Areas of interest (AOIs) are well-established means of providing semantic information for visualizing, analyzing, and classifying gaze data. However, the usual manual annotation of AOIs is time-consuming and further impaired by ambiguities in label assignments. To address these issues, we present an interactive labeling approach that combines visualization, machine learning, and user-centered explainable annotation. Our system provides uncertainty-aware visualization to build trust in classification with an increasing number of annotated examples. It combines specifically designed EyeFlower glyphs, dimensionality reduction, and selection and exploration techniques in an integrated workflow. The approach is versatile and hardware-agnostic, supporting video stimuli from stationary and unconstrained mobile eye tracking alike. We conducted an expert review to assess labeling strategies and trust building.
Multienzyme assemblies mediated by multivalent interaction play a crucial role in cellular processes. However, the three-dimensional (3D) programming of an enzyme complex with defined enzyme activity in vitro remains unexplored, primarily owing to limitations in precisely controlling the spatial topological configuration. Herein, we introduce a nanoscale 3D enzyme assembly using a tetrahedral DNA framework (TDF), enabling the replication of spatial topological configuration and maintenance of an identical edge-to-edge distance akin to natural enzymes. Our results demonstrate that 3D nanoscale enzyme assemblies in both two-enzyme systems (glucose oxidase (GOx)/horseradish peroxidase (HRP)) and three-enzyme systems (amylglucosidase (AGO)/GOx/HRP) lead to enhanced cascade catalytic activity compared to the low-dimensional structure, resulting in â¼5.9- and â¼7.7-fold enhancements over homogeneous diffusional mixtures of free enzymes, respectively. Furthermore, we demonstrate the enzyme assemblies for the detection of the metabolism biomarkers creatinine and creatine, achieving a low limit of detection, high sensitivity, and broad detection range.
Enzymes, Immobilized , Glucose Oxidase , Enzymes, Immobilized/chemistry , Horseradish Peroxidase/chemistry , Glucose Oxidase/chemistry , DNA/chemistry
Colorectal cancer (CRC) has a high degree of heterogeneity and identifying the genetic information of individual tumor cells could help enhance our understanding of tumor biology and uncover potential therapeutic targets for CRC. In this study, we identified LPCAT2+ tumor cell populations with less malignancy than LPCAT2- tumor cells in human and mouse CRC tissues using scRNA-seq. Combining in vitro and in vivo experiments, we found that LPCAT2 could inhibit the proliferation of CRC cells by inducing ferroptosis. Mechanistically, LPCAT2 arrested PRMT1 in cytoplasm of CRC cells via regulating acetylation of PRMT1 at the K145 site. In turn, PRMT1 enhanced SLC7A11 promoter activity. Thus, LPCAT2 attenuated the positive regulatory effect of PRMT1 on SLC7A11 promoter. Notably, SLC7A11 acts as a ferroptosis regulator. Furthermore, in LPCAT2 knockout mice (LPCAT2-/-) colon cancer model, we found that LPCAT2-/- mice exhibited more severe lesions, while PRMT1 or SLC7A11 inhibitors delayed the progression. Altogether, we elucidated that LPCAT2 suppresses SLC7A11 expression by inhibiting PRMT1 nuclear translocation, thereby inducing ferroptosis in CRC cells. Moreover, inhibitors of the PRMT1/SLC7A11 axis could delay tumor progression in CRC with low LPCAT2 expression, making it a potentially effective treatment for CRC.
BACKGROUND: Currently, there is a lack of ideal risk prediction tools in the field of emergency general surgery (EGS). The American Association for the Surgery of Trauma recommends developing risk assessment tools specifically for EGS-related diseases. In this study, we sought to utilize machine learning (ML) algorithms to explore and develop a web-based calculator for predicting five perioperative risk events of eight common operations in EGS. METHOD: This study focused on patients with EGS and utilized electronic medical record systems to obtain data retrospectively from five centers in China. Five ML algorithms, including Random Forest (RF), Support Vector Machine, Naive Bayes, XGBoost, and Logistic Regression, were employed to construct predictive models for postoperative mortality, pneumonia, surgical site infection, thrombosis, and mechanical ventilation >48 h. The optimal models for each outcome event were determined based on metrics, including the value of the Area Under the Curve, F1 score, and sensitivity. A comparative analysis was conducted between the optimal models and Emergency Surgery Score (ESS), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and American Society of Anesthesiologists (ASA) classification. A web-based calculator was developed to determine corresponding risk probabilities. RESULT: Based on 10,993 patients with EGS, we determined the optimal RF model. The RF model also exhibited strong predictive performance compared with the ESS, APACHE II score, and ASA classification. Using this optimal model, we developed an online calculator with a questionnaire-guided interactive interface, catering to both the preoperative and postoperative application scenarios. CONCLUSIONS: We successfully developed an ML-based calculator for predicting the risk of postoperative adverse events in patients with EGS. This calculator accurately predicted the occurrence risk of five outcome events, providing quantified risk probabilities for clinical diagnosis and treatment.
