A study of search strategy availability statements and sharing practices for systematic reviews: Ask and you might receive

The literature search underpins data collection for all systematic reviews (SRs). The SR reporting guideline PRISMA, and its extensions, aim to facilitate research transparency and reproducibility, and ultimately improve the quality of research, by instructing authors to provide specific research materials and data upon publication of the manuscript. Search strategies are one item of data that are explicitly included in PRISMA and the critical appraisal tool AMSTAR2. Yet some authors use search availability statements implying that the search strategies are available upon request instead of providing strategies up front. We sought out reviews with search availability statements, characterized them, and requested the search strategies from authors via email. Over half of the included reviews cited PRISMA but less than a third included any search strategies. After requesting the strategies via email as instructed, we received replies from 46% of authors, and eventually received at least one search strategy from 36% of authors. Requesting search strategies via email has a low chance of success. Ask and you might receive-but you probably will not. SRs that do not make search strategies available are low quality at best according to AMSTAR2; Journal editors can and should enforce the requirement for authors to include their search strategies alongside their SR manuscripts.

Ambiguity in Statistical Analysis Methods and Nonconformity With Prespecified Commitment to Data Sharing in a Cluster Randomized Controlled Trial

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A global assessment of the Raunkiaeran shortfall in plants: geographic biases in our knowledge of plant traits

This article is part of the Special Collection ‘Global plant diversity and distribution’. See https://www.newphytologist.org/global-plant-diversity for more details.

Availability of Physical Activity Tracking Data from Wearable Devices for Glaucoma Patients

Physical activity has been found to potentially modulate glaucoma risk, but the evidence remains inconclusive. The increasing use of wearable physical activity trackers may provide longitudinal and granular data suitable to address this issue, but little is known regarding the characteristics and availability of these data sources. We performed a scoping review and query of data sources on the availability of wearable physical activity data for glaucoma patients. Literature databases (PubMed and MEDLINE) were reviewed with search terms consisting of those related to physical activity trackers and those related to glaucoma, and we evaluated results at the intersection of these two groups. Biomedical databases were also reviewed, for which we completed database queries. We identified eight data sources containing physical activity tracking data for glaucoma, with two being large national databases (UK BioBank and All of Us) and six from individual journal articles providing participant-level information. The number of glaucoma patients with physical activity tracking data available, types of glaucoma-related data, fitness devices utilized, and diversity of participants varied across all sources. Overall, there were limited analyses of these data, suggesting the need for additional research to further investigate how physical activity may alter glaucoma risk.

The Expectation and Reality of the HepG2 Core Metabolic Profile

To represent the composition of small molecules circulating in HepG2 cells and the formation of the "core" of characteristic metabolites that often attract researchers' attention, we conducted a meta-analysis of 56 datasets obtained through metabolomic profiling via mass spectrometry and NMR. We highlighted the 288 most commonly studied compounds of diverse chemical nature and analyzed metabolic processes involving these small molecules. Building a complete map of the metabolome of a cell, which encompasses the diversity of possible impacts on it, is a severe challenge for the scientific community, which is faced not only with natural limitations of experimental technologies, but also with the absence of transparent and widely accepted standards for processing and presenting the obtained metabolomic data. Formulating our research design, we aimed to reveal metabolites crucial to the Hepg2 cell line, regardless of all chemical and/or physical impact factors. Unfortunately, the existing paradigm of data policy leads to a streetlight effect. When analyzing and reporting only target metabolites of interest, the community ignores the changes in the metabolomic landscape that hide many molecular secrets.

Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy

Smart living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for smart living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in smart living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of smart living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in smart living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of context awareness, data availability, personalization, and privacy in HAR, this paper offers a comprehensive resource for researchers and practitioners striving to advance smart living services and applications. The methodology for this literature review involved conducting targeted Scopus queries to ensure a comprehensive coverage of relevant publications in the field. Efforts have been made to thoroughly evaluate the existing literature, identify research gaps, and propose future research directions. The comparative advantages of this review lie in its comprehensive coverage of the dimensions essential for smart living services and applications, addressing the limitations of previous reviews and offering valuable insights for researchers and practitioners in the field.

