Long-term Ecological Research: Chasing fashions or being prepared for fashion changes?

Long-term-ecological-research (LTER) faces many challenges, including the difficulty of obtaining long-term funding, changes in research questions and sampling designs, keeping researchers collecting standardized data for many years, impediments to interactions with local people, and the difficulty of integrating the needs of local decision makers with "big science". These issues result in a lack of universally accepted guidelines as to how research should be done and integrated among LTER sites. Here we discuss how the RAPELD (standardized field infrastructure system), can help deal with these issues as a complementary technique in LTER studies, allowing comparisons across landscapes and ecosystems and reducing sampling costs. RAPELD uses local surveys to understand broad spatial and temporal patterns while enhancing decision-making and training of researchers, local indigenous groups and traditional communities. Sampling of ecological data can be carried out by different researchers through standardized protocols, resulting in spatial data that can be used to answer temporal questions, and allow new questions to be investigated. Results can also be integrated into existing biodiversity networks. Integrated systems are the most efficient way to save resources, maximize results, and accumulate information that can be used in the face of the unknown unknowns upon which our future depends.

The Program for Biodiversity Research in Brazil: The role of regional networks for biodiversity knowledge, dissemination, and conservation.

The Program for Biodiversity Research (PPBio) is an innovative program designed to integrate all biodiversity research stakeholders. Operating since 2004, it has installed long-term ecological research sites throughout Brazil and its logic has been applied in some other southern-hemisphere countries. The program supports all aspects of research necessary to understand biodiversity and the processes that affect it. There are presently 161 sampling sites (see some of them at Supplementary Appendix), most of which use a standardized methodology that allows comparisons across biomes and through time. To date, there are about 1200 publications associated with PPBio that cover topics ranging from natural history to genetics and species distributions. Most of the field data and metadata are available through PPBio web sites or DataONE. Metadata is available for researchers that intend to explore the different faces of Brazilian biodiversity spatio-temporal variation, as well as for managers intending to improve conservation strategies. The Program also fostered, directly and indirectly, local technical capacity building, and supported the training of hundreds of undergraduate and graduate students. The main challenge is maintaining the long-term funding necessary to understand biodiversity patterns and processes under pressure from global environmental changes.

Compositional response of Amazon forests to climate change.

Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Supporting biomedical ontology evolution by identifying outdated concepts and the required type of change.

The consistent evolution of ontologies is a major challenge for systems using semantically enriched data, for example, for annotating, indexing, or reasoning. The biomedical domain is a typical example where ontologies, expressed with different formalisms, have been used for a long time and whose dynamic nature requires the regular revision of underlying systems. However, the automatic identification of outdated concepts and proposition of revision actions to update them are still open research questions. Solutions to these problems are of great interest to organizations that manage huge and dynamic ontologies. In this paper, we present an approach for (i) identifying the concepts of an ontology that require revision and (ii) suggesting the type of revision. Our analysis is based on three aspects: structural information encoded in the ontology, relational information gained from external source of knowledge (i.e., PubMed and UMLS) and temporal information derived from the history of the ontology. Our approach aims to evaluate different methods and parameters used by supervised learning classifiers to identify both the set of concepts that need revision, and the type of revision. We applied our approach to four well-known biomedical ontologies/terminologies (ICD-9-CM, MeSH, NCIt and SNOMED CT) and compared our results to similar approaches. Our model shows accuracy ranging from 68% (for SNOMED CT) to 91% (for MeSH), and an average of 71% when considering all datasets together.

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

BACKGROUND: Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. METHODS: We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. RESULTS: We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. CONCLUSIONS: The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance.

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

Fast demographic traits promote high diversification rates of Amazonian trees.

The Amazon rain forest sustains the world's highest tree diversity, but it remains unclear why some clades of trees are hyperdiverse, whereas others are not. Using dated phylogenies, estimates of current species richness and trait and demographic data from a large network of forest plots, we show that fast demographic traits--short turnover times--are associated with high diversification rates across 51 clades of canopy trees. This relationship is robust to assuming that diversification rates are either constant or decline over time, and occurs in a wide range of Neotropical tree lineages. This finding reveals the crucial role of intrinsic, ecological variation among clades for understanding the origin of the remarkable diversity of Amazonian trees and forests.

