scholarly journals Estimating probabilistic dark diversity based on the hypergeometric distribution

2019 ◽  
Author(s):  
Carlos P. Carmona ◽  
Robert Szava-Kovats ◽  
Meelis Pärtel
Keyword(s):  
Hypergeometric Distribution ◽  
Data Availability ◽  
Present Species ◽  
List Type ◽  
Species Frequency ◽  
Ecological Information ◽  
Degree Of Certainty ◽  
Species Membership ◽  
A Site ◽  
Best Estimator

AbstractThe biodiversity of a site includes the absent species from the region that are theoretically able to live in the site’s particular ecological conditions. These species constitute the dark diversity of the site. Unlike present species, dark diversity is unobservable and can only be estimated. Most existing methods to designate dark diversity act in a binary fashion. However, dark diversity is more suitably defined as a fuzzy set—in which the degree of certainty about species membership is expressed as a probability.We present a new method to estimate probabilistic dark diversity based on the hypergeometric distribution. The method relies on co-occurrences to infer the strength of the association between pairs of species and assign probabilistic adscription to dark diversity to absent species. We compare it with two established methods to estimate dark diversity (Beals index and favorability correction). To test the methods, we created simulations based on individual agents in which the suitability of each species in each site is known. We compared the ability of the methods to accurately predict suitability and the size of dark diversity, and compared their sensitivity to data availability. Further, we assessed the methods in two real datasets with nested sampling designs.Our simulations revealed that predictions of the Beals method were extremely sensitive to species frequency, and predicted suitability poorly. The Favorability transformation corrected this relationship, but did still predicted extremely low probabilities for species with very little information. The Hypergeometric method outperformed the Beals and Favorability methods in all considered aspects in the simulations and displayed better characteristics in the real datasets.Probabilistic consideratiosn of biodiversity will help to acknowledge the uncertainty associated with ecological information. Although the Beals method has been described as the best estimator of dark diversity, it should be preferred only when the goal is to predict future apperances of species. However, studies on dark diversity should focus on the ecological affinities of species. The Hypergeometric method is the most promising method to estimate probabilistic dark diversity and species pool composition based on co-occurrences.

scholarly journals Longitudinal experiences and impact of the COVID-19 pandemic among people with past or current eating disorders in Sweden

2021 ◽  
Author(s):  
Andreas Birgegård ◽  
Afrouz Abbaspour ◽  
Stina Borg ◽  
David Clinton ◽  
Emma Forsén Mantilla ◽  
...  
Keyword(s):  
Eating Disorders ◽  
Eating Disorder ◽  
Data Availability ◽  
Evidence Based ◽  
List Type ◽  
Convenience Sample ◽  
Eating Disorder Symptom ◽  
Disorder Symptom ◽  
Evidence Based Care ◽  
The Impact

AbstractObjectiveTo document the impact of the COVI-19 pandemic on the health and well-being of individuals with past and current eating disorders in Sweden.MethodWe re-contacted participants from two previous Swedish studies who had a known lifetime history of an eating disorder. Participants completed an online questionnaire about their health and functioning at baseline early in the pandemic (Wave 1; N=982) and six months later (Wave 2); N=646).ResultsThree important patterns emerged: 1) higher current eating disorder symptom levels were associated with greater anxiety, worry, and pandemic-related eating disorder symptom increase; 2) patterns were fairly stable across time, although a concerning number who reported being symptom-free at Wave 1 reported re-emergence of symptoms at Wave 2; and only a minority of participants with current eating disorders were in treatment, and of those who were in treatment, many reported fewer treatment sessions than pre-pandemic and decreased quality of care.ConclusionsThe COVID-19 pandemic is posing serious health challenges for individuals with eating disorders, whether currently symptomatic or in remission. We encourage health service providers and patient advocates to be alert to the needs of individuals with eating disorders and to take active measures to ensure access to appropriate evidence-based care both during and following the pandemic.Significant Outcomes and LimitationsIndividuals with eating disorders symptoms or current active disorder report higher adverse impact of COVID-19 on their mental healthEven individuals who were symptom-free early in the pandemic reported a resurgence of eating disorder symptomsA large proportion of symptomatic individuals were not in treatment for their eating disorder, services should be aware and access to evidence-based care should be ensured across SwedenLimitations included the use of a convenience sample with atypical diagnostic distribution, and a low initial response rate, possibly introducing bias and limiting generalisability.Data Availability StatementFully anonymized data are available from the corresponding author upon request.

scholarly journals Changes in social cohesion in a long-lived species under a perturbation regime

2019 ◽  
Author(s):  
M. Genovart ◽  
O. Gimenez ◽  
A. Bertolero ◽  
R. Choquet ◽  
D. Oro ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Social Cohesion ◽  
Group Living ◽  
Social Bonding ◽  
World Population ◽  
List Type ◽  
Social Species ◽  
The Social ◽  
Capture Recapture ◽  
A Site

AbstractUnderstanding the behaviour of a population under perturbations is crucial and can help to mitigate the effects of global change. Sociality can influence the dynamics of behavioural processes and plays an important role on populations’ resilience. However little is known about the effects of perturbations on the social cohesion of group-living animals.To explore the strength of social cohesion and its dynamics under perturbations, we studied an ecological system involving a colonial, long-lived species living in a site experiencing a shift to a perturbed regime. This regime, caused by the invasion of predators, led this colony to hold from 70% to only 3% of the total world population in only one decade. Because birds breed aggregated in discrete and annually changing patches within large colonies, we could disentangle whether annual aggregation was random or resulted from social bonding among individuals. Our goals were 1) to uncover if there was any long-term social bonding between individuals and 2) to examine whether the perturbation regime affected social cohesion.We explored social cohesion by means of contingency tables and, within the Social Network Analysis framework, by modeling interdependencies among observations using additive and multiplicative effects (AME) and accounted for missing data. We analysed 25 years of monitoring with an individual capture-recapture database of more than 3,500 individuals.We showed that social bonding occurs over years in this species. We additionally show that social bonding strongly decreased after the perturbation regime. We propose that sociality and individual behavioural heterogeneity have been playing a major role driving dispersal and thus population dynamics over the study period.Perturbations may lead not only to changes in individuals’ behaviours and fitness but also to a change in populations’ social cohesion. The demographic consequences of the breaking down of social bonds are still not well understood, but they can be critical for population dynamics of social species. Further studies considering individual heterogeneity, sociality and different types of perturbations should be carried out to improve our understanding on the resilience of social species.

scholarly journals kinesin recruitment by adapter SKIP on melanosomes is dynamically controlled by LC3B phosphorylation

2021 ◽  
Author(s):  
Yogaspoorthi Subramaniam ◽  
Divya Murthy ◽  
Desingu Ayyappa Raja ◽  
Amrita Ramkumar ◽  
Sridhar Sivasubbu ◽  
...  
Keyword(s):  
Incident Light ◽  
Zebrafish Embryos ◽  
Cell Periphery ◽  
List Type ◽  
Melanocyte Stimulating Hormone ◽  
External Cues ◽  
Lysosome Related Organelles ◽  
A Site ◽  
Molecular Components ◽  
Skin Tanning