In search of a perfect trait set: A workflow presentation based on the conservation status assessment of Poland's dendroflora

Considering the dynamically changing environment, we cannot be sure whether we are using the best possible plant functional traits to explain ecological mechanisms. We provide a quantitative comparison of 13 trait sets to determine the availability of functional traits representing different plant organs, assess the trait sets with the highest explanatory potential, and check whether including a higher number of traits in a model increases its accuracy. We evaluated the trait sets by preparing 13 models using similar methodology and responding to a research question: How do models with different sets of functional traits predict the conservation status of species? We used the dataset covering all woody species from Poland (N = 387), with 23 functional traits. Our findings indicate that what matters most for a trait set of high explanatory power is the precise selection of those traits. The best fit model was based on the findings of Díaz et al. (2016; The global spectrum of plant form and function, Nature, 529, 167-171) and included only six traits. Importantly, traits representing different plant organs should be included whenever possible: Three of the four best models from our comparison were the ones that included traits of various plant organs.

A Modified CGM Algorithm Enhances Data Availability While Retaining iCGM Performance

The algorithm for the Dexcom G6 CGM System was enhanced to retain accuracy while reducing the frequency and duration of sensor error. The new algorithm was evaluated by post-processing raw signals collected from G6 pivotal trials (NCT02880267) and by assessing the difference in data availability after a limited, real-world launch. Accuracy was comparable with the new algorithm-the overall %20/20 was 91.7% before and 91.8% after the algorithm modification; MARD was unchanged. The mean data gap due to sensor error nearly halved and total time spent in sensor error decreased by 59%. A limited field launch showed similar results, with a 43% decrease in total time spent in sensor error. Increased data availability may improve patient experience and CGM data integration into insulin delivery systems.

Challenges of Data Availability and Use in Conducting Health-EDRM Research in a Post-COVID-19 World

Disasters disrupt communication channels, infrastructure, and overburden health systems. This creates unique challenges to the functionality of surveillance tools, data collection systems, and information sharing platforms. The WHO Health Emergency and Disaster Risk Management (Health-EDRM) framework highlights the need for appropriate data collection, data interpretation, and data use from individual, community, and global levels. The COVID-19 crisis has evolved the way hazards and risks are viewed. No longer as a linear event but as a protracted hazard, with cascading and compound risks that affect communities facing complex risks such as climate-related disasters or urban growth. The large-scale disruptions of COVID-19 show that disaster data must evolve beyond mortality and frequency of events, in order to encompass the impact on the livelihood of communities, differentiated between population groups. This includes relative economic losses and psychosocial damage. COVID-19 has created a global opportunity to review how the scientific community classifies data, and how comparable indicators are selected to inform evidence-based resilience building and emergency preparedness. A shift into microlevel data, and regional-level information sharing is necessary to tailor community-level interventions for risk mitigation and disaster preparedness. Real-time data sharing, open governance, cross-organisational, and inter-platform collaboration are necessary not just in Health-EDRM and control of biological hazards, but for all natural hazards and man-made disasters.

Global Revisit Interval Analysis of Landsat-8 -9 and Sentinel-2A -2B Data for Terrestrial Monitoring

The combination of Landsat-8, Landsat-9, Sentinel-2A and Sentinel-2B data provides a new perspective in remote sensing application for terrestrial monitoring. Jointly, these four sensors together offer global 10–30-m multi-spectral data coverage at a higher temporal revisit frequency. In this study, combinations of four sensors were used to examine the revisit interval by modelled orbit swath information. To investigate different factors that could influence data availability, an analysis was carried out for one year based on daytime surface observations of Landsat-8 and Sentinel-2A -2B. We found that (i) the global median average of revisit intervals for the combination of four sensors was 2.3 days; (ii) the global mean average number of surface observations was 141.4 for the combination of Landsat-8 and Sentinel-2A -2B; (iii) the global mean average cloud-weighted number of observations for the three sensors combined was 81.9. Three different locations were selected to compare with the cloud-weighted number of observations, and the results show an appropriate accuracy. The utility of combining four sensors together and the implication for terrestrial monitoring are discussed.

Canadian Electricity Markets during the COVID-19 Pandemic: An Initial Assessment

This article examines the effect of the coronavirus disease 2019 (COVID-19) pandemic on electricity markets across select Canadian provinces, using available data. Using high-frequency electricity data, we find electricity demand declined by roughly 10 percent in Ontario and by about 5 percent in Alberta, British Columbia, and New Brunswick. On the supply side, in Alberta we find reductions from some natural gas plants and an increase in net generation from the oil sands region, whereas Ontario sees an increase in net electricity exports. Policy implications include potential rate impacts as a result of fixed charges spread over a smaller rate base, the potential use of electricity data as a real-time economic indicator during the pandemic, and a call to arms to make electricity data across all Canadian provinces more readily available.