Understanding semantic mapping evolution by observing changes in biomedical ontologies.

Knowledge Organization Systems (KOSs) are extensively used in the biomedical domain to support information sharing between software applications. KOSs are proposed covering different, but overlapping subjects, and mappings indicate the semantic relation between concepts from two KOSs. Over time, KOSs change as do the mappings between them. This can result from a new discovery or a revision of existing knowledge which includes corrections of concepts or mappings. Indeed, changes affecting KOS entities may force the underline mappings to be updated in order to ensure their reliability over time. To tackle this open research problem, we study how mappings are affected by KOS evolution. This article presents a detailed descriptive analysis of the impact that changes in KOS have on mappings. As a case study, we use the official mappings established between SNOMED CT and ICD-9-CM from 2009 to 2011. Results highlight factors according to which KOS changes in varying degrees influence the evolution of mappings.

Analysis and implementation of the DynDiff tool when comparing versions of ontology.

BACKGROUND: Ontologies play a key role in the management of medical knowledge because they have the properties to support a wide range of knowledge-intensive tasks. The dynamic nature of knowledge requires frequent changes to the ontologies to keep them up-to-date. The challenge is to understand and manage these changes and their impact on depending systems well in order to handle the growing volume of data annotated with ontologies and the limited documentation describing the changes. METHODS: We present a method to detect and characterize the changes occurring between different versions of an ontology together with an ontology of changes entitled DynDiffOnto, designed according to Semantic Web best practices and FAIR principles. We further describe the implementation of the method and the evaluation of the tool with different ontologies from the biomedical domain (i.e. ICD9-CM, MeSH, NCIt, SNOMEDCT, GO, IOBC and CIDO), showing its performance in terms of time execution and capacity to classify ontological changes, compared with other state-of-the-art approaches. RESULTS: The experiments show a top-level performance of DynDiff for large ontologies and a good performance for smaller ones, with respect to execution time and capability to identify complex changes. In this paper, we further highlight the impact of ontology matchers on the diff computation and the possibility to parameterize the matcher in DynDiff, enabling the possibility of benefits from state-of-the-art matchers. CONCLUSION: DynDiff is an efficient tool to compute differences between ontology versions and classify these differences according to DynDiffOnto concepts. This work also contributes to a better understanding of ontological changes through DynDiffOnto, which was designed to express the semantics of the changes between versions of an ontology and can be used to document the evolution of an ontology.

P2Y12 inhibitor monotherapy versus dual antiplatelet therapy in patients with acute coronary syndromes undergoing coronary stenting: rationale and design of the NEOMINDSET Trial.

Dual antiplatelet therapy (DAPT) is currently the standard of care after percutaneous coronary intervention (PCI). Recent studies suggest that reducing DAPT to 1-3 months followed by an aspirin-free single antiplatelet therapy (SAPT) strategy with a potent P2Y12 inhibitor is safe and associated with less bleeding. However, to date, no randomised trial has tested the impact of initiating SAPT immediately after PCI, particularly in patients with acute coronary syndromes (ACS). NEOMINDSET is a multicentre, randomised, open-label trial with a blinded outcome assessment designed to compare SAPT versus DAPT in 3,400 ACS patients undergoing PCI with the latest-generation drug-eluting stents (DES). After successful PCI and up to 4 days following hospital admission, patients are randomised to receive SAPT with a potent P2Y12 inhibitor (ticagrelor or prasugrel) or DAPT (aspirin plus a potent P2Y12 inhibitor) for 12 months. Aspirin is discontinued immediately after randomisation in the SAPT group. The choice between ticagrelor and prasugrel is at the investigator's discretion. The primary hypothesis is that SAPT will be non-inferior to DAPT with respect to the composite endpoint of all-cause mortality, stroke, myocardial infarction or urgent target vessel revascularisation, but superior to DAPT on rates of bleeding defined by Bleeding Academic Research Consortium 2, 3 or 5 criteria. NEOMINDSET is the first study that is specifically designed to test SAPT versus DAPT immediately following PCI with DES in ACS patients. This trial will provide important insights on the efficacy and safety of withdrawing aspirin in the early phase of ACS. (ClinicalTrials.gov: NCT04360720).

