A retrospective assessment of COVID-19 model performance in the USA.

Coronavirus disease 2019 (COVID-19) forecasts from over 100 models are readily available. However, little published information exists regarding the performance of their uncertainty estimates (i.e. probabilistic performance). To evaluate their probabilistic performance, we employ the classical model (CM), an established method typically used to validate expert opinion. In this analysis, we assess both the predictive and probabilistic performance of COVID-19 forecasting models during 2021. We also compare the performance of aggregated forecasts (i.e. ensembles) based on equal and CM performance-based weights to an established ensemble from the Centers for Disease Control and Prevention (CDC). Our analysis of forecasts of COVID-19 mortality from 22 individual models and three ensembles across 49 states indicates that-(i) good predictive performance does not imply good probabilistic performance, and vice versa; (ii) models often provide tight but inaccurate uncertainty estimates; (iii) most models perform worse than a naive baseline model; (iv) both the CDC and CM performance-weighted ensembles perform well; but (v) while the CDC ensemble was more informative, the CM ensemble was more statistically accurate across states. This study presents a worthwhile method for appropriately assessing the performance of probabilistic forecasts and can potentially improve both public health decision-making and COVID-19 modelling.

Comprehensive evidence implies a higher social cost of CO2.

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations.

Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM2.5) is associated with mortality. Nevertheless, extrapolating results to understudied locations may involve considerable uncertainty. To explore this issue, this review discusses the evidence for (i) the associated risk of mortality, (ii) the shape of the concentration-response function, (iii) a causal interpretation, and (iv) how the source mix/composition of PM2.5 and population characteristics may alter the effect. The accumulated evidence suggests the following: (i) In the United States, the change in all-cause mortality risk per µg/m3 is about 0.8%. (ii) The concentration-response function appears nonlinear. (iii) Causation is overwhelmingly supported. (iv) Fossil fuel combustion-related sources are likely more toxic than others, and age, race, and income may modify the effect. To illustrate the use of our findings in support of a risk assessment in an understudied setting, we consider Kuwait. However, given the complexity of this relationship and the heterogeneity in reported effects, it is unreasonable to think that, in such circumstances, point estimates can be meaningful. Consequently, quantitative probabilistic estimates, which cannot be derived objectively, become essential. Formally elicited expert judgment can provide such estimates, and this review provides the evidence to support an elicitation.

Carpal tunnel syndrome and Raynaud's phenomenon: a narrative review.

BACKGROUND: Raynaud's phenomenon (RP) is a recognized symptom associated with carpal tunnel syndrome (CTS) and is also the vascular manifestation of hand arm vibration syndrome (HAVS). The symptoms of HAVS and CTS are such that there is a significant possibility of misdiagnosis and an incorrect attribution of vascular and sensory symptoms. An understanding of the relationship between RP and CTS is essential when undertaking health surveillance of vibration-exposed workers presenting with combined vascular and sensory symptoms. AIMS: To clarify the relationship between CTS and Raynaud's phenomenon. METHODS: A systematic search was undertaken of studies that reviewed links between CTS and Raynaud's phenomenon (RP). RESULTS: A total of 4170 papers were identified, with 21 articles that were then reviewed in full, including 1 meta-analysis of 8 studies. Eighteen papers, not included in the meta-analysis, were found including 3 case control studies, 9 case reports, 2 prospective studies and 4 retrospective reviews. Papers were reviewed on the basis of the diagnostic criteria used for CTS and RP. Our review of the literature confirms a substantial body of evidence of a relationship between RP and CTS. CONCLUSIONS: It is recommended that assessment of vibration exposed individuals who report concurrent RP and separate sensory symptoms suggestive of, or compatible with CTS, should formally exclude CTS before attributing symptoms to HAVS.

Ice Sheet and Climate Processes Driving the Uncertainty in Projections of Future Sea Level Rise: Findings From a Structured Expert Judgement Approach.