An Evaluation of Nephrology Literature for Transparency and Reproducibility Indicators: Cross-Sectional Review

INTRODUCTION

Reproducibility is critical to diagnostic accuracy and treatment implementation. Concurrent with clinical reproducibility, research reproducibility establishes whether the use of identical study materials and methodologies in replication efforts permits researchers to arrive at similar results and conclusions. In this study, we address this gap by evaluating nephrology literature for common indicators of transparent and reproducible research.

METHODS

We searched the National Library of Medicine catalog to identify 36 MEDLINE-indexed, English-language nephrology journals. We randomly sampled 300 publications published between January 1, 2014, and December 31, 2018.

RESULTS

Our search yielded 28,835 publications, of which we randomly sampled 300 publications. Of the 300 publications, 152 (50.7%) were publicly available, whereas 143 (47.7%) were restricted through paywall and 5 (1.7%) were inaccessible. Of the remaining 295 publications, 123 were excluded because they lack empirical data necessary for reproducibility. Of the 172 publications with empirical data, 43 (25%) reported data availability statements and 4 (2.3%) analysis scripts. Of the 71 publications analyzed for preregistration and protocol availability, 0 (0.0%) provided links to a protocol and 8 (11.3%) were preregistered.

CONCLUSION

Our study found that reproducible and transparent research practices are infrequently used by the nephrology research community. Greater efforts should be made by both funders and journals. In doing so, an open science culture may eventually become the norm rather than the exception.

Identifying exceptional malaria occurrences in the absence of historical data in South Sudan: a method validation

Background

Detecting unusual malaria events that may require an operational intervention is challenging, especially in endemic contexts with continuous transmission such as South Sudan. Médecins Sans Frontières (MSF) utilises the classic average plus standard deviation (AV+SD) method for malaria surveillance. This and other available approaches, however, rely on antecedent data, which are often missing.

Objective

To investigate whether a method using linear regression (LR) over only 8 weeks of retrospective data could be an alternative to AV+SD.

Design

In the absence of complete historical malaria data from South Sudan, data from weekly influenza reports from 19 Norwegian counties (2006-2015) were used as a testing data set to compare the performance of the LR and the AV+SD methods. The moving epidemic method was used as the gold standard. Subsequently, the LR method was applied in a case study on malaria occurrence in MSF facilities in South Sudan (2010-2016) to identify malaria events that required a MSF response.

Results

For the Norwegian influenza data, LR and AV+SD methods did not perform differently (P > 0.05). For the South Sudanese malaria data, the LR method identified historical periods when an operational response was mounted.

Conclusion

The LR method seems a plausible alternative to the AV+SD method in situations where retrospective data are missing.

Research priorities for maintaining biodiversity's contributions to people in Latin America

Maintaining biodiversity is crucial for ensuring human well-being. The authors participated in a workshop held in Palenque, Mexico, in August 2018, that brought together 30 mostly early-career scientists working in different disciplines (natural, social and economic sciences) with the aim of identifying research priorities for studying the contributions of biodiversity to people and how these contributions might be impacted by environmental change. Five main groups of questions emerged: (1) Enhancing the quantity, quality, and availability of biodiversity data; (2) Integrating different knowledge systems; (3) Improved methods for integrating diverse data; (4) Fundamental questions in ecology and evolution; and (5) Multi-level governance across boundaries. We discuss the need for increased capacity building and investment in research programmes to address these challenges.

On the Combination of Multi-Cloud and Network Coding for Cost-Efficient Storage in Industrial Applications

The adoption of both Cyber–Physical Systems (CPSs) and the Internet-of-Things (IoT) has enabled the evolution towards the so-called Industry 4.0. These technologies, together with cloud computing and artificial intelligence, foster new business opportunities. Besides, several industrial applications need immediate decision making and fog computing is emerging as a promising solution to address such requirement. In order to achieve a cost-efficient system, we propose taking advantage from spot instances, a new service offered by cloud providers, which provide resources at lower prices. The main downside of these instances is that they do not ensure service continuity and they might suffer from interruptions. An architecture that combines fog and multi-cloud deployments along with Network Coding (NC) techniques, guarantees the needed fault-tolerance for the cloud environment, and also reduces the required amount of redundant data to provide reliable services. In this paper we analyze how NC can actually help to reduce the storage cost and improve the resource efficiency for industrial applications, based on a multi-cloud infrastructure. The cost analysis has been carried out using both real AWS EC2 spot instance prices and, to complement them, prices obtained from a model based on a finite Markov chain, derived from real measurements. We have analyzed the overall system cost, depending on different parameters, showing that configurations that seek to minimize the storage yield a higher cost reduction, due to the strong impact of storage cost.