Influence of the dental implant number and load direction on stress distribution in a 3-unit implant-supported fixed dental prosthesis.

BACKGROUND: The choice between 2 or 3 implants to support a 3-unit implant-supported fixed dental prosthesis (FDP) still generates doubt in clinical practice. OBJECTIVES: The aim of this study was to evaluate stress distribution in 3-unit implant-supported FDPs according to the implant number and load direction. MATERIAL AND METHODS: A numerical simulation was performed to analyze stress and strain according to the implant number (2 or 3) and load direction (axial or oblique). A model of a jaw was created by means of the modeling software Rhinoceros, v. 5.0 SR8. External hexagon implants, micro-conical abutments and screws were also modeled. The final geometries were exported to the computer-aided engineering (CAE) software Ansys, v. 17.2, and all materials were considered homogeneous, isotropic and elastic. Different load directions were applied for each model (300 N) at the center of the prosthesis. RESULTS: The von Mises stress and strain values were obtained for the titanium structures and the bone, respectively. The implant number influenced the prosthesis biomechanics, with higher stress and strain concentrations when 2 implants were simulated. The oblique load also affected the mechanical response, showing higher stress and strain in comparison with the axial load, regardless of the implant number. CONCLUSIONS: It was concluded that for a 3-unit implant-supported FDP, a greater number of implants associated with axial loads can result in a better mechanical response during chewing.

Computer Aided Design Modelling and Finite Element Analysis of Premolar Proximal Cavities Restored with Resin Composites.

This study evaluated the stress distribution in five different class II cavities of premolar models restored with conventional or bulk-fill flowable composite by means of finite element analysis (FEA) under shrinkage and occlusal loading. An upper validated premolar model was imported in the software, and five class II cavities with different occlusal extensions and dimensions were prepared: horizontal cavity on the mesial surface (horizontal slot), mesio-occlusal cavity, mesial cavity (vertical slot), tunnel type cavity and direct access cavity. The models were restored with conventional or bulk-fill flowable resin composite. The tested materials were considered as homogeneous, linear, and isotropic. The Maximum Principal Stress criteria was chosen to evaluate the tensile stress results. The lowest shrinkage stress value was observed in the direct access cavity restored with bulk-fill flowable resin composite (36.12 MPa). The same cavity, restored with conventional composite showed a score of 36.14 MPa. The horizontal slot cavity with bulk-fill flowable showed a score of 46.71 MPa. The mesio-occlusal cavity with bulk-fill flowable had a score of 53.10 MPa, while with conventional composite this was 55.35 MPa. Higher shrinkage stress was found in the vertical slot cavity with conventional resin 56.14 MPa, followed by the same cavity with bulk-fill flowable 56.08 MPa. Results indicated that the use of bulk-fill flowable composite resin more significantly decreased the polymerization shrinkage stress magnitude. The larger the cavity and the volume of material necessary to restore the tooth, the greater the residual stress on enamel and dentin tissue.

Influence of Polymeric Restorative Materials on the Stress Distribution in Posterior Fixed Partial Dentures: 3D Finite Element Analysis.

