Current state and next-generation CAR-T cells in multiple myeloma.

Chimeric antigen receptor T cells (CAR-T cells) have emerged as a potentially transformative new approach to treating hematological malignancies. Ide-cel, an autologous B cell maturation antigen (BCMA) targeting CAR-T cells, has recently been approved to treat multiple myeloma (MM). Here, we review the main clinical trials of CAR-T cells in MM with the most advanced autologous BCMA-directed ide-cel and cilta-cel, the human CARs orva-cel and CT053, the alternative manufacturing process with P-BCMA-101 and bb21217, the dual CAR GC012F and the allogenic BCMA-directed CAR-T cells ALLO-715. In light of those clinical data, we provide an overview of CAR-T cells' main potential resistance mechanisms, including antigen loss, antigen spreading, anti-CAR antibodies, CAR-T cell exhaustion, and the emergence of a non-permissive microenvironment. Finally, we describe the principal area of research to build the next generation of CAR-T cells, with armored-, gated- or commuting-CARs, CARs associated with knock out of specific genes, and CAR-T cells made from γδT cells or NK cells.

Impact of equatorial Atlantic variability on ENSO predictive skill.

El Niño-Southern Oscillation (ENSO) is a key mode of climate variability with worldwide climate impacts. Recent studies have highlighted the impact of other tropical oceans on its variability. In particular, observations have demonstrated that summer Atlantic Niños (Niñas) favor the development of Pacific Niñas (Niños) the following winter, but it is unclear how well climate models capture this teleconnection and its role in defining the seasonal predictive skill of ENSO. Here we use an ensemble of seasonal forecast systems to demonstrate that a better representation of equatorial Atlantic variability in summer and its lagged teleconnection mechanism with the Pacific relates to enhanced predictive capacity of autumn/winter ENSO. An additional sensitivity study further shows that correcting SST variability in equatorial Atlantic improves different aspects of forecast skill in the Tropical Pacific, boosting ENSO skill. This study thus emphasizes that new efforts to improve the representation of equatorial Atlantic variability, a region with long standing systematic model biases, can foster predictive skill in the region, the Tropical Pacific and beyond, through the global impacts of ENSO.

Sensitivity of winter North Atlantic-European climate to resolved atmosphere and ocean dynamics.

Northern Hemisphere western boundary currents, like the Gulf Stream, are key regions for cyclogenesis affecting large-scale atmospheric circulation. Recent observations and model simulations with high-temporal and -spatial resolution have provided evidence that the associated ocean fronts locally affect troposphere dynamics. A coherent view of how this affects the mean climate and its variability is, however, lacking. In particular the separate role of resolved ocean and atmosphere dynamics in shaping the atmospheric circulation is still largely unknown. Here we demonstrate for the first time, by using coupled seasonal forecast experiments at different resolutions, that resolving meso-scale oceanic variability in the Gulf Stream region strongly affects mid-latitude interannual atmospheric variability, including the North Atlantic Oscillation. Its impact on climatology, however, is minor. Increasing atmosphere resolution to meso-scale, on the other hand, strongly affects mean climate but moderately its variability. We also find that regional predictability relies on adequately resolving small-scale atmospheric processes, while resolving small-scale oceanic processes acts as an unpredictable source of noise, except for the North Atlantic storm-track where the forcing of the atmosphere translates into skillful predictions.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.