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This paper presents new palaeoecological data from north County Mayo (Co. Mayo), western Ireland, and reviews published data with a view to achieving a better understanding of the timing and nature of early farming in the region, its impact on the natural environment, and the factors, including climate change, that influenced mid- and late-Holocene vegetation dynamics and farming in the region. A long pollen profile from Glenulra, a deep basin situated within Céide Fields, and short profiles from blanket peat that overlies the prehistoric stone-wall field system provide unambiguous evidence for substantial farming, including widespread woodland clearance, in the early British and Irish Neolithic (beginning ca. 3800 BCE). This was followed by a distinct lull that lasted several centuries until farming activity resumed again, at first modestly (at ca. 2700 BCE) and then more markedly from 2350 BCE, i.e. at the Neolithic–Chalcolithic transition. It is argued on the basis of this and other palaeoecological evidence, including pollen analytical investigations at nearby Garrynagran, that, contrary to recent suggestions, there is no reason to doubt the widely held view that the stone-wall field system – unique in a western European Neolithic context – is correctly ascribable to the earlier part of the British and Irish Neolithic. The history of pine growing in bog contexts (mainly blanket bog) in the region is considered in the light of 14C dates derived from pine timbers, and the results of dendrochronological investigations at Garrynagran that have enabled two floating pine chronologies to be constructed, are presented. The climatic implications of these data are discussed within local and wider regional contexts.

This study sought to understand how state-level policies inform and promote the implementation of restorative justice in education (RJE). A content analysis of 60 laws revealed that definitions, structures, and supports varied greatly, causing us to question whether policies support a systematic implementation of RJE and how policies can prevent the misuse of RJE as an alternative system of punishment. We recommend that laws clearly define the paradigm shift underlying RJE, and provide sustained support to promote a realignment of policies and practices with attention to incorporating measures of accountability to larger values surrounding equity and justice.

Abstract Background Electronic health record (EHR) transitions are known to be highly disruptive, can drastically impact clinician and staff experiences, and may influence patients’ experiences using the electronic patient portal. Clinicians and staff can gain insights into patient experiences and be influenced by what they see and hear from patients. Through the lens of an emergency preparedness framework, we examined clinician and staff reactions to and perceptions of their patients’ experiences with the portal during an EHR transition at the Department of Veterans Affairs (VA). Methods This qualitative case study was situated within a larger multi-methods evaluation of the EHR transition. We conducted a total of 122 interviews with 30 clinicians and staff across disciplines at the initial VA EHR transition site before, immediately after, and up to 12 months after go-live (September 2020-November 2021). Interview transcripts were coded using a priori and emergent codes. The coded text segments relevant to patient experience and clinician interactions with patients were extracted and analyzed to identify themes. For each theme, recommendations were defined based on each stage of an emergency preparedness framework (mitigate, prepare, respond, recover). Results In post-go-live interviews participants expressed concerns about the reliability of communicating with their patients via secure messaging within the new EHR portal. Participants felt ill-equipped to field patients’ questions and frustrations navigating the new portal. Participants learned that patients experienced difficulties learning to use and accessing the portal; when unsuccessful, some had difficulties obtaining medication refills via the portal and used the call center as an alternative. However, long telephone wait times provoked patients to walk into the clinic for care, often frustrated and without an appointment. Patients needing increased in-person attention heightened participants’ daily workload and their concern for patients’ well-being. Recommendations for each theme fit within a stage of the emergency preparedness framework. Conclusions Application of an emergency preparedness framework to EHR transitions could help address the concerns raised by the participants, (1) mitigating disruptions by identifying at-risk patients before the transition, (2) preparing end-users by disseminating patient-centered informational resources, (3) responding by building capacity for disrupted services, and (4) recovering by monitoring integrity of the new portal function.

