The split-and-drift random graph, a null model for speciation

We introduce a new random graph model motivated by biological questions relating to speciation. This random graph is defined as the stationary distribution of a Markov chain on the space of graphs on $\{1, \ldots, n\}$. The dynamics of this Markov chain is governed by two types of events: vertex duplication, where at constant rate a pair of vertices is sampled uniformly and one of these vertices loses its incident edges and is rewired to the other vertex and its neighbors; and edge removal, where each edge disappears at constant rate. Besides the number of vertices $n$, the model has a single parameter $r_n$. Using a coalescent approach, we obtain explicit formulas for the first moments of several graph invariants such as the number of edges or the number of complete subgraphs of order $k$. These are then used to identify five non-trivial regimes depending on the asymptotics of the parameter $r_n$. We derive an explicit expression for the degree distribution, and show that under appropriate rescaling it converges to classical distributions when the number of vertices goes to infinity. Finally, we give asymptotic bounds for the number of connected components, and show that in the sparse regime the number of edges is Poissonian.Comment: added Proposition 2.4 and formal proofs of Proposition 2.3 and 2.

A branching process with coalescence to model random phylogenetic networks

We introduce a biologically natural, mathematically tractable model of random phylogenetic network to describe evolution in the presence of hybridization. One of the features of this model is that the hybridization rate of the lineages correlates negatively with their phylogenetic distance. We give formulas / characterizations for quantities of biological interest that make them straightforward to compute in practice. We show that the appropriately rescaled network, seen as a metric space, converges to the Brownian continuum random tree, and that the uniformly rooted network has a local weak limit, which we describe explicitly

Combinatorial and stochastic properties of ranked tree-child networks

Tree-child networks are a recently-described class of directed acyclic graphs that have risen to prominence in phylogenetics (the study of evolutionary trees and networks). Although these networks have a number of attractive mathematical properties, many combinatorial questions concerning them remain intractable. In this paper, we show that endowing these networks with a biologically relevant ranking structure yields mathematically tractable objects, which we term ranked tree-child networks (RTCNs). We explain how to derive exact and explicit combinatorial results concerning the enumeration and generation of these networks. We also explore probabilistic questions concerning the properties of RTCNs when they are sampled uniformly at random. These questions include the lengths of random walks between the root and leaves (both from the root to the leaves and from a leaf to the root); the distribution of the number of cherries in the network; and sampling RTCNs conditional on displaying a given tree. We also formulate a conjecture regarding the scaling limit of the process that counts the number of lineages in the ancestry of a leaf. The main idea in this paper, namely using ranking as a way to achieve combinatorial tractability, may also extend to other classes of networks

Synthèse en solution et en phase solide de petits carbocyles et étude de la formation de macrocycles à quatorze membres par réaction au palladium et au cuivre

La synthèse en solution et son application à la synthèse sur support solide sont présentées pour: (1) La réaction d'alkylation du connecteur malonate, (2) L'étude de la formation de cycles carbonés à cinq, six et sept membres avec deux connecteurs, le malonate et le phénylacétate, (3) L'étude de la formation de macrocycles à quatorze membres par cyclisation de type iodure aromatique--étain (type Stille) et de type étain--étain (type Piers)

Explaining Query Answers under Inconsistency-Tolerant Semantics over Description Logic Knowledge Bases (Extended Abstract)

The problem of querying description logic (DL) knowledge bases (KBs) using database-style queries (in particular, conjunctive queries) has been a major focus of recent DL research. Since scalability is a key concern, much of the work has focused on lightweight DLs for which query answering can be performed in polynomial time w.r.t. the size of the ABox. The DL-Lite family of lightweight DLs [10] is especially popular due to the fact that query answering can be reduced, via query rewriting, to the problem of standard database query evaluation. Since the TBox is usually developed by experts and subject to extensive debugging, it is often reasonable to assume that its contents are correct. By contrast, the ABox is typically substantially larger and subject to frequent modifications, making errors almost inevitable. As such errors may render the KB inconsistent, several inconsistency-tolerant semantics have been introduced in order to provide meaningful answers to queries posed over inconsistent KBs. Arguably the most well-known is the AR semantics [17], inspired by work on consistent query answering in databases (cf. [4] for a survey). Query answering under AR semantics amounts to considering those answers (w.r.t. standard semantics) that can be obtained from every repair, the latter being defined as an inclusion-maximal subset of the ABox that is consistent with the TBox. A more cautious semantics, called IAR semantics The need to equip reasoning systems with explanation services is widely acknowledged by the DL community. Indeed, there have been numerous works on axiom pinpointing, in which the objective is to identify (minimal) subsets of a KB that entail a given TBox axiom (or ABox assertion

