Correlation of Pseudomonas aeruginosa Phage Resistance with the Numbers and Types of Antiphage Systems.

Phage therapeutics offer a potentially powerful approach for combating multidrug-resistant bacterial infections. However, to be effective, phage therapy must overcome existing and developing phage resistance. While phage cocktails can reduce this risk by targeting multiple receptors in a single therapeutic, bacteria have mechanisms of resistance beyond receptor modification. A rapidly growing body of knowledge describes a broad and varied arsenal of antiphage systems encoded by bacteria to counter phage infection. We sought to understand the types and frequencies of antiphage systems present in a highly diverse panel of Pseudomonas aeruginosa clinical isolates utilized to characterize novel antibacterials. Using the web-server tool PADLOC (prokaryotic antiviral defense locator), putative antiphage systems were identified in these P. aeruginosa clinical isolates based on sequence homology to a validated and curated catalog of known defense systems. Coupling this host bacterium sequence analysis with host range data for 70 phages, we observed a correlation between existing phage resistance and the presence of higher numbers of antiphage systems in bacterial genomes. We were also able to identify antiphage systems that were more prevalent in highly phage-resistant P. aeruginosa strains, suggesting their importance in conferring resistance.

Plasticity versus Evolutionary Divergence: What Causes Habitat Partitioning in Urban-Adapted Birds?

AbstractHabitat partitioning can facilitate the coexistence of closely related species and often results from competitive interference inducing plastic shifts of subordinate species in response to aggressive, dominant species (plasticity) or the evolution of ecological differences in subordinate species that reduce their ability to occupy habitats where the dominant species occurs (evolutionary divergence). Evidence consistent with both plasticity and evolutionary divergence exist, but the relative contributions of each to habitat partitioning have been difficult to discern. Here we use a global data set on the breeding occurrence of birds in cities to test predictions of these alternative hypotheses to explain previously described habitat partitioning associated with competitive interference. Consistent with plasticity, the presence of behaviorally dominant congeners in a city was associated with a 65% reduction in the occurrence of subordinate species, but only when the dominant was a widespread breeder in urban habitats. Consistent with evolutionary divergence, increased range-wide overlap with dominant congeners was associated with a 56% reduction in the occurrence of subordinates in cities, even when the dominant was absent from the city. Overall, our results suggest that both plasticity and evolutionary divergence play important, concurrent roles in habitat partitioning among closely related species in urban environments.

Recent collapse of crop belts and declining diversity of US agriculture since 1840.

Over the last century, US agriculture greatly intensified and became industrialized, increasing in inputs and yields while decreasing in total cropland area. In the industrial sector, spatial agglomeration effects are typical, but such changes in the patterns of crop types and diversity would have major implications for the resilience of food systems to global change. Here, we investigate the extent to which agricultural industrialization in the United States was accompanied by agglomeration of crop types, not just overall cropland area, as well as declines in crop diversity. Based on county-level analyses of individual crop land cover area in the conterminous United States from 1840 to 2017, we found a strong and abrupt spatial concentration of most crop types in very recent years. For 13 of the 18 major crops, the widespread belts that characterized early 20th century US agriculture have collapsed, with spatial concentration increasing 15-fold after 2002. The number of counties producing each crop declined from 1940 to 2017 by up to 97%, and their total area declined by up to 98%, despite increasing total production. Concomitantly, the diversity of crop types within counties plummeted: in 1940, 88% of counties grew >10 crops, but only 2% did so in 2017, and combinations of crop types that once characterized entire agricultural regions are lost. Importantly, declining crop diversity with increasing cropland area is a recent phenomenon, suggesting that corresponding environmental effects in agriculturally dominated counties have fundamentally changed. For example, the spatial concentration of agriculture has important consequences for the spread of crop pests, agrochemical use, and climate change. Ultimately, the recent collapse of most agricultural belts and the loss of crop diversity suggest greater vulnerability of US food systems to environmental and economic change, but the spatial concentration of agriculture may also offer environmental benefits in areas that are no longer farmed.

An alternative formulation of Coxian phase-type distributions with covariates: Application to emergency department length of stay.

In this article, we present a new methodology to model patient transitions and length of stay in the emergency department using a series of conditional Coxian phase-type distributions, with covariates. We reformulate the Coxian models (standard Coxian, Coxian with multiple absorbing states, joint Coxian, and conditional Coxian) to take into account heterogeneity in patient characteristics such as arrival mode, time of admission, and age. The approach differs from previous research in that it reduces the computational time, and it allows the inclusion of patient covariate information directly into the model. The model is applied to emergency department data from University Hospital Limerick in Ireland, where we find broad agreement with a number of commonly used survival models (parametric Weibull and log-normal regression models and the semiparametric Cox proportional hazards model).