Predictability of demographic rates based on phylogeny and biological similarity

Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.

Patterns, biases and prospects in the distribution and diversity of Neotropical snakes

MOTIVATION

We generated a novel database of Neotropical snakes (one of the world's richest herpetofauna) combining the most comprehensive, manually compiled distribution dataset with publicly available data. We assess, for the first time, the diversity patterns for all Neotropical snakes as well as sampling density and sampling biases.

MAIN TYPES OF VARIABLES CONTAINED

We compiled three databases of species occurrences: a dataset downloaded from the Global Biodiversity Information Facility (GBIF), a verified dataset built through taxonomic work and specialized literature, and a combined dataset comprising a cleaned version of the GBIF dataset merged with the verified dataset.

SPATIAL LOCATION AND GRAIN

Neotropics, Behrmann projection equivalent to 1° × 1°.

TIME PERIOD

Specimens housed in museums during the last 150 years.

MAJOR TAXA STUDIED

Squamata: Serpentes.

SOFTWARE FORMAT

Geographical information system (GIS).

RESULTS

The combined dataset provides the most comprehensive distribution database for Neotropical snakes to date. It contains 147,515 records for 886 species across 12 families, representing 74% of all species of snakes, spanning 27 countries in the Americas. Species richness and phylogenetic diversity show overall similar patterns. Amazonia is the least sampled Neotropical region, whereas most well-sampled sites are located near large universities and scientific collections. We provide a list and updated maps of geographical distribution of all snake species surveyed.

MAIN CONCLUSIONS

The biodiversity metrics of Neotropical snakes reflect patterns previously documented for other vertebrates, suggesting that similar factors may determine the diversity of both ectothermic and endothermic animals. We suggest conservation strategies for high-diversity areas and sampling efforts be directed towards Amazonia and poorly known species.

Land management: data availability and process understanding for global change studies

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.

Use FlowRepository to share your clinical data upon study publication

A fundamental tenet of scientific research is that published results including underlying data should be open to independent validation and refutation. Data sharing encourages collaboration, facilitates quality and reduces redundancy in data production. Authors submitting manuscripts to several journals have already adopted the habit of sharing their underlying flow cytometry data by deposition to FlowRepository-a data repository that is jointly supported by the International Society for Advancement of Cytometry, the International Clinical Cytometry Society and the European Society for Clinical Cell Analysis. De-identification is required for publishing data from clinical studies and we discuss ways to satisfy data sharing requirements and patient privacy requirements simultaneously. Scientific communities in the fields of microarray, proteomics, and sequencing have been benefiting from reuse and re-exploration of data in public repositories for over decade. We believe it is time that clinicians follow suit and that de-identified clinical data also become routinely available along with published cytometry-based findings. © 2016 International Clinical Cytometry Society.

Health Economic Data Requirements and Availability in the European Union: Results of a Survey Among 10 European Countries

OBJECTIVES

To compare data requirements and their availability for health economic (HE) evaluations in five countries in Central/Eastern Europe (CEE) (Poland, the Czech Republic, Slovakia, Hungary, and Romania) and five countries in Western Europe (WE) (the United Kingdom, France, Germany, The Netherlands, and Sweden).

METHODS

A questionnaire was developed and distributed to market access personnel from Pfizer who were asked to complete the questionnaire either from their own knowledge or with support of external experts. The questionnaire focused on the obligation to conduct HE assessment for reimbursement submissions, local HE guidelines, applied discount rates for future costs and effects, willingness-to-pay thresholds, and available data sources.

