Maternal urinary metabolic signatures of fetal growth and associated clinical and environmental factors in the INMA study

Background Maternal metabolism during pregnancy is a major determinant of the intra-uterine environment and fetal outcomes. Herein, we characterize the maternal urinary metabolome throughout pregnancy to identify maternal metabolic signatures of fetal growth in two subcohorts and explain potential sources of variation in metabolic profiles based on lifestyle and clinical data. Methods We used 1H nuclear magnetic resonance (NMR) spectroscopy to characterize maternal urine samples collected in the INMA birth cohort at the first (n = 412 and n = 394, respectively, in Gipuzkoa and Sabadell cohorts) and third trimesters of gestation (n = 417 and 469). Metabolic phenotypes that reflected longitudinal intra- and inter-individual variation were used to predict measures of fetal growth and birth weight. Results A metabolic shift between the first and third trimesters of gestation was characterized by 1H NMR signals arising predominantly from steroid by-products. We identified 10 significant and reproducible metabolic associations in the third trimester with estimated fetal, birth, and placental weight in two independent subcohorts. These included branched-chain amino acids; isoleucine, valine, leucine, alanine and 3 hydroxyisobutyrate (metabolite of valine), which were associated with a significant fetal weight increase at week 34 of up to 2.4 % in Gipuzkoa (P < 0.005) and 1 % in Sabadell (P < 0.05). Other metabolites included pregnancy-related hormone by-products of estrogens and progesterone, and the methyl donor choline. We could explain a total of 48–53 % of the total variance in birth weight of which urine metabolites had an independent predictive power of 12 % adjusting for all other lifestyle/clinical factors. First trimester metabolic phenotypes could not predict reproducibly weight at later stages of development. Physical activity, as well as other modifiable lifestyle/clinical factors, such as coffee consumption, vitamin D intake, and smoking, were identified as potential sources of metabolic variation during pregnancy. Conclusions Significant reproducible maternal urinary metabolic signatures of fetal growth and birth weight are identified for the first time and linked to modifiable lifestyle factors. This novel approach to prenatal screening, combining multiple risk factors, present a great opportunity to personalize pregnancy management and reduce newborn disease risk in later life

Electronic sculpting of ligand-GPCR subtype selectivity:the case of angiotensin II

GPCR subtypes possess distinct functional and pharmacological profiles, and thus development of subtype-selective ligands has immense therapeutic potential. This is especially the case for the angiotensin receptor subtypes AT1R and AT2R, where a functional negative control has been described and AT2R activation highlighted as an important cancer drug target. We describe a strategy to fine-tune ligand selectivity for the AT2R/AT1R subtypes through electronic control of ligand aromatic-prolyl interactions. Through this strategy an AT2R high affinity (<i>K</i>_i = 3 nM) agonist analogue that exerted 18,000-fold higher selectivity for AT2R versus AT1R was obtained. We show that this compound is a negative regulator of AT1R signaling since it is able to inhibit MCF-7 breast carcinoma cellular proliferation in the low nanomolar range

Child-rearing With Minimal Domination: A Republican Account

Parenting involves an extraordinary degree of power over children. Republicans are concerned about domination, which, on one view, is the holding of power that fails to track the interests of those over whom it is exercised. On this account, parenting as we know it is dominating due to the low standards necessary for acquiring and retaining parental rights and the extent of parental power. Domination cannot be fully eliminated from child-rearing without unacceptable loss of value. Most likely, republicanism requires that we minimise children’s domination. I examine alternative models of child-rearing that are immune to republican criticism

Physical-based optimization for non-physical image dehazing methods

Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied. Some of the most successful image dehazing algorithms are based on image processing methods but do not follow any physical image formation model, which limits their performance. In this paper, we propose a post-processing technique to alleviate this handicap by enforcing the original method to be consistent with a popular physical model for image formation under haze. Our results improve upon those of the original methods qualitatively and according to several metrics, and they have also been validated via psychophysical experiments. These results are particularly striking in terms of avoiding over-saturation and reducing color artifacts, which are the most common shortcomings faced by image dehazing methods

Low-Density Parity-Check Codes for Nonergodic Block-Fading Channels

We solve the problem of designing powerful low-density parity-check (LDPC) codes with iterative decoding for the block-fading channel. We first study the case of maximum-likelihood decoding, and show that the design criterion is rather straightforward. Unfortunately, optimal constructions for maximum-likelihood decoding do not perform well under iterative decoding. To overcome this limitation, we then introduce a new family of full-diversity LDPC codes that exhibit near-outage-limit performance under iterative decoding for all block-lengths. This family competes with multiplexed parallel turbo codes suitable for nonergodic channels and recently reported in the literature.Comment: Submitted to the IEEE Transactions on Information Theor

