Objective:The use of multilevel modelling with data from population-based surveys is often limited by the small number of cases per level-2 unit, prompting many researchers to use single-level ...techniques such as ordinary least squares regression.Design:Monte Carlo simulations are used to investigate the effects of data sparseness on the validity of parameter estimates in two-level versus single-level models.Setting:Both linear and non-linear hierarchical models are simulated in order to examine potential differences in the effects of small group size across continuous and discrete outcomes. Results are then compared with those obtained using disaggregated techniques (ordinary least squares and logistic regression).Main results:At the extremes of data sparseness (two observations per group), the group level variance components are overestimated in the two-level models. But with an average of only five observations per group, valid and reliable estimates of all parameters can be obtained when using a two-level model with either a continuous or a discrete outcome. In contrast, researchers run the risk of Type I error (standard errors biased downwards) when using single-level models even when there are as few as two observations per group on average. Bias is magnified when modelling discrete outcomes.Conclusions:Multilevel models can be reliably estimated with an average of only five observations per group. Disaggregated techniques carry an increased risk of Type I error, even in situations where there is only limited clustering in the data.
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Methane is an abundant gas used in energy recovery systems, heating, and transport. Methanotrophs are bacteria capable of using methane as their sole carbon source. Although intensively researched, ...the myriad of potential biotechnological applications of methanotrophic bacteria has not been comprehensively discussed in a single review. Methanotrophs can generate single-cell protein, biopolymers, components for nanotechnology applications (surface layers), soluble metabolites (methanol, formaldehyde, organic acids, and ectoine), lipids (biodiesel and health supplements), growth media, and vitamin B12 using methane as their carbon source. They may be genetically engineered to produce new compounds such as carotenoids or farnesene. Some enzymes (dehydrogenases, oxidase, and catalase) are valuable products with high conversion efficiencies and can generate methanol or sequester CO2 as formic acid ex vivo. Live cultures can be used for bioremediation, chemical transformation (propene to propylene oxide), wastewater denitrification, as components of biosensors, or possibly for directly generating electricity. This review demonstrates the potential for methanotrophs and their consortia to generate value while using methane as a carbon source. While there are notable challenges using a low solubility gas as a carbon source, the massive methane resource, and the potential cost savings while sequestering a greenhouse gas, keeps interest piqued in these unique bacteria.
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IJS, KILJ, NUK, PNG, UL, UM
Background The Tennessee Surgical Quality Collaborative analyzes NSQIP data from 21 participating hospitals. The Tennessee Surgical Quality Collaborative has reduced surgical complications, but ...causative factors are unclear. We sought to correlate surgical duration with complications to reveal mitigating strategies. Study Design Risk-adjusted Tennessee Surgical Quality Collaborative data on 104,632 general and vascular cases had a standard duration for 35 procedures (eg, breast, colectomy) calculated and NSQIP outcomes complication rates recorded. We derived a marginal time risk for each extra hour of operative time and reported per 1,000 cases. Results Procedures taking <95% upper confidence standard time limit (n = 99,741) were deemed “not long” and had significantly fewer urinary tract infections, organ-space surgical site infection, sepsis/septic shock, prolonged intubation, and pneumonia. “Long” cases had increased rates of these complications and also deep venous thrombosis, deep incisional infection, and wound disruption. Per 1,000 cases, there were 116 occurrences per operating room hour. Surgical site infections occurred in 14.4/1,000 cases per hour; risk started at 42 minutes of operative time. Death, pneumonia, and prolonged intubation saw their risks begin before the operation. The highest marginal time risk was for sepsis, occurring 16.6 times per additional hour of operative time over standard. Studying only the 25,146 clean procedures, a significant correlation (p < 0.001) to operation duration persisted, despite an occurrence incidence of 4.5%. Conclusions Duration of operation correlates with complications and time longer than a statewide established standard carries higher risk. To reduce risk of complications, these data support expeditious surgical technique and preoperative pulmonary training, and offer accurate outcomes assessment for patient counseling based on case duration. These data can be used directly to counsel individual surgeons to improve outcomes.
