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Fractional flow reserve (FFR) measurements are recommended for assessing hemodynamic coronary stenosis severity. Intracoronary ECG (icECG) is easily obtainable and highly sensitive in detecting myocardial ischemia due to its close vicinity to the myocardium. We hypothesized that the remission time of myocardial ischemia on icECG after a controlled coronary occlusion accurately detects hemodynamically relevant coronary stenosis. This retrospective, observational study included patients with chronic coronary syndrome undergoing hemodynamic coronary stenosis assessment immediately following a strictly 1-min proximal coronary artery balloon occlusion with simultaneous icECG recording. icECG was used for a beat-to-beat analysis of the ST-segment shift during reactive hyperemia immediately following balloon deflation. The time from coronary balloon deflation until the ST-segment shift reached 37% of its maximum level, i.e., icECG ST-segment shift remission time (τ-icECG in seconds), was obtained by an automatic algorithm. τ-icECG was tested against the simultaneously obtained reactive hyperemia FFR at a threshold of 0.80 as a reference parameter. From 120 patients, 139 icECGs (age, 68 ± 10 yr old) were analyzed. Receiver operating characteristic (ROC) analysis of τ-icECG for the detection of hemodynamically relevant coronary stenosis at an FFR of ≤0.80 was performed. The area under the ROC curve was equal to 0.621 (P = 0.0363) at an optimal τ-icECG threshold of 8 s (sensitivity, 61%; specificity, 67%). τ-icECG correlated inversely and linearly with FFR (P = 0.0327). This first proof-of-concept study demonstrates that τ-icECG, a measure of icECG ST segment-shift remission after a 1-min coronary artery balloon occlusion accurately detects hemodynamically relevant coronary artery stenosis according to FFR at a threshold of ≥8 s. NEW & NOTEWORTHY: Invasive hemodynamic measurements are recommended by the current cardiology guidelines to guide percutaneous coronary interventions in the setting of chronic coronary syndrome. However, those pressure-derived indices demonstrate several theoretical and practical limitations. Thus, this study demonstrates the accuracy of a novel, pathophysiology-driven approach using intracoronary ECG for the identification of hemodynamically relevant coronary lesions by quantitatively assessing myocardial ischemia remission. [ABSTRACT FROM AUTHOR]

Terrestrial biosphere models are a key tool in investigating the role played by land surface in the global climate system. However, few models simulate the geographic distribution of biomes dynamically, opting instead to prescribe them using remote sensing products. While prescribing land cover still allows for the simulation of the impacts of climate change on vegetation growth and the impacts of land use change, it prevents the simulation of climate-change-driven biome shifts, with implications for the projection of future terrestrial carbon sink. Here, we isolate the impacts of prescribed vs. dynamic land cover implementations in a terrestrial biosphere model. We first introduce a new framework for evaluating dynamic land cover (i.e., the spatial distribution of plant functional types across the land surface), which can be applied across terrestrial biosphere models alongside standard benchmarking of energy, water, and carbon cycle variables in model intercomparison projects. After validating simulated land cover, we then show that the simulated terrestrial carbon sink differs significantly between simulations with dynamic vs. prescribed land cover for a high-CO 2 future scenario. This is because of important range shifts that are only simulated when dynamic land cover is implemented: tree expansion into the Arctic and Amazonian transition from forest to grassland. In particular, the projected change in net land–atmosphere CO 2 flux at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover. Our results illustrate the importance of climate-change-driven biome shifts for projecting future terrestrial carbon sink. [ABSTRACT FROM AUTHOR]

Terrestrial biosphere models are a key tool in investigating the role played by the land surface in the global climate system. However, few models simulate the geographic distribution of biomes dynamically, opting to prescribe them instead using remote sensing products. While prescribing land cover still allows for the simulation of the impacts of climate change on vegetation growth as well as the impacts of land use change, it prevents the simulation of climate change-driven biome shifts, with implications for projecting the future terrestrial carbon sink. Here, we isolate the impacts of prescribed vs. dynamic land cover implementations in a terrestrial biosphere model. We first introduce a framework for evaluating dynamic land cover (i.e., the spatial distribution of plant functional types across the land surface), which can be applied across terrestrial biosphere models alongside standard benchmarking of energy, water, and carbon cycle variables. After establishing confidence in simulated land cover, we then show that the simulated terrestrial carbon sink differs significantly between simulations with dynamic vs. prescribed land cover for a high CO2 future scenario. This is because of important range shifts that are only simulated when dynamic land cover is implemented: tree expansion into the Arctic and Amazonian transition from forest to grassland. In particular, the projected net land-atmosphere CO2 flux at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover. Our results illustrate the importance of climate change-driven biome shifts for projecting the future terrestrial carbon sink. [ABSTRACT FROM AUTHOR]