Landscape of toxin-neutralizing therapeutics for snakebite envenoming (2015-2022): Setting the stage for an R&D agenda

BACKGROUND

Progress in snakebite envenoming (SBE) therapeutics has suffered from a critical lack of data on the research and development (R&D) landscape. A database characterising this information would be a powerful tool for coordinating and accelerating SBE R&D. To address this need, we aimed to identify and categorise all active investigational candidates in development for SBE and all available or marketed products.

METHODOLOGY/PRINCIPAL FINDINGS

In this landscape study, publicly available data and literature were reviewed to canvas the state of the SBE therapeutics market and research pipeline by identifying, characterising, and validating all investigational drug and biologic candidates with direct action on snake venom toxins, and all products available or marketed from 2015 to 2022. We identified 127 marketed products and 196 candidates in the pipeline, describing a very homogenous market of similar but geographically bespoke products and a diverse but immature pipeline, as most investigational candidates are at an early stage of development, with only eight candidates in clinical development.

CONCLUSIONS/SIGNIFICANCE

Further investment and research is needed to address the shortfalls in products already on the market and to accelerate R&D for new therapeutics. This should be accompanied by efforts to converge on shared priorities and reshape the current SBE R&D ecosystem to ensure translation of innovation and access.

Three facets of emotion regulation in old and very old age: Strategy use, effectiveness, and variability

The ability to regulate emotions in stressful situations is an important building block for high well-being across the lifespan. Yet, very little is known about how old and very old adults regulate their emotions. In this study, 123 young old adults (Mage = 67.18, SD = 0.94) and 47 very old adults (Mage = 86.70, SD = 1.46) were prompted 6 times a day for 7 consecutive days to report both their stressors and 10 emotion regulation strategies. Overall, there was little indication of age differences in the use of emotion regulation strategies during exposure to stressors, but very old, as compared with young old, individuals used three of the 10 strategies considered here more intensively. The 10 emotion regulation strategies were similarly effective across age groups based on their association with perceived overall emotion regulation success. We also did not find age group differences in within-strategy variability, defined as the variation in using a given strategy across stressor situations. By contrast, between-strategy variability, defined as the selective use of fewer rather than many strategies across stressor situations, was lower for very old participants. Only between-strategy, and not within-strategy, variability contributed to overall emotion regulation success. There was no age group difference in this regard. Taken together, the evidence suggests small age differences in emotion regulation if at all. This is noteworthy given the advanced age of the very old subsample in this study and the deficits in multiple domains of functioning reported in the literature for this advanced age. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Dental divisions: exploring racial inequities of dental caries amongst children

DATA SOURCES

The search strategy involved three sequential stages. Initially, MEDLINE/PubMed was explored for relevant articles, identifying pertinent terms for formal searching. Using the terms ethnic, race, minoritised and dental caries, a strategy was formed and nine databases searched. Finally, hand-searching of reference lists of included articles and sourcing grey literature from relevant government reports, national oral health surveys, and registries which had comparative data for dental caries between racial groups, completed the search.

STUDY SELECTION

Studies included were original primary research which reported dental caries and compared racially minoritised children, aged 5-11 years, to similarly aged from national, majority, or privileged populations. Dental caries had to be recorded from a clinical examination which assessed decayed, missing, and filled teeth (dmft) in primary dentitions. Studies were excluded if they used immigration status as a basis of racial status, or they were a case report, case series, in vitro study, or literature review.

DATA EXTRACTION AND SYNTHESIS

After removing duplicates, two independent researchers screened abstracts, prior to extracting critical data following full-text reviews of included articles. Information collected included study and participant characteristics, definitions of race, and dental caries measurement. The authors of studies which had missing data were contacted, whilst those not written in the English language were translated. Methodological quality of each study was independently assessed by two reviewers using a modified version of the Newcastle-Ottawa scale. All studies were included in the review regardless of quality. A narrative overview of all included studies was conducted. Meta-analyses were completed using studies that reported the mean and standard deviation of the caries outcomes in both groups. Caries outcomes included severity (defined as mean dmft) or prevalence (percentage of teeth with untreated dental caries > 0%). Due to anticipated heterogeneity, statistical analyses approaches such as I2 statistics were used to estimate between-study variability. Additional sub-group analyses were conducted based on country of study and world income index. Contour-enhanced funnel plots and trim-and-fill analysis were completed to explore potential publication bias. Sensitivity analyses were performed to ensure robustness of the findings.

