Inferred drought-induced plant allocation shifts and their impact on drought legacy at a tropical forest site.

While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long-lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought-induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model-data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5 months. The inferred allocation shifts influenced the post-drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust-boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought-free conditions. Overall, allocation shifts accounted for 65% [45%-75%] of drought legacy effects in modeled NBE. In summary, drought-induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land-atmosphere CO2 exchanges and should be accounted for in ecosystem models.

Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal.

Tropical wetlands contribute ∼30% of the global methane (CH4) budget. Limited observational constraints on tropical wetland CH4 emissions lead to large uncertainties and disparities in representing emissions. In this work, we combine remote sensing observations with atmospheric and wetland models to investigate dry season wetland CH4 emissions from the Pantanal region of South America. We incorporate inundation maps generated from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation together with traditional inundation maps to generate an ensemble of wetland CH4 emission realizations. We challenge these realizations with daily satellite observations for May-July when wetland CH4 emission predictions diverge. We find that the CYGNSS inundation products predict larger emissions in May, in better agreement with observations. We use the model ensemble to generate an empirical observational constraint on CH4 emissions independent of choice of inundation map, finding large dry season wetland CH4 emissions (31.7 ± 13.6 and 32.0 ± 20.2 mg CH4/m2/day in May and June/July during 2018/2019, respectively). These May/June/July emissions are 2-3 times higher than current models, suggesting that annual wetland emissions may be higher than traditionally simulated. Observed trends in the early dry season indicate that dynamics during this period are of importance in representing tropical wetland CH4 behaviors.

Global net biome CO2 exchange predicted comparably well using parameter-environment relationships and plant functional types.

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points.

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate-plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012-2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011-2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012-2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states-showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.

Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America.

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

Successful Embolization of Hemorrhagic Hepatic Hydatid Cyst Followed by Surgical Resection: Report of Two Cases and Review of the Literature.

Hepatic hydatid cysts (HHCs) are common in endemic areas. Mostly they are asymptomatic, but some cause serious complications. We report 2 cases of HHC complicated arterial bleeding. Owing to signs of active bleeding, the patients were treated with selective embolization of the hepatic artery to stop the bleeding and stabilize the patients' condition. Subsequently, partial hepatectomy of the involved liver lobe was performed in an elective setting and without postoperative complications. We recommend bridging therapy by selective angiography and embolization for hemorrhagic hepatic hydatid cyst before definitive surgical treatment.

The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times.

The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85-88%) in contrast to higher latitudes (73-82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42-0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64-0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types.

Strain-specific altered nicotine metabolism in 3,3'-diindolylmethane (DIM) exposed mice.

Two indole compounds, indole-3-carbinol (I3C) and its acid condensation product, 3,3'-diindolymethane (DIM), have been shown to suppress the expression of flavin-containing monooxygenases (FMO) and to induce some hepatic cytochrome P450s (CYPs) in rats. In liver microsomes prepared from rats fed I3C or DIM, FMO-mediated nicotine N-oxygenation was decreased, whereas CYP-mediated nicotine metabolism to nicotine iminium and subsequently to cotinine was unchanged. Therefore, it was hypothesized that in mice DIM would also suppress nicotine N-oxygenation without affecting CYP-mediated nicotine metabolism. Liver microsomes were produced from male and female C57BL/6 J and CD1 mice fed 2500 parts per million (ppm) DIM for 14 days. In liver microsomes from DIM-fed mice, FMO-mediated nicotine N-oxygenation did not differ from the controls, but CYP-mediated nicotine metabolism was significantly increased, with results varying by sex and strain. To confirm the effects of DIM in vivo, control and DIM-fed CD1 male mice were injected subcutaneously with nicotine, and the plasma concentrations of nicotine, cotinine and nicotine-N-oxide were measured over 30 minutes. The DIM-fed mice showed greater cotinine concentrations compared with the controls 10 minutes following injection. It is concluded that the effects of DIM on nicotine metabolism in vitro and in vivo differ between mice and rats and between mouse strains, and that DIM is an effective inducer of CYP-mediated nicotine metabolism in commonly studied mouse strains.

Mouse strain-specific acute respiratory effects of nicotine unrelated to nicotine metabolism.

Plethysmograph measurement of respiratory phenotypes provides a highly sensitive means to study nicotine response in experimental model animals. We measured average respiratory frequency, tidal volume, minute volume and inspiratory time in C3H/HeJ and C57BL/6J mice subcutaneously administered 0.35 and 0.70 mg/kg nicotine. Both mouse strains showed significantly altered respiratory and locomotion phenotypes relative to saline-injected controls when administered the higher dose, but only C57BL/6J responded to the lower nicotine dose. Respiratory and locomotion phenotypes rarely differed significantly by sex. To investigate whether the strain-specific differences in nicotine sensitivity were related to differences in clearance, we followed up by measuring nicotine clearance in C3H/HeJ and C57BL/6J mice (0.35 mg/kg subcutaneous) and found sex differences in both strains, but no difference between strains.

