Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

Objective:The development and application of end-of-life patient decision aids for elderly were systematically reviewed and analyzed in order to supply guidance for the design of localized patient decision aids in China.Methods:Using the Scoping Review Guidelines as a methodological framework, a systematic search was conducted across databases including China National Knowledge Infrastructure, Wanfang, China Biology Medicine, PubMed, Web of Science, Embase, Cochrane Library, CINAHL, and BIOSIS. The search period covered from the inception of these databases to October 31, 2023. Two professionally trained researchers were responsible for screening, extracting, and organizing the retrieved literature.Results:A total of 5 studies on decision aids were included. These primarily employed paper graphics, interactive web pages, or multimedia slides as formats. The content encompassed various aspects such as palliative care options along with their pros and cons, assisting patients in clarifying their personal values, encouraging patients to document their decision-making preferences, and initiating end-of-life conversations with family members. Age-friendly design strategies were adopted in 4 studies; efficacy was validated in 3 studies, and in two of these studies, significant improvements were observed in engagement of patients (or substitute decision-makers) in ACP and the consistency of decision preferences (both P< 0.05). Conclusions:End-of-life decision aids for elderly patients can improve decision-making outcomes to some extent, however, the form and quality standards of them need to be improved, and their long-term effect needs further research and verification. It is recommended that in the future, the needs for end-of-life decision-making should be properly assessed based on the health literacy level, and high-quality localized end-of-life decision aids should be developed and popularized.

Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

Objective:The development and application of end-of-life patient decision aids for elderly were systematically reviewed and analyzed in order to supply guidance for the design of localized patient decision aids in China.Methods:Using the Scoping Review Guidelines as a methodological framework, a systematic search was conducted across databases including China National Knowledge Infrastructure, Wanfang, China Biology Medicine, PubMed, Web of Science, Embase, Cochrane Library, CINAHL, and BIOSIS. The search period covered from the inception of these databases to October 31, 2023. Two professionally trained researchers were responsible for screening, extracting, and organizing the retrieved literature.Results:A total of 5 studies on decision aids were included. These primarily employed paper graphics, interactive web pages, or multimedia slides as formats. The content encompassed various aspects such as palliative care options along with their pros and cons, assisting patients in clarifying their personal values, encouraging patients to document their decision-making preferences, and initiating end-of-life conversations with family members. Age-friendly design strategies were adopted in 4 studies; efficacy was validated in 3 studies, and in two of these studies, significant improvements were observed in engagement of patients (or substitute decision-makers) in ACP and the consistency of decision preferences (both P< 0.05). Conclusions:End-of-life decision aids for elderly patients can improve decision-making outcomes to some extent, however, the form and quality standards of them need to be improved, and their long-term effect needs further research and verification. It is recommended that in the future, the needs for end-of-life decision-making should be properly assessed based on the health literacy level, and high-quality localized end-of-life decision aids should be developed and popularized.

Exosomes are a subpopulation of extracellular vesicles ranging in size from 30 to 150 nm. They contain a variety of biological molecules including proteins, lipids, and genetic materials by which they can act as mediators of cell-to-cell communication. Increasing studies on exosomes have elucidate the mechanism of communication between immune cells. Mast cells are found to release exosomes in both resting and activated states, but the quantity, contents and functions of the exosomes are significantly different in different states. Mast cell-derived exosomes are involved in the maturation and antigen presentation of dendritic cells, and mediate the activation of T lymphocytes and the polarization of macrophages. These results provide new insights into the role of exosomes in mast cell function and immune regulation.

With the accelerating of aging population in China, the long-term care demand of the elderly is increasing. In recent years, extended reality technology has shown great development potential in assisting elderly chronic nursing, rehabilitation nursing, psychological nursing, palliative care, nursing personnel training. This paper reviews the application status of extended reality technology in geriatric care at home and abroad, and puts forward the problems and countermeasures of extended reality technology applied in geriatric care, so as to provide reference for promoting the application of extended reality technology in geriatric care.

