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Objectives: Rates of surgically treated carpal tunnel syndrome (CTS) among blue- and white-collar workers and housewives in the general population were compared.Methods: Surgically treated cases of idiopathic CTS were investigated among 25-59-year-old residents of Tuscany, Italy, during 1997-2000, based on obligatory discharge records from all Italian public/private hospitals, archived according to residence on Tuscany's regional database. Population data were extracted from the 2001 census.Results: After excluding repeat admissions, 8801 eligible cases were identified. Age-standardised rates (per 100 000 person-years) of surgical CTS were: "blue-collar women", 367.8; "white-collar women", 88.1; "housewives", 334.5; "blue-collar men", 73.5; and "white-collar men", 15.3. Compared with reference categories (same-sex white-collar workers): female blue-collar workers experienced a 4.2-fold higher standardised rate; housewives, a 3.8-fold excess; and male blue-collar workers, a 4.8-fold excess (all p<0.001). Male and female blue-collar workers showed approximately three to sevenfold higher age-specific rates compared to their white-collar counterparts (all p<0.001). Housewives' rates were similar to those of blue-collar female workers up to 40-44 years of age, after which they were significantly lower (p<0.002). At all ages, housewives' rates were much higher (p<0.001) than those of white-collar women.Conclusions: Surgically treated CTS was three to seven times more common (depending on age/gender) in blue-collar than in white-collar workers, which is difficult to explain by differences in body weight or other individual factors. Thus, occupational risk factors seem relevant throughout working life. The high rates for full-time housewives suggest that domestic chores should be investigated as a possible risk factor for CTS. [ABSTRACT FROM AUTHOR]

With public health policy increasingly relying on mathematical models to provide insights about the impacts of potential policy options, the demand for uncertainty and sensitivity analyses that explore the implications of different assumptions in a model continues to expand. Although analysts continue to develop methods to meet the demand, most modelers rely on a single method in the context of their assessments and presentations of results, and few analysts provide results that facilitate comparisons between uncertainty and sensitivity analysis methods. METHODS: vary in their degree of analytical difficulty and in the nature of the information that they provide, and analysts should communicate results with a note that not all methods yield the same insights. The authors explore several sensitivity analysis methods to test whether the choice of method affects the insights and importance rankings of inputs from the analysis. They use a dynamic cost-effectiveness model of a hypothetical infectious disease as the basis to perform 1-way and multi-way sensitivity analyses, design of experiments, and Morris' method. They also compute partial derivatives as well as a number of probabilistic sensitivity measures, including correlations, regression coefficients, and the correlation ratio, to demonstrate the existing methods and to compare them. The authors find that the magnitudes and rankings of sensitivity measures depend on the selected method(s) and make recommendations regarding the choice of method depending on the complexity of the model, number of uncertain inputs, and desired types of insights from the sensitivity analysis. [ABSTRACT FROM AUTHOR]

Objective To compare the yield of hand-searching with optimised electronic search strategies in retrieving occupational health (OH) intervention studies published in a language other than English. Methods The authors systematically hand-searched and screened reports of OH intervention studies published in Italian in peer-reviewed scientific journals between 1990 and 2008. The authors evaluated how many of them met the Cochrane Occupational Safety and Health Review Groups (OSHRG) definition of being an OH intervention study and how many potentially relevant studies retrieved by hand-searching would not be found by PubMed alone using the OSHRG's most specific and most sensitive search strings. Results Hand-searching retrieved 25 articles (reporting 27 studies), including nine not indexed in MEDLINE. Most studies (81%, 22/27) had a before-after design and only one was a randomised trial. The OSHRG's most sensitive search string retrieved all 16 articles published in the Italian language journals that were indexed in MEDLINE, while the most specific search strategy retrieved nine articles (56%, 9/16). The most specific search string showed a lower 'number needed to read' value than the most sensitive one (60 vs 132). Conclusions These findings suggest that a sensitive electronic search strategy may be able to find most of the OH interventions published in languages other than English that are indexed in MEDLINE. Hand-searching of important national journals not indexed in MEDLINE should be considered when conducting particularly in-depth research. [ABSTRACT FROM AUTHOR]