AbstractAnterograde melanosome transport is essential for adaptive skin tanning response. However, the molecular components involved, their interplay and regulation by external cues in melanosome transport remain under-explored. Silencing of kinesin motors revealed that several members including the established KIF5B and a novel candidate KIF1B, mediate melanosome movement. The camouflage behaviour of zebrafish embryos induced by incident light or α -MSH requires kif1b, suggesting a conserved melanosome transport machinery across vertebrates. Interestingly, the peri-nuclear melanosome accumulation upon kinesin knockdown is recapitulated by the silencing of autophagy effector MAP1LC3B (LC3B). Pull-down assays identified KIF1B, but not KIF5B, to be the LC3B-associated kinesin. LC3B binds the adapter SKIP via its LIR docking region that is proximal to Thr12 residue, a site for phosphorylation by Protein Kinase A. We demonstrate that phosphorylation of LC3B at Thr12 is stimulated by α-MSH, which potentiates the anterograde melanosome transport. Thereby, our study, identifies a novel kinesin motor KIF1B for melanosome movement and establishes LC3B as the key molecular component that facilitates α-MSH responsive mobilization of melanosomes.Key HighlightsKinesin screen reveals non-redundant use of KIF5B, KIF1B motors for melanosome transportkif1b is required for camouflage response in zebrafish and melanosome movement in mammalsN-terminal region of LC3B interacts with adapter SKIP and couples kinesin KIF1Bα-MSH activates PKA-mediated phosphorylation of LC3B to potentiate anterograde movementSignificanceMelanosomes are lysosome related organelles containing melanin pigment, that are synthesized in melanocytes and transferred to the recipient keratinocytes of skin. This involves long range melanosome movement within melanocytes to reach cell periphery for the transfer to follow. Physiologically, UV protection involves local secretion of melanocyte stimulating hormone (α-MSH) that acts on melanocytes to promote skin tanning response. Herein, we investigate the components involved in this process and establish that the melanosome movement is dynamically controlled by α-MSH through phosphorylation of LC3B. These findings establish the mechanism behind the rapid distribution of melanosomes during tanning response and provide opportunity to intervene for sun protection.

scholarly journals Seeding COVID-19 across sub-Saharan Africa: an analysis of reported importation events across 48 countries

2020 ◽  
Author(s):  
Laura A Skrip ◽  
Prashanth Selvaraj ◽  
Brittany Hagedorn ◽  
Andre Lin Ouédraogo ◽  
Navideh Noori ◽  
...  
Keyword(s):  
Premature Death ◽  
Communicable Diseases ◽  
Data Availability ◽  
Sub Saharan Africa ◽  
Morbidity And Mortality ◽  
List Type ◽  
Travel History ◽  
Non Communicable Diseases ◽  
Sub Saharan ◽  
Ssa Countries

AbstractBackgroundThe first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. While case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, SSA countries remain vulnerable to COVID morbidity and mortality due to systemic healthcare weaknesses, less financial resources and infrastructure to address the new crisis, and untreated comorbidities. Variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events.MethodsConfirmed cases reported by SSA countries were line-listed to capture epidemiological details related to early transmission events into and within countries. Data were retrieved from publicly available sources, including institutional websites, situation reports, press releases, and social media accounts, with supplementary details obtained from news articles. A data availability score was calculated for each imported case in terms of how many indicators (sex, age, travel history, date of arrival in country, reporting date of confirmation, and how detected) could be identified. We assessed the relationship between time to first importation and overall Global Health Security Index (GHSI) using Cox regression. K-means clustering grouped countries according to healthcare capacity and health and demographic risk factors.ResultsA total of 13,201 confirmed cases of COVID-19 were reported by 48 countries in SSA during the 54 days following the first known introduction to the region. Out of the 2516 cases for which travel history information was publicly available, 1129 (44.9%) were considered importation events. At the regional level, imported cases tended to be male (65.0%), were a median 41.0 years old (Range: 6 weeks - 88 years), and most frequently had recent travel history from Europe (53.1%). The median time to reporting an introduction was 19 days; a country’s time to report its first importation was not related to GHSI, after controlling for air traffic. Countries that had, on average, the highest case fatality rates, lowest healthcare capacity, and highest probability of premature death due to non-communicable diseases were among the last to report any cases.ConclusionsCountries with systemic, demographic, and pre-existing health vulnerabilities to severe COVID-related morbidity and mortality are less likely to report any cases or may be reporting with limited public availability of information. Reporting on COVID detection and response efforts, as well as on trends in non-COVID illness and care-seeking behavior, is critical to assessing direct and indirect consequences and capacity needs in resource-constrained settings. Such assessments aid in the ability to make data-driven decisions about interventions, country priorities, and risk assessment.Key MessagesWe line-listed epidemiological indicators for the initial cases reported by 48 countries in sub-Saharan Africa by reviewing and synthesizing information provided by official institutional outlets and news sources.Our findings suggest that countries with the largest proportions of untreated comorbidities, as measured by probability of premature death due to non-communicable diseases, and the fewest healthcare resources tended to not be reporting any cases at one-month post-introduction into the region.Using data availability as a measure of gaps in detection and reporting and relating them to COVID-specific parameters for morbidity and mortality provides a measure of vulnerability.Accurate and available information on initial cases in seeding local outbreaks is key to projecting case counts and assessing the potential impact of intervention approaches, such that support for local data teams will be important as countries make decisions about control strategies.

