cGAS-STING signalling regulates microglial chemotaxis in genome instability.

Defective DNA damage signalling and repair is a hallmark of age-related and genetic neurodegenerative disease. One mechanism implicated in disease progression is DNA damage-driven neuroinflammation, which is largely mediated by tissue-resident immune cells, microglia. Here, we utilise human microglia-like cell models of persistent DNA damage and ATM kinase deficiency to investigate how genome instability shapes microglial function. We demonstrate that upon DNA damage the cytosolic DNA sensing cGAS-STING axis drives chronic inflammation and a robust chemokine response, exemplified by production of CCL5 and CXCL10. Transcriptomic analyses revealed that cell migratory pathways were highly enriched upon IFN-ß treatment of human iPSC-derived microglia, indicating that the chemokine response to DNA damage mirrors type I interferon signalling. Furthermore, we find that STING deletion leads to a defect in microglial chemotaxis under basal conditions and upon ATM kinase loss. Overall, this work provides mechanistic insights into cGAS-STING-dependent neuroinflammatory mechanisms and consequences of genome instability in the central nervous system.

Reversal of High Fat Diet-Induced Obesity, Systemic Inflammation, and Astrogliosis by the NLRP3 Inflammasome Inhibitors NT-0249 and NT-0796.

Systemic and cerebral inflammatory responses are implicated in the pathogenesis of obesity and associated metabolic impairment. While the NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome has been linked to obesity-associated inflammation, whether it contributes to the development or maintenance of obesity is unknown. We provide support for a direct role of saturated fatty acids, such as palmitic acid, as NLRP3 activating stimuli in obese states. To investigate whether NLRP3 activation contributes to the pathogenesis of diet-induced obesity (DIO) in mice, we tested two different clinical-stage NLRP3 inflammasome inhibitors. We demonstrate a contributory role of this key inflammasome to established obesity and associated systemic and cerebral inflammation. By comparing their effects to calorie restriction, we aimed to identify specific NLRP3-sensitive mechanisms contributing to obesity-induced inflammation (as opposed to be those regulated by weight loss per se). In addition, a direct comparison of an NLRP3 inhibitor to a glucagon like peptide-1 receptor agonist, semaglutide (Wegovy), in the DIO model allowed an appreciation of the relative efficacy of these two therapeutic strategies on obesity, its associated systemic inflammatory response, and cerebral gliosis. We show that two structurally distinct, NLRP3 inhibitors, NT-0249 and NT-0796, reverse obesity in the DIO mouse model and that brain exposure appears necessary for efficacy. In support of this, we show that DIO-driven hypothalamic glial fibrillary acidic protein expression is blocked by dosing with NT-0249/NT-0796. While matching weight loss driven by semaglutide or calorie restriction, remarkably, NLRP3 inhibition provided enhanced improvements in disease-relevant biomarkers of acute phase response, cardiovascular inflammation, and lipid metabolism. SIGNIFICANCE STATEMENT: Obesity is a global health concern that predisposes individuals to chronic disease such as diabetes and cardiovascular disease at least in part by promoting systemic inflammation. We report that in mice fed a high-fat, obesogenic diet, obesity is reversed by either of two inhibitors of the intracellular inflammatory mediator NLRP3. Furthermore, NLRP3 inhibition reduces both hypothalamic gliosis and circulating biomarkers of cardiovascular disease risk beyond what can be achieved by either the glucagon like peptide-1 agonist semaglutide or calorie restriction alone.

Alzheimer's disease-associated R47H TREM2 increases, but wild-type TREM2 decreases, microglial phagocytosis of synaptosomes and neuronal loss.

