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Successful cancer immunotherapy entails activation of innate immune receptors to promote dendritic cell (DC) maturation, antigen presentation, up-regulation of costimulatory molecules, and cytokine secretion, leading to activation of tumor antigen-specific cytotoxic T lymphocytes (CTLs). Here we screened a synthetic library of 100,000 compounds for innate immune activators using TNF production by THP-1 cells as a readout. We identified and optimized a potent human and mouse Toll-like receptor (TLR)1/TLR2 agonist, Diprovocim, which exhibited an EC50 of 110 pM in human THP-1 cells and 1.3 nM in primary mouse peritoneal macrophages. In mice, Diprovocim-adjuvanted ovalbumin immunization promoted antigen-specific humoral and CTL responses and synergized with anti–PD-L1 treatment to inhibit tumor growth, generating long-term antitumor memory, curing or prolonging survival of mice engrafted with the murine melanoma B16-OVA. Diprovocim induced greater frequencies of tumor-infiltrating leukocytes than alum, of which CD8 T cells were necessary for the antitumor effect of immunization plus anti–PD-L1 treatment.

Structurally disparate molecules reportedly engage and activate Toll-like receptor (TLR) 4 and other TLRs, yet the interactions that mediate binding and activation by dissimilar ligands remain unknown. We describe Neoseptins, chemically synthesized peptidomimetics that bear no structural similarity to the established TLR4 ligand, lipopolysaccharide (LPS), but productively engage the mouse TLR4 (mTLR4)/myeloid differentiation factor 2 (MD-2) complex. Neoseptin-3 activates mTLR4/MD-2 independently of CD14 and triggers canonical myeloid differentiation primary response gene 88 (MyD88)- and Toll-interleukin 1 receptor (TIR) domain-containing adaptor inducing IFN-beta (TRIF)- dependent signaling. The crystal structure mTLR4/MD-2/Neoseptin-3 at 2.57-Å resolution reveals that Neoseptin-3 binds as an asymmetrical dimer within the hydrophobic pocket of MD-2, inducing an active receptor complex similar to that induced by lipid A. However, Neoseptin-3 and lipid A form dissimilar molecular contacts to achieve receptor activation; hence strong TLR4/MD-2 agonists need not mimic LPS.

Though tropical cyclone (TC) models have been routinely evaluated against track and intensity observations, little work has been performed to validate modeled TC wind fields over land. In this paper, we present a simple framework for evaluating simulated low‐level inland winds with in‐situ observations and existing TC structure theory. The Automated Surface Observing Systems, Florida Coastal Monitoring Program, and best track data are used to generate a theory‐predicted wind profile that reasonably represents the observed radial distribution of TC wind speeds. We quantitatively and qualitatively evaluated the modeled inland TC wind fields, and described the model performance with a set of simple indicators. The framework was used to examine the performance of a high‐resolution two‐way nested Geophysical Fluid Dynamics Laboratory model on recent U.S. landfalling TCs. Results demonstrate the capacity of using this framework to assess the modeled TC low‐level wind field in the absence of dense inland observations. Plain Language Summary Some of the biggest human impacts of tropical cyclone (TC) winds come after the TC makes landfall. A skillful prediction of the radial distribution of winds is essential for forecasting TC‐induced inland hazards. However, the forecast skill of numerical hurricane models on inland TC wind fields has rarely been evaluated since it is challenging to collect wind observations during landfall, and the network of regular weather observations is too spread out to capture the strongest winds associated with a TC. This inhibits the improvement of forecast models and limits our understanding of the TC's inland evolution. Our work combines available inland in‐situ wind observations over the southeastern U.S. with existing TC structure theory, and presents a new “optimal” estimate of the post‐landfall winds. Our framework is found to be useful for evaluating the post‐landfall TC winds in hurricane forecast models. In addition, the new evaluation technique can intuitively demonstrate how well the model simulates TC intensity and structure. Key Points We introduce a new framework for evaluating modeled inland tropical cyclone (TC) wind fields with observation‐based, theory‐predicted wind profiles The theory‐predicted wind profile well represents the observed radial distribution of inland TC wind speeds We propose simple indicators to summarize the model performance on inland wind field predictions

We present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms. Plain Language Summary At many weather forecasting centers where computer weather models are run, different models are run for different applications. However, each separate model multiplies the effort needed to maintain and upgrade each model and makes it difficult to move improvements between models. We present a new “unified” weather modeling system, System for High‐resolution prediction on Earth‐to‐Local Domains, able to be configured for a variety of applications. This system uses a powerful computer code, FV3, to compute the fluid motion of the atmosphere at any scale and also able to zoom in on areas of interest to better “see” severe storms or intense hurricanes. We show how we started from a quickly assembled model for testing FV3 and then gradually improved the representation of different atmospheric processes and expanded into new uses for the system, including short‐range severe thunderstorm prediction, hurricane forecasting, and forecasts out to as long as 6 weeks. We address some of the challenges that we faced and discuss prospects for future model improvements. Since many of the parts of System for High‐resolution prediction on Earth‐to‐Local Domains are used by models being developed by the National Weather Service for use by weather forecasters, the advances described here can be rapidly introduced into those models, eventually improving official forecasts. Key Points A unified “one code, one executable, one workflow” global prediction modeling system is presented SHiELD's multiple configurations show prediction skill and simulation fidelity matching or exceeding those of existing U.S. models The FV3 Dynamical Core provides a powerful foundation for unified prediction modeling