scholarly journals The German Gestational Diabetes Study (PREG): Rationale, Methodology and Design

2021 ◽  
Author(s):  
Louise Fritsche ◽  
Julia Hummel ◽  
Robert Wagner ◽  
Dorina Löffler ◽  
Julia Hartkopf ◽  
...  
Keyword(s):  
Gestational Diabetes ◽  
Medical School ◽  
Data Access ◽  
Ethics Committee ◽  
Data Availability ◽  
List Type ◽  
Diabetes Research ◽  
Link Type ◽  
Study Participants

AbstractIntroductionSince the introduction of the new International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria for gestational diabetes mellitus (GDM) in 2012, diagnosis and treatment of GDM has improved. But even well-treated GDM might still have impact on long-term health of the mother and her offspring, though, this relation has not been conclusively studied yet.MethodsThe multicenter PREG study is designed to metabolically and phenotypically characterize women with a 75 g five-point oral glucose tolerance test (OGTT) during and repeatedly after pregnancy. The offspring of the study participants are followed up until adulthood with developmental tests and metabolic and epigenetic phenotyping in the PREG offspring study. By in-depth phenotyping of the mother and her offspring, we aim to elucidate the relationship of maternal hyperglycemia during pregnancy and adequate treatment and its impact on the long-term health for both.Ethics and disseminationThe study protocol has been reviewed and approved by the ethics committee of the University Hospital Tübingen (protocol numbers 218/2012BO2 and 617/2020BO1), the ethics committee of the Technical University Dresden (protocol number EK263072013), the ethics committee of the medical school of the Heinrich Heine University Düsseldorf (protocol number 4051) and the ethics committee of the medical school of University of Leipzig (protocol number 038-15-09032015). The results will be disseminated through conference presentations and peer-reviewed publications.RegistrationThe PREG study and the PREG offspring study are registered with Clinical Trials (ClinicalTrials.gov Identifiers: NCT04270578, NCT04722900).Strengths and limitations of this studyThe main strength of the multicenter PREG study are the in-depth phenotyping of mothers during pregnancy and repeatedly after delivery.Data acquisition and sample handling are done according to standard operating procedures in all study sites, thus, ensuring a high quality for each data point.A PREG biobank is set up and samples are available for researchers of the German Center for Diabetes Research (DZD).Children of the study participants are repeatedly examined to cover the period of childhood and adolescence.The PREG study is not planned as a population-based cohort but is enriched for GDM cases.Data Availability StatementAll requests for data and materials will be promptly reviewed by the Data Access Steering Committee to verify whether the request is subject to any intellectual property or confidentiality obligations. Individual-level data may be subject to confidentiality. Any data and materials that can be shared will be released via a Material Transfer Agreement.

scholarly journals Using historical dip net data to infer absence of flatwoods salamanders in stochastic environments

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12388
Author(s):  
George C. Brooks ◽  
Carola A. Haas
Keyword(s):  
Environmental Conditions ◽  
Landscape Connectivity ◽  
Breeding Population ◽  
Environmental Stochasticity ◽  
Stochastic Environments ◽  
Annual Variability ◽  
Biological Phenomena ◽  
Ambystoma Bishopi ◽  
Degree Of Certainty ◽  
A Site

