Explore the vast range of titles available.

The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization, and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large-scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral resolution equivalent roughly to 2.8∘) and ocean (nominally 1∘) general circulation models, a sea-ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada.

The electrocardiogram (ECG) is a valuable tool for the diagnosis of myocardial ischemia as it presents distinctive ischemic patterns. Deep learning methods such as convolutional neural networks (CNN) are employed to extract data-derived features and to recognize natural patterns. Hence, CNN enable an unbiased view on well-known clinical phenomenon, e.g., myocardial ischemia. This study tested a novel, hypothesis-generating approach using pre-trained CNN to determine the optimal ischemic parameter as obtained from the highly susceptible intracoronary ECG (icECG). This was a retrospective observational study in 228 patients with chronic coronary syndrome. Each patient had participated in clinical trials with icECG recording and ST-segment shift measurement at the beginning (i.e., non-ischemic) and the end (i.e., ischemic) of a one-minute proximal coronary artery balloon occlusion establishing the reference. Using these data (893 icECGs in total), two pre-trained, open-access CNN (GoogLeNet/ResNet101) were trained to recognize ischemia. The best performing CNN during training were compared with the icECG ST-segment shift for diagnostic accuracy in the detection of artificially induced myocardial ischemia. Using coronary patency or occlusion as reference for absent or present myocardial ischemia, receiver-operating-characteristics (ROC)-analysis of manually obtained icECG ST-segment shift (mV) showed an area under the ROC-curve (AUC) of 0.903±0.043 (p<0.0001, sensitivity 80%, specificity 92% at a cut-off of 0.279mV). The best performing CNN showed an AUC of 0.924 (sensitivity 93%, specificity 92%). DeLong-Test of the ROC-curves showed no significant difference between the AUCs. The underlying morphology responsible for the network prediction differed between the trained networks but was focused on the ST-segment and the T-wave for myocardial ischemia detection. When tested in an experimental setting with artificially induced coronary artery occlusion, quantitative icECG ST-segment shift and CNN using pathophysiologic prediction criteria detect myocardial ischemia with similarly high accuracy.

Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well suited to address these complex and emerging global change problems but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v.1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here, we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container, and AMBER are freely available for community use.

Paclitaxel is a powerful chemotherapeutic drug, used for the treatment of many cancer types, including esophageal adenocarcinomas (EAC). Autophagy is a lysosome-dependent degradation process maintaining cellular homeostasis. Defective autophagy has been implicated in cancer biology and therapy resistance. We aimed to assess the impact of autophagy on chemotherapy response in EAC, with a special focus on paclitaxel. Responsiveness of EAC cell lines, OE19, FLO-1, OE33 and SK-GT-4, to paclitaxel was assessed using Alamar Blue assays. Autophagic flux upon paclitaxel treatment in vitro was assessed by immunoblotting of LC3B-II and quantitative assessment of WIP1 mRNA. Immunohistochemistry for the autophagy markers LC3B and p62 was applied on tumor tissue from 149 EAC patients treated with neoadjuvant chemotherapy, including pre- and post-therapeutic samples (62 matched pairs). Tumor response was assessed by histology. For comparison, previously published data on 114 primary resected EAC cases were used. EAC cell lines displayed differing responsiveness to paclitaxel treatment; however this was not associated with differential autophagy regulation. High p62 cytoplasmic expression on its own (p ≤ 0.001), or in combination with low LC3B (p = 0.034), was associated with nonresponse to chemotherapy, regardless of whether or not the regiments contained paclitaxel, but there was no independent prognostic value of LC3B or p62 expression patterns for EAC after neoadjuvant treatment. p62 and related pathways, most likely other than autophagy, play a role in chemotherapeutic response in EAC in a clinical setting. Therefore p62 could be a novel therapeutic target to overcome chemoresistance in EAC.

