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Real‐time forecasted ice information for large lakes, such as the Great Lakes, is critical for essential operations, such as ice breaking, commercial navigation, search and rescue, and oil spill response. Existing forecast products for large lake ice conditions are not available for medium‐range time horizons (5–16 days out), yet they could provide important information for decision making, particularly for ice breaking and spill responses. In addition, ice forecasts for Earth's largest lakes at these timescales could be important for Medium‐Range Weather (MRW) forecasting. However, the skill of existing operational products in predicting ice conditions at MRW timescales has not been studied. This work aims to determine how well ice forecasts from a coupled large lake hydrodynamic‐ice model perform for MRW forecast horizons. Simulations were carried out for the 2022 Great Lakes ice season, using 8 different 16‐day forecast periods. Forecast results were compared to observations of meteorology and ice conditions from the U.S. National Ice Center. Results show the MRW ice forecasts in the Great Lakes outperform persistence‐based forecasts. These findings could inform the development or extension of lake operational ice forecasting and the potential of coupling between atmospheric and large lake models at medium‐range forecast time scales. Plain Language Summary: Ice information for large lakes is critical for essential operations, such as ice breaking, commercial navigation, search and rescue, and oil spill response. Ice forecasts are currently not available in the medium‐range (5–16 days out) time scale, yet they could provide valuable information for decision making. This information could also be important for medium‐range weather forecasts. The skill of existing Great Lakes ice forecast products at medium‐range time scales is currently unknown. Our work aims to determine how well ice forecasts from an atmosphere‐lake model perform for medium‐range time scales. Simulations were carried out for the 2022 Great Lakes ice season, using 8 different 16‐day forecast periods. The modeled forecasts were compared to observations from the National Ice Center and observed meteorological conditions. Results show that the modeled forecasts outperform persistence forecasts. These findings could inform the development or extension of ice forecasting and the potential of an atmosphere‐lake model at medium‐range time scales. Key Points: Medium‐range (5‐ to 16‐day) ice forecasts show utility in the Great LakesModel ice forecasts outperform ice persistence forecastsAir temperature bias in medium‐range weather forecasts is the likely greatest contributor to ice error [ABSTRACT FROM AUTHOR]

Currently, information regarding the influence of growth factors on the cytoskeleton, including G-CSF and GMCSF, remains limited. In the present study we show alterations in F-actin distribution and cell cycle progression in HL-60 promyelocytic leukemia cells, resulting from treatment with these cytokines in vitro. We found that both agents caused F-actin reorganization. Although multiple potential effects of various growth factors have been described previously, in our experimental conditions, we observed some rather subtle differences between the effects of G-CSF and GM-CSF on studied cells. The presence of these cytokines in the cell environment caused not only increased F-actin labeling in the cytoplasm, but also a weaker intensity of peripheral ring staining in comparison with control cells. In spite of the fact that HL60 cells exposed to G-CSF and GM-CSF contained different F-actin structures such as aggregates and F-actin network, the rate of actin polymerization was not significantly enhanced. Moreover, alterations were mainly related to considerable changes in the relative proportion of these different structures, what might be reflected by specific features of the differentiation process, with regard to the kind of stimulating factor used. Thus, reorganization of F-actin and other results obtained in our experimental conditions, might reflect unique characteristics of the differentiation process in HL-60 cells, involving low apoptosis frequency, the G1 to S phase transition in the cell cycle, as well as possible alternative ways of the cell death.

Clostridium difficile toxin B (TcdB) inactivates the small GTPases Rho, Rac and Cdc42 during intoxication of mammalian cells. In the current work, we show that TcdB has the potential to stimulate caspase-dependent and caspase-independent apoptosis. The apoptotic pathways became evident when caspase-3-processed-vimentin was detected in TcdB-treated HeLa cells. Caspase-3 activation was subsequently confirmed in TcdB-intoxicated HeLa cells. Interestingly, caspase inhibitor delayed TcdB-induced cell death, but did not alter the time-course of cytopathic effects. A similar effect was also observed in MCF-7 cells, which are deficient in caspase-3 activity. The time-course to cell death was almost identical between cells treated with TcdB plus caspase inhibitor and cells intoxicated with the TcdB enzymatic domain (TcdB1-556). Unlike TcdB treated cells, intoxication with TcdB1-556 or expression of TcdB1-556 in a transfected cell line, did not stimulate caspase-3 activation yet cells exhibited cytopathic effects and cell death. Although TcdB1-556 treated cells did not demonstrate caspase-3 activation these cells were apoptotic as determined by differential annexin-V/propidium iodide staining and nucleosomal DNA fragmentation. These data indicate TcdB triggers caspase-independent apoptosis as a result of substrate inactivation and may evoke caspase-dependent apoptosis due to a second, yet undefined, activity of TcdB. This is the first example of a bacterial virulence factor with the potential to stimulate multiple apoptotic pathways in host cells.