The ice sheets covering Antarctica and Greenland present the greatest uncertainty in, and largest potential contribution to, future sea level rise. The uncertainty arises from a paucity of suitable observations covering the full range of ice sheet behaviors, incomplete understanding of the influences of diverse processes, and limitations in defining key boundary conditions for the numerical models. To investigate the impact of these uncertainties on ice sheet projections we undertook a structured expert judgement study. Here, we interrogate the findings of that study to identify the dominant drivers of uncertainty in projections and their relative importance as a function of ice sheet and time. We find that for the 21st century, Greenland surface melting, in particular the role of surface albedo effects, and West Antarctic ice dynamics, specifically the role of ice shelf buttressing, dominate the uncertainty. The importance of these effects holds under both a high-end 5°C global warming scenario and another that limits global warming to 2°C. During the 22nd century the dominant drivers of uncertainty shift. Under the 5°C scenario, East Antarctic ice dynamics dominate the uncertainty in projections, driven by the possible role of ice flow instabilities. These dynamic effects only become dominant, however, for a temperature scenario above the Paris Agreement 2°C target and beyond 2100. Our findings identify key processes and factors that need to be addressed in future modeling and observational studies in order to reduce uncertainties in ice sheet projections.

Vine Regression with Bayes Nets: A Critical Comparison with Traditional Approaches Based on a Case Study on the Effects of Breastfeeding on IQ.

Regular vines (R-vines) copulas build high dimensional joint densities from arbitrary one-dimensional margins and (conditional) bivariate copula densities. Vine densities enable the computation of all conditional distributions, though the calculations can be numerically intensive. Saturated continuous nonparametric Bayes nets (CNPBN) are regular vines. Computing regression functions from the vine copula density is termed vine regression. The epicycles of regression-including/excluding covariates, interactions, higher order terms, multicollinearity, model fit, transformations, heteroscedasticity, bias-are dispelled. One simply computes the regressions from the vine copula density. Only the question of finding an adequate vine copula remains. Vine regression is applied to a data set from the National Longitudinal Study of Youth relating breastfeeding to IQ. The expected effects of breastfeeding on IQ depend on IQ, on the baseline level of breastfeeding, on the duration of additional breastfeeding and on the values of other covariates. A child given two weeks breastfeeding can expect to increase his/her IQ by 1.5-2 IQ points by adding 10 weeks of breastfeeding, depending on values of other covariates. A child given two years breastfeeding can expect to gain from 0.48-0.65 IQ points from 10 additional weeks. Adding 10 weeks breastfeeding to each of the 3,179 children in this data set has a net present value $50,700,000 according to the Bayes net, compared to $29,000,000 according to the linear regression.

Rationale and design of a mechanistic clinical trial of JAK inhibition to prevent ventilator-induced diaphragm dysfunction.

INTRODUCTION: Ventilator-induced diaphragm dysfunction (VIDD) is an important phenomenon that has been repeatedly demonstrated in experimental and clinical models of mechanical ventilation. Even a few hours of MV initiates signaling cascades that result in, first, reduced specific force, and later, atrophy of diaphragm muscle fibers. This severe, progressive weakness of the critical ventilatory muscle results in increased duration of MV and thus increased MV-associated complications/deaths. A drug that could prevent VIDD would likely have a major positive impact on intensive care unit outcomes. We identified the JAK/STAT pathway as important in VIDD and then demonstrated that JAK inhibition prevents VIDD in rats. We subsequently developed a clinical model of VIDD demonstrating reduced contractile force of isolated diaphragm fibers harvested after ∼7 vs ∼1 h of MV during a thoracic surgical procedure. MATERIALS AND METHODS: The NIH-funded clinical trial that has been initiated is a prospective, placebo controlled trial: subjects undergoing esophagectomy are randomized to receive 6 preoperative doses of the FDA-approved JAK inhibitor Tofacitinib (commonly used for rheumatoid arthritis) vs. placebo. The primary outcome variable will be the difference in the reduction that occurs in force generation of diaphragm single muscle fibers (normalized to their cross-sectional area), in the Tofacitinib vs. placebo subjects, over 6 h of MV. DISCUSSION: This trial represents a first-in-human, mechanistic clinical trial of a drug to prevent VIDD. It will provide proof-of-concept in human subjects whether JAK inhibition prevents clinical VIDD, and if successful, will support an ICU-based clinical trial that would determine whether JAK inhibition impacts clinical outcome variables such as duration of MV and mortality.

The role of the super-relaxed state of myosin in human metabolism.