Triggering receptor on myeloid cells 2 (TREM2) is an innate immune receptor, upregulated on the surface of microglia associated with amyloid plaques in Alzheimer's disease (AD). Individuals heterozygous for the R47H variant of TREM2 have greatly increased risk of developing AD. We examined the effects of wild-type (WT), R47H and knock-out (KO) of human TREM2 expression in three microglial cell systems. Addition of mouse BV-2 microglia expressing R47H TREM2 to primary mouse neuronal cultures caused neuronal loss, not observed with WT TREM2. Neuronal loss was prevented by using annexin V to block exposed phosphatidylserine, an eat-me signal and ligand of TREM2, suggesting loss was mediated by microglial phagocytosis of neurons exposing phosphatidylserine. Addition of human CHME-3 microglia expressing R47H TREM2 to LUHMES neuronal-like cells also caused loss compared to WT TREM2. Expression of R47H TREM2 in BV-2 and CHME-3 microglia increased their uptake of phosphatidylserine-beads and synaptosomes versus WT TREM2. Human iPSC-derived microglia with heterozygous R47H TREM2 had increased phagocytosis of synaptosomes vs common-variant TREM2. Additionally, phosphatidylserine liposomes increased activation of human iPSC-derived microglia expressing homozygous R47H TREM2 versus common-variant TREM2. Finally, overexpression of TREM2 in CHME-3 microglia caused increased expression of cystatin F, a cysteine protease inhibitor, and knock-down of cystatin F increased CHME-3 uptake of phosphatidylserine-beads. Together, these data suggest that R47H TREM2 may increase AD risk by increasing phagocytosis of synapses and neurons via greater activation by phosphatidylserine and that WT TREM2 may decrease microglial phagocytosis of synapses and neurons via cystatin F.

Structural insight into allosteric modulation of protease-activated receptor 2.

Protease-activated receptors (PARs) are a family of G-protein-coupled receptors (GPCRs) that are irreversibly activated by proteolytic cleavage of the N terminus, which unmasks a tethered peptide ligand that binds and activates the transmembrane receptor domain, eliciting a cellular cascade in response to inflammatory signals and other stimuli. PARs are implicated in a wide range of diseases, such as cancer and inflammation. PARs have been the subject of major pharmaceutical research efforts but the discovery of small-molecule antagonists that effectively bind them has proved challenging. The only marketed drug targeting a PAR is vorapaxar, a selective antagonist of PAR1 used to prevent thrombosis. The structure of PAR1 in complex with vorapaxar has been reported previously. Despite sequence homology across the PAR isoforms, discovery of PAR2 antagonists has been less successful, although GB88 has been described as a weak antagonist. Here we report crystal structures of PAR2 in complex with two distinct antagonists and a blocking antibody. The antagonist AZ8838 binds in a fully occluded pocket near the extracellular surface. Functional and binding studies reveal that AZ8838 exhibits slow binding kinetics, which is an attractive feature for a PAR2 antagonist competing against a tethered ligand. Antagonist AZ3451 binds to a remote allosteric site outside the helical bundle. We propose that antagonist binding prevents structural rearrangements required for receptor activation and signalling. We also show that a blocking antibody antigen-binding fragment binds to the extracellular surface of PAR2, preventing access of the tethered ligand to the peptide-binding site. These structures provide a basis for the development of selective PAR2 antagonists for a range of therapeutic uses.

Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States.

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (RT ) in 85 large cities across the conterminous United States for the period 2001-2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and RT was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in RT mainly occurred in cities in relatively cold regions with an annual mean temperature <17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban-rural difference in both SOS and RT was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in RT magnitude in urban areas. These findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.

CD33M inhibits microglial phagocytosis, migration and proliferation, but the Alzheimer's disease-protective variant CD33m stimulates phagocytosis and proliferation, and inhibits adhesion.

