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.

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.

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.

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.

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.

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.

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.

An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost.

Strategies adopted globally to mitigate the threat of COVID-19 have primarily involved lockdown measures with substantial economic and social costs with varying degrees of success. Morbidity patterns of COVID-19 variants have a strong association with age, while restrictive lockdown measures have association with negative mental health outcomes in some age groups. Reduced economic prospects may also afflict some age cohorts more than others. Motivated by this, we propose a model to describe COVID-19 community spread incorporating the role of age-specific social interactions. Through a flexible parameterisation of an age-structured deterministic Susceptible Exposed Infectious Removed (SEIR) model, we provide a means for characterising different forms of lockdown which may impact specific age groups differently. Social interactions are represented through age group to age group contact matrices, which can be trained using available data and are thus locally adapted. This framework is easy to interpret and suitable for describing counterfactual scenarios, which could assist policy makers with regard to minimising morbidity balanced with the costs of prospective suppression strategies. Our work originates from an Irish context and we use disease monitoring data from February 29th 2020 to January 31st 2021 gathered by Irish governmental agencies. We demonstrate how Irish lockdown scenarios can be constructed using the proposed model formulation and show results of retrospective fitting to incidence rates and forward planning with relevant "what if / instead of" lockdown counterfactuals. Uncertainty quantification for the predictive approaches is described. Our formulation is agnostic to a specific locale, in that lockdown strategies in other regions can be straightforwardly encoded using this model.

Behavioral dominance interactions between Nicrophorus orbicollis and N. tomentosus burying beetles (Coleoptera: Silphidae).

Asymmetric interference competition, where one species is behaviorally dominant over another, appears widespread in nature with the potential to structure ecological communities through trade-offs between competitive dominance and environmental tolerance. The details of how species interact and the factors that contribute to behavioral dominance, however, are poorly known for most species, yet such details are important for understanding when and why trade-offs occur. Here, we examine behavioral interactions between two species of burying beetles (Coleoptera: Silphidae) that compete for limited breeding resources (i.e., small vertebrate carcasses) in nature, to identify behaviors involved in interference competition and to test if large body size, species identity, or time of arrival best predict behavioral dominance among species. To test these ideas, we placed same-sex individuals of Nicrophorus orbicollis (early to mid-summer breeder) and N. tomentosus (late summer to fall breeder) into an enclosure together with a 25-30 g mouse carcass (Mus musculus). We then video-recorded all behaviors, including neutral and aggressive interactions, for 13 h per trial (N = 14 trials). For each interaction, we assigned a winner based on which beetle retained its position instead of fleeing or retained possession of the carcass; the overall behavioral dominant was determined as the individual that won the most interactions over the length of the trial. We found that large body size was the best predictor of behavioral dominance. In most interactions, N. orbicollis was larger and dominant over N. tomentosus; however, when N. tomentosus was larger they outcompeted smaller N. orbicollis, illustrating the importance of body size in aggressive contests. The order of arrival to the carcass (priority effects) did not predict behavioral dominance. The larger size and abundance of N. orbicollis in nature suggest a competitive asymmetry between the species, supporting the idea that N. orbicollis constrains the ability of N. tomentosus to breed earlier in the summer.

Generalized mean-field approximation for the Deffuant opinion dynamics model on networks.

When the interactions of agents on a network are assumed to follow the Deffuant opinion dynamics model, the outcomes are known to depend on the structure of the underlying network. This behavior cannot be captured by existing mean-field approximations for the Deffuant model. In this paper, a generalized mean-field approximation is derived that accounts for the effects of network topology on Deffuant dynamics through the degree distribution or community structure of the network. The accuracy of the approximation is examined by comparison with large-scale Monte Carlo simulations on both synthetic and real-world networks.

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).

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.

Serum uric acid and mortality thresholds among men and women in the Irish health system: A cohort study.