A multiparameter regression model for interval-censored survival data.

We develop flexible multiparameter regression (MPR) survival models for interval-censored survival data arising in longitudinal prospective studies and longitudinal randomised controlled clinical trials. A multiparameter Weibull regression survival model, which is wholly parametric, and has nonproportional hazards, is the main focus of the article. We describe the basic model, develop the interval-censored likelihood, and extend the model to include gamma frailty and a dispersion model. We evaluate the models by means of a simulation study and a detailed reanalysis of data from the Signal Tandmobiel study. The results demonstrate that the MPR model with frailty is computationally efficient and provides an excellent fit to the data.

"No, We Should Do It": Youth Training Youth in Activist Research Methods.

This article explores a 9-month process of youth research capacity-building, beginning with the training of high school and college aged researchers in qualitative methodologies and concluding with both tentative and comprehensive policy recommendations, at the behest of the youth, for altering the landscape of a major Southeastern city to ensure greater equity of opportunity in particular for minoritized youth and their families. Our analysis led us to consider the ways in which community-engaged youth and their adult partners created a culture of reciprocity and respect as they worked together to train other youth to conduct their own justice-oriented inquiry projects.

Land-use and climatic causes of environmental novelty in Wisconsin since 1890.

Multiple global change drivers are increasing the present and future novelty of environments and ecological communities. However, most assessments of environmental novelty have focused only on future climate and were conducted at scales too broad to be useful for land management or conservation. Here, using historical county-level data sets of agricultural land use, forest composition, and climate, we conduct a regional-scale assessment of environmental novelty for Wisconsin landscapes from ca. 1890 to 2012. Agricultural land-use data include six cropland types, livestock densities for four livestock species, and human populations. Forestry data comprise biomass-weighted relative abundances for 15 tree genera. Climate data comprise seasonal means for temperature and precipitation. We found that forestry and land use are the strongest cause of environmental novelty (NoveltyForest  = 3.66, NoveltyAg  = 2.83, NoveltyClimate  = 1.60, with Wisconsin's forests transformed by early 20th-century logging and its legacies and multiple waves of agricultural innovation and obsolescence. Climate change is the smallest contributor to contemporary novelty, with precipitation signals stronger than temperature. Magnitudes and causes of environmental novelty are strongly spatially patterned, with novelty in southern Wisconsin roughly twice that in northern Wisconsin. Forestry is the most important cause of novelty in the north, land use and climate change are jointly important in the southwestern Wisconsin, and land use and forest composition are most important in central and eastern Wisconsin. Areas of high regional novelty tend also to be areas of high local change, but local change has not pushed all counties beyond regional baselines. Seven counties serve as the best historical analogues for over one-half of contemporary Wisconsin counties (40/72), and so can offer useful historical counterparts for contemporary systems and help managers coordinate to tackle similar environmental challenges. Multi-dimensional environmental novelty analyses, like those presented here, can help identify the best historical analogues for contemporary ecosystems, places where new management rules and practices may be needed because novelty is already high, and the main causes of novelty. Separating regional novelty clearly from local change and measuring both across many dimensions and at multiple scales thus helps advance ecology and sustainability science alike.

Deep mantle structure as a reference frame for movements in and on the Earth.

Earth's residual geoid is dominated by a degree-2 mode, with elevated regions above large low shear-wave velocity provinces on the core-mantle boundary beneath Africa and the Pacific. The edges of these deep mantle bodies, when projected radially to the Earth's surface, correlate with the reconstructed positions of large igneous provinces and kimberlites since Pangea formed about 320 million years ago. Using this surface-to-core-mantle boundary correlation to locate continents in longitude and a novel iterative approach for defining a paleomagnetic reference frame corrected for true polar wander, we have developed a model for absolute plate motion back to earliest Paleozoic time (540 Ma). For the Paleozoic, we have identified six phases of slow, oscillatory true polar wander during which the Earth's axis of minimum moment of inertia was similar to that of Mesozoic times. The rates of Paleozoic true polar wander (<1°/My) are compatible with those in the Mesozoic, but absolute plate velocities are, on average, twice as high. Our reconstructions generate geologically plausible scenarios, with large igneous provinces and kimberlites sourced from the margins of the large low shear-wave velocity provinces, as in Mesozoic and Cenozoic times. This absolute kinematic model suggests that a degree-2 convection mode within the Earth's mantle may have operated throughout the entire Phanerozoic.