BACKGROUND: The super-relaxed state of myosin (SRX) plays a fundamental role in maintaining the low resting metabolic rate of skeletal muscle. Our previous work on this state has been in animal models. Piperine is a small molecule that has been shown to destabilize the SRX in rabbit fast twitch fibers. METHODS: Here we extend this work to human muscle obtained from biopsies of the vastus lateralis of both lean and obese subjects. The slow release of nucleotides by myosin in the SRX was measured by incubating permeable fibers in a fluorescent analog of ATP and chasing with ATP. RESULTS: The fraction of myosin heads in the SRX was 0.48 ± 0.04 with a lifetime of 148 ± 5 s in lean subjects and a fraction of 0.41 ± 0.05 and a lifetime of 176 ± 7 s in obese subjects. Addition of 100 µM piperine decreased the SRX population by 43 ± 7% in lean subjects and 36 ± 7% in obese subjects, with little change in lifetimes. Addition of piperine to human cardiac cells had no effect on the SRX, a requirement for a drug to treat metabolic diseases. CONCLUSIONS: In human muscle the SRX and its responses to piperine are similar to those seen previously, with no significant differences between muscles from lean and obese subjects. Thus analogs of piperine that have greater specificity could provide effective treatment for metabolic diseases. The SRX provides a potential mechanism contributing to the large dynamic range of metabolic rate.

Attribution of Illnesses Transmitted by Food and Water to Comprehensive Transmission Pathways Using Structured Expert Judgment, United States.

Illnesses transmitted by food and water cause a major disease burden in the United States despite advancements in food safety, water treatment, and sanitation. We report estimates from a structured expert judgment study using 48 experts who applied Cooke's classical model of the proportion of disease attributable to 5 major transmission pathways (foodborne, waterborne, person-to-person, animal contact, and environmental) and 6 subpathways (food handler-related, under foodborne; recreational, drinking, and nonrecreational/nondrinking, under waterborne; and presumed person-to-person-associated and presumed animal contact-associated, under environmental). Estimates for 33 pathogens were elicited, including bacteria such as Salmonella enterica, Campylobacter spp., Legionella spp., and Pseudomonas spp.; protozoa such as Acanthamoeba spp., Cyclospora cayetanensis, and Naegleria fowleri; and viruses such as norovirus, rotavirus, and hepatitis A virus. The results highlight the importance of multiple pathways in the transmission of the included pathogens and can be used to guide prioritization of public health interventions.

Nanomolar ATP binding to single myosin cross-bridges in rigor: a molecular approach to studying myosin ATP kinetics using single human cardiomyocytes.

Our knowledge in the field of cardiac muscle and associated cardiomyopathies has been evolving incrementally over the past 60 years and all was possible due to the parallel progress in techniques and methods allowing to take a fresh glimpse at an old problem. Here, we describe an exciting tool used to examine the various states of the human cardiac myosin at the single molecule level. By imaging single Alexa647-ATP binding to permeabilised cardiomyocytes using total internal reflection fluorescence (TIRF) microscopy, we are able to acquire large populations of events in a short timeframe (~ 5000 sites in ~ 10 min) and measure each binding event with high spatio-temporal resolution. The applied algorithm decomposes the point pattern of single molecule binding events into individually distinct binding sites that enables us to recover kinetic parameters, such as bound or free time per site. This single molecule binding approach is a useful tool used to examine muscle contractility. Of particular importance is its application to probing the dynamic lifetimes and proportion of myosins in the super-relaxed state in human cardiomyopathies.

Biophysics of human anatomy and physiology-a Special Issue in honor of Prof. Cristobal dos Remedios on the occasion of his 80th birthday.

In 2001, Cristobal dos Remedios was made Professor of Anatomy (now emeritus) within Australia's highest-ranked university (University of Sydney). For the majority of his career, he has examined the biomechanics and biophysics of human muscle contraction. To coincide with the occasion of his 80th birthday, this Special Issue has commissioned a collection of review articles from experts exploring biophysical subjects within the general areas of human anatomy and physiology. After introducing the scope and contents of the Issue, we provide a short scientific biography, placing his scientific achievements within the context of the course of his life's developments.

Quantifying uncertainty about future antimicrobial resistance: Comparing structured expert judgment and statistical forecasting methods.

