Maternal Serum Meteorin Levels and the Risk of Preeclampsia

Background

Meteorin (METRN) is a recently described neutrophic factor with angiogenic properties. This is a nested case-control study in a longitudinal cohort study that describes the serum profile of METRN during different periods of gestation in healthy and preeclamptic pregnant women. Moreover, we explore the possible application of METRN as a biomarker.

Methods and Findings

Serum METRN was measured by ELISA in a longitudinal prospective cohort study in 37 healthy pregnant women, 16 mild preeclamptic women, and 20 healthy non-pregnant women during the menstrual cycle with the aim of assessing serum METRN levels and its correlations with other metabolic parameters. Immunostaining for METRN protein was performed in placenta. A multivariate logistic regression model was proposed and a classifier model was formulated for predicting preeclampsia in early and middle pregnancy. The performance in classification was evaluated using measures such as sensitivity, specificity, and the receiver operating characteristic (ROC) curve. In healthy pregnant women, serum METRN levels were significantly elevated in early pregnancy compared to middle and late pregnancy. METRN levels are significantly lower only in early pregnancy in preeclamptic women when compared to healthy pregnant women. Decision trees that did not include METRN levels in the first trimester had a reduced sensitivity of 56% in the detection of preeclamptic women, compared to a sensitivity of 69% when METRN was included.

Conclusions

The joint measurements of circulating METRN levels in the first trimester and systolic blood pressure and weight in the second trimester significantly increase the probabilities of predicting preeclampsia.     

Inequality as a Powerful Predictor of Infant and Maternal Mortality around the World

Background

Maternal and infant mortality are highly devastating, yet, in many cases, preventable events for a community. The human development of a country is a strong predictor of maternal and infant mortality, reflecting the importance of socioeconomic factors in determinants of health. Previous research has shown that the Human Development Index (HDI) predicts infant mortality rate (IMR) and the maternal mortality ratio (MMR). Inequality has also been shown to be associated with worse health in certain populations. The main purpose of the present study was to determine the correlation and predictive power of the Inequality Adjusted Human Development Index (IHDI) as a measure of inequality with the Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR), Early Neonatal Mortality Rate (ENMR), Late Neonatal Mortality Rate (LNMR), and the Post Neonatal Mortality Rate (PNMR).

Methods and Findings

Data for the present study were downloaded from two sources: infant and maternal mortality data were downloaded from the Global Burden of Disease 2013 Cause of Death Database and the Human Development Index (HDI) and Inequality-Adjusted Human Development Index (IHDI) data were downloaded from the United Nations Development Program (UNDP). Pearson correlation coefficients were estimated, following logarithmic transformations to the data, to examine the relationship between HDI and IHDI with MMR, IMR, ENMR, LNMR, and PNMR. Steiger’s Z test for the equality of two dependent correlations was utilized in order to determine whether the HDI or IHDI was more strongly associated with the outcome variables. Lastly, we constructed OLS regression models in order to determine the predictive power of the HDI and IHDI in terms of the MMR, IMR, ENMR, LNMR, and PNMR.Maternal and infant mortality were both strongly and negatively correlated with both HDI and IHDI; however, Steiger’s Z test for the equality of two dependent correlations revealed that IHDI was more strongly correlated than HDI with MMR (Z = 4.897, p < 0.001), IMR (Z = 2.524, p = 0.012), ENMR (Z = 2.936, p = 0.003), LNMR (Z = 2.272, p = 0.023), and PNMR (Z = 2.277, p = 0.023). Furthermore, side-by-side OLS regression models revealed that, when IHDI was used as the predictor variable instead of HDI, the R ² value was 0.053 higher for MMR, 0.025 higher for IMR, 0.038 higher for ENMR, 0.029 higher for LNMR, and 0.026 higher for PNMR.

Conclusions

Even when both the HDI and the IHDI correlate with the infant and maternal mortality rates, the IHDI is a better predictor for these two health indicators. Therefore, these results add more evidence that inequality is playing an important role in determining the health status of various populations in the world and more efforts should be put into programs to fight inequality.     

Sleep/Wake Dynamics Changes during Maturation in Rats

Objectives

Conventional scoring of sleep provides little information about the process of transitioning between vigilance states. We applied the state space technique (SST) using frequency band ratios to follow normal maturation of different sleep/wake states, velocities of movements, and transitions between states of juvenile (postnatal day 34, P34) and young adult rats (P71).

