SciCombinator

Discover the most talked about and latest scientific content & concepts.

Concept: Vector space

443

Two decades of research indicate causal associations between social relationships and mortality, but important questions remain as to how social relationships affect health, when effects emerge, and how long they last. Drawing on data from four nationally representative longitudinal samples of the US population, we implemented an innovative life course design to assess the prospective association of both structural and functional dimensions of social relationships (social integration, social support, and social strain) with objectively measured biomarkers of physical health (C-reactive protein, systolic and diastolic blood pressure, waist circumference, and body mass index) within each life stage, including adolescence and young, middle, and late adulthood, and compare such associations across life stages. We found that a higher degree of social integration was associated with lower risk of physiological dysregulation in a dose-response manner in both early and later life. Conversely, lack of social connections was associated with vastly elevated risk in specific life stages. For example, social isolation increased the risk of inflammation by the same magnitude as physical inactivity in adolescence, and the effect of social isolation on hypertension exceeded that of clinical risk factors such as diabetes in old age. Analyses of multiple dimensions of social relationships within multiple samples across the life course produced consistent and robust associations with health. Physiological impacts of structural and functional dimensions of social relationships emerge uniquely in adolescence and midlife and persist into old age.

Concepts: Epidemiology, Hypertension, Obesity, Blood pressure, Sociology, Body mass index, Old age, Vector space

226

BACKGROUND TO THE DEBATE: Tobacco continues to kill millions of people around the world each year and its use is increasing in some countries, which makes the need for new, creative, and radical efforts to achieve the tobacco control endgame vitally important. One such effort is discussed in this PLOS Medicine Debate, where Simon Chapman presents his proposal for a “smoker’s license” and Jeff Collin argues against. Chapman sets out a case for introducing a smart card license for smokers designed to limit access to tobacco products and encourage cessation. Key elements of the smoker’s license include smokers setting daily limits, financial incentives for permanent license surrender, and a test of health risk knowledge for commencing smokers. Collin argues against the proposal, saying that it would shift focus away from the real vector of the epidemic-the tobacco industry-and that by focusing on individuals it would censure victims, increase stigmatization of smokers, and marginalize the poor.

Concepts: Tobacco, English-language films, Vector space, Proposal, Focusing, Limit, Limit of a sequence, Ryan Reynolds

193

BACKGROUND TO THE DEBATE: Tobacco continues to kill millions of people around the world each year and its use is increasing in some countries, which makes the need for new, creative, and radical efforts to achieve the tobacco control endgame vitally important. One such effort is discussed in this PLOS Medicine Debate, where Simon Chapman presents his proposal for a “smoker’s license” and Jeff Collin argues against. Chapman sets out a case for introducing a smart card license for smokers designed to limit access to tobacco products and encourage cessation. Key elements of the smoker’s license include smokers setting daily limits, financial incentives for permanent license surrender, and a test of health risk knowledge for commencing smokers. Collin argues against the proposal, saying that it would shift focus away from the real vector of the epidemic-the tobacco industry-and that by focusing on individuals it would censure victims, increase stigmatization of smokers, and marginalize the poor.

Concepts: Tobacco, English-language films, Vector space, Proposal, Focusing, Limit, Limit of a sequence, Ryan Reynolds

170

Aseptic loosening of all-polyethylene glenoid components remains a limiting factor in achieving long-term implant survival in total shoulder arthroplasty (TSA). This study prospectively evaluated the functional and radiographic outcomes of patients undergoing TSA with a novel, porous, tantalum-backed glenoid component, with a minimum 2 years of follow-up.

Concepts: Vector space, Shoulder

169

SUMMARY: Pathview is a novel tool set for pathway based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway, and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines. AVAILABILITY: The package is freely available under the GPLv3 licence through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/. CONTACT: luo_weijun@yahoo.com.

Concepts: Mathematics, Integral, Vector space, Derivative, Functional analysis

144

Primary fibroblasts from a high grade steatosis patient were reprogrammed by transduction of retroviruses OCT4, SOX2, c-MYC and KLF4. IPSCs were characterized by immunocytochemistry, embryoid body-formation, DNA-fingerprint, karyotype analysis and comparative transcriptome analyses with the human embryonic stem cell line H1 revealed a Pearsons correlation coefficient of 0.9287. Resource table.

Concepts: Cell, Stem cell, Stem cells, Cell biology, Cellular differentiation, Embryonic stem cell, Vector space, Transcription factors

141

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Concepts: Algorithm, Vector space, Problem solving, Computational complexity theory, Delaunay triangulation, Spanning tree protocol, Heuristic, Wireless sensor network

139

As a specific kind of non-Euclidean metric lies in projective space, Cayley-Klein metric has been recently introduced in metric learning to deal with the complex data distributions in computer vision tasks. In this paper, we extend the original Cayley-Klein metric to the multiple Cayley-Klein metric, which is defined as a linear combination of several Cayley-Klein metrics. Since Cayley-Klein is a kind of non-linear metric, its combination could model the data space better, thus lead to an improved performance. We show how to learn a multiple Cayley-Klein metric by iterative optimization over single Cayley-Klein metric and their combination coefficients under the objective to maximize the performance on separating inter-class instances and gathering intra-class instances. Our experiments on several benchmarks are quite encouraging.

Concepts: Fundamental physics concepts, Vector space, Machine learning, Computer, Computer program, Knowledge, Optimization, Machine code

67

To determine whether trial publications of glucose lowering drugs are dominated by a small group of highly prolific authors (“supertrialists”) and to identify some of their characteristics.

Concepts: Insulin, Diabetes mellitus, Glucose, Blood sugar, Algebraic structure, Vector space, Field, Ring

42

In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) - a dimensionality reduction technique - to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor dimensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner. We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures.

Concepts: Dimension, Euclidean space, Vector space, Space, Spacetime, Linear algebra, Real number, Point