Recently, a new method has been introduced to study ion-molecule reactions at very low collision energies, down to below k B ⋅ 1 K (Allmendinger et al 2016 ChemPhysChem 17 3596). To eliminate the acceleration of the ions by stray electric fields in the reaction volume, the reactions are observed within the orbit of a Rydberg electron with large principal quantum number n > 20. This electron is assumed not to influence the reaction taking place between the ion core and the neutral molecules. This assumption is tested here with the example of the He( n ) + CO → C( n ′) + O + He reaction, which is expected to be equivalent to the He + + CO → C + + O + He reaction, using a merged-beam approach enabling measurements of relative reaction rates for collision energies E coll in the range from 0 to about k B ⋅ 25 K with a collision-energy resolution of ∼ k B ⋅ 200 mK at E coll = 0. In contrast to the other ion-molecule reactions studied so far with this method, the atomic ion product (C + ) is in its electronic ground state and does not have rotational and vibrational degrees of freedom so that the corresponding Rydberg product [C( n ′)] cannot decay by autoionization. Consequently, one can investigate whether the principal quantum number is effectively conserved, as would be expected in the spectator Rydberg-electron model. We measure the distribution of principal quantum numbers of the reactant He( n ) and product C( n ′) Rydberg atoms by pulsed-field ionization following initial preparation of He( n ) in states with n values between 30 and 45 and observe that the principal quantum number of the Rydberg electron is conserved during the reaction. This observation indicates that the Rydberg electron is not affected by the reaction, from which we can conclude that it does not affect the reaction either. This conclusion is strengthened by measurements of the collision-energy-dependent reaction yields at n = 30, 35 and 40, which exhibit the same behavior, i.e. a marked decrease below E coll ≈ k B ⋅ 5 K.

The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) is an open-source community model designed to address research questions that explore the role of the land surface in the global climate system. Here, we evaluate how well CLASSIC reproduces the energy, water, and carbon cycle when forced with quasi-observed meteorological data. Model skill scores summarize how well model output agrees with observation-based reference data across multiple statistical metrics. A lack of agreement may be due to deficiencies in the model, its forcing data, and/or reference data. To address uncertainties in the forcing, we evaluate an ensemble of CLASSIC runs that is based on three meteorological data sets. To account for observational uncertainty, we compute benchmark skill scores that quantify the level of agreement among independent reference data sets. The benchmark scores demonstrate what score values a model may realistically achieve given the uncertainties in the observations. Our results show that uncertainties associated with the forcing and observations are considerably large. For instance, for 10 out of 19 variables assessed in this study, the sign of the bias changes depending on what forcing and reference data are used. Benchmark scores are much lower than expected, implying large observational uncertainties. Model and benchmark score values are mostly similar, indicating that CLASSIC performs well when considering observational uncertainty. Future model development should address (i) a positive albedo bias and resulting shortwave radiation bias in parts of the Northern Hemisphere (NH) extratropics and Tibetan Plateau, (ii) an out-of-phase seasonal gross primary productivity cycle in the humid tropics of South America and Africa, (iii) a lacking spatial correlation of annual mean net ecosystem exchange with site-level measurements, (iv) an underestimation of fractional area burned and corresponding emissions in the boreal forests, (v) a negative soil organic carbon bias in high latitudes, and (vi) a time lag in seasonal leaf area index maxima in parts of the NH extratropics. Our results will serve as a baseline for guiding and monitoring future CLASSIC development.

Climate-related disasters in Bolivia are frequent, severe, and manifold and affect large parts of the population, economy, and ecosystems. Potentially amplified through climate change, natural hazards are of growing concern. To better understand these events, homogenized daily observations of temperature (29 stations) and precipitation (68 stations) from 1960 to 2009 were analyzed in this study. The impact of the positive (+) and negative (−) phases of the three climate modes (i) Pacific decadal oscillation (PDO), (ii) El Niño–Southern Oscillation (ENSO) with El Niño (EN) and La Niña (LN) events, and (iii) Antarctic Oscillation (AAO) were assessed. Temperatures were found to be higher during PDO(+), EN, and AAO(+) in the Andes. Total amounts of rainfall, as well as the number of extreme events, were higher during PDO(+), EN, and LN in the lowlands. During austral summer [December–February (DJF)], EN led to drier conditions in the Andes with more variable precipitation. Temperatures increased at a rate of 0.1°C per decade, with stronger increases in the Andes and in the dry season. Rainfall totals increased from 1965 to 1984 [12% in DJF and 18% in June–August (JJA)] and decreased afterward (−4% in DJF and −10% in JJA), following roughly the pattern of PDO. Trends of climate extremes generally corresponded to trends of climate means. Findings suggest that Bolivia’s climate will be warmer and drier than average in the near-term future. Having entered PDO(−) in 2007, droughts and LN-related floods can be expected in the lowlands, while increasing temperatures suggest higher risks of drought in the Andes.

