Comparing binary efficacy outcomes for systemic immunomodulatory treatments for atopic dermatitis in a living systematic review and network meta-analysis.

BACKGROUND: Systemic treatments for atopic dermatitis (AD) are evaluated primarily in placebo-controlled trials with binary efficacy outcomes. In a living systematic review and network meta-analysis (NMA), we previously analysed continuous efficacy measures. OBJECTIVES: To compare binary efficacy outcomes of systemic treatments for AD. METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, Latin American and Caribbean Health Science Information (LILACS) database, Global Resource for Eczema Trials (GREAT) database and trial registries up to 1 March 2023. We included randomized trials examining ≥ 8 weeks of treatment with systemic immunomodulatory medications for moderate-to-severe AD. We screened titles, abstracts and full texts and abstracted data independently, in duplicate. Outcomes included the proportion of patients achieving at least 50%, 75% and 90% improvements in Eczema Area and Severity Index (EASI 50, EASI 75 and EASI 90, respectively) and Investigator Global Assessment (IGA) success. We performed random-effects Bayesian NMAs to calculate odds ratios (OR) and 95% credible intervals (CrIs) between each intervention for each outcome. RESULTS: Eighty-three trials with 22 122 participants were included in the systematic review. In analyses limited to trials of 8-16 weeks' duration with predominantly adult populations, abrocitinib 200 mg daily (OR 1.5, 95% CrI 1.1-2.2) and upadacitinib 15 mg daily (OR 1.7, 95% CrI 0.9-3.3) and 30 mg daily (OR 2.5, 95% CrI 1.3-5.0) were associated with higher odds of achieving EASI 50 vs. dupilumab. Abrocitinib 100 mg daily (OR 0.7, 95% CrI 0.5-1.0), baricitinib 2 mg daily (OR 0.4, 95% CrI 0.3-0.5) and 4 mg daily (OR 0.5, 95% CrI 0.3-0.7), and tralokinumab (OR 0.4, 95% CrI 0.3-0.6) were associated with lower odds of achieving EASI 50 vs. dupilumab. Results were similar for EASI 75, EASI 90 and IGA success. CONCLUSIONS: Supporting results for continuous outcome measures, upadacitinib 30 mg daily and abrocitinib 200 mg daily are the most efficacious with regard to binary efficacy endpoints up to 16 weeks in adults with moderate-to-severe AD, followed by upadacitinib 15 mg daily, dupilumab and abrocitinib 100 mg daily. Dupilumab and both doses of upadacitinib and abrocitinib are more efficacious than baricitinib 4 and 2 mg daily and tralokinumab.

Divergence in rates of phenotypic plasticity among ectotherms.

An individual's fitness cost associated with environmental change likely depends on the rate of adaptive phenotypic plasticity, and yet our understanding of plasticity rates in an ecological and evolutionary context remains limited. We provide the first quantitative synthesis of existing plasticity rate data, focusing on acclimation of temperature tolerance in ectothermic animals, where we demonstrate applicability of a recently proposed analytical approach. The analyses reveal considerable variation in plasticity rates of this trait among species, with half-times (how long it takes for the initial deviation from the acclimated phenotype to be reduced by 50% when individuals are shifted to a new environment) ranging from 3.7 to 770.2 h. Furthermore, rates differ among higher taxa, being higher for amphibians and reptiles than for crustaceans and fishes, and with insects being intermediate. We argue that a more comprehensive understanding of phenotypic plasticity will be attained through increased focus on the rate parameter.

The effects of systemic immunomodulatory treatments on COVID-19 outcomes in patients with atopic dermatitis: Results from the global SECURE-AD registry.