Diamonds sampled by plumes from the core-mantle boundary.

Diamonds are formed under high pressure more than 150 kilometres deep in the Earth's mantle and are brought to the surface mainly by volcanic rocks called kimberlites. Several thousand kimberlites have been mapped on various scales, but it is the distribution of kimberlites in the very old cratons (stable areas of the continental lithosphere that are more than 2.5 billion years old and 300 kilometres thick or more) that have generated the most interest, because kimberlites from those areas are the major carriers of economically viable diamond resources. Kimberlites, which are themselves derived from depths of more than 150 kilometres, provide invaluable information on the composition of the deep subcontinental mantle lithosphere, and on melting and metasomatic processes at or near the interface with the underlying flowing mantle. Here we use plate reconstructions and tomographic images to show that the edges of the largest heterogeneities in the deepest mantle, stable for at least 200 million years and possibly for 540 million years, seem to have controlled the eruption of most Phanerozoic kimberlites. We infer that future exploration for kimberlites and their included diamonds should therefore be concentrated in continents with old cratons that once overlay these plume-generation zones at the core-mantle boundary.

The rise of novelty in ecosystems.

Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessment of novelty was based on abiotic factors (temperature, precipitation, and nitrogen deposition) plus human population, and shows that there are already large areas with high novelty today relative to the early 20th century, and that there will even be more such areas by 2050. Interestingly, the places that are most novel are often not the places where absolute changes are largest; highlighting that novelty is inherently different from change. For the ecological sciences, highly novel ecosystems present new opportunities to test ecological theories, but also challenge the predictive ability of ecological models and their validation. For biodiversity conservation, increasing novelty presents some opportunities, but largely challenges. Conservation action is necessary along the entire continuum of novelty, by redoubling efforts to protect areas where novelty is low, identifying conservation opportunities where novelty is high, developing flexible yet strong regulations and policies, and establishing long-term experiments to test management approaches. Meeting the challenge of novelty will require advances in the science of ecology, and new and creative. conservation approaches.

The competitive exclusion-tolerance rule explains habitat partitioning among co-occurring species of burying beetles.

Habitat partitioning among co-occurring, ecologically similar species is widespread in nature and thought to be an important mechanism for coexistence. The factors that cause habitat partitioning, however, are unknown for most species. We experimentally tested among three alternative hypotheses to explain habitat partitioning among two species of co-occurring burying beetle (Nicrophorus) that occupy forest (Nicrophorus orbicollis) and wetland (Nicrophorus hebes) habitats. Captive experiments revealed that the larger N. orbicollis (forest) was consistently dominant to N. hebes (wetland) in competitive interactions for carcasses that they require for reproduction. Transplant enclosure experiments in nature revealed that N. hebes had poor reproductive success whenever the dominant N. orbicollis was present. In the absence of N. orbicollis, N. hebes performed as well, or better, in forest versus its typical wetland habitat. In contrast, N. orbicollis performed poorly in wetlands regardless of the presence of N. hebes. These results support the competitive exclusion-tolerance rule where the competitively dominant N. orbicollis excludes the subordinate N. hebes from otherwise suitable or preferable forest habitat, while the subordinate N. hebes is uniquely able to tolerate the challenges of breeding in wetlands. Transplant experiments further showed that carcass burial depth-an important trait thought to enhance the competitive ability of the dominant N. orbicollis-is costly in wetland habitats. In the presence of N. hebes, N. orbicollis buried carcasses deeper; deeper burial is thought to provide a competitive advantage in forests but further compromised the reproductive success of N. orbicollis in wetlands. Overall, results provide evidence that the competitive exclusion-tolerance rule underlies habitat partitioning among ecologically similar species and that the traits important for competitive dominance in relatively benign environments are costly in more challenging environments, consistent with a trade-off.

Genome sequence of the Klebsiella quasipneumoniae bacteriophage EKq1 with activity against Klebsiella pneumoniae.

We describe the genome of a lytic phage EKq1 isolated on Klebsiella quasipneumoniae, with activity against Klebsiella pneumoniae. EKq1 is an unclassified representative of the class Caudoviricetes, similar to Klebsiella phages VLCpiS8c, phiKp_7-2, and vB_KleS-HSE3. The 48,244-bp genome has a GC content of 56.43% and 63 predicted protein-coding genes.

Integrating Pre-test Probability and Point-of-Care Ultrasound (POCUS) in the Emergency Department (ED) Diagnosis of Small Bowel Obstruction (SBO).

