The role of positive emotion in harmful health behavior: Implications for theory and public health campaigns.

Meta-analyses have concluded that positive emotions do not reduce appetitive risk behaviors (risky behaviors that fulfill appetitive or craving states, such as smoking and excessive alcohol use). We propose that this conclusion is premature. Drawing on the Appraisal Tendency Framework and related theories of emotion and decision-making, we hypothesized that gratitude (a positive emotion) can decrease cigarette smoking, a leading cause of premature death globally. A series of multimethod studies provided evidence supporting our hypothesis (collective N = 34,222). Using nationally representative US samples and an international sample drawn from 87 countries, Studies 1 and 2 revealed that gratitude was inversely associated with likelihood of smoking, even after accounting for numerous covariates. Other positive emotions (e.g., compassion) lacked such consistent associations, as expected. Study 3, and its replication, provided further support for emotion specificity: Experimental induction of gratitude, unlike compassion or sadness, reduced cigarette craving compared to a neutral state. Study 4, and its replication, showed that inducing gratitude causally increased smoking cessation behavior, as evidenced by enrollment in a web-based cessation intervention. Self-reported gratitude mediated the effects in both experimental studies. Finally, Study 5 found that current antismoking messaging campaigns by the US Centers for Disease Control and Prevention primarily evoked sadness and compassion, but seldom gratitude. Together, our studies advance understanding of positive emotion effects on appetitive risk behaviors; they also offer practical implications for the design of public health campaigns.

Reassessing the role of urban green space in air pollution control.

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

Civilian national service programs can powerfully increase youth voter turnout.

Low rates of youth voting are a feature of contemporary democracies the world over, with the United States having some of the lowest youth turnout rates in the world. However, far too little is known about how to address the dismal rates of youth voter participation found in many advanced democracies. In this paper, we examine the causal effect of a potentially scalable solution that has attracted renewed interest today: voluntary national service programs targeted at the youth civilian population. Leveraging the large pool of young people who apply each year to participate in the Teach For America (TFA) program-a prominent voluntary national service organization in the United States that integrates college graduates into teaching roles in low-income communities for 2 y-we examine the effect of service participation on voter turnout. To do so, we match TFA administrative records to large-scale nationwide voter files and employ a fuzzy regression discontinuity design around the recommended admittance cutoff for the TFA program. We find that serving as a teacher in the Teach For America national service program has a large effect on civic participation-substantially increasing voter turnout rates among applicants admitted to the program. This effect is noticeably larger than that of previous efforts to increase youth turnout. Our results suggest that civilian national service programs targeted at young people have great promise in helping to narrow the stubborn and enduring political engagement gap between younger and older citizens.

European Society of Cardiology: the 2023 Atlas of Cardiovascular Disease Statistics.

This report from the European Society of Cardiology (ESC) Atlas Project updates and expands upon the 2021 report in presenting cardiovascular disease (CVD) statistics for the ESC member countries. This paper examines inequalities in cardiovascular healthcare and outcomes in ESC member countries utilizing mortality and risk factor data from the World Health Organization and the Global Burden of Disease study with additional economic data from the World Bank. Cardiovascular healthcare data were collected by questionnaire circulated to the national cardiac societies of ESC member countries. Statistics pertaining to 2022, or latest available year, are presented. New material in this report includes contemporary estimates of the economic burden of CVD and mortality statistics for a range of CVD phenotypes. CVD accounts for 11% of the EU's total healthcare expenditure. It remains the most common cause of death in ESC member countries with over 3 million deaths per year. Proportionately more deaths from CVD occur in middle-income compared with high-income countries in both females (53% vs. 34%) and males (46% vs. 30%). Between 1990 and 2021, median age-standardized mortality rates (ASMRs) for CVD decreased by median >50% in high-income ESC member countries but in middle-income countries the median decrease was <12%. These inequalities between middle- and high-income ESC member countries likely reflect heterogeneous exposures to a range of environmental, socioeconomic, and clinical risk factors. The 2023 survey suggests that treatment factors may also contribute with middle-income countries reporting lower rates per million of percutaneous coronary intervention (1355 vs. 2330), transcatheter aortic valve implantation (4.0 vs. 153.4) and pacemaker implantation (147.0 vs. 831.9) compared with high-income countries. The ESC Atlas 2023 report shows continuing inequalities in the epidemiology and management of CVD between middle-income and high-income ESC member countries. These inequalities are exemplified by the changes in CVD ASMRs during the last 30 years. In the high-income ESC member countries, ASMRs have been in steep decline during this period but in the middle-income countries declines have been very small. There is now an important need for targeted action to reduce the burden of CVD, particularly in those countries where the burden is greatest.

A Bioinspired Gradient Design Strategy for Cellulose-Based Electromagnetic Wave Absorbing Structural Materials.

