With the development of economic globalization, "internationalization" has become the key word in the national economic development strategy. Chinese materia medica (CMM) is the treasure of ancient Chinese science, and now has entered the era of international development. CMM compound is an important part of CMM, and patent protection is an important guarantee for the internationalization of Chinese medicine products. This paper explores the factors influencing the international influence of CMM from the perspective of patents; Besides, this paper is based on the CMM listed companies' patents at home and abroad as the research object, establish the evaluation index of the international influence by combining the number of foreign applicants' patents that cite it and the number of citing patents' family number. Construct the patent index system to evaluate the international influence of patents, and explore the factors influencing the international influence of CMM patent by establishing count models. The empirical study found that increasing R&D team size, absorbing large areas of technology and more scientific literatures can enhance the international influence of CMM patent; Patents that protect effective sites, effective ingredients, and quality control/inspection methods can generate more profound international influence. At last, we put forward some suggestions to improve the international influence of CMM according to the results of empirical analysis.

OBJECTIVE: To evaluate the implications of the prognostic nutrition index (PNI) in non-metastatic renal cell carcinoma (RCC) patients treated with surgery and to compare it with other hematological biomarkers, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and systemic immune inflammation index (SII). METHODS: A cohort of 328 non-metastatic RCC patients who received surgical treatment between 2010 and 2012 at Peking University First Hospital was analyzed retrospectively. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values of the hematological biomarkers. The Youden index was maximum for PNI was value of 47.3. So we divided the patients into two groups (PNI≤ 47. 3 and >47. 3) for further analysis. Categorical variables [age, gender, body mass index (BMI), surgery type, histological subtype, necrosis, pathological T stage and tumor grade] were compared using the Chi-square test and Student' s t test. The association of the biomarkers with overall survival (OS) and disease-free survival (DFS) was analyzed using Kaplan-Meier methods with log-rank test, followed by multivariate Cox proportional hazards model. RESULTS: According to the maximum Youden index of ROC curve, the best cut-off value of PNI is 47. 3. Low level of PNI was significantly associated with older age, lower BMI and higher tumor pathological T stage (P < 0.05). Kaplan-Meier univariate analysis showed that lower PNI was significantly correlated with poor OS and DFS (P < 0.05). In addition, older age, lower BMI, tumor necrosis, higher tumor pathological T stage and Fuhrman grade were significantly correlated with poor OS (P < 0.05). Cox multivariate analysis showed that among the four hematological indexes, only PNI was an independent factor significantly associated with OS, whether as a continuous variable (HR=0.9, 95%CI=0.828-0.978, P=0.013) or a classified variable (HR=2.397, 95%CI=1.061-5.418, P=0.036). CONCLUSION Low PNI was a significant predictor for advanced pathological T stage, decreased OS, or DFS in non-metastatic RCC patients treated with surgery. In addition, PNI was superior to the other hematological biomar-kers as a useful tool for predicting prognosis of RCC in our study. It should be externally validated in future research before the PNI can be used widely as a predictor of RCC patients undergoing nephrectomy.
Humans ; Prognosis ; Nutrition Assessment ; Carcinoma, Renal Cell/surgery* ; Retrospective Studies ; Biomarkers ; Kidney Neoplasms/pathology*

