after ACF surgeries, and the survival rate was 83.3%. Doppler ultrasound showed turbulent blood flow of arterial to venous shunt at the anastomosis of open ACF (23/25) in the renal failure+ACF group. HE staining showed typical eccentric neointimal hyperplasia in the outflow tract of ACF vein in the renal failure+ACF group. Conclusions:The adenine-induced ACF rat model is successfully constructed, and ACF shows typical eccentric neointimal hyperplasia. The ACF construction would provide a reliable animal model to study the mechanism and intervention of neointimal hyperplasia for autologous arteriovenous fistula.

Objective:To establish UPLC fingerprint method and 2 contents determination methods of Buddleja officinalis; To provide a reference for improving the quality control standard and evaluation of Buddleja officinalis from different habitats.Methods:UPLC method was used to establish the fingerprints of 17 batches of Buddleja officinalis. The similarity evaluation, clustering analysis, principal component analysis and orthogonal partial least squares discriminant analysis were used to compare the quality differences of Buddleja officinalis from different habitats. The contents of acteoside and linarin in Buddleja officinalis were determined.Results:There were 12 common peaks in UPLC fingerprints of Buddleja officinalis, six of which were identified as echinacoside, acteoside, cynaroside, isoacteoside, linarin, and apigenin. The fingerprint similarity of 17 batches of Buddleja officinalis was more than 0.9; Buddleja officinalis from different habitats were classified into 2 groups. Five differential markers were determined by OPLS-DA analysis. The order of significance was acteoside > peak 3 > echinacoside > isoacteoside > linarin. Edgeworthia chrysantha was identified by the method of fingerprint as counterfeit. The results of content determination showed that the content of Buddleja officinalis in Hubei and Sichuan was the high and stable.Conclusion:The method can effectively analyze the differences of Buddleja officinalis from different habitats, and provide reference for the quality control of Buddleja officinalis.

Objective To establish the ultra-high performance liquid chromatography(UPLC)chromatographic fingerprint of Notopterygii Rhizoma et Radix;To determine the contents of ferulic acid,nodakenin,ammijin,notopterol,isoimperatorin and volatile oil of Notopterygii Rhizoma et Radix from different producing areas;To provide reference for quality evaluation of Notopterygii Rhizoma et Radix.Methods Waters BEH C18 chromatographic column(2.1 mm×150 mm,1.7 μm)was used,with mobile phase acetonitrile-0.02%formic acid aqueous solution gradient elution,flow rate 0.25 mL/min,column temperature 25℃,detection wavelength 330 nm,injection volume 2 μL.UPLC fingerprints of 25 batches of Notopterygii Rhizoma et Radix were established,and the similarity analysis and chemometrics analysis were carried out.The contents of ferulic acid,nodakenin,ammijin,notopterol and isoimperatorin were determined simultaneously,and the contents of volatile oil was determined by steam distillation method.Results Totally 23 common fingerprint peaks were calibrated,11 known components were identified.According to the results of the cluster analysis and principal component analysis,25 batches of Notopterygii Rhizoma et Radix samples were divided into 3 categories,and the 6 potential differential components were screened out by orthogonal partial least squares-discriminant analysis(OPLS-DA).The results showed that the contents of notopterol and volatile oil from Sichuan Province were higher than those from Gansu Province and Qinghai Province.Conclusion The method established in the study is accurate and reliable,which can provide scientific basis and reference for the quality evaluation and control of Notopterygii Rhizoma et Radix.