The advances in AI-enabled techniques have accelerated the creation and automation of visualizations in the past decade. However, presenting visualizations in a descriptive and generative format remains a challenge. Moreover, current visualization embedding methods focus on standalone visualizations, neglecting the importance of contextual information for multi-view visualizations. To address this issue, we propose a new representation model, Chart2Vec, to learn a universal embedding of visualizations with context-aware information. Chart2Vec aims to support a wide range of downstream visualization tasks such as recommendation and storytelling. Our model considers both structural and semantic information of visualizations in declarative specifications. To enhance the context-aware capability, Chart2Vec employs multi-task learning on both supervised and unsupervised tasks concerning the cooccurrence of visualizations. We evaluate our method through an ablation study, a user study, and a quantitative comparison. The results verified the consistency of our embedding method with human cognition and showed its advantages over existing methods.
BACKGROUND: Lipopolysaccharide (LPS) can induce systemic inflammation and affect the growth and development of poultry. As a kind of traditional Chinese medicine, polysaccharide of Atractylodes macrocephala Koidz (PAMK) can effectively improve the growth performance of animals and improve the immunity of animal bodies. OBJECTIVES: The purpose of this study was to investigate the effects of PAMK on LPS-induced inflammatory response, proliferation, differentiation and apoptosis of chicken embryonic myogenic cells. METHODS: We used chicken embryonic myogenic cells as a model by detecting EdU/MYHC immunofluorescence, the expression of inflammation, proliferation, differentiation-related genes and proteins and the number of apoptotic cells in the condition of adding LPS, PAMK, belnacasan (an inhibitor of Caspase1) or their combinations. RESULTS: The results showed that LPS stimulation increased the expression of inflammatory factors, inhibited proliferation and differentiation, and excessive apoptosis in chicken embryonic myogenic cells, and PAMK alleviated these adverse effects induced by LPS. After the addition of belnacasan (inhibitor of Caspase1), apoptosis in myogenic cells was inhibited, and therefore, the number of apoptotic cells and the expression of pro-apoptotic genes Caspase1 and Caspase3 were increased. In addition, belnacasan inhibited the increased expression of inflammatory factors, inhibited proliferation, differentiation and excessive apoptosis in chicken embryonic myogenic cells induced by LPS. CONCLUSIONS: This study provides a theoretical basis for further exploring the mechanism of action of PAMK and exogenous LPS on chicken embryonic myogenic cells and lays the foundation for the development and application of green feed additives in animal husbandry industry.
Atractylodes , Lipopolysaccharides , Animals , Lipopolysaccharides/toxicity , Chickens , Polysaccharides/pharmacology , Apoptosis , Cell Proliferation , Inflammation/veterinary
Black carbon (BC) and brown carbon (BrC) are aerosols that absorb light and thereby contribute to climate change. In this study, the light absorption properties and spatiotemporal distributions of equivalent BC (eBC) and BrC aerosols were determined based on continuous measurements of aerosol light absorption from January to August 2017, using a seven-channel aethalometer at 49 sampling sites in China. The source apportionments of BC and BrC were identified using the BC/PM2.5, absorption Ångström exponent, the concentration-weighted trajectory method, and the random forest model. Based on the results, BC was the dominant light absorber, whereas BrC was responsible for a higher proportion of the light absorption in northern compared to southern China. The light absorption of BrC was highest in winter (34.3 Mm-1), followed by spring (19.0 Mm-1) and summer (3.6 Mm-1). The combustion of liquid fuels accounted for over 50 % of the light absorption coefficient of BC in most cities and the importance of carbon monoxide (CO) and nitrogen dioxide (NO2) was over 10 % for BC emitted by liquid fuel combustion, based on the random forest model. The contribution of solid fuel combustion to BC in the north was larger than that in the southern regions as coal combustion and crop residue burning are important emission sources of BC in most northern cities. The contribution of primary BrC to light absorption was high in some northern cities, whereas that of secondary BrC was prevalent in some southern cities. The diurnal variations in secondary BrC were affected by changes in odd oxygen and relative humidity, which promoted the photobleaching of the chromophores and aqueous-phase reactions of secondary BrC.