The effects of death and post-mortem cold ischemia on human tissue transcriptomes

Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.Peer ReviewedPostprint (published version

Children's Vulnerability and Legitimate Authority Over Children

Children's vulnerability gives rise to duties of justice towards children and determines when authority over them is legitimately exercised. I argue for two claims. First, children's general vulnerability to objectionable dependency on their caregivers entails that they have a right not to be subject to monopolies of care, and therefore determines the structure of legitimate authority over them. Second, children's vulnerability to the loss of some special goods of childhood determines the content of legitimate authority over them. My interest is in the so-far little-discussed goods of engaging in world discovery, artistic creation, philosophical pursuits and experimentation with one's self. I call these ‘special goods of childhood’ because individuals, in general, only have full access to them during childhood and they make a distinctive and weighty contribution to wellbeing. Therefore, they are part of the metric of justice towards children. The overall conclusion is that we ought to make good institutional care part of every child's upbringing

Monitoring CD27 expression to evaluate Mycobacterium tuberculosis activity in HIV-1 infected individuals in vivo.

The level of bacterial activity is only poorly defined during asymptomatic Mycobacterium tuberculosis (MTB) infection. The objective was to study the capacity of a new biomarker, the expression of the T cell maturation marker CD27 on MTB-specific CD4 T cells, to identify active tuberculosis (TB) disease in subjects from a MTB and HIV endemic region. The frequency and CD27 expression of circulating MTB-specific CD4 T cells was determined in 96 study participants after stimulation with purified protein derivative (PPD) using intracellular cytokine staining for IFNgamma (IFNγ). Subjects were then stratified by their TB and HIV status. Within PPD responders, a CD27(-) phenotype was associated with active TB in HIV(-) (p = 0.0003) and HIV(+) (p = 0.057) subjects, respectively. In addition, loss of CD27 expression preceded development of active TB in one HIV seroconverter. Interestingly, in contrast to HIV(-) subjects, MTB-specific CD4 T cell populations from HIV(+) TB-asymptomatic subjects were often dominated by CD27(-) cells. These data indicate that down-regulation of CD27 on MTB-specific CD4 T cell could be used as a biomarker of active TB, potentially preceding clinical TB disease. Furthermore, these data are consistent with the hypothesis that late, chronic HIV infection is frequently associated with increased mycobacterial activity in vivo. The analysis of T cell maturation and activation markers might thus be a useful tool to monitor TB disease progression

Towards a Collision-Free WLAN: Dynamic Parameter Adjustment in CSMA/E2CA

Carrier Sense Multiple Access with Enhanced Collision Avoidance (CSMA/ECA) is a distributed MAC protocol that allows collision-free access to the medium in WLAN. The only difference between CSMA/ECA and the well-known CSMA/CA is that the former uses a deterministic backoff after successful transmissions. Collision-free operation is reached after a transient state during which some collisions may occur. This article shows that the duration of the transient state can be shortened by appropriately setting the contention parameters. Standard absorbing Markov Chain theory can be used to describe the behaviour of the system in the transient state and to predict the expected number of slots to reach the collision-free operation. The article also introduces CSMA/E2CA, in which a deterministic backoff is used two consecutive times after a successful transmission. CSMA/E2CA converges quicker to collision-free operation and delivers higher performance than CSMA/CA in harsh wireless scenarios with high frame error rates. To achieve collision-free operations when the number of contenders is large, it may be necessary to dynamically adjust the contention parameter. The last part of the article suggests an approach for such parameter adjustment which is validated by simulation results

Reconstructing dynamical networks via feature ranking

Empirical data on real complex systems are becoming increasingly available. Parallel to this is the need for new methods of reconstructing (inferring) the topology of networks from time-resolved observations of their node-dynamics. The methods based on physical insights often rely on strong assumptions about the properties and dynamics of the scrutinized network. Here, we use the insights from machine learning to design a new method of network reconstruction that essentially makes no such assumptions. Specifically, we interpret the available trajectories (data) as features, and use two independent feature ranking approaches -- Random forest and RReliefF -- to rank the importance of each node for predicting the value of each other node, which yields the reconstructed adjacency matrix. We show that our method is fairly robust to coupling strength, system size, trajectory length and noise. We also find that the reconstruction quality strongly depends on the dynamical regime