Nicotine dependence is associated with functional variation in FMO3, an enzyme that metabolizes nicotine in the brain.

A common haplotype of the flavin-containing monooxygenase gene FMO3 is associated with aberrant mRNA splicing, a twofold reduction in in vivo nicotine N-oxidation and reduced nicotine dependence. Tobacco remains the largest cause of preventable mortality worldwide. CYP2A6, the primary hepatic nicotine metabolism gene, is robustly associated with cigarette consumption but other enzymes contribute to nicotine metabolism. We determined the effects of common variants in FMO3 on plasma levels of nicotine-N-oxide in 170 European Americans administered deuterated nicotine. The polymorphism rs2266780 (E308G) was associated with N-oxidation of both orally administered and ad libitum smoked nicotine (P⩽3.3 × 10-5 controlling for CYP2A6 genotype). In vitro, the FMO3 G308 variant was not associated with reduced activity, but rs2266780 was strongly associated with aberrant FMO3 mRNA splicing in both liver and brain (P⩽6.5 × 10-9). Surprisingly, in treatment-seeking European American smokers (n=1558) this allele was associated with reduced nicotine dependence, specifically with a longer time to first cigarette (P=9.0 × 10-4), but not with reduced cigarette consumption. As N-oxidation accounts for only a small percentage of hepatic nicotine metabolism we hypothesized that FMO3 genotype affects nicotine metabolism in the brain (unlike CYP2A6, FMO3 is expressed in human brain) or that nicotine-N-oxide itself has pharmacological activity. We demonstrate for the first time nicotine N-oxidation in human brain, mediated by FMO3 and FMO1, and show that nicotine-N-oxide modulates human α4ß2 nicotinic receptor activity in vitro. These results indicate possible mechanisms for associations between FMO3 genotype and smoking behaviors, and suggest nicotine N-oxidation as a novel target to enhance smoking cessation.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

Wetlands are the single largest natural source of atmospheric methane (CH4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH4 emissions, we synthesized nongrowing season and annual CH4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m2 in bogs to 5.2 g/m2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m-2  year-1 in tundra bogs to 78 g m-2  year-1 in temperate marshes. Uplands varied from CH4 sinks to CH4 sources with a median annual flux of 0.0 ± 0.2 g m-2  year-1 . The measured fraction of annual CH4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH4 emissions. Using this constraint, the modeled nongrowing season wetland CH4 flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH4 flux was 37 ± 7 Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate.

Variants in two adjacent genes, EGLN2 and CYP2A6, influence smoking behavior related to disease risk via different mechanisms.

Genome-wide significant associations with cigarettes per day (CPD) and risk for lung cancer and chronic obstructive pulmonary disease (COPD) were previously reported in a region of 19q13, including CYP2A6 (nicotine metabolism enzyme) and EGLN2 (hypoxia response). The associated single nucleotide polymorphisms (SNPs) were assumed to be proxies for functional variation in CYP2A6. Here, we demonstrate that when CYP2A6 and EGLN2 genotypes are analyzed together, the key EGLN2 variant, rs3733829, is not associated with nicotine metabolism independent of CYP2A6, but is nevertheless independently associated with CPD, and with breath carbon monoxide (CO), a phenotype associated with cigarette consumption and relevant to hypoxia. SNPs in EGLN2 are also associated with nicotine dependence and with smoking efficiency (CO/CPD). These results indicate a previously unappreciated novel mechanism behind genome-wide significant associations with cigarette consumption and disease risk unrelated to nicotine metabolism.

Use of a predictive model derived from in vivo endophenotype measurements to demonstrate associations with a complex locus, CYP2A6.

This study demonstrates a novel approach to test associations between highly heterogeneous genetic loci and complex phenotypes. Previous investigations of the relationship between Cytochrome P450 2A6 (CYP2A6) genotype and smoking phenotypes made comparisons by dividing subjects into broad categories based on assumptions that simplify the range of function of different CYP2A6 alleles, their numerous possible diplotype combinations and non-additive allele effects. A predictive model that translates CYP2A6 diplotype into a single continuous variable was previously derived from an in vivo metabolism experiment in 189 European Americans. Here, we apply this model to assess associations between genotype, inferred nicotine metabolism and smoking behaviors in larger samples without direct nicotine metabolism measurements. CYP2A6 genotype is not associated with nicotine dependence, as defined by the Fagerström Test of Nicotine Dependence, demonstrating that cigarettes smoked per day (CPD) and nicotine dependence have distinct genetic correlates. The predicted metric is significantly associated with CPD among African Americans and European American dependent smokers. Individual slow metabolizing genotypes are associated with lower CPD, but the predicted metric is the best predictor of CPD. Furthermore, optimizing the predictive model by including additional CYP2A6 alleles improves the fit of the model in an independent data set and provides a novel method of predicting the functional impact of alleles without direct metabolism measurements. Lastly, comprehensive genotyping and in vivo metabolism data are used to demonstrate that genome-wide significant associations between CPD and single nucleotide polymorphisms are the result of synthetic associations.

