Objective To investigate the regulatory effect of artemisinin derivative dihydroartemisinin(DHA)on anti-tumor immune function of CD8+T cells induced by non-small cell lung cancer(NSCLC)cells.Methods NSCLC A549 cells were divided into DMSO control group and DHA treatment group.A549 cells were treated with DMSO and DHA at different concentrations(25,50 and 100 μmol/L),and the optimal concentration of DHA was selected to treat A549 cells for 0,24,48 and 72 h according to half maximal inhibitory concentrate(IC50).CCK-8 method and colony formation test were used to detect the effect of DHA on the proliferation and colony formation ability of A549 cells.Peripheral blood mononuclear cells(PBMCs)of healthy individuals were isolated by density gradient centrifugation.After monocytes were removed by adhesion method,A549 cells pretreated with mitomycin C were co-cultured with PBMCs at 10:1 ratio.After 2 weeks,flow cytometry was used to detect the proportion of CD8+T cells and the expression levels of perforin and granzyme B.Results Compared with the control group,the proliferation inhibition rates of A549 cells increased after treatment with 25,50 and 100 μmol/L DHA for 24 h(P<0.01).The IC50 of DHA on A549 cells was46.26 μmol/L.According to IC50 concentration analysis,the inhibi-tion rates of A549 cells treated with 50 μmol/L DHA for 0,24,48 and 72h were 1.53%,53.50%,63.84%and 69.91%,and the cells inhibition rates of A548 cells increased compared with the previous observation time point,namely 0,24 and 48 h(P<0.01).The colony formation assay showed that the colony formation number of A549 cells in DHA treated group decreased compared with the control group(P<0.01).Flow cytometry results showed that compared with the control group,the proportion of CD8+T cells induced by A549 cells in the co-culture system and the proportion of CD8+T cells expressing perforin and granzyme B were higher in DHA pretreatment group(P<0.01).Conclusion DHA inhibits the growth of NSCLC cells and promotes anti-tumor immune response of CD8+T cells induced by NSCLC cells.

Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Objective Investigating the impact of miR-15a-5p on autophagy in trophoblast cells of pre-eclamptic placenta.Methods Collect 20 cases of normal placental tissue and 20 cases of preeclamptic placental tissue from December 2020 to December 2022.Use fluorescence quantitative PCR to detect the expression of miR-15a-5p in placental tissue and trophoblast cells,and study its correlation with patient blood pressure.The HTR8-S/Vneo cells are divided into normal group(control)and hypoxia group,and the effect of hypoxia on the expression of miR-15a-5p is observed.Additionally,mimic-NC group,mimic-NC+hypoxia group,miR-15a-5p mimic group,miR-15a-5p mimic+hypoxia group,inhibitor-NC group,inhibitor-NC+hypoxia group,miR-15a-5p inhibitor group,and miR-15a-5p inhibitor+hypoxia groups are set up to observe the effect of miR-15a-5p on hypoxia-induced autophagy-related proteins LC3B and p62 protein in trophoblast cells.Western blot is used to detect the expression levels of autophagy-related proteins LC3B and p62 protein in each group;TargetScan website predicts the target genes of miR-15a-5p,and detects their expression levels in placental tissue and trophoblast cells.Results Compared with the control group,the expression levels of miR-15a-5p were significantly increased in the placentas and hypoxic trophoblasts of preeclampsia,and they were positively correlated with the blood pressure of the patients.Under hypoxic conditions,the overexpressed miR-15a-5p promoted the protein expression of LC3BII/I,while the relative expression of P62 was decreased.But after interference with miR-15a-5p,LC3BII/I expression was down-regulated and P62 expression was up-regulated.The results of quantitative PCR and Western blot showed that the expression levels of YAP1 in the preeclampsia placental tissues and hypoxic trophoblasts were significantly reduced.Conclusion The upregulation of miR-15a-5p in trophoblast cells of the placenta in individuals with preeclampsia could enhance autophagy in preeclampsia by forming a complex with YAP1.

Objective: Previous research has explored a variety of mental disorders associated with Internet Gaming Disoder (IGD) and Social Media Addiction (SMA). To date, few studies focused on the network characteristics and investigated mood and sleep symptoms across SMA and IGD of adolescence at a group-specific level. This study aims to identify different characteristics of IGD and SMA and further determine the group-specific psychopathology process among adolescents. Methods: We conducted a cross-sectional study to recruit a cohort of 7,246 adolescents who were scored passing the cutoff point of Internet Gaming Disorder Scale-Short Form and Bergen Social Media Addiction Scale, as grouped in IGD and SMA, or otherwise into the control group. Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-item, and Pittsburgh Sleep Quality Index were assessed for the current study, and all assessed items were investigated using network analysis. Results: Based on the analytical procedure, the participants were divided into three groups, the IGD group (n=789), SMA group (n=713) and control group (n=5,744). The edge weight bootstrapping analysis shows that different groups of networks reach certain accuracy, and the network structures of the three groups are statistically different (pcontrol-IGD=0.004, pcontrol-SMA<0.001, pIGD-SMA<0.001). The core symptom of SMA is “feeling down, depressed, or hopeless”, while IGD is “feeling tired or having little energy”. Conclusion Although IGD and SMA are both subtypes of internet addiction, the psychopathology processes of IGD and SMA are different. When dealing with IGD and SMA, different symptoms should be addressed.

Objective:To explore the effectiveness of the artificial intelligence-endoscopic ultrasound (AI-EUS) biliary and pancreatic recognition system in assisting the recognition of EUS images.Methods:Subjects who received EUS due to suspicious biliary and pancreatic diseases from December 2019 to August 2020 were prospectively collected from the database of Department of Gastroenterology, Renmin Hospital of Wuhan University. Pancreatic EUS images of 28 subjects were included for recognition of pancreas standard station. EUS images of bile duct of 29 subjects were included for recognition of bile duct standard station. Eight new endoscopists from the Gastroenterology Department of Renmin Hospital of Wuhan University read the 57 EUS videos with and without the assistance of AI-EUS biliary and pancreatic recognition system. Accuracy of endoscopists' identification of biliary and pancreatic standard sites with and without the assistance of AI-EUS was compared.Results:The accuracy of pancreas standard station identification of the new endoscopists increased from 67.2% (903/1 344) to 78.4% (1 054/1 344) with the assistance of AI-EUS. The accuracy of bile duct standard station identification increased from 56.4% (523/928) to 73.8% (685/928).Conclusion:AI-EUS biliary and pancreatic recognition system can improve the accuracy of EUS images recognition of biliary and pancreatic system, which can assist diagnosis in clinical work.

Objective: To explore the correlation between epidermal growth factor receptor ( EGFR) mutation and brain metastasis in lung adenocarcinoma． Methods: Comparisons of brain metastasis between lung adenocarcinoma patients with EGFR exon 19 deletion ( 19 Del) and a single point mutation of L858R in exon 21 (21 L858R) at initial diagnosis and after EGFR-TKIs targeted therapy were analyzed．The CCK-8 assay was used to detect and calculate the semi-inhibitory concentration (IC50 ) of gefitinib against EGFR-mutated lung adenoma cell lines PC9 and H3255 . Results: Of the 410 patients with lung adenocarcinoma，a total of 153 (37. 3% ) cases had brain metastasis．Age，lymph node metastasis and 21 L858R mutation were high-risk factors for brain metastasis of lung adenocarcinoma．Among newly diagnosed 48 EGFR-mutated lung adenocarcinoma patients with brain metastasis ，the number of 19 Del and 21 L858R were 14 and 34，respectively (P = 0. 006) ．There were 17 patients with 19 Del and 20 patients with 21 L858R were observed to complicated by brain metastasis after receiving EGFR-TKIs targeted therapy．The median time of brain metastasis after EGFR-TKIs treatment were 15 months (8. 50，25. 00) and 7 months (4. 25，12. 25 ) ，respectively ( P = 0. 013 ) ． The IC50 of PC9 and H3255 to gefitinib were (0. 037 ± 0. 008) and (0. 150 ± 0. 040) μmol / L，respectively (P = 0. 007) ． Conclusion Age younger than or equal to 60 years，lymph node N2-3 stage，and EGFR 21 L858R mutation are high-risk factors for brain metastases in patients with lung adenocarcinoma，and the latter still has a shorter time to brain metastases than 19 Del mutations after treatment with EGFR-TKIs，which may be related to drug sensitivity.

