Endogenous soluble receptor for advanced glycation endproducts is increased in preeclampsia

OBJECTIVE: Preeclampsia is a serious complication in pregnancy with an increased future cardiovascular risk for both mother and newborn. Recently, low levels of endogenous soluble receptor for advanced glycation endproducts (esRAGE) have been associated with increased cardiovascular risk. In the current study, we investigated esRAGE serum levels in patients with preeclampsia as compared to healthy gestational age-matched controls. METHODS: esRAGE was quantified by enzyme-linked immunosorbent assay in controls and patients with preeclampsia during pregnancy (control: n = 20, preeclampsia: n = 16) and 6 months after delivery (control: n = 19, preeclampsia: n = 15). Furthermore, esRAGE was correlated to clinical and biochemical measures of renal function, glucose and lipid metabolism, as well as inflammation. RESULTS: During pregnancy, median maternal serum esRAGE concentrations were more than three-fold higher in patients with preeclampsia (200 ng/l) than in controls (63 ng/l) (P < 0.01). Furthermore, esRAGE levels positively correlated with age, blood pressure, creatinine, adiponectin, and C-reactive protein, whereas a negative correlation existed with fasting insulin and the homeostasis model assessment of insulin resistance index. In multivariate analyses, homeostasis model assessment of insulin resistance and C-reactive protein independently predicted esRAGE serum levels and explained 44% of the variation in esRAGE concentrations. Surprisingly, median esRAGE concentrations 6 months after delivery were significantly lower in former patients with preeclampsia (270 ng/l) than in controls (342 ng/l) in contrast to the results obtained during pregnancy. CONCLUSION: We showed that maternal esRAGE concentrations are significantly increased in patients with preeclampsia during pregnancy. Here, insulin sensitivity and inflammatory status independently predict serum esRAGE levels.     

Secretory products from human adipocytes impair endothelial function via nuclear factor kappaB

Hyperplasia and hypertrophy of fat cells can be found in obesity, and increased adiposity is associated with endothelial dysfunction as an early event of atherosclerosis. However, it is unclear whether human adipocytes directly influence endothelial function. To study the crosstalk between fat and endothelial cells, human umbilical venous endothelial cells (HUVECs), and human coronary artery endothelial cells (HCAECs) were cultured in infranatants (Adipo) of primary differentiated human adipocytes. Interestingly, incubation of HUVECs and HCAECs with Adipo significantly increased monocyte adhesion 7.3 and 2.2-fold, respectively. VCAM-1, ICAM-1, and E-selectin in HUVECs were upregulated 3.9, 3.0, and 9.5-fold, respectively, under these conditions. Furthermore, Adipo significantly stimulated NFkappaB activity 1.9-fold. The NFkappaB inhibitor MG-132 and heat inactivation significantly reversed Adipo-stimulated monocyte adhesion. TNFalpha-neutralizing antibodies partly reversed Adipo-induced monocyte adhesion. In contrast, thiazolidinedione-pretreatment of human adipocytes did not alter the effects of Adipo. Adipo did not show cytotoxic effects. Taken together, we demonstrate that endothelial dysfunction is induced by adipocyte-secreted factors via NFkappaB partly dependent on TNFalpha.     

N-Chlorotaurine Exhibits Fungicidal Activity against Therapy-Refractory Scedosporium Species and Lomentospora prolificans

N-Chlorotaurine (NCT), a well-tolerated endogenous long-lived oxidant that can be applied topically as an antiseptic, was tested on its fungicidal activity against Scedosporium and Lomentospora, opportunistic fungi that cause severe infections with limited treatment options, mainly in immunocompromised patients. In quantitative killing assays, both hyphae and conidia of Scedosporium apiospermum, Scedosporium boydii, and Lomentospora prolificans (formerly Scedosporium prolificans) were killed by 55 mM (1.0%) NCT at pH 7.1 and 37°C, with a 1- to 4-log₁₀ reduction in CFU after 4 h and a 4- to >6-log₁₀ reduction after 24 h. The addition of ammonium chloride to NCT markedly increased this activity. LIVE/DEAD staining of conidia treated with 1.0% NCT for 0.5 to 3 h increased the permeability of the cell wall and membrane. Preincubation of the test fungi in 1.0% NCT for 10 to 60 min delayed the time to germination of conidia by 2 h to >12 h and reduced their germination rate by 10.0 to 100.0%. Larvae of Galleria mellonella infected with 1.0 × 10⁷ conidia of S. apiospermum and S. boydii died at a rate of 90.0 to 100% after 8 to 12 days. The mortality rate was reduced to 20 to 50.0% if conidia were preincubated in 1.0% NCT for 0.5 h or if heat-inactivated conidia were used. Our study demonstrates the fungicidal activity of NCT against different Scedosporium and Lomentospora species. A postantifungal effect connected with a loss of virulence occurs after sublethal incubation times. The augmenting effect of ammonium chloride can be explained by the formation of monochloramine.     

