Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

Aim To anticipate the mechanism of zuka- mu granules (ZKMG) in the treatment of bronchial asthma, and to confirm the projected outcomes through in vivo tests via using network pharmacology and molecular docking technology. Methods The database was examined for ZKMG targets, active substances, and prospective targets for bronchial asthma. The protein protein interaction network diagram (PPI) and the medication component target network were created using ZKMG and the intersection targets of bronchial asthma. The Kyoto Encyclopedia of Genes and Genomics (KEGG) and gene ontology (GO) were used for enrichment analysis, and network pharmacology findings were used for molecular docking, ovalbumin (OVA) intraperitoneal injection was used to create a bronchial asthma model, and in vivo tests were used to confirm how ZKMG affected bronchial asthma. Results There were 176 key targets for ZKMG's treatment of bronchial asthma, most of which involved biological processes like signal transduction, negative regulation of apoptotic processes, and angiogenesis. ZKMG contained 194 potentially active components, including quercetin, kaempferol, luteolin, and other important components. Via signaling pathways such TNF, vascular endothelial growth factor A (VEGFA), cancer pathway, and MAPK, they had therapeutic effects on bronchial asthma. Conclusion Key components had strong binding activity with appropriate targets, according to molecular docking data. In vivo tests showed that ZKMG could reduce p-p38, p-ERKl/2, and p-I

Objective To investigate the accuracy and application value of the Tada formula in evalua-ting the meningioma volume based on 3D reconstruction technology.Methods The thin-slice magnetic reso-nance images of 297 patients with meningioma treated in the neurosurgery department of 940 Hospital of PLA Joint logistics Support Force from January 2014 to May 2022 were retrospectively analyzed.The meningioma volume was evaluated by the Tada formula method and three-dimensional reconstruction method respectively.The accuracy of the evaluation of meningeal tumor volume by the Tada formula was analyzed by grouping sta-tistics.Results In the whole sample and the concentrated sample,the obtained meningioma total volumes had no statistical difference between the two methods(P＞0.05),the Spearman correlation coefficients were 0.995 and 0.993 respectively,and the intragroup correlation coefficients(ICC)were 0.992 and 0.989,respec-tively.In the Bland-Altman plot,most of the data points were within the limit of uniformity.Compared with different groups,the Tada formula had a slightly lower accuracy in the volume assessment of meningiomas with higher degree of irregularity,and a better accuracy in the volume assessment of supratentorial meningio-mas than subtentorial meningiomas.Conclusion The Tada formula could accurately evaluate the volume of meningioma,and it could be used as a preliminary method to evaluate meningioma volume in clinic

Objective To evaluate the characteristics of different antigen-specific T cell immune responses to severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)after inoculation with 2 doses of SARS-CoV-2 inactivated vaccine for 12 months.Methods Fifteen healthy adults were enrolled in this study and blood samples collected at 12 months after receiving two doses of SARS-CoV-2 inactivated vaccine.The level and phenotypic characteristics of SARS-CoV-2 antigen-specific T lymphocytes were detected by activation-induced markers(AIM)based on polychromatic flow cytometry.Results After 12 months of inoculation with 2 doses of SARS-CoV-2 inactivated vaccine,more than 90%of adults had detectable Spike and Non-spike antigen-specific CD4+ T cells immune responses(Spike:14/15,P=0.0001;Non-spike:15/15,P<0.0001).80%of adults had detectable Spike and Non-spike antigen-specific CD8+ T cells immune responses(Spike:12/15,P=0.0463;Non-spike:12/15,P=0.0806).Antigen-specific CD4+ T cells induced by SARS-CoV-2 inactivated vaccination after 12 months were composed of predominantly central memory(CM)and effector memory 1(EM1)cells.On the other hand,in terms of helper subsets,antigen-specific CD4+ T cells mainly showed T helper 1/17(Th1/17)and T helper 2(Th2)phenotypes.Conclusions SARS-CoV-2 inactivated vaccination generates durable and extensive antigen-specific CD4+ T cell memory responses,which may be the key factor for the low proportion of severe coronavirus disease 2019(COVID-19)infection in China.