CD33 is a Siglec (sialic acid-binding immunoglobulin-type lectin) receptor on microglia. Human CD33 can be alternatively spliced into two isoforms: the long isoform (CD33M) and a shorter isoform (CD33m) that lacks the sialic acid-binding site. CD33m appears to protect against Alzheimer's disease; however, it remains unclear how. To investigate potential mechanisms by which CD33m may confer protection, we expressed the CD33m and CD33M isoforms of human CD33 in mouse BV-2 and human CHME3 microglial cells and assessed microglia functions. In the BV-2 cells, CD33M inhibited microglial phagocytosis of beads, synapses, debris and dead cells, while CD33m increased phagocytosis of beads, debris and cells. RNAi knockdown of the endogenous mouse CD33 increased phagocytosis and prevented CD33m's (but not CD33M's) effect on phagocytosis. CD33M increased cell attachment but inhibited cell proliferation, while CD33m did the opposite. We also found that CD33M inhibited cell migration. In human CHME3 cells, CD33M increased cell attachment, but inhibited phagocytosis, proliferation and migration, whereas CD33m did the opposite. We conclude that CD33M inhibits microglial phagocytosis, inhibits migration and increases adhesion, while CD33m increases phagocytosis, proliferation and inhibits adhesion. Thus, CD33m might protect against Alzheimer's disease by increasing microglial proliferation, movement and phagocytosis of debris and dead cells.

Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere.

Satellite-derived sun-induced chlorophyll fluorescence (SIF) has been increasingly used for estimating gross primary production (GPP). However, the relationship between SIF and GPP has not been well defined, impeding the translation of satellite observed SIF to GPP. Previous studies have generally assumed a linear relationship between SIF and GPP at daily and longer time scales, but support for this assumption is lacking. Here, we used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH). Based on multiple SIF products and MODIS and FLUXCOM GPP data, we found strong seasonal hump-shaped patterns for the GPP/SIF ratio over northern latitudes, with higher values in the summer than in the spring or autumn. This hump-shaped GPP/SIF seasonal variation was confirmed by examining different SIF products and was evident for most vegetation types except evergreen broadleaf forests. The seasonal amplitude of the GPP/SIF ratio decreased from the boreal/arctic region to drylands and the tropics. For most of the NH, the lowest GPP/SIF values occurred in October or September, while the maximum GPP/SIF values were evident in June and July. The most pronounced seasonal amplitude of GPP/SIF occurred in intermediate temperature and precipitation ranges. GPP/SIF was positively related to temperature in the early and late parts of the growing season, but not during the peak growing months. These shifting relationships between temperature and GPP/SIF across different months appeared to play a key role in the seasonal dynamics of GPP/SIF. Several mechanisms may explain the patterns we observed, and future research encompassing a broad range of climate and vegetation settings is needed to improve our understanding of the spatial and temporal relationships between SIF and GPP. Nonetheless, the strong seasonal variation in GPP/SIF we identified highlights the importance of incorporating this behavior into SIF-based GPP estimations.

Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations.

Effective use of solar-induced chlorophyll fluorescence (SIF) to estimate and monitor gross primary production (GPP) in terrestrial ecosystems requires a comprehensive understanding and quantification of the relationship between SIF and GPP. To date, this understanding is incomplete and somewhat controversial in the literature. Here we derived the GPP/SIF ratio from multiple data sources as a diagnostic metric to explore its global-scale patterns of spatial variation and potential climatic dependence. We found that the growing season GPP/SIF ratio varied substantially across global land surfaces, with the highest ratios consistently found in boreal regions. Spatial variation in GPP/SIF was strongly modulated by climate variables. The most striking pattern was a consistent decrease in GPP/SIF from cold-and-wet climates to hot-and-dry climates. We propose that the reduction in GPP/SIF with decreasing moisture availability may be related to stomatal responses to aridity. Furthermore, we show that GPP/SIF can be empirically modeled from climate variables using a machine learning (random forest) framework, which can improve the modeling of ecosystem production and quantify its uncertainty in global terrestrial biosphere models. Our results point to the need for targeted field and experimental studies to better understand the patterns observed and to improve the modeling of the relationship between SIF and GPP over broad scales.

