[摘 要] 甲状腺癌是内分泌系统中最为常见的恶性肿瘤，近年来其发病率呈现出显著的上升趋势。乙酰化修饰作为一种重要的蛋白质翻译后修饰，参与调控各个类型甲状腺癌相关基因的转录表达、细胞周期进程及侵袭能力。组蛋白去乙酰化酶（HDAC）抑制剂在甲状腺癌治疗中显示出潜在的应用前景。本文通过调研近年来相关文献，系统回顾了乙酰化修饰在参与甲状腺癌发生发展过程中的生物学功能及其调控机制，进一步探讨HDAC抑制剂在临床治疗中的应用前景，为甲状腺癌的靶向治疗提供坚实的理论依据和提出可行的治疗策略。

Non-communicable diseases(NCDs),including cardiovascular diseases,cancer,metabolic diseases,and skeletal diseases,pose significant challenges to public health worldwide.The complex pathogenesis of these diseases is closely linked to oxidative stress and inflammatory damage.Nuclear factor erythroid 2-related factor 2(Nrf2),a critical transcription factor,plays an important role in regulating antioxidant and anti-inflammatory responses to protect the cells from oxidative damage and inflammation-mediated injury.Therefore,Nrf2-targeting therapies hold promise for preventing and treating NCDs.Quercetin(Que)is a widely available flavonoid that has significant antioxidant and anti-inflammatory properties.It modulates the Nrf2 signaling pathway to ameliorate oxidative stress and inflammation.Que modulates mitochondrial function,apoptosis,autophagy,and cell damage biomarkers to regulate oxidative stress and inflammation,highlighting its efficacy as a therapeutic agent against NCDs.Here,we discussed,for the first time,the close association between NCD pathogenesis and the Nrf2 signaling pathway,involved in neurodegenerative diseases(NDDs),cardiovascular disease,cancers,organ damage,and bone damage.Furthermore,we reviewed the availability,pharmacokinetics,pharmaceutics,and therapeutic applica-tions of Que in treating NCDs.In addition,we focused on the challenges and prospects for its clinical use.Que represents a promising candidate for the treatment of NCDs due to its Nrf2-targeting properties.

Objective To investigate the clinical phenotypes and genotypes of children with congenital fibrinogen disorder(CFD).Methods A retrospective analysis was conducted on the clinical data of 16 children with CFD.Polymerase chain reaction was used to amplify all exons and flanking sequences of the FGA,FGB,and FGG genes,and sequencing was performed to analyze mutation characteristics.Results Among the 16 children,there were 9 boys(56%)and 7 girls(44%),with a median age of 4 years at the time of attending the hospital.Among these children,9(56%)attended the hospital due to bleeding events,and 7(44%)were diagnosed based on preoperative examination.The children with bleeding events had a significantly lower fibrinogen activity than those without bleeding events(P<0.05).Genetic testing was conducted on 12 children and revealed a total of 12 mutations,among which there were 4 novel mutations,i.e.,c.80T>C and c.1368delC in the FGA gene and c.1007T>A and C.1053C>A in the FGG gene.There were 2 cases of congenital afibrinogenemia caused by null mutations of the FGA gene,with relatively severe bleeding symptoms.There were 7 cases of congenital dysfibrinogenemia mainly caused by heterozygous missense mutations of the FGG and FGA genes,and their clinical phenotypes ranged from asymptomatic phenotype to varying degrees of bleeding.Conclusions The clinical phenotypes of children with CFD are heterogeneous,and the severity of bleeding is associated with the level of fibrinogen activity,but there is a weak association between clinical phenotype and genotype.

Robotics ; Robotic Surgical Procedures ; Kidney Transplantation

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 explore an efficient and automatic method for determining the anatomical landmarks of three-dimensional(3D) mandibular data, and to preliminarily evaluate the performance of the method. METHODS: The CT data of 40 patients with normal craniofacial morphology were collected (among them, 30 cases were used to establish the 3D mandibular average model, and 10 cases were used as test datasets to validate the performance of this method in determining the mandibular landmarks), and the 3D mandibular data were reconstructed in Mimics software. Among the 40 cases of mandibular data after the 3D reconstruction, 30 cases that were more similar to the mean value of Chinese mandibular features were selected, and the size of the mandibular data of 30 cases was normalized based on the Procrustes analysis algorithm in MATLAB software. Then, in the Geomagic Wrap software, the 3D mandibular average shape model of the above 30 mandibular data was constructed. Through symmetry processing, curvature sampling, index marking and other processing procedures, a 3D mandible structured template with 18 996 semi-landmarks and 19 indexed mandibular anatomical landmarks were constructed. The open source non-rigid registration algorithm program Meshmonk was used to match the 3D mandible template constructed above with the tested patient's 3D mandible data through non-rigid deformation, and 19 anatomical landmark positions of the patient's 3D mandible data were obtained. The accuracy of the research method was evaluated by comparing the distance error of the landmarks manually marked by stomatological experts with the landmarks marked by the method of this research. RESULTS: The method of this study was applied to the data of 10 patients with normal mandibular morphology. The average distance error of 19 landmarks was 1.42 mm, of which the minimum errors were the apex of the coracoid process [right: (1.01±0.44) mm; left: (0.56±0.14) mm] and maximum errors were the anterior edge of the lowest point of anterior ramus [right: (2.52±0.95) mm; left: (2.57±1.10) mm], the average distance error of the midline landmarks was (1.15±0.60) mm, and the average distance error of the bilateral landmarks was (1.51±0.67) mm. CONCLUSION The automatic determination method of 3D mandibular anatomical landmarks based on 3D mandibular average shape model and non-rigid registration algorithm established in this study can effectively improve the efficiency of automatic labeling of 3D mandibular data features. The automatic determination of anatomical landmarks can basically meet the needs of oral clinical applications, and the labeling effect of deformed mandible data needs to be further tested.
Humans ; Imaging, Three-Dimensional/methods* ; Mandible/diagnostic imaging* ; Software ; Algorithms ; Anatomic Landmarks/anatomy & histology*

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.