The Global Carbon Project estimates that the terrestrial biosphere has absorbed about one‐third of anthropogenic CO2 emissions during the 1959–2019 period. This sink‐estimate is produced by an ensemble of terrestrial biosphere models and is consistent with the land uptake inferred from the residual of emissions and ocean uptake. The purpose of our study is to understand how well terrestrial biosphere models reproduce the processes that drive the terrestrial carbon sink. One challenge is to decide what level of agreement between model output and observation‐based reference data is adequate considering that reference data are prone to uncertainties. To define such a level of agreement, we compute benchmark scores that quantify the similarity between independently derived reference data sets using multiple statistical metrics. Models are considered to perform well if their model scores reach benchmark scores. Our results show that reference data can differ considerably, causing benchmark scores to be low. Model scores are often of similar magnitude as benchmark scores, implying that model performance is reasonable given how different reference data are. While model performance is encouraging, ample potential for improvements remains, including a reduction in a positive leaf area index bias, improved representations of processes that govern soil organic carbon in high latitudes, and an assessment of causes that drive the inter‐model spread of gross primary productivity in boreal regions and humid tropics. The success of future model development will increasingly depend on our capacity to reduce and account for observational uncertainties. Plain Language Summary Earth's natural vegetation absorbs about one‐third of CO2 emissions caused by human activities. This value is produced by a group of models rather than through direct observations. Our study assesses how well models reproduce the processes that drive the CO2 exchange between land and atmosphere using a wide range of data sets that are mainly derived from field measurements and satellite images. These reference data sets are prone to errors that are not quantified in a consistent manner. To account for such errors, we first compare different reference data sets against each other. We then compare model output against reference data and assess whether the differences are comparable to the differences among the reference data sets. We conclude that the performance of models is encouraging given how uncertain reference data are, but that ample potential for improvements remains. Key Points Differences between model and observations are often similar compared to differences between independently derived observation‐based data We quantify differences between independently derived observations to disentangle model deficiencies from observational uncertainties Future work should address biases in soil organic carbon, leaf area index, and the large spread of gross primary productivity among models

Extratropical cyclones (ETCs) are known to intensify due to three vertically interacting positive potential vorticity perturbations that are associated with potential temperature anomalies close to the surface (θB ), condensational heating in the lower-level atmosphere (q sat), and stratospheric intrusion in the upper-level atmosphere (q tr). This study presents the first climatological assessment of how much each of these three mechanisms contributes to the intensity of extreme ETCs. Using relative vorticity at 850 hPa as a measure of ETC intensity, results show that in about half of all cases the largest contributions during maximum ETC intensity are associated with q sat (53% of all ETCs), followed by q tr (36%) and θB (11%). The relative frequency of storms that are dominated by q sat is higher 1) during warmer months (61% of all ETCs during warmer months) compared to colder months (50%) and 2) in the Pacific (56% of all ETCs in the Pacific) compared to the Atlantic (46%). The relative frequency of ETCs that are dominated by θB is larger 1) during colder months (13%) compared to warmer months (3%), 2) in the Atlantic (15%) compared to the Pacific (8%), and 3) in western (11%–20%) compared to eastern ocean basins (4%–9%). These findings are based on piecewise potential vorticity inversion conducted for intense ETCs that occurred from 1980 to 2016 in the Northern Hemisphere (3273 events; top 7%). The results may serve as a baseline for evaluating ETC biases and uncertainties in global climate models.

[This corrects the article DOI: 10.1371/journal.pone.0197610.].[This corrects the article DOI: 10.1371/journal.pone.0197610.].