Introduction A computed tomography (CT) scan and point-of-care ultrasound (POCUS) are commonly employed for diagnosing small bowel obstructions (SBOs). Prior studies demonstrated that POCUS has 90-95% sensitivity and specificity compared with CT scanning, which is the gold standard. Unlike other imaging modalities (in which the ordering and performing clinician are not the same), POCUS-performing/interpreting sonologists must recognize the risk of confirmation bias in the POCUS application. Per Bayesian analysis, the likelihood of a diagnosis being true following a diagnostic test is based on the ordering clinician's pre-test probability and the test characteristics (sensitivity and specificity, from which positive and negative likelihood ratios can be calculated). Consequently, establishing pre-test probability is important in informing downstream diagnostic or therapeutic interventions, as pre-test probability influences post-test odds. Little research has been done on the role of POCUS sonologist's pre-test probability and actual POCUS results regarding SBO. This study assessed the role of POCUS, integrating pre-test probability and POCUS results to determine post-test odds. Methods One hundred six patients were recruited on a convenience basis and underwent POCUS and CT between April 2017 and December 2022. All sonographers were credentialed in POCUS. POCUS sonologists' pre-test probabilities and POCUS and CT results were captured, which were compared. Sensitivity, specificity, LR+, and LR- were calculated, and correlations were made between pre-test probability and POCUS and CT results.  Results POCUS exhibited a sensitivity of 92% and specificity of 90%, with a corresponding positive likelihood ratio (LR+) of 9.3 and a negative likelihood ratio (LR-) of 0.09 for diagnosing SBO. Among patients with a high pre-test probability of SBO, a negative ultrasound yielded post-test odds of 0.4%, whereas a positive POCUS yielded post-test odds of 39.6%. Among patients with a low pre-test probability, a negative POCUS resulted in post-test odds of 0%, while a positive POCUS led to post-test odds of 2.1%, yielding a number needed to scan (NNS) of ~50 to identify a patient with an SBO on CT. Conclusion This study confirmed POCUS's sensitivity and specificity of ~90-95% and a corresponding LR+ of 9.2 and LR- of 0.9. Pre-test probability substantially affected post-test odds. Patients with a high pre-test probability and a positive POCUS had post-test odds of 39.6 and should have a confirmatory CT, while those with a negative POCUS have very low post-test odds and very likely will not benefit from CT. Patients with low pre-test probability and a positive POCUS have post-test odds of 2.1%, similar to the Wells Score and HEART score; such patients may not benefit from a CT, though clinicians should use their judgment/discretion. Patients with a low pre-test probability and a negative POCUS have post-test odds of 0% and should not have a CT. Among low pre-test probability patients, the NNS was ~50 to identify patients with an SBO on CT.

Variable selection using a smooth information criterion for distributional regression models.

Modern variable selection procedures make use of penalization methods to execute simultaneous model selection and estimation. A popular method is the least absolute shrinkage and selection operator, the use of which requires selecting the value of a tuning parameter. This parameter is typically tuned by minimizing the cross-validation error or Bayesian information criterion, but this can be computationally intensive as it involves fitting an array of different models and selecting the best one. In contrast with this standard approach, we have developed a procedure based on the so-called "smooth IC" (SIC) in which the tuning parameter is automatically selected in one step. We also extend this model selection procedure to the distributional regression framework, which is more flexible than classical regression modelling. Distributional regression, also known as multiparameter regression, introduces flexibility by taking account of the effect of covariates through multiple distributional parameters simultaneously, e.g., mean and variance. These models are useful in the context of normal linear regression when the process under study exhibits heteroscedastic behaviour. Reformulating the distributional regression estimation problem in terms of penalized likelihood enables us to take advantage of the close relationship between model selection criteria and penalization. Utilizing the SIC is computationally advantageous, as it obviates the issue of having to choose multiple tuning parameters. Supplementary Information: The online version contains supplementary material available at 10.1007/s11222-023-10204-8.

Penalized variable selection in multi-parameter regression survival modeling.

Standard survival models such as the proportional hazards model contain a single regression component, corresponding to the scale of the hazard. In contrast, we consider the so-called "multi-parameter regression" approach whereby covariates enter the model through multiple distributional parameters simultaneously, for example, scale and shape parameters. This approach has previously been shown to achieve flexibility with relatively low model complexity. However, beyond a stepwise type selection method, variable selection methods are underdeveloped in the multi-parameter regression survival modeling setting. Therefore, we propose penalized multi-parameter regression estimation procedures using the following penalties: least absolute shrinkage and selection operator, smoothly clipped absolute deviation, and adaptive least absolute shrinkage and selection operator. We compare these procedures using extensive simulation studies and an application to data from an observational lung cancer study; the Weibull multi-parameter regression model is used throughout as a running example.

