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.

Individualized fetal growth assessment: critical evaluation of key concepts in the specification of third trimester size trajectories.

Abstract: Objectives: To characterize second and third trimester fetal growth using Individualized Growth Assessment methods in a larger cohort of fetuses with normal neonatal growth outcomes.Methods: A prospective longitudinal study of 119 pregnancies was performed from 18 weeks, MA, to delivery. Measurements of several 1D and 3D fetal size parameters were obtained from 3D volume data sets at 3–4 week intervals. Regression analyses were used to determine Start Points (SP) and Rossavik model (P = c {t} k + st) coefficients c. k and s for each parameter in each fetus. Second trimester growth velocity reference ranges were determined and size model specification functions re-established, the latter used to generate individual size models. Actual measurements were compared to predicted third trimester size trajectories using Percent Deviations. New age-specific reference ranges for the Percent Deviations of each parameter were defined using 2-level statistical modeling.Results: Rossavik models fit the data for...

The origin of amniotic fluid monocytes/macrophages in women with intra-amniotic inflammation or infection

Abstract: Background Monocytes, after neutrophils, are the most abundant white blood cells found in the amniotic cavity of women with intra-amniotic inflammation/infection. However, the origin of such cells has not been fully investigated. Herein, we determined (1) the origin of amniotic fluid monocytes/macrophages from women with intra-amniotic inflammation/infection, (2) the relationship between the origin of amniotic fluid monocytes/macrophages and preterm or term delivery and (3) the localization of monocytes/macrophages in the placental tissues. Methods Amniotic fluid samples (n = 16) were collected from women with suspected intra-amniotic inflammation or infection. Amniotic fluid monocytes/macrophages were purified by fluorescence-activated cell sorting, and DNA fingerprinting was performed. Blinded placental histopathological evaluations were conducted. Immunohistochemistry was performed to detect CD14+ monocytes/macrophages in the placental tissues. Results DNA fingerprinting revealed that (1) 56.25% (9/16) of amniotic fluid samples had mostly fetal monocytes/macrophages, (2) 37.5% (6/16) had predominantly maternal monocytes/macrophages and (3) one sample (6.25% [1/16]) had a mixture of fetal and maternal monocytes/macrophages. (4) Most samples with predominantly fetal monocytes/macrophages were from women who delivered early preterm neonates (77.8% [7/9]), whereas all samples with mostly maternal monocytes/macrophages or a mixture of both were from women who delivered term or late preterm neonates (100% [7/7]). (5) Most of the women included in this study presented acute maternal and fetal inflammatory responses in the placenta (85.7% [12/14]). (6) Women who had mostly fetal monocytes/macrophages in amniotic fluid had abundant CD14+ cells in the umbilical cord and chorionic plate, whereas women with mostly maternal amniotic fluid monocytes/macrophages had abundant CD14+ cells in the chorioamniotic membranes. Conclusion Amniotic fluid monocytes/macrophages can be of either fetal or maternal origin, or a mixture of both, in women with intra-amniotic inflammation or infection. These immune cells could be derived from the fetal and maternal vasculature of the placenta.

A system biology approach for the steady-state analysis of gene signaling networks

Abstract: The existing approaches used to identify the relevant pathways in a given condition do not consider a number of important biological factors such as magnitude of each gene's expression change, their position and interactions in the given pathways, etc. Recently, an impact analysis approach was proposed that considers these crucial biological factors to analyze regulatory pathways at systems biology level. This approach calculates perturbations induced by each gene in a pathway, and propagates them through the entire pathway to compute an impact factor for the given pathway. Here we propose an alternative approach that uses a linear system to compute the impact factor. Our proposed approach eliminates the possible stability problems when the perturbations are propagated through a pathway that contains positive feedback loops. Additionally, the proposed approach is able to consider the type of genes when calculating the impact factors.

Maternal and fetal T cells in term pregnancy and preterm labor.

Abstract: Pregnancy is a state of immunological balance during which the mother and the developing fetus must tolerate each other while maintaining sufficient immunocompetence to ward off potential threats. The site of closest contact between the mother and fetus is the decidua, which represents the maternal–fetal interface. Many of the immune cell subsets present at the maternal–fetal interface have been well described; however, the importance of the maternal T cells in this compartment during late gestation and its complications, such as preterm labor and birth, has only recently been established. Moreover, pioneer and recent studies have indicated that fetal T cells are activated in different subsets of preterm labor and may elicit distinct inflammatory responses in the amniotic cavity, leading to preterm birth. In this review, we describe the established and proposed roles for maternal T cells at the maternal–fetal interface in normal term parturition, as well as the demonstrated contributions of such cells to the pathological process of preterm labor and birth. We also summarize the current knowledge of and proposed roles for fetal T cells in the pathophysiology of the preterm labor syndrome. It is our hope that this review provides a solid conceptual framework highlighting the importance of maternal and fetal T cells in late gestation and catalyzes new research questions that can further scientific understanding of these cells and their role in preterm labor and birth, the leading cause of neonatal mortality and morbidity worldwide.

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.