Objective To analyze the detection rate of carbapenem-resistant Klebsiella pneumoniae(CRKP)in Guangdong Provincial Second Hospital of Traditional Chinese Medicine(the hospital)and analyze the main drug resistance genes and virulence genes of CRKP,so as to understand the molecular epidemiologi-cal mechanism of its infection strains.Methods The detection rate of CRKP infection in the hospital from 2020 to 2023 was retrospectively analyzed,and a total of 84 strains of CRKP were collected from July to De-cember 2022 in the hospital.The clinical data of the strains were collected,and the corresponding drug resist-ance genes and virulence genes were amplified by PCR.The modified carbapenem inactivation method(mCIM)was uesd to detect carbapenemase.Results The detection rates of CRKP in the Guangdong Provincial Second Hospital of Traditional Chinese Medicine from 2020 to 2023 were relatively high,and were higher than 46.00％.84 non-repeated CRKP strains were collected from July to December of 2022,and most samples were from respiratory tract,accounting for 55.95％.The patients were mainly from acupuncture and rehabilitation departments,accounting for 34.52％.Drug sensitivity tests showed that CRKP was highly resistant to various cephalosporin and extended spectrum beta lactam drugs,and only showed high sensitivity to tigecycline and polymyxin.The positive rate of mCIM test was 84.52％(71/84),and the other 15.48％results were neutral,which failed to determine whether they produced carbapenemase.A total of 73 strains were detected with car-bapenemase gene,accounting for 86.90％,involving 4 genotypes.The detection rates of blaKPC,blaNDM,blaIMP,and blaOXA-48 were 83.33％,2.38％,1.19％,and 1.19％,respectively.One of them carried both blaKPC and blaNDM genes,and multiple β-lactamases were detected.The detection rates of blaSHV,bla-TEM,blaCTX-M-9,and blaCTX-M-1 were 96.43％,78.57％,64.29％,and 2.38％,respectively.The detection rates of five virulence genes,blaiucA,blarmpA2,blairoB,blapeg-334,and blarmpA,were 42.86％,41.67％,27.38％,3.57％,and 2.38％,respectively.The proportion of strains carrying three or more virulence genes was 17.85％(15/84).Conclusion The detection rate of CRKP in the hospital is relatively high,and the drug resistance situation is serious,with Klebsiella pneumoniae carbapenemase(KPC)as the main drug resistance gene.A high proportion of Carbapenem-resistant hypervirulent Klebsiella pneumoniae(CR-hvKp)strains is found,and the infection prevention and control situation is not optimistic.It is necessary to further strengthen the hospital infection control measures and standardize the scientific and reasonable drug use.

Objective:To establish ultra performance liquid chromatography (UPLC) characteristic chromatogram of Pulsatilla chinensis; To provide reference for the origin identification and quality control of Pulsatilla chinensis. Methods:UPLC Method was adopted. The determination was performed on a column of Agilent SB C18 (2.1 mm×100 mm, 1.8 μm) . The mobile phase was acetonitrile-methanol (2:1) -0.1% phosphoric acid solution by fradient elution at a flow rate of 0.30ml/min. The column temperature was 30 ℃. The detection wavelength was 215 nm. The injection volume was 2 μl. The common counterfeit products and medicinal herbs of Pulsatilla chinensis from different areas were evaluated by comparison of characteristic chromatogram, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Results:There were 9 characteristic peaks in the characteristic chromatogram of Pulsatilla chinensis, and 8 common peaks were identified by high resolution mass spectrometry and comparison of reference materials. Through PCA analysis, it was possible to clearly distinguish the medicinal herbs of Pulsatilla chinensis from different areas. Combined with OPLS-DA analysis, it was found that peak 2, peak 3, peak 6 were the main markers of Pulsatilla chinensis from different producing areas. Conclusion:The established method has good specificity, repeatability and durability, and it can effectively distinguish the common counterfeits of Pulsatilla chinensis, and provide the basis of quality control and selection of origin for Pulsatilla chinensis.

Objective:To establish the ultra high performance liquid chromatography (UPLC) fingerprints of Mume flos at different flowering stages; To provide reference for the quality research of Mume flos.Methods:The fingerprints of Mume flos were established by UPLC method, and the common peaks were identified by high performance liquid chromatography high resolution mass spectrometry (LC-MS). Chemometrics analysis was carried out with the fingerprints' common peak area of plum blossom at different flowering stages as a variable. Semiquantitative analysis of changes in flavonoids and phenolic acids in Mume flos at different flowering stages was conduct using peak area calculation method.Results:Totally 31 common peaks were identified in the fingerprints of plum blossom medicinal materials at different flowering stages and 9 components were identified. Clustering analysis (HCA) and principal component analysis (PCA) both classified plum blossom medicinal herbs at different flowering stages into three categories. Among them, there were significant differences between the groups at the bud stage, blooming period, and final flowering period, while the differences between the groups at blooming period and final flowering period were relatively small. The orthogonal partial least squares discriminant analysis (OPLS-DA) screened 16 different components with VIP>1.0. The contents of phenolic acids in different flowering stages were as follows: bud stage>blooming period>final flowering period, while the contents of flavonoids were as follows: blooming period>final flowering period>bud stage.Conclusions:This method is simple and reliable, and can provide reference for the quality evaluation of plum blossom medicinal materials at different flowering stages.