460 research outputs found
Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis
IntroductionAdvances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome.MethodsMultivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality.ResultsWe identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters.ConclusionsHere we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients
Cell-specific discrimination of desmosterol and desmosterol mimetics confers selective regulation of LXR and SREBP in macrophages.
Activation of liver X receptors (LXRs) with synthetic agonists promotes reverse cholesterol transport and protects against atherosclerosis in mouse models. Most synthetic LXR agonists also cause marked hypertriglyceridemia by inducing the expression of sterol regulatory element-binding protein (SREBP)1c and downstream genes that drive fatty acid biosynthesis. Recent studies demonstrated that desmosterol, an intermediate in the cholesterol biosynthetic pathway that suppresses SREBP processing by binding to SCAP, also binds and activates LXRs and is the most abundant LXR ligand in macrophage foam cells. Here we explore the potential of increasing endogenous desmosterol production or mimicking its activity as a means of inducing LXR activity while simultaneously suppressing SREBP1c-induced hypertriglyceridemia. Unexpectedly, while desmosterol strongly activated LXR target genes and suppressed SREBP pathways in mouse and human macrophages, it had almost no activity in mouse or human hepatocytes in vitro. We further demonstrate that sterol-based selective modulators of LXRs have biochemical and transcriptional properties predicted of desmosterol mimetics and selectively regulate LXR function in macrophages in vitro and in vivo. These studies thereby reveal cell-specific discrimination of endogenous and synthetic regulators of LXRs and SREBPs, providing a molecular basis for dissociation of LXR functions in macrophages from those in the liver that lead to hypertriglyceridemia
Altering physiological networks using drugs: steps towards personalized physiology
BACKGROUND: The rise of personalized medicine has reminded us that each patient must be treated as an individual. One factor in making treatment decisions is the physiological state of each patient, but definitions of relevant states and methods to visualize state-related physiologic changes are scarce. We constructed correlation networks from physiologic data to demonstrate changes associated with pressor use in the intensive care unit. METHODS: We collected 29 physiological variables at one-minute intervals from nineteen trauma patients in the intensive care unit of an academic hospital and grouped each minute of data as receiving or not receiving pressors. For each group we constructed Spearman correlation networks of pairs of physiologic variables. To visualize drug-associated changes we split the networks into three components: an unchanging network, a network of connections with changing correlation sign, and a network of connections only present in one group. RESULTS: Out of a possible 406 connections between the 29 physiological measures, 64, 39, and 48 were present in each of the three component networks. The static network confirms expected physiological relationships while the network of associations with changed correlation sign suggests putative changes due to the drugs. The network of associations present only with pressors suggests new relationships that could be worthy of study. CONCLUSIONS: We demonstrated that visualizing physiological relationships using correlation networks provides insight into underlying physiologic states while also showing that many of these relationships change when the state is defined by the presence of drugs. This method applied to targeted experiments could change the way critical care patients are monitored and treated
Phenomenology of non-standard Z couplings in exclusive semileptonic b -> s transitions
The rare decays , and
are analyzed in a generic scenario where New Physics effects
enter predominantly via penguin contributions. We show that this
possibility is well motivated on theoretical grounds, as the vertex
is particularly susceptible to non-standard dynamics. In addition, such a
framework is also interesting phenomenologically since the coupling
is rather poorly constrained by present data. The characteristic features of
this scenario for the relevant decay rates and distributions are investigated.
We emphasize that both sign and magnitude of the forward-backward asymmetry of
the decay leptons in , , carry sensitive information on New Physics. The observable is proposed as a useful probe of
non-standard CP violation in couplings.Comment: Minor modifications; version to appear in Phys. Rev.
Howard walnut trees can be brought into bearing without annual pruning
In traditionally managed Howard walnut orchards, trees are pruned annually during
the orchard development phase, an expensive operation in terms of labor and prunings
disposal costs. Our observations and some prior research by others had suggested that
pruning may not be necessary in walnut. In a trial of pruned and unpruned hedgerow
trees over 8 years, beginning a year after planting, we documented canopy growth,
tree height, yield and nut quality characteristics and also the effects of fruit removal.
Pruning altered canopy shape but did not lead to increases in canopy development,
yield or nut quality. Although fruit removal stimulated more vegetative growth in
both the pruned and unpruned treatments, fruit removal did not result in an increase
in midday canopy photosynthetically active radiation interception or cumulative yield
when fruit removal was stopped after year 4. After 8 years, there were no significant
differences in tree height, nut quality or cumulative yield among any of the treatments,
which suggests that not pruning young Howard orchards could provide a net benefit
to growers
Asymmetric Dark Matter from Leptogenesis
We present a new realization of asymmetric dark matter in which the dark
matter and lepton asymmetries are generated simultaneously through two-sector
leptogenesis. The right-handed neutrinos couple both to the Standard Model and
to a hidden sector where the dark matter resides. This framework explains the
lepton asymmetry, dark matter abundance and neutrino masses all at once. In
contrast to previous realizations of asymmetric dark matter, the model allows
for a wide range of dark matter masses, from keV to 10 TeV. In particular, very
light dark matter can be accommodated without violating experimental
constraints. We discuss several variants of our model that highlight
interesting phenomenological possibilities. In one, late decays repopulate the
symmetric dark matter component, providing a new mechanism for generating a
large annihilation rate at the present epoch and allowing for mixed warm/cold
dark matter. In a second scenario, dark matter mixes with the active neutrinos,
thus presenting a distinct method to populate sterile neutrino dark matter
through leptogenesis. At late times, oscillations and dark matter decays lead
to interesting indirect detection signals.Comment: 32 pages + appendix, references added, minor change
Final State Interactions and New Physics in B -> pi K Decays
Within the Standard Model, and if one assumes that soft rescattering effects
are negligible, the CP asymmetry A^dir_CP (B^\pm -> \pi^\pm K) is predicted to
be very small and the ratio R = BR(B_d -> \pi^\mp K^\pm)/BR(B^\pm -> \pi^\pm K)
provides a bound on the angle \gamma of the unitarity triangle, sin^2 \gamma
\leq R. We estimate the corrections from soft rescattering effects using an
approach based on Regge phenomenology, and find effects of order 10% with large
uncertainties. In particular, we conclude that A^dir_CP \sim 0.2 and sin^2
\gamma \sim 1.2 R could not be taken unambiguously to signal New Physics. Using
SU(3) relations, we suggest experimental tests that could constrain the size of
the soft rescattering effects thus reducing the related uncertainty. Finally,
we study the effect of various models of New Physics on A^dir_CP and on R.Comment: 20 pages, RevTex, no figures; a few typos corrected, references
added, brief additional discussion of uncertanties is adde
The s ---> d gamma decay in and beyond the Standard Model
The New Physics sensitivity of the s ---> d gamma transition and its
accessibility through hadronic processes are thoroughly investigated. Firstly,
the Standard Model predictions for the direct CP-violating observables in
radiative K decays are systematically improved. Besides, the magnetic
contribution to epsilon prime is estimated and found subleading, even in the
presence of New Physics, and a new strategy to resolve its electroweak versus
QCD penguin fraction is identified. Secondly, the signatures of a series of New
Physics scenarios, characterized as model-independently as possible in terms of
their underlying dynamics, are investigated by combining the information from
all the FCNC transitions in the s ---> d sector.Comment: 54 pages, 14 eps figure
Testing new physics with the electron g-2
We argue that the anomalous magnetic moment of the electron (a_e) can be used
to probe new physics. We show that the present bound on new-physics
contributions to a_e is 8*10^-13, but the sensitivity can be improved by about
an order of magnitude with new measurements of a_e and more refined
determinations of alpha in atomic-physics experiments. Tests on new-physics
effects in a_e can play a crucial role in the interpretation of the observed
discrepancy in the anomalous magnetic moment of the muon (a_mu). In a large
class of models, new contributions to magnetic moments scale with the square of
lepton masses and thus the anomaly in a_mu suggests a new-physics effect in a_e
of (0.7 +- 0.2)*10^-13. We also present examples of new-physics theories in
which this scaling is violated and larger effects in a_e are expected. In such
models the value of a_e is correlated with specific predictions for processes
with violation of lepton number or lepton universality, and with the electric
dipole moment of the electron.Comment: 34 pages, 7 figures. Minor changes and references adde
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