Characterization and preclinical evaluation of a protease activated receptor 2 (PAR2) monoclonal antibody as a preventive therapy for migraine.

AIM: Migraine pain is thought to result from activation of meningeal nociceptors that might involve dural mast cell degranulation and release of proteases and pronociceptive mediators. Tryptase, the most abundant dural mast cell protease, has been demonstrated to stimulate dural mast cells, as well as trigeminal nociceptors by activating the protease activated receptor 2. Mast cell or neuronal protease activated receptors 2 may therefore represent a novel target for migraine treatment. In this study, we characterized and evaluated a novel protease activated receptor 2 monoclonal antibody as a preventive anti-migraine pain therapy in preclinical models. METHODS: Flow cytometry, immunocytochemistry, calcium imaging, Homogeneous Time Resolved Technology (HTRF) epitope competition assay and serum pharmacokinetic (PK) assay in rats were performed to confirm the activity, specificity and in vivo stability of PAR650097, a novel anti- protease activated receptor 2 monoclonal antibody. In vivo assessment was performed in female C57BL/6J mice by evaluation of PAR650097 in preventing cutaneous allodynia elicited by (a) supradural injection of the protease activated receptor 2 agonist, Ser-Leu-Ile-Gly-Arg-Leu-amide trifluoroacetate (SLIGRL), or calcitonin gene-related (CGRP) peptide, and (b) induction of latent sensitization by priming with three daily episodes of restraint stress followed by challenge with a subthreshold inhalational exposure to umbellulone (UMB), a transient receptor potential ankyrin 1 (TRPA1) agonist. PAR650097 was administered as a pretreatment prior to the first restraint stress, umbellulone exposure, SLIGRL or calcitonin gene-related peptide injection. Additionally, fremanezumab, a calcitonin gene-related peptide antibody was administered as pre-treatment prior to supradural administration of calcitonin gene-related peptide or SLIGRL. RESULTS: In vitro, PAR650097 demonstrated rapid interaction with protease activated receptor 2, enabling it to fully inhibit protease-induced protease activated receptor 2 activation, in human and mouse cells, with high potency. Furthermore, PAR650097 was highly selective for protease activated receptor 2, demonstrating no affinity for protease activated receptor 1 protein and no functional effect on the activation of cellular protease activated receptor 1 with thrombin. In addition, PAR650097 had an acceptable PK profile, compatible with testing the effects of selective protease activated receptor 2 inhibition in vivo. In vivo, PAR650097 blocked cutaneous allodynia induced by either supradural SLIGRL or calcitonin gene-related peptide. Fremanezumab abolished cutaneous allodynia induced by supradural CGRP, and partially attenuated cutaneous allodynia induced by SLIGRL. Administration of PAR650097, before the first restraint stress episode, did not prevent the acute stress-induced cutaneous allodynia or restraint stress priming revealed by cutaneous allodynia induced by inhalational umbellulone. In contrast, PAR650097 prevented expression of cutaneous allodynia when given before the umbellulone challenge in restraint stress-primed animals. CONCLUSION: PAR650097 specifically inhibits endogenously expressed protease activated receptor 2 in human and mouse cells with high potency. This antibody has an acceptable PK profile in rodents and effectively blocked SLIGR-induced cutaneous allodynia. PAR650097 additionally prevented cutaneous allodynia induced by supradural calcitonin gene-related peptide, indicating that the protease activated receptor 2 receptor is a downstream consequence of calcitonin gene-related peptide actions. Fremanezumab effectively blocked calcitonin gene-related peptide-induced cutaneous allodynia and only partially reduced cutaneous allodynia induced by a protease activated receptor 2 activator, suggesting both calcitonin gene-related peptide-dependent and -independent mechanisms in promoting migraine pain. While PAR650097 did not prevent stress-induced cutaneous allodynia or priming, it effectively prevented cutaneous allodynia induced by a TRPA1 agonist in animals with latent sensitization. Activation of protease activated receptor 2, therefore, contributes to both calcitonin gene-related peptide-dependent and -independent mechanisms in promoting migraine-like pain. Therapeutic targeting of protease activated receptor 2 receptors may represent an anti-migraine pain strategy with a potentially broad efficacy profile.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change.

