The impact of gene transfer techniques in eukaryotic cell biology. Berlin, Heidelberg, New York, Tokyo: Springer-Verlag, 1984. 209 S., 76 Abb., 96 DM

1986 ◽  
Vol 6 (1) ◽  
pp. 44-44
Author(s):  
E. Spanier
Keyword(s):  
New York ◽  
Gene Transfer ◽  
Cell Biology ◽  
Eukaryotic Cell ◽  
The Impact ◽  
Gene Transfer Techniques

Roundtable Discussion of the Impact of the 4th World Symposium on Pulmonary Hypertension

2009 ◽  
Vol 8 (2) ◽  
pp. 89-94
Author(s):  
Robyn J. Barst ◽  
Marc Humbert ◽  
Ivan M. Robbins ◽  
Lewis J. Rubin ◽  
Robyn J. Park
Keyword(s):  
New York ◽  
Pulmonary Hypertension ◽  
Vascular Diseases ◽  
Assistant Professor ◽  
Associate Professor ◽  
Future Research ◽  
Columbia University ◽  
School Of Medicine ◽  
Maryland School ◽  
The Impact

A discussion among attendees of the 4th World Symposium on Pulmonary Hypertension took place to share “an insider's look” into the current and future research and treatment implications in pulmonary hypertension. Myung H. Park, MD, guest editor of this issue of Advances in Pulmonary Hypertension, Assistant Professor of Medicine and Director, Pulmonary Vascular Diseases Program, Division of Cardiology, University of Maryland School of Medicine, Baltimore, moderated the discussion. Participants included Robyn Barst, MD, Professor Emerita, Columbia University, New York; Marc Humbert, MD, PhD, Universite Paris-Sud, French Referal Center for Pulmonary Hypertension, Hopital Antoine-Beclere, Assistance Publique Hopitaux de Paris, Clamart, France; Ivan Robbins, MD, Associate Professor of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee; and Lewis J. Rubin, MD, Clinical Professor, Department of Medicine, University of California, San Diego.

The Impact of Translational Research in Breast Cancer Care: Can we Improve the Therapeutic Scenario?

2018 ◽  
Vol 18 (6) ◽  
pp. 832-836
Author(s):  
Giuseppe Buono ◽  
Francesco Schettini ◽  
Francesco Perri ◽  
Grazia Arpino ◽  
Roberto Bianco ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Translational Research ◽  
Cell Biology ◽  
Cancer Biology ◽  
Hormone Receptors ◽  
Treatment Strategies ◽  
Growth Factor Receptor ◽  
Molecular Heterogeneity ◽  
Therapeutic Implications ◽  
The Impact

Traditionally, breast cancer (BC) is divided into different subtypes defined by immunohistochemistry (IHC) according to the expression of hormone receptors and overexpression/amplification of human epidermal growth factor receptor 2 (HER2), with crucial therapeutic implications. In the last few years, the definition of different BC molecular subgroups within the IHC-defined subtypes and the identification of the important role that molecular heterogeneity can play in tumor progression and treatment resistance have inspired the search for personalized therapeutic approaches. In this scenario, translational research represents a key strategy to apply knowledge from cancer biology to the clinical setting, through the study of all the tumors “omics”, including genomics, transcriptomics, proteomics, epigenomics, and metabolomics. Importantly, the introduction of new high-throughput technologies, such as next generation sequencing (NGS) for the study of cancer genome and transcriptome, greatly amplifies the potential and the applications of translational research in the oncology field. Moreover, the introduction of new experimental approaches, such as liquid biopsy, as well as new-concept clinical trials, such as biomarker-driven adaptive studies, may represent a turning point for BC translational research. </P><P> It is likely that translational research will have in the near future a significant impact on BC care, especially by giving us the possibility to dissect the complexity of tumor cell biology and develop new personalized treatment strategies.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

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