The increase of multidrug resistance and resistance to last-line antibiotics is a major global public health threat. Although surveillance programs provide useful current and historical information on the scale of the problem, the future emergence and spread of antibiotic resistance is uncertain, and quantifying this uncertainty is crucial for guiding decisions about investment in antibiotics and resistance control strategies. Mathematical and statistical models capable of projecting future rates are challenged by the paucity of data and the complexity of the emergence and spread of resistance, but experts have relevant knowledge. We use the Classical Model of structured expert judgment to elicit projections with uncertainty bounds of resistance rates through 2026 for nine pathogen-antibiotic pairs in four European countries and empirically validate the assessments against data on a set of calibration questions. The performance-weighted combination of experts in France, Spain, and the United Kingdom projected that resistance for five pairs on the World Health Organization's priority pathogens list (E. coli and K. pneumoniae resistant to third-generation cephalosporins and carbapenems and MRSA) would remain below 50% in 2026. In Italy, although upper bounds of 90% credible ranges exceed 50% resistance for some pairs, the medians suggest Italy will sustain or improve its current rates. We compare these expert projections to statistical forecasts based on historical data from the European Antimicrobial Resistance Surveillance Network (EARS-Net). Results from the statistical models differ from each other and from the judgmental forecasts in many cases. The judgmental forecasts include information from the experts about the impact of current and future shifts in infection control, antibiotic usage, and other factors that cannot be easily captured in statistical forecasts, demonstrating the potential of structured expert judgment as a tool for better understanding the uncertainty about future antibiotic resistance.

Ice sheet contributions to future sea-level rise from structured expert judgment.

Despite considerable advances in process understanding, numerical modeling, and the observational record of ice sheet contributions to global mean sea-level rise (SLR) since the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, severe limitations remain in the predictive capability of ice sheet models. As a consequence, the potential contributions of ice sheets remain the largest source of uncertainty in projecting future SLR. Here, we report the findings of a structured expert judgement study, using unique techniques for modeling correlations between inter- and intra-ice sheet processes and their tail dependences. We find that since the AR5, expert uncertainty has grown, in particular because of uncertain ice dynamic effects. For a +2 °C temperature scenario consistent with the Paris Agreement, we obtain a median estimate of a 26 cm SLR contribution by 2100, with a 95th percentile value of 81 cm. For a +5 °C temperature scenario more consistent with unchecked emissions growth, the corresponding values are 51 and 178 cm, respectively. Inclusion of thermal expansion and glacier contributions results in a global total SLR estimate that exceeds 2 m at the 95th percentile. Our findings support the use of scenarios of 21st century global total SLR exceeding 2 m for planning purposes. Beyond 2100, uncertainty and projected SLR increase rapidly. The 95th percentile ice sheet contribution by 2200, for the +5 °C scenario, is 7.5 m as a result of instabilities coming into play in both West and East Antarctica. Introducing process correlations and tail dependences increases estimates by roughly 15%.

Piperine, an alkaloid inhibiting the super-relaxed state of myosin, binds to the myosin regulatory light chain.

Piperine, an alkaloid from black pepper, was found to inhibit the super-relaxed state (SRX) of myosin in fast-twitch skeletal muscle fibers. In this work we report that the piperine molecule binds heavy meromyosin (HMM), whereas it does not interact with the regulatory light chain (RLC)-free subfragment-1 (S1) or with control proteins from the same muscle molecular machinery, G-actin and tropomyosin. To further narrow down the location of piperine binding, we studied interactions between piperine and a fragment of skeletal myosin consisting of the full-length RLC and a fragment of the heavy chain (HCF). The sequence of HCF was designed to bind RLC and to dimerize via formation of a stable coiled coil, thus producing a well-folded isolated fragment of the myosin neck. Both chains were co-expressed in Escherichia coli, the RLC/HCF complex was purified and tested for stability, composition and binding to piperine. RLC and HCF chains formed a stable heterotetrameric complex (RLC/HCF)2 which was found to bind piperine. The piperine molecule was also found to bind isolated RLC. Piperine binding to RLC in (RLC/HCF)2 altered the compactness of the complex, suggesting that the mechanism of SRX inhibition by piperine is based on changing conformation of the myosin.