We describe the third version of the Geophysical Fluid Dynamics Laboratory cloud microphysics scheme (GFDL MP v3) implemented in the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD). Compared to the GFDL MP v2, the GFDL MP v3 is entirely reorganized, optimized, and modularized into functions. The particle size distribution (PSD) of all hydrometeor categories is redefined to better mimic observations, and the cloud droplet number concentration (CDNC) is calculated from the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA2) aerosol data. In addition, the GFDL MP has been redesigned so all processes use the redefined PSD to ensure overall consistency and easily permit the introduction of new PSDs and microphysical processes. A year's worth of global 13‐km, 10‐day weather forecasts were performed with the new GFDL MP. Compared to the GFDL MP v2, the GFDL MP v3 significantly improves SHiELD's predictions of geopotential height, air temperature, and specific humidity in the Troposphere, as well as the high, middle and total cloud fractions and the liquid water path. The predictions are improved even further by the use of reanalysis aerosol data to calculate CDNC, and also by using the more realistic PSD available in GFDL MP v3. However, the upgrade of the GFDL MP shows little impact on the precipitation prediction. Degradations caused by the new scheme are discussed and provide a guide for future GFDL MP development. Plain Language Summary Weather and climate models represent “microphysical” (MP) cloud and precipitation processes by assuming a certain distribution of particle sizes and then computing how the distributions affect transformations of one type of particle (cloud droplets, raindrops, ice crystals, snowflakes, etc.) into another. These schemes also assume the concentrations of the particulate matter (both naturally‐occurring and human‐made, such as soot, sulfate, dust, sea salt, etc.) onto which water condenses or ice freezes. One scheme that we use for global weather prediction, the Geophysical Fluid Dynamics Laboratory cloud microphysics scheme, has been recently upgraded to improve the consistency and realism of these processes, including more realistic cloud droplet size distributions, and use a more accurate time‐and‐space count of sulfate particles to calculate the number of cloud droplets. We find that this upgrade significantly improves global weather predictions, especially of the large‐scale weather patterns and their clouds and precipitation. Key Points The Geophysical Fluid Dynamics Laboratory (GFDL) cloud microphysics scheme (GFDL MP) has been thoroughly updated for better physical realism and consistency The upgraded GFDL MP significantly improves large‐scale weather prediction within the GFDL System for High‐resolution prediction on Earth‐to‐Local Domains model Changes to the particle size distributions and cloud droplet number concentrations show significant impacts on weather prediction

We introduce a 6.5‐km version of the Geophysical Fluid Dynamics Laboratory (GFDL)'s System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD). This global model is designed to bridge the gap between global medium‐range weather prediction and global storm‐resolving simulation while remaining practical for real‐time forecast. The 6.5‐km SHiELD represents a significant advancement over GFDL's flagship global forecast system, the 13‐km SHiELD. This global model features a holistically‐developed scale‐aware suite of physical parameterizations, stepping into the formidable convective “gray zone” of resolutions below 10 km. Comparative analyses with the 13‐km SHiELD, conducted over a 3‐year hindcast period, highlight noteworthy improvements across global‐scale, regional‐scale, tropical cyclone (TC), and continental convection predictions. In particular, the 6.5‐km SHiELD excels in predicting considerably finer‐scale convective systems associated with large‐scale frontal systems and extratropical cyclones. The predictions of global temperature, wind, cloud, and precipitation are significantly improved in this global model. Regionally, over the contiguous United States and the Maritime Continent, substantial reductions in prediction biases of precipitation, cloud cover, and wind fields are also found. In the mesoscale realm, the model demonstrates prominent improvements in global TC intensity and continental convective precipitation prediction: biases are relieved, and skill is higher. These findings affirm the superiority of the 6.5‐km SHiELD compared to the current 13‐km SHiELD, which will advance weather prediction by successfully addressing both synoptic weather systems and specific storm‐scale phenomena in the same global model. Plain Language Summary One commonly used strategy to improve a weather model's forecast skill is to increase its resolution, which requires additional computer resources and new dynamical and physical processes within the model to handle the smaller‐scale features that can then be represented. The Geophysical Fluid Dynamics Laboratory has developed a 13‐km System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD) for conventional global weather prediction, as well as a 3.25‐km eXperimental‐SHiELD (X‐SHiELD) for global storm‐resolving simulation. The 13‐km model is too coarse to represent some high‐impact weather systems, but the 3.25‐km model is too computationally expensive for regular use. This study focuses on developing a 6.5‐km version of SHiELD, designed as an intermediate‐resolution model to bridge the gap between global weather prediction and global storm‐resolving simulation, aiming to improve global weather prediction toward storm‐resolving scales. As the model's resolution enters the “gray zone,” typically defined as 10 km or below where thunderstorms are partially resolved, it necessitates adjustments to various physical parameterizations originally designed for coarser resolutions. Through a comprehensive evaluation of the model's prediction skill across global, regional, and mesoscale domains, we have noted significant improvements in global forecasting accuracy, regional weather predictions, tropical cyclone, and continental precipitation predictions. Key Points A 6.5‐km version of the SHiELD global prediction system has been developed at GFDL to improve predictions from global scales to mesoscale The 6.5‐km SHiELD exhibits significant improvements in global and regional medium‐range weather predictions over the previous 13‐km version The 6.5‐km SHiELD also demonstrates distinct improvements in predicting global tropical cyclones and continental convective precipitation