BACKGROUND: Limited data are available on the effects of systemic immunomodulatory treatments on COVID-19 outcomes in patients with atopic dermatitis (AD). OBJECTIVE: To investigate COVID-19 outcomes in patients with AD treated with or without systemic immunomodulatory treatments, using a global registry platform. METHODS: Clinicians were encouraged to report cases of COVID-19 in their patients with AD in the Surveillance Epidemiology of Coronavirus Under Research Exclusion for Atopic Dermatitis (SECURE-AD) registry. Data entered from 1 April 2020 to 31 October 2021 were analysed using multivariable logistic regression. The primary outcome was hospitalization from COVID-19, according to AD treatment groups. RESULTS: 442 AD patients (mean age 35.9 years, 51.8% male) from 27 countries with strongly suspected or confirmed COVID-19 were included in analyses. 428 (96.8%) patients were treated with a single systemic therapy (n = 297 [67.2%]) or topical therapy only (n = 131 [29.6%]). Most patients treated with systemic therapies received dupilumab (n = 216). Fourteen patients (3.2%) received a combination of systemic therapies. Twenty-six patients (5.9%) were hospitalized. No deaths were reported. Patients treated with topical treatments had significantly higher odds of hospitalization, compared with those treated with dupilumab monotherapy (odds ratio (OR) 4.65 [95%CI 1.71-14.78]), including after adjustment for confounding variables (adjusted OR (aOR) 4.99 [95%CI 1.4-20.84]). Combination systemic therapy which did not include systemic corticosteroids was associated with increased odds of hospitalization, compared with single agent non-steroidal immunosuppressive systemic treatment (OR 8.09 [95%CI 0.4-59.96], aOR 37.57 [95%CI 1.05-871.11]). Hospitalization was most likely in patients treated with combination systemic therapy which included systemic corticosteroids (OR 40.43 [95%CI 8.16-207.49], aOR 45.75 [95%CI 4.54-616.22]). CONCLUSIONS: Overall, the risk of COVID-19 complications appears low in patients with AD, even when treated with systemic immunomodulatory agents. Dupilumab monotherapy was associated with lower hospitalization than other therapies. Combination systemic treatment, particularly combinations including systemic corticosteroids, was associated with the highest risk of severe COVID-19.

Evolution of population dynamics following invasion by a non-native predator.

Invasive predatory species are frequently observed to cause evolutionary responses in prey phenotypes, which in turn may lead to evolutionary shifts in the population dynamics of prey. Research has provided a link between rates of predation and the evolution of prey population growth in the lab, but studies from natural populations are rare. Here, we tested for evolutionary changes in population dynamics parameters of zooplankton Daphnia pulicaria following invasion by the predator Bythotrephes longimanus into Lake Kegonsa, Wisconsin, US. We used a resurrection ecological approach, whereby clones from pre- and post-invasive periods were hatched from eggs obtained in sediment cores and were used in a 3-month growth experiment. Based on these data, we estimated intrinsic population growth rates (r), the shape of density dependence (θ) and carrying capacities (K) using theta-logistic models. We found that post-invasion Daphnia maintained a higher r and K under these controlled, predation-free laboratory conditions. Evidence for changes in θ was weaker. Whereas previous experimental evolution studies of predator-prey interactions have demonstrated that genotypes that have evolved under predation have inferior competitive ability when the predator is absent, this was not the case for the Daphnia. Given that our study was conducted in a laboratory environment and the possibility for genotype-by-environment interactions, extrapolating these apparent counterintuitive results to the wild should be done with caution. However, barring such complications, we discuss how selection for reduced predator exposure, either temporally or spatially, may have led to the observed changes. This scenario suggests that complexities in ecological interactions represents a challenge when predicting the evolutionary responses of population dynamics to changes in predation pressure in natural systems.

Evolutionary change in metabolic rate of Daphnia pulicaria following invasion by the predator Bythotrephes longimanus.

Metabolic rate is a trait that may evolve in response to the direct and indirect effects of predator-induced mortality. Predators may indirectly alter selection by lowering prey densities and increasing resource availability or by intensifying resource limitation through changes in prey behavior (e.g., use of less productive areas). In the current study, we quantify the evolution of metabolic rate in the zooplankton Daphnia pulicaria following an invasive event by the predator Bythotrephes longimanus in Lake Mendota, Wisconsin, US. This invasion has been shown to dramatically impact D. pulicaria, causing a ~60% decline in their biomass. Using a resurrection ecology approach, we compared the metabolic rate of D. pulicaria clones originating prior to the Bythotrephes invasion with that of clones having evolved in the presence of Bythotrephes. We observed a 7.4% reduction in metabolic rate among post-invasive clones compared to pre-invasive clones and discuss the potential roles of direct and indirect selection in driving this change.