The CC chemokine receptor 6 (CCR6) is a potential target for chronic inflammatory diseases. Previously, we reported an active CCR6 structure in complex with its cognate chemokine CCL20, revealing the molecular basis of CCR6 activation. Here, we present two inactive CCR6 structures in ternary complexes with different allosteric antagonists, CCR6/SQA1/OXM1 and CCR6/SQA1/OXM2. The oxomorpholine analogues, OXM1 and OXM2 are highly selective CCR6 antagonists which bind to an extracellular pocket and disrupt the receptor activation network. An energetically favoured U-shaped conformation in solution that resembles the bound form is observed for the active analogues. SQA1 is a squaramide derivative with close-in analogues reported as antagonists of chemokine receptors including CCR6. SQA1 binds to an intracellular pocket which overlaps with the G protein site, stabilizing a closed pocket that is a hallmark of inactive GPCRs. Minimal communication between the two allosteric pockets is observed, in contrast to the prevalent allosteric cooperativity model of GPCRs. This work highlights the versatility of GPCR antagonism by small molecules, complementing previous knowledge of CCR6 activation, and sheds light on drug discovery targeting CCR6., (© 2024. The Author(s).)

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., (© 2022 The Authors.)

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., (© 2022 The Authors.)

Background: The majority of cases of idiopathic acute pancreatitis (IAP) are thought to result from occult biliary disease. A growing body of evidence suggests that cholecystectomy for IAP reduces the risk of recurrence by up to two thirds. This study examined nationwide uptake and disparities in adoption of cholecystectomy for IAP., Methods: The National Inpatient Sample was queried to identify admissions for IAP between October 2015 and December 2018. Patients who underwent cholecystectomy before discharge and those that did not were compared using Wald χ 2 tests for categorical variables and Student's t test for continuous variables. Patient- and hospital-level predictors of cholecystectomy were identified using weighted multivariable logistic regression., Results: Of 62,305 estimated admissions for IAP, only 665 (1.1%) underwent cholecystectomy before discharge. Female sex, initiation of total parenteral nutrition (TPN), insurance status, and hospital type were associated with cholecystectomy on univariable analysis. On multivariable analysis, Hispanic patients (odds ration [OR] 1.60, 95% confidence interval [CI] 1.01-2.56), patients on TPN (OR 2.70, 95% CI 1.17-6.24), and those with private insurance (OR 2.18, 95% CI 1.48-3.21 versus Medicare/Medicaid) were more likely to receive operations. Small hospitals and hospitals in rural areas were least likely to perform empiric cholecystectomies., Conclusion: Despite increasing evidence supporting cholecystectomy after IAP, the practice remains rare in the United States. Educational efforts and active implementation efforts are needed to promote adoption. Particular attention should be focused on small, rural centers and those that disproportionately care for uninsured patients and patients with public insurance., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM 2.5 ) 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 PM 2.5 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/m 3 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.

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., (© 2021 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic., Competing Interests: Declaration of interests T.T. and M.W. are shareholders and board members of Sosei Heptares. The authors A.J.H.B., G.A.B., K.A.B., J.B., J.E.C., M.S.C., R.M.C., J.C.E., E.H., A.J., C.J.L., J.L., F.H.M., P.J.N., K.O., G.O., J.C.P., M.P., N.R., P.R., B.G.T., R.T.S., C.d.G., G.M., and B.T. are or have been employees of Heptares Therapeutics and are shareholders of Sosei Heptares., (Copyright © 2021. Published by Elsevier Inc.)

Drawing on risk methods from volcano crises, we developed a rapid COVID-19 infection model for the partial return of pupils to primary schools in England in June and July 2020, and a full return in September 2020. The model handles uncertainties in key parameters, using a stochastic re-sampling technique, allowing us to evaluate infection levels as a function of COVID-19 prevalence and projected pupil and staff headcounts. Assuming average national adult prevalence, for the first scenario (as at 1 June 2020) we found that between 178 and 924 [90% CI] schools would have at least one infected individual, out of 16 769 primary schools in total. For the second return (July), our estimate ranged between 336 (2%) and 1873 (11%) infected schools. For a full return in September 2020, our projected range was 661 (4%) to 3310 (20%) infected schools, assuming the same prevalence as for 5 June. If national prevalence fell to one-quarter of that, the projected September range would decrease to between 381 (2%) and 900 (5%) schools but would increase to between 2131 (13%) and 9743 (58%) schools if prevalence increased to 4× June level. When regional variations in prevalence and school size distribution were included in the model, a slight decrease in the projected number of infected schools was indicated, but uncertainty on estimates increased markedly. The latter model variant indicated that 82% of infected schools would be in areas where prevalence exceeded the national average and the probability of multiple infected persons in a school would be higher in such areas. Post hoc , our model projections for 1 September 2020 were seen to have been realistic and reasonable (in terms of related uncertainties) when data on schools' infections were released by official agencies following the start of the 2020/2021 academic year., (© 2021 The Authors.)

