PI3Kγ and PI3Kδ have important regulatory roles in the immune system, and targeting these two subtypes helps to reshape the tumor microenvironment. PI3Kγ and PI3Kδ are potential targets for tumor immunotherapy. In this study, a series of new pyrazolopyrimidine derivatives were designed and synthesized on the basis of our previously reported PI3K inhibitors, resulting in the discovery of compound 16l as a potent and selective PI3Kγ/δ dual inhibitor. Compound 16l demonstrated strong biochemical potencies against PI3Kγ and PI3Kδ with IC₅₀ values of 0.11 and 0.79 nmol·L^-1. In cell-based assays, it potently inhibited the PI3Kγ and PI3Kδ mediated Akt S473 phosphorylation with EC₅₀ values of 3 and 7 nmol·L^-1. In vivo, compound 16l exhibited acceptable pharmacokinetic properties in Sprague-Dawley (SD) rats and suppressed the tumor growth in a MC38 syngeneic mouse model. The animal experiments were approved by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences (approval number: DWLL-2000-06). In addition, no appreciable human ether-a-go-go-related gene (hERG) inhibition was observed for compound 16l even at 30 μmol·L^-1. These results suggested that compound 16l might be a potential research tool for studying the PI3Kγ/δ mediated signaling pathways.

Hepatohilar cholangiocarcinoma is a common malignant tumor of the biliary system,and radical surgery is one of the important treatment methods.Due to the narrow space at the hi-lum and the high rate of anatomical variation,radical surgery is challenging.By using medical imag-ing technology and 3D reconstruction,surgeons can accurately determine the stage and classifica-tion of hilar cholangiocarcinoma preoperatively.They can assess the tumor's resectability by Ac-cording to the bile duct separation limit points(U point,P point)and anticipate the impact of portal vein,bile duct,and arterial variations on the surgical plan,thereby improving the rate of radical re-section and reducing complication rates.

BACKGROUND: Clinical outcomes are poor if patients with acute heart failure (AHF) are discharged with residual congestion in the presence of renal dysfunction. However, there is no single indication to reflect the combined effects of the two related pathophysiological processes. We, therefore, proposed an indicator, congestion and renal index (CRI), and examined the associations between the CRI and one-year outcomes and the incremental prognostic value of CRI compared with the established scoring systems in a multicenter prospective cohort of AHF. METHODS: We enrolled AHF patients and calculated the ratio of thoracic fluid content index divided by estimated glomerular filtration rate before discharge, as CRI. Then we examined the associations between CRI and one-year outcomes. RESULTS: A total of 944 patients were included in the analysis (mean age 63.3 ± 13.8 years, 39.3% women). Compared with patients with CRI ≤ 0.59 mL/min per kΩ, those with CRI > 0.59 mL/min per kΩ had higher risks of cardiovascular death or HF hospitalization (HR = 1.56 [1.13-2.15]) and all-cause death or all-cause hospitalization (HR = 1.33 [1.01-1.74]). CRI had an incremental prognostic value compared with the established scoring system. CONCLUSIONS In patients with AHF, CRI is independently associated with the risk of death or hospitalization within one year, and improves the risk stratification of the established risk models.

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 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*

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 establish a deep learning algorithm that can accurately determine three-dimensional facial anatomical landmarks, multi-view stacked hourglass convolutional neural networks (MSH-CNN) and to construct three-dimensional facial midsagittal plane automatically based on MSH-CNN and weighted Procrustes analysis algorithm. METHODS: One hundred subjects with no obvious facial deformity were collected in our oral clinic. Three-dimensional facial data were scanned by three-dimensional facial scanner. Experts annotated twenty-one facial landmarks and midsagittal plane of each data. Eighty three-dimensional facial data were used as training set, to train the MSH-CNN in this study. The overview of MSH-CNN network architecture contained multi-view rendering and training the MSH-CNN network. The three-dimensional facial data were rendered from ninety-six views that were fed to MSH-CNN and the output was one heatmap per landmark. The result of the twenty-one landmarks was accurately placed on the three-dimensional facial data after a three-dimensional view ray voting process. The remaining twenty three-dimensional facial data were used as test set. The trained MSH-CNN automatically determined twenty-one three-dimensional facial anatomical landmarks of each case of data, and calculated the distance between each MSH-CNN landmark and the expert landmark, which was defined as position error. The midsagittal plane of the twenty subjects' could be automatically constructed, using the MSH-CNN and Procrustes analysis algorithm. To evaluate the effect of midsagittal plane by automatic method, the angle between the midsagittal plane constructed by the automatic method and the expert annotated plane was calculated, which was defined as angle error. RESULTS: For twenty subjects with no obvious facial deformity, the average angle error of the midsagittal plane constructed by MSH-CNN and weighted Procrustes analysis algorithm was 0.73°±0.50°, in which the average position error of the twenty-one facial landmarks automatically determined by MSH-CNN was (1.13±0.24) mm, the maximum position error of the orbital area was (1.31±0.54) mm, and the minimum position error of the nasal area was (0.79±0.36) mm. CONCLUSION This research combines deep learning algorithms and Procrustes analysis algorithms to realize the fully automated construction of the three-dimensional midsagittal plane, which initially achieves the construction effect of clinical experts. The obtained results constituted the basis for the independent intellectual property software development.
Algorithms ; Deep Learning ; Face ; Humans ; Neural Networks, Computer ; Software