Objective:To investigate the regulatory effects of mitofusin 1 (MFN1) on lipopolysaccharide (LPS)-induced Raw264.7 mouse macrophages pyroptosis and to provide reference for further study on the prevention of inflammation and fibrosis caused by macrophage dysfunction.Methods:Raw264.7 mouse macrophages were cultured in vitro and used to construct a model of LPS-induced pyroptosis. CCK-8 staining, PI staining, LDH release assay and Western blot were used to verify the Raw264.7 pyroptosis induced by LPS. MFN1 expression was detected by Western blot. DCFH-DA probe was used to detect the synthesis of total reactive oxygen species (ROS); Mito-SOX was used to detect mitochondrial ROS; JC-1 mitochondrial membrane potential was detected by fluorescence probe to reflect mitochondrial damage. Based on Ubibrowser database, it was predicted that MFN1 could bind to a variety of E3 ubiquitin ligases. Then, immunofluorescence and co-immunoprecipitation (CO-IP) were used to analyze MFN1 ubiquitination. An overexpression plasmid for MFN1 was constructed and transfected into Raw264.7 cells to detect the changes in pyroptosis and mitochondrial function. Results:LPS could induce the pyroptosis of Raw264.7 cells and mitochondrial dysfunction. MFN1 expression was decreased after LPS stimulation. Ubiquitinated MFN1 was detected by CO-IP. Ubiquitination inhibitor MG-132 inhibited LPS-induced expression of pyroptosis-related proteins including NLRP3, Pro-caspase-1, Caspase-1, IL-1β and IL-18 and improved mitochondrial function. MFN1 overexpression relieved the mitochondrial dysfunction and pyroptosis of Raw264.7 cells induced by LPS.Conclusions:The ubiquitination of MFN1 induced by LPS was involved in mitochondrial dysfunction and macrophage pyroptosis, suggesting that MFN1 was a potential target for the treatment of macrophage-induced inflammation and related diseases.

Objective:To study the clinicopathological features, diagnosis, treatment and prognosis of patients with solid pseudopapillary neoplasm of the pancreas (SPN).Methods:From Jan 2008 to Dec 2017, 112 pathology confirmed SPN patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University were followed up. The clinicopathological characteristics and diagnosis were analyzed.Results:Most SPN patients were young women, the ratio of male to female is 1∶7. SPN patients have no typical clinical symptoms. The preoperative diagnostic accuracy of SPN was 57.14% with imaging examination. Pathological diagnosis depends mainly on immunohistochemical staining. All patients underwent surgical resection. Follow-up ranged from 4 to 123 months. The mean follow-up time was 49 months. All patients were doing well and no recurrence or metastasis was found.Conclusions:SPN is a rare tumor with low malignant potential. Surgical resection is effective.

OBJECTIVES: At present, the research on clear aligner of molar distalization mainly focuses on the upper jaw, while the research on mandibular molars is few.This study aims to evaluate the therapeutic effect of mandibular molars distalization with clear aligner via cone beam CT (CBCT) and Dolphin software. METHODS: Twenty cases of mandibular molars with clear aligner were included according to the inclusion and exclusion criteria. CBCT was taken before treatment (T0) and when the first molar was moved in place (T1). Dolphin software was used to measure the effectiveness of molar distalization. Three-dimensional changes in direction and the impact on the incisors and facial soft and hard tissues were evaluated. RESULTS: The effective rates of crown and root distalization of the second and first mandibular molars were 74%, 49%, and 71%, 47%, respectively. The second and first molars were both the distal buccal cusp with the largest distalization [(2.15 ± 0.91) mm and (1.85±1.09) mm], respectively, with significant difference between the T0 and T1 ( CONCLUSIONS Clear aligner can effectively move mandibular molars farther, the crown is more effective than the root, and it is tilted. The second mandibular molar is more effective than the first mandibular molar in its distant displacement and three-dimensional changes. Molar distalization causes minor changes in mandibular incisors and facial soft and hard tissues.
Cephalometry ; Maxilla ; Molar ; Orthodontic Appliances, Removable ; Tooth Movement Techniques

Objective: To summarize the clinicopathological features of cystic meningioangiomatosis. Methods: The clinical manifestations, imaging characteristics and pathological features of a case of cystic meningioangiomatosis were analysed, and the relevant literature was reviewed. Results: A 16-year-old male patient from Xuanwu Hospital, Capital Medical University had a history of epileptic seizures for more than three months. Magnetic resonance imaging (MRI) demonstrated a cystic mass in the left frontal lobe with long T₁ and long T₂ signals. Extensive resection of the upper frontal gyrus was performed. The excised lesion presented with a cystic shape after incision and contained colorless translucent liquid. Microscopic examination of the lesion showed that the number of blood vessels in the local cortex of the brain tissue was increased and the vessels appeared to be branching. The blood vessel walls were surrounded by proliferative spindle cells, which were arranged in concentric circles. Immunohistochemical study revealed that those spindle cells and the cyst wall were vimentin positive. These cells had a rich reticular fibers. Ten months after the operation, the general condition of the patient was good, no epileptic seiƶure was observed, and the follow-up MRI did not reveal any residual lesion. Conclusions MRI of cystic meningioangiomatosis shows cystic space occupying. Pathological findings show typical features of meningioangiomatosis and cystic space formation. Cystic meningioangiomatosis has good prognosis after surgical resection.