The future trajectory of atmospheric CO2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in-depth understanding of model sensitivities and uncertainties in non-steady-state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO2 enrichment. Here, we systematically assessed if a biogeochemical process-based model (3D-CMCC-CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest ageing and structuring as well as under climate change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 yr of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon and nitrogen pools early in forest simulation (i.e., for NPP up to ~37%, 256 g C·m-2 ·yr-1 and for SWB up to ~90%, 65 Mg C/ha, when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium to longer time scales, and under climate change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e., for NPP up to ~30%, 167 g C·m-2 ·yr-1 and for SWB up to ~24%, 64 Mg C/ha, when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate change (i.e., warming and changes in atmospheric CO2 concentration) itself although model sensitivities were generally higher under climate change scenarios. Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.

Informing climate models with rapid chamber measurements of forest carbon uptake.

Models predicting ecosystem carbon dioxide (CO2 ) exchange under future climate change rely on relatively few real-world tests of their assumptions and outputs. Here, we demonstrate a rapid and cost-effective method to estimate CO2 exchange from intact vegetation patches under varying atmospheric CO2 concentrations. We find that net ecosystem CO2 uptake (NEE) in a boreal forest rose linearly by 4.7 ± 0.2% of the current ambient rate for every 10 ppm CO2 increase, with no detectable influence of foliar biomass, season, or nitrogen (N) fertilization. The lack of any clear short-term NEE response to fertilization in such an N-limited system is inconsistent with the instantaneous downregulation of photosynthesis formalized in many global models. Incorporating an alternative mechanism with considerable empirical support - diversion of excess carbon to storage compounds - into an existing earth system model brings the model output into closer agreement with our field measurements. A global simulation incorporating this modified model reduces a long-standing mismatch between the modeled and observed seasonal amplitude of atmospheric CO2 . Wider application of this chamber approach would provide critical data needed to further improve modeled projections of biosphere-atmosphere CO2 exchange in a changing climate.

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor.

324 I. 324 II. 325 III. 326 IV. 327 328 References 328 SUMMARY: Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate-carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate-carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward.

Reversible photocapture of a [2]rotaxane harnessing a barbiturate template.

Photoirradiation of a hydrogen-bonded molecular complex comprising acyclic components, namely, a stoppered thread (1) with a central barbiturate motif and an optimized doubly anthracene-terminated acyclic Hamilton-like receptor (2b), leads to an interlocked architecture, which was isolated and fully characterized. The sole isolated interlocked photoproduct (Φ = 0.06) is a [2]rotaxane, with the dimerized anthracenes assuming a head-to-tail geometry, as evidenced by NMR spectroscopy and consistent with molecular modeling (PM6). A different behavior was observed on irradiating homologous molecular complexes 1⊂2a, 1⊂2b, and 1⊂2c, where the spacers of 2a, 2b, and 2c incorporated 3, 6, and 9 methylene units, respectively. While no evidence of interlocked structure formation was observed following irradiation of 1⊂2a, a kinetically labile rotaxane was obtained on irradiating the complex 1⊂2c, and ring slippage was revealed. A more stable [2]rotaxane was formed on irradiating 1⊂2b, whose capture is found to be fully reversible upon heating, thereby resetting the system, with some fatigue (38%) after four irradiation­thermal reversion cycles.

Photoperiodic regulation of the seasonal pattern of photosynthetic capacity and the implications for carbon cycling.

