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..

MicroRNAs in plants

Abstract: The present invention generally relates to the production and expression of microRNA (miRNA) in plants. In some cases, production and expression of miRNA can be used to at least partially inhibit or alter gene expression in plants. For instance, in some embodiments, a nucleotide sequence, which may encode a sequence substantially complementary to a gene to be inhibited or otherwise altered, may be prepared and inserted into a plant cell. Expression of the nucleotide sequence may cause the formation of precursor miRNA, which may, in turn, be cleaved (for example, with Dicer or other nucleases, including, for example, nucleases associated with RNA interference), to produce an miRNA sequence substantially complementary to the gene. The miRNA sequence may then interact with the gene (e.g., complementary binding) to inhibit the gene. In some cases, the nucleotide sequence may be an isolated nucleotide sequence. Other embodiments of the invention are directed to the precursor miRNA and/or the final miRNA sequence, as well as methods of making, promoting, and use thereof.

X-Ray Properties of Black-Hole Binaries

Abstract: We review the properties and behavior of 20 X-ray binaries that contain a dynamically-confirmed black hole, 17 of which are transient systems. During the past decade, many of these transien...

Toward machine emotional intelligence: analysis of affective physiological state

Abstract: The ability to recognize emotion is one of the hallmarks of emotional intelligence, an aspect of human intelligence that has been argued to be even more important than mathematical and verbal intelligences. This paper proposes that machine intelligence needs to include emotional intelligence and demonstrates results toward this goal: developing a machine's ability to recognize the human affective state given four physiological signals. We describe difficult issues unique to obtaining reliable affective data and collect a large set of data from a subject trying to elicit and experience each of eight emotional states, daily, over multiple weeks. This paper presents and compares multiple algorithms for feature-based recognition of emotional state from this data. We analyze four physiological signals that exhibit problematic day-to-day variations: The features of different emotions on the same day tend to cluster more tightly than do the features of the same emotion on different days. To handle the daily variations, we propose new features and algorithms and compare their performance. We find that the technique of seeding a Fisher Projection with the results of sequential floating forward search improves the performance of the Fisher Projection and provides the highest recognition rates reported to date for classification of affect from physiology: 81 percent recognition accuracy on eight classes of emotion, including neutral.

A framework for human microbiome research

Abstract: A variety of microbial communities and their genes (microbiome) exist throughout the human body, playing fundamental roles in human health and disease. The NIH funded Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 to 18 body sites up to three times, which to date, have generated 5,177 microbial taxonomic profiles from 16S rRNA genes and over 3.5 Tb of metagenomic sequence. In parallel, approximately 800 human-associated reference genomes have been sequenced. Collectively, these data represent the largest resource to date describing the abundance and variety of the human microbiome, while providing a platform for current and future studies.

DNA replication in eukaryotic cells

Abstract: ▪ Abstract The maintenance of the eukaryotic genome requires precisely coordinated replication of the entire genome each time a cell divides. To achieve this coordination, eukaryotic cells use an ordered series of steps to form several key protein assemblies at origins of replication. Recent studies have identified many of the protein components of these complexes and the time during the cell cycle they assemble at the origin. Interestingly, despite distinct differences in origin structure, the identity and order of assembly of eukaryotic replication factors is highly conserved across all species. This review describes our current understanding of these events and how they are coordinated with cell cycle progression. We focus on bringing together the results from different organisms to provide a coherent model of the events of initiation. We emphasize recent progress in determining the function of the different replication factors once they have been assembled at the origin.