Objective: To investigate the mechanism of signal transducer and activator of transcription 3 (STAT3) and cancer associated fibroblasts (CAF) jointly generate chemo-resistance in epithelial-ovarian cancer and their effect on prognosis. Methods: A total of 119 patients with high-grade ovarian serous cancer who received surgery in Cancer Hospital of Chinese Academy of Medical Sciences from September 2009 to October 2017 were collected. The clinico-pathological data and follow-up data were complete. Multivariate Cox regression model was used to analyze the prognostic factors. Ovarian cancer tissue chips of patients in our hospital were prepared. EnVision two-step method immunohistochemistry was used to detect the protein expression levels of STAT3, the specific markers of CAF activation, fibroblast activating protein (FAP), and type Ⅰ collagen (COL1A1) secreted by CAF. The relationship between the expression of STAT3, FAP, COL1A1 protein and drug resistance and prognosis of ovarian cancer patients was analyzed, and the correlation between the expression of three proteins was analyzed. These results were verified through the gene expression and prognostic information of human ovarian cancer tissues collected in the GSE26712 dataset of gene expression omnibus (GEO) database. Results: (1) Multivariate Cox regression model analysis showed that chemotherapy resistance was an independent risk factor for overall survival (OS) of ovarian cancer (P<0.001). (2) The expression levels of STAT3, FAP, and COL1A1 proteins in chemotherapy resistant patients were significantly higher than those in chemotherapy sensitive patients (all P<0.05). Patients with high expression of STAT3, FAP, and COL1A1 had significantly shorter OS than those with low expression (all P<0.05). According to the human ovarian cancer GSE26712 dataset of GEO database, patients with high expression of STAT3, FAP, and COL1A1 also showed shorter OS than patients with low expression (all P<0.05), the verification results were consistent with the detection results of ovarian cancer patients in our hospital. (3) Correlation analysis showed that the protein level of STAT3 was positively correlated with FAP and COL1A1 in our hospital's ovarian cancer tissue chips (r=0.47, P<0.001; r=0.30, P=0.006), the analysis of GEO database GSE26712 dataset showed that the expression of STAT3 gene and FAP, COL1A1 gene were also significantly positively correlated (r=0.31, P<0.001; r=0.52, P<0.001). Conclusion: STAT3 and CAF could promote chemotherapy resistance of ovarian cancer and lead to poor prognosis.
Female ; Humans ; Cancer-Associated Fibroblasts/pathology* ; Carcinoma, Ovarian Epithelial ; Ovarian Neoplasms/pathology* ; Prognosis ; STAT3 Transcription Factor/metabolism* ; Drug Resistance, Neoplasm

Objective: To provide a new solution for the digital design of nasal prostheses, this study explores the three-dimensional (3D) facial morphology completion method for external nasal defects based on the non-rigid registration process of 3D face template. Methods: A total of 20 male patients with tooth defect and dentition defect who visited the Department of Prosthodontics, Peking University School and Hospital of Stomatology from June to December 2022 were selected, age 18-45 years old. The original 3D facial data of patients were collected, and the 3D facial data of the external nose defect was constructed in Geomagic Wrap 2021 software. Using the structured 3D face template data constructed in the previous research of the research group, the 3D face template was deformed and registered to the 3D facial data of external nose defect (based on the morphology of non-defective area) by non-rigid registration algorithm (MeshMonk program), and the personalized deformed data of the 3D face template was obtained, as the complemented facial 3D data. Based on the defect boundary of the 3D facial data of the external nose defect, the complemented external nose 3D data can be cut out from the complemented facial 3D data. Then the nasofacial angle and nasolabial angle of the complemented facial 3D data and the original 3D facial data was compared and analyzed, the ratio between the nose length and mid-face height, nose width and medial canthal distance of the complemented facial 3D data was measured, the edge fit between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was evaluated, and the morphological difference of the nose between the complemented external nose 3D data and the original 3D facial data was analyzed. Results: There was no significant statistically difference (t=-0.23, P=0.823; Z=-1.72, P=0.086) in the nasofacial angle (28.2°±2.9°, 28.4°±3.5° respectively) and nasolabial angle [95.4°(19.2°), 99.9°(9.5°) respectively] between the 20 original 3D facial data and the complemented facial 3D data. The value of the ratio of nose length to mid-face height in the complemented facial 3D data was 0.63±0.03, and the value of the ratio of nose width to medial canthal distance was 1.07±0.08. The curve deviation (root mean square value) between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was (0.37±0.09) mm, the maximum deviation was (1.14±0.32) mm, and the proportion of the curve deviation value within±1 mm was (97±3)%. The distance of corresponding nose landmarks between the complemented facial 3D data and the original 3D facial data were respectively, Nasion: [1.52(1.92)] mm; Pronasale: (3.27±1.21) mm; Subnasale: (1.99±1.09) mm; Right Alare: (2.64±1.34) mm; Left Alare: (2.42± 1.38) mm. Conclusions: The method of 3D facial morphology completion of external nose defect proposed in this study has good feasibility. The constructed complemented external nose 3D data has good facial coordination and edge fit, and the morphology is close to the nose morphology of the original 3D facial data.