Agent-based null models for examining experimental social interaction networks.

We consider the analysis of temporal data arising from online interactive social experiments, which is complicated by the fact that classical independence assumptions about the observations are not satisfied. Therefore, we propose an approach that compares the output of a fitted (linear) model from the observed interaction data to that generated by an assumed agent-based null model. This allows us to discover, for example, the extent to which the structure of social interactions differs from that of random interactions. Moreover, we provide network visualisations that identify the extent of ingroup favouritism and reciprocity as well as particular individuals whose behaviour differs markedly from the norm. We specifically consider experimental data collected via the novel Virtual Interaction APPLication (VIAPPL). We find that ingroup favouritism and reciprocity are present in social interactions observed on this platform, and that these behaviours strengthen over time. Note that, while our proposed methodology was developed with VIAPPL in mind, its potential usage extends to any type of social interaction data.

Reformulation of Processed Yogurt and Breakfast Cereals over Time: A Scoping Review.

Poor diet is responsible for a quarter of European non-communicable disease (NCD)-related deaths. The reformulation of sugar, salt, and saturated fat in processed packaged foods offers an opportunity to reduce consumption of nutrients of concern and also support a reduction in energy intake. To date, there have been no publications measuring progress in food reformulation by compiling published evidence for a food category. The aim of this scoping review was to identify, characterize and summarise the findings of studies analysing the reformulation of processed yogurt and breakfast cereals. The review answered the research question: "What is the impact of food reformulation on the nutrient quality of yogurt and breakfast cereals available in the retail environment?" The research protocol was defined based on PRISMA-ScR guidelines. Five databases were searched in May 2022. Thirteen studies, published between 2010 and 2021 and completed across seven countries were eligible for inclusion. There were sufficient eligible studies to identify trends in sodium, salt, and sugar reduction in breakfast cereals. However, there was minimal or no reduction in energy, which may bring into question the use of food reformulation as part of an overall health strategy for obesity reduction.

Genome Sequence of Staphylococcus aureus Phage ESa2.

We describe the genome of a lytic phage, ESa2, isolated from environmental water and specific for Staphylococcus aureus. ESa2 belongs to the family Herelleviridae and genus Kayvirus. Its genome consists of 141,828 bp, with 30.25% GC content, 253 predicted protein-coding sequences, 3 tRNAs, and 10,130-bp-long terminal repeats.

Determinants of Intravenous Infusion Longevity and Infusion Failure via a Nonlinear Model Analysis of Smart Pump Event Logs: Retrospective Study.

BACKGROUND: Infusion failure may have severe consequences for patients receiving critical, short-half-life infusions. Continued interruptions to infusions can lead to subtherapeutic therapy. OBJECTIVE: This study aims to identify and rank determinants of the longevity of continuous infusions administered through syringe drivers, using nonlinear predictive models. Additionally, this study aims to evaluate key factors influencing infusion longevity and develop and test a model for predicting the likelihood of achieving successful infusion longevity. METHODS: Data were extracted from the event logs of smart pumps containing information on care profiles, medication types and concentrations, occlusion alarm settings, and the final infusion cessation cause. These data were then used to fit 5 nonlinear models and evaluate the best explanatory model. RESULTS: Random forest was the best-fit predictor, with an F1-score of 80.42, compared to 5 other models (mean F1-score 75.06; range 67.48-79.63). When applied to infusion data in an individual syringe driver data set, the predictor model found that the final medication concentration and medication type were of less significance to infusion longevity compared to the rate and care unit. For low-rate infusions, rates ranging from 2 to 2.8 mL/hr performed best for achieving a balance between infusion longevity and fluid load per infusion, with an occlusion versus no-occlusion ratio of 0.553. Rates between 0.8 and 1.2 mL/hr exhibited the poorest performance with a ratio of 1.604. Higher rates, up to 4 mL/hr, performed better in terms of occlusion versus no-occlusion ratios. CONCLUSIONS: This study provides clinicians with insights into the specific types of infusion that warrant more intense observation or proactive management of intravenous access; additionally, it can offer valuable information regarding the average duration of uninterrupted infusions that can be expected in these care areas. Optimizing rate settings to improve infusion longevity for continuous infusions, achieved through compounding to create customized concentrations for individual patients, may be possible in light of the study's outcomes. The study also highlights the potential of machine learning nonlinear models in predicting outcomes and life spans of specific therapies delivered via medical devices.