Although temperature is an important driver of seasonal changes in photosynthetic physiology, photoperiod also regulates leaf activity. Climate change will extend growing seasons if temperature cues predominate, but photoperiod-controlled species will show limited responsiveness to warming. We show that photoperiod explains more seasonal variation in photosynthetic activity across 23 tree species than temperature. Although leaves remain green, photosynthetic capacity peaks just after summer solstice and declines with decreasing photoperiod, before air temperatures peak. In support of these findings, saplings grown at constant temperature but exposed to an extended photoperiod maintained high photosynthetic capacity, but photosynthetic activity declined in saplings experiencing a naturally shortening photoperiod; leaves remained equally green in both treatments. Incorporating a photoperiodic correction of photosynthetic physiology into a global-scale terrestrial carbon-cycle model significantly improves predictions of seasonal atmospheric CO(2) cycling, demonstrating the benefit of such a function in coupled climate system models. Accounting for photoperiod-induced seasonality in photosynthetic parameters reduces modeled global gross primary production 2.5% (∼4 PgC y(-1)), resulting in a >3% (∼2 PgC y(-1)) decrease of net primary production. Such a correction is also needed in models estimating current carbon uptake based on remotely sensed greenness. Photoperiod-associated declines in photosynthetic capacity could limit autumn carbon gain in forests, even if warming delays leaf senescence.

Substrate and environmental controls on microbial assimilation of soil organic carbon: a framework for Earth system models.

A mechanistic understanding of microbial assimilation of soil organic carbon is important to improve Earth system models' ability to simulate carbon-climate feedbacks. A simple modelling framework was developed to investigate how substrate quality and environmental controls over microbial activity regulate microbial assimilation of soil organic carbon and on the size of the microbial biomass. Substrate quality has a positive effect on microbial assimilation of soil organic carbon: higher substrate quality leads to higher ratio of microbial carbon to soil organic carbon. Microbial biomass carbon peaks and then declines as cumulative activity increases. The simulated ratios of soil microbial biomass to soil organic carbon are reasonably consistent with a recently compiled global data set at the biome level. The modelling framework developed in this study offers a simple approach to incorporate microbial contributions to the carbon cycling into Earth system models to simulate carbon-climate feedbacks and explain global patterns of microbial biomass.

Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites.

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies.

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2 ] (eCO2 ) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)-nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground-below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C-N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2 , given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections.

Neutrophil cerebrovascular transmigration triggers rapid neurotoxicity through release of proteases associated with decondensed DNA.

Cerebrovascular inflammation contributes to diverse CNS disorders through mechanisms that are incompletely understood. The recruitment of neutrophils to the brain can contribute to neurotoxicity, particularly during acute brain injuries, such as cerebral ischemia, trauma, and seizures. However, the regulatory and effector mechanisms that underlie neutrophil-mediated neurotoxicity are poorly understood. In this study, we show that mouse neutrophils are not inherently toxic to neurons but that transendothelial migration across IL-1-stimulated brain endothelium triggers neutrophils to acquire a neurotoxic phenotype that causes the rapid death of cultured neurons. Neurotoxicity was induced by the addition of transmigrated neutrophils or conditioned medium, taken from transmigrated neutrophils, to neurons and was partially mediated by excitotoxic mechanisms and soluble proteins. Transmigrated neutrophils also released decondensed DNA associated with proteases, which are known as neutrophil extracellular traps. The blockade of histone-DNA complexes attenuated transmigrated neutrophil-induced neuronal death, whereas the inhibition of key neutrophil proteases in the presence of transmigrated neutrophils rescued neuronal viability. We also show that neutrophil recruitment in the brain is IL-1 dependent, and release of proteases and decondensed DNA from recruited neutrophils in the brain occurs in several in vivo experimental models of neuroinflammation. These data reveal new regulatory and effector mechanisms of neutrophil-mediated neurotoxicity (i.e., the release of proteases and decondensed DNA triggered by phenotypic transformation during cerebrovascular transmigration). Such mechanisms have important implications for neuroinflammatory disorders, notably in the development of antileukocyte therapies.

Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months.

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.