Clinical factors and outcomes of spleen-conserving surgery versus total splenectomy in splenic injuries: A nationwide database study.

BACKGROUND: The objective of this study was to identify factors associated with the use of spleen-conserving surgeries, as well as patient outcomes, on a national scale. METHODS: This retrospective cohort study (2010-2015) included patients (age≥16 years) with splenic injury in the National Trauma Data Bank. Patients who received a total splenectomy or a spleen-conserving surgery were compared for demographics and clinical outcomes. RESULTS: During the study period, 18,425 received a total splenectomy and 1,825 received a spleen-conserving surgery. Total splenectomy was more likely to be performed for patients with age>65 (odds ratio [OR]: 0.63, p â€‹< â€‹0.001), systolic blood pressure<90 (OR: 0.63, p â€‹< â€‹0.001), heart rate>120 (OR: 0.83, p â€‹= â€‹0.007), and high-grade injuries (OR: 0.18, p â€‹< â€‹0.001). Penetrating trauma patients were more likely to undergo a spleen-conserving surgery (OR: 3.31, p â€‹< â€‹0.001). The use of spleen-conserving surgery was associated with a lower risk of pneumonia (OR: 0.79, p â€‹= â€‹0.009) and venous thromboembolism (OR: 0.72, p â€‹= â€‹0.006). CONCLUSIONS: Spleen-conserving surgeries may be considered for patients with penetrating trauma, age<65, hemodynamic stability, and low-grade injuries. Spleen-conserving surgeries have decreased risk of pneumonia and venous thromboembolism.

Visualizing Large-Scale Spatial Time Series with GeoChron.

In geo-related fields such as urban informatics, atmospheric science, and geography, large-scale spatial time (ST) series (i.e., geo-referred time series) are collected for monitoring and understanding important spatiotemporal phenomena. ST series visualization is an effective means of understanding the data and reviewing spatiotemporal phenomena, which is a prerequisite for in-depth data analysis. However, visualizing these series is challenging due to their large scales, inherent dynamics, and spatiotemporal nature. In this study, we introduce the notion of patterns of evolution in ST series. Each evolution pattern is characterized by 1) a set of ST series that are close in space and 2) a time period when the trends of these ST series are correlated. We then leverage Storyline techniques by considering an analogy between evolution patterns and sessions, and finally design a novel visualization called GeoChron, which is capable of visualizing large-scale ST series in an evolution pattern-aware and narrative-preserving manner. GeoChron includes a mining framework to extract evolution patterns and two-level visualizations to enhance its visual scalability. We evaluate GeoChron with two case studies, an informal user study, an ablation study, parameter analysis, and running time analysis.

In vitro acne disease model from inertial focusing effect for studying the interactions between sebocyte glands and macrophages.

Acne is one of the most widespread skin diseases. The acne mechanism is intricate, involving interactions between different types of cells (i.e., sebocytes and macrophages). One of the challenges in studying the mechanism of acne is that current in vitro culture methods cannot reflect the 3D cellular environment in the tissue, including inflammatory stimuli and cellular interactions especially the interactions between sebocytes and immune cells. To solve this issue, we generated an in vitro acne disease model consisting of 3D artificial sebocyte glands and macrophages through the inertial focusing effect method. Using this model, we produced a controllable inflammatory environment similar to the acne pathogenetic process in the skin. The 3D artificial sebocyte glands and macrophages can be separated for analyzing each cell type, assisting the in-depth understanding of the acne mechanism. This study indicates that proinflammatory macrophages promote lipid accumulation and induce oxidative stress in sebocyte glands. Additionally, in an inflammatory environment, sebocyte glands induce macrophage polarization into the M1 phenotype. Employing this model for drug screening, we also demonstrated that, cannabidiol (CBD), a clinically investigated drug, is effective in restoring lipid accumulation, oxidative stress, inflammatory cytokines and macrophage polarization in the acne disease.

3D artificial sebocyte glands from inertial focusing effect for facile and flexible analysis of light damage and drug screening.