Objective To analyze the application value of uterine artery flow and cerebral placental rate(CPR)in diagnosing fetal growth restriction(FGR).Methods A total of 114 pregnant women with clinically diagnosed late-onset FGR who were hospitalized in Jiangxi Maternal and Child Health Hospital from January 2021 to June 2022 were assigned to study group,and 122 pregnant women with normal intrauterine development were assigned to control group.The blood flow parameters of uterine artery(UtA),umbilical artery(UA)and middle cerebral artery(MCA)in two groups were determined by ultrasound,and CPR in two groups was calculated.The blood flow difference and pregnancy outcome of two groups were compared.Receiver operating characteristic(ROC)curve was used to analyze the application value of UtA and CPR alone and combined in the clinical diagnosis of FGR.Results The UtA resistance index(RI)of pregnant women in study group was higher than that of control group,the fetal UA blood flow parameter was higher than that of control group,the MCA blood flow parameter and the CPR value were both lower than those of control group,the differences were statistically significant(P<0.05).The birth weight and 1min Apgar score of study group were lower than those of control group(P<0.001).In addition,the incidence of emergency cesarean section operation,premature delivery and neonates transferred to neonatal intensive care unit(NICU)due to various complications in study group were significantly higher than those in control group(P<0.05).ROC curve showed that in predicting FGR,the area under the curve(AUC)of UtA-RI was 0.82(95%CI:0.77-0.88).The predictive efficiency of CPR was 0.75(95%CI:0.69-0.81).The combination of UtA-RI and CPR parameters had the highest efficiency in predicting FGR,with an AUC of 0.92(95%CI:0.89-0.95).Conclusion CPR combined with UtA-RI monitoring has clinical application value for early detection of FGR,guiding intervention,and improving adverse perinatal outcomes.

ObjectiveIt was reported that the transthyretin (TTR) has a neuroprotective effect on Alzheimer’s disease (AD), which is manifested by the ability of TTR to inhibit the pathological aggregation of amyloid beta protein (Aβ). In this work, we investigated the mechanism of the interactions between TTR and Aβ at the molecular level to reveal the neuroprotective effect of TTR on AD. MethodsProtein-protein docking was used to explore the models of interaction between different structural forms of TTR and Aβ, and molecular dynamics simulation was further applied to investigate the dynamic process of the interaction between the two. ResultsBoth TTR tetramer and monomer can interact with Aβ monomer, and the thyroxine-binding channel of TTR tetramer is the main binding site of Aβ monomer. In addition, the EF helix and EF loop of TTR tetramer were also able to bind Aβ monomer. When the TTR tetramer dissociates, the hydrophobic site of the internal TTR monomer is exposed, which has a strong affinity for Aβ monomer. For the interaction between Aβ aggregates and TTR, a higher degree of aggregation can be formed between TTR monomer and Aβ aggregates due to the β-sheet-rich property of TTR monomer and Aβ aggregates, which may therefore reduce the cytotoxicity of Aβ aggregates. ConclusionBoth TTR tetramer and monomer can inhibit Aβ aggregation by “sequestering” Aβ monomer, while TTR monomer can reduce the cytotoxicity of Aβ aggregates by forming large co-aggregation with Aβ aggregates. This work can provide an important theoretical basis for the design and discovery of anti-AD drugs based on the neuroprotective effects of TTR.

This paper outlines the common aspects of constructing integrated urban medical groups,focusing on governance,organizational restructuring,operational modes,and mechanism synergy.It then delves into the challenges in China's group construction,highlighting issues with power-responsibility alignment,capacity evolution,incentive alignment,and performance evaluation.Finally,the paper suggests strategies to enhance China's compact urban medical groups,focusing on governance reform,capacity building,benefit integration,and performance evaluation.