Abstract The last decade of phylogenetics has seen the development of many methods that leverage constraints plus dynamic programming. The goal of this algorithmic technique is to produce a phylogeny that is optimal with respect to some objective function and that lies within a constrained version of tree space. The popular species tree estimation method ASTRAL, for example, returns a tree that (1) maximizes the quartet score computed with respect to the input gene trees and that (2) draws its branches (bipartitions) from the input constraint set. This technique has yet to be used for parsimony problems where the input are binary characters, sometimes with missing values. Here, we introduce the clade-constrained character parsimony problem and present an algorithm that solves this problem for the Dollo criterion score in $$O(|\Sigma |^{3.726}(n+k) + |\Sigma |^{1.726}nk)$$ O ( | Σ | 3.726 ( n + k ) + | Σ | 1.726 n k ) time, where n is the number of leaves, k is the number of characters, and $$\Sigma$$ Σ is the set of clades used as constraints. Dollo parsimony, which requires traits/mutations to be gained at most once but allows them to be lost any number of times, is widely used for tumor phylogenetics as well as species phylogenetics, for example analyses of low-homoplasy retroelement insertions across the vertebrate tree of life. This motivated us to implement our algorithm in a software package, called Dollo-CDP, and evaluate its utility for analyzing retroelement insertion presence / absence patterns for bats, birds, toothed whales as well as simulated data. Our results show that Dollo-CDP can improve upon heuristic search from a single starting tree, often recovering a better scoring tree. Moreover, Dollo-CDP scales to data sets with much larger numbers of taxa than branch-and-bound while still having an optimality guarantee, albeit a more restricted one. Lastly, we show that our algorithm for Dollo parsimony can easily be adapted to Camin-Sokal parsimony but not Fitch parsimony.

Abstract Cancer progression and treatment can be informed by reconstructing its evolutionary history from tumor cells. Although many methods exist to estimate evolutionary trees (called phylogenies) from molecular sequences, traditional approaches assume the input data are error-free and the output tree is fully resolved. These assumptions are challenged in tumor phylogenetics because single-cell sequencing produces sparse, error-ridden data and because tumors evolve clonally. Here, we study the theoretical utility of methods based on quartets (four-leaf, unrooted phylogenetic trees) in light of these barriers. We consider a popular tumor phylogenetics model, in which mutations arise on a (highly unresolved) tree and then (unbiased) errors and missing values are introduced. Quartets are then implied by mutations present in two cells and absent from two cells. Our main result is that the most probable quartet identifies the unrooted model tree on four cells. This motivates seeking a tree such that the number of quartets shared between it and the input mutations is maximized. We prove an optimal solution to this problem is a consistent estimator of the unrooted cell lineage tree; this guarantee includes the case where the model tree is highly unresolved, with error defined as the number of false negative branches. Lastly, we outline how quartet-based methods might be employed when there are copy number aberrations and other challenges specific to tumor phylogenetics.

Abstract Background The Salmonella enterica serovar Newport red onion outbreak of 2020 was the largest foodborne outbreak of Salmonella in over a decade. The epidemiological investigation suggested two farms as the likely source of contamination. However, single nucleotide polymorphism (SNP) analysis of the whole genome sequencing data showed that none of the Salmonella isolates collected from the farm regions were linked to the clinical isolates—preventing the use of phylogenetics in source identification. Here, we explored an alternative method for analyzing the whole genome sequencing data driven by the hypothesis that if the outbreak strain had come from the farm regions, then the clinical isolates would disproportionately contain plasmids found in isolates from the farm regions due to horizontal transfer. Results SNP analysis confirmed that the clinical isolates formed a single, nearly-clonal clade with evidence for ancestry in California going back a decade. The clinical clade had a large core genome (4,399 genes) and a large and sparsely distributed accessory genome (2,577 genes, at least 64% on plasmids). At least 20 plasmid types occurred in the clinical clade, more than were found in the literature for Salmonella Newport. A small number of plasmids, 14 from 13 clinical isolates and 17 from 8 farm isolates, were found to be highly similar (> 95% identical)—indicating they might be related by horizontal transfer. Phylogenetic analysis was unable to determine the geographic origin, isolation source, or time of transfer of the plasmids, likely due to their promiscuous and transient nature. However, our resampling analysis suggested that observing a similar number and combination of highly similar plasmids in random samples of environmental Salmonella enterica within the NCBI Pathogen Detection database was unlikely, supporting a connection between the outbreak strain and the farms implicated by the epidemiological investigation. Conclusion Horizontally transferred plasmids provided evidence for a connection between clinical isolates and the farms implicated as the source of the outbreak. Our case study suggests that such analyses might add a new dimension to source tracking investigations, but highlights the need for detailed and accurate metadata, more extensive environmental sampling, and a better understanding of plasmid molecular evolution.