Background:Slight mucosal lesions in the early stage of gastric cancer(GC)are difficult to recognize,and the miss rate of early GC by conventional endoscopy is high.Artificial intelligence(AI)systems can assist in the identification of gastric neoplastic lesions and reduce miss rate,but it is not clear whether AI-assisted endoscopic screening is cost-effective.Aims:The subjects of this study were to evaluate the cost-effectiveness of a population-based endoscopy screening program for GC in high-incidence countries(China,Japan and South Korea),and to explore the applicability of domestic AI--Intelligent and real-time endoscopy analytical device(IREAD)-assisted endoscopy for GC screening in these three countries.Methods:Based on the natural history of GC,a Markov model with cycle year of 1 year was constructed to compare cost-effectiveness of two strategies for GC screening in recommended age group:no screening(the control strategy),conventional endoscopy screening and IREAD-assisted endoscopy screening.Data such as transition probabilities of different states and treatment costs were obtained from previously published studies.The cost-effectiveness analysis was conducted from the perspective of society by calculating cost,Quality adjusted life years(QALY),Incremental cost effectiveness ratio(ICER).Results:The cohort results showed that 15.87%and 24.52%of GC-related deaths could be respectively avoid by conventional endoscopy screening and IREAD-assisted endoscopy screening in China,which the screening effects were similar to Japan;In South Korea,Conventional endoscopic screening and IREAD-assisted endoscopic screening averted 41.34%and 53.15%of GC-related deaths,respectively.Between the two strategies,IREAD-assisted endoscopic screening is more economic,with ICER of $34 827.61/QALY,$87 978.71/QALY and $10 574.30/QALY in China,Japan and South Korea,respectively,which were lower than the willingness-to-pay(WTP)threshold.Conclusions:When the threshold of WTP is 3 times Gross domestic product per capita,the application of AI-assisted endoscopy for GC screening in age-specific population in high-incidence countries may be more cost-effective.Meanwhile,this study provides important evidence for the promotion of domestic IRAED-assisted endoscopy in GC screening in China,Japan and South Korea.

Minimal residual disease (MRD) has been used for warning of relapse and guiding the therapy selection for hematological malignancies including acute leukemia. Based on MRD-related content reported at the 64th American Society of Hematology (ASH) Annual Meeting, this article discusses the progress of MRD-directed individualized therapy for hematological malignancies with a primary focus on acute myeloid leukemia.

Objective:To evaluate deep learning for differentiating invasion depth of colorectal adenomas under image enhanced endoscopy (IEE).Methods:A total of 13 246 IEE images from 3 714 lesions acquired from November 2016 to June 2021 were retrospectively collected in Renmin Hospital of Wuhan University, Shenzhen Hospital of Southern Medical University and the First Hospital of Yichang to construct a deep learning model to differentiate submucosal deep invasion and non-submucosal deep invasion lesions of colorectal adenomas. The performance of the deep learning model was validated in an independent test and an external test. The full test was used to compare the diagnostic performance between 5 endoscopists and the deep learning model. A total of 35 videos were collected from January to June 2021 in Renmin Hospital of Wuhan University to validate the diagnostic performance of the endoscopists with the assistance of deep learning model.Results:The accuracy and Youden index of the deep learning model in image test set were 93.08% (821/882) and 0.86, which were better than those of endoscopists [the highest were 91.72% (809/882) and 0.78]. In video test set, the accuracy and Youden index of the model were 97.14% (34/35) and 0.94. With the assistance of the model, the accuracy of endoscopists was significantly improved [the highest was 97.14% (34/35)].Conclusion:The deep learning model obtained in this study could identify submucosal lesions with deep invasion accurately for colorectal adenomas, and could improve the diagnostic accuracy of endoscopists.

Brain-computer interfaces (BCIs) have become one of the cutting-edge technologies in the world, and have been mainly applicated in medicine. In this article, we sorted out the development history and important scenarios of BCIs in medical application, analyzed the research progress, technology development, clinical transformation and product market through qualitative and quantitative analysis, and looked forward to the future trends. The results showed that the research hotspots included the processing and interpretation of electroencephalogram (EEG) signals, the development and application of machine learning algorithms, and the detection and treatment of neurological diseases. The technological key points included hardware development such as new electrodes, software development such as algorithms for EEG signal processing, and various medical applications such as rehabilitation and training in stroke patients. Currently, several invasive and non-invasive BCIs are in research. The R&D level of BCIs in China and the United State is leading the world, and have approved a number of non-invasive BCIs. In the future, BCIs will be applied to a wider range of medical fields. Related products will develop shift from a single mode to a combined mode. EEG signal acquisition devices will be miniaturized and wireless. The information flow and interaction between brain and machine will give birth to brain-machine fusion intelligence. Last but not least, the safety and ethical issues of BCIs will be taken seriously, and the relevant regulations and standards will be further improved.
Humans ; Brain-Computer Interfaces ; Medicine ; Algorithms ; Artificial Intelligence ; Brain