Environmental change and the rate of phenotypic plasticity.

With rapid and less predictable environmental change emerging as the 'new norm', understanding how individuals tolerate environmental stress via plastic, often reversible changes to the phenotype (i.e., reversible phenotypic plasticity, RPP), remains a key issue in ecology. Here, we examine the potential for better understanding how organisms overcome environmental challenges within their own lifetimes by scrutinizing a somewhat overlooked aspect of RPP, namely the rate at which it can occur. Although recent advances in the field provide indication of the aspects of environmental change where RPP rates may be of particular ecological relevance, we observe that current theoretical models do not consider the evolutionary potential of the rate of RPP. Whilst recent theory underscores the importance of environmental predictability in determining the slope of the evolved reaction norm for a given trait (i.e., how much plasticity can occur), a hitherto neglected possibility is that the rate of plasticity might be a more dynamic component of this relationship than previously assumed. If the rate of plasticity itself can evolve, as empirical evidence foreshadows, rates of plasticity may have the potential to alter the level predictability in the environment as perceived by the organism and thus influence the slope of the evolved reaction norm. However, optimality in the rate of phenotypic plasticity, its evolutionary dynamics in different environments and influence of constraints imposed by associated costs remain unexplored and may represent fruitful avenues of exploration in future theoretical and empirical treatments of the topic. We conclude by reviewing published studies of RPP rates, providing suggestions for improving the measurement of RPP rates, both in terms of experimental design and in the statistical quantification of this component of plasticity.

Systemic Immunomodulatory Treatments for Atopic Dermatitis: Update of a Living Systematic Review and Network Meta-analysis.

Importance: Systemic treatments for atopic dermatitis are being evaluated primarily in placebo-controlled trials; network meta-analysis can provide relative efficacy and safety estimates for treatments that have not been compared head to head. Objective: To compare reported measures of efficacy and assessments of safety in clinical trials of systemic treatments for atopic dermatitis in a living systematic review and network meta-analysis. Data Sources: The Cochrane Central Register of Controlled Trials, MEDLINE, Embase, Latin American and Caribbean Health Science Information database, Global Resource of EczemA Trials database, and trial registries were searched through June 15, 2021. Study Selection: Randomized clinical trials examining 8 or more weeks of treatment with systemic immunomodulatory medications for moderate-to-severe atopic dermatitis were included after screening titles, abstracts, and papers in duplicate. Data Extraction and Synthesis: Data were abstracted in duplicate. Bayesian network meta-analyses and assessed Grading of Recommendations Assessment, Development and Evaluation certainty of evidence were performed. The updated analysis was completed from June to December 2021. Main Outcomes and Measures: Outcomes include change in Eczema Area and Severity Index (EASI), Patient Oriented Eczema Measure (POEM), Dermatology Life Quality Index (DLQI), and Peak Pruritus Numeric Rating Scales (PP-NRS). Results: Since October 2019, 21 new studies were added, for a total of 60 trials with 16 579 patients. Up to 16 weeks of treatment in adults, abrocitinib, 200 mg daily (mean difference [MD], 2.2; 95% credible interval [CrI], 0.2-4.0; high certainty) and upadacitinib, 30 mg daily (MD, 2.7; 95% CrI, 0.6-4.7; high certainty) were associated with reduced EASI slightly more than dupilumab, 600 mg then 300 mg every 2 weeks. Abrocitinib, 100 mg daily (MD, -2.1; 95% CrI, -4.1 to -0.3; high certainty), baricitinib, 4 mg daily (MD, -3.2; 95% CrI, -5.7 to -0.8; high certainty), baricitinib, 2 mg daily (MD, -5.2; 95% CrI, -7.5 to -2.9; high certainty) and tralokinumab, 600 mg then 300 mg every 2 weeks (MD, -3.5; 95% CrI, -5.8 to -1.3; high certainty) were associated with reduced EASI slightly less than dupilumab. There was little or no difference between upadacitinib, 15 mg daily, and dupilumab (MD, 0.2; 95% CrI, -1.9 to 2.2; high certainty). The pattern of results was similar for POEM, DLQI, and PP-NRS. Conclusions and Relevance: In this systematic review and meta-analysis, abrocitinib, 200 mg; and upadacitinib, 30 mg daily, were associated with slightly better scores than dupilumab, and upadacitinib, 15 mg daily, was associated with similar scores to dupilumab. Abrocitinib, 100 mg daily, baricitinib, 4 mg and 2 mg daily, and tralokinumab, 300 mg, every 2 weeks were associated with slightly worse scores.