The sebaceous gland is a neuro-immuno-endocrine organ responsible for maintaining regular skin functions. Overdose exposure of UV and visible light (e.g., blue light) can cause sebocyte gland function disorders or even different diseases (e.g., chronic actinic dermatitis). Studying the mechanism of light-induced damage in sebaceous glands has been challenging, since ex vivo culture of sebaceous glands is difficult due to its short life in culture medium. To address this issue, a versatile 3D artificial sebocyte gland model was established using the inertial focusing effect for studying the impact of light damage and screening potential drugs. The artificial sebocyte gland exhibited specific biological function and structure similar to natural sebocyte glands. Using this artificial sebocyte gland, the interactions between the artificial organ and blue light or UV were studied. The results indicated that UV and blue light upregulated lipid secretion and downregulated cell viability within the sebocytes. Light damage intensified oxidative stress and promoted pro-inflammation cytokines (i.e., IL-1ß and TNF-α) production in the artificial sebocytes. Additionally, the therapeutic effects of cannabidiol, a clinically tested drug for treating acne, was also indicated on restoring light damaged sebaceous gland functions. These results indicate that the 3D artificial sebocyte gland could be a versatile, fast, and low-cost platform for skincare studies or drug screening.

MetaGlyph: Automatic Generation of Metaphoric Glyph-based Visualization.

Glyph-based visualization achieves an impressive graphic design when associated with comprehensive visual metaphors, which help audiences effectively grasp the conveyed information through revealing data semantics. However, creating such metaphoric glyph-based visualization (MGV) is not an easy task, as it requires not only a deep understanding of data but also professional design skills. This paper proposes MetaGlyph, an automatic system for generating MGVs from a spreadsheet. To develop MetaGlyph, we first conduct a qualitative analysis to understand the design of current MGVs from the perspectives of metaphor embodiment and glyph design. Based on the results, we introduce a novel framework for generating MGVs by metaphoric image selection and an MGV construction. Specifically, MetaGlyph automatically selects metaphors with corresponding images from online resources based on the input data semantics. We then integrate a Monte Carlo tree search algorithm that explores the design of an MGV by associating visual elements with data dimensions given the data importance, semantic relevance, and glyph non-overlap. The system also provides editing feedback that allows users to customize the MGVs according to their design preferences. We demonstrate the use of MetaGlyph through a set of examples, one usage scenario, and validate its effectiveness through a series of expert interviews.

Mental contamination among people in China: A replication of a moral manipulation experiment.

BACKGROUND AND OBJECTIVES: Mental contamination can be evoked by thoughts, images, and memories without having physically contacted any contaminants. Although several experiments have investigated the mechanism of mental contamination, none has been conducted in the Chinese socio-cultural context. Considering the potential cultural-sensitivity of mental contamination we replicated Elliott and Radomsky's experiment (2009) to examine whether an imagined immoral act would prompt mental contamination among female university students in China. METHODS: We assigned participants (n = 148) to 4 conditions in which they listened to an audio recording asking them to imagine that they had (a) shared a consensual kiss with a moral man, (b) shared a consensual kiss with an immoral man, (c) received a non-consensual kiss from a moral man, (d) or received a non-consensual kiss from an immoral man. Afterwards, they completed questionnaires, and their personal hygiene behaviours were recorded. RESULTS: As in the precedent study, participants who imagined a non-consensual kiss reported greater feelings of mental contamination than ones who imagined a consensual kiss. Unlike in that study, however, imagining a consensual kiss from a moral man also aroused strong mental contamination. LIMITATIONS: It remains unclear which aspect of immoral acts (information or behaviour) weigh more in evoking mental contamination. CONCLUSIONS: The results suggest that imagining sexually immoral acts can evoke feelings of mental contamination among people in China. Nevertheless, cultural beliefs and attitude towards sexuality may play a role of causing the discrepancies.

Psychological risk and protective factors associated with depression among older adults in mainland China: A systematic review and meta-analysis.

BACKGROUND: Although geriatric depression is a public health concern in mainland China, findings about its psychological risk and protective factors have been inconsistent, and its prevention programmes have been deficient. To improve interventions for geriatric depression, we designed a study to systematically estimate the effect size of those factors. METHODS: To identify psychological risk and protective factors of geriatric depression, we conducted two independent literature searches in English- and Chinese-language databases, and we used a random effects model to analyse effect sizes. RESULTS: We identified 15 psychological risk and protective factors in 66 studies. The pooled effect sizes between the factors and geriatric depression ranged from 0.129 to 0.567. Self-esteem displayed a large effect size with depression (r = -0.567), whereas medium-to-large effect sizes emerged between geriatric depression and negative perceptions of age (r = 0.452), resilience (r = -0.426), rumination (r = 0.432), neuroticism (r = 0.381), extraversion (r = -0.363), self-efficacy (r = -0.357), sense of control (r = -0.343), and negative coping strategies (r = 0.315). The sample's mean age, the percentage of women sampled, and the research quality of the studies significantly moderated certain associations. LIMITATIONS: Large heterogeneity, the inexplicability of causal relationships between the factors and geriatric depression, and the lack of generalisability to special groups limit our findings. CONCLUSIONS: Self-esteem and perceptions of age are potential targets for improving interventions for geriatric depression in mainland China, which should continue to be developed and assessed for their effectiveness.