Efficient biocatalytic cascade reactions play a crucial role in guiding intricate, specific and selective intracellular transformation processes. However, the catalytic activity of the enzyme cascade reaction in bulk solution was greatly impacted by the spatial morphology and inter-enzyme distance. The programmability and addressability nature of framework nucleic acid (FNA) allows to be used as scaffold for immobilization and to direct the spatial arrangement of enzyme cascade molecules. Here, we used tetrahedral DNA framework (TDF) as nanorulers to assemble two enzymes for constructing a double-enzyme complex, which significantly enhance the catalytic efficiency of sarcosine oxidase (SOx)/horseradish peroxidase (HRP) cascade system. We synthesized four types of TDF nanorulers capable of programming the lateral distance between enzymes from 5.67â nm to 12.33â nm. Enzymes were chemical modified by ssDNA while preserving most catalytic activity. Polyacrylamide gel electrophoresis (PAGE), transmission electron microscopy (TEM) and atomic force microscopy (AFM) were used to verify the formation of double-enzyme complex. Four types of double-enzyme complexes with different enzyme distance were constructed, in which TDF26 (SOx+HRP) exhibited the highest relative enzyme cascade catalytic activity, ~3.11-fold of free-state enzyme. Importantly, all the double-enzyme complexes demonstrate a substantial improvement in enzyme cascade catalytic activity compared to free enzymes.
Utilization of lipids as energy substrates after birth causes cardiomyocyte (CM) cell-cycle arrest and loss of regenerative capacity in mammalian hearts. Beyond energy provision, proper management of lipid composition is crucial for cellular and organismal health, but its role in heart regeneration remains unclear. Here, we demonstrate widespread sphingolipid metabolism remodeling in neonatal hearts after injury and find that SphK1 and SphK2, isoenzymes producing the same sphingolipid metabolite sphingosine-1-phosphate (S1P), differently regulate cardiac regeneration. SphK2 is downregulated during heart development and determines CM proliferation via nuclear S1P-dependent modulation of histone acetylation. Reactivation of SphK2 induces adult CM cell-cycle re-entry and cytokinesis, thereby enhancing regeneration. Conversely, SphK1 is upregulated during development and promotes fibrosis through an S1P autocrine mechanism in cardiac fibroblasts. By fine-tuning the activity of each SphK isoform, we develop a therapy that simultaneously promotes myocardial repair and restricts fibrotic scarring to regenerate the infarcted adult hearts.
Heart , Lysophospholipids , Sphingolipids , Sphingosine/analogs & derivatives , Animals , Sphingolipids/metabolism , Isoenzymes , Mammals/metabolism , Phosphotransferases (Alcohol Group Acceptor)/metabolism
OBJECTIVES: To assess and compare the effectiveness of various treatment approaches for laryngeal contact granulomas (LCG). METHODS: A retrospective analysis was conducted on a cohort of 45 patients diagnosed with LCG at the Second Affiliated Hospital of Xi'an Jiaotong University from October 2017 to May 2023. Based on the treatment modalities administered, patients were categorized into three groups: acid suppression alone, hormone injection combined with acid suppression, and surgery combined with acid suppression. Subsequently, the study compared differences in treatment efficacy and average healing time among these three groups, using various indicators. RESULTS: The findings indicate that the granuloma size in LCG patients with hoarseness (0.126, 95% CI 0.087-0.288) was significantly greater compared to LCG patients without hoarseness (0.047, 95% CI 0.014-0.083) (P = 0.001). However, there were no significant variations in age, morphology (unlobulated/lobulated), laterality ratio (left/right), sex ratio (male/female), history of tracheal intubation (non-intubation/intubation), and RFS score (RFS > 7/RFS ≤ 7) (P > 0.05), regardless of the presence of hoarseness symptoms. At the treatment observation endpoint of 3 months, the curative ratio in the group receiving hormone injection combined with acid suppression was found to be significantly higher compared to the group receiving acid suppression alone (P = 0.018). In addition, the average healing time of patients in the hormone injection combined with acid suppression group was notably shorter than that of the acid suppression alone group (P = 0.007). CONCLUSIONS: The combination of hormonal injections and acid suppression may enhance the curative ratio and expedite the healing time of LCG.
