Roberto Romero

Bio: Roberto Romero is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Amniotic fluid & Chorioamnionitis. The author has an hindex of 151, co-authored 1516 publications receiving 108321 citations. Previous affiliations of Roberto Romero include University of Michigan & Weizmann Institute of Science.

The maternal plasma soluble vascular endothelial growth factor receptor-1 concentration is elevated in SGA and the magnitude of the increase relates to Doppler abnormalities in the maternal and fetal circulation.

Abstract: Objectives. The soluble form of vascular endothelial growth factor receptor-1 (sVEGFR-1), an antagonist to vascular endothelial growth factor and placental growth factor, has been implicated in the pathophysiology of preeclampsia. Preeclampsia and pregnancy complicated with small for gestational age (SGA) fetuses share some pathophysiologic derangements, such as failure of physiologic transformation of the spiral arteries, endothelial cell dysfunction, and leukocyte activation. The objectives of this study were to: (1) determine whether plasma concentrations of sVEGFR-1 in mothers with SGA fetuses without preeclampsia at the time of diagnosis are different from those in patients with preeclampsia or normal pregnant women, and (2) examine the relationship between plasma concentrations of sVEGFR-1 and Doppler velocimetry in uterine and umbilical arteries in patients with preeclampsia and those with SGA.Study design. A cross-sectional study was conducted to determine the concentrations of the soluble form of...

Macrophage Inflammatory Protein‐1α in Term and Preterm Parturtition: Effect of Microbial Invasion of the Amniotic Cavity

Abstract: PROBLEM This study was conducted to determine whether: (1) gestational age, parturition, and microbial invasion of the amniotic cavity (MIAC) are associated with changes in amniotic fluid concentrations of immunoreactive macrophage inflammatory protein-1 alpha; (2) amniotic fluid concentrations of macrophage inflammatory protein-1 alpha are correlated with the white blood cell count and the concentrations of interleukin-8 in amniotic fluid. METHOD Amniotic fluid was retrieved by amniocentesis from 126 patients; 54 women with preterm labor and intact membranes (no MIAC-delivery at term, N = 21; no MIAC-preterm delivery, N = 16; MIAC-preterm delivery, N = 17); 62 patients at term (no labor, N = 19; labor-no MIAC, N = 20; labor-MIAC, N = 23); and 10 patients in the midtrimester of pregnancy. Amniotic fluid was cultured for aerobic, anaerobic and Mycoplasma species. Determinations of amniotic fluid macrophage inflammatory protein-1 alpha and interleukin-8 were performed with immunoassays validated for amniotic fluid (sensitivity: 14.2 pg/ml and 0.3 ng/ml, respectively). Kruskal-Wallis analysis of variance (ANOVA) for censored data, Mann-Whitney U test and Spearman's rank correlation were performed for analysis. RESULTS 1) Amniotic fluid macrophage inflammatory protein-1 alpha was present in only 31.0% (9/29) of patients not in labor (midtrimester and term). 2) Patients with preterm labor and MIAC had higher amniotic fluid concentrations of macrophage inflammatory protein-1 alpha than those without MIAC (no MIAC-delivery at term: median 0.0 pg/ml, range 0.0-221.2; no MIAC-preterm delivery: median 37.4 pg/ml, range 0.0-494.6; MIAC-preterm delivery: median 7171.0 pg/ml, range 402.5-37994.0; P < 0.00001). 3) Among patients at term, MIAC was associated with higher concentrations of amniotic fluid macrophage inflammatory protein-1 alpha than patients without MIAC (no labor: median 0.0 pg/ml, range 0.0-25.6; labor-no MIAC: median 16.7 pg/ml, range 0.0-161.6; labor-MIAC: median 103.8 pg/ml, range 0.0-4349.0, P < 0.001). 4) Among patients in preterm labor, a strong correlation was found between amniotic fluid concentrations of macrophage inflammatory protein-1 alpha and interleukin-8 (r = 0.9, P < 0.00001) and between amniotic fluid macrophage inflammatory protein-1 alpha concentrations and amniotic fluid white blood cell count (r = 0.6, P < 0.0001). CONCLUSIONS (1) Macrophage inflammatory protein-1 alpha is undetectable in most amniotic fluid samples from patients in the midtrimester of pregnancy and at term not in labor. (2) Microbial invasion of the amniotic cavity is associated with increased concentrations of immunoreactive amniotic fluid macrophage inflammatory protein-1 alpha in both term and preterm gestations. (3) Amniotic fluid macrophage inflammatory protein-1 alpha concentrations significantly correlate with interleukin-8 levels and white blood cell count in amniotic fluid. Our data strongly suggest a role for macrophage inflammatory protein-1 alpha in the mechanisms responsible for the recruitment of leukocytes into the amniotic cavity during the course of intrauterine infection.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.