Objective:To investigate the expression levels and clinical significance of miR-627 and miR-448 in colorectal cancer tissues.Methods:Ninety-eight patients with colorectal cancer admitted to Xi’an Jiaotong University Affiliated Red Cross Hospital from Apr. 2019 to Apr. 2021 were gathered. Colorectal cancer tissue and adjacent tissues were collected during surgery, and the expression levels of miR-627 and miR-448 were detected by qRT-PCR. According to postoperative follow-up, patients were separated into a good prognosis group and a poor prognosis group. Kaplan-Meier survival curve was applied to analyze the relationship between miR-627, miR-448 and the prognosis of colorectal cancer patients. ROC curve was plotted to analyze the predictive value of miR-627 and miR-448 for poor prognosis in colorectal cancer. The prognostic factors of colorectal cancer patients were analyzed using COX regression.Results:There was a difference in the expression levels of miR-627 and miR-448 between colorectal cancer tissue and adjacent tissues ( P<0.05). The expression of miR-627 and miR-448 in colorectal cancer tissue was related to clinical features (TNM stage, differentiation degree, lymph node metastasis, and depth of infiltration) ( P<0.05). The survival rate of patients with high expression of miR-627 was higher than that of patients with low expression ( χ2=10.050, P<0.05); the survival rate of patients with high expression of miR-448 was higher than that of patients with low expression ( χ2=9.033, P<0.05). The expression levels of miR-627 and miR-448 in the poor prognosis group were greatly lower than those in the good prognosis group ( P<0.05). According to the ROC curve, the AUC of miR-627 in predicting poor prognosis of colorectal cancer was 0.811, the AUC of miR-448 in predicting poor prognosis of colorectal cancer was 0.772, and the AUC of combination of the two in predicting poor prognosis of colorectal cancer was 0.859. The combination of the two was better than their individual predictions (Z combination vs. miR-627=2.538, Z combination vs. miR-448=2.572, P<0.05). Multivariate COX regression found that miR-627, miR-448, and clinical features (TNM stage, degree of differentiation, lymph node metastasis, and depth of infiltration) were risk factors affecting the prognosis of colorectal cancer patients ( P<0.05) . Conclusion:The expression levels of miR-627 and miR-448 in colorectal cancer tissues were greatly reduced. The combination of the two is related to the clinical characteristics and prognosis of patients, and can greatly improve the predictive value for prognosis of colorectal cancer patients.

Objective:To investigate the expression levels and clinical significance of miR-627 and miR-448 in colorectal cancer tissues.Methods:Ninety-eight patients with colorectal cancer admitted to Xi’an Jiaotong University Affiliated Red Cross Hospital from Apr. 2019 to Apr. 2021 were gathered. Colorectal cancer tissue and adjacent tissues were collected during surgery, and the expression levels of miR-627 and miR-448 were detected by qRT-PCR. According to postoperative follow-up, patients were separated into a good prognosis group and a poor prognosis group. Kaplan-Meier survival curve was applied to analyze the relationship between miR-627, miR-448 and the prognosis of colorectal cancer patients. ROC curve was plotted to analyze the predictive value of miR-627 and miR-448 for poor prognosis in colorectal cancer. The prognostic factors of colorectal cancer patients were analyzed using COX regression.Results:There was a difference in the expression levels of miR-627 and miR-448 between colorectal cancer tissue and adjacent tissues ( P<0.05). The expression of miR-627 and miR-448 in colorectal cancer tissue was related to clinical features (TNM stage, differentiation degree, lymph node metastasis, and depth of infiltration) ( P<0.05). The survival rate of patients with high expression of miR-627 was higher than that of patients with low expression ( χ2=10.050, P<0.05); the survival rate of patients with high expression of miR-448 was higher than that of patients with low expression ( χ2=9.033, P<0.05). The expression levels of miR-627 and miR-448 in the poor prognosis group were greatly lower than those in the good prognosis group ( P<0.05). According to the ROC curve, the AUC of miR-627 in predicting poor prognosis of colorectal cancer was 0.811, the AUC of miR-448 in predicting poor prognosis of colorectal cancer was 0.772, and the AUC of combination of the two in predicting poor prognosis of colorectal cancer was 0.859. The combination of the two was better than their individual predictions (Z combination vs. miR-627=2.538, Z combination vs. miR-448=2.572, P<0.05). Multivariate COX regression found that miR-627, miR-448, and clinical features (TNM stage, degree of differentiation, lymph node metastasis, and depth of infiltration) were risk factors affecting the prognosis of colorectal cancer patients ( P<0.05) . Conclusion:The expression levels of miR-627 and miR-448 in colorectal cancer tissues were greatly reduced. The combination of the two is related to the clinical characteristics and prognosis of patients, and can greatly improve the predictive value for prognosis of colorectal cancer patients.

