We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

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Model-based Analysis of ChIP-Seq (MACS)

Ferroptosis: An Iron-Dependent Form of Nonapoptotic Cell Death

March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association

Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.

Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. 

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …

Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

MAP3K7 and CHD1 Are Novel Mediators of Resistance to Oncolytic Vesicular Stomatitis Virus in Prostate Cancer Cells.

BACKGROUND: Tumor associated macrophages (TAMS) have been suggested to be key players in the tumor microenvironment. The M2 activation phenotype is believed to be the predominant TAM phenotype in solid tumors. To further define the role of M2 TAMs and analyze the cross-talk between tumor cells and TAMs, we examined the presence of macrophage markers in glioblastoma (GBM) tumors, their responses to various treatments, the genetic profile of M2 macrophages and also potential mediators of tumor cells communication with TAMs. METHODS: GBM tumor specimens were assayed for macrophage/microglia and M2 activation markers via immunohistochemistry and immunofluorescence. GBM tumor lysates and glioma tumor cell lines were assayed for M2 macrophage activation markers, CD163, CD204 and CD206 via immunoblotting. Gene expression analysis in a THP-1 model of macrophages was performed using Affymetrix Human Gene 1.0 ST Array. Proteins released by GBM cells were analyzed by mass spectrometry (LC-MS). Cells were cultured under various conditions of hypoxia or stem-like cells promoting or they were exposed to irradiation. RESULTS: Pan-macrophage CD68, microglia CD11b, and monocyte marker CD14 were all readily detected in GBM. CD163 + , CD204 + , and CD206+ cells were found to be richly present throughout GBM tumors. To confirm the M2 activation phenotype marker expression pattern, THP-1 monocytic cells model polarized by IL-4/IL-13 expressed CD163, CD204 and CD206. We also isolated the CD163+ cells from the resected specimens that, interestingly, expressed also an astrocytic cell marker, GFAP. Unexpectedly, GBM cells in culture were also found to express macrophage markers. Macrophage markers expression was differential in response to hypoxia, stem-like cells conditions and irradiation. In situ staining of GBM tumor specimens showed the co-localization of M2 macrophage markers and GFAP. We also found two groups of gene expression patterns in THP-1 M2 macrophages that differ from M1 and M0 types, with potential individual candidates for new M2 and also M1 markers. Among the proteins specifically picked by LC-MS, several are known to be associated with activated astrocytes (CTGF), immune cells (CCL2) or other stromal cells (periostin), and to some extent with tumor cells. CONCLUSIONS: GBM cells express macrophage activation markers CD163, CD204 and CD206, which is a novel observation. This finding implies the existence of a subset of GBM cells with a potential important functional role in the tumor microenvironment. Also, more specific markers for M2 macrophages are needed. Moreover, GBM cells release an abundance of factors enabling communication with TAMs. SECONDARY CATEGORY: Immunobiology & Immunotherapy.

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Functional presence of m2 macrophage markers in gbm tumor cells

Multimodal Assessment of Estrogen Receptor mRNA Profiles to Quantify Estrogen Pathway Activity in Breast Tumors.

It is provided a method of designing oligonucleotide probe(s) for nucleic acid detection comprising the following steps in any order: (i) identifying and selecting region(s) of a target nucleic acid to be amplified, the region(s) having an efficiency of amplification (AE) higher than the average AE; and (ii) designing oligonucleotide probe(s) capable of hybridizing to the selected region(s). It is also provided a method of detecting at least one target nucleic acid comprising the steps of: (i) providing a biological sample; (ii) amplifying the nucleic acid(s) of the biological sample; (iii) providing at least an oligonucleotide probe capable of hybridizing to at least a target nucleic acid, if present in the biological sample; and (iv) contacting the probe(s) with the amplified nucleic acids and detecting the probe(s) hybridized to the target nucleic acid(s). In particular, the method indicates the presence of at least a pathogen, for example a virus, in a human biological sample. The probes may be placed on a support, for example a microarray or a biochip.

Method of probe design and/or of nucleic acids detection

The invention provides an in vitro method for predicting clinical outcome of a patient affected with a non-small cell lung carcinoma (NSCLC), which method comprises determining the expression level of at least 8 genes in a biological sample of said patient.

Lance D. Miller

Papers

MAP3K7 and CHD1 Are Novel Mediators of Resistance to Oncolytic Vesicular Stomatitis Virus in Prostate Cancer Cells.

Functional presence of m2 macrophage markers in gbm tumor cells

Multimodal Assessment of Estrogen Receptor mRNA Profiles to Quantify Estrogen Pathway Activity in Breast Tumors.

Method of probe design and/or of nucleic acids detection

A method for predicting clinical outcome of patients with non-small cell lung carcinoma