Objective: To explore a method for digitally designing and fabricating a sequential tooth-sectioning guide that can assist in the extraction of mandibular horizontal impacted third molars, preliminarily evaluate its feasibility and provide a reference for clinical application. Methods: Twenty patients with mandibular low level impacted third molars who visited the Department of General Dentistry, Peking University School and Hospital of Stomatology from March 2021 to January 2022 were selected. Cone-beam CT showed direct contact between the roots and mandibular canal, and full range impressions of the patients' intraoral teeth were taken and optical scans of the dental model were performed. The patients' cone-beam CT data and optical scan data were reconstructed in three dimensions, anatomical structure extraction, registration fusion, and the design of the structure of the guide (including crown-sectioning guide and root-sectioning guide) by Mimics 24.0, Geomagic Wrap 2021, and Magics 21.0 software, and then the titanium guide was three dimension printed, and the guide was tried on the dental model. After confirmation, the guide was used to assist the dentist in the operation. We observed whether the guide was in place, the number of tooth splitting, the matching of tooth splitting with the preoperative design, the operation time, and whether there were any complications. Results: In this study, 20 sectioning guides were successfully printed, all of them were well fitted in the patients' mouth, the average number of section was 3.4 times, the tooth parts was better matched with the preoperative design, and the average operative time of the guides was (29.2±9.8) minutes without complications such as perforation of the bone cortex. Conclusions: The use of sequential sectioning guides to assist in the extraction of mandibular impacted third molars was initially validated to accurately replicate the preoperative sectioning design, and is expected to provide a digital solution to improve surgical precision and ensure safety. Further studies with larger sample sizes are needed to evaluate its accuracy and safety.

Objective: To explore an automatic landmarking method for anatomical landmarks in the three-dimensional (3D) data of the maxillary complex and preliminarily evaluate its reproducibility and accuracy. Methods: From June 2021 to December 2022, spiral CT data of 31 patients with relatively normal craniofacial morphology were selected from those who visited the Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology. The sample included 15 males and 16 females, with the age of (33.3±8.3) years. The maxillary complex was reconstructed in 3D using Mimics software, and the resulting 3D data of the maxillary complex was mesh-refined using Geomagic software. Two attending physicians and one associate chief physician manually landmarked the 31 maxillary complex datasets, determining 24 anatomical landmarks. The average values of the three expert landmarking results were used as the expert-defined landmarks. One case that conformed to the average 3D morphological characteristics of healthy individuals' craniofacial bones was selected as the template data, while the remaining 30 cases were used as target data. The open-source MeshMonk program (a non-rigid registration algorithm) was used to perform an initial alignment of the template and target data based on 4 landmarks (nasion, left and right zygomatic arch prominence, and anterior nasal spine). The template data was then deformed to the shape of the target data using a non-rigid registration algorithm, resulting in the deformed template data. Based on the unchanged index property of homonymous landmarks before and after deformation of the template data, the coordinates of each landmark in the deformed template data were automatically retrieved as the automatic landmarking coordinates of the homonymous landmarks in the target data, thus completing the automatic landmarking process. The automatic landmarking process for the 30 target data was repeated three times. The root-mean-square distance (RMSD) of the dense corresponding point pairs (approximately 25 000 pairs) between the deformed template data and the target data was calculated as the deformation error of the non-rigid registration algorithm, and the intra-class correlation coefficient (ICC) of the deformation error in the three repetitions was analyzed. The linear distances between the automatic landmarking results and the expert-defined landmarks for the 24 anatomical landmarks were calculated as the automatic landmarking errors, and the ICC values of the 3D coordinates in the three automatic landmarking repetitions were analyzed. Results: The average three-dimensional deviation (RMSD) between the deformed template data and the corresponding target data for the 30 cases was (0.70±0.09) mm, with an ICC value of 1.00 for the deformation error in the three repetitions of the non-rigid registration algorithm. The average automatic landmarking error for the 24 anatomical landmarks was (1.86±0.30) mm, with the smallest error at the anterior nasal spine (0.65±0.24) mm and the largest error at the left oribital (3.27±2.28) mm. The ICC values for the 3D coordinates in the three automatic landmarking repetitions were all 1.00. Conclusions: This study established an automatic landmarking method for three-dimensional data of the maxillary complex based on a non-rigid registration algorithm. The accuracy and repeatability of this method for landmarking normal maxillary complex 3D data were relatively good.
Male ; Female ; Humans ; Adult ; Imaging, Three-Dimensional/methods* ; Reproducibility of Results ; Algorithms ; Software ; Tomography, Spiral Computed ; Anatomic Landmarks/anatomy & histology*