Constitutive receptor activity/inverse agonism and functional selectivity/biased agonism are 2 concepts in contemporary pharmacology that have major implications for the use of drugs in medicine and ...research as well as for the processes of new drug development. Traditional receptor theory postulated that receptors in a population are quiescent unless activated by a ligand. Within this framework ligands could act as agonists with various degrees of intrinsic efficacy, or as antagonists with zero intrinsic efficacy. We now know that receptors can be active without an activating ligand and thus display "constitutive" activity. As a result, a new class of ligand was discovered that can reduce the constitutive activity of a receptor. These ligands produce the opposite effect of an agonist and are called inverse agonists. The second topic discussed is functional selectivity, also commonly referred to as biased agonism. Traditional receptor theory also posited that intrinsic efficacy is a single drug property independent of the system in which the drug acts. However, we now know that a drug, acting at a single receptor subtype, can have multiple intrinsic efficacies that differ depending on which of the multiple responses coupled to a receptor is measured. Thus, a drug can be simultaneously an agonist, an antagonist, and an inverse agonist acting at the same receptor. This means that drugs have an additional level of selectivity (signaling selectivity or "functional selectivity") beyond the traditional receptor selectivity. Both inverse agonism and functional selectivity need to be considered when drugs are used as medicines or as research tools.
The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we ...discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution.
Clinical Pharmacology & Therapeutics (2013); 93 3, 252–259. doi:10.1038/clpt.2012.237
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Aims/hypothesis
The aim of this project was to build a new version of the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS-OM1), a patient-level simulation tool for predicting ...lifetime health outcomes of people with type 2 diabetes mellitus.
Methods
Data from 5,102 UKPDS patients from the 20 year trial and the 4,031 survivors entering the 10 year post-trial monitoring period were used to derive parametric proportional hazards models predicting absolute risk of diabetes complications and death. We re-estimated the seven original event equations and estimated new equations for diabetic ulcer and some second events. The additional data permitted inclusion of new risk factor predictors such as estimated GFR. We also developed four new equations for all-cause mortality. Internal validation of model predictions of cumulative incidence of all events and death was carried out and a contemporary patient-level dataset was used to compare 10 year predictions from the original and the new models.
Results
Model equations were based on a median 17.6 years of follow-up and up to 89,760 patient-years of data, providing double the number of events, greater precision and a larger number of significant covariates. The new model, UKPDS-OM2, is internally valid over 25 years and predicts event rates for complications, which are lower than those from the existing model.
Conclusions/interpretation
The new UKPDS-OM2 has significant advantages over the existing model, as it captures more outcomes, is based on longer follow-up data, and more comprehensively captures the progression of diabetes. Its use will permit detailed and reliable lifetime simulations of key health outcomes in people with type 2 diabetes mellitus.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Gas morphology and kinematics in the Milky Way contain key information for understanding the formation and evolution of our Galaxy. We present hydrodynamical simulations based on realistic ...barred Milky Way potentials constrained by recent observations. Our model can reproduce most features in the observed longitude–velocity diagram, including the Central Molecular Zone, the Near and Far 3 kpc arms, the Molecular Ring, and the spiral arm tangents. It can also explain the noncircular motions of masers from the recent BeSSeL2 survey. The central gas kinematics are consistent with a mass of 6.9 × 10
8
M
⊙
in the Nuclear Stellar Disk. Our model predicts the formation of an elliptical gaseous ring surrounding the bar, which is composed of the 3 kpc arms, the Norma arm, and the bar-spiral interfaces. This ring is similar to those “inner” rings in some Milky Way analogs with a boxy/peanut-shaped bulge (e.g., NGC 4565 and NGC 5746). The kinematics of gas near the solar neighborhood are governed by the Local arm. The bar pattern speed constrained by our gas model is 37.5–40 km s
−1
kpc
−1
, corresponding to a corotation radius of
R
CR
= 6.0–6.4 kpc. The rotation curve of our model rises gently within the central ∼ 5 kpc, significantly less steep than those predicted by some recent zoom-in cosmological simulations.
