GATA6-AS1 suppresses epithelial-mesenchymal transition of pancreatic cancer under hypoxia through regulating SNAI1 mRNA stability.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a hypoxic microenvironment, a high rate of heterogeneity as well as a high likelihood of recurrence. Mounting evidence has affirmed that long non-coding RNAs (lncRNAs) participate in the carcinogenesis of PDAC cells. In this study, we revealed significantly decreased expression of GATA6-AS1 in PDAC based on the GEO dataset and our cohorts, and showed that low GATA6-AS1 expression was linked to unfavorable clinicopathologic characteristics as well as a poor prognosis. Gain- and loss-of-function studies demonstrated that GATA6-AS1 suppressed the proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) process of PDAC cells under hypoxia. In vivo data confirm the suppressive roles of GATA6-AS1/SNAI1 in tumor growth and lung metastasis of PDAC. Mechanistically, hypoxia-driven E26 transformation-specific sequence-1 (ETS1), as an upstream modulatory mechanism, was essential for the downregulation of GATA6-AS1 in PDAC cells. GATA6-AS1 inhibited the expression of fat mass and obesity-associated protein (FTO), an N6-methyladenosine (m6A) eraser, and repressed SNAI1 mRNA stability in an m6A-dependent manner. Our data suggested that GATA6-AS1 can inhibit PDAC cell proliferation, invasion, migration, EMT process and metastasis under hypoxia, and disrupting the GATA6-AS1/FTO/SNAI1 axis might be a viable therapeutic approach for refractory hypoxic pancreatic cancers.

Nomogram based on spleen volume expansion rate predicts esophagogastric varices bleeding risk in patients with hepatitis B liver cirrhosis.

Background: We aimed to explore the risk factors for hemorrhage of esophagogastric varices (EGVs) in patients with hepatitis B cirrhosis and to construct a novel nomogram model based on the spleen volume expansion rate to predict the risk of esophagogastric varices bleeding. Methods: Univariate and multivariate logistic regression analysis was used to analyze the risk factors for EGVs bleeding. Nomograms were established based on the multivariate analysis results. The predictive accuracy of the nomograms was assessed using the area under the curve (AUC or C-index) of the receiver operating characteristic (ROC) and calibration curves. Decision curve analysis was used to determine the clinical benefit of the nomogram. We created a nomogram of the best predictive models. Results: A total of 142 patients' hepatitis B cirrhosis with esophagogastric varices were included in this study, of whom 85 (59.9%) had a history of EGVs bleeding and 57 (40.1%) had no EGVs bleeding. The spleen volume expansion rate, serum sodium levels (mmol/L), hemoglobin levels (g/L), and prothrombin time (s) were independent predictors for EGVs bleeding in patients with hepatitis B liver cirrhosis (P < 0.05). The above predictors were included in the nomogram prediction model. The area under the ROC curve (AUROC) of the nomogram was 0.781, the C-index obtained by internal validation was 0.757, and the calibration prediction curve fit well with the ideal curve. The AUROCs of the PLT-MELD and APRI were 0.648 and 0.548, respectively. Conclusion: In this study, a novel nomogram for predicting the risk of EGVs bleeding in patients with hepatitis B cirrhosis was successfully constructed by combining the spleen volume expansion rate, serum sodium levels, hemoglobin levels, and prothrombin time. The predictive model can provide clinicians with a reference to help them make clinical decisions.

Stratified analysis of multiple management of gastric cancer: A population-based study of incidence, mortality and DALY.

The aim was to illuminate the difference in incidence, mortality, and disability-adjusted life-years (DALYs) of gastric cancer (GC) between the United States of America (US) and China. The multiple management was analyzed with stratification to explore an effective survival improvement strategy. The Global Burden of Disease Study data was analyzed to assess GC morbidity, mortality and DALYs from 1990 to 2019 in the US and China. The age-period-cohort model was established to generate estimation of metrics. Verification was completed and stratified analysis of the multiple management was performed by accessing data of Surveillance, Epidemiology, and End Results database in 1992 to 2019. Continuous downtrends in GC incidence, mortality and DALYs from 1990 to 2019 and persistent uptrends in 1-, 3-year survival from 1992 to 2019 were observed in the US population. In the Chinese population, the overall trends of incidence, mortality and DALYs decreased with a fluctuating manner. The lower overall survival rates were observed in elderly, unmarried patients, distant disease and poor grade, as well as patients lacking of medical treatment (P < .05). In stratified analyses, single local therapy decreased and the other modalities increased over time across different stages. Moreover, combined treatment and single systemic therapy decreased, but single local and conservative therapy increased with age. The study quantified the incidence, GC-specific mortality and DALYs in the US and China and estimated stage profiles, 1- and 3-year survival in the US. The heavy burden on later-onset GC (>70) and potential increase on early-onset GC (<40) needed to be addressed. Combined modalities and single chemotherapy were becoming more widely used over time, however, their uses decreased with age because of poor physical fitness. Our findings provide new insights into management tailoring appropriately to specific subgroups contributes to the increasing survival rate.