A Visualization Approach for Monitoring Order Processing in E-Commerce Warehouse.

The efficiency of warehouses is vital to e-commerce. Fast order processing at the warehouses ensures timely deliveries and improves customer satisfaction. However, monitoring, analyzing, and manipulating order processing in the warehouses in real time are challenging for traditional methods due to the sheer volume of incoming orders, the fuzzy definition of delayed order patterns, and the complex decision-making of order handling priorities. In this paper, we adopt a data-driven approach and propose OrderMonitor, a visual analytics system that assists warehouse managers in analyzing and improving order processing efficiency in real time based on streaming warehouse event data. Specifically, the order processing pipeline is visualized with a novel pipeline design based on the sedimentation metaphor to facilitate real-time order monitoring and suggest potentially abnormal orders. We also design a novel visualization that depicts order timelines based on the Gantt charts and Marey's graphs. Such a visualization helps the managers gain insights into the performance of order processing and find major blockers for delayed orders. Furthermore, an evaluating view is provided to assist users in inspecting order details and assigning priorities to improve the processing performance. The effectiveness of OrderMonitor is evaluated with two case studies on a real-world warehouse dataset.

VideoModerator: A Risk-aware Framework for Multimodal Video Moderation in E-Commerce.

Video moderation, which refers to remove deviant or explicit content from e-commerce livestreams, has become prevalent owing to social and engaging features. However, this task is tedious and time consuming due to the difficulties associated with watching and reviewing multimodal video content, including video frames and audio clips. To ensure effective video moderation, we propose VideoModerator, a risk-aware framework that seamlessly integrates human knowledge with machine insights. This framework incorporates a set of advanced machine learning models to extract the risk-aware features from multimodal video content and discover potentially deviant videos. Moreover, this framework introduces an interactive visualization interface with three views, namely, a video view, a frame view, and an audio view. In the video view, we adopt a segmented timeline and highlight high-risk periods that may contain deviant information. In the frame view, we present a novel visual summarization method that combines risk-aware features and video context to enable quick video navigation. In the audio view, we employ a storyline-based design to provide a multi-faceted overview which can be used to explore audio content. Furthermore, we report the usage of VideoModerator through a case scenario and conduct experiments and a controlled user study to validate its effectiveness.

Real-Time Visual Analysis of High-Volume Social Media Posts.

Breaking news and first-hand reports often trend on social media platforms before traditional news outlets cover them. The real-time analysis of posts on such platforms can reveal valuable and timely insights for journalists, politicians, business analysts, and first responders, but the high number and diversity of new posts pose a challenge. In this work, we present an interactive system that enables the visual analysis of streaming social media data on a large scale in real-time. We propose an efficient and explainable dynamic clustering algorithm that powers a continuously updated visualization of the current thematic landscape as well as detailed visual summaries of specific topics of interest. Our parallel clustering strategy provides an adaptive stream with a digestible but diverse selection of recent posts related to relevant topics. We also integrate familiar visual metaphors that are highly interlinked for enabling both explorative and more focused monitoring tasks. Analysts can gradually increase the resolution to dive deeper into particular topics. In contrast to previous work, our system also works with non-geolocated posts and avoids extensive preprocessing such as detecting events. We evaluated our dynamic clustering algorithm and discuss several use cases that show the utility of our system.

Prevalence of depression among older adults living in care homes in China: A systematic review and meta-analysis.