Near infrared chemical imaging (NIR-CI) is an emerging technology for rapidly analyzing the critical quality attribute of Chinese materia medica (CMM). It integrates NIR spectroscopy with chemical imaging. In this paper, it provided a systematic introduction to NIR-CI, such as the core part of instrument, the reliability, transformation, analysis and application of high-dimensional data acquisition. In addition, current studies of NIR-CI application in pharmaceutical field were analyzed. Finally, future opportunities and challenges of NIR -CI applications in the quality control of CMM preparation were prospected.

This study was aimed to optimize the near infrared (NIR) variable selection method based on multivariate detection limit (MDL). Using Qing-Kai-Ling (QKL) injection as object, three variable selection methods (interval par-tial least-squares, iPLS; backward interval partial least squares, BiPLS; moving window interval partial least squares, mwPLS) were used to establish the PLS models of baicalin in QKL injection, respectively. The prediction ability of different variable selection method was compared. MDL of all models were calculated in contrast to the MDL value of full spectra PLS model, to select optimal variable selection method. The results showed that different variable selec-tion methods had different prediction ability. Among them, iPLS had the best performance which determination coef-ficient of prediction (Rpre2) and the root mean square errors of prediction (SEP) were 0.996 5 and 602.3 μg·mL-1, re-spectively. All MDLs of different variable selection methods were reduced compared with the full spectra PLS model. The value of iPLS was the lowest comes to be 1.19 μg·mL-1. The results above indicated that the best variable se-lection method for baicalin in QKL injection was iPLS. MDL theory took the error of calibration and validation set and the leverage of external sample into account, which can comprehensively evaluate model detection performance compared to the classic chemical indicator parameters. This method was particularly suitable for the variable selec-tion method optimization of NIR quantitative model of low concentration sample such as Chinese herbal medicine.

This article was aimed to study the different clinical characteristics using drug pair of Cassia twig and white peony root with the contents ratio of 1:1 and 1:2. Based on the different clinical treatment of drug pair of Cas-sia twig and white peony root, different compositional ingredients in ratio of 1:1 and 1:2 were illuminated by HPLC/MS method. The drug pair of Cassia twig and white peony roots in ratio of 1:1 and 1:2 and single herbs were ex-tracted for HPLC/MS analysis. A protocol was followed, including acetonitrile - 0.1% acetic acid with gradient elution, positive mode, 350℃ capillary temperature and 300℃ vaporization temperature. The results showed that Procyanidol B2 and 2-Hydroxy cinnamal dehyde can be extracted from single Cassia twig, but 2-Hydroxy cinna-mal dehyde cannot be detected in drug pair. It showed the contents of Procyanidol B2 in 1:1 ratio was more than 1:2 ratio. Simultaneously, Palbinone, paeoniflorin sulfonate, 1,2,3,6-Tetra-O-galloyl-β-D-glucose, Paeoniflorin, Pae-oniflorin isomers, Benzoylpaeo-niflorin, and Benzoyl Paeoniflorin isomers can also be dissolved in white peony root. In addition, the contents of 1,2,3,6-Tetra-O-galloyl-β-D-glucose, Paeoniflorin, Benzoylpaeo-niflorin, and Benzoyl Paeoniflorin isomers in 1:1 were more than 1:2. The contents of Palbinone, paeoniflorin sulfonate and Paeoniflorin isomers in 1:2 were more than 1:1. It was concluded that Procyanidol B2, 1,2,3,6-Tetra-O-galloyl-β-D-glucose, Paeoniflorin, Benzoylpaeo-niflorin and Benzoyl Paeoniflorin isomers in 1:1 were more than 1:2. The contents of Pal-binone, Paeoniflorin sulfonate and Paeoniflorin isomers in 1:2 were more than 1:1. It provided a scientific basis for traditional Chinese medicine treatment using rational drug pair.