The ECCO-Darwin Data-Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean \u3cem\u3ep\u3c/em\u3eCO\u3csub\u3e2\u3c/sub\u3e and Air-Sea CO\u3csub\u3e2\u3c/sub\u3e Flux

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO2. To address this challenge, we have updated and improved ECCO-Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint-based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data-constrained ECCO physics, a Green\u27s function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO-Darwin exhibits broad-scale consistency with observed surface ocean pCO2 and air-sea CO2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO2 uptake occur in subpolar seasonally stratified biomes, where ECCO-Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO-Darwin has a time-mean global ocean CO2 sink (2.47 ± 0.50 Pg C year−1) and interannual variability that are more consistent with interpolation-based products. Compared to interpolation-based methods, ECCO-Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO-Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate-related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property-conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies

Attribution of space-time variability in global-ocean dissolved inorganic Carbon

The inventory and variability of oceanic dissolved inorganic carbon (DIC) is driven by the interplay of physical, chemical, and biological processes. Quantifying the spatiotemporal variability of these drivers is crucial for a mechanistic understanding of the ocean carbon sink and its future trajectory. Here, we use the Estimating the Circulation and Climate of the Ocean-Darwin ocean biogeochemistry state estimate to generate a global-ocean, data-constrained DIC budget and investigate how spatial and seasonal-to-interannual variability in three-dimensional circulation, air-sea CO2 flux, and biological processes have modulated the ocean sink for 1995–2018. Our results demonstrate substantial compensation between budget terms, resulting in distinct upper-ocean carbon regimes. For example, boundary current regions have strong contributions from vertical diffusion while equatorial regions exhibit compensation between upwelling and biological processes. When integrated across the full ocean depth, the 24-year DIC mass increase of 64 Pg C (2.7 Pg C year−1) primarily tracks the anthropogenic CO2 growth rate, with biological processes providing a small contribution of 2 (1.4 Pg C). In the upper 100 m, which stores roughly 13 (8.1 Pg C) of the global increase, we find that circulation provides the largest DIC gain (6.3 Pg C year−1) and biological processes are the largest loss (8.6 Pg C year−1). Interannual variability is dominated by vertical advection in equatorial regions, with the 1997–1998 El Niño-Southern Oscillation causing the largest year-to-year change in upper-ocean DIC (2.1 Pg C). Our results provide a novel, data-constrained framework for an improved mechanistic understanding of natural and anthropogenic perturbations to the ocean sink. © 2022. The Authors

The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO₂ and Air‐Sea CO₂ Flux

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO₂. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green's function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean pCO₂ and air‐sea CO₂ flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO₂ uptake occur in subpolar seasonally stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean global ocean CO₂ sink (2.47 ± 0.50 Pg C year⁻¹) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies

A dynamic network approach for the study of human phenotypes

The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure

Pharmacokinetics of isoflavones, daidzein and genistein, after ingestion of soy beverage compared with soy extract capsules in postmenopausal Thai women

BACKGROUND: Isoflavones from soybeans may provide some beneficial impacts on postmenopausal health. The purpose of this study was to compare the pharmacokinetics and bioavailability of plasma isoflavones (daidzein and genistein) after a single dose of orally administered soy beverage and soy extract capsules in postmenopausal Thai women. METHODS: We conducted a randomized two-phase crossover pharmacokinetic study in 12 postmenopausal Thai women. In the first phase, each subject randomly received either 2 soy extract capsules (containing daidzin : genistin = 7.79 : 22.57 mg), or soy beverage prepared from 15 g of soy flour (containing daidzin : genistin = 9.27 : 10.51 mg). In the second phase, the subjects received an alternative preparation in the same manner after a washout period of at least 1 week. Blood samples were collected immediately before and at 0.5, 1, 2, 4, 6, 8, 10, 12, 24 and 32 h after administration of the soy preparation in each phase. Plasma daidzein and genistein concentrations were determined by using high performance liquid chromatography (HPLC). The pharmacokinetic parameters of daidzein and genistein, i.e. maximal plasma concentration (C(max)), time to maximal plasma concentration (T(max)), area under the plasma concentration-time curve (AUC) and half-life (t(1/2)), were estimated using the TopFit version 2.0 software with noncompartmental model analysis. RESULTS: There were no significant differences in the mean values of C(max)/dose, AUC(0–32)/dose, AUC(0-∝)/dose, T(max), and t(1/2 )of genistein between both preparations. For pharmacokinetic parameters of daidzein, the mean values of C(max)/dose, T(max), and t(1/2 )did not significantly differ between both preparations. Nonetheless, the mean AUC(0–32)/dose and AUC(0-∝)/dose after administration of soy extract capsules were slightly (but significantly, p < 0.05) higher than those of soy beverage. CONCLUSION: The bioavailability of daidzein, which was adjusted for the administered dose (AUC/dose), following a single oral administration of soy beverage was slightly (but significantly) less than that of soy extract capsules, whereas, the bioavailability adjusted for administered dose of genistein from both soy preparations were comparable. The other pharmacokinetic parameters of daidzein and genistein, including C(max )adjusted for the dose, T(max )and t(1/2), were not different between both soy preparations

A Randomized Community-based Intervention Trial Comparing Faith Community Nurse Referrals to Telephone-Assisted Physician Appointments for Health Fair Participants with Elevated Blood Pressure

To measure the effect of faith community nurse referrals versus telephone-assisted physician appointments on blood pressure control among persons with elevated blood pressure at health fairs. Randomized community-based intervention trial conducted from October 2006 to October 2007 of 100 adults who had an average blood pressure reading equal to or above a systolic of 140 mm Hg or a diastolic of 90 mm Hg obtained at a faith community nurse-led church health event. Participants were randomized to either referral to a faith community nurse or to a telephone-assisted physician appointment. The average enrollment systolic blood pressure (SBP) was 149 ± 14 mm Hg, diastolic blood pressure (DBP) was 87 ± 11 mm Hg, 57% were uninsured and 25% were undiagnosed at the time of enrollment. The follow-up rate was 85% at 4 months. Patients in the faith community nurse referral arm had a 7 ± 15 mm Hg drop in SBP versus a 14 ± 15 mm Hg drop in the telephone-assisted physician appointment arm (p = 0.04). Twenty-seven percent of the patients in the faith community nurse referral arm had medication intensification compared to 32% in the telephone-assisted physician appointment arm (p = 0.98). Church health fairs conducted in low-income, multiethnic communities can identify many people with elevated blood pressure. Facilitating physician appointments for people with elevated blood pressure identified at health fairs confers a greater decrease in SBP than referral to a faith community nurse at four months