Design

24-h sleep recordings of eight P34 and nine P71 were analyzed using conventional scoring criteria and SST one week following implantation of telemetric transmitter. SST is a non-categorical approach that allows novel quantitative and unbiased examination of vigilance-states dynamics and state transitions. In this approach, behavioral changes are described in a 2-dimensional state space that is derived from spectral characteristics of the electroencephalography.

Measurements and Results

With maturation sleep intensity declines, the duration of deep slow wave sleep (DSWS) and light slow wave sleep (LSWS) decreases and increases, respectively. Vigilance state determination, as a function of frequency, is not constant; there is a substantial shift to higher ratio 1 in all vigilance states except DSWS. Deep slow wave sleep decreases in adult relative to juvenile animals at all frequencies. P71 animals have 400% more trajectories from Wake to LSWS (p = 0.005) and vice versa (p = 0.005), and 100% more micro-arousals (p = 0.021), while trajectories from LSWS to DSWS (p = 0.047) and vice versa (p = 0.033) were reduced by 60%. In both juvenile and adult animals, no significant changes were found in sleep velocity at all regions of the 2-dimensional state space plot; suggesting that maturation has a partial effect on sleep stability.

Conclusions

Here, we present novel and original evidence that SST enables visualization of vigilance-state intensity, transitions, and velocities that were not evident by traditional scoring methods. These observations provide new perspectives in sleep state dynamics and highlight the usefulness of this technique in exploring the development of sleep-wake activity.     

Fight or flight: plastic behavior under self-generated heterogeneity

Plants are able to plastically respond to their ubiquitously heterogeneous environments; however, little is known about the conditions under which plants are expected to avoid or confront their neighbors in dense stands, where heterogeneity is self-generated by non-uniform growth and feedback between plant interactions and stand heterogeneity. We studied the role of plasticity for spatial pattern-formation and the resulting stand-level fitness of clonal plants, assuming variable types of plastic behavior. Specifically, the adaptive values of behavior ranging from pure avoidance, to neutral and pure confrontation were assessed using a simulation model of stands of clonally growing plants with varying capacity of plastic behavior. The results demonstrated significant effects of the type of competitive behavior on mean final densities of single-species stands at equilibrium. Density was the lowest and aggregation was the highest in stands of purely confrontational plants, and density was highest in stands of neutral and purely avoiding plants. When competing against a neutral photometer (i.e. non-plastic but otherwise identical plant), the best competitors were plants that avoided their neighbors in 0.33–0.50 of the cases and were neutral otherwise. Differences in adaptive values of individual behaviors depended both on the distance over which the environmental structure (i.e. local density) was perceived, and on overall density. Density-independent ramet mortality profoundly changed the effectiveness of competitive behaviors. Under high levels of mortality, avoidance was the most effective and confrontation the least effective behavior. The results indicate that individual-based behaviors might affect higher organizational levels, and that their reciprocal interactions with resource levels and patchiness, and responsiveness to density-independent mortality might generate higher-order feedbacks that intricately affect the fate of individual ramets and the patterning of whole stands and communities.     

Altered Lipid Droplet Dynamics in Hepatocytes Lacking Triacylglycerol Hydrolase Expression

Lipid droplets (LDs) form from the endoplasmic reticulum (ER) and grow in size by obtaining triacylglycerols (TG). Triacylglycerol hydrolase (TGH), a lipase residing in the ER, is involved in the mobilization of TG stored in LDs for the secretion of very-low-density lipoproteins. In this study, we investigated TGH-mediated changes in cytosolic LD dynamics. We have found that TGH deficiency resulted in decreased size and increased number of LDs in hepatocytes. Using fluorescent fatty acid analogues to trace LD formation, we observed that TGH deficiency did not affect the formation of nascent LDs on the ER. However, the rate of lipid transfer into preformed LDs was significantly slower in the absence of TGH. Absence of TGH expression resulted in increased levels of membrane diacylglycerol and augmented phospholipid synthesis, which may be responsible for the delayed lipid transfer. Therefore, altered maturation (growth) rather than nascent formation (de novo synthesis) may be responsible for the observed morphological changes of LDs in TGH-deficient hepatocytes.     