OBJECTIVES: Despite the large number of older adults living in care homes in China, the reported prevalence of depression in such settings has varied greatly, while its pooled overall prevalence has remained unknown. In response, our systematic review and meta-analysis were designed to provide accurate, comprehensive evidence of the prevalence of geriatric depression in care homes in China. METHODS: Literature searches were conducted independently by two investigators in English- and Chinese-language databases from database inception through January 2020. The prevalence of depressive symptoms in late life was analyzed with a random effects model. RESULTS: In 69 studies addressing older adults living in care homes in China, the pooled overall prevalence of depressive symptoms was 36.8% (95% CI, 32.7%-41.1%). Respective estimates for mild and moderate-to-severe depressive symptoms were 29.1% (95% CI, 25.2%-32.7%) and 9.1% (95% CI, 7.5%-11.0%). Subgroup analyses revealed significant differences in the prevalence of late-life depression in care homes according to the type of care home, the individual's socioeconomic status, and the measurement instrument(s) used. Meta-regression analysis indicated that the prevalence of late-life depression among older adults living in care homes generally rose from 1991 to 2019. CONCLUSIONS: Given the high prevalence of geriatric depression in China's care homes, future studies should examine its risk and protective factors in those settings.

Multifunctional Laser-Induced Graphene Papers with Combined Defocusing and Grafting Processes for Patternable and Continuously Tunable Wettability from Superlyophilicity to Superlyophobicity.

Functional surfaces with tunable and patternable wettability have attracted significant research interests because of remarkable advantages in biomedicine, environmental, and energy storage applications. Based on combined defocusing and grafting strategy for processing laser-induced graphene papers (LIGPs) with variable surface roughness (58.18-6.08 µm) and F content (0-25.9%), their wettability can be tuned continuously from superlyophilicity (contact angle CA ≈ 0° ) to superlyophobicity (CA > 150° ), for various liquids with a wide range of surface tensions from 27.5 to 72.8 mN m-1 . In addition to reaching multiple wetting characteristics including amphiphilic, amphiphobic, and hydrophobic-oleophilic states, three designable processes are further developed for achieving LIGPs with various wetting patterns, including hydrophilic arrays or channels, hydrophobic-to-hydrophilic gradients, and Janus. Activated by the customly designed structures and properties, multifunctional and multi-scenario applications are successfully attempted, including 2D-/3D- directional cell cultivation, water transportation diode, self-triggered liquid transfer & collection, etc.

Prevalence of depressive symptoms among older adults in mainland China: A systematic review and meta-analysis.

BACKGROUND: To date, the reported prevalence of late-life depression in China has varied considerably, and the pooled overall prevalence of depressive symptoms among older adults in China and the tendency of the rate to change in the past 30 years have remained unknown. Thus, our study was designed to form an accurate and comprehensive picture of the recent prevalence of depressive symptoms among older adults in China. METHODS: Literature searches were conducted independently by two investigators in English- and Chinese-language databases from database inception to January 2020. The prevalence of depressive symptoms was analysed with a random effects model. RESULTS: In the 81 eligible studies (n = 261,697) identified, the pooled overall prevalence of depressive symptoms among older adults in China was 20.0% (95% CI, 17.5%-22.8%), with high heterogeneity, Q = 22,947.0, I2 = 99.7%, p < .001. Subgroup analyses revealed significant differences in the prevalence of late-life depression depending upon gender, marital status, socio-economic status, and measurement scale(s) used. Meta-regression indicated that the prevalence of depressive symptoms among older adults in China increased from the 1990s to the 2000s but slightly decreased from the 2000s to the 2010s. LIMITATIONS: Significant heterogeneity among the studies reviewed was unavoidable, and the findings was not generalisable to all regions in China. CONCLUSIONS: Depressive symptoms are common among older adults in China, and policies should be developed that consider vulnerable older adults in particular.

PlotThread: Creating Expressive Storyline Visualizations using Reinforcement Learning.

Storyline visualizations are an effective means to present the evolution of plots and reveal the scenic interactions among characters. However, the design of storyline visualizations is a difficult task as users need to balance between aesthetic goals and narrative constraints. Despite that the optimization-based methods have been improved significantly in terms of producing aesthetic and legible layouts, the existing (semi-) automatic methods are still limited regarding 1) efficient exploration of the storyline design space and 2) flexible customization of storyline layouts. In this work, we propose a reinforcement learning framework to train an AI agent that assists users in exploring the design space efficiently and generating well-optimized storylines. Based on the framework, we introduce PlotThread, an authoring tool that integrates a set of flexible interactions to support easy customization of storyline visualizations. To seamlessly integrate the AI agent into the authoring process, we employ a mixed-initiative approach where both the agent and designers work on the same canvas to boost the collaborative design of storylines. We evaluate the reinforcement learning model through qualitative and quantitative experiments and demonstrate the usage of PlotThread using a collection of use cases.