RESULTS

Seventy-five studies were included from a variety of countries. A higher mean dmft score of 2.30 (0.45, 4.15) and prevalence of decayed teeth (d > 0) was 23% (95% CI: 16, 31) was noted amongst racially minoritised children compared to privileged children's populations. Notable disparities were reported in high-income countries, with minoritised children burdening the greatest distribution of caries incidence. The study faced challenges in consistent racial classification and encountered high heterogeneity in its findings, leading to varied GRADE assessment scores.

CONCLUSIONS

The study calls for global, social, and political changes to tackle the substantial disparities in dental caries among minoritised children to achieve oral health equity.

The national distribution of lymphatic filariasis cases in Malawi using patient mapping and geostatistical modelling

BACKGROUND

In 2020 the World Health Organization (WHO) declared that Malawi had successfully eliminated lymphatic filariasis (LF) as a public health problem. Understanding clinical case distributions at a national and sub-national level is important, so essential care packages can be provided to individuals living with LF symptoms. This study aimed to develop a national database and map of LF clinical cases across Malawi using geostatistical modelling approaches, programme-identified clinical cases, antigenaemia prevalence and climate information.

METHODOLOGY

LF clinical cases identified through programme house-to-house surveys across 90 sub-district administrative boundaries (Traditional Authority (TA)) and antigenaemia prevalence from 57 sampled villages in Malawi were used in a two-step geostatistical modelling process to predict LF clinical cases across all TAs of the country. First, we modelled antigenaemia prevalence in relation to climate covariates to predict nationwide antigenaemia prevalence. Second, we modelled clinical cases for unmapped TAs based on our antigenaemia prevalence spatial estimates.

PRINCIPLE FINDINGS

The models estimated 20,938 (95% CrI 18,091 to 24,071) clinical cases in unmapped TAs (70.3%) in addition to the 8,856 (29.7%), programme-identified cases in mapped TAs. In total, the overall national number of LF clinical cases was estimated to be 29,794 (95% CrI 26,957 to 32,927). The antigenaemia prevalence and clinical case mapping and modelling found the highest burden of disease in Chikwawa and Nsanje districts in the Southern Region and Karonga district in the Northern Region of the country.

CONCLUSIONS

The models presented in this study have facilitated the development of the first national LF clinical case database and map in Malawi, the first endemic country in sub-Saharan Africa. It highlights the value of using existing LF antigenaemia prevalence and clinical case data together with modelling approaches to produce estimates that may be used for the WHO dossier requirements, to help target limited resources and implement long-term health strategies.

High rate of species misidentification reduces the taxonomic certainty of European biodiversity databases of ivies (Hedera L.)

The digitization of natural history specimens and the popularization of citizen science are creating an unprecedented availability of large amounts of biodiversity data. These biodiversity inventories can be severely affected by species misidentification, a source of taxonomic uncertainty that is rarely acknowledged in biodiversity data management. For these reasons, taxonomists debate the use of online repositories to address biological questions at the species level. Hedera L. (ivies) provides an excellent case study as it is well represented in both herbaria and online repositories with thousands of records likely to be affected by high taxonomic uncertainty. We analyze the sources and extent of taxonomic errors in the identification of the European ivy species by reviewing herbarium specimens and find a high misidentification rate (18% on average), which varies between species (maximized in H. hibernica: 55%; H. azorica: 48%; H. iberica: 36%) and regions (maximized in the UK: 38% and Spain: 27%). We find a systematic misidentification of all European ivies with H. helix behind the high misidentification rates in herbaria and warn of even higher rates in online records. We compile a spatial database to overcome the large discrepancies we observed in species distributions between online and morphologically reviewed records.