OBJECTIVES: To investigate the clinical treatment outcomes and the changes of the outcomes over time in extremely preterm twins in Guangdong Province, China. METHODS: A retrospective analysis was performed for 269 pairs of extremely preterm twins with a gestational age of <28 weeks who were admitted to the department of neonatology in 26 grade A tertiary hospitals in Guangdong Province from January 2008 to December 2017. According to the admission time, they were divided into two groups: 2008-2012 and 2013-2017. Besides, each pair of twins was divided into the heavier infant and the lighter infant subgroups according to birth weight. The perinatal data of mothers and hospitalization data of neonates were collected. The survival rate of twins and the incidence rate of complications were compared between the 2008-2012 and 2013-2017 groups. RESULTS: Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of severe asphyxia and smaller head circumference at birth (P<0.05). The mortality rates of both of the twins, the heavier infant of the twins, and the lighter infant of the twins were lower in the 2013-2017 group compared with the 2008-2012 group (P<0.05). Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of pulmonary hemorrhage, patent ductus arteriosus (PDA), periventricular-intraventricular hemorrhage (P-IVH), and neonatal respiratory distress syndrome (NRDS) and a higher incidence rate of bronchopulmonary dysplasia (P<0.05). CONCLUSIONS There is a significant increase in the survival rate over time in extremely preterm twins with a gestational age of <28 weeks in the 26 grade A tertiary hospitals in Guangdong Province. The incidences of severe asphyxia, pulmonary hemorrhage, PDA, P-IVH, and NRDS decrease in both the heavier and lighter infants of the twins, but the incidence of bronchopulmonary dysplasia increases. With the improvement of diagnosis and treatment, the multidisciplinary collaboration between different fields of fetal medicine including prenatal diagnosis, obstetrics, and neonatology is needed in the future to jointly develop management strategies for twin pregnancy.
Bronchopulmonary Dysplasia/epidemiology* ; Female ; Gestational Age ; Humans ; Infant ; Infant, Extremely Premature ; Infant, Newborn ; Pregnancy ; Respiratory Distress Syndrome, Newborn/epidemiology* ; Retrospective Studies ; Treatment Outcome

Osteoarthritis (OA) is a common degenerative disease of the motor system with a high morbidity and disability rate. The pathogenesis of OA is not clear at present. Previous studies believe that the pathogenesis of OA is mainly related to trauma factors, while recent studies have shown that metabolic factors, including abnormal cholesterol metabolism, are also closely related to OA. The treatment of OA is mainly symptomatic treatment at the early stage and surgical treatment at the late stage, and there is no specific drug. Previously, BNTA, a small molecule drug with cartilage protective effects, has been shown to have a good effect on OA caused by trauma, but its effect on OA caused by high cholesterol remains unclear. In order to explore the therapeutic effect of BNTA on OA caused by high cholesterol and its mechanism, the OA model of rats was constructed by adopting high cholesterol diets, and paraffin sections of knee joints were taken for histological evaluation. Lipid accumulation in chondrocytes of rats was assessed by oil red O staining. The expression of genes and proteins related to anabolism, catabolism and cholesterol metabolism in chondrocytes was assessed by RT-qPCR, immunofluorescence and immunohistochemistry. The results showed that BNTA could alleviate OA pathological manifestations and improve the OARSI (Osteoarthritis Research Society International) score in the OA model of high cholesterol rats. In rat chondrocytes, BNTA can promote the expression of anabolism-related genes col2, sox9 and acan, inhibit the expression of catabolism-related genes mmp13 and adamts5, and improve the lipid accumulation caused by high cholesterol in rat chondrocytes. BNTA can up-regulate Insig1 expression in rat chondrocytes and the OA model of high cholesterol rats. This study confirmed that high cholesterol can aggravate OA in vivo and in vitro, and can increase lipid accumulation in rat chondrocytes. Taken together, BNTA can alleviate OA phenotypes induced by high cholesterol and improve abnormal lipid accumulation in chondrocytes, possibly by inhibiting cholesterol biosynthesis in cells by upregulating Insig1, thereby alleviating abnormal lipid accumulation.