Granuloma, Laryngeal , Hoarseness , Humans , Male , Female , Retrospective Studies , Hoarseness/etiology , Hoarseness/therapy , Granuloma, Laryngeal/surgery , Granuloma , Hormones
OBJECTIVE: Stocking density (SD) is an important issue in the poultry industry, which is related to the production performance, intestinal health and immune status. In the present study, the effects of SD on the metabolism and homeostasis of uric acid as well as the related functions of the liver and kidney in ducks were examined. METHODS: A total of 360 healthy 56-day-old Shan-ma ducks were randomly divided into the low stocking density (n = 60, density = 5 birds/m2), medium stocking density (n = 120, density = 10 birds/m2) and high stocking density groups (HSD; n = 180, density = 15 birds/m2). Samples were collected in the 3rd, 6th, and 9th weeks of the experiment for analysis. RESULTS: The serum levels of uric acid, lipopolysaccharide and inflammatory cytokines (interleukin-1ß [IL-1ß], IL-8, and tumor necrosis factor-α [TNF-α]) were increased significantly in the HSD group. Serious histopathological lesions could be seen in both the livers and kidneys in the HSD group in the 9th week. The mRNA expression levels of inflammatory cytokines (IL-8 and TNF-α) and related pathway components (toll-like receptor 4, myeloid differentiation primary response gene 88, and nuclear factor-κB) were increased significantly in both the livers and kidneys in the HSD group. The mRNA expression levels of enzymes (adenosine deaminase, xanthine oxidase, phosphoribosyl pyrophosphate amidotransferase, and phosphoribosyl pyrophosphate synthetase 1) related to the synthesis of uric acid increased significantly in the livers in the HSD group. However, the mRNA expression level of solute carrier family 2 member 9, which plays an important role in the excretion of uric acid by the kidney, was decreased significantly in the kidneys in the HSD group. CONCLUSION: These results indicated that a higher SD could cause tissue inflammatory lesions in the liver and kidney and subsequently affect the metabolism and homeostasis of uric acid, and is helpful for guiding decisions related to the breeding and production of ducks.
'General requirements for the production of extracellular vesicles derived from human stem cells' is the first guideline for stem cells derived extracellular vesicles in China, jointly drafted and agreed upon by experts from the Chinese Society for Stem Cell Research. This standard specifies the general requirements, process requirements, packaging and labelling requirements and storage requirements for preparing extracellular vesicles derived from human stem cells, which is applicable to the research and production of extracellular vesicles derived from stem cells. It was originally released by the China Society for Cell Biology on 30 August 2022. We hope that the publication of this guideline will promote institutional establishment, acceptance and execution of proper protocols, and accelerate the international standardisation of extracellular vesicles derived from human stem cells.
Extracellular Vesicles , Stem Cells , Humans , China
In recent years, more and more researchers have reflected on the undervaluation of emotion in data visualization and highlighted the importance of considering human emotion in visualization design. Meanwhile, an increasing number of studies have been conducted to explore emotion-related factors. However, so far, this research area is still in its early stages and faces a set of challenges, such as the unclear definition of key concepts, the insufficient justification of why emotion is important in visualization design, and the lack of characterization of the design space of affective visualization design. To address these challenges, first, we conducted a literature review and identified three research lines that examined both emotion and data visualization. We clarified the differences between these research lines and kept 109 papers that studied or discussed how data visualization communicates and influences emotion. Then, we coded the 109 papers in terms of how they justified the legitimacy of considering emotion in visualization design (i.e., why emotion is important) and identified five argumentative perspectives. Based on these papers, we also identified 61 projects that practiced affective visualization design. We coded these design projects in three dimensions, including design fields (where), design tasks (what), and design methods (how), to explore the design space of affective visualization design.