Local extinction and undetected presence are two very different biological phenomena, but they can be challenging to differentiate. Stochastic environments hamper the development of standardized monitoring schemes for wildlife, and make it more challenging to plan and evaluate the success of conservation efforts. To avoid reintroductions of species at risk that could jeopardize extant populations, managers attempting translocation events require a higher level of confidence that a failure to confirm presence represents a true absence. For many pond breeding amphibians, monitoring of the breeding population occurs indirectly through larval surveys. Larval development and successful recruitment only occurs after a sequence of appropriate environmental conditions, thus it is possible for a breeding population of adults to exist at a site but for detectability of the species to be functionally zero. We investigate how annual variability in detection influences long-term monitoring efforts of Reticulated Flatwoods Salamanders (Ambystoma bishopi) breeding in 29 wetlands in Florida. Using 8 years of historic dip net data, we simulate plausible monitoring scenarios that incorporate environmental stochasticity into estimates of detection probability. We found that annual variation in environmental conditions precluded a high degree of certainty in predicting site status for low-intensity monitoring schemes. Uncertainty was partly alleviated by increasing survey effort, but even at the highest level of sampling intensity assessed, multiple years of monitoring are required to confidently determine presence/absence at a site. Combined with assessments of habitat quality and landscape connectivity, our results can be used to identify sites suitable for reintroduction efforts. Our methodologies can be generally applied to increase the effectiveness of surveys for diverse organisms for which annual variability in detectability is known.

scholarly journals 827 Streamlining design of safe and effective TCR therapies with AI

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A866-A866
Author(s):  
Mikolaj Mizera ◽  
Anna Sanecka-Duin ◽  
Maciej Jasiński ◽  
Paulina Król ◽  
Giovanni Mazzocco ◽  
...  
Keyword(s):  
Clinical Trial ◽  
T Cell ◽  
T Cell Receptors ◽  
In Silico ◽  
Data Availability ◽  
List Type ◽  
Development Fund ◽  
Cell Therapies ◽  
Cell Receptors ◽  
Cancer Immunotherapies