SUMMARY
Seasonal signals in geodetic time-series have long been recognized to be associated with environmental phenomena such as polar motion, atmospheric loading, groundwater loading and other ...hydrological processes. Modelling these periodic signals is crucial for the geophysical interpretation of these time-series. The most common approach used for resolving seasonal (annual and semi-annual) signals is their approximation by sinusoidal functions with constant amplitudes. However, because of their environmental source, seasonal signals are likely to be quasi-periodic. In this study, we investigate a Gaussian process (GP) to model quasi-periodic signals in geodetic time-series, a flexible method that allows capturing the variability structure in the data using covariance functions. We use the Markov Chain Monte Carlo method to evaluate the posterior probability density function. To test its effectiveness, we apply this method to a synthetic time-series in the presence of time-correlated noise. We find that the GP model provides a better fit to the time-series, resulting in time-series residuals with fewer systematic effects. We use the GP model to estimate the secular velocity of selected GPS sites from Antarctica and Alaska, as well as an example of Gravity Recovery and Climate Experiment time-series. The Bayesian aspect of the GP model allows inferring the linear velocity ensemble in the vicinity of the true solution while taking into account the quasi-periodic systematics in the time-series.
Abstract
We have derived absolute proper motions of the entire Galactic bulge region from VVV Infrared Astrometric Catalogue (VIRAC) and Gaia. We present these both as integrated on-sky maps and, ...after isolating standard candle red clump (RC) stars, as a function of distance using RC magnitude as a proxy. These data provide a new global, 3D view of the Milky Way barred bulge kinematics. We find a gradient in the mean longitudinal proper motion, $\langle \mu _ l^\star \rangle $, between the different sides of the bar, which is sensitive to the bar pattern speed. The split RC has distinct proper motions and is colder than other stars at similar distance. The proper motion correlation map has a quadrupole pattern in all magnitude slices showing no evidence for a separate, more axisymmetric inner bulge component. The line-of-sight integrated kinematic maps show a high central velocity dispersion surrounded by a more asymmetric dispersion profile. $\sigma _{\mu _l} / \sigma _{\mu _b}$ is smallest, ≈1.1, near the minor axis and reaches ≈1.4 near the disc plane. The integrated $\langle \mu_b\rangle$ pattern signals a superposition of bar rotation and internal streaming motion, with the near part shrinking in latitude and the far part expanding. To understand and interpret these remarkable data, we compare to a made-to-measure barred dynamical model, folding in the VIRAC selection function to construct mock maps. We find that our model of the barred bulge, with a pattern speed of 37.5 $\mathrm{ \mathrm{ km \, s^{-1}} \, kpc^{-1} }$, is able to reproduce all observed features impressively well. Dynamical models like this will be key to unlocking the full potential of these data.
Resprouting as a response to disturbance is now widely recognized as a key functional trait among woody plants and as the basis for the persistence niche. However, the underlying mechanisms that ...define resprouting responses to disturbance are poorly conceptualized. Resprouting ability is constrained by the interaction of the disturbance regime that depletes the buds and resources needed to fund resprouting, and the environment that drives growth and resource allocation. We develop a buds-protection-resources (BPR) framework for understanding resprouting in fire-prone ecosystems, based on bud bank location, bud protection, and how buds are resourced. Using this framework we go beyond earlier emphases on basal resprouting and highlight the importance of apical, epicormic and below-ground resprouting to the persistence niche. The BPR framework provides insights into: resprouting typologies that include both fire resisters (i.e. survive fire but do not resprout) and fire resprouters; the methods by which buds escape fire effects, such as thick bark; and the predictability of community assembly of resprouting types in relation to site productivity, disturbance regime and competition. Furthermore, predicting the consequences of global change is enhanced by the BPR framework because it potentially forecasts the retention or loss of above-ground biomass.
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