In this study, we determined the crystal structure of an engineered human adenosine A 2A receptor bound to a partial agonist and compared it to structures cocrystallized with either a full agonist or an antagonist/inverse agonist. The interaction between the partial agonist, belonging to a class of dicyanopyridines, and amino acids in the ligand binding pocket inspired us to develop a small library of derivatives and assess their affinity in radioligand binding studies and potency and intrinsic activity in a functional, label-free, intact cell assay. It appeared that some of the derivatives retained the partial agonist profile, whereas other ligands turned into inverse agonists. We rationalized this remarkable behavior with additional computational docking studies.

Personal contacts drive COVID-19 infections. After being closed (23 March 2020) UK primary schools partially re-opened on 1 June 2020 with social distancing and new risk mitigation strategies. We conducted a structured expert elicitation of teachers to quantify primary school contact patterns and how contact rates changed upon re-opening with risk mitigation measures in place. These rates, with uncertainties, were determined using a performance-based algorithm. We report mean number of contacts per day for four cohorts within schools, with associated 90% confidence ranges. Prior to lockdown, younger children (Reception and Year 1) made 15 contacts per day [range 8.35] within school, older children (Year 6) 18 contacts [range 5.55], teaching staff 25 contacts [range 4.55] and non-classroom staff 11 contacts [range 2.27]. After re-opening, the mean number of contacts was reduced by 53% for young children, 62% for older children, 60% for classroom staff and 64% for other staff. Contacts between teaching and non-teaching staff reduced by 80%. The distributions of contacts per person are asymmetric with heavy tail reflecting a few individuals with high contact numbers. Questions on risk mitigation and supplementary structured interviews elucidated how new measures reduced daily contacts in-school and contribute to infection risk reduction., Competing Interests: We declare we have no competing interests., (© 2021 The Authors.)

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.

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A 2A adenosine receptor (AR). Eight A 2A AR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A 2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A 2A AR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A 2A AR, an emerging target in immuno-oncology., (© 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

The orexin system, which consists of the two G protein-coupled receptors OX 1 and OX 2 , activated by the neuropeptides OX-A and OX-B, is firmly established as a key regulator of behavioral arousal, sleep, and wakefulness and has been an area of intense research effort over the past two decades. X-ray structures of the receptors in complex with 10 new antagonist ligands from diverse chemotypes are presented, which complement the existing structural information for the system and highlight the critical importance of lipophilic hotspots and water molecules for these peptidergic GPCR targets. Learnings from the structural information regarding the utility of pharmacophore models and how selectivity between OX 1 and OX 2 can be achieved are discussed.

A series of novel allosteric antagonists of the GLP-1 receptor (GLP-1R), exemplified by HTL26119, are described. SBDD approaches were employed to identify HTL26119, exploiting structural understanding of the allosteric binding site of the closely related Glucagon receptor (GCGR) (Jazayeri et al., 2016) and the homology relationships between GCGR and GLP-1R. The region around residue C347 6.36b of the GLP-1R receptor represents a key difference from GCGR and was targeted for selectivity for GLP-1R., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Alec Morton has received a speakers’ fee from the Office of Health Economics for participation in a workshop on health technology assessment for new antibiotics, sponsored by pharmaceutical companies. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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%., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

The discovery of ligands via affinity-mediated selection of DNA-encoded chemical libraries is driven by the quality and concentration of the protein target. G-protein-coupled receptors (GPCRs) and other membrane-bound targets can be difficult to isolate in their functional state and at high concentrations, and therefore have been challenging for affinity-mediated selection. Here, we report a successful selection campaign against protease-activated receptor 2 (PAR2). Using a thermo-stabilized mutant of PAR2, we conducted affinity selection using our >100-billion-compound DNA-encoded library. We observed a number of putative ligands enriched upon selection, and subsequent cellular profiling revealed these ligands to comprise both agonists and antagonists. The agonist series shared structural similarity with known agonists. The antagonists were shown to bind in a novel allosteric binding site on the PAR2 protein. This report serves to demonstrate that cell-free affinity selection against GPCRs can be achieved with mutant stabilized protein targets.