Development of a Website for a Living Network Meta-analysis of Atopic Dermatitis Treatments Using a User-Centered Design: Multimethod Study.

BACKGROUND: A rapid expansion of systemic immunological treatment options for atopic dermatitis (AD) has created a need for clinically relevant and understandable comparative efficacy and safety information for patients and clinicians. Given the scarcity of head-to-head trials, network meta-analysis (NMA) is an alternative way to enable robust comparisons among treatment options; however, NMA results are often complex and difficult to directly implement in shared decision-making. OBJECTIVE: The aim of this study is to develop a website that effectively presents the results of a living systematic review and NMA on AD treatments to patient and clinician users. METHODS: We conducted a multimethod study using iterative feedback from adults with AD, adult caregivers of children with AD, dermatologists, and allergists within a user-centered design framework. We used questionnaires followed by workshops among patients and clinicians to develop and improve the website interface. Usability testing was done with a caregiver of a patient with eczema. RESULTS: Questionnaires were completed by 31 adults with AD or caregivers and 94 clinicians. Patients and caregivers felt it was very important to know about new treatments (20/31, 65%). Clinicians felt the lack of evidence-based comparisons between treatments was a barrier to care (55/93, 59%). "Avoiding dangerous side effects" was ranked as the most important priority for patients (weighted ranking 5.2/7, with higher ranking being more important), and "improving patients' overall symptoms" was the most important priority for clinicians (weighted ranking 5.0/6). A total of 4 patients and 7 clinicians participated in workshops; they appreciated visualizations of the NMA results and found the website valuable for comparing different treatments. The patients suggested changes to simplify the interface and clarify terminology related to comparative efficacy. The user in the usability testing found the website intuitive to navigate. CONCLUSIONS: We developed a website, "eczematherapies.com," with a user-centered design approach. Visualizations of NMA results enable users to compare treatments as part of their shared decision-making process.

Learning from disease registries during a pandemic: Moving toward an international federation of patient registries.

High-quality dermatology patient registries often require considerable time to develop and produce meaningful data. Development time is influenced by registry complexity and regulatory hurdles that vary significantly nationally and institutionally. The rapid emergence of the coronavirus disease 2019 (COVID-19) global pandemic has challenged health services in an unprecedented manner. Mobilization of the dermatology community in response has included rapid development and deployment of multiple, partially harmonized, international patient registries, reinventing established patient registry timelines. Partnership with patient organizations has demonstrated the critical nature of inclusive patient involvement. This global effort has demonstrated the value, capacity, and necessity for the dermatology community to adopt a more cohesive approach to patient registry development and data sharing that can lead to myriad benefits. These include improved utilization of limited resources, increased data interoperability, improved ability to rapidly collect meaningful data, and shortened response times to generate real-world evidence. We call on the global dermatology community to support the development of an international federation of patient registries to consolidate and operationalize the lessons learned during this pandemic. This will provide an enduring means of applying this knowledge to the maintenance and development of sustainable, coherent, and impactful patient registries of benefit now and in the future.

Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals.

BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD) and heart failure are the most common cardiovascular diseases. Non-invasive diagnostic testing for CAD requires radiation, heart rate acceleration, and imaging infrastructure. Early detection of left ventricular dysfunction is critical in heart failure management, the best measure of which is an elevated left ventricular end-diastolic pressure (LVEDP) that can only be measured using invasive cardiac catheterization. There exists a need for non-invasive, safe, and fast diagnostic testing for CAD and elevated LVEDP. This research employs nonlinear dynamics to assess for significant CAD and elevated LVEDP using non-invasively acquired photoplethysmographic (PPG) and three-dimensional orthogonal voltage gradient (OVG) signals. PPG (variations of the blood volume perfusing the tissue) and OVG (mechano-electrical activity of the heart) signals represent the dynamics of the cardiovascular system. METHODS: PPG and OVG were simultaneously acquired from two cohorts, (i) symptomatic subjects that underwent invasive cardiac catheterization, the gold standard test (408 CAD positive with stenosis≥ 70% and 186 with LVEDP≥ 20 mmHg) and (ii) asymptomatic healthy controls (676). A set of Poincaré-based synchrony features were developed to characterize the interactions between the OVG and PPG signals. The extracted features were employed to train machine learning models for CAD and LVEDP. Five-fold cross-validation was used and the best model was selected based on the average area under the receiver operating characteristic curve (AUC) across 100 runs, then assessed using a hold-out test set. RESULTS: The Elastic Net model developed on the synchrony features can effectively classify CAD positive subjects from healthy controls with an average validation AUC=0.90±0.03 and an AUC= 0.89 on the test set. The developed model for LVEDP can discriminate subjects with elevated LVEDP from healthy controls with an average validation AUC=0.89±0.03 and an AUC=0.89 on the test set. The feature contributions results showed that the selection of a proper registration point for Poincaré analysis is essential for the development of predictive models for different disease targets. CONCLUSIONS: Nonlinear features from simultaneously-acquired signals used as inputs to machine learning can assess CAD and LVEDP safely and accurately with an easy-to-use, portable device, utilized at the point-of-care without radiation, contrast, or patient preparation.

Machine learning: at the heart of failure diagnosis.

PURPOSE OF REVIEW: Refinement in machine learning (ML) techniques and approaches has rapidly expanded artificial intelligence applications for the diagnosis and classification of heart failure (HF). This review is designed to provide the clinician with the basics of ML, as well as this technologies future utility in HF diagnosis and the potential impact on patient outcomes. RECENT FINDINGS: Recent studies applying ML methods to unique data sets available from electrocardiography, vectorcardiography, echocardiography, and electronic health records show significant promise for improving diagnosis, enhancing detection, and advancing treatment of HF. Innovations in both supervised and unsupervised methods have heightened the diagnostic accuracy of models developed to identify the presence of HF and further augmentation of model capabilities are likely utilizing ensembles of ML algorithms derived from different techniques. SUMMARY: This article is an overview of recent applications of ML to achieve improved diagnosis of HF and the resultant implications for patient management.

The old and the large may suffer disproportionately during episodes of high temperature: evidence from a keystone zooplankton species.

Widespread declines in the body size of aquatic ectotherms have been attributed to the poorer ability of older, larger individuals to tolerate high temperature. Here, using the thermal death time curve framework, we investigate the relationship between temperature tolerance and size/age by measuring the change in heat tolerance of the keystone zooplankton species Daphnia magna across a range of temperature intensities (and hence exposures of varying duration) among individuals that differed up to 3-fold in size and thus varied in age also. Across the gradient of exposure temperatures, younger, smaller individuals were more tolerant than older, larger individuals. This suggests that the young and the small may be better equipped to withstand temperature challenges that are both intense/brief and more moderate/prolonged. Our study generalizes results obtained from more acute tolerance assays, providing physiological evidence consistent with the observed reductions in ectotherm body size as a response to warming in aquatic systems.

Systemic Immunomodulatory Treatments for Patients With Atopic Dermatitis: A Systematic Review and Network Meta-analysis.