RESULTS

HE is mandatory in all CEE and three WE participating countries for reimbursement applications of innovative drugs. Usually, cost-effectiveness analysis and budget-impact analyses are required. The preferred outcome of cost-effectiveness analysis is quality-adjusted-life years. In Romania, France, and the Czech Republic, guidelines could not be identified at the time of the survey. The applicant usually prepares HE evaluations; in Sweden, the United Kingdom, The Netherlands, and Poland, unlocked models have to be presented for scrutiny. Discount rates vary from 1.5% to 5%, and, usually, is the same for costs and outcomes (except in The Netherlands and Poland). Only the United Kingdom, Poland, and Slovakia have an explicit willingness-to-pay threshold. In Poland, it is based on the gross domestic product per capita, and in Slovakia, it is based on multiples of average monthly salary. Differences were found on data availability. In WE, data can be acquired easier than in CEE. Health insurance funds do not provide their data unless they were published. Patient registries are either not available in CEE or difficult to access, so applicants mostly rely on retrospective medical chart data, hospital information systems, or expert panels.

CONCLUSIONS

We found similar requirements for HE analyses in CEE and WE but differences in data availability. This results in less accurate inputs across the CEE, influencing analyses' outcomes.

The extent of food waste generation across EU-27: different calculation methods and the reliability of their results

The reduction of food waste is seen as an important societal issue with considerable ethical, ecological and economic implications. The European Commission aims at cutting down food waste to one-half by 2020. However, implementing effective prevention measures requires knowledge of the reasons and the scale of food waste generation along the food supply chain. The available data basis for Europe is very heterogeneous and doubts about its reliability are legitimate. This mini-review gives an overview of available data on food waste generation in EU-27 and discusses their reliability against the results of own model calculations. These calculations are based on a methodology developed on behalf of the Food and Agriculture Organization of the United Nations and provide data on food waste generation for each of the EU-27 member states, broken down to the individual stages of the food chain and differentiated by product groups. The analysis shows that the results differ significantly, depending on the data sources chosen and the assumptions made. Further research is much needed in order to improve the data stock, which builds the basis for the monitoring and management of food waste.

Characteristics, availability and uses of vital registration and other mortality data sources in post-democracy South Africa

The value of good-quality mortality data for public health is widely acknowledged. While effective civil registration systems remains the 'gold standard' source for continuous mortality measurement, less than 25% of deaths are registered in most African countries. Alternative data collection systems can provide mortality data to complement those from civil registration, given an understanding of data source characteristics and data quality. We aim to document mortality data sources in post-democracy South Africa; to report on availability, limitations, strengths, and possible complementary uses of the data; and to make recommendations for improved data for mortality measurement. Civil registration and alternative mortality data collection systems, data availability, and complementary uses were assessed by reviewing blank questionnaires, death notification forms, death data capture sheets, and patient cards; legislation; electronic data archives and databases; and related information in scientific journals, research reports, statistical releases, government reports and books. Recent transformation has enhanced civil registration and official mortality data availability. Additionally, a range of mortality data items are available in three population censuses, three demographic surveillance systems, and a number of national surveys, mortality audits, and disease notification programmes. Child and adult mortality items were found in all national data sources, and maternal mortality items in most. Detailed cause-of-death data are available from civil registration and demographic surveillance. In a continent often reported as lacking the basic data to infer levels, patterns and trends of mortality, there is evidence of substantial improvement in South Africa in the availability of data for mortality assessment. Mortality data sources are many and varied, providing opportunity for comparing results and improved public health planning. However, more can and must be done to improve mortality measurement by improving data quality, triangulating data, and expanding analytic capacity. Cause data, in particular, must be improved.

Evaluation of the comprehensiveness and reliability of the chromium composition of foods in the literature ()

In the early 1960s, trivalent chromium Cr(3+) became recognized as an essential trace element due to its potential metabolic and cardiovascular benefits. No comprehensive chromium database currently exists; thus a thorough review of the literature was conducted to examine the availability and reliability of chromium data for foods. A number of key issues were identified that challenge the feasibility of adding chromium to a food and nutrient database. Foremost, dietary chromium data reported in the literature prior to 1980 cannot be relied on because of problematic analytical issues before that time. Next, paucity of data emerged as an issue that could impede database completeness. Finally, large variation in reported chromium content of foods may render disputable representative chromium values. This variation has been speculated to originate from differences in growing and particularly processing foods. Furthermore, contamination of chromium from laboratory equipment and/or materials is possible and also believed to contribute to the variation observed in reported values. As a result, database developers must carefully consider the availability and reliability of information on the chromium composition of foods when deciding whether to incorporate chromium into or exclude it from a nutrient database.