Cellulose nanofiber (CNF) possesses excellent intrinsic properties, and many CNF-based high-performance structural and functional materials have been developed recently. However, the coordination of the mechanical properties and functionality is still a considerable challenge. Here, a CNF-based structural material is developed by a bioinspired gradient structure design using hollow magnetite nanoparticles and the phosphorylation-modified CNF as building blocks, which simultaneously achieves a superior mechanical performance and electromagnetic wave absorption (EMA) ability. Benefiting from the gradient design, the flexural strength of the structural material reached ∼205 MPa. Meanwhile, gradient design improves impedance matching, contributing to the high EMA ability (-59.5 dB) and wide effective absorption width (5.20 GHz). Besides, a low coefficient of thermal expansion and stable storage modulus was demonstrated as the temperature changes. The excellent mechanical, thermal, and EMA performance exhibited great potential for application in stealth equipment and electromagnetic interference protecting electronic packaging materials.

Effectiveness of mailed outreach and patient navigation to promote HCC screening process completion: a multicentre pragmatic randomised clinical trial.

BACKGROUND: Hepatocellular carcinoma (HCC) is plagued by failures across the cancer care continuum, leading to frequent late-stage diagnoses and high mortality. We evaluated the effectiveness of mailed outreach invitations plus patient navigation to promote HCC screening process completion in patients with cirrhosis. METHODS: Between April 2018 and September 2021, we conducted a multicentre pragmatic randomised clinical trial comparing mailed outreach plus patient navigation for HCC screening (n=1436) versus usual care with visit-based screening (n=1436) among patients with cirrhosis at three US health systems. Our primary outcome was screening process completion over a 36-month period, and our secondary outcome was the proportion of time covered (PTC) by screening. All patients were included in intention-to-screen analyses. RESULTS: All 2872 participants (median age 61.3 years; 32.3% women) were included in intention-to-screen analyses. Screening process completion was observed in 6.6% (95% CI: 5.3% to 7.9%) of patients randomised to outreach and 3.3% (95% CI: 2.4% to 4.3%) of those randomised to usual care (OR 2.05, 95% CI: 1.44 to 2.92). The intervention increased HCC screening process completion across most subgroups including age, sex, race and ethnicity, Child-Turcotte-Pugh class and health system. PTC was also significantly higher in the outreach arm than usual care (mean 37.5% vs 28.2%; RR 1.33, 95% CI: 1.31 to 1.35). Despite screening underuse, most HCC in both arms were detected at an early stage. CONCLUSION: Mailed outreach plus navigation significantly increased HCC screening process completion versus usual care in patients with cirrhosis, with a consistent effect across most examined subgroups. However, screening completion remained suboptimal in both arms, underscoring a need for more intensive interventions. TRIAL REGISTRATION NUMBER: NCT02582918.

MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry.

BACKGROUND: As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved. RESULTS: Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support. CONCLUSIONS: In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets.

BACKGROUND: Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. RESULTS: Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. CONCLUSIONS: NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .

MitoFish, MitoAnnotator, and MiFish Pipeline: Updates in 10 Years.

MitoFish, MitoAnnotator, and MiFish Pipeline are comprehensive databases of fish mitochondrial genomes (mitogenomes), accurate annotation software of fish mitogenomes, and a web platform for metabarcoding analysis of fish mitochondrial environmental DNA (eDNA), respectively. The MitoFish Suite currently receives over 48,000 visits worldwide every year; however, the performance and usefulness of the online platforms can still be improved. Here, we present essential updates on these platforms, including an enrichment of the reference data sets, an enhanced searching function, substantially faster genome annotation and eDNA analysis with the denoising of sequencing errors, and a multisample comparative analysis function. These updates have made our platform more intuitive, effective, and reliable. These updated platforms are freely available at http://mitofish.aori.u-tokyo.ac.jp/.

Progress report of a cross-organ and biomarker-based basket-type clinical trial: BELIEVE Trial.

Cancer genomic medicine using next-generation sequencers has been developing. However, the number of patients who could receive genomically matched therapy is limited because off-label use or patient-oriented compassionate use was not permitted under National Health Insurance in Japan. To improve patient drug accessibility, we initiated a biomarker-based basket-type clinical trial (NCCH1901) in October 2019 under patient-proposed healthcare services. We listed the drugs that had high medical needs but were not covered by National Healthcare Insurance. Then we included these drugs before patient proposal so that they could access off-label drugs soon after they had the results of CGP tests. All drugs were provided free of charge by pharmaceutical companies. The objective was to administer off-label drugs and to collect efficacy and safety data for these drugs. The primary endpoint was the response rate based on the best overall response for up to 16 weeks. As of January 31, 2022, we included 18 drug cohorts and 295 patients were treated in this study. The most common cancer was brain tumor, followed by carcinoma of endocrine organs and colorectal cancer. BRAF mutations and ERBB2 amplifications were the frequent genomic abnormalities to be enrolled. This study was one way to access off-label drugs, and contributed significantly to providing treatment opportunities for patients in Japan.