Importance: Most clinical trials assessing systemic immunomodulatory treatments for patients with atopic dermatitis are placebo-controlled. Objective: To compare the effectiveness and safety of systemic immunomodulatory treatments for patients with atopic dermatitis in a systematic review and network meta-analysis. Data Sources: The Cochrane Central Register of Controlled Trials, MEDLINE, Embase, Latin American and Caribbean Health Science Information database, Global Resource of Eczema Trials database, and clinical trial registries were searched from inception to October 28, 2019. Study Selection: English-language randomized clinical trials of 8 weeks or more of treatment with systemic immunomodulatory medications for moderate to severe atopic dermatitis were included. Titles, abstracts, and articles were screened in duplicate. Of 10 324 citations, 39 trials were included. Data Extraction and Synthesis: Data were extracted in duplicate, and the review adhered to Preferred Reporting Items for Systematic Reviews and Meta-analyses for Network Meta-Analyses guidelines. Random-effects bayesian network meta-analyses were performed and certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation criteria. Main Outcomes and Measures: Prespecified outcomes were change in signs of disease, symptoms, quality of life, itch, withdrawals, and serious adverse events. Results: A total of 39 trials with 6360 patients examining 20 medications and placebo were included. Most trials were conducted for adults receiving up to 16 weeks of therapy. Dupilumab, 300 mg every 2 weeks, was associated with improvement in the Eczema Area and Severity Index score vs placebo (mean difference, 11.3-point reduction; 95% credible interval [CrI], 9.7-13.1 [high certainty]). Cyclosporine (standardized mean difference, -1.1; 95% CrI, -1.7 to -0.5 [low certainty]) and dupilumab (standardized mean difference, -0.9; 95% CrI, -1.0 to -0.8 [high certainty]) were similarly effective vs placebo in clearing clinical signs of atopic dermatitis and may be superior to methotrexate (standardized mean difference, -0.6; 95% CrI, -1.1 to 0.0 [low certainty]) and azathioprine (standardized mean difference, -0.4; 95% CrI, -0.8 to -0.1 [low certainty]). Several investigational medications for atopic dermatitis are promising, but data to date are limited to small early-phase trials. Safety analyses were limited by low event rates. Conclusions and Relevance: Dupilumab and cyclosporine may be more effective for up to 16 weeks of treatment than methotrexate and azathioprine for treating adult patients with atopic dermatitis. More studies directly comparing established and novel treatments beyond 16 weeks are needed and will be incorporated into future updates of this review.

Acclimation capacity and rate change through life in the zooplankton Daphnia.

When a change in the environment occurs, organisms can maintain an optimal phenotypic state via plastic, reversible changes to their phenotypes. These adjustments, when occurring within a generation, are described as the process of acclimation. While acclimation has been studied for more than half a century, global environmental change has stimulated renewed interest in quantifying variation in the rate and capacity with which this process occurs, particularly among ectothermic organisms. Yet, despite the likely ecological importance of acclimation capacity and rate, how these traits change throughout life among members of the same species is largely unstudied. Here we investigate these relationships by measuring the acute heat tolerance of the clonally reproducing zooplankter Daphnia magna of different size/age and acclimation status. The heat tolerance of individuals completely acclimated to relatively warm (28°C) or cool (17°C) temperatures diverged during development, indicating that older, larger individuals had a greater capacity to increase heat tolerance. However, when cool acclimated individuals were briefly exposed to the warm temperature (i.e. were 'heat-hardened'), it was younger, smaller animals with less capacity to acclimate that were able to do so more rapidly because they obtained or came closer to obtaining complete acclimation of heat tolerance. Our results illustrate that within a species, individuals can differ substantially in how rapidly and by how much they can respond to environmental change. We urge greater investigation of the intraspecific relationship between acclimation and development along with further consideration of the factors that might contribute to these enigmatic patterns of phenotypic variation.

Adaptive Maternal Investment in the Wild? Links between Maternal Growth Trajectory and Offspring Size, Growth, and Survival in Contrasting Environments.