Abstract Background Face-to-face feedback plays an important role in health professionals’ workplace learning. The literature describes guiding principles regarding effective feedback but it is not clear how to enact these. We aimed to create a Feedback Quality Instrument (FQI), underpinned by a social constructivist perspective, to assist educators in collaborating with learners to support learner-centred feedback interactions. In earlier research, we developed a set of observable educator behaviours designed to promote beneficial learner outcomes, supported by published research and expert consensus. This research focused on analysing and refining this provisional instrument, to create the FQI ready-to-use. Methods We collected videos of authentic face-to-face feedback discussions, involving educators (senior clinicians) and learners (clinicians or students), during routine clinical practice across a major metropolitan hospital network. Quantitative and qualitative analyses of the video data were used to refine the provisional instrument. Raters administered the provisional instrument to systematically analyse educators’ feedback practice seen in the videos. This enabled usability testing and resulted in ratings data for psychometric analysis involving multifaceted Rasch model analysis and exploratory factor analysis. Parallel qualitative research of the video transcripts focused on two under-researched areas, psychological safety and evaluative judgement, to provide practical insights for item refinement. The provisional instrument was revised, using an iterative process, incorporating findings from usability testing, psychometric testing and parallel qualitative research and foundational research. Results Thirty-six videos involved diverse health professionals across medicine, nursing and physiotherapy. Administering the provisional instrument generated 174 data sets. Following refinements, the FQI contained 25 items, clustered into five domains characterising core concepts underpinning quality feedback: set the scene, analyse performance, plan improvements, foster learner agency, and foster psychological safety. Conclusions The FQI describes practical, empirically-informed ways for educators to foster quality, learner-centred feedback discussions. The explicit descriptions offer guidance for educators and provide a foundation for the systematic analysis of the influence of specific educator behaviours on learner outcomes.

Abstract One of the Grand Challenges in Science is the construction of the Tree of Life, an evolutionary tree containing several million species, spanning all life on earth. However, the construction of the Tree of Life is enormously computationally challenging, as all the current most accurate methods are either heuristics for NP-hard optimization problems or Bayesian MCMC methods that sample from tree space. One of the most promising approaches for improving scalability and accuracy for phylogeny estimation uses divide-and-conquer: a set of species is divided into overlapping subsets, trees are constructed on the subsets, and then merged together using a “supertree method”. Here, we present Exact-RFS-2, the first polynomial-time algorithm to find an optimal supertree of two trees, using the Robinson-Foulds Supertree (RFS) criterion (a major approach in supertree estimation that is related to maximum likelihood supertrees), and we prove that finding the RFS of three input trees is NP-hard. Exact-RFS-2 is available in open source form on Github at https://github.com/yuxilin51/GreedyRFS .

Abstract Motivation Estimated gene trees are often inaccurate, due to insufficient phylogenetic signal in the single gene alignment, among other causes. Gene tree correction aims to improve the accuracy of an estimated gene tree by using computational techniques along with auxiliary information, such as a reference species tree or sequencing data. However, gene trees and species trees can differ as a result of gene duplication and loss (GDL), incomplete lineage sorting (ILS), and other biological processes. Thus gene tree correction methods need to take estimation error as well as gene tree heterogeneity into account. Many prior gene tree correction methods have been developed for the case where GDL is present. Results Here, we study the problem of gene tree correction where gene tree heterogeneity is instead due to ILS and/or HGT. We introduce TRACTION, a simple polynomial time method that provably finds an optimal solution to the RF-optimal tree refinement and completion (RF-OTRC) Problem, which seeks a refinement and completion of a singly-labeled gene tree with respect to a given singly-labeled species tree so as to minimize the Robinson−Foulds (RF) distance. Our extensive simulation study on 68,000 estimated gene trees shows that TRACTION matches or improves on the accuracy of well-established methods from the GDL literature when HGT and ILS are both present, and ties for best under the ILS-only conditions. Furthermore, TRACTION ties for fastest on these datasets. We also show that a naive generalization of the RF-OTRC problem to multi-labeled trees is possible, but can produce misleading results where gene tree heterogeneity is due to GDL.

After publication of [1], the authors were informed by John A. Rhodes of a counterexample to Theorem 11 of [1].