Ankle fractures are common musculoskeletal injuries that may result in tibiotalar joint dislocations. Ankle fracture-dislocations occur via similar mechanisms as ankle fractures, although the persistence or magnitude of the deforming force is sufficient to disrupt any remaining bony or soft-tissue stability. Ankle fracture-dislocations likely represent distinct clinical entities, as the pathology, management, and patient outcomes following these injuries differ from those seen in more common ankle fractures without dislocation. Ankle fracture-dislocations have higher rates of concomitant injury including open fractures, chondral lesions, and intra-articular loose bodies. Long-term outcomes in ankle fracture-dislocations are worse than ankle fractures without dislocation. Higher rates of posttraumatic osteoarthritis and chronic pain have also been reported. In this review, we discuss the current literature regarding the history, management, and outcomes of ankle-fracture dislocations and highlight the need for future study.

We present a new global‐to‐regional model, cfvGFS, able to explicitly (without parameterization) represent convection over part of the Earth. This model couples the Geophysical Fluid Dynamics Laboratory Finite‐Volume Cubed‐Sphere Dynamical Core (FV3) to the Global Forecast System physics and initial conditions, augmented with a six‐category microphysics and a modified planetary boundary layer scheme. We examine the characteristics of cfvGFS on a 3‐km continental U. S. domain nested within a 13‐km global model. The nested cfvGFS still has good hemispheric skill comparable to or better than the operational Global Forecast System, while supercell thunderstorms, squall lines, and derechos are explicitly represented over the refined region. In particular, cfvGFS has excellent representations of fine‐scale updraft helicity fields, an important proxy for severe weather forecasting. Precipitation biases are found to be smaller than in uniform‐resolution global models and competitive with operational regional models; the 3‐km domain also improves upon the global models in 2‐m temperature and humidity skill. We discuss further development of cfvGFS and the prospects for a unified global‐to‐regional prediction system. Key Points A global‐to‐regional refined atmosphere model is presented for simultaneous, skillful global and convective‐permitting predictions Springtime forecasts show precipitation skill equal to or better than operational global and regional models Models based on the Finite‐Volume Cubed‐Sphere Dynamical Core show great promise for unifying global and regional prediction systems

The impact of storm size on the forecast of tropical cyclone storm track and intensity is investigated using the 2016 version of the operational GFDL hurricane model. Evaluation was made for 1529 forecasts in the Atlantic, eastern Pacific, and western North Pacific basins, during the 2014 and 2015 seasons. The track and intensity errors were computed from forecasts in which the 34-kt (where 1 kt = 0.514 m s−1) wind radii obtained from the operational TC vitals that are used to initialize TCs in the GFDL model were replaced with wind radii estimates derived using an equally weighted average of six objective estimates. It was found that modifying the radius of 34-kt winds had a significant positive impact on the intensity forecasts in the 1–2 day lead times. For example, at 48 h, the intensity error was reduced 10%, 5%, and 4% in the Atlantic, eastern Pacific, and western North Pacific, respectively. The largest improvements in intensity forecasts were for those tropical cyclones undergoing rapid intensification, with a maximum error reduction in the 1–2 day forecast lead time of 14% and 17% in the eastern and western North Pacific, respectively. The large negative intensity biases in the eastern and western North Pacific were also reduced 25% and 75% in the 12–72-h forecast lead times. Although the overall impact on the average track error was neutral, forecasts of recurving storms were improved and tracks of nonrecurving storms degraded. Results also suggest that objective specification of storm size may impact intensity forecasts in other high-resolution numerical models, particularly for tropical cyclones entering a rapid intensification phase.

The posterior malleolar fragment is frequently involved in rotational ankle fractures, but diagnosis and definitive management remains controversial. Ankle fractures with a posterior malleolar component that are not identified and treated in a timely manner may contribute significantly to future comorbidities, including continued pain, instability, and the development of arthritis. This article highlights the anatomic features of posterior malleolar ankle fractures, the classification schemes used, and discusses the various nonsurgical and surgical methods currently used. Level of Evidence: Level V, expert opinion.