Seamless EMR data access: Integrated governance, digital health and the OMOP-CDM

Objectives In this overview, we describe theObservational Medical Outcomes Partnership Common Data Model (OMOP-CDM), the established governance processes employed in EMR data repositories, and demonstrate how OMOP transformed data provides a lever for more efficient and secure access to electronic medical record (EMR) data by health service providers and researchers.Methods Through pseudonymisation and common data quality assessments, the OMOP-CDM provides a robust framework for converting complex EMR data into a standardised format. This allows for the creation of shared end-to-end analysis packages without the need for direct data exchange, thereby enhancing data security and privacy. By securely sharing de-identified and aggregated data and conducting analyses across multiple OMOP-converted databases, patient-level data is securely firewalled within its respective local site.Results By simplifying data management processes and governance, and through the promotion of interoperability, the OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting.Discussion Adoption of the OMOP-CDM internationally and locally enables conversion of vast amounts of complex, and heterogeneous EMR data into a standardised structured data model, simplifies governance processes, and facilitates rapid repeatable cross-institution analysis through shared end-to-end analysis packages, without the sharing of data.Conclusion The adoption of the OMOP-CDM has the potential to transform health data analytics by providing a common platform for analysing EMR data across diverse healthcare settings.

Co-design for stroke intervention development: Results of a scoping review

BACKGROUND

Co-design methodology seeks to actively engage end-users in developing interventions. It is increasingly used to design stroke interventions; however, limited guidance exists, particularly with/for individuals with stroke who have diverse cognitive, physical and functional abilities. Thus, we describe 1) the extent of existing research that has used co-design for stroke intervention development and 2) how co-design has been used to develop stroke interventions among studies that explicitly used co-design, including the rationale, types of co-designed stroke interventions, participants involved, research methodologies/approaches, methods of incorporating end-users in the research, co-design limitations, challenges and potential strategies reported by researchers.

MATERIALS AND METHODS

A scoping review informed by Joanna Briggs Institute and Arksey & O'Malley methodology was conducted by searching nine databases on December 21, 2022, to locate English-language literature that used co-design to develop a stroke intervention. Additional data sources were identified through a hand search. Data sources were de-duplicated, and two research team members reviewed their titles, abstracts and full text to ensure they met the inclusion criteria. Data relating to the research objectives were extracted, analyzed, and reported numerically and descriptively.

RESULTS

Data sources used co-design for stroke intervention development with (n = 89) and without (n = 139) explicitly using the term 'co-design.' Among studies explicitly using co-design, it was commonly used to understand end-user needs and generate new ideas. Many co-designed interventions were technology-based (65%), and 48% were for physical rehabilitation or activity-based. Co-design was commonly conducted with multiple participants (82%; e.g., individuals with stroke, family members/caregivers and clinicians) and used various methods to engage end-users, including focus groups and workshops. Limitations, challenges and potential strategies for recruitment, participant-engagement, contextual and logistical and ethics of co-designed interventions were described.

CONCLUSIONS

Given the increasing popularity of co-design as a methodology for developing stroke interventions internationally, these findings can inform future co-designed studies.

RiceProteomeDB (RPDB): a user-friendly database for proteomics data storage, retrieval, and analysis

Rice, feeding a significant portion of the world, poses unique proteomic challenges critical to agricultural research and global food security. The complexity of the rice proteome, influenced by various genetic and environmental factors, demands specialized analytical approaches for effective study. The central challenges in rice proteomics lie in developing custom methods suited to the unique aspects of rice biology. These include data preprocessing, method selection, and result validation, all of which are essential for advancing rice research. Our aim is to decode these proteomic intricacies to facilitate breakthroughs in strain improvement, disease resistance, and yield optimization, all vital for combating global food insecurity. To achieve this, we have created the RiceProteomeDB (RPDB), a React + Django database, offering a streamlined and comprehensive platform for the analysis of rice proteomics data. RiceProteomeDB (RPDB) simplifies proteomics data management and analysis. It offers features for data organization, preprocessing, method selection, result validation, and data sharing. Researchers can access processed rice proteomics data, conduct analyses, and explore experimental conditions. The user-friendly web interface enhances navigation and interaction. RPDB fosters collaboration by enabling data sharing and proper acknowledgment of sources, contributing to proteomics research and knowledge dissemination. Availability and implementation: Web application: http://riceproteome.plantprofile.net/ . The web application's source code, user's manual, and sample data: https://github.com/dongu7610/Riceproteome .

