Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database

Submillimeter Studies of Prestellar Cores and Protostars: Probing the Initial Conditions for Protostellar Collapse

Improving our understanding of the initial conditions and earliest stages of protostellar collapse is crucial to gain insight into the origin of stellar masses, multiple systems, and protoplanetary disks. Observationally, there are two complementary approaches to this problem: (1) studying the structure and kinematics of prestellar cores observed prior to protostar formation, and (2) studying the structure of young (e.g. Class 0) accreting protostars observed soon after point mass formation. We discuss recent advances made in this area thanks to (sub)millimeter mapping observations with large single-dish telescopes and interferometers. In particular, we argue that the beginning of protostellar collapse is much more violent in cluster-forming clouds than in regions of distributed star formation. Major breakthroughs are expected in this field from future large submillimeter instruments such as Herschel and ALMA.Comment: 12 pages, 9 figures, to appear in the proceedings of the conference "Chemistry as a Diagnostic of Star Formation" (C.L. Curry & M. Fich eds.

Dichlorido-2κ2 Cl-{μ-6,6′-dimeth­oxy-2,2′-[propane-1,3-diylbis(nitrilo­methyl­idyne)]diphenolato-1κ4 O 1,N,N′,O 1′:2κ2 O 1,O 1′}copper(II)zinc(II)

In the title compound, [CuZnCl2(C19H20N2O4)], the CuII ion exhibits a slightly distorted square-planar coordination geometry defined by two N atoms and two O atoms of the 6,6′-dimeth­oxy-2,2′-[propane-1,3-diylbis(nitrilo­methyl­idyne)]diphenolate Schiff base ligand. The ZnII ion is also four-coordinated by the two phenolate O atoms of the Schiff base ligand and by two cis-coordinated chloride anions

Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM

We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known. To solve this semi-blind deconvolution problem, prior distributions are specified for the PSF and the 3D image. Joint image reconstruction and PSF estimation is then performed within a Bayesian framework, using a variational algorithm to estimate the posterior distribution. The image prior distribution imposes an explicit atomic measure that corresponds to image sparsity. Importantly, the proposed Bayesian deconvolution algorithm does not require hand tuning. Simulation results clearly demonstrate that the semi-blind deconvolution algorithm compares favorably with previous Markov chain Monte Carlo (MCMC) version of myopic sparse reconstruction. It significantly outperforms mismatched non-blind algorithms that rely on the assumption of the perfect knowledge of the PSF. The algorithm is illustrated on real data from magnetic resonance force microscopy (MRFM)

Bcl3 prevents acute inflammatory lung injury in mice by restraining emergency granulopoiesis

Granulocytes are pivotal regulators of tissue injury. However, the transcriptional mechanisms that regulate granulopoiesis under inflammatory conditions are poorly understood. Here we show that the transcriptional coregulator B cell leukemia/lymphoma 3 (Bcl3) limits granulopoiesis under emergency (i.e., inflammatory) conditions, but not homeostatic conditions. Treatment of mouse myeloid progenitors with G-CSF — serum concentrations of which rise under inflammatory conditions — rapidly increased Bcl3 transcript accumulation in a STAT3-dependent manner. Bcl3-deficient myeloid progenitors demonstrated an enhanced capacity to proliferate and differentiate into granulocytes following G-CSF stimulation, whereas the accumulation of Bcl3 protein attenuated granulopoiesis in an NF-κB p50–dependent manner. In a clinically relevant model of transplant-mediated lung ischemia reperfusion injury, expression of Bcl3 in recipients inhibited emergency granulopoiesis and limited acute graft damage. These data demonstrate a critical role for Bcl3 in regulating emergency granulopoiesis and suggest that targeting the differentiation of myeloid progenitors may be a therapeutic strategy for preventing inflammatory lung injury

Neutral and Cationic Rare Earth Metal Alkyl and Benzyl Compounds with the 1,4,6-Trimethyl-6-pyrrolidin-1-yl-1,4-diazepane Ligand and Their Performance in the Catalytic Hydroamination/Cyclization of Aminoalkenes

