SCARB1-encoded circ _0029343 induces p73 splicing to promote growth and metastasis of hepatocellular carcinoma via miR-486-5p/SRSF3 axis.

Circular RNAs (circRNAs) exhibit essential regulation in the malignant development of hepatocellular carcinoma (HCC). This study aims to investigate the physiological mechanisms of circ_0029343 encoded by scavenger receptor class B member 1 (SCARB1) involved in the growth and metastasis of HCC. Differentially expressed mRNAs in HCC were obtained, followed by the prediction of target genes of differentially expressed miRNAs and gene ontology and kyoto encyclopedia of genes and genomes analysis on the differentially expressed mRNAs. Moreover, the regulatory relationship between circRNAs encoded by SCARB1 and differentially expressed miRNAs was predicted. In vitro cell experiments were performed to verify the effects of circ_0029343, miR-486-5p, and SRSF3 on the malignant features of HCC cells using the gain- or loss-of-function experiments. Finally, the effects of circ_0029343 on the growth and metastasis of HCC cells in xenograft mouse models were also explored. It was found that miR-486-5p might interact with seven circRNAs encoded by SCARB1, and its possible downstream target gene was SRSF3. Moreover, SRSF3 was associated with the splicing of various RNA. circ_0029343 could sponge miR-486-5p to up-regulate SRSF3 and activate PDGF-PDGFRB (platelet-derived growth factor and its receptor, receptor beta) signaling pathway by inducing p73 splicing, thus promoting the proliferation, migration, and invasion and inhibiting apoptosis of HCC cells. In vivo, animal experiments further confirmed that overexpression of circ_0029343 could promote the growth and metastasis of HCC cells in nude mice. circ_0029343 encoded by SCARB1 may induce p73 splicing and activate the PDGF-PDGFRB signaling pathway through the miR-486-5p/SRSF3 axis, thus promoting the growth and metastasis of HCC cells.

JMJD6-BRD4 complex stimulates lncRNA HOTAIR transcription by binding to the promoter region of HOTAIR and induces radioresistance in liver cancer stem cells.

BACKGROUND: Long non-coding RNA (lncRNA) HOTAIR acts importantly in liver cancer development, but its effect on radioresistance remains poorly understood. Here, our study probed into the possible impact of HOTAIR in radioresistance in liver cancer stem cells (LCSCs) and to elucidate its molecular basis. METHODS: Following sorting of stem and non-stem liver cancer cells, LCSCs were identified and subjected to RNA-seq analysis for selecting differentially expressed genes. Expression of HOTAIR was determined in liver cancer tissues and CSCs. The stemness, proliferation, apoptosis and radioresistance of LCSCs were then detected in response to altered expression of HOTAIR-LSD1-JMJD6-BRD4. RESULTS: Ectopic HOTAIR expression was found to promote radioresistance of LCSCs by maintaining its stemness. Mechanistic investigations indicated that HOTAIR recruited LSD1 to the MAPK1 promoter region and reduced the level of H3K9me2 in the promoter region, thus elevating ERK2 (MAPK1) expression. JMJD6-BRD4 complex promoted HOTAIR transcription by forming a complex and positively regulated ERK2 (MAPK1) expression, maintaining the stemness of LCSCs, and ultimately promoting their radioresistance in vitro and in vivo. CONCLUSION: Collectively, our work highlights the promoting effect of the JMJD6-BRD4 complex on the radioresistance of LCSCs through a HOTAIR-dependent mechanism.

Tumor suppressive lncRNA MEG3 binds to EZH2 and enhances CXCL3 methylation in gallbladder cancer.