A systematic review on the direct approach to elicit the demand-side cost-effectiveness threshold: Implications for low- and middle-income countries

Several literature review studies have been conducted on cost-effectiveness threshold values. However, only a few are systematic literature reviews, and most did not investigate the different methods, especially in-depth reviews of directly eliciting WTP per QALY. Our study aimed to 1) describe the different direct approach methods to elicit WTP/QALY; 2) investigate factors that contribute the most to the level of WTP/QALY value; and 3) investigate the relation between the value of WTP/QALY and GDP per capita and give some recommendations on feasible methods for eliciting WTP/QALY in low- and middle-income countries (LMICs). A systematic review concerning select studies estimating WTP/QALY from a direct approach was carried out in seven databases, with a cut off date of 03/2022. The conversion of monetary values into 2021 international dollars (i$) was performed via CPI and PPP indexes. The influential factors were evaluated with Bayesian model averaging. Criteria for recommendation for feasible methods in LMICs are made based on empirical evidence from the systematic review and given the resource limitation in LMICs. A total of 12,196 records were identified; 64 articles were included for full-text review. The WTP/QALY method and values varied widely across countries with a median WTP/QALY value of i$16,647.6 and WTP/QALY per GDP per capita of 0.53. A total of 11 factors were most influential, in which the discrete-choice experiment method had a posterior probability of 100%. Methods for deriving WTP/QALY vary largely across studies. Eleven influential factors contribute most to the level of values of WTP/QALY, in which the discrete-choice experiment method was the greatest affected. We also found that in most countries, values for WTP/QALY were below 1 x GDP per capita. Some important principles are addressed related to what LMICs may be concerned with when conducting studies to estimate WTP/QALY.

Applying sequence analysis to uncover 'real-world' clinical pathways from routinely collected data: a systematic review

OBJECTIVES

This systematic review aims to elucidate the methodological practices and reporting standards associated with sequence analysis (SA) for the identification of clinical pathways in real-world scenarios, using routinely collected data.

STUDY DESIGN AND SETTING

We conducted a methodological systematic review, searching five medical and health databases: MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science. The search encompassed articles from the inception of these databases up to February 28, 2023. The search strategy comprised two distinctive sets of search terms, specifically focused on sequence analysis and clinical pathways.

RESULTS

19 studies met the eligibility criteria for this systematic review. Nearly 60% of the included studies were published in or after 2021, with a significant proportion originating from Canada (n = 7) and France (n = 5). 90% of the studies adhered to the fundamental SA steps. The optimal matching (OM) method emerged as the most frequently employed dissimilarity measure (63%), while agglomerative hierarchical clustering using Ward's linkage was the preferred clustering algorithm (53%). However, it is imperative to underline that a majority of the studies inadequately reported key methodological decisions pertaining to SA.

CONCLUSION

This review underscores the necessity for enhanced transparency in reporting both data management procedures and key methodological choices within SA processes. The development of reporting guidelines and a robust appraisal tool tailored to assess the quality of SA would be invaluable for researchers in this field.

Emotion regulation efficacy beliefs: The outsized impact of base rates

To regulate others' emotions effectively we must learn about the efficacy of our regulation attempts. Deciding whether we made someone else feel better involves a causal judgment about the effect of our intervention on their emotional state. The current study examined whether, like other causal judgments, beliefs about emotion regulation efficacy are disproportionately affected by base rates. In two experiments, we showed that participants' perceived efficacy at helping a target regulate their emotions was more influenced by the target's average emotion levels than the relative effect of regulating versus not regulating the target's emotion. This led participants to conclude that they were helpful both when they were not (Experiment 1) and even when they made the target feel worse (Experiment 2). These findings suggest that our beliefs about the effectiveness of other-directed emotion regulation are notably biased by the average level of emotion expressed by the regulation target. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Golden tears: A cross-country study of crying in the Olympics

This article studies tears of joy by exploring data on the behavior of gold medalists of all 450 individual events at the 2012 and 2016 Summer Olympic Games at the end of the medalists' respective competitions and during the medal ceremonies. We find that women cry more than men, older athletes cry more than younger athletes, athletes from the host country cry more at the end of the competition, and athletes cry more when they receive information on their victory immediately after completing their task. When looking at the socioeconomic characteristics of athletes' countries, we find that men from countries with larger female labor force participation rates cry more than men from countries with lower female labor force participation, and athletes from countries with higher religious fractionalization cry less than those from countries with lower fractionalization. Finally, we find no relationship between the wealth of a country and the propensity of its athletes of any gender to cry. We discuss possible mechanisms that drive our results and suggest future directions for observational studies on emotions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Burn data management and usage across Canada