BACKGROUND: This study evaluated the effect of interim restorative materials (acrylic resin (AR), resin composite (RC) or polyetheretherketone (PEEK) for dental computer-aided design/computer-aided manufacturing (CAD/CAM)) on the stress distribution of a posterior three-unit fixed partial denture. METHODS: The abutment teeth (first molar and first premolar) were modeled using the BioCAD protocol containing 1.5 mm of axial reduction and converging axial walls. A static structural analysis was performed in the computer-aided engineering software, and the Maximum Principal Stress criterion was used to analyze the prosthesis and the cement layers of both abutment teeth. The materials were considered isotropic, linearly elastic, homogeneous and with bonded contacts. An axial load (600 N) was applied to the occlusal surface of the second premolar. RESULTS: Regardless of the restorative material, the region of the prosthetic connectors showed the highest tensile stress magnitude. The highest stress peak was observed with the use of RC (129 MPa) compared to PEEK and AR. For the cement layers, RC showed the lowest values in the occlusal region (7 MPa) and the highest values for the cervical margin (14 MPa) compared to PEEK (21 and 12 MPa) and AR (21 and 13 MPa). CONCLUSIONS: Different interim restorative materials for posterior fixed partial dentures present different biomechanical behavior. The use of resin composite can attenuate the stress magnitude on the cement layer, and the use of acrylic resin can attenuate the stress magnitude on the connector region.

Non-structural carbohydrates mediate seasonal water stress across Amazon forests.

Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSCT) concentrations in both organs were remarkably similar across communities. However, NSCT and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSCT in the form of SS (SS:NSCT) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.

Drought-mortality relationships for tropical forests.

*The rich ecology of tropical forests is intimately tied to their moisture status. Multi-site syntheses can provide a macro-scale view of these linkages and their susceptibility to changing climates. Here, we report pan-tropical and regional-scale analyses of tree vulnerability to drought. *We assembled available data on tropical forest tree stem mortality before, during, and after recent drought events, from 119 monitoring plots in 10 countries concentrated in Amazonia and Borneo. *In most sites, larger trees are disproportionately at risk. At least within Amazonia, low wood density trees are also at greater risk of drought-associated mortality, independent of size. For comparable drought intensities, trees in Borneo are more vulnerable than trees in the Amazon. There is some evidence for lagged impacts of drought, with mortality rates remaining elevated 2 yr after the meteorological event is over. *These findings indicate that repeated droughts would shift the functional composition of tropical forests toward smaller, denser-wooded trees. At very high drought intensities, the linear relationship between tree mortality and moisture stress apparently breaks down, suggesting the existence of moisture stress thresholds beyond which some tropical forests would suffer catastrophic tree mortality.

Reference values of office central blood pressure, pulse wave velocity, and augmentation index recorded by means of the Mobil-O-Graph PWA monitor.

Assessment of central blood pressure (BP), pulse wave velocity (PWV), and augmentation index (AIx) measurements may improve cardiovascular risk stratification. This study aimed to establish reference office values for central BP, PWV, and AIx by means of a Mobil-O-Graph PWA monitor and to evaluate the impact of cardiovascular risk factors (CVRFs) on these measurements. We cross-sectionally evaluated clinical characteristics, central BP, PWV, AIx, and peripheral BP measurements among 867 apparently healthy individuals (age = 46.0 ± 15.5 years, 39% males) who were free of obesity, hypertension, active smoking, dyslipidemia, and diabetes (CVRF-No) and 5632 individuals (age = 57.0 ± 14.7 years, 44% males) with at least one of these major CVRFs (CVRF-Yes). Reference values for central BP, PWV, and AIx were provided for the CVRF-No and CVRF-Yes groups, stratified by age and sex. PWV and AIx exhibited curvilinear increases with age, and there was an interaction between age and sex for central systolic BP and PWV in both the CVRF-No and CVRF-Yes groups. The results of a multivariable analysis including the whole sample (n = 6499) showed that obesity had a direct association with central BP, while diabetes was directly related to PWV. In addition, alcohol intake was directly associated with central BP, while performance of physical activity was inversely related to AIx. In conclusion, values of office-measured central BP, PWV, and AIx obtained in an apparently healthy population and in a population with CVRFs are now available according to age and sex and may be useful to build thresholds for use in clinical practice.

Tree mode of death and mortality risk factors across Amazon forests.

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted-modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth-survival trade-off in driving tropical tree mortality.