Intracellular sodium sensing: SIK1 network,hormone action and high blood pressure

Sodium is the main determinant of body fluid distribution. Sodium accumulation causes water retention and, often, high blood pressure. At the cellular level, the concentration and active transport of sodium is handled by the enzyme Na⁺,K⁺-ATPase, whose appearance enabled evolving primitive cells to cope with osmotic stress and contributed to the complexity of mammalian organisms. Na⁺,K⁺-ATPase is a platform at the hub of many cellular signaling pathways related to sensing intracellular sodium and dealing with its detrimental excess. One of these pathways relies on an intracellular sodium-sensor network with the salt-inducible kinase 1 (SIK1) at its core. When intracellular sodium levels rise, and after the activation of calcium-related signals, this network activates the Na⁺,K⁺-ATPase and expel the excess of sodium from the cytosol. The SIK1 network also mediates sodium-independent signals that modulate the activity of the Na⁺,K⁺-ATPase, like dopamine and angiotensin, which are relevant per se in the development of high blood pressure. Animal models of high blood pressure, with identified mutations in components of multiple pathways, also have alterations in the SIK1 network. The introduction of some of these mutants into normal cells causes changes in SIK1 activity as well. Some cellular processes related to the metabolic syndrome, such as insulin effects on the kidney and other tissues, also appear to involve the SIK1. Therefore, it is likely that this protein, by modulating active sodium transport and numerous hormonal responses, represents a “crossroad” in the development and adaptation to high blood pressure and associated diseases.     

The nucleotide sugar transporters AtUTr1 and AtUTr3 are required for the incorporation of UDP‐glucose into the endoplasmic reticulum,are essential for pollen development and are needed for embryo sac progress in Arabidopsis thaliana

Uridine 5′‐diphosphate (UDP)‐glucose is transported into the lumen of the endoplasmic reticulum (ER), and the Arabidopsis nucleotide sugar transporter AtUTr1 has been proposed to play a role in this process; however, different lines of evidence suggest that another transporter(s) may also be involved. Here we show that AtUTr3 is involved in the transport of UDP‐glucose and is located at the ER but also at the Golgi. Insertional mutants in AtUTr3 showed no obvious phenotype. Biochemical analysis in both AtUTr1 and AtUTr3 mutants indicates that uptake of UDP‐glucose into the ER is mostly driven by these two transporters. Interestingly, the expression of AtUTr3 is induced by stimuli that trigger the unfolded protein response (UPR), a phenomenon also observed for AtUTr1, suggesting that both AtUTr1 and AtUTr3 are involved in supplying UDP‐glucose into the ER lumen when misfolded proteins are accumulated. Disruption of both AtUTr1 and AtUTr3 causes lethality. Genetic analysis showed that the atutr1 atutr3 combination was not transmitted by pollen and was poorly transmitted by the ovules. Cell biology analysis indicates that knocking out both genes leads to abnormalities in both male and female germ line development. These results show that the nucleotide sugar transporters AtUTr1 and AtUTr3 are required for the incorporation of UDP‐glucose into the ER, are essential for pollen development and are needed for embryo sac progress in Arabidopsis thaliana.     