INTRODUCTION

While some countries collect burn clinical data as part of nonspecific trauma datasets, others have developed burn registries allowing for benchmarking of outcome and quality-of-care data. The objectives of this project are to characterize the current state of burn clinical data collection and analysis in Canada, and to explore the interest of Canadian burn centers in contributing to a nation-wide burn registry.

METHODS

A 23-item mixed methods survey was created and delivered via REDCap® to burn directors of 22 burn centers across Canada. Quantitative items were analyzed by means of descriptive statistics, and thematic analysis was used to explore qualitative data.

RESULTS

Sixteen (72 %) complete survey responses were received. All respondent units collect burn clinical data. Data are largely collected for quality improvement (69 %) and clinical research (50 %) purposes. Half of the institutions did not analyze their data, and a majority (67 %) did not benchmark their data against other datasets. The majority of respondents (93 %) demonstrated interest in contributing to a Canada-wide burn registry.

CONCLUSION

Although all respondent units are currently collecting burn clinical data, there is an opportunity to improve data analysis, benchmarking, and knowledge translation. Most centers demonstrated interest in contributing to a novel Canadian burn registry.

Architecture of the Mass Spectrometry Data Management Pipeline in the SMART-CARE Project

In the SMART-CARE project- a systems medicine approach to stratification of cancer recurrence in Heidelberg, Germany - a streamlined mass-spectrometry (MS) workflow for identification of cancer relapse was developed. This project has multiple partners from clinics, laboratories and computational teams. For optimal collaboration, consistent documentation and centralized storage, the linked data repository was designed. Clinical, laboratory and computational group members interact with this platform and store meta- and raw-data. The specific architectural choices, such as pseudonymization service, uploading process and other technical specifications as well as lessons learned are presented in this work. Altogether, relevant information in order to provide other research groups with a head-start for tackling MS data management in the context of systems medicine research projects is described.

Case-Reported Data Management Methodology Using an RDF Data Model for Building a Multicenter Clinical Registry

In multicenter clinical research, case-reported clinical data are managed for each research project. Participating institutions manage the mapping between standardized codes and in-house codes. To use the data extracted from electronic medical records in case report forms, it is necessary to pay attention to the gap in the semantic hierarchy. Managing mapping information between in-house and standardized codes is centralized in Resource Description Framework (RDF) stores. The relationship between standardized and in-house codes is described in RDF and stored in RDF stores. RESTful APIs for accessing RDF stores in SPARQL was developed and verified. The relationship between standardized codes and in-house codes of pharmaceuticals was expressed in RDF triples. As a +result of the operational verification of the implemented APIs, it was confirmed that data management with knowledge bases expressed in RDF graphs is possible. The ability to dynamically modify mapping definitions enables flexible data management and ease of operational restrictions.

Development of Integrated Data Quality Management System for Observational Medical Outcomes Partnership Common Data Model

The amount of research on the gathering and handling of healthcare data keeps growing. To support multi-center research, numerous institutions have sought to create a common data model (CDM). However, data quality issues continue to be a major obstacle in the development of CDM. To address these limitations, a data quality assessment system was created based on the representative data model OMOP CDM v5.3.1. Additionally, 2,433 advanced evaluation rules were created and incorporated into the system by mapping the rules of existing OMOP CDM quality assessment systems. The data quality of six hospitals was verified using the developed system and an overall error rate of 0.197% was confirmed. Finally, we proposed a plan for high-quality data generation and the evaluation of multi-center CDM quality.