Experimental silicification of the extremophilic Archaea Pyrococcus abyssi and Methanocaldococcus jannaschii: applications in the search for evidence of life in early Earth and extraterrestrial rocks

International audienceHydrothermal activity was common on the early Earth and associated micro-organisms would most likely have included thermophilic to hyperthermophilic species. 3.5–3.3 billion-year-old, hydrothermally influenced rocks contain silicified microbial mats and colonies that must have been bathed in warm to hot hydrothermal emanations. Could they represent thermophilic or hyperthermophilic micro-organisms and if so, how were they preserved? We present the results of an experiment to silicify anaerobic, hyperthermophilic micro-organisms from the Archaea Domain Pyrococcus abyssi and Methanocaldococcus jannaschii, that could have lived on the early Earth. The micro-organisms were placed in a silica-saturated medium for periods up to 1 year. Pyrococcus abyssi cells were fossilized but the M. jannaschii cells lysed naturally after the exponential growth phase, apart from a few cells and cell remains, and were not silicified although their extracellular polymeric substances were. In this first simulated fossilization of archaeal strains, our results suggest that differences between species have a strong influence on the potential for different micro-organisms to be preserved by fossilization and that those found in the fossil record represent probably only a part of the original diversity. Our results have important consequences for biosignatures in hydrothermal or hydrothermally influenced deposits on Earth, as well as on early Mars, as environmental conditions were similar on the young terrestrial planets and traces of early Martian life may have been similarly preserved as silicified microfossils

Examination of Urinary Pesticide Concentrations, Protective Behaviors, and Risk Perceptions Among Latino and Latina Farmworkers in Southwestern Idaho

Introduction: Studies have documented high levels of pesticide exposure among men farmworkers; however, few have examined exposures or the experiences of women farmworkers. Data gaps also exist regarding farmworkers’ perceived risk and control related to pesticides, information that is critical to develop protective interventions. Objective: We aimed to compare urinary pesticide biomarker concentrations between Latino and Latina farmworkers and examine associations with occupational characteristics, risk perceptions, perceived control, and protective behaviors. Methods: We enrolled a convenience sample of 62 farmworkers (30 men and 32 women) during the pesticide spray season from April–July 2022 in southwestern Idaho. Participants were asked to complete two visits within a seven-day period; at each visit, we collected a urine sample and administered a questionnaire assessing demographic and occupational information. Urine samples were composited and analyzed for 17 biomarkers of herbicides and of organophosphate (OP) and pyrethroid insecticides. Results: Ten pesticide biomarkers (TCPy, MDA, PNP, 3-PBA, 4-F-3-PBA, cis- and trans-DCCA, 2,4-D, Glyphosate, AMPA) were detected in \u3e80% of samples. Men and women had similar urinary biomarker concentrations (p = 0.19–0.94); however, women worked significantly fewer hours than men (p = 0.01), wore similar or greater levels of Personal Protective Equipment (PPE), and were slightly more likely to report having experienced an Acute Pesticide Poisoning (26% of women vs. 14% of men; p = 0.25). We observed inconsistencies in risk perceptions, perceived control, and protective behaviors among men. Discussion: Our study is one the first to examine pesticide exposure and risk perceptions among a cohort of farmworkers balanced on gender. Taken with previous findings, our results suggest that factors such as job tasks, biological susceptibility, or access to trainings and protective equipment might uniquely impact women farmworkers’ exposure and/or vulnerability to pesticides. Women represent an increasing proportion of the agricultural workforce, and larger studies are needed to disentangle these findings