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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.


Papers
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Journal ArticleDOI
TL;DR: The results provide a basis for the clinical impression that the onset of labor in women with preterm premature rupture of the membranes is associated with a subclinical intraamniotic infection.

351 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated the relationship between the local expression of cytokines and periventricular leukomalacia, a common neonatal brain white matter lesion, and determined whether high expression of tumor necrosis factor-α, interleukin-1β, and interleuxin-6 was observed in these lesions.

346 citations

Journal ArticleDOI
TL;DR: It is concluded that neutrophil attractant/activating peptide-1/interleukin-8 is part of the host response to microbial invasion of the amniotic cavity and that increasedAmniotic fluid availability of this cytokine occurs in term and preterm parturition.

343 citations

Journal ArticleDOI
TL;DR: The role of infection in the pathogenesis of preterm labor and delivery, and the specific mechanisms through which this association is demonstrated are presented are presented.

342 citations

Journal ArticleDOI
TL;DR: In this article, the concentrations of sVEGFR-1 in plasma of pre-eclamptic patients change prior to the clinical manifestations of the disease and correlates with the severity of the diseases.
Abstract: Objective: Accumulating evidence suggests that the balance between vascular endothelial growth factor (VEGF), placental growth factor (PlGF), and their receptors is important for effective vasculogenesis, angiogenesis, and placental development. Recently, the soluble form of VEGFR-1 (sVEGFR-1), an antagonist to VEGF and PlGF, has been implicated in the pathophysiology of pre-eclampsia. Plasma sVEGFR-1 concentration is elevated in pre-eclampsia at the time of clinical diagnosis and correlates with the severity of the disease. The purpose of this study was to determine whether the concentrations of sVEGFR-1 in plasma of pre-eclamptic patients change prior to the clinical manifestations of the disease.Methods: A longitudinal case-control study was conducted in normal pregnant women (n = 44) and patients with pre-eclampsia (n = 44). Blood sampling was performed at six intervals: (1) 7–16 weeks; (2) 16–24 weeks; (3) 24–28 weeks; (4) 28–32 weeks; (5) 32–36 weeks; and (6) more than 37 weeks of gestation. To exam...

339 citations


Cited by
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Journal ArticleDOI
TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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.

22,147 citations

Journal ArticleDOI
TL;DR: The latest version of STRING more than doubles the number of organisms it covers, and offers 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.
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/.

10,584 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
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.

10,124 citations

01 Jan 2014
TL;DR: 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.
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.

9,618 citations

Journal ArticleDOI
TL;DR: A short cervical length and a raised cervical-vaginal fetal fibronectin concentration are the strongest predictors of spontaneous preterm birth.

6,275 citations