An Overview of Data Management in Human Subjects Research

Research studies generate data in various forms. Data can be quantitative or qualitative. Research involving human subjects requires protection of data to ensure privacy. Various regulations and local policies need to be followed to ensure data security. Data management plans are critical for effective data stewardship and include details plan on data collection, management, storage, and formatting. This paper will review data collection tools, data security strategies, file management, data storage, government regulations, prepping data for analysis, reference management, and file management.

neo4jsbml: import systems biology markup language data into the graph database Neo4j

Systems Biology Markup Language (SBML) has emerged as a standard for representing biological models, facilitating model sharing and interoperability. It stores many types of data and complex relationships, complicating data management and analysis. Traditional database management systems struggle to effectively capture these complex networks of interactions within biological systems. Graph-oriented databases perform well in managing interactions between different entities. We present neo4jsbml, a new solution that bridges the gap between the Systems Biology Markup Language data and the Neo4j database, for storing, querying and analyzing data. The Systems Biology Markup Language organizes biological entities in a hierarchical structure, reflecting their interdependencies. The inherent graphical structure represents these hierarchical relationships, offering a natural and efficient means of navigating and exploring the model's components. Neo4j is an excellent solution for handling this type of data. By representing entities as nodes and their relationships as edges, Cypher, Neo4j's query language, efficiently traverses this type of graph representing complex biological networks. We have developed neo4jsbml, a Python library for importing Systems Biology Markup Language data into a Neo4j database using a user-defined schema. By leveraging Neo4j's graphical database technology, exploration of complex biological networks becomes intuitive and information retrieval efficient. Neo4jsbml is a tool designed to import Systems Biology Markup Language data into a Neo4j database. Only the desired data is loaded into the Neo4j database. neo4jsbml is user-friendly and can become a useful new companion for visualizing and analyzing metabolic models through the Neo4j graphical database. neo4jsbml is open source software and available at https://github.com/brsynth/neo4jsbml.

Promoting TEFCA with Blockchain Technology: A Decentralized Approach to Patient-centered Healthcare Data Management

The Trusted Exchange Framework and Common Agreement (TEFCA) is a framework consisting of seven principles designed to create a secure and seamless health information exchange system across various healthcare settings. The ultimate goal of TEFCA is to facilitate public health surveillance, increase interoperability, promote data sharing, and ensure patient-centered healthcare data management. While the implementation of these principles is challenging, blockchain technology, with its unique features such as transparency, auditability, immutability, and anonymity, can provide a promising solution to the development of TEFCA. This article delves into the potential of blockchain technology to promote TEFCA design. By providing an immutable and transparent ledger, blockchain ensures data integrity, openness, and patient privacy. Overall, the use of blockchain technology can help address the challenges of implementing TEFCA principles and promote patient empowerment and control over their health data, improve data interoperability, and enhance healthcare quality.

Methods and measures to evaluate the impact of participatory model building on public policymakers: a scoping review protocol

INTRODUCTION

Public policymakers are increasingly engaged in participatory model building processes, such as group model building. Understanding the impacts of policymaker participation in these processes on policymakers is important given that their decisions often have significant influence on the dynamics of complex systems that affect health. Little is known about the extent to which the impacts of participatory model building on public policymakers have been evaluated or the methods and measures used to evaluate these impacts.

METHODS AND ANALYSIS

A scoping review protocol was developed with the objectives of: (1) scoping studies that have evaluated the impacts of facilitated participatory model building processes on public policymakers who participated in these processes; and (2) describing methods and measures used to evaluate impacts and the main findings of these evaluations. The Joanna Briggs Institute's Population, Concept, Context framework was used to formulate the article identification process. Seven electronic databases-MEDLINE (Ovid), ProQuest Health and Medical, Scopus, Web of Science, Embase (Ovid), CINAHL Complete and PsycInfo-will be searched. Identified articles will be screened according to inclusion and exclusion criteria and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist for scoping reviews will be used and reported. A data extraction tool will collect information across three domains: study characteristics, methods and measures, and findings. The review will be conducted using Covidence, a systematic review data management platform.

ETHICS AND DISSEMINATION

The scoping review produced will generate an overview of how public policymaker engagement in participatory model building processes has been evaluated. Findings will be disseminated through peer-reviewed publications and to communities of practice that convene policymakers in participatory model building processes. This review will not require ethics approval because it is not human subject research.