Computer Graphics , Emotions , Humans
Geese evolved from migratory birds, and when they consume excessive high-energy feed, glucose is converted into triglycerides. A large amount of triglyceride deposition can induce incomplete oxidation of fatty acids, leading to lipid accumulation in the liver and the subsequent formation of fatty liver. In the Chaoshan region of Guangdong, China, Shitou geese develop a unique form of fatty liver through 24 h overfeeding of brown rice. To investigate the mechanisms underlying the formation of fatty liver in Shitou geese, we collected liver samples from normally fed and overfed geese. The results showed that the liver size in the treatment group was significantly larger, weighing 3.5 times more than that in the control group. Extensive infiltration of lipid droplets was observed in the liver upon staining of tissue sections. Biochemical analysis revealed that compared to the control group, the treatment group showed significantly elevated levels of total cholesterol (T-CHO), triglycerides (TG), and glycogen in the liver. However, no significant differences were observed in the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), which are common indicators of liver damage. Furthermore, we performed a combined transcriptomic and lipidomic analysis of the liver samples and identified 1,510 differentially expressed genes (DEGs) and 1,559 significantly differentially abundant metabolites (SDMs). The enrichment analysis of the DEGs revealed their enrichment in metabolic pathways, cellular process-related signaling pathways, and specific lipid metabolism pathways. We also conducted KEGG enrichment analysis of the SDMs and compared them with the enriched signaling pathways obtained from the DEGs. In this study, we identified 3 key signaling pathways involved in the formation of fatty liver in Shitou geese, namely, the biosynthesis of unsaturated fatty acids, glycerol lipid metabolism, and glycerophospholipid metabolism. In these pathways, genes such as glycerol-3-phosphate acyltransferase, mitochondrial (GPAM), 1-acylglycerol-3-phosphate O-acyltransferase 2 (AGPAT2), diacylglycerol O-acyltransferase 2 (DGAT2), lipase, endothelial (LIPG), lipoprotein lipase (LPL), phospholipase D family member 4 (PLD4), and phospholipase A2 group IVF (PLA2G4F) may regulate the synthesis of metabolites, including triacylglycerol (TG), phosphatidate (PA), 1,2-diglyceride (DG), phosphatidylethanolamine (PE), and phosphatidylcholine (PC). These genes and metabolites may play a predominant role in the development of fatty liver, ultimately promoting the accumulation of TG in the liver and leading to the progression of fatty liver.
Fatty Liver , Transcriptome , Animals , Geese/genetics , Geese/metabolism , Lipidomics , Glycerol/metabolism , Chickens/genetics , Fatty Liver/genetics , Fatty Liver/veterinary , Fatty Liver/metabolism , Liver/metabolism , Triglycerides/metabolism , Lipid Metabolism
Graph or network data are widely studied in both data mining and visualization communities to review the relationship among different entities and groups. The data facts derived from graph visual analysis are important to help understand the social structures of complex data, especially for data journalism. However, it is challenging for data journalists to discover graph data facts and manually organize correlated facts around a meaningful topic due to the complexity of graph data and the difficulty to interpret graph narratives. Therefore, we present an automatic graph facts generation system, Calliope-Net, which consists of a fact discovery module, a fact organization module, and a visualization module. It creates annotated node-link diagrams with facts automatically discovered and organized from network data. A novel layout algorithm is designed to present meaningful and visually appealing annotated graphs. We evaluate the proposed system with two case studies and an in-lab user study. The results show that Calliope-Net can benefit users in discovering and understanding graph data facts with visually pleasing annotated visualizations.
The exploratory visual analysis (EVA) of time series data uses visualization as the main output medium and input interface for exploring new data. However, for users who lack visual analysis expertise, interpreting and manipulating EVA can be challenging. Thus, providing guidance on EVA is necessary and two relevant questions need to be answered. First, how to recommend interesting insights to provide a first glance at data and help develop an exploration goal. Second, how to provide step-by-step EVA suggestions to help identify which parts of the data to explore. In this work, we present a reinforcement learning (RL)-based system, Visail, which generates EVA sequences to guide the exploration of time series data. As a user uploads a time series dataset, Visail can generate step-by-step EVA suggestions, while each step is visualized as an annotated chart combined with textual descriptions. The RL-based algorithm uses exploratory data analysis knowledge to construct the state and action spaces for the agent to imitate human analysis behaviors in data exploration tasks. In this way, the agent learns the strategy of generating coherent EVA sequences through a well-designed network. To evaluate the effectiveness of our system, we conducted an ablation study, a user study, and two case studies. The results of our evaluation suggested that Visail can provide effective guidance on supporting EVA on time series data.
Cardiac fibrosis is a pathological response characterized by excessive deposition of fibrous connective tissue within the heart. It typically occurs following cardiac injuries or diseases. However, the lack of suitable models for disease modeling and high-throughput drug discovery has hindered the establishment of an effective treatments for cardiac fibrosis. The emergence and rapid progress of stem-cell and lineage reprogramming technology offer an unprecedented opportunity to develop an improved humanized and patient-specific model for studying cardiac fibrosis, providing a platform for screening potential drugs and synchronously elucidating the underlying molecular mechanisms. Furthermore, reprogramming cardiac fibroblasts into cardiomyocyte-like cells to reduce scar volume and induce myocardial tissue regeneration is a promising approach in treating cardiac fibrosis. In this review, we summarize the current advancements in stem cell technologies applied to study cardiac fibrosis and provide insights for future investigations into its mechanisms, drug discovery as well as therapy method.