AT2 Receptor and Tissue Injury: Therapeutic Implications

The converging clinical effectiveness of mineralocorticoid receptor antagonists (MRAs) Spironolactone and Eplerenone has made their safety profiles/cost-effectiveness key determinants of “agents of choice” across a broad range of clinical indications. The clinical biology of the aldosterone molecule and its range of effects in varied organ systems have been well elucidated from recent mechanistic and systematic studies. Clinical experience with Spironolactone is well established, as is its adverse effects profile. The range of adverse effects experienced with Spironolactone subsequently led to its modification and synthesis of Eplerenone. Recent published reports have confirmed lower prevalence rates of sex-related adverse effects attributable to Eplerenone compared to Spironolactone. There is, however, not much to choose between these agents in regards to other adverse effects including hyperkalemia and kidney failure. As was the experience with Spironolactone, as more robust observational data on Eplerenone accrues, it is possible that the real-life experience of its adverse profile may be discordant with that reported by randomized controlled clinical trials (RCTs). In addition, its metabolism by the vulnerable and highly polymorphic cytochrome dependent pathway also makes it susceptible to various drug interactions. The potential implication of the latter (including morbidity and mortality) may take years to evolve.     

Predicting species’ range limits from functional traits for the tree flora of North America

Using functional traits to explain species’ range limits is a promising approach in functional biogeography. It replaces the idiosyncrasy of species-specific climate ranges with a generic trait-based predictive framework. In addition, it has the potential to shed light on specific filter mechanisms creating large-scale vegetation patterns. However, its application to a continental flora, spanning large climate gradients, has been hampered by a lack of trait data. Here, we explore whether five key plant functional traits (seed mass, wood density, specific leaf area (SLA), maximum height, and longevity of a tree)—indicative of life history, mechanical, and physiological adaptations—explain the climate ranges of 250 North American tree species distributed from the boreal to the subtropics. Although the relationship between traits and the median climate across a species range is weak, quantile regressions revealed strong effects on range limits. Wood density and seed mass were strongly related to the lower but not upper temperature range limits of species. Maximum height affects the species range limits in both dry and humid climates, whereas SLA and longevity do not show clear relationships. These results allow the definition and delineation of climatic “no-go areas” for North American tree species based on key traits. As some of these key traits serve as important parameters in recent vegetation models, the implementation of trait-based climatic constraints has the potential to predict both range shifts and ecosystem consequences on a more functional basis. Moreover, for future trait-based vegetation models our results provide a benchmark for model evaluation.In 1895 the Danish plant ecologist Eugen Warming defined for the first time the objectives of a functional plant biogeography, when he expressed the need “to investigate the problems concerning the economy of plants, the demands that they make on their environment, and the means that they use to use the surrounding conditions….” He already envisioned how to tackle this: “This subject leads us into deep morphological, anatomical, and physiological investigations; […] it is very difficult, yet very alluring; but only in few cases can its problems be satisfactorily solved at the present time” (1).Since Warming’s days plant science has progressed beyond the study of just a “few cases.” For more than a century now, botanists and plant ecologists have collected data on morphological, anatomical, and physiological traits (2, 3), and have mapped the distributions of tens of thousands of plant species (e.g., Global Biodiversity Information Facility, www.gbif.org). In addition, climatologists and soil scientists have provided us with high-resolution global maps of the plant’s surrounding condition. With this it has now become feasible to analyze the functional underpinnings of plant distributions for entire regional floras across large-scale environmental gradients (4). It is well established that on regional and global scales, climate determines the distribution not only of plant species but also of form and function (5, 6) because it constitutes the overall physical constraint under which plants must establish and reproduce, before biotic interactions may modulate plant fitness. Plants have evolved a multitude of adaptations to climatic constraints, which are expressed in the diversity of their functional traits. These allow them to tolerate climate extremes such as summer drought or low winter temperatures. In other words, the climate range occupied by plants should be predictable from their functional traits.Current species distribution models (SDMs) (7) use correlations between current climate and species distributions, so-called climate envelopes. Even modern dynamic global vegetation models (DGVMs) (8) capable of representing carbon acquisition, water balance, and competitive interactions of plant functional types (PFTs) in great mechanistic detail, still incorporate empirical climate envelopes to constrain PFT distributions. This obvious lack of mechanism is an important limitation when such models are used to predict vegetation shifts under future climate scenarios, especially under novel combinations of climate variables (8). Here, we introduce a unique approach—the “double quantile” approach (Fig. 1 and see Linking Traits to Climate Ranges)—that allows us to predict species distribution limits from functional plant traits. Although still empirical at heart, this approach has distinct advantages: (i) The very nature of the traits emerging as suitable predictors of species distribution limits sheds light on the biological mechanisms. Accordingly, below we are able to put forward concrete hypotheses of the biological underpinnings of trait–climate limit relationships. (ii) Functional traits serve as a common currency across species and thus provide the basis for assimilating the behavior of many species into a single generic predictive framework. (iii) Because this approach replaces idiosyncrasy by generality, the handshake with process-oriented models is greatly facilitated as will be discussed below.Open in a separate windowFig. 1.(A) Species are distributed along climatic gradients and occupy species-specific climate ranges, which can be characterized by three measures: the upper limit (red squares), the lower limit (blue squares), and the median (black squares) for which the highest species’ occurrence probability is suggested. (B) To explore the response of the climate range measures to traits, we related them separately against the traits using linear quantile regression analysis. We estimated the upper quantiles for the upper limits, the lower quantiles for the lower limits, and the median quantile for the median; a solid line indicates a slope significantly different from zero (increasing or decreasing) and a dotted line represents a nonsignificant slope. The area between the outermost regression lines represents the possible climate range species can occupy across their trait values whereas areas outside these lines describe no-go areas. (C) We distinguish three types of response patterns: (i) one-sided constraint, i.e., significant slope at only one limit (the upper or the lower one); (ii) two-sided constraint with reverse slopes at both limits; and (iii) constant shift with aligned slopes at both limits.Here, we explore the potential of five functional traits—specific leaf area (SLA), wood density, maximum height, seed mass, and tree longevity—to explain the climate range limits and mean climate preferences of 250 North American tree species covering a temperature gradient from the boreal to the subtropics and a gradient from 65 to 3,000 mm of annual precipitation. Although there has been a first attempt to incorporate trait information in SDMs (9), we present here a unique study using plant functional traits to predict their limiting effect on species’ climate ranges at a taxonomic and climatic scale relevant for DGVMs. We chose to present the relationship between traits and species climate range limits from a trait perspective to highlight their potential for predicting species’ climate niches as a holistic measure of plant performance in response to climate. Unlike previous studies, our double quantile approach places an emphasis on the responses of species-specific climate ranges at the potentially stressful ends of climate gradients, where strong effects of functional traits on range limits can be expected.