BACKGROUND: Elevation of serum uric acid (SUA) is associated with increased mortality; however, controversy exists regarding the nature of the relationship and differences between men and women. We explored relationships of SUA levels with all-cause mortality in a large cohort of patients within the Irish health system. METHODS: A retrospective cohort study of 26,525 participants was conducted using data from the National Kidney Disease Surveillance System. SUA was modelled in increments of 59.48 µmol/L (1 mg/dL), Cox's proportional hazards model estimated hazard ratios (HRs) and 95% Confidence Intervals (CI), median lifetimes were also computed separately for men and women. Mortality patterns were further explored using penalised splines. RESULTS: There were 1,288 (4.9%) deaths over a median follow-up of 5.1 years. In men, the risk of mortality was greatest for the lowest (<238 µmol/L) and highest (>535 µmol/L) categories [HR 2.35 (1.65-3.14) and HR 2.52 (1.87-3.29) respectively]; the corresponding median lifetimes for men were reduced by 9.5 and 11.7 years respectively compared to the referent. In women, mortality risks were elevated for SUA >416 mol/L [HR 1.69 (1.13-2.47) and beyond; the corresponding median lifetime for women were reduced by 5.9 years compared to the referent. Spline analysis revealed a U-shaped association between SUA and mortality in men, while for women, the pattern of association was J-shaped. CONCLUSION: Mortality patterns attributed to SUA differ between men and women. Optimal survival was associated with SUA concentrations of 304-454 µmol/L for men and < 409 µmol/L for women.

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.

Novel combination therapy for melanoma induces apoptosis via a gap junction positive feedback mechanism.

Metastatic melanoma cells overexpressing gap junctions were assayed for their ability to propagate cell death by a novel combination therapy that generates reactive oxygen species (ROS) by both 1) non-thermal plasma (NTP) and 2) tirapazamine (TPZ) under hypoxic conditions. Results demonstrate additive-to-synergistic effects of combination therapy compared to each agent individually. NTP induces highly localized cell death in target areas whereas TPZ partially reduces viability over the total surface area. However, when high gap junction expression was induced in melanoma cells, effects of combination NTP+TPZ therapy was augmented, spreading cell death across the entire plate. Similarly, in vivo studies of human metastatic melanoma in a mouse tumor model demonstrate that the combined effect of NTP+TPZ causes a 90% reduction in tumor volume, specifically in the model expressing gap junctions. Treatment with NTP+TPZ increases gene expression in the apoptotic pathway and oxidative stress while decreasing genes related to cell migration. Immune response was also elicited through differential regulation of cytokines and chemokines, suggesting potential for this therapy to induce a cytotoxic immune response with fewer side effects than current therapies. Interestingly, the gap junction protein, Cx26 was upregulated following treatment with NTP+TPZ and these gap junctions were shown to maintain functionality during the onset of treatment. Therefore, we propose that gap junctions both increase the efficacy of NTP+TPZ and perpetuate a positive feedback mechanism of gap junction expression and tumoricidal activity. Our unique approach to ROS induction in tumor cells with NTP+TPZ shows potential as a novel cancer treatment.

"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.

Agreement threshold on Axelrod's model of cultural dissemination.

Shared opinions are an important feature in the formation of social groups. In this paper, we use the Axelrod model of cultural dissemination to represent opinion-based groups. In the Axelrod model, each agent has a set of features which each holds one of a set of nominally related traits. Survey data has a similar structure, where each participant answers each of a set of items with responses from a fixed list. We present an alternative method of displaying the Axelrod model by representing it as a bipartite graph, i.e., participants and their responses as separate nodes. This allows us to see which feature-trait combinations are selected in the final state. This visualisation is particularly useful when representing survey data as it illustrates the co-evolution of attitudes and opinion-based groups in Axelrod's model of cultural diffusion. We also present a modification to the Axelrod model. A standard finding of the Axelrod model with many features is for all agents to fully agree in one cluster. We introduce an agreement threshold and allow nodes to interact only with those neighbours who are within this threshold (i.e., those with similar opinions) rather than those with any opinion. This method reliably yields a large number of clusters for small agreement thresholds and, importantly, does not limit to single cluster when the number of features grows large. This potentially provides a method for modelling opinion-based groups where as opinions are added, the number of clusters increase.

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.