Using unsupervised clustering approaches to identify common mental health profiles and associated mental health-care service-use patterns in Ontario, Canada.

Mental health is a complex, multidimensional concept that goes beyond clinical diagnoses, including psychological distress, life stress, and well-being. In this study, we aimed to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service-use patterns. The data source was the 2012 Canadian Community Health Survey-Mental Health, linked to administrative health-care data; all Ontario, Canada, adult respondents were included. We used a partitioning around medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them according to their sociodemographic and service-use characteristics. We identified 4 groups with distinct mental health profiles, including 1 group that met the clinical threshold for a depressive diagnosis, with the remaining 3 groups expressing differences in positive mental health, life stress, and self-rated mental health. The 4 groups had different age, employment, and income profiles and exhibited differential access to mental health-care services. This study represents the first step in identifying complex profiles of mental health at the population level in Ontario. Further research is required to better understand the potential causes and consequences of belonging to each of the mental health profiles identified. This article is part of a Special Collection on Mental Health.

Mitigating the impact of blood shortages in England.

The supply of blood components and products in sufficient quantities is key to any effective health care system. This report describes the challenges faced by the English blood service, NHS Blood and Transplant (NHSBT), towards the end of the COVID-19 pandemic, which in October 2022 led to an Amber Alert being declared to hospitals indicating an impending blood shortage. The impact on the hospital transfusion services and clinical users is explained. The actions taken by NHSBT to mitigate the blood supply challenges and ensure equity of transfusion support for hospitals in England including revisions to the national blood shortage plans are described. This report focuses on the collaboration and communication between NHSBT, NHS England (NHSE), Department of Health and Social Care (DHSC), National Blood Transfusion Committee (NBTC), National Transfusion Laboratory Managers Advisory Group for NBTC (NTLM), National Transfusion Practitioners Network, the medical Royal Colleges and clinical colleagues across the NHS.

Commercial Versus Medicaid Insurance and Use of High-Priced Anticancer Treatments.

BACKGROUND: Because the markups on cancer drugs vary by payor, providers' financial incentive to use high-price drugs is differential according to each patient's insurance type. We evaluated the association between patient insurer (commercial vs Medicaid) and the use of high-priced cancer treatments. MATERIALS AND METHODS: We linked cancer registry, administrative claims, and demographic data for individuals diagnosed with cancer in North Carolina from 2004 to 2011, with either commercial or Medicaid insurance. We selected cancers with multiple FDA-approved, guideline-recommended chemotherapy options and large price differences between treatment options: advanced colorectal, lung, and head and neck cancer. The outcome was a receipt of a higher-priced option, and the exposure was insurer: commercial versus Medicaid. We estimated risk ratios (RRs) for the association between insurer and higher-priced treatment using log-binomial models with inverse probability of exposure weights. RESULTS: Of 812 patients, 209 (26%) had Medicaid. The unadjusted risk of receiving higher-priced treatment was 36% (215/603) for commercially insured and 27% (57/209) for Medicaid insured (RR: 1.31, 95% CI: 1.02-1.67). After adjustment for confounders the association was attenuated (RR: 1.15, 95% CI: 0.81-1.65). Exploratory subgroup analysis suggested that commercial insurance was associated with increased receipt of higher-priced treatment among patients treated by non-NCI-designated providers (RR: 1.53, 95% CI: 1.14-2.04). CONCLUSIONS: Individuals with Medicaid and commercial insurance received high-priced treatments in similar proportion, after accounting for differences in case mix. However, modification by provider characteristics suggests that insurance type may influence treatment selection for some patient groups. Further work is needed to determine the relationship between insurance status and newer, high-price drugs such as immune-oncology agents.

Understanding the causes of missingness in primary care: a realist review.

BACKGROUND: Although missed appointments in healthcare have been an area of concern for policy, practice and research, the primary focus has been on reducing single 'situational' missed appointments to the benefit of services. Little attention has been paid to the causes and consequences of more 'enduring' multiple missed appointments in primary care and the role this has in producing health inequalities. METHODS: We conducted a realist review of the literature on multiple missed appointments to identify the causes of 'missingness.' We searched multiple databases, carried out iterative citation-tracking on key papers on the topic of missed appointments and identified papers through searches of grey literature. We synthesised evidence from 197 papers, drawing on the theoretical frameworks of candidacy and fundamental causation. RESULTS: Missingness is caused by an overlapping set of complex factors, including patients not identifying a need for an appointment or feeling it is 'for them'; appointments as sites of poor communication, power imbalance and relational threat; patients being exposed to competing demands, priorities and urgencies; issues of travel and mobility; and an absence of choice or flexibility in when, where and with whom appointments take place. CONCLUSIONS: Interventions to address missingness at policy and practice levels should be theoretically informed, tailored to patients experiencing missingness and their identified needs and barriers; be cognisant of causal domains at multiple levels and address as many as practical; and be designed to increase safety for those seeking care.

Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study.

BACKGROUND: Most studies on the impact of the COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of the pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression. METHODS: Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged ≥ 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modeling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression. RESULTS: We found an immediate increase in depression incidence (RR = 1.21, 95% CI: 1.10-1.33, p < 0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a 3-year period. CONCLUSIONS: During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises.

The mouse metabolic phenotyping center (MMPC) live consortium: an NIH resource for in vivo characterization of mouse models of diabetes and obesity.

The Mouse Metabolic Phenotyping Center (MMPC)Live Program was established in 2023 by the National Institute for Diabetes, Digestive and Kidney Diseases (NIDDK) at the National Institutes of Health (NIH) to advance biomedical research by providing the scientific community with standardized, high quality phenotyping services for mouse models of diabetes and obesity. Emerging as the next iteration of the MMPC Program which served the biomedical research community for 20 years (2001-2021), MMPCLive is designed as an outwardly-facing consortium of service cores that collaborate to provide reduced-cost consultation and metabolic, physiologic, and behavioral phenotyping tests on live mice for U.S. biomedical researchers. Four MMPCLive Centers located at universities around the country perform complex and often unique procedures in vivo on a fee for service basis, typically on mice shipped from the client or directly from a repository or vendor. Current areas of expertise include energy balance and body composition, insulin action and secretion, whole body carbohydrate and lipid metabolism, cardiovascular and renal function, food intake and behavior, microbiome and xenometabolism, and metabolic pathway kinetics. Additionally, an opportunity arose to reduce barriers to access and expand the diversity of the biomedical research workforce by establishing the VIBRANT Program. Directed at researchers historically underrepresented in the biomedical sciences, VIBRANT-eligible investigators have access to testing services, travel and career development awards, expert advice and experimental design consultation, and short internships to learn test technologies. Data derived from experiments run by the Centers belongs to the researchers submitting mice for testing which can be made publicly available and accessible from the MMPCLive database following publication. In addition to services, MMPCLive staff provide expertise and advice to researchers, develop and refine test protocols, engage in outreach activities, publish scientific and technical papers, and conduct educational workshops and training sessions to aid researchers in unraveling the heterogeneity of diabetes and obesity.

Dung beetles increase plant growth: a meta-analysis.

The ecosystem services provided by dung beetles are well known and valued. Dung beetles bury dung for feeding and breeding, and it is generally thought that the process of burying dung increases nutrient uptake by plant roots, which promotes plant growth. Many studies have tested the effects of dung beetles on plant growth, but there has been no quantitative synthesis of these studies. Here we use a multi-level meta-analysis to estimate the average effect of dung beetles on plant growth and investigate factors that moderate this effect. We identified 28 publications that investigated dung beetle effects on plant growth. Of these, 24 contained the minimum quantitative data necessary to include in a meta-analysis. Overall, we found that dung beetles increased plant growth by 17%; the 95% CI for possible values for the true increase in plant growth that were most compatible with our data, given our statistical model, ranged from 1% to 35%. We found evidence that the dung beetle-plant growth relationship is influenced by the plant measurement type and the number of beetles accessing the dung. However, beetles did not increase plant growth in all quantitative trials, as individual effect sizes ranged from -72% to 806%, suggesting important context-dependence in the provision of ecosystem services.

DOMAS: a data management software framework for advanced light sources.

In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF).

Serverless computing in omics data analysis and integration.

A comprehensive analysis of omics data can require vast computational resources and access to varied data sources that must be integrated into complex, multi-step analysis pipelines. Execution of many such analyses can be accelerated by applying the cloud computing paradigm, which provides scalable resources for storing data of different types and parallelizing data analysis computations. Moreover, these resources can be reused for different multi-omics analysis scenarios. Traditionally, developers are required to manage a cloud platform's underlying infrastructure, configuration, maintenance and capacity planning. The serverless computing paradigm simplifies these operations by automatically allocating and maintaining both servers and virtual machines, as required for analysis tasks. This paradigm offers highly parallel execution and high scalability without manual management of the underlying infrastructure, freeing developers to focus on operational logic. This paper reviews serverless solutions in bioinformatics and evaluates their usage in omics data analysis and integration. We start by reviewing the application of the cloud computing model to a multi-omics data analysis and exposing some shortcomings of the early approaches. We then introduce the serverless computing paradigm and show its applicability for performing an integrative analysis of multiple omics data sources in the context of the COVID-19 pandemic.

Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization.

Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.