Anticipating future conditions via trajectory sensitivity

Plants are known to be highly responsive to environmental heterogeneity and normally allocate more biomass to organs that grow in richer patches. However, recent evidence demonstrates that plants can discriminately allocate more resources to roots that develop in patches with increasing nutrient levels, even when their other roots develop in richer patches. Responsiveness to the direction and steepness of spatial and temporal trajectories of environmental variables might enable plants to increase their performance by improving their readiness to anticipated resource availabilities in their immediate proximity. Exploring the ecological implications and mechanisms of trajectory-sensitivity in plants is expected to shed new light on the ways plants learn their environment and anticipate its future challenges and opportunities.Key words: Gradient perception, phenotypic plasticity, anticipatory responses, plant behavior, plant learningNatural environments present organisms with myriad challenges of surviving and reproducing under changing conditions.¹ Depending on its extent, predictability and costs, environmental heterogeneity may select for various combinations of genetic differentiation and phenotypic plasticity.^2–6 However, phenotypic plasticity is both limited and costly.⁷ One of the main limitations of phenotypic plasticity is the lag between the perception of the environment and the time the products of the plastic responses are fully operational.⁷ For instance, the developmental time of leaves may significantly limit the adaptive value of their plastic modification due to mismatches between the radiation levels and temperatures prevailing during their development and when mature and fully functional.^8,9 Accordingly, selection is expected to promote responsiveness to cues that bear information regarding the probable future environment.^9,10Indeed, anticipatory responses are highly prevalent, if not universal, amongst living organisms. Whether through intricate cerebral processes, such as in vertebrates, nervous coordination, as in Echinoderms,¹¹ or by relatively rudimentary non-neural processes, such as in plants¹² and bacteria,¹³ accumulating examples suggest that virtually all known life forms are able to not only sense and plastically respond to their immediate environment but also anticipate probable future conditions via environmental correlations.¹⁰Perhaps the best known example of plants'' ability to anticipate future conditions is their responsiveness to spectral red/far-red cues, which is commonly tightly correlated with future probability of light competition.¹⁴ Among others, plants have been shown to respond to cues related to anticipated herbivory^15,16 and nitrogen availability.¹⁷ Imminent stress is commonly anticipated by the perception of a prevailing stress. For example, adaptation to anticipated severe stress was demonstrated to be inducted by early priming by sub-acute drought,¹⁸ root competition¹⁹ and salinity.²⁰Future conditions can also be anticipated by gradient perception: because resource and stress levels are often changing along predictable spatial and temporal trajectories, spatio-temporal dynamics of environmental variables might convey information regarding anticipated growth conditions (Fig. 1). For example, the order of changes in day length, rather than day length itself, are known to assist plants in differentiating fall from spring and thus avoid blooming in the wrong season.²¹ In addition, responsiveness to environmental gradients as such, i.e., sensitivity to the direction and steepness of environmental trajectories, independently from the stationary levels of the same factors, has been demonstrated in higher organisms, such as the perception of acceleration in contrast to velocity;²² and the dynamics of skin temperature in contrast to stationary skin temperature;²³ where the adaptive value of the second-order derivatives of environmental factors is paramount. Similar perception capabilities have also been demonstrated in rudimentary life forms such as bacteria (reviewed in refs. ¹³ and ²⁴) and plants.^25,26 Specifically, perception of environmental trajectories might assist organisms to both anticipate future conditions and better utilize the more promising patches in their immediate environment.^27,28Open in a separate windowFigure 1Trajectory sensitivity in plants. The hypothetical curves depict examples of spatio-temporal trajectories of resource availability, which might be utilized by plants to increase foraging efficiency in newly-encountered patches. When young or early-in-the-season (segment 1–2), plants are expected to allocate more resources to roots that experience the most promising (steepest increases or shallowest decreases) resource availabilities (e.g., allocating more resources to organs in INC-1 than INC-2). In addition, plants are predicted to avoid allocation to roots experiencing decreasing trajectories (DEC, segment 1–2); although temporarily more abundant with resources, such DEC patches are expected to become poorer than alternative patches in the longer run (segment 2–3).²⁹ However, responsiveness to environmental trajectories is only predicted where the expected period of resource uptake is relatively long, e.g., when plants are still active in segment 2–3, a stipulation which might not be fulfilled in e.g., short-living annuals with life span shorter than segment 1–2.In a recent study, Pisum plants have been demonstrated to be sensitive to temporal changes in nutrient availabilities. Specifically, plants allocated greater biomass to roots growing under dynamically-improving nutrient levels than to roots that grew under continuously higher, yet stationary or deteriorating, nutrient availabilities.²⁹ Allocation to roots in poorer patches might seem maladaptive if only stationary nutrient levels are accounted for, and indeed-almost invariably, plants are known to allocate more resources to organs that experience higher (non-toxic) resource levels (reviewed in ref. ³³). Accordingly, the new findings suggest that rather than merely responding to the prevailing nutrient availabilities, root growth and allocation are also responsive to trajectories of nutrient availabilities (Fig. 1).¹⁰Although Shemesh et al.²⁹ demonstrated trajectory-sensitivity of individual roots to temporal gradient of nutrient availabilities, it is likely that this sensitivity helps plants sense spatial gradients, whereby root tips perceive changes in growth conditions as they move through space.³⁴ Interestingly, because the trajectory-sensitivity was observed when whole roots were subjected to changing nutrient levels, it is likely that trajectory sensitivity in roots is based on the integration of sensory inputs perceived by yet-to-be-determined parts of the root over time, i.e., temporal sensitivity/memory (e.g. reviewed in ref. ³⁵), rather than on the integration of sensory inputs at different locations on the same individual roots (i.e., spatial sensitivity).Besides the direction of change, it is hypothesized that plants are also sensitive to the steepness of environmental trajectories (Fig. 1). This might be especially crucial in short-living annuals, which are expected to only be responsive to trajectories steep enough to be indicative of changes in growth conditions before the expected termination of the growth season (Fig. 1).Studying responsiveness to environmental variability is pivotal for understanding the ecology and evolution of any living organism. However, until recently most attention has been given to the study of responses to stationary spatial and temporal heterogeneities in growth conditions. Exploring the ecological implications and mechanisms of trajectory sensitivity in plants is expected to shed new light on the ways plants learn their immediate environment and anticipate its future challenges and opportunities.