Thermal limits of leaf metabolism across biomes

High-temperature tolerance in plants is important in a warming world, with extreme heat waves predicted to increase in frequency and duration, potentially leading to lethal heating of leaves. Global patterns of high-temperature tolerance are documented in animals, but generally not in plants, limiting our ability to assess risks associated with climate warming. To assess whether there are global patterns in high-temperature tolerance of leaf metabolism, we quantified Tcrit (high temperature where minimal chlorophyll a fluorescence rises rapidly and thus photosystem II is disrupted) and Tmax (temperature where leaf respiration in darkness is maximal, beyond which respiratory function rapidly declines) in upper canopy leaves of 218 plant species spanning seven biomes. Mean site-based Tcrit values ranged from 41.5 °C in the Alaskan arctic to 50.8 °C in lowland tropical rainforests of Peruvian Amazon. For Tmax, the equivalent values were 51.0 and 60.6 °C in the Arctic and Amazon, respectively. Tcrit and Tmax followed similar biogeographic patterns, increasing linearly (˜8 °C) from polar to equatorial regions. Such increases in high-temperature tolerance are much less than expected based on the 20 °C span in high-temperature extremes across the globe. Moreover, with only modest high-temperature tolerance despite high summer temperature extremes, species in mid-latitude (~20–50°) regions have the narrowest thermal safety margins in upper canopy leaves; these regions are at the greatest risk of damage due to extreme heat-wave events, especially under conditions when leaf temperatures are further elevated by a lack of transpirational cooling. Using predicted heat-wave events for 2050 and accounting for possible thermal acclimation of Tcrit and Tmax, we also found that these safety margins could shrink in a warmer world, as rising temperatures are likely to exceed thermal tolerance limits. Thus, increasing numbers of species in many biomes may be at risk as heat-wave events become more severe with climate change.Access to the two Peruvian sites was also facilitated by a Moore Foundation grant (Oliver Phillips, Yadvinder Mahli, and Jon Lloyd; www.rainfor.org). This work was funded by grants/fellowships from the Australian Research Council (DP0986823, DP130101252, CE140100008, FT0991448) to O.K.A., DP140103415 to M.G.T., FT110100457 to P.M., Natural Environment Research Council (UK) to P.M. (NERC NE/F002149/1), USA National Science Foundation to K.L.G. (DEB-1234162), U.S. Department of Energy to P.B.R. (DE-FG02-7ER64456), and U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER) through the Southeastern Regional Center of the National Institute for Climatic Change Research at Duke University to M.G.T and Texas AgriLife Research to M.G.T

Implications of improved representations of plant respiration in a changing climate

Land-atmosphere exchanges influence atmospheric CO2. Emphasis has been on describing photosynthetic CO2 uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (R d) and temperature dependencies. This allows characterisation of baseline R d, instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates R d to whole-plant respiration R p, driven with meteorological forcings spanning uncertainty across climate change models. For pre-industrial estimates, new baseline R d increases R p and especially in the tropics. Compared to new baseline, revised instantaneous response decreases R p for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new R d estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how R d aggregates to whole-plant respiration. Our analysis suggests R p could be around 30% higher than existing estimates.C.H. acknowledges the NERC CEH National Capability fund. We acknowledge the many climate research centres that contributed GCM outputs in to the Coupled Model Intercomparison Project (CMIP5) database. The support of the Australian Research Council to O.K.A. and P.M. (DP130101252, CE140100008, FT0991448, FT110100457) is acknowledged, as are awards DE-FG02-07ER64456 from the US Department of Energy, Office of Science, Office of Biological and Environmental Research and DEB-1234162 from the U.S. National Science Foundation (NSF) Long-Term Ecological Research Program (to P.B.R.); and National Science Foundation International Polar Year Grant (to K.L.G.). L.M.M. acknowledges the support of the Natural Environment Research Council (NERC) South American Biomass Burning Analysis (SAMBBA) project grant code NE/ J010057/1

Convergence in the temperature response of leaf respiration across biomes and plant functional types

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration–temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates

Rad51 and DNA-PKcs are involved in the generation of specific telomere aberrations induced by the quadruplex ligand 360A that impair mitotic cell progression and lead to cell death

Functional telomeres are protected from non-homologous end-joining (NHEJ) and homologous recombination (HR) DNA repair pathways. Replication is a critical period for telomeres because of the requirement for reconstitution of functional protected telomere conformations, a process that involves DNA repair proteins. Using knockdown of DNA-PKcs and Rad51 expression in three different cell lines, we demonstrate the respective involvement of NHEJ and HR in the formation of telomere aberrations induced by the G-quadruplex ligand 360A during or after replication. HR contributed to specific chromatid-type aberrations (telomere losses and doublets) affecting the lagging strand telomeres, whereas DNA-PKcs-dependent NHEJ was responsible for sister telomere fusions as a direct consequence of G-quadruplex formation and/or stabilization induced by 360A on parental telomere G strands. NHEJ and HR activation at telomeres altered mitotic progression in treated cells. In particular, NHEJ-mediated sister telomere fusions were associated with altered metaphase-anaphase transition and anaphase bridges and resulted in cell death during mitosis or early G1. Collectively, these data elucidate specific molecular and cellular mechanisms triggered by telomere targeting by the G-quadruplex ligand 360A, leading to cancer cell death

The Great American Crime Decline : Possible Explanations

This chapter examines the most important features of the crime decline in the United States during the 1990s-2010s but also takes a broader look at the violence declines of the last three centuries. The author argues that violent and property crime trends might have diverged in the 1990s, with property crimes increasingly happening in the online sphere and thus traditional property crime statistics not being reflective of the full picture. An important distinction is made between ‘contact crimes’ and crimes that do not require a victim and offender to be present in the same physical space. Contrary to the uncertainties engendered by property crime, the declines in violent (‘contact’) crime are rather general, and have been happening not only across all demographic and geographic categories within the United States but also throughout the developed world. An analysis of research literature on crime trends has identified twenty-four different explanations for the crime drop. Each one of them is briefly outlined and examined in terms of conceptual clarity and empirical support. Nine crime decline explanations are highlighted as the most promising ones. The majority of these promising explanations, being relative newcomers in the crime trends literature, have not been subjected to sufficient empirical scrutiny yet, and thus require further research. One potentially fruitful avenue for future studies is to examine the association of the most promising crime decline explanations with improvements in self-control

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Global Carbon Budget 2023

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based f CO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8 ± 0.4 Gt C yr−1, and SLAND was 3.8 ± 0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023)

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests