2,530 research outputs found
Drift vs Shift: Decoupling Trends and Changepoint Analysis
We introduce a new approach for decoupling trends (drift) and changepoints
(shifts) in time series. Our locally adaptive model-based approach for robustly
decoupling combines Bayesian trend filtering and machine learning based
regularization. An over-parameterized Bayesian dynamic linear model (DLM) is
first applied to characterize drift. Then a weighted penalized likelihood
estimator is paired with the estimated DLM posterior distribution to identify
shifts. We show how Bayesian DLMs specified with so-called shrinkage priors can
provide smooth estimates of underlying trends in the presence of complex noise
components. However, their inability to shrink exactly to zero inhibits direct
changepoint detection. In contrast, penalized likelihood methods are highly
effective in locating changepoints. However, they require data with simple
patterns in both signal and noise. The proposed decoupling approach combines
the strengths of both, i.e. the flexibility of Bayesian DLMs with the hard
thresholding property of penalized likelihood estimators, to provide
changepoint analysis in complex, modern settings. The proposed framework is
outlier robust and can identify a variety of changes, including in mean and
slope. It is also easily extended for analysis of parameter shifts in
time-varying parameter models like dynamic regressions. We illustrate the
flexibility and contrast the performance and robustness of our approach with
several alternative methods across a wide range of simulations and application
examples
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Big bottlenecks in cardiovascular tissue engineering.
Although tissue engineering using human-induced pluripotent stem cells is a promising approach for treatment of cardiovascular diseases, some limiting factors include the survival, electrical integration, maturity, scalability, and immune response of three-dimensional (3D) engineered tissues. Here we discuss these important roadblocks facing the tissue engineering field and suggest potential approaches to overcome these challenges
Solar angular momentum loss over the past several millennia
The Sun and Sun-like stars lose angular momentum to their magnetized stellar winds. This braking torque is coupled to the stellar magnetic field, such that changes in the strength and/or geometry of the field modifies the efficiency of this process. Since the space age, we have been able to directly measure solar wind properties using in situ spacecraft. Furthermore, indirect proxies such as sunspot number, geomagnetic indices, and cosmogenic radionuclides, constrain the variation of solar wind properties on centennial and millennial timescales. We use near-Earth measurements of the solar wind plasma and magnetic field to calculate the torque on the Sun throughout the space age. Then, reconstructions of the solar open magnetic flux are used to estimate the time-varying braking torque during the last nine millennia. We assume a relationship for the solar mass-loss rate based on observations during the space age which, due to the weak dependence of the torque on mass-loss rate, does not strongly affect our predicted torque. The average torque during the last nine millennia is found to be 2.2 × 1030 erg, which is comparable to the average value from the last two decades. Our data set includes grand minima (such as the Maunder Minimum), and maxima in solar activity, where the torque varies from ~1 to 5 × 1030 erg (averaged on decadal timescales), respectively. We find no evidence for any secular variation of the torque on timescales of less than 9000 yr
The GALEX Arecibo SDSS Survey. VIII. Final Data Release -- The Effect of Group Environment on the Gas Content of Massive Galaxies
We present the final data release from the GALEX Arecibo SDSS Survey (GASS),
a large Arecibo program that measured the HI properties for an unbiased sample
of ~800 galaxies with stellar masses greater than 10^10 Msun and redshifts
0.025<z<0.05. This release includes new Arecibo observations for 250 galaxies.
We use the full GASS sample to investigate environmental effects on the cold
gas content of massive galaxies at fixed stellar mass. The environment is
characterized in terms of dark matter halo mass, obtained by cross-matching our
sample with the SDSS group catalog of Yang et al. Our analysis provides, for
the first time, clear statistical evidence that massive galaxies located in
halos with masses of 10^13-10^14 Msun have at least 0.4 dex less HI than
objects in lower density environments. The process responsible for the
suppression of gas in group galaxies most likely drives the observed quenching
of the star formation in these systems. Our findings strongly support the
importance of the group environment for galaxy evolution, and have profound
implications for semi-analytic models of galaxy formation, which currently do
not allow for stripping of the cold interstellar medium in galaxy groups.Comment: 36 pages, 16 figures. Accepted for publication in MNRAS. Version with
supplementary material available at
http://www.mpa-garching.mpg.de/GASS/pubs.php . GASS released data can be
found at http://www.mpa-garching.mpg.de/GASS/data.ph
Loss of Wdfy3 in mice alters cerebral cortical neurogenesis reflecting aspects of the autism pathology.
Autism spectrum disorders (ASDs) are complex and heterogeneous developmental disabilities affecting an ever-increasing number of children worldwide. The diverse manifestations and complex, largely genetic aetiology of ASDs pose a major challenge to the identification of unifying neuropathological features. Here we describe the neurodevelopmental defects in mice that carry deleterious alleles of the Wdfy3 gene, recently recognized as causative in ASDs. Loss of Wdfy3 leads to a regionally enlarged cerebral cortex resembling early brain overgrowth described in many children on the autism spectrum. In addition, affected mouse mutants display migration defects of cortical projection neurons, a recognized cause of epilepsy, which is significantly comorbid with autism. Our analysis of affected mouse mutants defines an important role for Wdfy3 in regulating neural progenitor divisions and neural migration in the developing brain. Furthermore, Wdfy3 is essential for cerebral expansion and functional organization while its loss-of-function results in pathological changes characteristic of ASDs
Clinical outcomes in high-hypoglycaemia-risk patients with type 2 diabetes switching to insulin glargine 300 U/mL versus a first-generation basal insulin analogue in the United States: Results from the DELIVER High Risk real-world study
Aims:
To compare 12-month clinical effectiveness of insulin glargine 300 units/mL (Gla-300) versus first-generation basal insulin analogues (BIAs) (insulin glargine 100 units/mL [Gla-100] or insulin detemir [IDet]) in patients with type 2 diabetes (T2D) who were at high risk of hypoglycaemia and switched from one BIA to a different one (Gla-300 or Gla-100/IDet) in a real-world setting. //
Methods:
DELIVER High Risk was a retrospective observational cohort study of 2550 patients with T2D who switched BIA to Gla-300 (Gla-300 switchers) and were propensity score-matched (1:1) to patients who switched to Gla-100 or IDet (Gla-100/IDet switchers). Outcomes were change in glycated haemoglobin A1c (HbA1c), attainment of HbA1c goals (<7% and <8%), and incidence and event rates of hypoglycaemia (all-hypoglycaemia and hypoglycaemia associated with an inpatient/emergency department [ED] contact). //
Results:
HbA1c reductions were similar following switching to Gla-300 or Gla-100/IDet (−0.51% vs. −0.53%; p = .67), and patients showed similar attainment of HbA1c goals. Patients in both cohorts had comparable all-hypoglycaemia incidence and event rates. However, the Gla-300 switcher cohort had a significantly lower risk of inpatient/ED-associated hypoglycaemia (adjusted odds ratio: 0.73, 95% confidence interval: 0.60–0.89; p = .002) and experienced significantly fewer inpatient/ED-associated hypoglycaemic events (0.21 vs. 0.33 events per patient per year; p < .001). //
Conclusion:
In patients with T2D at high risk of hypoglycaemia, switching to Gla-300 or Gla-100/IDet achieved similar HbA1c reductions and glycaemic goal attainment, but Gla-300 switchers had a significantly lower risk of hypoglycaemia associated with an inpatient/ED contact during 12 months after switching
Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves
Kepler provides light curves of 156,000 stars with unprecedented precision.
However, the raw data as they come from the spacecraft contain significant
systematic and stochastic errors. These errors, which include discontinuities,
systematic trends, and outliers, obscure the astrophysical signals in the light
curves. To correct these errors is the task of the Presearch Data Conditioning
(PDC) module of the Kepler data analysis pipeline. The original version of PDC
in Kepler did not meet the extremely high performance requirements for the
detection of miniscule planet transits or highly accurate analysis of stellar
activity and rotation. One particular deficiency was that astrophysical
features were often removed as a side-effect to removal of errors. In this
paper we introduce the completely new and significantly improved version of PDC
which was implemented in Kepler SOC 8.0. This new PDC version, which utilizes a
Bayesian approach for removal of systematics, reliably corrects errors in the
light curves while at the same time preserving planet transits and other
astrophysically interesting signals. We describe the architecture and the
algorithms of this new PDC module, show typical errors encountered in Kepler
data, and illustrate the corrections using real light curve examples.Comment: Submitted to PASP. Also see companion paper "Kepler Presearch Data
Conditioning II - A Bayesian Approach to Systematic Error Correction" by Jeff
C. Smith et a
Apolipoprotein-induced conversion of phosphatidylcholine bilayer vesicles into nanodisks
AbstractApolipoprotein mediated formation of nanodisks was studied in detail using apolipophorin III (apoLp-III), thereby providing insight in apolipoprotein–lipid binding interactions. The spontaneous solubilization of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) vesicles occured only in a very narrow temperature range at the gel–liquid–crystalline phase transition temperature, exhibiting a net exothermic interaction based on isothermal titration calorimetry analysis. The resulting nanodisks were protected from proteolysis by trypsin, endoproteinase Glu-C, chymotrypsin and elastase. DMPC solubilization and the simultaneous formation of nanodisks were promoted by increasing the vesicle diameter, protein to lipid ratio and concentration. Inclusion of cholesterol in DMPC dramatically enhanced the rate of nanodisk formation, presumably by stabilization of lattice defects which form the main insertion sites for apolipoprotein α-helices. The presence of fully saturated acyl chains with a length of 13 or 14 carbons in phosphatidylcholine allowed the spontaneous vesicle solubilization upon apolipoprotein addition. Nanodisks with C13:0-phosphatidylcholine were significantly smaller with a diameter of 11.7±3.1nm compared to 18.5±5.6nm for DMPC nanodisks determined by transmission electron microscopy. Nanodisk formation was not observed when the phosphatidylcholine vesicles contained acyl chains of 15 or 16 carbons. However, using very high concentrations of lipid and protein (>10mg/ml), 1,2,-dipalmitoyl-sn-glycero-3-phosphocholine nanodisks could be produced spontaneously although the efficiency remained low
Improved asymmetry prediction for short interfering RNA s
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102096/1/febs12599.pd
Life in Hot Carbon Monoxide: The Complete Genome Sequence of Carboxydothermus hydrogenoformans Z-2901
We report here the sequencing and analysis of the genome of the thermophilic bacterium Carboxydothermus hydrogenoformans Z-2901. This species is a model for studies of hydrogenogens, which are diverse bacteria and archaea that grow anaerobically utilizing carbon monoxide (CO) as their sole carbon source and water as an electron acceptor, producing carbon dioxide and hydrogen as waste products. Organisms that make use of CO do so through carbon monoxide dehydrogenase complexes. Remarkably, analysis of the genome of C. hydrogenoformans reveals the presence of at least five highly differentiated anaerobic carbon monoxide dehydrogenase complexes, which may in part explain how this species is able to grow so much more rapidly on CO than many other species. Analysis of the genome also has provided many general insights into the metabolism of this organism which should make it easier to use it as a source of biologically produced hydrogen gas. One surprising finding is the presence of many genes previously found only in sporulating species in the Firmicutes Phylum. Although this species is also a Firmicutes, it was not known to sporulate previously. Here we show that it does sporulate and because it is missing many of the genes involved in sporulation in other species, this organism may serve as a “minimal” model for sporulation studies. In addition, using phylogenetic profile analysis, we have identified many uncharacterized gene families found in all known sporulating Firmicutes, but not in any non-sporulating bacteria, including a sigma factor not known to be involved in sporulation previously
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