BackgroundAdoptive cell therapies with T lymphocytes expressing engineered T cell receptors (TCRs) are one of the most promising approaches to cancer therapy.1 However, the experimentally driven development of novel TCR therapies is limited by the enormous biological variability of peptide:Human Leukocyte Antigen:TCR (pHLA:TCR) complexes. The in silico methods hold the promise to streamline the discovery of novel TCR therapies by reducing costs and time of laboratory research. In particular, the prediction of TCR binding to a target antigen, as well as the prediction of TCR off-target toxicity2 can provide useful insights supporting the development of safe therapies. We aimed at the development of an experimentally validated AI model of pHLA:TCR binding that will help to prioritize and reduce the number of in vitro assays necessary to discover novel TCRs for cancer therapies.MethodsThe limiting factor of successful pHLA:TCR binding modeling is data availability and completeness of TCR characterization. To address this issue, we are building an oncological pHLA:TCR database with paired alpha and beta chain TCR sequences. We are collecting and sequencing tumor and normal samples from 100 cancer patients, as part of an observational clinical trial. Those data are then screened with the Ardigen's ArdImmune Vax platform3 4 to select immunogenic epitopes. T cells that bind those epitopes are subsequently sorted and used to generate TCR sequencing data at single-cell resolution. We use data-driven and simulation-based models to extract insights about the dynamics of a pHLA:TCR system to predict the binding probability and explain the inference made by the model.ResultsWe optimized our data collection pipeline for the cost-efficient acquisition of a large oncological pHLA:TCR dataset. These data will enable us to build efficient models to streamline the development of TCR therapies against cancer.We benchmarked our modeling approach for pHLA:TCR binding against existing solutions5–7 on publicly available data. We also show how focus on model explainability facilitates the detection of model inconsistency of uncertain predictions by expert inspection. Our toxicity assessment solution2 extends the applicability of our system to the prediction of TCR safety profile.ConclusionsThe presented work shows perspectives and limitations of AI-aided TCR therapy development. We present results for our pHLA:TCR binding model, a TCR-toxicity-screening solution, and the study design of our observational clinical trial. Our growing database of pHLA:TCR interactions will enable us to develop highly predictive pHLA:TCR binding models, in particular for oncological targets.AcknowledgementsWe acknowledge funding through the project “Creating an innovative AI-based (Artificial Intelligence) IN SILICO TECHNOLOGY TCRact to launch a NEW SERVICE for designing and optimizing T-cell receptors (TCR) for use in cancer immunotherapies” cofunded by European Regional Development Fund (ERDF) as part of Smart Growth Operational Programme 2014–2020.ReferencesFarkona S, Diamandis EP, Blasutig IM. Cancer immunotherapy: the beginning of the end of cancer? BMC Med 2016;14:73. PMCID: PMC4858828.Murcia Pienkowski VA, Mazzocco G, Niemiec I, Sanecka-Duin A, Krol P, Myronov O, Skoczylas P, Kaczmarczyk J, Blum A. Off-target toxicity prediction in cellular cancer immunotherapies [Internet]. Cytotherapy. 2021;S96. Available from: http://dx.doi.org/10.1016/s1465324921004229.Stepniak P, Mazzocco G, Myronov A, Niemiec I, Gruba K, Skoczylas P, Sanecka-Duin A, Drwal M, Kaczmarczyk J. AI-augmented design of effective therapeutic cancer vaccines and adoptive cell therapies. Journal For Immunotherapy Of Cancer. Bmc Campus, 4 Crinan St, London N1 9xw, England; 2019.Mazzocco G, Niemiec I, Myronov A, Skoczylas P, Kaczmarczyk J, Sanecka-Duin A, Gruba K, Król P, Drwal M, Szczepanik M, Pyrc K, Stȩpniak P. AI aided design of epitope-based vaccine for the induction of cellular immune responses against SARS-CoV-2. Front Genet. 2021;12:602196. PMCID: PMC8027494.Weber A, Born J, Rodriguez Martínez M. TITAN: T-cell receptor specificity prediction with bimodal attention networks. Bioinformatics. 2021;37(Suppl_1):i237–i244. PMCID: PMC8275323.Springer I, Besser H, Tickotsky-Moskovitz N, Dvorkin S, Louzoun Y. Prediction of specific TCR-peptide binding from large dictionaries of TCR-Peptide Pairs. Front Immunol 2020;11:1803. PMCID: PMC7477042.Jurtz VI, Jessen LE, Bentzen AK, Jespersen MC, Mahajan S, Vita R, Jensen KK, Marcatili P, Hadrup SR, Peters B, Nielsen M. NetTCR: sequence-based prediction of TCR binding to peptide-MHC complexes using convolutional neural networks [Internet]. Available from: http://dx.doi.org/10.1101/433706

scholarly journals An Rshiny app for modelling environmental DNA data: accounting for false positive and false negative observation error

2020 ◽  
Author(s):  
Alex Diana ◽  
Eleni Matechou ◽  
Jim E. Griffin ◽  
Andrew S. Buxton ◽  
Richard A. Griffiths
Keyword(s):  
Statistical Method ◽  
False Positive ◽  
False Negative ◽  
Environmental Dna ◽  
Bayesian Variable Selection ◽  
Observation Error ◽  
List Type ◽  
Data Set ◽  
A Site ◽  
User Friendly

AbstractEnvironmental DNA (eDNA) surveys have become a popular tool for assessing the distribution of species. However, it is known that false positive and false negative observation error can occur at both stages of eDNA surveys, namely the field sampling stage and laboratory analysis stage.We present an RShiny app that implements the Griffin et al. (2019) statistical method, which accounts for false positive and false negative errors in both stages of eDNA surveys. Following Griffin et al. (2019), we employ a Bayesian approach and perform efficient Bayesian variable selection to identify important predictors for the probability of species presence as well as the probabilities of observation error at either stage.We demonstrate the RShiny app using a data set on great crested newts collected by Natural England in 2018 and we identify water quality, pond area, fish presence, macrophyte cover, frequency of drying as important predictors for species presence at a site.The state-of-the-art statistical method that we have implemented is the only one that has specifically been developed for the purposes of modelling false negatives and false positives in eDNA data. Our RShiny app is user-friendly, requires no prior knowledge of R and fits the models very efficiently. Therefore, it should be part of the tool-kit of any researcher or practitioner who is collecting or analysing eDNA data.