PRMD: an integrated database for plant RNA modifications

The scope and function of RNA modifications in model plant systems have been extensively studied, resulting in the identification of an increasing number of novel RNA modifications in recent years. Researchers have gradually revealed that RNA modifications, especially N6-methyladenosine (m6A), which is one of the most abundant and commonly studied RNA modifications in plants, have important roles in physiological and pathological processes. These modifications alter the structure of RNA, which affects its molecular complementarity and binding to specific proteins, thereby resulting in various of physiological effects. The increasing interest in plant RNA modifications has necessitated research into RNA modifications and associated datasets. However, there is a lack of a convenient and integrated database with comprehensive annotations and intuitive visualization of plant RNA modifications. Here, we developed the Plant RNA Modification Database (PRMD; http://bioinformatics.sc.cn/PRMD and http://rnainformatics.org.cn/PRMD) to facilitate RNA modification research. This database contains information regarding 20 plant species and provides an intuitive interface for displaying information. Moreover, PRMD offers multiple tools, including RMlevelDiff, RMplantVar, RNAmodNet and Blast (for functional analyses), and mRNAbrowse, RNAlollipop, JBrowse and Integrative Genomics Viewer (for displaying data). Furthermore, PRMD is freely available, making it useful for the rapid development and promotion of research on plant RNA modifications.

EVLncRNAs 3.0: an updated comprehensive database for manually curated functional long non-coding RNAs validated by low-throughput experiments

Long noncoding RNAs (lncRNAs) have emerged as crucial regulators across diverse biological processes and diseases. While high-throughput sequencing has enabled lncRNA discovery, functional characterization remains limited. The EVLncRNAs database is the first and exclusive repository for all experimentally validated functional lncRNAs from various species. After previous releases in 2018 and 2021, this update marks a major expansion through exhaustive manual curation of nearly 25 000 publications from 15 May 2020, to 15 May 2023. It incorporates substantial growth across all categories: a 154% increase in functional lncRNAs, 160% in associated diseases, 186% in lncRNA-disease associations, 235% in interactions, 138% in structures, 234% in circular RNAs, 235% in resistant lncRNAs and 4724% in exosomal lncRNAs. More importantly, it incorporated additional information include functional classifications, detailed interaction pathways, homologous lncRNAs, lncRNA locations, COVID-19, phase-separation and organoid-related lncRNAs. The web interface was substantially improved for browsing, visualization, and searching. ChatGPT was tested for information extraction and functional overview with its limitation noted. EVLncRNAs 3.0 represents the most extensive curated resource of experimentally validated functional lncRNAs and will serve as an indispensable platform for unravelling emerging lncRNA functions. The updated database is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs3/.

Selecting an Ecological Momentary Assessment Platform: Tutorial for Researchers

BACKGROUND

Although ecological momentary assessment (EMA) has been applied in psychological research for decades, delivery methods have evolved with the proliferation of digital technology. Technological advances have engendered opportunities for enhanced accessibility, convenience, measurement precision, and integration with wearable sensors. Notwithstanding, researchers must navigate novel complexities in EMA research design and implementation.

OBJECTIVE

In this paper, we aimed to provide guidance on platform selection for clinical scientists launching EMA studies.

METHODS

Our team includes diverse specialties in child and adolescent behavioral and mental health with varying expertise on EMA platforms (eg, users and developers). We (2 research sites) evaluated EMA platforms with the goal of identifying the platform or platforms with the best fit for our research. We created a list of extant EMA platforms; conducted a web-based review; considered institutional security, privacy, and data management requirements; met with developers; and evaluated each of the candidate EMA platforms for 1 week.

RESULTS

We selected 2 different EMA platforms, rather than a single platform, for use at our 2 research sites. Our results underscore the importance of platform selection driven by individualized and prioritized laboratory needs; there is no single, ideal platform for EMA researchers. In addition, our project generated 11 considerations for researchers in selecting an EMA platform: (1) location; (2) developer involvement; (3) sample characteristics; (4) onboarding; (5) survey design features; (6) sampling scheme and scheduling; (7) viewing results; (8) dashboards; (9) security, privacy, and data management; (10) pricing and cost structure; and (11) future directions. Furthermore, our project yielded a suggested timeline for the EMA platform selection process.

CONCLUSIONS

This study will guide scientists initiating studies using EMA, an in vivo, real-time research tool with tremendous promise for facilitating advances in psychological assessment and intervention.