Here we report an efficient method to generate multiple co-structures of the A 2A G protein-coupled receptor (GPCR) with small-molecules from a single preparation of a thermostabilised receptor crystallised in Lipidic Cubic Phase (LCP). Receptor crystallisation is achieved following purification using a low affinity "carrier" ligand (theophylline) and crystals are then soaked in solutions containing the desired (higher affinity) compounds. Complete datasets to high resolution can then be collected from single crystals and seven structures are reported here of which three are novel. The method significantly improves structural throughput for ligand screening using stabilised GPCRs, thereby actively driving Structure-Based Drug Discovery (SBDD).

The complement system is a crucial component of the host response to infection and tissue damage. Activation of the complement cascade generates anaphylatoxins including C5a and C3a. C5a exerts a pro-inflammatory effect via the G-protein-coupled receptor C5a anaphylatoxin chemotactic receptor 1 (C5aR1, also known as CD88) that is expressed on cells of myeloid origin. Inhibitors of the complement system have long been of interest as potential drugs for the treatment of diseases such as sepsis, rheumatoid arthritis, Crohn's disease and ischaemia-reperfusion injuries. More recently, a role of C5a in neurodegenerative conditions such as Alzheimer's disease has been identified. Peptide antagonists based on the C5a ligand have progressed to phase 2 trials in psoriasis and rheumatoid arthritis; however, these compounds exhibited problems with off-target activity, production costs, potential immunogenicity and poor oral bioavailability. Several small-molecule competitive antagonists for C5aR1, such as W-54011 and NDT9513727, have been identified by C5a radioligand-binding assays. NDT9513727 is a non-peptide inverse agonist of C5aR1, and is highly selective for the primate and gerbil receptors over those of other species. Here, to study the mechanism of action of C5a antagonists, we determine the structure of a thermostabilized C5aR1 (known as C5aR1 StaR) in complex with NDT9513727. We found that the small molecule bound between transmembrane helices 3, 4 and 5, outside the helical bundle. One key interaction between the small molecule and residue Trp213 5.49 seems to determine the species selectivity of the compound. The structure demonstrates that NDT9513727 exerts its inverse-agonist activity through an extra-helical mode of action.

Where policy and science intersect, there are always issues of ambiguous and conflicting lines of evidence. Combining disparate information sources is mathematically complex; common heuristics based on simple statistical models easily lead us astray. Here, we use Bayesian Nets (BNs) to illustrate the complexity in reasoning under uncertainty. Data from joint research at Resources for the Future and NASA Langley are used to populate a BN for predicting equilibrium climate sensitivity (ECS). The information sources consist of measuring the rate of decadal temperature rise (DTR) and measuring the rate of percentage change in cloud radiative forcing (CRF), with both the existing configuration of satellites and with a proposed enhanced measuring system. The goal of all measurements is to reduce uncertainty in equilibrium climate sensitivity. Subtle aspects of probabilistic reasoning with concordant and discordant measurements are illustrated. Relative to the current prior distribution on ECS, we show that after 30 years of observing with the current systems, the 2 σ uncertainty band for ECS would be shrunk on average to 73% of its current value. With the enhanced systems over the same time, it would be shrunk to 32% of its current value. The actual shrinkage depends on the values actually observed. These results are based on models recommended by the Social Cost of Carbon methodology and assume a Business as Usual emissions path.

