Trait positions for elevated invasiveness in adaptive ecological networks

Our ability to predict the outcome of invasion declines rapidly as non-native species progress through intertwined ecological barriers to establish and spread in recipient ecosystems. This is largely due to the lack of systemic knowledge on key processes at play as species establish self-sustaining populations within the invaded range. To address this knowledge gap, we present a mathematical model that captures the eco-evolutionary dynamics of native and non-native species interacting within an ecological network. The model is derived from continuous-trait evolutionary game theory (i.e., Adaptive Dynamics) and its associated concept of invasion fitness which depicts dynamic demographic performance that is both trait mediated and density dependent. Our approach allows us to explore how multiple resident and non-native species coevolve to reshape invasion performance, or more precisely invasiveness, over trait space. The model clarifies the role of specific traits in enabling non-native species to occupy realised opportunistic niches. It also elucidates the direction and speed of both ecological and evolutionary dynamics of residing species (natives or non-natives) in the recipient network under different levels of propagule pressure. The versatility of the model is demonstrated using four examples that correspond to the invasion of (i) a horizontal competitive community; (ii) a bipartite mutualistic network; (iii) a bipartite antagonistic network; and (iv) a multi-trophic food web. We identified a cohesive trait strategy that enables the success and establishment of non-native species to possess high invasiveness. Specifically, we find that a non-native species can achieve high levels of invasiveness by possessing traits that overlap with those of its facilitators (and mutualists), which enhances the benefits accrued from positive interactions, and by possessing traits outside the range of those of antagonists, which mitigates the costs accrued from negative interactions. This ‘central-to-reap, edge-to-elude’ trait strategy therefore describes the strategic trait positions of non-native species to invade an ecological network. This model provides a theoretical platform for exploring invasion strategies in complex adaptive ecological networks

Beyond the Ultra-deep Frontier Fields And Legacy Observations (BUFFALO): a high-resolution strong + weak-lensing view of Abell 370

The HST treasury program BUFFALO provides extended wide-field imaging of the six Hubble Frontier Fields galaxy clusters. Here we present the combined strong and weak-lensing analysis of Abell 370, a massive cluster at z=0.375. From the reconstructed total projected mass distribution in the 6arcmin x 6arcmin BUFFALO field-of-view, we obtain the distribution of massive substructures outside the cluster core and report the presence of a total of seven candidates, each with mass $\sim 5 \times 10^{13}M_{\odot}$. Combining the total mass distribution derived from lensing with multi-wavelength data, we evaluate the physical significance of each candidate substructure, and conclude that 5 out of the 7 substructure candidates seem reliable, and that the mass distribution in Abell 370 is extended along the North-West and South-East directions. While this finding is in general agreement with previous studies, our detailed spatial reconstruction provides new insights into the complex mass distribution at large cluster-centric radius. We explore the impact of the extended mass reconstruction on the model of the cluster core and in particular, we attempt to physically explain the presence of an important external shear component, necessary to obtain a low root-mean-square separation between the model-predicted and observed positions of the multiple images in the cluster core. The substructures can only account for up to half the amplitude of the external shear, suggesting that more effort is needed to fully replace it by more physically motivated mass components. We provide public access to all the lensing data used as well as the different lens models.Comment: 29 pages, 17 figures, 3 table

Repeated Human Exposure to Semivolatile Organic Compounds by Inhalation: Novel Protocol for a Nonrandomized Study.

peer reviewed[en] BACKGROUND: Semivolatile organic compounds (SVOCs) comprise several different chemical families used mainly as additives in many everyday products. SVOCs can be released into the air as aerosols and deposit on particulate matter during use by dispersion, evaporation, or abrasion. Phthalates are SVOCs of growing concern due to their endocrine-disrupting effects. Human data on the absorption, distribution, metabolism, and excretion (ADME) of these compounds upon inhalation are almost nonexistent. OBJECTIVE: The goal of this study is to develop a method for repeated inhalation exposures to SVOCs to characterize their ADME in humans. METHODS: We will use diethylhexyl phthalate (DEHP), a major indoor air pollutant, as a model SVOC in this novel protocol. The Swiss official Commission on Ethics in Human Research, Canton de Vaud, approved the study on October 14, 2020 (project-ID 2020-01095). Participants (n=10) will be repeatedly exposed (2 short daily exposures over 4 days) to isotope-labeled DEHP (DEHP-d4) to distinguish administered exposures from background exposures. DEHP-d4 aerosols will be generated with a small, portable, aerosol-generating device. Participants will inhale DEHP-d4-containing aerosols themselves with this device at home. Air concentrations of the airborne phthalates will be less than or equal to their occupational exposure limit (OEL). DEHP-d4 and its metabolites will be quantified in urine and blood before, during, and after exposure. RESULTS: Our developed device can generate DEHP-d4 aerosols with diameters of 2.5 μm or smaller and a mean DEHP-d4 mass of 1.4 (SD 0.2) μg per puff (n=6). As of May 2023, we have enrolled 5 participants. CONCLUSIONS: The portable device can be used to generate phthalate aerosols for repeated exposure in human studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51020

Drugs targeting the bone microenvironment: new therapeutic tools in Ewing's sarcoma?

Introduction: Ewing's sarcoma (ES) is the second most frequent malignant primary bone tumour in children, adolescents and young adults. The overall survival is 60 – 70% at 5 years but still very poor for patients with metastases, disease relapse or for those not responding to chemotherapy. For these high risk patients, new therapeutic approaches are needed beyond conventional therapies (chemotherapy, surgery and radiation) such as targeted therapies. Areas covered: Transcriptomic and genomic analyses in ES have revealed alterations in genes that control signalling pathways involved in many other cancer types. To set up more specific approaches, it is reasonable to think that the particular microenvironment of these bone tumours is essential for their initiation and progression, including in ES. To support this hypothesis, preclinical studies using drugs targeting bone cells (bisphosphonate zoledronate, anti-receptor activator of NF-κB ligand strategies) showed promising results in animal models. This review will discuss the new targeted therapeutic options in ES, focusing more particularly on the ones modulating the bone microenvironment. Expert opinion: Targeting the microenvironment represents a new option for patients with ES. The proof-of-concept has been demonstrated in preclinical studies using relevant animal models, especially for zoledronate, which induced a strong inhibition of tumour progression in an orthotopic bone model

A Membrane Protein/Signaling Protein Interaction Network for Arabidopsis Version AMPv2

Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs) out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway-compatible vector. The mating-based split ubiquitin system was used to screen for potential protein–protein interactions (pPPIs) among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases (RLKs), 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions, and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 386) pPPIs between 179 proteins, yielding a scale-free network (r2 = 0.863). Eighty of 142 transmembrane RLKs tested positive, identifying 3 homomers, 63 heteromers, and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs) had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G-protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Light and heavy fragments mass correlation in the 197Au+130Te transfer reaction

We studied multinucleon transfer (MNT) processes in the 197Au+130Te at Elab=1.07 GeV system coupling the PRISMA magnetic spectrometer to NOSE, an ancillary particle detector. We constructed a mass correlation matrix associating to each light fragment identified in PRISMA the corresponding mass distribution of the heavy partner detected in NOSE and, through the comparison with Monte Carlo simulations, we could infer about the role of neutron evaporation in multinucleon transfer reactions for the population of neutron-rich heavy nuclei

Using Dynamic Stochastic Modelling to Estimate Population Risk Factors in Infectious Disease: The Example of FIV in 15 Cat Populations

BACKGROUND:In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS:To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION:Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease