673 research outputs found
Mitochondrial DNA, chloroplast DNA and the origins of development in eukaryotic organisms
<p>Abstract</p> <p>Background</p> <p>Several proposals have been made to explain the rise of multicellular life forms. An internal environment can be created and controlled, germ cells can be protected in novel structures, and increased organismal size allows a "division of labor" among cell types. These proposals describe advantages of multicellular versus unicellular organisms at levels of organization at or above the individual cell. I focus on a subsequent phase of evolution, when multicellular organisms initiated the process of development that later became the more complex embryonic development found in animals and plants. The advantage here is realized at the level of the mitochondrion and chloroplast.</p> <p>Hypothesis</p> <p>The extreme instability of DNA in mitochondria and chloroplasts has not been widely appreciated even though it was first reported four decades ago. Here, I show that the evolutionary success of multicellular animals and plants can be traced to the protection of organellar DNA. Three stages are envisioned. <it>Sequestration </it>allowed mitochondria and chloroplasts to be placed in "quiet" germ line cells so that their DNA is not exposed to the oxidative stress produced by these organelles in "active" somatic cells. This advantage then provided <it>Opportunity</it>, a period of time during which novel processes arose for signaling within and between cells and (in animals) for cell-cell recognition molecules to evolve. <it>Development </it>then led to the enormous diversity of animals and plants.</p> <p>Implications</p> <p>The potency of a somatic stem cell is its potential to generate cell types other than itself, and this is a systems property. One of the biochemical properties required for stemness to emerge from a population of cells might be the metabolic quiescence that protects organellar DNA from oxidative stress.</p> <p>Reviewers</p> <p>This article was reviewed by John Logsdon, Arcady Mushegian, and Patrick Forterre.</p
Geometric Cross-Modal Comparison of Heterogeneous Sensor Data
In this work, we address the problem of cross-modal comparison of aerial data
streams. A variety of simulated automobile trajectories are sensed using two
different modalities: full-motion video, and radio-frequency (RF) signals
received by detectors at various locations. The information represented by the
two modalities is compared using self-similarity matrices (SSMs) corresponding
to time-ordered point clouds in feature spaces of each of these data sources;
we note that these feature spaces can be of entirely different scale and
dimensionality. Several metrics for comparing SSMs are explored, including a
cutting-edge time-warping technique that can simultaneously handle local time
warping and partial matches, while also controlling for the change in geometry
between feature spaces of the two modalities. We note that this technique is
quite general, and does not depend on the choice of modalities. In this
particular setting, we demonstrate that the cross-modal distance between SSMs
corresponding to the same trajectory type is smaller than the cross-modal
distance between SSMs corresponding to distinct trajectory types, and we
formalize this observation via precision-recall metrics in experiments.
Finally, we comment on promising implications of these ideas for future
integration into multiple-hypothesis tracking systems.Comment: 10 pages, 13 figures, Proceedings of IEEE Aeroconf 201
A multiple-method approach reveals a declining amount of chloroplast DNA during development in Arabidopsis
<p>Abstract</p> <p>Background</p> <p>A decline in chloroplast DNA (cpDNA) during leaf maturity has been reported previously for eight plant species, including <it>Arabidopsis thaliana</it>. Recent studies, however, concluded that the amount of cpDNA during leaf development in Arabidopsis remained constant.</p> <p>Results</p> <p>To evaluate alternative hypotheses for these two contradictory observations, we examined cpDNA in Arabidopsis shoot tissues at different times during development using several methods: staining leaf sections as well as individual isolated chloroplasts with 4',6-diamidino-2-phenylindole (DAPI), real-time quantitative PCR with DNA prepared from total tissue as well as from isolated chloroplasts, fluorescence microscopy of ethidium-stained DNA molecules prepared in gel from isolated plastids, and blot-hybridization of restriction-digested total tissue DNA. We observed a developmental decline of about two- to three-fold in mean DNA per chloroplast and two- to five-fold in the fraction of cellular DNA represented by chloroplast DNA.</p> <p>Conclusion</p> <p>Since the two- to five-fold reduction in cpDNA content could not be attributed to an artifact of chloroplast isolation, we conclude that DNA within Arabidopsis chloroplasts is degraded <it>in vivo </it>as leaves mature.</p
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Wearable activity sensors and early pain after total joint arthroplasty.
A prospective observational cohort of 20 primary total hip arthroplasty (n = 12) and total knee arthroplasty (n = 8) patients (mean age: 63 ± 6 years) was passively monitored with a consumer-level wearable activity sensor before and 6 weeks after surgery. Patients were clustered by minimal change or decreased activity using sensor data. Decreased postoperative activity was associated with greater pain reduction (-5.5 vs -2.0, P = .03). All patients surpassed minimal clinical benefit thresholds of total joint arthroplasty (TJA) (Hip Disability and Osteoarthritis Score Junior 30.5 vs 20.8, P = .23; Knee Injury and Osteoarthritis Outcome Score Junior 23.3 vs 18.2, P = .77) within 6 weeks. Patients who objectively "take it easy" after TJA may experience less pain with no difference in early subjective outcome. Remote, passive analysis of outpatient wearable sensor data may permit real-time detection of early problems after TJA
Probabilistic Fréchet means for time varying persistence diagrams
© 2015, Institute of Mathematical Statistics. All rights reserved.In order to use persistence diagrams as a true statistical tool, it would be very useful to have a good notion of mean and variance for a set of diagrams. In [23], Mileyko and his collaborators made the first study of the properties of the Fréchet mean in (D<inf>p</inf>, W<inf>p</inf>), the space of persistence diagrams equipped with the p-th Wasserstein metric. In particular, they showed that the Fréchet mean of a finite set of diagrams always exists, but is not necessarily unique. The means of a continuously-varying set of diagrams do not themselves (necessarily) vary continuously, which presents obvious problems when trying to extend the Fréchet mean definition to the realm of time-varying persistence diagrams, better known as vineyards. We fix this problem by altering the original definition of Fréchet mean so that it now becomes a probability measure on the set of persistence diagrams; in a nutshell, the mean of a set of diagrams will be a weighted sum of atomic measures, where each atom is itself a persistence diagram determined using a perturbation of the input diagrams. This definition gives for each N a map (D<inf>p</inf>)<sup>N</sup>→ℙ(D<inf>p</inf>). We show that this map is Hölder continuous on finite diagrams and thus can be used to build a useful statistic on vineyards
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