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Sepsis claims an estimated 30 million episodes and 6 million deaths per year, and treatment options are rather limited. Human neutrophil peptides 1-3 (HNP1-3) are the most abundant neutrophil granule proteins but their neutrophil content varies because of unusually extensive gene copy number polymorphism. A genetic association study found that increased copy number of the HNP-encoding gene DEFA1/DEFA3 is a risk factor for organ dysfunction during sepsis development. However, direct experimental evidence demonstrating that these risk alleles are pathogenic for sepsis is lacking because the genes are present only in some primates and humans. Here, we generate DEFA1/DEFA3 transgenic mice with neutrophil-specific expression of the peptides. We show that mice with high copy number of DEFA1/DEFA3 genes have more severe sepsis-related vital organ damage and mortality than mice with low copy number of DEFA1/DEFA3 or wild-type mice, resulting from more severe endothelial barrier dysfunction and endothelial cell pyroptosis after sepsis challenge. Mechanistically, HNP-1 induces endothelial cell pyroptosis via P2X7 receptor-mediating canonical caspase-1 activation in a NLRP3 inflammasome-dependent manner. Based on these findings, we engineered a monoclonal antibody against HNP-1 to block the interaction with P2X7 and found that the blocking antibody protected mice carrying high copy number of DEFA1/DEFA3 from lethal sepsis. We thus demonstrate that DEFA1/DEFA3 copy number variation strongly modulates sepsis development in vivo and explore a paradigm for the precision treatment of sepsis tailored by individual genetic information.

Temperature is the principal driver of global atmospheric formaldehyde (HCHO) and its primary oxidation precursor biogenic volatile organic compounds (BVOCs). We revisit such a temperature (T‐) dependency globally, leveraging TROPOMI HCHO column data. We find substantial variations in the T‐dependency of biogenic HCHO across plant functional types (PFTs), with the highest over Broadleaf Evergreen Tropical Trees (doubling every 6.0 K ± 4.1 K) and lowest over Arctic C3 Grass (doubling every 30.8 K ± 9.6 K). The GEOS‐Chem model interprets HCHO columns' T‐dependency at the PFT level (r = 0.87), with a 16% discrepancy on average. The discrepancy can be explained by BVOC emissions T‐dependency for Broadleaf Evergreen Tropical Trees and Warm C4 Grass and can be attributed to the insensitivity of HCHO columns to BVOC emissions for other PFTs. Our findings underscore a potentially magnified variation of BVOC emissions by GEOS‐Chem and MEGAN therein, particularly in regions experiencing greater temperature variations. Plain Language Summary: We use remote sensing data from an up‐to‐date monitor to examine the temperature (T‐) dependency of biogenic formaldehyde (HCHO), a proxy of a series of volatile organic gases released by plants, in a global manner. We find that the effect of temperature on HCHO varies significantly between different types of plants, with tropical evergreen trees showing the most sensitivity to temperature and Arctic grasses showing the least. The GEOS‐Chem, a state‐of‐the‐art chemical transport model, interprets such temperature sensitivity among plants with nonnegligible discrepancies. The sensitivity of volatile organic gases released by plants to temperature explains the sensitivity of HCHO to temperature for some plants, such as tropical evergreen trees and warm‐season grasses. Key Points: Temperature (T‐) dependency of biogenic HCHO columns varies substantially across plant functional types (PFTs)The GEOS‐Chem model with the MEGAN module implemented primarily interprets the T‐dependency of HCHO columns at the PFT levelThe T‐dependency of biogenic volatile organic compound (BVOC) emissions mainly accounts for that of HCHO columns in Broadleaf Evergreen Tropical Trees and Warm C4 Grass regions [ABSTRACT FROM AUTHOR]

The frequency, intensity, and duration of extreme heatwaves are projected to increase in the global context of climate change. However, evidence of how anthropogenic emissions respond to heatwaves and further impact air quality remains elusive. Here, we use satellite remote sensing measurements alongside chemical transport model simulations to reveal abrupt variations in primary and secondary air pollutants introduced by extreme heatwaves. We highlight evidence from China and India, where satellite sulfur dioxide (SO2) and nitrogen dioxide (NO2) columns over thermal power plants enhance consistently responding to heatwaves. We attribute such spiked emissions to soaring electricity use and demonstrate that bottom‐up inventories underestimate the emissions from the power sector by 34.9% for the selected case. Elevated emissions facilitate fine particulate matter (PM2.5) and ozone (O3) formation over thermal power plants in an inhomogeneous manner, due to the combined effect of atmospheric oxidizing capacity, thermal decomposition of peroxyacetyl nitrate, planetary boundary layer rise, and air stagnation. Our results underscore the emerging challenge of pollution control attributable to the increasing climate penalty and the necessity of targeted control strategies and alternative energy sources during heatwaves. Plain Language Summary: Heatwaves are associated with high ambient temperatures and adverse health outcomes, but how anthropogenic emissions of atmospheric pollutants respond to heatwaves remains less explored. Here, we provide evidence from space for the first time that sulfur dioxide (SO2) and nitrogen dioxide (NO2) over thermal power plants enhance consistently responding to heatwaves. We attribute such spiked emissions to soaring electricity use, a feedback previously overlooked by state‐of‐the‐art emission inventories. The enhanced emissions increase levels of fine particulate matter (PM2.5) and surface ozone (O3) in an inhomogeneous manner during heatwaves due to the combined effect of chemistry and meteorology. Key Points: We detect enhanced SO2 and NO2 columns over power plants during heatwavesWe provide evidence of increasing electricity use and emissions in the power sectorElevated precursor emissions facilitate PM2.5 and O3 formation in an inhomogeneous manner under the combined effect of chemistry and meteorology [ABSTRACT FROM AUTHOR]

Binding of different ligands to glucocorticoid receptor (GR) may induce different conformational changes and even trigger completely opposite biological functions. To understand the allosteric communication within the GR ligand binding domain, the folding pathway of helix 12 (H12) induced by the binding of the agonist dexamethasone (DEX), antagonist RU486, and modulator AZD9567 are explored by molecular dynamics simulations and Markov state model analysis. The ligands can regulate the volume of the activation function‐2 through the residues Phe737 and Gln738. Without ligand or with agonist binding, H12 swings from inward to outward to visit different folding positions. However, the binding of RU486 or AZD9567 perturbs the structural state, and the passive antagonist state appears more stable. Structure‐based virtual screening and in vitro bioassays are used to discover novel GR ligands that bias the conformation equilibria toward the passive antagonist state. HP‐19 exhibits the best anti‐inflammatory activity (IC50 = 0.041 ± 0.011 µm) in nuclear factor‐kappa B signaling pathway, which is comparable to that of DEX. HP‐19 also does not induce adverse effect‐related transactivation functions of GR. The novel ligands discovered here may serve as promising starting points for the development of GR modulators. [ABSTRACT FROM AUTHOR]