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Abstract Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using ‘off-the-shelf’ products, such as allogeneic CAR natural killer T (^AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into^AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced^AlloCAR-NKT cells with high yield and purity. We generated^AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of^AlloCAR-NKT cells support their potential for clinical translation. 

Abstract The variability and predictability of tropical cyclone genesis frequency (TCGF) during 1973–2010 at both basinwide and sub-basin scales in the northwest Pacific are investigated using a 100-member ensemble of 60-km-resolution atmospheric simulations that are forced with observed sea surface temperatures (SSTs). The sub-basin regions include the South China Sea (SCS) and the four quadrants of the open ocean. The ensemble-mean results well reproduce the observed interannual-to-decadal variability of TCGF in the southeast (SE), northeast (NE), and northwest (NW) quadrants, but show limited skill in the SCS and the southwest (SW) quadrant. The skill in the SE and NE quadrants is responsible for the model’s ability to replicate the observed variability in basinwide TCGF. Above-normal TCGF is tied to enhanced relative SST (i.e., local SST minus tropical-mean SST) either locally or to the southeast of the corresponding regions in both the observations and ensemble mean for the SE, NE, and NW quadrants, but only in the ensemble mean for the SCS and the SW quadrant. These results demonstrate the strong SST control of TCGF in the SE, NE, and NW quadrants; both empirical and theoretical analyses suggest that ensembles of ∼10, 20, 35, and 15 members can capture the SST-forced TCGF variability in these three sub-basin regions and the entire basin, respectively. In the SW quadrant and the SCS, TCGF contains excessive noise, particularly in the observations, and thus shows low predictability. The variability and predictability of the large-scale atmospheric environment and synoptic-scale disturbances and their contributions to those of TCGF are also discussed. 

Abstract This study quantifies the contributions of tropical sea surface temperature (SST) variations during the boreal warm season to the interannual-to-decadal variability in tropical cyclone genesis frequency (TCGF) over the Northern Hemisphere ocean basins. The first seven leading modes of tropical SST variability are found to affect basinwide TCGF in one or more basins, and are related to canonical El Niño–Southern Oscillation (ENSO), global warming (GW), the Pacific meridional mode (PMM), Atlantic multidecadal oscillation (AMO), Pacific decadal oscillation (PDO), and the Atlantic meridional mode (AMM). These modes account for approximately 58%, 50%, and 56% of the variance in basinwide TCGF during 1969–2018 over the North Atlantic (NA), northeast Pacific (NEP), and northwest Pacific (NWP) Oceans, respectively. The SST effect is weak on TCGF variability in the north Indian Ocean. The SST modes dominating TCGF variability differ among the basins: ENSO, the AMO, AMM, and GW are dominant for the NA; ENSO and the AMO for the NEP; and the PMM, interannual AMO, and GW for the NWP. A specific mode may have opposite effects on TCGF in different basins, particularly between the NA and NEP. Sliding-window multiple linear regression analyses show that the SST effects on basinwide TCGF are stable in time in the NA and NWP, but have strengthened since the 1990s in the NEP. The SST effects on local TC genesis and occurrence frequency are also explored, and the underlying physical mechanisms are examined by diagnosing a genesis potential index and its components. 

The operation and maintenance of infrastructure components and systems can be modeled as a Markov process, partially or fully observable. Information about the current condition can be summarized by the “inner” state of a finite state controller. When a control policy is assigned, the stochastic evolution of the system is completely described by a Markov transition function. This article applies finite state Markov chain analyses to identify relevant features of the time evolution of a controlled system. We focus on assessing if some critical conditions are reachable (or if some actions will ever be taken), in identifying the probability of these critical events occurring within a time period, their expected time of occurrence, their long-term frequency, and the probability that some events occur before others. We present analytical methods based on linear algebra to address these questions, discuss their computational complexity and the structure of the solution. The analyses can be performed after a policy is selected for a Markov decision process (MDP) or a partially observable MDP. Their outcomes depend on the selected policy and examining these outcomes can provide the decision makers with deeper understanding of the consequences of following that policy, and may also suggest revising it.