Massachusetts Institute of Technology

About: Massachusetts Institute of Technology is a education organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Laser. The organization has 116795 authors who have published 268000 publications receiving 18272025 citations. The organization is also known as: MIT & M.I.T..

Alternative energy technologies

Abstract: Fossil fuels currently supply most of the world's energy needs, and however unacceptable their long-term consequences, the supplies are likely to remain adequate for the next few generations. Scientists and policy makers must make use of this period of grace to assess alternative sources of energy and determine what is scientifically possible, environmentally acceptable and technologically promising.

A Perspective on Cancer Cell Metastasis

Abstract: Metastasis causes most cancer deaths, yet this process remains one of the most enigmatic aspects of the disease. Building on new mechanistic insights emerging from recent research, we offer our perspective on the metastatic process and reflect on possible paths of future exploration. We suggest that metastasis can be portrayed as a two-phase process: The first phase involves the physical translocation of a cancer cell to a distant organ, whereas the second encompasses the ability of the cancer cell to develop into a metastatic lesion at that distant site. Although much remains to be learned about the second phase, we feel that an understanding of the first phase is now within sight, due in part to a better understanding of how cancer cell behavior can be modified by a cell-biological program called the epithelial-to-mesenchymal transition.

Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia

Abstract: BACKGROUND—Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined The relationships between patterns of mutations and epigenetic phenotypes are not yet clear METHODS—We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis RESULTS—AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes Of these, an average of 5 are in genes that are recurrently mutated in AML A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcriptionfactor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumorsuppressor genes (16%), DNA-methylation–related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%) Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories CONCLUSIONS—We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification (Funded by the National Institutes of Health) The molecular pathogenesis of acute myeloid leukemia (AML) has been studied with the use of cytogenetic analysis for more than three decades Recurrent chromosomal structural variations are well established as diagnostic and prognostic markers, suggesting that acquired genetic abnormalities (ie, somatic mutations) have an essential role in pathogenesis 1,2 However, nearly 50% of AML samples have a normal karyotype, and many of these genomes lack structural abnormalities, even when assessed with high-density comparative genomic hybridization or single-nucleotide polymorphism (SNP) arrays 3-5 (see Glossary) Targeted sequencing has identified recurrent mutations in FLT3, NPM1, KIT, CEBPA, and TET2 6-8 Massively parallel sequencing enabled the discovery of recurrent mutations in DNMT3A 9,10 and IDH1 11 Recent studies have shown that many patients with

Identification of Causal Effects Using Instrumental Variables

Abstract: We outline a framework for causal inference in settings where assignment to a binary treatment is ignorable, but compliance with the assignment is not perfect so that the receipt of treatment is nonignorable. To address the problems associated with comparing subjects by the ignorable assignment—an “intention-to-treat analysis”—we make use of instrumental variables, which have long been used by economists in the context of regression models with constant treatment effects. We show that the instrumental variables (IV) estimand can be embedded within the Rubin Causal Model (RCM) and that under some simple and easily interpretable assumptions, the IV estimand is the average causal effect for a subgroup of units, the compliers. Without these assumptions, the IV estimand is simply the ratio of intention-to-treat causal estimands with no interpretation as an average causal effect. The advantages of embedding the IV approach in the RCM are that it clarifies the nature of critical assumptions needed for a...