Culturally adapted and lay-delivered cognitive behaviour therapy for older adults with depressive symptoms in rural China: a pilot trial.

BACKGROUND: Late-life depression issues in developing countries are challenging because of understaffing in mental health. Cognitive behavioural therapy (CBT) is effective for treating depression. AIM: This pilot trial examined the adherence and effectiveness of an eight-session adapted CBT delivered by trained lay health workers for older adults with depressive symptoms living in rural areas of China, compared with the usual care. METHOD: Fifty with screen-positive depression were randomly assigned to the CBT arm or the care as usual (CAU) arm. The primary outcomes were the session completion of older adults and changes in depressive symptoms, assessed using the Geriatric Depression Scale (GDS). RESULTS: The majority (19/24) of participants in the CBT arm completed all sessions. Mixed-effect linear regression showed that the CBT reduced more GDS scores over time compared with CAU. CONCLUSION: Lay-delivered culturally adapted CBT is potentially effective for screen-positive late-life depression.

Perspectives on Triple-Negative Breast Cancer: Current Treatment Strategies, Unmet Needs, and Potential Targets for Future Therapies.

Triple-negative breast cancer (TNBC), characterized by the absence or low expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2), is the most aggressive subtype of breast cancer. TNBC accounts for about 15% of breast cancer cases in the U.S., and is known for high relapse rates and poor overall survival (OS). Chemo-resistant TNBC is a genetically diverse, highly heterogeneous, and rapidly evolving disease that challenges our ability to individualize treatment for incomplete responders and relapsed patients. Currently, the frontline standard chemotherapy, composed of anthracyclines, alkylating agents, and taxanes, is commonly used to treat high-risk and locally advanced TNBC. Several FDA-approved drugs that target programmed cell death protein-1 (Keytruda) and programmed death ligand-1 (Tecentriq), poly ADP-ribose polymerase (PARP), and/or antibody drug conjugates (Trodelvy) have shown promise in improving clinical outcomes for a subset of TNBC. These inhibitors that target key genetic mutations and specific molecular signaling pathways that drive malignant tumor growth have been used as single agents and/or in combination with standard chemotherapy regimens. Here, we review the current TNBC treatment options, unmet clinical needs, and actionable drug targets, including epidermal growth factor (EGFR), vascular endothelial growth factor (VEGF), androgen receptor (AR), estrogen receptor beta (ERß), phosphoinositide-3 kinase (PI3K), mammalian target of rapamycin (mTOR), and protein kinase B (PKB or AKT) activation in TNBC. Supported by strong evidence in developmental, evolutionary, and cancer biology, we propose that the K-RAS/SIAH pathway activation is a major tumor driver, and SIAH is a new drug target, a therapy-responsive prognostic biomarker, and a major tumor vulnerability in TNBC. Since persistent K-RAS/SIAH/EGFR pathway activation endows TNBC tumor cells with chemo-resistance, aggressive dissemination, and early relapse, we hope to design an anti-SIAH-centered anti-K-RAS/EGFR targeted therapy as a novel therapeutic strategy to control and eradicate incurable TNBC in the future.

Unmet Clinical Need: Developing Prognostic Biomarkers and Precision Medicine to Forecast Early Tumor Relapse, Detect Chemo-Resistance and Improve Overall Survival in High-Risk Breast Cancer.

Chemo-resistant breast cancer is a major barrier to curative treatment for a significant number of women with breast cancer. Neoadjuvant chemotherapy (NACT) is standard first- line treatment for most women diagnosed with high-risk TNBC, HER2+, and locally advanced ER+ breast cancer. Current clinical prognostic tools evaluate four clinicopathological factors: Tumor size, LN status, pathological stage, and tumor molecular subtype. However, many similarly treated patients with identical residual cancer burden (RCB) following NACT experience distinctly different tumor relapse rates, clinical outcomes and survival. This problem is particularly apparent for incomplete responders with a high-risk RCB classification following NACT. Therefore, there is a pressing need to identify new prognostic and predictive biomarkers, and develop novel curative therapies to augment current standard of care (SOC) treatment regimens to save more lives. Here, we will discuss these unmet needs and clinical challenges that stand in the way of precision medicine and personalized cancer therapy.