Gallbladder cancer is a malignant tumor with a high mortality rate. Accumulating evidence supports that lncRNA MEG3 may halt the progression of gallbladder cancer, while the downstream mechanism is rarely studied. Thus, we aim to investigate the molecular basis of the tumor-suppressing role of lncRNA MEG3 in gallbladder cancer. The expression of lncRNA MEG3 and CXCL3 was measured in patient serum and cell lines of gallbladder cancer. The viability, apoptosis, migration, and invasion of gallbladder cancer cells were assessed following ectopic MEG3 expression, as detected by CCK-8, flow cytometry, and Transwell assays. The interaction among lncRNA MEG3, EZH2, and CXCL3 was explored through ChIP, RNA pull-down, and RIP assays. The effects of lncRNA MEG3 and CXCL3 on tumor growth were evaluated by a mouse xenograft model. lncRNA MEG3 was expressed at a low level in gallbladder cancer patient serum and cell lines, while CXCL3 was highly expressed. MEG3 overexpression repressed the malignant behaviors of gallbladder cancer cells and promoted their apoptosis. MEG3 was mainly localized in the nucleus. MEG3 bound to EZH2, and EZH2 catalyzed the H3K27 trimethylation of the CXCL3 promoter region. MEG3 downregulated CXCL3 by activating EZH2-mediated H3K27 trimethylation of CXCL3; MEG3 overexpression attenuated cancer cell malignant behaviors in vitro and suppressed tumor growth in vivo in gallbladder cancer by inhibiting CXCL3 expression. Altogether, our results indicate that lncRNA MEG3 impedes gallbladder cancer development via the EZH2-CXCL3 axis, offering potential biomarkers for gallbladder cancer management.

Promises and Pitfalls: Using Large Language Models to Generate Visualization Items.

Visualization items-factual questions about visualizations that ask viewers to accomplish visualization tasks-are regularly used in the field of information visualization as educational and evaluative materials. For example, researchers of visualization literacy require large, diverse banks of items to conduct studies where the same skill is measured repeatedly on the same participants. Yet, generating a large number of high-quality, diverse items requires significant time and expertise. To address the critical need for a large number of diverse visualization items in education and research, this paper investigates the potential for large language models (LLMs) to automate the generation of multiple-choice visualization items. Through an iterative design process, we develop the VILA (Visualization Items Generated by Large LAnguage Models) pipeline, for efficiently generating visualization items that measure people's ability to accomplish visualization tasks. We use the VILA pipeline to generate 1,404 candidate items across 12 chart types and 13 visualization tasks. In collaboration with 11 visualization experts, we develop an evaluation rulebook which we then use to rate the quality of all candidate items. The result is the VILA bank of ∼1,100 items. From this evaluation, we also identify and classify current limitations of the VILA pipeline, and discuss the role of human oversight in ensuring quality. In addition, we demonstrate an application of our work by creating a visualization literacy test, VILA-VLAT, which measures people's ability to complete a diverse set of tasks on various types of visualizations; comparing it to the existing VLAT, VILA-VLAT shows moderate to high convergent validity (R = 0.70). Lastly, we discuss the application areas of the VILA pipeline and the VILA bank and provide practical recommendations for their use. All supplemental materials are available at https://osf.io/ysrhq/.

LOXL4 Shuttled by Tumor Cells-derived Extracellular Vesicles Promotes Immune Escape in Hepatocellular Carcinoma by Activating the STAT1/PD-L1 Axis.

Emerging evidence has validated that extracellular vesicles (EVs) regulate hepatocellular carcinoma (HCC) progression, while its role in HCC immune escape remains to be elucidated. This study investigates the role of EVs-encapsulated lysyl oxidase like-4 (LOXL4) derived from tumor cells in HCC immune escape. HCC-related microarray data sets GSE36376 and GSE87630 were obtained for differential analysis, followed by identifying the essential genes related to the prognosis of HCC patients. Bone marrow-derived macrophages were treated with EVs derived from mouse Hepa 1-6 cells and cocultured with CD8 + T cells to observe the CD8 + T-cell activity. At last, a mouse HCC orthotopic xenograft model was constructed to verify the effects of HCC cell-derived EVs on the immune escape of HCC cells and tumorigenicity in vivo by delivering LOXL4. It was found that ACAT1, C4BPA, EHHADH, and LOXL4 may be the essential genes related to the prognosis of HCC patients. On the basis of the TIMER database, there was a close correlation between LOXL4 and macrophage infiltration in HCC. Besides, STAT1 was closely related to LOXL4. In vitro experiments demonstrated that LOXL4 could induce programmed death-ligand 1 expression in macrophages and immunosuppression by activating STAT1. In vivo experiments also verified that HCC cell-derived EVs promoted the immune escape of HCC cells and tumorigenicity by delivering LOXL4. LOXL4 was delivered into macrophages via EVs to induce programmed death-ligand 1 by activating STAT1 and inhibiting the killing ability of CD8 + T cells to HCC cells, thus promoting immune escape in HCC.

Probablement, Wahrscheinlich, Likely? A Cross-Language Study of How People Verbalize Probabilities in Icon Array Visualizations.