Ferroptosis is a distinctive form of iron-dependent cell death characterized by significant ultrastructural changes in mitochondria. Given the crucial involvement of mitochondria in various cellular processes such as reactive oxygen species production, energy metabolism, redox status, and iron metabolism, mounting evidence suggests a vital role of mitochondria in the regulation and execution of ferroptosis. Furthermore, there exists a strong correlation between ferroptosis and various diseases. In this review, we aim to summarize the mechanisms underlying the induction and defense of ferroptosis, emphasizing the influence of mitochondria on this intricate process. Additionally, we provide an overview of the role of ferroptosis in disease, particularly cancer, and elucidate the mechanisms by which drugs targeting mitochondria impact ferroptosis. By presenting a theoretical foundation and reference point, this review aims to contribute to both basic cell biology research and the investigation of clinically relevant diseases.
OBJECTIVES: Shifting macrophages towards an anti-inflammatory state is key in treating osteoarthritis (OA) by reducing inflammation and tissue damage. However, the underlying mechanisms guiding this shift remain largely undefined. STUB1, an E3 ubiquitin ligase, known for its regulatory role in macrophage polarization. This study aims to explore the function and underlying action mechanisms of STUB1 in OA. METHODS: An in vivo OA model was established in rats. Hematoxylin-Eosin and safranin O-fast green staining were performed to reveal the hispathological injuries in knee-joint tissues. Immunohistochemistry and flow cytometry were performed to detect the distribution of M1 and M2 macrophages. The inflammatory response (TNF-α and IL-6 levels) was evaluated by ELISA. In vitro, the interaction between STUB1 and NFR2 was determined by CO-IP and pull-down assays. After treated with LPS (an in vitro model of OA), the viability and apoptosis of chondrocytes were measured by CCK-8 and flow cytometry, respectively. RESULTS: Silencing STUB1 alleviated OA in rats, as indicated by reduced subchondral bone thickness, knee synovitis score, histopathological damages, and inflammatory response. STUB1 silencing also decreased M1 macrophages and increased M2 macrophages in both in vivo and in vitro settings. NRF2 was identified as a target of STUB1, with STUB1 mediating its ubiquitination. Silencing NRF2 reversed the effects of STUB1 silencing on inducing M2 macrophage polarization. Furthermore, silencing STUB1 upregulated NRF2 expression in LPS-treated chondrocytes, promoting cell viability and inhibiting apoptosis. CONCLUSION: Silencing STUB1 induces M2 macrophage polarization by inhibiting NRF2 ubiquitination, thereby contributing to the mitigation of OA.
NF-E2-Related Factor 2 , Osteoarthritis , Animals , Rats , Inflammation/pathology , Lipopolysaccharides/pharmacology , Macrophages/metabolism , NF-E2-Related Factor 2/metabolism , Osteoarthritis/pathology
Science has long been viewed as a key driver of economic growth and rising standards of living. Knowledge about how scientific advances support marketplace inventions is therefore essential for understanding the role of science in propelling real-world applications and technological progress. The increasing availability of large-scale datasets tracing scientific publications and patented inventions and the complex interactions among them offers us new opportunities to explore the evolving dual frontiers of science and technology at an unprecedented level of scale and detail. However, we lack suitable visual analytics approaches to analyze such complex interactions effectively. Here we introduce InnovationInsights, an interactive visual analysis system for researchers, research institutions, and policymakers to explore the complex linkages between science and technology, and to identify critical innovations, inventors, and potential partners. The system first identifies important associations between scientific papers and patented inventions through a set of statistical measures introduced by our experts from the field of the Science of Science. A series of visualization views are then used to present these associations in the data context. In particular, we introduce the Interplay Graph to visualize patterns and insights derived from the data, helping users effectively navigate citation relationships between papers and patents. This visualization thereby helps them identify the origins of technical inventions and the impact of scientific research. We evaluate the system through two case studies with experts followed by expert interviews. We further engage a premier research institution to test-run the system, helping its institution leaders to extract new insights for innovation. Through both the case studies and the engagement project, we find that our system not only meets our original goals of design, allowing users to better identify the sources of technical inventions and to understand the broad impact of scientific research; it also goes beyond these purposes to enable an array of new applications for researchers and research institutions, ranging from identifying untapped innovation potential within an institution to forging new collaboration opportunities between science and industry.