Functional Traits: Selection and Relevance.

The five traits represent key functions defining plant strategy axes related to the fundamental tradeoffs of resource acquisition and reproduction (10, 11) and are thus indicative of life history, mechanical, and physiological mechanisms. Furthermore, some of these traits are frequently used as parameters in DGVMs (2). Because these traits vary across climatic gradients (12, 13), they are ideally suited to gain insight into processes shaping tree distributions at continental scales and at the same time to improve predictions on ecosystem functions under climate change. SLA is a key trait of the leaf economic spectrum (14) and defines a species’ resource use strategy from acquisitive to conservative. It is related to growth rate under different climatic conditions (15) and reflects tradeoffs in species’ shade and drought tolerances (16). Wood density is related to the efficiency and safety of water transport (17) and represents a tradeoff between mechanical strength and vertical growth. It is strongly correlated with growth and mortality rates (12). Maximum height describes the maximum recorded height of a species and quantifies species’ carbon gain strategy via light capture (18); it is related to successional status, shade tolerance and responds to gradients in precipitation on a global scale (19). Seed mass correlates positively with seedling survival rates under hazardous conditions during seedling establishment (11) and negatively with dispersal distance and the number of seeds produced per unit energy invested (20). Maximum tree longevity determines species responses to disturbance (21), compensates for reduced fecundity or juvenile survival (22), and relates to defensive investment (23).

Linking Traits to Climate Ranges.

We derive a tree species’ climate range from its natural geographic distribution (24). We use a set of eight bioclimatic variables (Methods) which represent dominant climatic gradients over North America and are widely used in climatic niche modeling (7, 25). To define a species’ climate range (Fig. 1A) we estimate for each bioclimatic variable the lower (5th quantile) and upper limits (95th quantile) and the median (50th quantile) across a species’ distribution range. Using linear quantile regression analysis (26), we regress across all species the three species-specific range measures against each of the five traits separately estimating the lower (10th, 5th), the upper (90th, 95th) and median (50th) regression quantiles, respectively (Fig. 1B). Thus, the 50th quantile regression lines fit to the medians (black line and squares in Fig. 1B) and describe how the mean realized climate niche depends on the trait values. The lower and upper quantile regression lines fit to the lower and upper limits (blue line and squares and red line and squares, respectively). In this double quantile approach, the outer regression lines enclose an area corresponding to the climate range the pool of 250 North American tree species can occupy across the range of their trait values (Fig. 1B). At the same time it identifies “no-go areas” which cannot be occupied by trees with a given trait value. The delineated areas can attain three possible shapes: (i) the area is wedge-shaped when there is a one-sided constraint, i.e., only one outer quantile represents a climatic extreme requiring a trait adaptation. (ii) The area has the form of an acute-angled triangle, when there is a two-sided constraint leading to reverse responses of the outer quantiles. Both triangular shapes, i and ii, imply that the possible climate range of the species pool changes with a given trait value (see Fig. 1C for examples). (iii) The area can have a rhomboid shape when the two-sided constraints are aligned. This implies a shift in the mean climate preference, but no change in the potential climate range per trait value.