Comparative evaluation of the clinical safety and efficiency of supraclavicular and infraclavicular approaches for subclavian venous catheterization in adults: A meta-analysis.

BACKGROUND: In this meta-analysis, we investigated the success rate of subclavian venous catheterization (SVC) as well as the incidence of related complications when performed via the supraclavicular (SC) or traditional infraclavicular (IC) approaches. METHODS: Ignoring the original language, we identified and analyzed eight randomized controlled trials (RCTs) published on or before December 30, 2018, after searching the following five bibliographic databases: PubMed, Springer, Medline, EMBASE, and the Cochrane Library. All included studies compared the clinical safety and efficiency of the SC and IC approaches for SVC in adults. The Cochrane Collaboration's Risk of Bias Tool was used to evaluate the methodological quality of each RCT. Cannulation failure rates and the incidence of malposition were regarded as the primary outcome measures. Secondary outcome measures included cannulation access time and the incidence of pneumothorax and artery puncture. RESULTS: Failure rates were significantly lower for SVC via the SC approach than via the IC approach [odds ratio, 0.66; 95% confidence interval (CI), 0.47 to 0.93]. The SC approach was also associated with a decreased incidence of catheter malposition, relative to that observed for the IC approach [odds ratio, 0.24; 95% CI, 0.13 to 0.46]. The SC approach did not reduce the time required for cannulation [mean difference, -74.74; 95% CI, -157.80 to 8.33], and there were no differences in the incidence of artery puncture [odds ratio, 0.60; 95% CI, 0.29 to 1.23] or pneumothorax [odds ratio, 0.89; 95% CI, 0.33 to 2.40]. CONCLUSION: Our findings suggest that SVC via the SC approach should be utilized in adults.

Harnessing the layer-by-layer assembly technique to design biomaterials vaccines for immune modulation in translational applications.

The existence of challenging diseases such as cancers, HIV and Zika requires developing new vaccines that can generate tunable and robust immune responses against the diseases. Biomaterials-based techniques have been broadly explored for designing vaccines that can produce controllable and potent immunity. Among the existing biomaterials-based strategies, the layer-by-layer (LbL) assembly technique is remarkably attractive in vaccine design due to its unique features such as programmed and versatile cargo loading, cargo protection, co-delivery, juxtaposing of immune signals, etc. In this work, we reviewed the existing LbL-based vaccine design techniques for translational applications. Specifically, we discussed nanovaccines constructed by coating polyelectrolyte multilayers (PEMs) on nanoparticles, microcapsule vaccines assembled from PEMs, polyplex/complex vaccines condensed from charged materials and microneedle vaccines deposited with PEMs, highlighting the employment of these techniques to promote immunity against diseases ranging from cancers to infectious and autoimmune diseases (i.e., HIV, influenza, multiple sclerosis, etc.). Additionally, the review specifically emphasized using LbL-based vaccine technologies for tuning the cellular and molecular pathways, demonstrating the unique advantages presented by these vaccination strategies. These studies showed the versatility and potency of using LbL-based techniques for designing the next generation of biomaterials vaccines for translational purposes.

iStoryline: Effective Convergence to Hand-drawn Storylines.

Storyline visualization techniques have progressed significantly to generate illustrations of complex stories automatically. However, the visual layouts of storylines are not enhanced accordingly despite the improvement in the performance and extension of its application area. Existing methods attempt to achieve several shared optimization goals, such as reducing empty space and minimizing line crossings and wiggles. However, these goals do not always produce optimal results when compared to hand-drawn storylines. We conducted a preliminary study to learn how users translate a narrative into a hand-drawn storyline and check whether the visual elements in hand-drawn illustrations can be mapped back to appropriate narrative contexts. We also compared the hand-drawn storylines with storylines generated by the state-of-the-art methods and found they have significant differences. Our findings led to a design space that summarizes 1) how artists utilize narrative elements and 2) the sequence of actions artists follow to portray expressive and attractive storylines. We developed iStoryline, an authoring tool for integrating high-level user interactions into optimization algorithms and achieving a balance between hand-drawn storylines and automatic layouts. iStoryline allows users to create novel storyline visualizations easily according to their preferences by modifying the automatically generated layouts. The effectiveness and usability of iStoryline are studied with qualitative evaluations.