scholarly journals Habitat differences filter functional diversity of low dispersive microscopic animals

2020 ◽  
Author(s):  
Alejandro Martínez ◽  
Guillermo García-Gómez ◽  
Álvaro García-Herrero ◽  
Nuria Sánchez ◽  
Fernando Pardos ◽  
...  
Keyword(s):  
Functional Diversity ◽  
Functional Traits ◽  
Environmental Variables ◽  
Habitat Preferences ◽  
Functional Space ◽  
Temporal Variations ◽  
Data Availability ◽  
List Type ◽  
Long Distance ◽  
Habitat Differences

AbstractWhereas the study of patterns of distribution of microscopic animals has long been dominated by the ubiquity paradigm, we are starting to appreciate that microscopic animals are not as widespread as previously thought and that habitat preferences may have a strong role in structuring their patterns of occurrence. However, we still ignore to what extent and through which mechanisms the environment selects for specific communities or traits in microscopic animals. This gap is partly due to the lack of data on the relevant traits of many species, and partly because measuring environmental variables at an appropriate resolution may be problematic.We here overcome both issues by analysing the functional space of marine mite communities living in a sea-grass (Posidonia oceanica) meadow across two habitats: the leaves and the matte. The strictly benthic lifestyle and the conserved morphology of mites allow for unambiguous characterization of their functional traits, while the discrete nature of the two habitats alleviates the uncertainty in their ecological characterization.Our results show that habitat filters the distribution of certain traits favouring a higher diversity, dispersion, and evenness of functional traits in the matte than in the leaves. We further observed temporal variations in the functional diversity of communities, potentially following the seasonal renovation and decay of seagrass leaves. However, in spite of the stark ecological differences between the two habitats and across seasons, the filtering effect is partial and affects mostly relative species abundances.We conclude that in other microscopic organisms, habitat filtering might appear even more subtle especially if they are capable of long distance dispersal or occur in ecological systems where environmental variables vary continuously or fluctuate through time. Our study therefore emphasises the need of moving from a merely taxonomical toward a functional view of ecological studies of microscopic organisms if we want to achieve a mechanistic understanding of their habitat and distribution patterns.Data availability statementRaw data and R script to generate the analyses will be deposited in a public repository upon acceptance.

scholarly journals Platelets in pediatric and neonatal sepsis: novel mediators of the inflammatory cascade

2021 ◽  
Author(s):  
Daniel O’Reilly ◽  
Claire A. Murphy ◽  
Richard Drew ◽  
Afif El-Khuffash ◽  
Patricia B. Maguire ◽  
...  
Keyword(s):  
Immune System ◽  
Immune Cells ◽  
Immune Cell ◽  
List Type ◽  
Innate And Adaptive Immunity ◽  
Complex Relationships ◽  
A Site ◽  
Cellular Components ◽  
Common Understanding ◽  
Platelet Transfusions

Abstract Sepsis, a dysregulated host response to infection, has been difficult to accurately define in children. Despite a higher incidence, especially in neonates, a non-specific clinical presentation alongside a lack of verified biomarkers has prevented a common understanding of this condition. Platelets, traditionally regarded as mediators of haemostasis and thrombosis, are increasingly associated with functions in the immune system with involvement across the spectrum of innate and adaptive immunity. The large number of circulating platelets (approx. 150,000 cells per microlitre) mean they outnumber traditional immune cells and are often the first to encounter a pathogen at a site of injury. There are also well-described physiological differences between platelets in children and adults. The purpose of this review is to place into context the platelet and its role in immunology and examine the evidence where available for its role as an immune cell in childhood sepsis. It will examine how the platelet interacts with both humoral and cellular components of the immune system and finally discuss the role the platelet proteome, releasate and extracellular vesicles may play in childhood sepsis. This review also examines how platelet transfusions may interfere with the complex relationships between immune cells in infection. Impact Platelets are increasingly being recognised as important “first responders” to immune threats. Differences in adult and paediatric platelets may contribute to differing immune response to infections. Adult platelet transfusions may affect infant immune responses to inflammatory/infectious stimuli.

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