A new neutral tridentate 1,4,6-trimethyl-6-pyrrolidin-1-yl-1,4-diazepane (L) was prepared. Reacting L with trialkyls M(CH2SiMe3)3(THF)2 (M = Sc, Y) and tribenzyls M(CH2Ph)3(THF)3 (M = Sc, La) yielded trialkyl complexes (L)M(CH2SiMe3)3 (M = Sc, 1; M = Y, 2) and tribenzyl complexes (L)M(CH2Ph)3 (M = Sc, 3; M = La, 4). Complexes 1 and 2 can be converted to their corresponding ionic compounds [(L)M(CH2SiMe3)2(THF)][B(C6H5)4] (M = Sc, Y) by reaction with [PhNMe2H][B(C6H5)4] in THF. Complexes 3 and 4 can be converted to cationic species [(L)M(CH2Ph)2]+ by reaction with [PhNMe2H][B(C6F5)4] in C6D5Br in the absence of THF. The neutral complexes 1-4 and their cationic derivatives were studied as catalysts for the hydroamination/cyclization of 2,2-diphenylpent-4-en-1-amine and N-methylpent-4-en-1-amine reference substrates and compared with ligand-free Sc, Y, and La neutral and cationic catalysts. The most effective catalysts in the series were the cationic L-yttrium catalyst (for 2,2-diphenylpent-4-en-1-amine) and the cationic lanthanum systems (for N-methylpent-4-en-1-amine). For the La catalysts, evidence was obtained for release of L from the metal during catalysis.

Calibrating Agent-Based Models Using Uncertainty Quantification Methods

Agent-based models (ABMs) can be found across a number of diverse application areas ranging from simulating consumer behaviour to infectious disease modelling. Part of their popularity is due to their ability to simulate individual behaviours and decisions over space and time. However, whilst there are plentiful examples within the academic literature, these models are only beginning to make an impact within policy areas. Whilst frameworks such as NetLogo make the creation of ABMs relatively easy, a number of key methodological issues, including the quantification of uncertainty, remain. In this paper we draw on state-of-the-art approaches from the fields of uncertainty quantification and model optimisation to describe a novel framework for the calibration of ABMs using History Matching and Approximate Bayesian Computation. The utility of the framework is demonstrated on three example models of increasing complexity: (i) Sugarscape to illustrate the approach on a toy example; (ii) a model of the movement of birds to explore the efficacy of our framework and compare it to alternative calibration approaches and; (iii) the RISC model of farmer decision making to demonstrate its value in a real application. The results highlight the efficiency and accuracy with which this approach can be used to calibrate ABMs. This method can readily be applied to local or national-scale ABMs, such as those linked to the creation or tailoring of key policy decisions

Osteogenic lineage restriction by osteoprogenitors cultured on nanometric grooved surfaces – the role of focal adhesion maturation

The differentiation of progenitor cells is dependent on more than biochemical signalling. Topographical cues in natural bone extracellular matrix guide cellular differentiation through the formation of focal adhesions, contact guidance, cytoskeletal rearrangement and ultimately gene expression. Osteoarthritis and a number of bone disorders present as growing challenges for our society. Hence, there is a need for next generation implantable devices to substitute for, or guide, bone repair in vivo. Cellular responses to nanometric topographical cues need to be better understood in vitro in order to ensure the effective and efficient integration and performance of these orthopaedic devices. In this study, the FDA approved plastic polycaprolactone, was embossed with nanometric grooves and the response of primary and immortalised osteoprogenitor cells observed. Nanometric groove dimensions were 240 nm or 540 nm deep and 12.5 μm wide. Cells cultured on test surfaces followed contact guidance along the length of groove edges, elongated along their major axis and showed nuclear distortion, they formed more focal complexes and a lower proportions of mature adhesions relative to planar controls. Down-regulation of the osteoblast marker genes RUNX2 and BMPR2 in primary and immortalised cells was observed on grooved substrates. Down-regulation appeared to directly correlate with focal adhesion maturation, indicating the involvement of ERK 1/2 negative feedback pathways following integrin mediated FAK activation

Electronic response of aligned multishell carbon nanotubes

We report calculations of the effective electronic response of aligned multishell carbon nanotubes. A local graphite-like dielectric tensor is assigned to every point of the multishell tubules, and the effective transverse dielectric function of the composite is computed by solving Maxwell's equations. Calculations of both real and imaginary parts of the effective dielectric function are presented, for various values of the filling fraction and the ratio of the internal and external radii of hollow tubules. Our full calculations indicate that the experimentally measured macroscopic dielectric function of carbon nanotube materials is the result of a strong electromagnetic coupling between the tubes, which cannot be accounted for with the use of simplified effective medium theories. The presence of surface plasmons is investigated, and both optical absorption cross sections and energy-loss spectra of aligned tubules are calculated.Comment: 4 pages, 4 figures, to appear in Phys. Rev.