Visualizations today are used across a wide range of languages and cultures. Yet the extent to which language impacts how we reason about data and visualizations remains unclear. In this paper, we explore the intersection of visualization and language through a cross-language study on estimative probability tasks with icon-array visualizations. Across Arabic, English, French, German, and Mandarin, n=50 participants per language both chose probability expressions - e.g. likely, probable - to describe icon-array visualizations (Vis-to-Expression), and drew icon-array visualizations to match a given expression (Expression-to-Vis). Results suggest that there is no clear one-to-one mapping of probability expressions and associated visual ranges between languages. Several translated expressions fell significantly above or below the range of the corresponding English expressions. Compared to other languages, French and German respondents appear to exhibit high levels of consistency between the visualizations they drew and the words they chose. Participants across languages used similar words when describing scenarios above 80% chance, with more variance in expressions targeting mid-range and lower values. We discuss how these results suggest potential differences in the expressiveness of language as it relates to visualization interpretation and design goals, as well as practical implications for translation efforts and future studies at the intersection of languages, culture, and visualization. Experiment data, source code, and analysis scripts are available at the following repository: https://osf.io/g5d4r/.

Adaptive Assessment of Visualization Literacy.

Visualization literacy is an essential skill for accurately interpreting data to inform critical decisions. Consequently, it is vital to understand the evolution of this ability and devise targeted interventions to enhance it, requiring concise and repeatable assessments of visualization literacy for individuals. However, current assessments, such as the Visualization Literacy Assessment Test (VLAT), are time-consuming due to their fixed, lengthy format. To address this limitation, we develop two streamlined computerized adaptive tests (CATs) for visualization literacy, A-VLAT and A-CALVI, which measure the same set of skills as their original versions in half the number of questions. Specifically, we (1) employ item response theory (IRT) and non-psychometric constraints to construct adaptive versions of the assessments, (2) finalize the configurations of adaptation through simulation, (3) refine the composition of test items of A-CALVI via a qualitative study, and (4) demonstrate the test-retest reliability (ICC: 0.98 and 0.98) and convergent validity (correlation: 0.81 and 0.66) of both CATs via four online studies. We discuss practical recommendations for using our CATs and opportunities for further customization to leverage the full potential of adaptive assessments. All supplemental materials are available at https://osf.io/a6258/.

Extracellular Vesicle-Loaded Oncogenic lncRNA NEAT1 from Adipose-Derived Mesenchymal Stem Cells Confers Gemcitabine Resistance in Pancreatic Cancer via miR-491-5p/Snail/SOCS3 Axis.

It is becoming increasingly evident that key mechanisms of mesenchymal stem cell (MSC) efficacy appear to associate with paracrine activities, and the delivery of cargos through extracellular vesicles (EVs) controls the mechanistic actions of MSCs. Thus, this study clarified a possible mechanism by which EV-encapsulated NEAT1 from adipose-derived mesenchymal stem cells (ADSCs) might mediate gemcitabine resistance in pancreatic cancer (PCa). Microarray profile suggested a differentially expressed lncRNA NEAT1 in PCa, and we determined its expression in PCa cells. NEAT1 was found to be upregulated in PCa. The binding affinity among NEAT1, miR-491-5p, and Snail was identified through bioinformatic analysis and experimental validation. NEAT1 competitively bound to miR-491-5p to elevate Snail expression and diminish SOCS3 expression. PCa cells were cocultured with EVs extracted from ADSCs, followed by assessment of malignant phenotypes, tumorigenesis, and gemcitabine resistance of PCa cells using gain- or loss-of-function experiments. ADSC-derived EVs carrying NEAT1 promoted PCa cell proliferation, migration, and gemcitabine resistance in vitro and enhanced tumorigenicity in vivo by inhibiting miR-491-5p and SOCS3 and upregulating Snail. Collectively, the findings from our study found a new potential strategy for gemcitabine resistance in PCa by illustrating the mechanistic insights of oncogenic ADSC-derived EVs-loaded NEAT1 via regulating the miR-491-5p/Snail/SOCS3 axis.

Study on the nitrogen content estimation model of cotton leaves based on "image-spectrum-fluorescence" data fusion.