The four adenosine receptors (ARs), A 1 , A 2A , A 2B , and A 3 , constitute a subfamily of G protein-coupled receptors (GPCRs) with exceptional foundations for structure-based ligand design. The vast amount of mutagenesis data, accumulated in the literature since the 1990s, has been recently supplemented with structural information, currently consisting of several inactive and active structures of the A 2A and inactive conformations of the A 1 ARs. We provide the first integrated view of the pharmacological, biochemical, and structural data available for this receptor family, by mapping onto the relevant crystal structures all site-directed mutagenesis data, curated and deposited at the GPCR database (available through http://www.gpcrdb.org). This analysis provides novel insights into ligand binding, allosteric modulation, and signaling of the AR family., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Ligand-protein binding kinetic rates are growing in importance as parameters to consider in drug discovery and lead optimization. In this study we analysed using surface plasmon resonance (SPR) the transition state (TS) properties of a set of six adenosine A 2A receptor inhibitors, belonging to both the xanthine and the triazolo-triazine scaffolds. SPR highlighted interesting differences among the ligands in the enthalpic and entropic components of the TS energy barriers for the binding and unbinding events. To better understand at a molecular level these differences, we developed suMetaD, a novel molecular dynamics (MD)-based approach combining supervised MD and metadynamics. This method allows simulation of the ligand unbinding and binding events. It also provides the system conformation corresponding to the highest energy barrier the ligand is required to overcome to reach the final state. For the six ligands evaluated in this study their TS thermodynamic properties were linked in particular to the role of water molecules in solvating/desolvating the pocket and the small molecules. suMetaD identified kinetic bottleneck conformations near the bound state position or in the vestibule area. In the first case the barrier is mainly enthalpic, requiring the breaking of strong interactions with the protein. In the vestibule TS location the kinetic bottleneck is instead mainly of entropic nature, linked to the solvent behaviour.

Historically, room-temperature structure determination was succeeded by cryo-crystallography to mitigate radiation damage. Here, we demonstrate that serial millisecond crystallography at a synchrotron beamline equipped with high-viscosity injector and high frame-rate detector allows typical crystallographic experiments to be performed at room-temperature. Using a crystal scanning approach, we determine the high-resolution structure of the radiation sensitive molybdenum storage protein, demonstrate soaking of the drug colchicine into tubulin and native sulfur phasing of the human G protein-coupled adenosine receptor. Serial crystallographic data for molecular replacement already converges in 1,000-10,000 diffraction patterns, which we collected in 3 to maximally 82 minutes. Compared with serial data we collected at a free-electron laser, the synchrotron data are of slightly lower resolution, however fewer diffraction patterns are needed for de novo phasing. Overall, the data we collected by room-temperature serial crystallography are of comparable quality to cryo-crystallographic data and can be routinely collected at synchrotrons.Serial crystallography was developed for protein crystal data collection with X-ray free-electron lasers. Here the authors present several examples which show that serial crystallography using high-viscosity injectors can also be routinely employed for room-temperature data collection at synchrotrons.

This corrects the article DOI: 10.1038/nature22800.

The adenosine A 1 and A 2A receptors belong to the purinergic family of G protein-coupled receptors, and regulate diverse functions of the cardiovascular, respiratory, renal, inflammation, and CNS. Xanthines such as caffeine and theophylline are weak, non-selective antagonists of adenosine receptors. Here we report the structure of a thermostabilized human A 1 receptor at 3.3 Å resolution with PSB36, an A 1 -selective xanthine-based antagonist. This is compared with structures of the A 2A receptor with PSB36 (2.8 Å resolution), caffeine (2.1 Å), and theophylline (2.0 Å) to highlight features of ligand recognition which are common across xanthines. The structures of A 1 R and A 2A R were analyzed to identify the differences that are important selectivity determinants for xanthine ligands, and the role of T270 7.35 in A 1 R (M270 7.35 in A 2A R) in conferring selectivity was confirmed by mutagenesis. The structural differences confirmed to lead to selectivity can be utilized in the design of new subtype-selective A 1 R or A 2A R antagonists., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Glucagon-like peptide 1 (GLP-1) regulates glucose homeostasis through the control of insulin release from the pancreas. GLP-1 peptide agonists are efficacious drugs for the treatment of diabetes. To gain insight into the molecular mechanism of action of GLP-1 peptides, here we report the crystal structure of the full-length GLP-1 receptor bound to a truncated peptide agonist. The peptide agonist retains an α-helical conformation as it sits deep within the receptor-binding pocket. The arrangement of the transmembrane helices reveals hallmarks of an active conformation similar to that observed in class A receptors. Guided by this structural information, we design peptide agonists with potent in vivo activity in a mouse model of diabetes.