Near infrared (NIR) strong field ionization and imaging of C60 sputtered molecules: overcoming matrix effects and improving sensitivity.

Strong field ionization (SFI) was applied for the secondary neutral mass spectrometry (SNMS) of patterned rubrene films, mouse brain sections, and Botryococcus braunii algal cell colonies. Molecular ions of rubrene, cholesterol, C31 diene/triene, and three wax monoesters were detected, representing some of the largest organic molecules ever ionized intact by a laser post-ionization experiment. In rubrene, the SFI SNMS molecular ion signal was ~4 times higher than in the corresponding secondary-ion mass spectroscopy (SIMS) analysis. In the biological samples, the achieved signal improvements varied among molecules and sampling locations, with SFI SNMS, in some cases, revealing analytes made completely undetectable by the influence of matrix effects in SIMS.

Suppressing phagocyte activation by overexpressing the phosphatidylserine lipase ABHD12 preserves sarmopathic nerves.

Programmed axon degeneration (AxD) is a key feature of many neurodegenerative diseases. In healthy axons, the axon survival factor NMNAT2 inhibits SARM1, the central executioner of AxD, preventing it from initiating the rapid local NAD+ depletion and metabolic catastrophe that precipitates axon destruction. Because these components of the AxD pathway act within neurons, it was also assumed that the timetable of AxD was set strictly by a cell-intrinsic mechanism independent of neuron-extrinsic processes later activated by axon fragmentation. However, using a rare human disease model of neuropathy caused by hypomorphic NMNAT2 mutations and chronic SARM1 activation (sarmopathy), we demonstrated that neuronal SARM1 can initiate macrophage-mediated axon elimination long before stressed-but-viable axons would otherwise succumb to cell-intrinsic metabolic failure. Investigating potential SARM1-dependent signals that mediate macrophage recognition and/or engulfment of stressed-but-viable axons, we found that chronic SARM1 activation triggers axonal blebbing and dysregulation of phosphatidylserine (PS), a potent phagocyte immunomodulatory molecule. Neuronal expression of the phosphatidylserine lipase ABDH12 suppresses nerve macrophage activation, preserves motor axon integrity, and rescues motor function in this chronic sarmopathy model. We conclude that PS dysregulation is an early SARM1-dependent axonal stress signal, and that blockade of phagocytic recognition and engulfment of stressed-but-viable axons could be an attractive therapeutic target for management of neurological disorders involving SARM1 activation.

Reduced STMN2 and pathogenic TDP-43, two hallmarks of ALS, synergize to accelerate motor decline in mice.

Pathological TDP-43 loss from the nucleus and cytoplasmic aggregation occurs in almost all cases of ALS and half of frontotemporal dementia patients. Stathmin2 (Stmn2) is a key target of TDP-43 regulation and aberrantly spliced Stmn2 mRNA is found in patients with ALS, frontotemporal dementia, and Alzheimer's Disease. STMN2 participates in the axon injury response and its depletion in vivo partially replicates ALS-like symptoms including progressive motor deficits and distal NMJ denervation. The interaction between STMN2 loss and TDP-43 dysfunction has not been studied in mice because TDP-43 regulates human but not murine Stmn2 splicing. Therefore, we generated trans-heterozygous mice that lack one functional copy of Stmn2 and express one mutant TDP-43Q331K knock-in allele to investigate whether reduced STMN2 function exacerbates TDP-43-dependent pathology. Indeed, we observe synergy between these two alleles, resulting in an early onset, progressive motor deficit. Surprisingly, this behavioral defect is not accompanied by detectable neuropathology in the brain, spinal cord, peripheral nerves or at neuromuscular junctions (NMJs). However, the trans-heterozygous mice exhibit abnormal mitochondrial morphology in their distal axons and NMJs. As both STMN2 and TDP-43 affect mitochondrial dynamics, and neuronal mitochondrial dysfunction is a cardinal feature of many neurodegenerative diseases, this abnormality likely contributes to the observed motor deficit. These findings demonstrate that partial loss of STMN2 significantly exacerbates TDP-43-associated phenotypes, suggesting that STMN2 restoration could ameliorate TDP-43 related disease before the onset of degeneration.

A compensatory effect upon splicing results in normal function of the CYP2A6*14 allele.