Clinical characteristic and pathogenesis of tumor-induced acute pancreatitis: a predictive model.

BACKGROUND: The aim of our study was to investigate the clinical characteristics and pathogenesis of tumor-induced acute pancreatitis (AP), and to develop a reliable prediction model of the clinical features to guide the diagnosis and treatment. METHODS: Patients with AP between January 2013 and December 2021 were enrolled in the study and were subdivided into the tumor group and the non-tumor group. The tumor group was subdivided into three groups based on the primary sites. Characteristic parameters, laboratory and imaging results were compared between groups. Least absolute shrinkage and selection operator regression model, XGBoost and random forest model were used to select the predictors associated with tumor-induced AP. Logistic regression analysis was used to validate the performance of the selected predictors and a nomogram was established to provide individualized probability of a tumor origin for AP. RESULTS: A total amount of 8970 patients were admitted for AP during the study period, and 8637 AP patients were enrolled in the study. Of these, 100 cases (1.16%) were tumor-induced AP. The tumor group was significantly older than the non-tumor group (t = 6.050, p = 0.000). Mild AP was observed in 90 cases, moderate AP in 9 cases and severe AP in one case. Tumors respectively originated from distal bile duct (14 cases), ampulla (13 cases) and pancreas (73 cases). The median time from initial AP to tumor diagnosis was 8.57 weeks and the median number of episode was 2 in the tumor group, which significantly surpassed the non-tumor group (p = 0.000). Age, white blood cell count, percentage of neutrophils, pancreatic or bile duct dilation and recurrent attacks were selected independent predictors for tumor origin. A nomogram model based on these factors was established. CONCLUSION: For patients with agnogenic AP, elderly man, recurrent attacks, pancreatic or bile duct dilatation and continuous no significant increase of inflammatory markers prompt to further screening of pancreatic biliary and ampulla.

A simultaneous electroencephalography and eye-tracking dataset in elite athletes during alertness and concentration tasks.

The dataset of simultaneous 64-channel electroencephalography (EEG) and high-speed eye-tracking (ET) recordings was collected from 31 professional athletes and 43 college students during alertness behavior task (ABT) and concentration cognitive task (CCT). The CCT experiment lasting 1-2 hours included five sessions for groups of the Shooting, Archery and Modern Pentathlon elite athletes and the controls. Concentration targets included shooting target and combination target with or without 24 different directions of visual distractors and 2 types of music distractors. Meditation and Schulte Grid trainings were done as interventions. Analysis of the dataset aimed to extract effective biological markers of eye movement and EEG that can assess the concentration level of talented athletes compared with same-aged controls. Moreover, this dataset is useful for the research of related visual brain-computer interfaces.

Human visual search follows a suboptimal Bayesian strategy revealed by a spatiotemporal computational model and experiment.

There is conflicting evidence regarding whether humans can make spatially optimal eye movements during visual search. Some studies have shown that humans can optimally integrate information across fixations and determine the next fixation location, however, these models have generally ignored the control of fixation duration and memory limitation, and the model results do not agree well with the details of human eye movement metrics. Here, we measured the temporal course of the human visibility map and performed a visual search experiment. We further built a continuous-time eye movement model that considers saccadic inaccuracy, saccadic bias, and memory constraints. We show that this model agrees better with the spatial and temporal properties of human eye movements and predict that humans have a memory capacity of around eight previous fixations. The model results reveal that humans employ a suboptimal eye movement strategy to find a target, which may minimize costs while still achieving sufficiently high search performance.