Objective:To investigate the risk factors of pleural effusion after spinal separation surgery for patients with spinal metastatic tumors.Methods:A total of 427 patients with spinal metastatic tumors from January 2014 to January 2022 in the Second Affiliated Hospital of Zhejiang University School of Medicine were retrospectively analyzed. There were 252 males and 175 females, with an average age of 59±12 years (range, 15-87 years). All patients underwent separation surgery. Based on the chest CT within 1 month after surgery, the volume of pleural effusion was measured individually by reconstruction software. Pleural effusion was defined as small volume (0-500 ml), moderate volume (500-1 000 ml), and large volume (above 1 000 ml). Baseline data and perioperative clinical outcomes were compared between the groups, and indicators with statistically significant differences were included in a binary logistic regression analysis to determine the independent risk factors for the development of pleural effusion after isolation of spinal metastatic cancer. Receiver operating characteristic (ROC) curves were conducted to calculate the area under the curve (AUC) for each independent risk factor.Results:All patients successfully completed the operation. Among the 427 patients, there were 35 cases of large pleural effusion, 42 cases of moderate pleural effusion, and 350 cases of small pleural effusion. There were significant differences in tumor size (χ 2=9.485, P=0.013), intraoperative blood loss ( Z=-2.503, P=0.011), blood transfusion ( Z=-2.983, P=0.003), preoperative total protein ( Z=2.681, P=0.007), preoperative albumin ( Z=1.720, P= 0.085), postoperative hemoglobin ( t=2.950, P=0.008), postoperative total protein ( Z=4.192, P<0.001), and postoperative albumin ( t=2.268, P=0.032) in the large pleural effusion group versus the small and moderate pleural effusion group. Logistic regression analysis showed that decreased preoperative albumin ( OR=0.89, P=0.045) and metastases located in the thoracic spine ( OR=4.01, P=0.039) were independent risk factors for the occurrence of large pleural effusion after separation surgery. The ROC curve showed that the AUC and 95% CI for preoperative albumin, lesion location, and the combined model were 0.637 (0.54, 0.74), 0.421 (0.36, 0.48), and 0.883 (0.81, 0.92). The combined predictive model showed good predictive value. Conclusion:The volume of pleural effusion can be measured individually and quantitatively based on chest CT. Decreased preoperative albumin and metastases located in the thoracic spine are independent risk factors for the occurrence of large pleural effusion after separation surgery. The combined prediction of the two factors has better predictive efficacy.

Phosphatase and tensin-homolog deleted on chromosome 10 (PTEN) is an important cancer suppressor gene. Its pathogenic mutation leads to PTEN hamartoma tumor syndrome (PHTS), a rare syndrome also known as Cowden syndrome, which is relevant to early-onset hereditary breast cancer (BC). In this paper, we report three patients with unilateral multicentric BC and synchronous and metachronous bilateral BC who harbored PTEN gene mutations, and summarize the clinical manifestations, pathological characteristics, diagnosis, treatment and follow-up outcomes to provide reference for management of PTEN gene mutation-related BC among the Cowden syndrome population.

Objective This study aims at establishing a teaching catalog and content for breast rare dis-eases and developing the syllabus for the breast rare disease using integrated multimodality of case-/problem-/resource-based learning(CBL+PBL+RBL).Methods By conducting bibliometrics co-occurrence analysis,we collected 6291 articles on breast rare disease published from January,1975 to June,2024.Additionally,we re-trieved the Textbook on Rare Diseases,the Catalog of Chinese Rare Disease,and Second Batch of Rare Dis-ease Catalog and then decided the teaching content.Results From 16,387 keywords,1000(6.1％)keywords were identified through co-occurrence analysis,including 50(0.3％)candidate diseases.These were classified into three categories:rare primary breast diseases,rare genetic mutation-related diseases associated with breast cancer,and rare systemic multi-system diseases involving the breast.From the candidate list,20(0.1％)rare primary breast diseases were further selected for their notable clinical teaching significance,and significant multi-systemic diseases affecting the breast,whether related to gene mutations or not.Teaching plans were draf-ted using a diversified parallel teaching approaches,taking into account the characteristics of different diseases and the focus of different teaching methods.Conclusions This study initiated the development of the teaching content for breast rare diseases and developed the teaching syllabus using the CBL+PBL+RBL integrated multi teaching model and targeting each rare breast disease for the critical point for teaching.