Life-history theory predicts that investment per offspring should correlate negatively with the quality of the environment that offspring are anticipated to encounter; parents may use their own experience as juveniles to predict this environment and may modulate offspring traits, such as growth capacity and initial size. We manipulated nutrient levels in the juvenile habitat of wild Atlantic salmon (Salmo salar) to investigate the hypothesis that the egg size that maximizes juvenile growth and survival depends on environmental quality. We also tested whether offspring traits were related to parental growth trajectory. Mothers that grew fast when young produced more offspring and smaller offspring than mothers that grew slowly to reach the same size. Despite their size disadvantage, offspring of faster-growing mothers grew faster than those of slower-growing mothers in all environments, counter to the expectation that they would be competitively disadvantaged. However, they had lower relative survival in environments where the density of older predatory/competitor fish was relatively high. These links between maternal (but not paternal) growth trajectory and offspring survival rate were independent of egg size, underscoring that mothers may be adjusting egg traits other than size to suit the environment their offspring are anticipated to face.

Hierarchical analysis of wild Atlantic salmon (Salmo salar) fecundity in relation to body size and developmental traits.

Using data from wild Atlantic salmon Salmo salar returning to spawn in seven Scottish rivers, we developed a model of fecundity based on individual body size and key developmental traits. We used a novel approach to model selection which maximises predictive accuracy for application to target river stocks to select the best from a suite of Bayesian hierarchical models. This approach aims to ensure the optimal model within the candidate set includes covariates that best predict out-of-sample data to estimate fecundity in areas where no direct observations are available. In addition to body size, the final model included the developmental characteristics of age at smolting and years spent at sea. Using two independent long-term monitoring datasets, the consequences of ignoring these characteristics was revealed by comparing predictions from the best model with models that omitted them.

How to quantify thermal acclimation capacity?

The capacity of organisms to acclimate will influence their ability to cope with ongoing global changes in thermal regimes. Here we highlight methodological issues associated with recent attempts to quantify variation in acclimation capacity among taxa and environments, and describe how these may introduce bias to conclusions. We then propose a measure of thermal acclimation capacity that more directly quantifies the process of acclimation. Future studies of variation in acclimation capacity should critically evaluate whether their chosen empirical metric accurately reflects the theoretical concept of acclimation.

Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning.

BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to cardiovascular (CV) medicine in arenas ranging from genomics to cardiac imaging analysis. Cardiac Phase Space Tomography Analysis (cPSTA), employing machine-learned linear models from an elastic net method optimized by a genetic algorithm, analyzes thoracic phase signals to identify unique mathematical and tomographic features associated with the presence of flow-limiting coronary artery disease (CAD). This novel approach does not require radiation, contrast media, exercise, or pharmacological stress. The objective of this trial was to determine the diagnostic performance of cPSTA in assessing CAD in patients presenting with chest pain who had been referred by their physician for coronary angiography. METHODS: This prospective, multicenter, non-significant risk study was designed to: 1) develop machine-learned algorithms to assess the presence of CAD (defined as one or more ≥ 70% stenosis, or fractional flow reserve ≤ 0.80) and 2) test the accuracy of these algorithms prospectively in a naïve verification cohort. This report is an analysis of phase signals acquired from 606 subjects at rest just prior to angiography. From the collective phase signal data, features were extracted and paired with the known angiographic results. A development set, consisting of signals from 512 subjects, was used for machine learning to determine an algorithm that correlated with significant CAD. Verification testing of the algorithm was performed utilizing previously untested phase signals from 94 subjects. RESULTS: The machine-learned algorithm had a sensitivity of 92% (95% CI: 74%-100%) and specificity of 62% (95% CI: 51%-74%) on blind testing in the verification cohort. The negative predictive value (NPV) was 96% (95% CI: 85%-100%). CONCLUSIONS: These initial multicenter results suggest that resting cPSTA may have comparable diagnostic utility to functional tests currently used to assess CAD without requiring cardiac stress (exercise or pharmacological) or exposure of the patient to radioactivity.