Objective: Precise monitoring of cotton leaves' nitrogen content is important for increasing yield and reducing fertilizer application. Spectra and images are used to monitor crop nitrogen information. However, the information expressed using nitrogen monitoring based on a single data source is limited and cannot consider the expression of various phenotypic and physiological parameters simultaneously, which can affect the accuracy of inversion. Introducing a multi-source data-fusion mechanism can improve the accuracy and stability of cotton nitrogen content monitoring from the perspective of information complementarity. Methods: Five nitrogen treatments were applied to the test crop, Xinluzao No. 53 cotton, grown indoors. Cotton leaf hyperspectral, chlorophyll fluorescence, and digital image data were collected and screened. A multilevel data-fusion model combining multiple machine learning and stacking integration learning was built from three dimensions: feature-level fusion, decision-level fusion, and hybrid fusion. Results: The determination coefficients (R2) of the feature-level fusion, decision-level fusion, and hybrid-fusion models were 0.752, 0.771, and 0.848, and the root-mean-square errors (RMSE) were 3.806, 3.558, and 2.898, respectively. Compared with the nitrogen estimation models of the three single data sources, R2 increased by 5.0%, 6.8%, and 14.6%, and the RMSE decreased by 3.2%, 9.5%, and 26.3%, respectively. Conclusion: The multilevel fusion model can improve accuracy to varying degrees, and the accuracy and stability were highest with the hybrid-fusion model; these results provide theoretical and technical support for optimizing an accurate method of monitoring cotton leaf nitrogen content.

The Risks of Ranking: Revisiting Graphical Perception to Model Individual Differences in Visualization Performance.

Graphical perception studies typically measure visualization encoding effectiveness using the error of an "average observer", leading to canonical rankings of encodings for numerical attributes: e.g., position area angle volume. Yet different people may vary in their ability to read different visualization types, leading to variance in this ranking across individuals not captured by population-level metrics using "average observer" models. One way we can bridge this gap is by recasting classic visual perception tasks as tools for assessing individual performance, in addition to overall visualization performance. In this paper we replicate and extend Cleveland and McGill's graphical comparison experiment using Bayesian multilevel regression, using these models to explore individual differences in visualization skill from multiple perspectives. The results from experiments and modeling indicate that some people show patterns of accuracy that credibly deviate from the canonical rankings of visualization effectiveness. We discuss implications of these findings, such as a need for new ways to communicate visualization effectiveness to designers, how patterns in individuals' responses may show systematic biases and strategies in visualization judgment, and how recasting classic visual perception tasks as tools for assessing individual performance may offer new ways to quantify aspects of visualization literacy. Experiment data, source code, and analysis scripts are available at the following repository: https://osf.io/8ub7t/?view_only=9be4798797404a4397be3c6fc2a68cc0.

The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1.

INTRODUCTION: Circular RNA (CircRNA) SCARB1 plays an oncogenic role in renal cell carcinoma, while its role in other cancers is unclear. The aim of this study was to explore the role of circRNA SCARB1 in hepatocellular carcinoma (HCC). METHODS: The expression of circRNA SCARB1, mature miR-497 and miR-497 precursor in HCC and paired non-tumor tissues from 64 HCC patients were analyzed by RT-qPCR. CircRNA SCARB1 was overexpressed in HCC cells, followed by the measurement of the expression levels of both mature miR-497 and miR-497 precursor to evaluate the effects of overexpression of circRNA SCARB1 on the maturation of miR-497. The effects of circRNA SCARB1 and miR-497 on the proliferation and migration of HCC cells were assessed by CCK-8 assay and Transwell assay, respectively. RESULTS: We found that circRNA SCARB1 was upregulated in HCC. In addition, mature miR-497 and miR-497 were downregulated in HCC. Correlation analysis showed that circRNA SCARB1 was inversely correlated with mature miR-497 but not miR-497 precursor. Consistently, in HCC cells, downregulated mature miR-497, but not miR-497 precursor, was observed in HCC cells transfected with circRNA SCARB1 expression vector. Analysis of cellular behaviors showed that overexpression of circRNA SCARB1 increased the proliferation and migration of HCC cells, while overexpression of miR-497 decreased cell proliferation and migration. Moreover, overexpression of miR-497 reduced the effects of overexpression of circRNA SCARB1. DISCUSSION: Therefore, circRNA SCARB1 is upregulated in HCC and promotes HCC cell proliferation and migration by suppressing the maturation of miR-497.