A synonymous variant in the first exon of CYP2A6, rs1137115 (51G>A), defines the common reference allele CYP2A6*1A, and is associated with lower mRNA expression and slower in-vivo nicotine metabolism. Another common allele, CYP2A6*14, differs from CYP2A6*1A by a single variant, rs28399435 (86G>A, S29N). However, CYP2A6*14 shows in-vivo activity comparable with that of full-function alleles, and significantly higher than CYP2A6*1A. rs1137115A is predicted to create an exonic splicing suppressor site overlapping an exonic splicing enhancer (ESE) site in the first exon of CYP2A6, whereas rs28399435A is predicted to strengthen another adjacent ESE, potentially compensating for rs1137115A. Using an allelic expression assay to assess cDNAs produced from rs1137115 heterozygous liver biopsy samples, lower expression of the CYP2A6*1A allele is confirmed while CYP2A6*14 expression is found to be indistinguishable from that of rs1137115G alleles. Quantitative PCR assays to determine the relative abundance of spliced and unspliced or partially spliced CYP2A6 mRNAs in liver biopsy samples show that *1A/*1A homozygotes have a significantly lower ratio, due to both a reduction in spliced forms and an increase in unspliced or partially spliced CYP2A6. These results show the importance of common genetic variants that effect exonic splicing suppressor and ESEs to explain human variation regarding clinically-relevant phenotypes.

Effects upon in-vivo nicotine metabolism reveal functional variation in FMO3 associated with cigarette consumption.

BACKGROUND: Flavin-containing monooxygenases (FMO) catalyze the metabolism of nucleophilic heteroatom-containing drugs and xenobiotics, including nicotine. Rare mutations in FMO3 are responsible for defective N-oxidation of dietary trimethylamine leading to trimethylaminuria, and common genetic variation in FMO3 has been linked to interindividual variability in metabolic function that may be substrate specific. METHODS: A genetic model of CYP2A6 function is used as a covariate to reveal functional polymorphism in FMO3 that indirectly influences the ratio of deuterated nicotine metabolized to cotinine following oral administration. The association is tested between FMO3 haplotype and cigarette consumption in a set of nicotine-dependent smokers. RESULTS: FMO3 haplotype, based on all common coding variants in Europeans, significantly predicts nicotine metabolism and accounts for ∼2% of variance in the apparent percent of nicotine metabolized to cotinine. The metabolic ratio is not associated with FMO2 haplotype or an FMO1 expression quantitative trait locus. Cross-validation demonstrates calculated FMO3 haplotype parameters to be robust and significantly improve the predictive nicotine metabolism model over CYP2A6 genotype alone. Functional classes of FMO3 haplotypes, as determined by their influence on nicotine metabolism to cotinine, are also significantly associated with cigarettes per day in nicotine-dependent European Americans (n=1025, P=0.04), and significantly interact (P=0.016) with CYP2A6 genotype to predict cigarettes per day. CONCLUSION: These findings suggest that common polymorphisms in FMO3 influence nicotine clearance and that these genetic variants in turn influence cigarette consumption.

The contribution of common UGT2B10 and CYP2A6 alleles to variation in nicotine glucuronidation among European Americans.

BACKGROUND: To develop a predictive genetic model of nicotine metabolism. UDP-glucuronosyltransferase-2B10 (UGT2B10) is the primary catalyst of nicotine glucuronidation. MATERIALS AND METHODS: The conversion of deuterated (D2)-nicotine to D2-nicotine-glucuronide, D2-cotinine, D2-cotinine-glucuronide, and D2-trans-3'-hydroxycotinine were quantified in 188 European Americans, and the contribution of UGT2B10 genotype to variability in first-pass nicotine glucuronidation assessed, following a procedure previously applied to nicotine C-oxidation. The proportion of total nicotine converted to nicotine-glucuronide [D2-nicotine-glucuronide/(D2-nicotine+D2-nicotine-glucuronide+D2-cotinine+D2-cotinine-glucuronide+D2-trans-3'-hydroxycotinine)] was the primary phenotype. RESULTS: The variant, rs61750900T (D67Y) (minor allele frequency=10%), is confirmed to abolish nicotine glucuronidation activity. Another variant, rs112561475G (N397D) (minor allele frequency=2%), is significantly associated with enhanced glucuronidation. rs112561475G is the ancestral allele of a well-conserved amino acid, indicating that the majority of human UGT2B10 alleles are derived hypomorphic alleles. CONCLUSION: CYP2A6 and UGT2B10 genotype explain 53% of the variance in oral nicotine glucuronidation in this sample. CYP2A6 and UGT2B10 genetic variants are also significantly associated with undeuterated (D0) nicotine glucuronidation in individuals smoking ad libitum. We find no evidence for further common variation markedly influencing hepatic UGT2B10 expression in European Americans.

GriddingMachine, a database and software for Earth system modeling at global and regional scales.

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.